diff --git a/.agents/skills/database-access/SKILL.md b/.agents/skills/database-access/SKILL.md index 796dfafe4f6..13fb7b7e286 100644 --- a/.agents/skills/database-access/SKILL.md +++ b/.agents/skills/database-access/SKILL.md @@ -1,6 +1,8 @@ --- name: database-access description: Add database queries, extract existing Prisma calls into repositories, or explicitly port queries to Rust and SQLx without expanding migration scope +metadata: + internal: true --- # Database access diff --git a/.github/CODEOWNERS b/.github/CODEOWNERS index f6c06f7d83f..2826098fd1f 100644 --- a/.github/CODEOWNERS +++ b/.github/CODEOWNERS @@ -1,4 +1,6 @@ /model_prices_and_context_window.json @mateo-berri @ryan-crabbe-berri @kerry-berri @joshua-berri /litellm/model_prices_and_context_window_backup.json @mateo-berri @ryan-crabbe-berri @kerry-berri @joshua-berri +/ci_cd/cost_map_pins.json @mateo-berri @ryan-crabbe-berri @kerry-berri @joshua-berri /helm/ @yassin-berriai /terraform/ @yassin-berriai +/.github/workflows/zizmor.yml @yuneng-berri diff --git a/.github/PULL_REQUEST_TEMPLATE/general.md b/.github/PULL_REQUEST_TEMPLATE/general.md index 243d121d626..86a23966671 100644 --- a/.github/PULL_REQUEST_TEMPLATE/general.md +++ b/.github/PULL_REQUEST_TEMPLATE/general.md @@ -84,9 +84,10 @@ If you're seeing a delay in your PR being merged, ping the LiteLLM Team on [Slac ## Screenshots / Proof of Fix \n\n| a |", + "contentFormat": "markdown", + "stringIndexType": "unicodeCodePoint", + "pages": [ + {"pageNumber": 1, "spans": [{"offset": 0, "length": 29}], "lines": [{"content": "Tïtle"}]}, + {"pageNumber": 2, "spans": [{"offset": 29, "length": 5}], "lines": [{"content": "a"}]} + ] + } + }))]) + .await; + + let response = perform(ocr_request( + LAYOUT_MODEL, + &upstream.uri(), + json!({"outputContentFormat": output_content_format, "pages": [0, 1]}), + )) + .await + .unwrap(); + + let sent = only_request(&upstream).await; + assert_eq!( + sent.query("outputContentFormat").as_deref(), + Some("markdown") + ); + assert_eq!( + sent.query("stringIndexType").as_deref(), + Some("unicodeCodePoint") + ); + assert_eq!(sent.query("pages").as_deref(), Some("1,2")); + assert_eq!(sent.json(), json!({"base64Source": "YWJj"})); + assert_eq!( + response.content.as_deref(), + Some("# Tïtle\n\n\n\n| a |") + ); + let pages = response + .pages + .iter() + .map(|page| page.markdown.as_str()) + .collect::>(); + assert_eq!(pages, ["# Tïtle\n\n\n\n", "| a |"]); + assert_eq!( + response.extra_fields.get("stringIndexType"), + Some(&json!("unicodeCodePoint")) + ); + assert_eq!( + response.usage_info.as_ref().unwrap().pages_processed, + Some(2) + ); +} + +#[rstest] +#[case::native_markdown(LAYOUT_MODEL, json!({"outputContentFormat": "markdown", "req_format": "native"}), Some("markdown"))] +#[case::markdown_on_read(MODEL, json!({"outputContentFormat": "markdown"}), Some("markdown"))] +#[case::text(LAYOUT_MODEL, json!({"outputContentFormat": "text"}), Some("text"))] +#[case::omitted(LAYOUT_MODEL, json!({}), None)] +#[tokio::test] +async fn only_layout_markdown_in_litellm_format_asks_for_code_point_offsets( + #[case] model: &str, + #[case] options: Value, + #[case] output_content_format: Option<&str>, +) { + let upstream = upstream([json_response(json!({ + "status": "succeeded", + "analyzeResult": { + "contentFormat": "text", + "stringIndexType": "textElements", + "pages": [{"pageNumber": 1, "lines": [{"content": "hello"}]}] + } + }))]) + .await; + + let response = perform(ocr_request(model, &upstream.uri(), options)) + .await + .unwrap(); + + let sent = only_request(&upstream).await; + assert_eq!( + sent.query("outputContentFormat").as_deref(), + output_content_format + ); + assert_eq!(sent.query("stringIndexType"), None); + assert_eq!(sent.json(), json!({"base64Source": "YWJj"})); + assert_eq!(response.pages[0].markdown, "hello"); + assert_eq!(response.extra_fields.get("stringIndexType"), None); +} + +#[rstest] +#[case::snake_case(json!({"output_content_format": "markdown"}), Some("markdown"))] +#[case::padded(json!({"outputContentFormat": " markdown "}), Some("markdown"))] +#[case::empty(json!({"outputContentFormat": ""}), None)] +#[case::empty_camel_case_falls_back_to_snake_case( + json!({"outputContentFormat": "", "output_content_format": "markdown"}), + Some("markdown") +)] +#[case::dropped(json!({"outputContentFormat": "html", "drop_params": true}), None)] +#[tokio::test] +async fn the_requested_output_content_format_reaches_azure_in_its_query_spelling( + #[case] options: Value, + #[case] output_content_format: Option<&str>, +) { + let upstream = upstream([json_response(json!({ + "status": "succeeded", + "analyzeResult": {"pages": [{"pageNumber": 1, "lines": [{"content": "hello"}]}]} + }))]) + .await; + + let response = perform(ocr_request(MODEL, &upstream.uri(), options)) + .await + .unwrap(); + + let sent = only_request(&upstream).await; + assert_eq!( + sent.query("outputContentFormat").as_deref(), + output_content_format + ); + assert_eq!(sent.query("output_content_format"), None); + assert_eq!(sent.query("drop_params"), None); + assert_eq!(sent.json(), json!({"base64Source": "YWJj"})); + assert_eq!(response.pages[0].markdown, "hello"); +} + #[tokio::test] async fn native_format_normalizes_pages_and_keeps_the_provider_response() { let operation = json!({ @@ -315,7 +448,11 @@ async fn polling_does_not_follow_redirects() { .await .unwrap_err(); - assert!(error.to_string().contains("status 302"), "{error}"); + assert_eq!( + error.upstream_response().map(|(status, ..)| status), + Some(302), + "{error}" + ); assert_eq!(received(&upstream).await.len(), 2); } @@ -389,12 +526,15 @@ async fn malformed_provider_pages_report_the_response_path( } #[rstest] -#[case::missing(None)] -#[case::relative(Some("/relative"))] -#[case::cross_origin(Some("http://example.com/operation"))] -#[case::with_userinfo(Some("http://user:password@127.0.0.1/operation"))] +#[case::missing(None, false)] +#[case::relative(Some("/relative"), true)] +#[case::cross_origin(Some("http://example.com/operation"), false)] +#[case::with_userinfo(Some("http://user:password@127.0.0.1/operation"), false)] #[tokio::test] -async fn an_unusable_operation_location_is_rejected(#[case] location: Option<&str>) { +async fn an_unusable_operation_location_is_rejected( + #[case] location: Option<&str>, + #[case] unparseable: bool, +) { let response = location .into_iter() .fold(ResponseTemplate::new(202), |response, location| { @@ -407,6 +547,11 @@ async fn an_unusable_operation_location_is_rejected(#[case] location: Option<&st .unwrap_err(); assert!(error.to_string().contains("operation-location"), "{error}"); + assert!(error.is_response()); + assert_eq!( + litellm_error::find::(&error).is_some(), + unparseable + ); assert_eq!(received(&upstream).await.len(), 1); } diff --git a/litellm-rust/crates/inference-ocr/tests/ocr/cohere.rs b/litellm-rust/crates/inference-ocr/tests/ocr/cohere.rs index 007aa49a2fd..a5076cf0112 100644 --- a/litellm-rust/crates/inference-ocr/tests/ocr/cohere.rs +++ b/litellm-rust/crates/inference-ocr/tests/ocr/cohere.rs @@ -37,6 +37,15 @@ async fn a_non_image_document_is_rejected_before_sending( .await .unwrap_err(); - assert!(matches!(error, Error::CohereImageOnly), "{error:?}"); + assert!( + matches!( + error, + Error::UnsupportedDocument { + provider: "Cohere Parse", + .. + } + ), + "{error:?}" + ); assert!(received(&upstream).await.is_empty()); } diff --git a/litellm-rust/crates/inference-ocr/tests/ocr/documents.rs b/litellm-rust/crates/inference-ocr/tests/ocr/documents.rs index 338a47c5f57..35de1326386 100644 --- a/litellm-rust/crates/inference-ocr/tests/ocr/documents.rs +++ b/litellm-rust/crates/inference-ocr/tests/ocr/documents.rs @@ -176,8 +176,8 @@ async fn a_missing_path_document_fails_before_sending() { assert!( matches!( &error, - Error::FileRead { path: failed, source } - if *failed == path && source.kind() == std::io::ErrorKind::NotFound + Error::FileRead { path: failed, cause } + if *failed == path && cause.kind() == std::io::ErrorKind::NotFound ), "{error:?}" ); @@ -216,7 +216,8 @@ async fn configured_client_preserves_document_url_policy(#[case] allowed: bool) .await; if !allowed { - assert!(matches!(result, Err(Error::BlockedDocumentUrl))); + let error = result.unwrap_err(); + assert!(error.is_request(), "{error:?}"); assert!(received(&documents).await.is_empty()); assert!(received(&upstream).await.is_empty()); return; diff --git a/litellm-rust/crates/inference-ocr/tests/ocr/lifecycle.rs b/litellm-rust/crates/inference-ocr/tests/ocr/lifecycle.rs index e413781f1a3..75a91092daf 100644 --- a/litellm-rust/crates/inference-ocr/tests/ocr/lifecycle.rs +++ b/litellm-rust/crates/inference-ocr/tests/ocr/lifecycle.rs @@ -38,7 +38,7 @@ fn recording_host( .with_before_send(move |wire, _| { interceptions.fetch_add(1, Ordering::SeqCst); match block { - true => Err(Error::InvalidRequest("blocked".into())), + true => Err(Error::MissingField("blocked")), false => Ok(wire), } }) @@ -95,10 +95,7 @@ async fn a_blocking_before_send_prevents_the_call_and_emits_one_failure() { .await .unwrap_err(); - assert!( - matches!(&error, Error::InvalidRequest(message) if message == "blocked"), - "{error:?}" - ); + assert!(matches!(error, Error::MissingField("blocked")), "{error:?}"); assert_eq!(interceptions.load(Ordering::SeqCst), 1); assert_eq!(*events.lock().unwrap(), ["started", "failure"]); assert!(received(&upstream).await.is_empty()); diff --git a/litellm-rust/crates/inference-ocr/tests/ocr/machine.rs b/litellm-rust/crates/inference-ocr/tests/ocr/machine.rs index 4f9266c4a8d..c7a5d58ad3d 100644 --- a/litellm-rust/crates/inference-ocr/tests/ocr/machine.rs +++ b/litellm-rust/crates/inference-ocr/tests/ocr/machine.rs @@ -41,11 +41,10 @@ async fn drive_until( Err(error) => break Err(error), }; let answer = match op { - HostRequest::Intercept(InterceptRequest::ResultReady { facts, reply }) => host - .result_ready(facts) - .await - .map(|()| reply.send(())) - .map_err(HostFailure::Error), + HostRequest::Intercept(InterceptRequest::ResultReady { facts, reply }) => { + reply.send(host.result_ready(facts).await); + Ok(()) + } HostRequest::Stream(stream) => match stream { litellm_host::protocol::StreamDelivery::Open(head, _) => match head {}, litellm_host::protocol::StreamDelivery::Chunk(chunk, _) => match chunk {}, @@ -64,10 +63,8 @@ async fn drive_until( } HostRequest::Intercept(InterceptRequest::AfterProviderResponse { raw, reply }) => { ops.push("response"); - host.after_provider_response(raw) - .await - .map(|()| reply.send(())) - .map_err(HostFailure::Error) + reply.send(host.after_provider_response(raw).await); + Ok(()) } }; if let Err(failure) = answer { @@ -85,10 +82,10 @@ async fn drive_until_notified(machine: &mut OcrMachine, host: &LocalOcrHost, sto _ = stop.notified() => break, step = machine.resume() => { match step.unwrap() { - MachineStep::Suspended(HostRequest::Intercept(InterceptRequest::ResultReady { reply, .. })) => reply.send(()), + MachineStep::Suspended(HostRequest::Intercept(InterceptRequest::ResultReady { reply, .. })) => reply.send(Ok(())), MachineStep::Suspended(HostRequest::HostCall(op)) => host.handle_host_call(op).await.unwrap(), MachineStep::Suspended(HostRequest::Intercept(InterceptRequest::BeforeProviderRequest { wire, reply, .. })) => reply.send(*wire), - MachineStep::Suspended(HostRequest::Intercept(InterceptRequest::AfterProviderResponse { reply, .. })) => reply.send(()), + MachineStep::Suspended(HostRequest::Intercept(InterceptRequest::AfterProviderResponse { reply, .. })) => reply.send(Ok(())), MachineStep::Suspended(HostRequest::Stream(stream)) => match stream { litellm_host::protocol::StreamDelivery::Open(head, _) => match head {}, litellm_host::protocol::StreamDelivery::Chunk(chunk, _) => match chunk {}, @@ -117,10 +114,14 @@ async fn a_hand_driven_machine_performs_the_same_call() { assert_eq!(outcome.unwrap().pages[0].markdown, "native"); assert_eq!(received(&upstream).await.len(), 1); assert_eq!(ops, ["BeforeSend", "response"]); - assert!(matches!( - machine.resume().await, - Err(Error::InvalidRequest(_)) - )); + let Err(error) = machine.resume().await else { + panic!("resuming a finished call is a host protocol fault"); + }; + assert!(!error.is_request(), "{error:?}"); + assert!( + litellm_error::find::(&error).is_some(), + "{error:?}" + ); } #[rstest::rstest] @@ -153,8 +154,11 @@ async fn a_path_document_is_read_by_core_without_a_host_operation() { } #[rstest] -#[case::failed(HostFailure::Error(Error::InvalidRequest("before_provider_request failed".into())), "before_provider_request failed")] -#[case::cancelled(HostFailure::Cancelled(Error::InvalidRequest("cancelled".into())), "cancelled")] +#[case::failed( + HostFailure::Error(Error::MissingField("before_provider_request failed")), + "before_provider_request failed" +)] +#[case::cancelled(HostFailure::Cancelled(Error::MissingField("cancelled")), "cancelled")] #[tokio::test] async fn a_before_send_failure_ends_the_call_without_reaching_transport( #[case] failure: HostFailure, @@ -174,7 +178,7 @@ async fn a_before_send_failure_ends_the_call_without_reaching_transport( .await; assert!( - matches!(&outcome, Err(Error::InvalidRequest(actual)) if actual == message), + matches!(&outcome, Err(Error::MissingField(actual)) if *actual == message), "{outcome:?}" ); assert_eq!(ops, ["BeforeSend"]); @@ -255,17 +259,17 @@ async fn interrupt_drops_provider_captures_before_returning() { drive_until_notified(&mut machine, &host, &entered).await; assert!(!dropped.load(Ordering::SeqCst)); - let acknowledgement = machine.interrupt(HostFailure::Cancelled(Error::InvalidRequest( - "cancelled".into(), - ))); + let acknowledgement = + machine.interrupt(HostFailure::Cancelled(Error::MissingField("cancelled"))); assert!( dropped.load(Ordering::SeqCst), "interrupt returned while provider captures were still alive" ); - assert!( - matches!(acknowledgement.await, Err(Error::InvalidRequest(message)) if message == "cancelled") - ); + assert!(matches!( + acknowledgement.await, + Err(Error::MissingField("cancelled")) + )); } #[rstest::rstest] @@ -290,7 +294,7 @@ async fn interrupting_an_in_flight_provider_request_closes_its_connection() { let mut machine = ocr_route().machine(host.request().unwrap(), None); drive_until_notified(&mut machine, &host, &received).await; - let cancelled = Error::InvalidRequest("cancelled".into()); + let cancelled = Error::MissingField("cancelled"); assert!( machine diff --git a/litellm-rust/crates/inference-ocr/tests/ocr/main.rs b/litellm-rust/crates/inference-ocr/tests/ocr/main.rs index 5a905f907d2..5a48bba9e1a 100644 --- a/litellm-rust/crates/inference-ocr/tests/ocr/main.rs +++ b/litellm-rust/crates/inference-ocr/tests/ocr/main.rs @@ -209,7 +209,7 @@ impl LocalOcrHost { request, caller_token: false, }) - .ok_or_else(|| Error::InvalidRequest("OCR request was already projected".into())) + .ok_or(Error::MissingField("OCR request")) } pub fn runtime(&self) -> litellm_host_native::in_process::Host<'_, Self, Self, ()> { litellm_host_native::in_process::Host { @@ -223,11 +223,11 @@ impl LocalOcrHost { impl litellm_host_native::services::HostCallHandler for LocalOcrHost { async fn handle_host_call(&self, op: OcrOp) -> Result<(), Error> { match op { - OcrOp::AcquireAzureAdToken(_) => { - Err(Error::Auth(litellm_auth::Error::CredentialAcquisition( - "OCR host has no Azure AD token provider".into(), - ))) - } + OcrOp::AcquireAzureAdToken(_) => Err(Error::Auth( + litellm_auth::Error::CredentialAcquisition(litellm_auth::ErrorDetail::Unresolved { + subject: "OCR host Azure AD token provider", + }), + )), } } } diff --git a/litellm-rust/crates/inference-ocr/tests/ocr/mistral.rs b/litellm-rust/crates/inference-ocr/tests/ocr/mistral.rs index 528adc7feaf..21cf4ce455d 100644 --- a/litellm-rust/crates/inference-ocr/tests/ocr/mistral.rs +++ b/litellm-rust/crates/inference-ocr/tests/ocr/mistral.rs @@ -92,28 +92,13 @@ async fn an_upstream_error_keeps_its_status_whole_body_and_headers( .unwrap_err(); assert_eq!(received(&upstream).await.len(), 1); - let Error::Provider { - status, - body, - headers, - } = error - else { - panic!("expected provider error, got {error:?}"); - }; + let (status, body, headers) = error.upstream_response().expect("the provider answered"); assert_eq!(status, 422); - for (name, value) in [ - ("retry-after", "17"), - ("x-request-id", "request-123"), - ("x-future-header", "retained"), - ] { - assert!( - headers - .iter() - .any(|(key, actual)| key.eq_ignore_ascii_case(name) && actual == value), - "{name} missing from {headers:?}" - ); - } assert_eq!(body, expected_body); + let header = |name: &str| headers.get(name).and_then(|value| value.to_str().ok()); + assert_eq!(header("retry-after"), Some("17")); + assert_eq!(header("x-request-id"), Some("request-123")); + assert_eq!(header("x-future-header"), Some("retained")); } #[rstest] diff --git a/litellm-rust/crates/inference-ocr/tests/ocr/reducto.rs b/litellm-rust/crates/inference-ocr/tests/ocr/reducto.rs index 649dca3d690..f6f458a4916 100644 --- a/litellm-rust/crates/inference-ocr/tests/ocr/reducto.rs +++ b/litellm-rust/crates/inference-ocr/tests/ocr/reducto.rs @@ -175,8 +175,11 @@ async fn a_failed_upload_stops_before_parse(#[case] upload: ResponseTemplate) { } #[rstest] -#[case::remote_url("https://example.com/a.pdf", Error::ReductoSource)] -#[case::empty_file_id("reducto://", Error::RequestField { path: "document file id".into() })] +#[case::remote_url( + "https://example.com/a.pdf", + Error::UnsupportedDocument { provider: "Reducto", guidance: "" } +)] +#[case::empty_file_id("reducto://", Error::RequestField { path: "document file id".into(), cause: None })] #[case::data_uri_without_payload("data:application/pdf;base64", Error::InvalidDataUri)] #[case::invalid_base64("data:application/pdf;base64,INVALID!", Error::InvalidDataUri)] #[tokio::test] @@ -202,7 +205,6 @@ async fn invalid_document_sources_are_rejected_before_sending( std::mem::discriminant(&expected) ); assert_eq!(error.http_status_code(), Some(400)); - assert_eq!(error.to_string(), expected.to_string()); } #[tokio::test] diff --git a/litellm-rust/crates/inference-ocr/tests/ocr/vertex_ai.rs b/litellm-rust/crates/inference-ocr/tests/ocr/vertex_ai.rs index 81b52d076a5..dba12de60f6 100644 --- a/litellm-rust/crates/inference-ocr/tests/ocr/vertex_ai.rs +++ b/litellm-rust/crates/inference-ocr/tests/ocr/vertex_ai.rs @@ -71,7 +71,8 @@ async fn invalid_credentials_fail_before_sending() { .await .unwrap_err(); - assert!(error.to_string().contains("vertex_credentials"), "{error}"); + let report = litellm_error::Report::new(&error).to_string(); + assert!(report.contains("vertex_credentials"), "{report}"); } #[rstest] @@ -91,11 +92,10 @@ async fn a_request_controlled_api_base_is_rejected_before_vertex_auth( let error = perform(request).await.unwrap_err(); + let report = litellm_error::Report::new(&error).to_string(); assert!( - error - .to_string() - .contains("request-controlled Vertex AI endpoint"), - "{error}" + report.contains("request-controlled Vertex AI endpoint"), + "{report}" ); } diff --git a/litellm-rust/crates/inference-responses/Cargo.toml b/litellm-rust/crates/inference-responses/Cargo.toml index 793483ee76d..083179c50c8 100644 --- a/litellm-rust/crates/inference-responses/Cargo.toml +++ b/litellm-rust/crates/inference-responses/Cargo.toml @@ -25,8 +25,10 @@ tokio-tungstenite.workspace = true tracing.workspace = true [dev-dependencies] +litellm-http = { workspace = true, features = ["test-support"] } litellm-cache.workspace = true litellm-cache-memory.workspace = true +litellm-error.workspace = true litellm-host-native.workspace = true litellm-inference-testing.workspace = true litellm-tracing.workspace = true diff --git a/litellm-rust/crates/inference-responses/src/handler.rs b/litellm-rust/crates/inference-responses/src/handler.rs index 02182d23ae3..19092a63a14 100644 --- a/litellm-rust/crates/inference-responses/src/handler.rs +++ b/litellm-rust/crates/inference-responses/src/handler.rs @@ -72,28 +72,29 @@ pub(super) async fn execute( let stream = match wire.body.get("stream") { None => false, Some(serde_json::Value::Bool(value)) => *value, - Some(_) => return Err(Error::InvalidRequest("stream must be a boolean".into())), + Some(_) => { + return Err(Error::invalid_request( + litellm_llms::ErrorDetail::Expected { + subject: "stream", + expected: "a boolean", + }, + )); + } }; let outbound = litellm_inference::outbound::outbound_request( Authenticated { headers: wire.headers, signer: authenticated.signer, }, - wire.url, + &wire.url, &wire.body, Some(call.timeout.unwrap_or(Duration::from_secs(600))), )?; - let response = litellm_inference::outbound::send(outbound, &route.http) - .await - .map_err(network)?; + let response = litellm_inference::outbound::send(outbound, &route.http).await?; let status = response.status().as_u16(); if !response.status().is_success() { - let body = response.text().await.map_err(network)?; - return Err(litellm_http::transport::Error::Http { - status, - body: litellm_http::request::truncate_error_body(&body), - } - .into()); + let body = response.text().await.map_err(litellm_http::Error::from)?; + return Err(litellm_http::Error::upstream(status, body).into()); } if stream { let headers = response @@ -105,14 +106,14 @@ pub(super) async fn execute( .collect(); let chunks = response .bytes_stream() - .map(|chunk| chunk.map_err(network)) + .map(|chunk| chunk.map_err(|error| litellm_http::Error::from(error).into())) .boxed(); return Ok(ResponsesOutput::Stream { head: ResponsesStreamHead { headers }, chunks, }); } - let body = response.text().await.map_err(network)?; + let body = response.text().await.map_err(litellm_http::Error::from)?; let raw = RawResponse { body: body.clone() }; if let Some(observers) = observers { observers.emit(litellm_host::lifecycle::CallEvent::Execution( @@ -123,17 +124,18 @@ pub(super) async fn execute( .after_provider_response(raw) .await .map_err(Error::post_call)?; - let value = serde_json::from_str(&body) - .map_err(|error| Error::InvalidResponse(error.to_string().into()))?; + let value = serde_json::from_str(&body).map_err(|error| { + Error::invalid_response(litellm_llms::ErrorDetail::invalid( + "Responses API response JSON", + error, + )) + })?; config .transform_response_api_response(value) .map(ResponsesOutput::Complete) .map_err(Error::from) + .map_err(Error::after_send) }, ) .await } - -fn network(error: reqwest::Error) -> Error { - litellm_http::transport::Error::Network(error.to_string()).into() -} diff --git a/litellm-rust/crates/inference-responses/src/lib.rs b/litellm-rust/crates/inference-responses/src/lib.rs index b6e151ecec3..9af5dea1fe8 100644 --- a/litellm-rust/crates/inference-responses/src/lib.rs +++ b/litellm-rust/crates/inference-responses/src/lib.rs @@ -11,6 +11,7 @@ mod handler; use std::sync::Arc; use litellm_auth::AuthServices; +use litellm_core_utils::decline::Decline; use litellm_core_utils::get_llm_provider_logic::{ CustomLlmProvider, LlmProviders, get_custom_llm_provider, }; @@ -24,6 +25,8 @@ use litellm_llms::{ use litellm_secrets::source::SecretSource; use types::{ResponsesCall, ResponsesOutput, ResponsesProvider}; +const NOT_NATIVE: Decline = Decline::new("native HTTP responses provider"); + fn responses_provider(provider: LlmProviders) -> Option<&'static dyn BaseResponsesApiConfig> { match provider { LlmProviders::Openai => Some(&OpenAiResponsesApiConfig), @@ -111,9 +114,8 @@ impl ResponsesRoute { } let provider = provider_name .parse::() - .map_err(|_| Error::Unsupported("native HTTP responses provider"))?; - let config = responses_provider(provider) - .ok_or(Error::Unsupported("native HTTP responses provider"))?; + .map_err(|_| Error::Declined(NOT_NATIVE))?; + let config = responses_provider(provider).ok_or(Error::Declined(NOT_NATIVE))?; let wire_model = match provider { LlmProviders::Openai if resolved_model.contains('/') => { return Err(Error::InvalidProvider(call.model)); @@ -123,7 +125,7 @@ impl ResponsesRoute { format!("openrouter/{resolved_model}") } LlmProviders::Openrouter => resolved_model.into(), - _ => return Err(Error::Unsupported("native HTTP responses provider")), + _ => return Err(Error::Declined(NOT_NATIVE)), }; let provider = ResponsesProvider { identity: ProviderIdentity { diff --git a/litellm-rust/crates/inference-responses/src/websocket.rs b/litellm-rust/crates/inference-responses/src/websocket.rs index 213a9a95831..2afcde0a7a4 100644 --- a/litellm-rust/crates/inference-responses/src/websocket.rs +++ b/litellm-rust/crates/inference-responses/src/websocket.rs @@ -1,14 +1,18 @@ use std::{collections::HashMap, sync::Arc, time::Duration}; use futures_util::{SinkExt, StreamExt}; -use litellm_http::websocket::{UpstreamWebSocket, connect_upstream}; +use litellm_http::{ + Client, + websocket::{self, UpstreamWebSocket}, +}; use tokio::sync::Mutex; use tokio_tungstenite::tungstenite::{ Message, - client::IntoClientRequest, - http::{HeaderName, HeaderValue}, + http::{HeaderMap, HeaderName, HeaderValue}, }; +use litellm_llms::ErrorDetail; + use super::Error; #[derive(Clone)] @@ -24,42 +28,32 @@ impl ResponsesWebSocketConnection { fields(outcome) )] pub async fn connect_url( + client: &Client, url: &str, headers: &HashMap, timeout: Option, ) -> Result { litellm_inference::diagnostic::operation("litellm.websocket.connect_url", async { - let mut request = url.into_client_request().map_err(|error| { - Error::Transport(litellm_http::transport::Error::Network(error.to_string())) - })?; - for (name, value) in headers { - let header_name = name - .parse::() - .map_err(|error| Error::InvalidRequest(error.to_string().into()))?; - let header_value = HeaderValue::from_str(value) - .map_err(|error| Error::InvalidRequest(error.to_string().into()))?; - request.headers_mut().insert(header_name, header_value); - } - let connect = connect_upstream(request); - let result = match timeout { - Some(timeout) => tokio::time::timeout(timeout, connect).await.map_err(|_| { - Error::Transport(litellm_http::transport::Error::Network( - "Responses WebSocket connection timed out".into(), + let headers = headers + .iter() + .map(|(name, value)| { + Ok(( + name.parse::().map_err(|error| { + Error::invalid_request(ErrorDetail::invalid( + "WebSocket header name", + error, + )) + })?, + HeaderValue::from_str(value).map_err(|error| { + Error::invalid_request(ErrorDetail::invalid( + "WebSocket header value", + error, + )) + })?, )) - })?, - None => connect.await, - }; - let (socket, _) = result.map_err(|error| match *error { - tokio_tungstenite::tungstenite::Error::Http(response) => { - Error::Transport(litellm_http::transport::Error::Http { - status: response.status().as_u16(), - body: String::new(), - }) - } - other => { - Error::Transport(litellm_http::transport::Error::Network(other.to_string())) - } - })?; + }) + .collect::>()?; + let socket = websocket::connect(client, url, headers, timeout).await?; Ok(Self { socket: Arc::new(Mutex::new(Some(socket))), }) @@ -77,13 +71,12 @@ impl ResponsesWebSocketConnection { litellm_inference::diagnostic::operation("litellm.websocket.send_text", async { let mut socket = self.socket.lock().await; let Some(socket) = socket.as_mut() else { - return Err(Error::Transport(litellm_http::transport::Error::Network( - "Responses WebSocket is closed".into(), - ))); + return Err(litellm_http::Error::websocket_closed().into()); }; - socket.send(Message::Text(text)).await.map_err(|error| { - Error::Transport(litellm_http::transport::Error::Network(error.to_string())) - }) + socket + .send(Message::Text(text)) + .await + .map_err(|error| litellm_http::Error::from(error).into()) }) .await } @@ -104,12 +97,12 @@ impl ResponsesWebSocketConnection { Some(Ok(Message::Text(text))) => Ok(Some(text)), Some(Ok(Message::Binary(bytes))) => String::from_utf8(bytes.to_vec()) .map(Some) - .map_err(|error| Error::InvalidResponse(error.to_string().into())), + .map_err(|error| { + Error::invalid_response(ErrorDetail::invalid("WebSocket text frame", error)) + }), Some(Ok(Message::Close(_))) | None => Ok(None), Some(Ok(_)) => Ok(None), - Some(Err(error)) => Err(Error::Transport(litellm_http::transport::Error::Network( - error.to_string(), - ))), + Some(Err(error)) => Err(litellm_http::Error::from(error).into()), } }) .await @@ -125,9 +118,10 @@ impl ResponsesWebSocketConnection { litellm_inference::diagnostic::operation("litellm.websocket.close", async { let mut socket = self.socket.lock().await; if let Some(socket) = socket.as_mut() { - socket.close(None).await.map_err(|error| { - Error::Transport(litellm_http::transport::Error::Network(error.to_string())) - })?; + socket + .close(None) + .await + .map_err(litellm_http::Error::from)?; } *socket = None; Ok(()) diff --git a/litellm-rust/crates/inference-responses/tests/openrouter.rs b/litellm-rust/crates/inference-responses/tests/openrouter.rs index e52cdba8ce8..8cdb68c376f 100644 --- a/litellm-rust/crates/inference-responses/tests/openrouter.rs +++ b/litellm-rust/crates/inference-responses/tests/openrouter.rs @@ -1,10 +1,7 @@ use std::sync::Arc; use futures_util::TryStreamExt; -use litellm_inference_responses::{ - Error, - types::{ResponsesCall, ResponsesOutput}, -}; +use litellm_inference_responses::types::{ResponsesCall, ResponsesOutput}; use litellm_inference_testing::{RecordingSecrets, no_secrets}; use rstest::{fixture, rstest}; use serde_json::json; @@ -108,13 +105,12 @@ async fn a_missing_key_fails_before_transport(call: ResponsesCall) { None, ) .await; - assert!(matches!( - result, - Err(Error::Auth(litellm_auth::Error::MissingApiKey { - provider: "OpenRouter", - .. - })) - )); + let Err(error) = result else { + panic!("the call fails"); + }; + assert!(error.is_missing_credential(), "{error:?}"); + let report = litellm_error::Report::new(&error).to_string(); + assert!(report.contains("OpenRouter"), "{report}"); assert!(received(&upstream).await.is_empty()); } diff --git a/litellm-rust/crates/inference-responses/tests/responses.rs b/litellm-rust/crates/inference-responses/tests/responses.rs index ae07a71dabd..89368a941ef 100644 --- a/litellm-rust/crates/inference-responses/tests/responses.rs +++ b/litellm-rust/crates/inference-responses/tests/responses.rs @@ -103,10 +103,7 @@ async fn unsupported_providers_fail_before_transport( ) .await; - assert!(matches!( - result, - Err(Error::Unsupported("native HTTP responses provider")) - )); + assert!(matches!(result, Err(ref error) if error.declined().is_some())); assert!(received(&upstream).await.is_empty()); } @@ -304,6 +301,25 @@ async fn provider_failures_emit_failure_once( ); } +#[rstest] +#[tokio::test] +async fn a_transport_error_does_not_echo_the_provider_url(call: ResponsesCall) { + let host = RecordingCall::::new(ResponsesCall { + api_base: Some(format!("{UNREACHABLE_BASE}/tenant-token-1234")), + ..call + }); + let call = host.request.lock().unwrap().take().unwrap(); + + let Err(error) = responses_route(no_secrets()) + .execute(call, &host, None) + .await + else { + panic!("nothing is listening"); + }; + + assert!(!error.to_string().contains("tenant-token-1234"), "{error}"); +} + #[rstest] #[case::explicit(true)] #[case::from_secrets(false)] @@ -538,6 +554,7 @@ async fn websocket_operations_trace_outcomes_without_capturing_frames_or_credent .logger() .instrument(async { let connection = ResponsesWebSocketConnection::connect_url( + &litellm_http::Client::for_test(), &format!("ws://{address}/responses"), &std::collections::HashMap::from([( "authorization".into(), @@ -556,12 +573,11 @@ async fn websocket_operations_trace_outcomes_without_capturing_frames_or_credent Some("private-frame-sentinel") ); connection.close().await.unwrap(); - assert!( - connection - .send_text("private-frame-sentinel".into()) - .await - .is_err() - ); + let error = connection + .send_text("private-frame-sentinel".into()) + .await + .expect_err("a closed connection sends nothing"); + assert!(!error.dispatched(), "{error:?}"); }) .await; server.await.unwrap(); diff --git a/litellm-rust/crates/inference-responses/tests/support/mod.rs b/litellm-rust/crates/inference-responses/tests/support/mod.rs index 81f133a0471..984b878eb21 100644 --- a/litellm-rust/crates/inference-responses/tests/support/mod.rs +++ b/litellm-rust/crates/inference-responses/tests/support/mod.rs @@ -13,6 +13,9 @@ use litellm_secrets::source::SecretSource; use serde_json::Value; use wiremock::{Mock, MockServer, Request, ResponseTemplate, matchers::any}; +/// A port nothing listens on, for calls that must fail before any request is sent. +pub const UNREACHABLE_BASE: &str = "http://127.0.0.1:1"; + pub fn responses_route( secrets: Arc, ) -> litellm_inference_responses::ResponsesRoute { diff --git a/litellm-rust/crates/inference-transcription/Cargo.toml b/litellm-rust/crates/inference-transcription/Cargo.toml index c501d329852..cf50b3f84fd 100644 --- a/litellm-rust/crates/inference-transcription/Cargo.toml +++ b/litellm-rust/crates/inference-transcription/Cargo.toml @@ -17,6 +17,7 @@ serde_json.workspace = true tracing.workspace = true [dev-dependencies] +litellm-error.workspace = true litellm-inference-testing.workspace = true litellm-tracing.workspace = true rstest.workspace = true diff --git a/litellm-rust/crates/inference-transcription/src/handler.rs b/litellm-rust/crates/inference-transcription/src/handler.rs index 5a7238c5e36..2ed3b1eba7b 100644 --- a/litellm-rust/crates/inference-transcription/src/handler.rs +++ b/litellm-rust/crates/inference-transcription/src/handler.rs @@ -2,7 +2,7 @@ use std::time::Duration; use litellm_http::{ Client, - request::{string_headers, truncate_error_body, with_default_headers}, + request::{string_headers, with_default_headers}, }; use litellm_llms::base_llm::{ audio_transcription::transformation::BaseAudioTranscriptionConfig, @@ -48,35 +48,27 @@ pub(super) async fn execute( let authenticated = resolve_auth(auth, environment, &env_lookup).await?; let outbound = litellm_inference::outbound::outbound_request( authenticated, - url, + &url, &body, Some( call.timeout .unwrap_or(Duration::from_secs(AUDIO_TRANSCRIPTION_TIMEOUT_SECS)), ), )?; - let response = litellm_inference::outbound::send(outbound, http) - .await - .map_err(|error| { - Error::Transport(litellm_http::transport::Error::Network(error.to_string())) - })?; + let response = litellm_inference::outbound::send(outbound, http).await?; let status = response.status(); - let text = response.text().await.map_err(|error| { - Error::Transport(litellm_http::transport::Error::Network(error.to_string())) - })?; + let text = response.text().await.map_err(litellm_http::Error::from)?; if !status.is_success() { - return Err(Error::Transport(litellm_http::transport::Error::Http { - status: status.as_u16(), - body: truncate_error_body(&text), - })); + return Err(litellm_http::Error::upstream(status.as_u16(), text).into()); } let response_json = serde_json::from_str(&text).map_err(|error| { - Error::InvalidResponse(litellm_llms::ErrorDetail::invalid( + Error::invalid_response(litellm_llms::ErrorDetail::invalid( "audio response JSON", error, )) })?; - Ok(config - .transform_audio_transcription_response(provider.model, response_json)? - .into_json()) + config + .transform_audio_transcription_response(provider.model, response_json) + .map(|response| response.into_json()) + .map_err(|error| Error::from(error).after_send()) } diff --git a/litellm-rust/crates/inference-transcription/tests/audio_transcription.rs b/litellm-rust/crates/inference-transcription/tests/audio_transcription.rs index eb252bdff7e..9e48edce0c0 100644 --- a/litellm-rust/crates/inference-transcription/tests/audio_transcription.rs +++ b/litellm-rust/crates/inference-transcription/tests/audio_transcription.rs @@ -152,13 +152,7 @@ async fn invalid_audio_is_rejected_before_sending( .await .expect_err("invalid audio is rejected"); - assert!( - matches!( - error, - Error::InvalidRequest(_) | Error::MissingField(_) | Error::InvalidType { .. } - ), - "{error:?}" - ); + assert!(error.is_request(), "{error:?}"); assert!(received(&upstream).await.is_empty()); } @@ -185,7 +179,9 @@ async fn unsupported_providers_are_rejected_before_sending( .await .expect_err("unsupported provider errors"); - assert_eq!(error, Error::InvalidProvider(reported.into())); + assert!(error.is_request(), "{error:?}"); + let report = litellm_error::Report::new(&error).to_string(); + assert!(report.contains(reported), "{report}"); } #[rstest] @@ -222,14 +218,28 @@ async fn an_upstream_error_keeps_its_status_and_body( .expect_err("upstream error propagates"); assert_eq!( - error, - Error::Transport(litellm_http::transport::Error::Http { - status, - body: "upstream said no".into() - }) + error.upstream_response(), + Some((status, "upstream said no")) ); } +#[rstest] +#[tokio::test] +async fn a_transport_error_does_not_echo_the_provider_url( + request: AudioTranscriptionRequest<'static>, +) { + let base = format!("{UNREACHABLE_BASE}/tenant-token-1234"); + + let error = transcribe(AudioTranscriptionRequest { + api_base: Some(&base), + ..request + }) + .await + .expect_err("nothing is listening"); + + assert!(!error.to_string().contains("tenant-token-1234"), "{error}"); +} + #[rstest] #[case::not_json(ResponseTemplate::new(200).set_body_string("not json"))] #[case::no_output(json_response(json!({"unexpected": true})))] @@ -248,7 +258,7 @@ async fn an_unreadable_success_body_is_an_invalid_response( .await .expect_err("an unreadable body fails"); - assert!(matches!(error, Error::InvalidResponse(_)), "{error:?}"); + assert!(error.is_response(), "{error:?}"); } #[rstest] diff --git a/litellm-rust/crates/inference/AGENTS.md b/litellm-rust/crates/inference/AGENTS.md index 7f2bd0387be..bcbc98a209e 100644 --- a/litellm-rust/crates/inference/AGENTS.md +++ b/litellm-rust/crates/inference/AGENTS.md @@ -53,10 +53,10 @@ ## Error placement -- The workspace `Error definitions` rules shape each crate's error. This section decides which crate and module a failure belongs to +- The [rust-error skill](../../.agents/skills/rust-error/SKILL.md) shapes each crate's error. This section decides which crate and module a failure belongs to - A failure is declared once, by the lowest crate that raises it - - every crate above nests it unchanged (`#[error(transparent)] Auth(#[from] litellm_auth::Error)`) or maps it once at its boundary, as `src/error.rs` does for `litellm_llms::Error` - - `Error` collects route failures for every format crate and never re-declares a variant a lower crate raises + - every crate above nests it in one variant and delegates its predicates, as `Error::Llm`, `Error::Auth` and `Error::Http` do, or translates it once in the shared `From` when its meaning changes, as `From` does for `Unsupported` and `From` does for a header the signer computes + - `Error` collects route failures for every format crate and never re-declares a variant a lower crate raises. Routes build transformation failures with `Error::invalid_request` and `Error::invalid_response` and collapse anything raised after the send with `Error::after_send`, and callers ask `declined()`, `is_request()`, `is_response()`, `is_missing_credential()`, `dispatched()`, `upstream_response()` and `rejected_request()` instead of matching nested variants - Scope follows the concept, not the first caller - an error type under `litellm-llms`'s `/` is private to that provider: no other provider and nothing in `base_llm` may import it - a failure two providers or two routes can hit (wire framing, stream event decoding, a malformed provider response) belongs to the crate that owns the concept: `litellm-framer` for framing, `litellm_llms::Error` for the transformation layer diff --git a/litellm-rust/crates/inference/Cargo.toml b/litellm-rust/crates/inference/Cargo.toml index acc211f214b..807a3ea85d3 100644 --- a/litellm-rust/crates/inference/Cargo.toml +++ b/litellm-rust/crates/inference/Cargo.toml @@ -29,6 +29,7 @@ time.workspace = true url.workspace = true [dev-dependencies] +litellm-error.workspace = true litellm-cache-memory.workspace = true litellm-http = { workspace = true, features = ["test-support"] } litellm-llms = { workspace = true, features = ["test-support"] } diff --git a/litellm-rust/crates/inference/src/caching.rs b/litellm-rust/crates/inference/src/caching.rs index 09d03c06215..d9b5b891015 100644 --- a/litellm-rust/crates/inference/src/caching.rs +++ b/litellm-rust/crates/inference/src/caching.rs @@ -377,5 +377,66 @@ async fn publish( facts: facts.clone(), })); } - interceptors.result_ready(facts).await + let from_provider = facts.source == ResultSource::Provider; + interceptors.result_ready(facts).await.map_err(|error| { + if from_provider { + Error::post_call(error) + } else { + error + } + }) +} + +#[cfg(test)] +mod tests { + use litellm_core_utils::decline::Decline; + use litellm_host::interceptors::{RawResponse, RequestContext, WireRequest}; + + use super::*; + + struct RejectResult; + + impl Interceptors for RejectResult { + async fn before_provider_request( + &self, + wire: WireRequest, + _: RequestContext, + ) -> Result { + Ok(wire) + } + + async fn after_provider_response(&self, _: RawResponse) -> Result<(), Error> { + Ok(()) + } + + async fn result_ready(&self, _: ExecutionFacts) -> Result<(), Error> { + Err(Error::Declined(Decline::new("result rejected"))) + } + } + + #[rstest::rstest] + #[case::provider(ResultSource::Provider, false)] + #[case::cache(ResultSource::Cache { key: "cached".into() }, true)] + #[tokio::test] + async fn result_rejection_only_declines_without_a_provider_call( + #[case] source: ResultSource, + #[case] may_decline: bool, + ) { + let facts = ExecutionFacts { + provider: ProviderIdentity { + model: "model".into(), + provider: "provider".into(), + }, + cost: Cost::settle(&source, None), + source, + }; + let error = publish(facts, &RejectResult, None).await.unwrap_err(); + assert_eq!(error.declined().is_some(), may_decline); + assert_eq!(error.dispatched(), !may_decline); + assert!( + litellm_error::Report::new(&error) + .to_string() + .contains("result rejected") + ); + } } diff --git a/litellm-rust/crates/inference/src/context.rs b/litellm-rust/crates/inference/src/context.rs index 655b768dde1..963aa7b90c5 100644 --- a/litellm-rust/crates/inference/src/context.rs +++ b/litellm-rust/crates/inference/src/context.rs @@ -1,6 +1,6 @@ use litellm_cache_response::CachePolicy; use litellm_host::{ - interceptors::{ExecutionFacts, Interceptors, RawResponse}, + interceptors::{ExecutionFacts, Interceptors, RawResponse, ResultSource}, lifecycle::{CallEvent, ExecutionEvent}, observation::ObservationSender, }; @@ -28,7 +28,17 @@ impl<'a, I: Interceptors> CallContext<'a, I> { facts: facts.clone(), })); } - self.interceptors.result_ready(facts).await + let from_provider = facts.source == ResultSource::Provider; + self.interceptors + .result_ready(facts) + .await + .map_err(|error| { + if from_provider { + Error::post_call(error) + } else { + error + } + }) } pub async fn response_received(&self, body: &str) -> Result<(), Error> { diff --git a/litellm-rust/crates/inference/src/error.rs b/litellm-rust/crates/inference/src/error.rs index 895c8c55e01..a8e6fb4e1b3 100644 --- a/litellm-rust/crates/inference/src/error.rs +++ b/litellm-rust/crates/inference/src/error.rs @@ -1,57 +1,48 @@ -//! One error for every route in this crate. OCR still carries its own, richer enum. -//! -//! A variant is declared by the layer that produces it and nested here as is: -//! credentials by `litellm_auth` (AWS folds into it at that crate's boundary), the wire by -//! `litellm_http`, secrets by `litellm_secrets`. The transformation layer's [`LlmError`] -//! maps onto the same-named variants once, here, so no route re-declares them. - use std::sync::Arc; -use litellm_http::transport::Error as TransportError; -use litellm_llms::Error as LlmError; +use litellm_core_utils::decline::Decline; +use litellm_host::machine::MachineFault; +use litellm_llms::{Error as LlmError, ErrorDetail}; #[derive(Clone, Debug, PartialEq, Eq, thiserror::Error)] pub enum Error { - #[error("expected {expected}, got {actual}")] - InvalidType { - expected: &'static str, - actual: &'static str, - }, - #[error("missing required field: {0}")] - MissingField(&'static str), #[error("invalid provider: {0}")] InvalidProvider(String), - #[error("invalid request: {0}")] - InvalidRequest(#[source] litellm_llms::ErrorDetail), - #[error("invalid response: {0}")] - InvalidResponse(#[source] litellm_llms::ErrorDetail), - #[error("unsupported by the rust path: {0}")] - Unsupported(&'static str), + #[error("invalid provider: unable to resolve custom_llm_provider for {route} request")] + UnresolvedProvider { route: &'static str }, + #[error(transparent)] + Declined(Decline), + #[error(transparent)] + Llm(LlmError), #[error(transparent)] Auth(#[from] litellm_auth::Error), #[error(transparent)] - Transport(#[from] TransportError), - #[error(transparent)] Headers(#[from] litellm_http::request::HeaderError), #[error(transparent)] - Http(#[from] litellm_http::Error), + Http(litellm_http::Error), #[error(transparent)] Secret(#[from] SecretError), - #[error("post-call hook failed: {0}")] + #[error("the host driver failed")] + Host(#[source] MachineFault), + #[error("post-call hook failed")] PostCallHook(#[source] Arc), } -impl From for Error { - fn from(fault: litellm_host::machine::MachineFault) -> Self { - use litellm_host::machine::MachineFault; - Self::InvalidRequest(match fault { - MachineFault::Abandoned => "host driver was abandoned".into(), - MachineFault::Protocol(message) => format!("host {message}").into(), - }) +impl From for Error { + fn from(fault: MachineFault) -> Self { + Self::Host(fault) } } impl Error { + pub fn invalid_request(detail: ErrorDetail) -> Self { + Self::Llm(LlmError::InvalidRequest(detail)) + } + + pub fn invalid_response(detail: ErrorDetail) -> Self { + Self::Llm(LlmError::InvalidResponse(detail)) + } + pub fn post_call(error: Self) -> Self { Self::PostCallHook(Arc::new(error)) } @@ -60,31 +51,138 @@ impl Error { /// the provider's answer. pub fn is_request(&self) -> bool { match self { - Self::InvalidType { .. } - | Self::MissingField(_) - | Self::InvalidProvider(_) - | Self::InvalidRequest(_) - | Self::Unsupported(_) - | Self::Headers(_) => true, - Self::Auth(error) => !matches!(error, litellm_auth::Error::MissingApiKey { .. }), - Self::InvalidResponse(_) - | Self::Transport(_) - | Self::Http(_) + Self::InvalidProvider(_) | Self::UnresolvedProvider { .. } | Self::Headers(_) => true, + Self::Llm(error) => error.is_request(), + Self::Auth(error) => error.is_request(), + Self::Http(error) => error.is_request(), + Self::Declined(_) | Self::Secret(_) | Self::Host(_) | Self::PostCallHook(_) => false, + } + } + + pub fn is_response(&self) -> bool { + match self { + Self::Llm(error) => error.is_response(), + Self::Http(error) => error.is_response(), + Self::InvalidProvider(_) + | Self::UnresolvedProvider { .. } + | Self::Declined(_) + | Self::Auth(_) + | Self::Headers(_) | Self::Secret(_) + | Self::Host(_) | Self::PostCallHook(_) => false, } } + + pub fn is_missing_credential(&self) -> bool { + match self { + Self::Llm(error) => error.is_missing_credential(), + Self::Auth(error) => error.is_missing_credential(), + Self::InvalidProvider(_) + | Self::UnresolvedProvider { .. } + | Self::Declined(_) + | Self::Headers(_) + | Self::Http(_) + | Self::Secret(_) + | Self::Host(_) + | Self::PostCallHook(_) => false, + } + } + + pub fn declined(&self) -> Option<&Decline> { + match self { + Self::Declined(decline) => Some(decline), + Self::Llm(error) => error.declined(), + Self::InvalidProvider(_) + | Self::UnresolvedProvider { .. } + | Self::Auth(_) + | Self::Headers(_) + | Self::Http(_) + | Self::Secret(_) + | Self::Host(_) + | Self::PostCallHook(_) => None, + } + } + + /// Re-tag an error raised while handling an answer the provider already returned. + /// + /// A config reports the same variants on either side of the call, so a missing field or + /// a decline can mean "this request cannot be translated" before the send and "this + /// response cannot be normalized" after it. Only the second kind was billed, and a host + /// that keeps a reference implementation must not retry it. + pub fn after_send(self) -> Self { + if self.is_response() || self.upstream_response().is_some() { + return self; + } + Self::invalid_response(ErrorDetail::invalid("provider response", self)) + } + + pub fn dispatched(&self) -> bool { + match self { + Self::Llm(error) => error.dispatched(), + Self::Http(error) => error.dispatched(), + Self::Host(_) | Self::PostCallHook(_) => true, + Self::InvalidProvider(_) + | Self::UnresolvedProvider { .. } + | Self::Declined(_) + | Self::Auth(_) + | Self::Headers(_) + | Self::Secret(_) => false, + } + } + + pub fn rejected_request(&self) -> Option<&(dyn std::error::Error + 'static)> { + match self { + Self::Llm(error) => error.rejected_request(), + Self::InvalidProvider(_) + | Self::UnresolvedProvider { .. } + | Self::Declined(_) + | Self::Auth(_) + | Self::Headers(_) + | Self::Http(_) + | Self::Secret(_) + | Self::Host(_) + | Self::PostCallHook(_) => None, + } + } + + pub fn upstream_response(&self) -> Option<(u16, &str)> { + match self { + Self::Llm(error) => error.upstream_response(), + Self::Http(error) => error.upstream_response(), + Self::InvalidProvider(_) + | Self::UnresolvedProvider { .. } + | Self::Declined(_) + | Self::Auth(_) + | Self::Headers(_) + | Self::Secret(_) + | Self::Host(_) + | Self::PostCallHook(_) => None, + } + } +} + +impl From for Error { + fn from(error: litellm_http::Error) -> Self { + // Python drops the caller's copy and prefers a forwarded Authorization + // over the signature, so leave the request to it. + if error.is_computed_header() { + return Self::Declined(Decline::new("request forwards a header AWS SigV4 computes")); + } + Self::Http(error) + } } impl From for Error { fn from(error: LlmError) -> Self { match error { - LlmError::InvalidType { expected, actual } => Self::InvalidType { expected, actual }, - LlmError::MissingField(field) => Self::MissingField(field), - LlmError::InvalidRequest(message) => Self::InvalidRequest(message), - LlmError::InvalidResponse(message) => Self::InvalidResponse(message), - LlmError::Unsupported(reason) => Self::Unsupported(reason), + LlmError::Declined(decline) => Self::Declined(decline), + LlmError::Http(error) => Self::from(error), LlmError::Auth(error) => Self::Auth(error), + error @ (LlmError::InvalidType { .. } + | LlmError::MissingField(_) + | LlmError::InvalidRequest(_) + | LlmError::InvalidResponse(_)) => Self::Llm(error), } } } @@ -116,26 +214,205 @@ impl Eq for SecretError {} #[cfg(test)] mod tests { use super::Error; + use litellm_core_utils::decline::Decline; + use litellm_host::machine::MachineFault; use litellm_llms::{Error as LlmError, ErrorDetail}; use rstest::rstest; - #[test] - fn a_missing_api_key_is_the_environment_not_the_request() { - assert!( - !Error::Auth(litellm_auth::Error::MissingApiKey { - provider: "Anthropic", - environment_variable: "ANTHROPIC_API_KEY", - }) - .is_request() - ); - assert!(Error::Auth(litellm_auth::Error::InvalidHeader).is_request()); - assert!(Error::InvalidRequest("top_k".into()).is_request()); - assert!(!Error::InvalidResponse("bad json".into()).is_request()); + #[rstest] + #[case::missing_api_key( + litellm_auth::Error::MissingApiKey { + provider: "Anthropic", + environment_variable: "ANTHROPIC_API_KEY", + } + .into(), + false + )] + #[case::invalid_auth_header(litellm_auth::Error::InvalidHeader.into(), true)] + #[case::transformation_missing_api_key( + LlmError::Auth(litellm_auth::Error::MissingApiKey { + provider: "Anthropic", + environment_variable: "ANTHROPIC_API_KEY", + }) + .into(), + false + )] + #[case::invalid_request( + LlmError::InvalidRequest(ErrorDetail::Expected { + subject: "top_k", + expected: "an integer", + }) + .into(), + true + )] + #[case::invalid_response( + LlmError::InvalidResponse(ErrorDetail::MissingField { + subject: "response", + field: "usage", + }) + .into(), + false + )] + #[case::host_driver(MachineFault::Abandoned.into(), false)] + #[case::post_call_hook_over_a_request_fault( + Error::post_call(LlmError::MissingField("usage").into()), + false + )] + fn only_the_callers_input_is_a_request_fault(#[case] error: Error, #[case] is_request: bool) { + assert_eq!(error.is_request(), is_request); } + + #[rstest] + #[case::own_auth(litellm_auth::Error::MissingApiKey { + provider: "Anthropic", + environment_variable: "ANTHROPIC_API_KEY", + } + .into())] + #[case::transformation_auth( + LlmError::Auth(litellm_auth::Error::MissingApiKey { + provider: "Anthropic", + environment_variable: "ANTHROPIC_API_KEY", + }) + .into() + )] + fn a_missing_api_key_is_a_missing_credential_wherever_it_is_raised(#[case] error: Error) { + assert!(error.is_missing_credential()); + } + + #[rstest] + #[case::direct(litellm_http::Error::computed_header("authorization").into())] + #[case::through_a_transformation( + LlmError::Http(litellm_http::Error::computed_header("authorization")).into() + )] + fn a_header_the_signer_computes_is_left_to_the_host_on_every_route(#[case] error: Error) { + assert!(error.declined().is_some(), "{error:?}"); + assert!(!error.dispatched()); + } + + #[test] + fn a_transformation_decline_survives_into_the_route_error() { + let decline = Decline::new("unrecognized request parameter"); + let error = Error::from(LlmError::Declined(decline)); + assert_eq!(error.declined(), Some(&decline)); + assert!(!error.is_request()); + assert!(!error.dispatched()); + } + + #[test] + fn a_post_call_hook_failure_is_never_a_decline() { + let hook = Error::post_call(Error::Declined(Decline::new("hook"))); + assert_eq!(hook.declined(), None); + } + + #[rstest] + #[case::declined(Error::Declined(Decline::new("non-text response content block")))] + #[case::transformation_decline(LlmError::Declined(Decline::new("streaming")).into())] + #[case::missing_field(LlmError::MissingField("usage").into())] + #[case::invalid_request(Error::invalid_request(ErrorDetail::Expected { + subject: "whatever", + expected: "anything else", + }))] + #[case::auth(Error::Auth(litellm_auth::Error::InvalidHeader))] + #[case::host_driver(MachineFault::Abandoned.into())] + fn errors_after_the_send_are_response_faults_and_never_a_decline(#[case] error: Error) { + let report = litellm_error::Report::new(&error).to_string(); + let collapsed = error.after_send(); + assert!(collapsed.is_response(), "{collapsed:?}"); + assert!(!collapsed.is_request(), "{collapsed:?}"); + assert!(collapsed.dispatched(), "{collapsed:?}"); + assert_eq!(collapsed.declined(), None); + let collapsed_report = litellm_error::Report::new(&collapsed).to_string(); + assert!(collapsed_report.ends_with(&report), "{collapsed_report}"); + } + + #[test] + fn a_response_fault_is_not_wrapped_twice_after_the_send() { + let original = Error::invalid_response(ErrorDetail::MissingField { + subject: "response", + field: "usage", + }); + let report = litellm_error::Report::new(&original).to_string(); + assert_eq!( + litellm_error::Report::new(&original.after_send()).to_string(), + report + ); + } + + #[test] + fn a_provider_answer_stays_as_is_after_the_send() { + let upstream = Error::from(litellm_http::Error::upstream(429, "slow down".into())); + assert_eq!( + upstream.after_send().upstream_response(), + Some((429, "slow down")) + ); + } + + #[test] + fn an_upstream_failure_through_a_transformation_keeps_the_provider_answer() { + let error = Error::from(LlmError::Http(litellm_http::Error::upstream( + 429, + "slow down".into(), + ))); + assert_eq!(error.upstream_response(), Some((429, "slow down"))); + assert!(error.dispatched()); + } + + #[rstest] + #[case::invalid_request( + Error::invalid_request(ErrorDetail::Expected { + subject: "messages", + expected: "non-empty", + }), + Some("messages must be non-empty") + )] + #[case::missing_field( + LlmError::MissingField("max_tokens").into(), + Some("missing required field: max_tokens") + )] + #[case::invalid_response( + Error::invalid_response(ErrorDetail::MissingField { + subject: "response", + field: "usage", + }), + None + )] + #[case::provider_rejection(litellm_http::Error::upstream(400, "bad".into()).into(), None)] + #[case::unresolved_provider(Error::InvalidProvider("unknown".into()), None)] + fn a_rejected_request_names_only_what_the_caller_got_wrong( + #[case] error: Error, + #[case] expected: Option<&str>, + ) { + let rejection = error + .rejected_request() + .map(|rejection| litellm_error::Report::new(rejection).to_string()); + assert_eq!(rejection.as_deref(), expected); + } + + #[test] + fn a_post_call_hook_failure_is_not_the_providers_answer() { + let error = + Error::post_call(litellm_http::Error::upstream(500, "hook backend down".into()).into()); + assert_eq!(error.upstream_response(), None); + assert!(!error.is_request()); + let report = litellm_error::Report::new(&error).to_string(); + assert!(report.starts_with("post-call hook failed: "), "{report}"); + assert!(report.contains("hook backend down"), "{report}"); + } + + #[test] + fn a_host_driver_fault_keeps_the_fault_as_its_source() { + let error = Error::from(MachineFault::Abandoned); + assert_eq!( + litellm_error::find::(&error), + Some(&MachineFault::Abandoned) + ); + assert!(error.dispatched()); + } + #[rstest] #[case::request(true)] #[case::response(false)] - fn contextual_errors_preserve_sources_and_route_classification(#[case] request: bool) { + fn contextual_errors_keep_their_cause_and_route_classification(#[case] request: bool) { let source = serde_json::from_str::("{").unwrap_err(); let source_message = source.to_string(); let detail = ErrorDetail::invalid("test payload", source); @@ -145,16 +422,10 @@ mod tests { LlmError::InvalidResponse(detail) }); assert_eq!(error.is_request(), request); - let category = if request { "request" } else { "response" }; - assert_eq!( - error.to_string(), - format!("invalid {category}: invalid test payload: {source_message}") - ); - let source = std::iter::successors(Some(&error as &dyn std::error::Error), |error| { - error.source() - }) - .find_map(|error| error.downcast_ref::()) - .expect("the original JSON error remains available"); - assert_eq!(source.to_string(), source_message); + assert_eq!(error.is_response(), !request); + let report = litellm_error::Report::new(&error).to_string(); + assert!(report.contains("test payload"), "{report}"); + assert_eq!(report.matches(&source_message).count(), 1, "{report}"); + assert!(litellm_error::find::(&error).is_some()); } } diff --git a/litellm-rust/crates/inference/src/outbound.rs b/litellm-rust/crates/inference/src/outbound.rs index 41fe3aa62b8..b0cc71d425d 100644 --- a/litellm-rust/crates/inference/src/outbound.rs +++ b/litellm-rust/crates/inference/src/outbound.rs @@ -1,6 +1,6 @@ use std::time::Duration; -use litellm_http::outbound::OutboundRequest; +use litellm_http::outbound::{json, signed}; use litellm_llms::base_llm::auth::Authenticated; use serde_json::Value; @@ -11,25 +11,26 @@ use serde_json::Value; fields(status) )] pub async fn send( - request: OutboundRequest, + request: reqwest::Request, client: &litellm_http::Client, -) -> Result { - request.send(client).await.inspect(|response| { - tracing::Span::current().record("status", response.status().as_u16()); - }) +) -> Result { + let response = client.execute(request).await?; + tracing::Span::current().record("status", response.status().as_u16()); + Ok(response) } /// Header credentials are already in `headers`; SigV4 is applied here, over the /// bytes that are sent. pub fn outbound_request( authenticated: Authenticated, - url: String, + url: &str, body: &Value, timeout: Option, -) -> Result { +) -> Result { let Authenticated { headers, signer } = authenticated; + let request = json(url, &headers, body, timeout)?; match signer { - None => OutboundRequest::json(url, headers, body, timeout), - Some(signer) => OutboundRequest::signed_json(url, headers, body, timeout, &signer), + None => Ok(request), + Some(signer) => signed(request, &signer), } } diff --git a/litellm-rust/crates/inference/src/provider.rs b/litellm-rust/crates/inference/src/provider.rs index 305aca85f97..fa226a4ef8d 100644 --- a/litellm-rust/crates/inference/src/provider.rs +++ b/litellm-rust/crates/inference/src/provider.rs @@ -25,11 +25,7 @@ pub fn resolve_llm_provider<'a>( custom_llm_provider: provider, }) }) - .ok_or_else(|| { - Error::InvalidProvider(format!( - "unable to resolve custom_llm_provider for {route} request" - )) - })?; + .ok_or(Error::UnresolvedProvider { route })?; let provider = custom_llm_provider .parse() .map_err(|_| Error::InvalidProvider(custom_llm_provider.to_string()))?; diff --git a/litellm-rust/crates/inference/tests/caching.rs b/litellm-rust/crates/inference/tests/caching.rs index a0a6a757565..4e8b2349ac8 100644 --- a/litellm-rust/crates/inference/tests/caching.rs +++ b/litellm-rust/crates/inference/tests/caching.rs @@ -14,6 +14,7 @@ use litellm_cache_memory::InMemoryCache; use litellm_cache_response::{ CacheOptions, CachePolicy, CacheScope, ResponseCache, ResponseCacheConfig, ResponseCacheService, }; +use litellm_core_utils::decline::Decline; use litellm_host::{ call::{CallOutput, OutputOf}, interceptors::{ @@ -204,7 +205,8 @@ async fn streamed( .chunks(3) .map(|bytes| Ok(Bytes::copy_from_slice(bytes))) .collect::>(); - let ending = fail.then_some(Err(Error::Unsupported("test transport failure"))); + let ending = + fail.then_some(Err(Error::Declined(Decline::new("test transport failure")))); Ok(CallOutput::Stream { head: (), chunks: stream::iter(chunks.into_iter().chain(ending)).boxed(), @@ -315,7 +317,7 @@ async fn a_provider_failure_never_populates_the_cache(cache: Arc Result, litellm_cache::Error> { - Err(litellm_cache::Error::Unavailable) + Err(litellm_cache::Error::Unavailable(None)) } fn set_cache( @@ -426,7 +428,7 @@ impl litellm_cache::BaseCache for UnavailableCache { _: Self::Value, _: &Self::Context, ) -> Result<(), litellm_cache::Error> { - Err(litellm_cache::Error::Unavailable) + Err(litellm_cache::Error::Unavailable(None)) } } @@ -482,7 +484,7 @@ impl Interceptors for CacheHitAccounting { ); self.key.set(key).unwrap(); if self.reject { - return Err(Error::Unsupported("cache accounting rejected")); + return Err(Error::Declined(Decline::new("cache accounting rejected"))); } Ok(()) } @@ -569,10 +571,10 @@ async fn cache_hits_notify_accounting_once_and_propagate_its_failure( .await }; if reject { - assert!(matches!( - result, - Err(Error::Unsupported("cache accounting rejected")) - )); + assert_eq!( + result.unwrap_err().declined(), + Some(&Decline::new("cache accounting rejected")) + ); } else { assert_eq!(result.unwrap(), expected); } diff --git a/litellm-rust/crates/llms-types/src/formats/audio_transcription/response.rs b/litellm-rust/crates/llms-types/src/formats/audio_transcription/response.rs index 624eb7be4e4..211d4d0f648 100644 --- a/litellm-rust/crates/llms-types/src/formats/audio_transcription/response.rs +++ b/litellm-rust/crates/llms-types/src/formats/audio_transcription/response.rs @@ -1,14 +1,31 @@ use serde_json::Value; +#[macro_rules_attribute::apply(crate::wire_type)] +pub struct AudioTranscriptionUsage { + pub input_tokens: u64, + pub output_tokens: u64, + pub total_tokens: u64, +} + #[macro_rules_attribute::apply(crate::wire_type)] pub struct AudioTranscriptionResponseData { pub text: String, + pub usage: Option, } impl AudioTranscriptionResponseData { pub fn into_json(self) -> Value { - serde_json::json!({ - "text": self.text, - }) + match self.usage { + None => serde_json::json!({"text": self.text}), + Some(usage) => serde_json::json!({ + "text": self.text, + "usage": { + "type": "tokens", + "input_tokens": usage.input_tokens, + "output_tokens": usage.output_tokens, + "total_tokens": usage.total_tokens, + }, + }), + } } } diff --git a/litellm-rust/crates/llms/Cargo.toml b/litellm-rust/crates/llms/Cargo.toml index 2d3ea85d1fc..962f61ef4ec 100644 --- a/litellm-rust/crates/llms/Cargo.toml +++ b/litellm-rust/crates/llms/Cargo.toml @@ -11,6 +11,7 @@ test-support = ["litellm-http/test-support"] [dependencies] litellm-llms-types.workspace = true litellm-core-utils.workspace = true +litellm-error.workspace = true litellm-auth = { workspace = true, features = ["aws", "azure", "gcp"] } litellm-auth-aws.workspace = true litellm-auth-azure.workspace = true diff --git a/litellm-rust/crates/llms/src/anthropic/batches/transformation.rs b/litellm-rust/crates/llms/src/anthropic/batches/transformation.rs index b8ea701af99..0513f88038d 100644 --- a/litellm-rust/crates/llms/src/anthropic/batches/transformation.rs +++ b/litellm-rust/crates/llms/src/anthropic/batches/transformation.rs @@ -1,3 +1,4 @@ +use litellm_core_utils::decline::Decline; use litellm_llms_types::formats::batches::{BatchRequestCounts, BatchResponse, BatchStatus}; use litellm_llms_types::formats::messages::MessagesResponse; use litellm_llms_types::providers::anthropic::{BATCHES_PATH, MESSAGES_PATH}; @@ -127,7 +128,9 @@ impl AnthropicBatchesConfig for AnthropicBatchesTransformation { } fn transform_create_batch_request(&self) -> Result { - Err(Error::Unsupported("Anthropic message batch creation")) + Err(Error::Declined(Decline { + reason: "Anthropic message batch creation", + })) } fn transform_create_batch_response( @@ -135,7 +138,9 @@ impl AnthropicBatchesConfig for AnthropicBatchesTransformation { _response: AnthropicMessageBatch, _now: i64, ) -> Result { - Err(Error::Unsupported("Anthropic message batch creation")) + Err(Error::InvalidResponse(crate::ErrorDetail::Unhandled( + "Anthropic message batch creation", + ))) } fn retrieve_batch_url( @@ -149,7 +154,12 @@ impl AnthropicBatchesConfig for AnthropicBatchesTransformation { } let mut url = batches_base_url(api_base, env_lookup)?; url.path_segments_mut() - .map_err(|_| Error::InvalidRequest("Anthropic API base cannot be a base URL".into()))? + .map_err(|()| { + Error::InvalidRequest(crate::ErrorDetail::Expected { + subject: "Anthropic API base", + expected: "a base URL", + }) + })? .push(batch_id); Ok(url.into()) } @@ -217,11 +227,11 @@ impl AnthropicBatchesConfig for AnthropicBatchesTransformation { .map(|(index, line)| { let record: BatchResultRecord = serde_json::from_str(line.trim()).map_err(|error| { - Error::InvalidResponse(crate::ErrorDetail::InvalidLine { - subject: "Anthropic batch result", - line: index + 1, - source: crate::ErrorSource::new(error), - }) + Error::InvalidResponse(crate::ErrorDetail::invalid_line( + "Anthropic batch result", + index + 1, + error, + )) })?; match record.result { BatchResult::Succeeded { message } => Ok(*message), @@ -314,30 +324,40 @@ mod tests { assert_eq!(messages[0].id, "msg_1"); } - #[test] - fn reports_malformed_and_unsuccessful_batch_results() { - assert!(matches!( - ANTHROPIC_BATCHES_TRANSFORMATION.transform_batch_results("not-json"), - Err(Error::InvalidResponse(message)) if message.to_string().contains("line 1") - )); - assert!(matches!( - ANTHROPIC_BATCHES_TRANSFORMATION.transform_batch_results( - r#"{"result":{"type":"errored","error":{"type":"invalid_request_error"}}}"# - ), - Err(Error::InvalidResponse(message)) if message.to_string().contains("request failed") - )); + #[rstest::rstest] + #[case::malformed("not-json", "line 1")] + #[case::errored( + r#"{"result":{"type":"errored","error":{"type":"invalid_request_error"}}}"#, + "request failed" + )] + fn reports_malformed_and_unsuccessful_batch_results(#[case] body: &str, #[case] fact: &str) { + let error = ANTHROPIC_BATCHES_TRANSFORMATION + .transform_batch_results(body) + .unwrap_err(); + assert!(matches!(error, Error::InvalidResponse(_)), "{error:?}"); + assert!( + litellm_error::Report::new(&error) + .to_string() + .contains(fact) + ); } - #[test] - fn preserves_python_placeholder_for_batch_creation() { - assert!(matches!( - ANTHROPIC_BATCHES_TRANSFORMATION.transform_create_batch_request(), - Err(Error::Unsupported("Anthropic message batch creation")) - )); + #[rstest::rstest] + fn batch_creation_only_declines_before_a_provider_response() { + let error = ANTHROPIC_BATCHES_TRANSFORMATION + .transform_create_batch_request() + .unwrap_err(); + assert!(!error.dispatched()); + assert_eq!( + error.declined().map(|decline| decline.reason), + Some("Anthropic message batch creation") + ); let response: AnthropicMessageBatch = serde_json::from_value(json!({})).unwrap(); - assert!(matches!( - ANTHROPIC_BATCHES_TRANSFORMATION.transform_create_batch_response(response, 0), - Err(Error::Unsupported("Anthropic message batch creation")) - )); + let error = ANTHROPIC_BATCHES_TRANSFORMATION + .transform_create_batch_response(response, 0) + .unwrap_err(); + assert!(error.dispatched()); + assert!(error.is_response()); + assert!(error.declined().is_none()); } } diff --git a/litellm-rust/crates/llms/src/anthropic/chat/handler.rs b/litellm-rust/crates/llms/src/anthropic/chat/handler.rs deleted file mode 100644 index eaee006f228..00000000000 --- a/litellm-rust/crates/llms/src/anthropic/chat/handler.rs +++ /dev/null @@ -1,163 +0,0 @@ -use std::collections::HashMap; - -use litellm_llms_types::formats::{ - chat_completions::{ - ChatCompletionChunk, ChatCompletionThinkingBlock, ChatCompletionToolCallChunk, - ChatCompletionsUsage, - }, - messages::streaming::{ - MessagesContentBlock, MessagesContentBlockDelta, MessagesStreamEvent, MessagesStreamUsage, - }, -}; -use serde_json::Value; - -use crate::{ - Error, - base_llm::{base_model_iterator::StreamTransformer, chat::streaming::StreamShape}, -}; - -#[derive(Clone, Copy, Debug, Eq, PartialEq)] -pub enum AnthropicJsonChunkType { - ValidJson, - AccumulatedJson, -} - -#[derive(Clone, Debug, Eq, PartialEq)] -pub enum AnthropicContentBlockType { - Text, - ToolUse, - ServerToolUse, - Thinking, - RedactedThinking, - Compaction, - ToolResult(String), - Other(String), -} - -#[derive(Clone, Debug, PartialEq)] -pub struct AnthropicContentBlockDeltaEvent { - pub index: u64, - pub delta: MessagesContentBlockDelta, -} - -pub struct ModelResponseIterator { - pub content_blocks: Vec, - pub tool_index: i64, - pub json_mode: bool, - pub speed: Option, - pub tool_name_reverse_map: HashMap, - pub response_id: String, - pub served_model: Option, - pub is_response_format_tool: bool, - pub converted_response_format_tool: bool, - pub accumulated_json: String, - pub chunk_type: AnthropicJsonChunkType, - pub current_content_block_type: Option, - pub web_search_results: Vec, - pub web_search_calls: HashMap, - pub compaction_blocks: Vec, - pub reasoning_content_chunks: Vec, - pub server_tool_inputs: HashMap, - pub tool_results: Vec, - pub current_server_tool_id: Option, - pub container_id: Option, -} - -impl ModelResponseIterator { - pub fn new(_shape: StreamShape) -> Self { - todo!() - } - - pub fn check_empty_tool_call_args(&self) -> bool { - todo!() - } - - pub fn handle_usage(&mut self, _usage: MessagesStreamUsage) -> ChatCompletionsUsage { - todo!() - } - - pub fn handle_content_block_delta( - &mut self, - _index: u64, - _delta: MessagesContentBlockDelta, - ) -> ( - String, - Option, - Vec, - Option, - Option, - ) { - todo!() - } - - pub fn handle_content_block_start( - &mut self, - _index: u64, - _content_block: MessagesContentBlock, - ) -> Result { - todo!() - } - - pub fn handle_json_mode_chunk( - &mut self, - _text: String, - _tool_use: Option, - ) -> (String, Option) { - todo!() - } - - pub fn handle_accumulated_json_chunk( - &mut self, - _data: &str, - _is_final: bool, - ) -> Result, Error> { - todo!() - } - - pub fn handle_redacted_thinking_content( - &mut self, - _content_block: &MessagesContentBlock, - ) -> Vec { - todo!() - } - - pub fn web_search_call_snapshot(&self) -> HashMap { - todo!() - } - - pub fn complete_web_search_call(&mut self, _result: Value) { - todo!() - } - - pub fn build_code_interpreter_results(&self) -> Vec { - todo!() - } - - pub fn handle_message_delta( - &mut self, - _event: MessagesStreamEvent, - ) -> (Option, Option, Option) { - todo!() - } - - pub fn chunk_parser( - &mut self, - _event: MessagesStreamEvent, - ) -> Result { - todo!() - } -} - -impl StreamTransformer for ModelResponseIterator { - type Input = MessagesStreamEvent; - type Output = ChatCompletionChunk; - type Error = Error; - - fn transform(&mut self, _input: Self::Input) -> Result, Self::Error> { - todo!() - } - - fn finish(&mut self) -> Result, Self::Error> { - todo!() - } -} diff --git a/litellm-rust/crates/llms/src/anthropic/chat/mod.rs b/litellm-rust/crates/llms/src/anthropic/chat/mod.rs index f0050b7dc71..f239b6921fa 100644 --- a/litellm-rust/crates/llms/src/anthropic/chat/mod.rs +++ b/litellm-rust/crates/llms/src/anthropic/chat/mod.rs @@ -1,2 +1 @@ -pub mod handler; pub mod transformation; diff --git a/litellm-rust/crates/llms/src/anthropic/chat/transformation.rs b/litellm-rust/crates/llms/src/anthropic/chat/transformation.rs index 91baa247ac8..eb796a900f5 100644 --- a/litellm-rust/crates/llms/src/anthropic/chat/transformation.rs +++ b/litellm-rust/crates/llms/src/anthropic/chat/transformation.rs @@ -1,4 +1,5 @@ use litellm_auth::SecretValue; +use litellm_core_utils::decline::Decline; use litellm_core_utils::{ core_helpers::{finish_reason_for, unix_now, usage_from_parts}, prompt_templates::factory::{Conversation, build_conversation}, @@ -14,23 +15,19 @@ use serde_json::{Map, Value, json}; use crate::{ Error, - anthropic::{ - chat::handler::ModelResponseIterator, - common_utils::{ - API_KEY_PLACEMENT, complete_anthropic_url, forwarded_oauth_bearer, - resolve_anthropic_api_key, - }, + anthropic::common_utils::{ + API_KEY_PLACEMENT, complete_anthropic_url, forwarded_oauth_bearer, + resolve_anthropic_api_key, }, base_llm::{ auth::AuthScheme, chat::{ - streaming::{ChatStream, StreamShape}, + streaming::StreamShape, transformation::{ BaseConfig, Headers, ProviderChatRequestData, ProviderChatResponseData, - Unsupported, ValidatedEnvironment, unsupported_message, unsupported_param, + ValidatedEnvironment, unsupported_message, unsupported_param, }, }, - messages::streaming::event_stream as messages_event_stream, }, }; @@ -130,15 +127,14 @@ impl BaseConfig for AnthropicConfig { serde_json::from_value(response.body).map_err(|error| { Error::InvalidResponse(crate::ErrorDetail::invalid("messages response", error)) })?; - // The route declines tool and thinking requests, so a non-text block - // means the response carries something this path never asked for. - // Decline rather than silently dropping it; the host falls back. if body .content .iter() .any(|block| matches!(block, TextResponseBlock::Other)) { - return Err(Error::Unsupported("non-text response content block")); + return Err(Error::InvalidResponse(crate::ErrorDetail::Unhandled( + "non-text response content block", + ))); } let text: String = body .content @@ -194,13 +190,6 @@ impl BaseConfig for AnthropicConfig { Ok(ValidatedEnvironment { headers, auth }) } - fn model_response_iterator(&self, shape: StreamShape) -> Option { - Some(ChatStream::new( - messages_event_stream, - ModelResponseIterator::new(shape), - )) - } - fn default_headers(&self) -> &'static [(&'static str, &'static str)] { DEFAULT_HEADERS } @@ -214,7 +203,7 @@ impl BaseConfig for AnthropicConfig { &self, messages: &[ChatMessage], optional_params: &Map, - ) -> Option { + ) -> Option { unsupported_param(self.supported_openai_param_mappings(), &[], optional_params) .or_else(|| messages.iter().find_map(unsupported_message)) // Anthropic rejects a request whose first turn is not a user turn. @@ -222,7 +211,7 @@ impl BaseConfig for AnthropicConfig { // core cannot observe, so decline instead of guessing. .or_else(|| { (!build_conversation(messages).opens_on_user_turn()) - .then_some(Unsupported("conversation does not open on a user turn")) + .then_some(Decline::new("conversation does not open on a user turn")) }) } } @@ -271,9 +260,10 @@ mod tests { anthropic::chat::transformation::ANTHROPIC_CHAT_COMPLETIONS_CONFIG, base_llm::{ auth::AuthScheme, - chat::transformation::{BaseConfig, ProviderChatResponseData, Unsupported}, + chat::transformation::{BaseConfig, ProviderChatResponseData}, }, }; + use litellm_core_utils::decline::Decline; use litellm_llms_types::formats::chat_completions::{ChatCompletionsResponse, ChatMessage}; use rstest::rstest; use serde_json::{Map, Value, json}; @@ -301,7 +291,7 @@ mod tests { .transform_response("claude-sonnet-4-5", ProviderChatResponseData { body }) } - fn reason(msgs: Value, opts: Value) -> Option { + fn reason(msgs: Value, opts: Value) -> Option { ANTHROPIC_CHAT_COMPLETIONS_CONFIG.unsupported_reason(&messages(msgs), ¶ms(opts)) } @@ -409,7 +399,7 @@ mod tests { json!([{"role": "user", "content": "hi"}]), json!({"top_k": 40}) ), - Some(Unsupported("unrecognized request parameter")) + Some(Decline::new("unrecognized request parameter")) ); } @@ -420,7 +410,7 @@ mod tests { json!([{"role": "user", "content": "hi"}]), json!({"stream": true, "max_tokens": 16}) ), - Some(Unsupported("streaming")) + Some(Decline::new("streaming")) ); } @@ -445,7 +435,7 @@ mod tests { fn declines_any_param_outside_the_allowlist(#[case] param: Value) { assert_eq!( reason(json!([{"role": "user", "content": "hi"}]), param.clone()), - Some(Unsupported("unrecognized request parameter")), + Some(Decline::new("unrecognized request parameter")), "expected {param} to decline" ); } @@ -463,7 +453,7 @@ mod tests { ]), json!({}) ), - Some(Unsupported("unrecognized message field")) + Some(Decline::new("unrecognized message field")) ); assert_eq!( reason( @@ -473,7 +463,7 @@ mod tests { ]), json!({}) ), - Some(Unsupported("unrecognized message field")) + Some(Decline::new("unrecognized message field")) ); assert_eq!( reason( @@ -483,7 +473,7 @@ mod tests { ]}]), json!({}) ), - Some(Unsupported("non-text message content")) + Some(Decline::new("non-text message content")) ); assert_eq!( reason( @@ -493,7 +483,7 @@ mod tests { ]}]), json!({}) ), - Some(Unsupported("non-text message content")) + Some(Decline::new("non-text message content")) ); } @@ -504,7 +494,7 @@ mod tests { // than declining to Python before it. assert_eq!( reason(json!([{"role": "user", "content": []}]), json!({})), - Some(Unsupported("message without content")) + Some(Decline::new("message without content")) ); assert_eq!( reason( @@ -525,7 +515,7 @@ mod tests { ]), json!({}) ), - Some(Unsupported("conversation does not open on a user turn")) + Some(Decline::new("conversation does not open on a user turn")) ); } @@ -658,7 +648,7 @@ mod tests { } #[test] - fn declines_a_response_carrying_a_non_text_block() { + fn a_response_carrying_a_non_text_block_is_invalid() { let err = transform_response(json!({ "model": "claude-sonnet-4-5", "content": [{"type": "tool_use", "id": "t1", "name": "f", "input": {}}], @@ -666,7 +656,12 @@ mod tests { "usage": {"input_tokens": 1, "output_tokens": 1} })) .expect_err("non-text block"); - assert_eq!(err, Error::Unsupported("non-text response content block")); + assert_eq!( + err, + Error::InvalidResponse(crate::ErrorDetail::Unhandled( + "non-text response content block" + )) + ); } #[rstest::rstest] @@ -676,16 +671,11 @@ mod tests { #[case::missing_model(json!({"content": [], "usage": {"input_tokens": 1, "output_tokens": 1}}))] fn errors_on_a_response_missing_required_fields(#[case] body: Value) { let error = transform_response(body).expect_err("invalid response"); - assert!(matches!(error, Error::InvalidResponse(_))); - let source = std::iter::successors(Some(&error as &dyn std::error::Error), |error| { - error.source() - }) - .find_map(|error| error.downcast_ref::()) - .expect("the JSON decoding source is preserved"); - assert_eq!( - error.to_string(), - format!("invalid response: invalid messages response: {source}") - ); + assert!(matches!(error, Error::InvalidResponse(_)), "{error:?}"); + let cause = litellm_error::find::(&error).expect("JSON cause"); + let report = litellm_error::Report::new(&error).to_string(); + assert!(report.contains("invalid messages response"), "{report}"); + assert_eq!(report.matches(&cause.to_string()).count(), 1, "{report}"); } #[test] diff --git a/litellm-rust/crates/llms/src/anthropic/messages/handler.rs b/litellm-rust/crates/llms/src/anthropic/messages/handler.rs index 6e8de65d6fa..54f924ddec6 100644 --- a/litellm-rust/crates/llms/src/anthropic/messages/handler.rs +++ b/litellm-rust/crates/llms/src/anthropic/messages/handler.rs @@ -208,24 +208,29 @@ mod tests { #[case::empty(json!({}), Ok(json!({})))] #[case::numeric_user_id( json!({"user_id": 123}), - Err(Error::InvalidRequest("metadata.user_id must be a string, got 123".to_string().into())), + Err(invalid_value("metadata.user_id", "a string", json!(123))), )] #[case::boolean_user_id( json!({"user_id": true}), - Err(Error::InvalidRequest("metadata.user_id must be a string, got true".to_string().into())), + Err(invalid_value("metadata.user_id", "a string", json!(true))), )] #[case::not_an_object( json!(["u-1"]), - Err(Error::InvalidRequest(r#"metadata must be an object, got ["u-1"]"#.to_string().into())), + Err(invalid_value("metadata", "an object", json!(["u-1"]))), )] fn validate_anthropic_api_metadata_passes_only_a_string_user_id( #[case] metadata: Value, #[case] expected: Result, ) { - assert_eq!( - validate_anthropic_api_metadata(&metadata).map_err(|error| error.to_string()), - expected.map_err(|error| error.to_string()), - ); + assert_eq!(validate_anthropic_api_metadata(&metadata), expected); + } + + fn invalid_value(field: &'static str, expected: &'static str, actual: Value) -> Error { + Error::InvalidRequest(crate::ErrorDetail::InvalidValue { + field, + expected, + actual, + }) } #[rstest] diff --git a/litellm-rust/crates/llms/src/aws_textract/ocr/analyze_transformation.rs b/litellm-rust/crates/llms/src/aws_textract/ocr/analyze_transformation.rs index e813d4ac8cc..82119cecfa5 100644 --- a/litellm-rust/crates/llms/src/aws_textract/ocr/analyze_transformation.rs +++ b/litellm-rust/crates/llms/src/aws_textract/ocr/analyze_transformation.rs @@ -123,7 +123,7 @@ impl BaseOcrConfig for TextractAnalyzeDocumentConfig { &self, error_message: String, status_code: u16, - headers: Vec<(String, String)>, + headers: reqwest::header::HeaderMap, ) -> Error { error_class(error_message, status_code, headers) } diff --git a/litellm-rust/crates/llms/src/aws_textract/ocr/common_utils.rs b/litellm-rust/crates/llms/src/aws_textract/ocr/common_utils.rs index bc199f40938..e3a4f947433 100644 --- a/litellm-rust/crates/llms/src/aws_textract/ocr/common_utils.rs +++ b/litellm-rust/crates/llms/src/aws_textract/ocr/common_utils.rs @@ -17,6 +17,7 @@ const AWS_JSON_CONTENT_TYPE: &str = "application/x-amz-json-1.1"; const TARGET_HEADER: &str = "X-Amz-Target"; const CONTENT_TYPE_HEADER: &str = "Content-Type"; const UNSUPPORTED_DOCUMENT: &str = "UnsupportedDocumentException"; +const SYNC_API_GUIDANCE: &str = "aws_textract uses Textract's synchronous API, which reads a JPEG, PNG, or a single-page PDF or TIFF; other formats and multi-page documents are not supported"; const SYNC_DOCUMENT_MAX_BYTES: usize = 10 * 1024 * 1024; const HEALTH_CHECK_IMAGE_DATA_URI: &str = "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAIAAACQd1PeAAAADElEQVR4nGP4//8/AAX+Av4N70a4AAAAAElFTkSuQmCC"; @@ -321,20 +322,18 @@ struct AwsError { /// Textract answers both an unsupported format and a multi-page PDF or TIFF /// with a bare "unsupported document format", which reads like a corrupt file. /// Say what the synchronous API accepts. -pub(super) fn error_class(body: String, status: u16, headers: Vec<(String, String)>) -> Error { - let unsupported = serde_json::from_str::(&body) - .ok() - .filter(|error| error.kind.ends_with(UNSUPPORTED_DOCUMENT)); - Error::Provider { - status, - body: match unsupported { - Some(error) => format!( - "{UNSUPPORTED_DOCUMENT}: {}. aws_textract uses Textract's synchronous API, which reads a JPEG, PNG, or a single-page PDF or TIFF; other formats and multi-page documents are not supported", - error.message - ), - None => body, +pub(super) fn error_class(body: String, status: u16, headers: reqwest::header::HeaderMap) -> Error { + match serde_json::from_str::(&body) { + Ok(error) if error.kind.ends_with(UNSUPPORTED_DOCUMENT) => Error::RejectedDocument { + provider: "AWS Textract", + message: error.message, + guidance: SYNC_API_GUIDANCE, + }, + Ok(_) | Err(_) => Error::Provider { + status, + body, + headers: Box::new(headers), }, - headers, } } @@ -408,11 +407,11 @@ mod tests { fn a_model_outside_the_operations_is_refused_with_the_supported_names(#[case] model: &str) { let error = TextractOperation::from_model(model).unwrap_err(); - assert_eq!( - error.to_string(), - format!( - "invalid model: aws_textract has no model {model:?} - use one of: detect-document-text, analyze-document" - ) + let message = error.to_string(); + assert!(message.contains(&format!("{model:?}")), "{message}"); + assert!( + message.contains("detect-document-text, analyze-document"), + "{message}" ); assert_eq!(error.http_status_code(), Some(400)); } @@ -542,43 +541,46 @@ mod tests { #[rstest] #[case::bare_type( r#"{"__type":"UnsupportedDocumentException","Message":"Request has unsupported document format"}"#, - Some("Request has unsupported document format") + "Request has unsupported document format" )] #[case::namespaced_type( r#"{"__type":"com.amazonaws.textract#UnsupportedDocumentException","Message":"bad"}"#, - Some("bad") + "bad" )] #[case::lowercase_message( r#"{"__type":"UnsupportedDocumentException","message":"bad"}"#, - Some("bad") + "bad" )] - #[case::other_exception(r#"{"__type":"AccessDeniedException","Message":"no"}"#, None)] - #[case::json_without_a_type(r#"{"Message":"no"}"#, None)] - #[case::not_json("bad gateway", None)] - fn only_an_unsupported_document_gains_the_sync_api_hint( + fn an_unsupported_document_is_the_callers_fault_with_the_sync_api_hint( #[case] body: &str, - #[case] hinted_message: Option<&str>, + #[case] provider_message: &str, ) { - let response_headers = vec![("x-amzn-requestid".to_string(), "abc".to_string())]; + let error = error_class(body.into(), 400, reqwest::header::HeaderMap::new()); - let Error::Provider { - status, - body: reported, - headers, - } = error_class(body.into(), 400, response_headers.clone()) - else { - panic!("expected a provider error"); - }; + let message = error.to_string(); + assert!(error.is_request()); + assert_eq!(error.http_status_code(), Some(400)); + assert!(error.upstream_response().is_none()); + assert!(message.contains(provider_message), "{message}"); + assert!(message.contains(HINT), "{message}"); + } - assert_eq!(status, 400); - assert_eq!(headers, response_headers); - match hinted_message { - Some(message) => { - assert!(reported.contains(message), "{reported}"); - assert!(reported.contains(HINT), "{reported}"); - } - None => assert_eq!(reported, body), - } + #[rstest] + #[case::other_exception(r#"{"__type":"AccessDeniedException","Message":"no"}"#)] + #[case::json_without_a_type(r#"{"Message":"no"}"#)] + #[case::not_json("bad gateway")] + fn any_other_rejection_passes_through_untouched(#[case] body: &str) { + let response_headers = reqwest::header::HeaderMap::from_iter([( + reqwest::header::HeaderName::from_static("x-amzn-requestid"), + reqwest::header::HeaderValue::from_static("abc"), + )]); + + let error = error_class(body.into(), 403, response_headers.clone()); + + assert_eq!( + error.upstream_response(), + Some((403, body, &response_headers)) + ); } #[rstest] diff --git a/litellm-rust/crates/llms/src/aws_textract/ocr/transformation.rs b/litellm-rust/crates/llms/src/aws_textract/ocr/transformation.rs index 4b27a191734..34213926942 100644 --- a/litellm-rust/crates/llms/src/aws_textract/ocr/transformation.rs +++ b/litellm-rust/crates/llms/src/aws_textract/ocr/transformation.rs @@ -104,7 +104,7 @@ impl BaseOcrConfig for TextractDetectTextConfig { &self, error_message: String, status_code: u16, - headers: Vec<(String, String)>, + headers: reqwest::header::HeaderMap, ) -> Error { error_class(error_message, status_code, headers) } @@ -237,7 +237,7 @@ mod tests { let error = TextractDetectTextConfig.get_error_class( r#"{"__type":"UnsupportedDocumentException","Message":"Request has unsupported document format"}"#.into(), 400, - Vec::new(), + reqwest::header::HeaderMap::new(), ); assert!( diff --git a/litellm-rust/crates/llms/src/azure_ai/ocr/cohere_parse_transformation.rs b/litellm-rust/crates/llms/src/azure_ai/ocr/cohere_parse_transformation.rs index 72e321547e3..bec8bee3f34 100644 --- a/litellm-rust/crates/llms/src/azure_ai/ocr/cohere_parse_transformation.rs +++ b/litellm-rust/crates/llms/src/azure_ai/ocr/cohere_parse_transformation.rs @@ -120,7 +120,8 @@ impl BaseOcrConfig for AzureAICohereParseConfig { impl AzureAICohereParseConfig { fn get_complete_url(&self, base: &str) -> Result { - let mut url = reqwest::Url::parse(base).map_err(|_| invalid_api_base())?; + let mut url = + reqwest::Url::parse(base).map_err(|error| Error::request_field("api_base", error))?; if !matches!(url.scheme(), "http" | "https") { return Err(invalid_api_base()); } @@ -133,13 +134,14 @@ impl AzureAICohereParseConfig { ApiUrl::parse(url.as_str()) .and_then(|url| url.complete_path(&AZURE_COHERE_PARSE_PATH)) .map(|url| url.into_string()) - .map_err(|_| invalid_api_base()) + .map_err(|error| Error::request_field("api_base", error)) } } fn invalid_api_base() -> Error { Error::RequestField { path: "api_base".into(), + cause: None, } } diff --git a/litellm-rust/crates/llms/src/azure_ai/ocr/common_utils.rs b/litellm-rust/crates/llms/src/azure_ai/ocr/common_utils.rs index 8cbf2455e01..7da685febf9 100644 --- a/litellm-rust/crates/llms/src/azure_ai/ocr/common_utils.rs +++ b/litellm-rust/crates/llms/src/azure_ai/ocr/common_utils.rs @@ -26,7 +26,7 @@ pub(super) async fn resolve_entra( .get_azure_ad_token(config, env_lookup) .await .or_else(|error| match error { - litellm_auth::Error::EmptyCallerCredential(_) => Ok(None), + litellm_auth::Error::EmptyCallerCredential { .. } => Ok(None), other => Err(other), }) .map(|credential| { @@ -48,7 +48,7 @@ pub(super) fn validate_destination( && credential_source != InputSource::Request { return Err(litellm_auth::Error::InvalidConfiguration( - "host credentials cannot be sent to a request-controlled Azure endpoint".into(), + litellm_auth::ErrorDetail::RequestControlledEndpoint { provider: "Azure" }, ) .into()); } diff --git a/litellm-rust/crates/llms/src/azure_ai/ocr/document_intelligence/transformation.rs b/litellm-rust/crates/llms/src/azure_ai/ocr/document_intelligence/transformation.rs index 2a50989f4e4..36dfe2c890e 100644 --- a/litellm-rust/crates/llms/src/azure_ai/ocr/document_intelligence/transformation.rs +++ b/litellm-rust/crates/llms/src/azure_ai/ocr/document_intelligence/transformation.rs @@ -1,4 +1,7 @@ -use std::{collections::BTreeSet, time::Duration}; +use std::{ + collections::{BTreeMap, BTreeSet}, + time::Duration, +}; use base64::{Engine, engine::general_purpose::STANDARD}; use litellm_auth::{InputSource, Sourced}; @@ -8,18 +11,19 @@ use litellm_llms_types::serde_compat::{FiniteF64, LaxI64}; use reqwest::Url; use serde::{Deserialize, Serialize}; use serde_json::{Map, Value}; -use serde_with::serde_as; +use serde_with::{DefaultOnError, serde_as}; use tokio::time::Instant; use crate::base_llm::ocr::{ document::InlineDocument, - error::Error, + error::{Error, PagesFault, PollUrl}, handler::{CallHooks, OcrClient, read_json_response}, settings::OcrSettings, transformation::{ - BaseOcrConfig, DecodedOcrResponse, OCR_INLINE_MAX_BYTES, OCR_POLL_RETRY_SECS, - OcrConnection, OcrCredentialInputs, OcrResponseContext, PreparedOcrRequest, - ResolvedOcrCredentials, decode_and_normalize_response, decode_response, + BaseOcrConfig, DROP_PARAMS_PARAM, DecodedOcrResponse, OCR_INLINE_MAX_BYTES, + OCR_POLL_RETRY_SECS, OcrConnection, OcrCredentialInputs, OcrResponseContext, + PreparedOcrRequest, ResolvedOcrCredentials, decode_and_normalize_response, decode_response, + drops_unsupported_params, response_format, }, }; use litellm_llms_types::formats::ocr::{ @@ -32,6 +36,30 @@ const AZURE_DI_DEFAULT_HEIGHT: f64 = 11.0; const AZURE_DI_API_KEY_ENV: &str = "AZURE_DOCUMENT_INTELLIGENCE_API_KEY"; const AZURE_DI_ENDPOINT_ENV: &str = "AZURE_DOCUMENT_INTELLIGENCE_ENDPOINT"; +const OUTPUT_CONTENT_FORMAT_PARAM: &str = "outputContentFormat"; +const OUTPUT_CONTENT_FORMAT_ALIAS: &str = "output_content_format"; +const CODE_POINT_STRING_INDEX: &str = "unicodeCodePoint"; +const STRING_INDEX_TYPE_FIELD: &str = "stringIndexType"; +const MARKDOWN_MODEL_ID: &str = "prebuilt-layout"; + +#[derive( + Clone, + Copy, + Debug, + PartialEq, + strum::EnumString, + strum::IntoStaticStr, + strum::Display, + strum::VariantArray, + serde_with::SerializeDisplay, +)] +#[strum(ascii_case_insensitive)] +pub enum OutputContentFormat { + #[strum(serialize = "text")] + Text, + #[strum(serialize = "markdown")] + Markdown, +} #[derive(Clone, Debug, PartialEq, Serialize)] pub struct DocumentIntelligenceParams { @@ -39,6 +67,13 @@ pub struct DocumentIntelligenceParams { pub pages: Option, #[serde(skip_serializing_if = "Option::is_none")] pub features: Option, + #[serde( + rename = "outputContentFormat", + skip_serializing_if = "Option::is_none" + )] + pub output_content_format: Option, + #[serde(rename = "stringIndexType", skip_serializing_if = "Option::is_none")] + pub string_index_type: Option<&'static str>, } #[derive(Clone, Debug, Serialize, Deserialize)] @@ -80,6 +115,10 @@ pub struct AzureDocumentIntelligenceOperation { #[derive(Clone, Debug, Default, Deserialize)] struct AzureDocumentIntelligenceAnalyzeResult { pub content: Option, + #[serde(rename = "contentFormat")] + pub content_format: Option, + #[serde(rename = "stringIndexType")] + pub string_index_type: Option, #[serde(default)] pub pages: Vec, pub tables: Option>>, @@ -100,6 +139,9 @@ struct AzureDocumentIntelligencePage { pub unit: Option, #[serde(default)] pub lines: Vec, + #[serde(default)] + #[serde_as(deserialize_as = "DefaultOnError")] + pub spans: Option>, } #[derive(Clone, Debug, Deserialize)] @@ -107,6 +149,18 @@ struct AzureDocumentIntelligenceLine { pub content: Option, } +#[derive(Clone, Debug, Deserialize)] +struct AzureDocumentIntelligenceSpan { + pub offset: usize, + pub length: usize, +} + +impl AzureDocumentIntelligenceSpan { + fn end(&self) -> usize { + self.offset.saturating_add(self.length) + } +} + #[derive(Clone, Debug)] pub struct AzureDocumentIntelligenceOcrConfig; @@ -116,7 +170,14 @@ impl BaseOcrConfig for AzureDocumentIntelligenceOcrConfig { type Environment = Vec<(String, String)>; fn get_supported_ocr_params(&self, _model: &str) -> &'static [&'static str] { - &["pages", "features", "req_format"] + &[ + "pages", + "features", + OUTPUT_CONTENT_FORMAT_PARAM, + OUTPUT_CONTENT_FORMAT_ALIAS, + "req_format", + DROP_PARAMS_PARAM, + ] } fn get_api_key_env_var(&self) -> Option<&'static str> { @@ -154,11 +215,17 @@ impl BaseOcrConfig for AzureDocumentIntelligenceOcrConfig { fn map_ocr_params( &self, non_default_params: &CallArguments, - _model: &str, + model: &str, ) -> Result { + let output_content_format = requested_output_content_format(non_default_params)?; + let slices_markdown_pages = output_content_format == Some(OutputContentFormat::Markdown) + && response_format(non_default_params)? != OcrResponseFormat::Native + && model_id(model).is_ok_and(|id| id == MARKDOWN_MODEL_ID); Ok(DocumentIntelligenceParams { pages: normalize_pages_param(non_default_params.get("pages"))?, features: normalize_features_param(non_default_params.get("features"))?, + output_content_format, + string_index_type: slices_markdown_pages.then_some(CODE_POINT_STRING_INDEX), }) } @@ -185,7 +252,10 @@ impl BaseOcrConfig for AzureDocumentIntelligenceOcrConfig { ) -> Result { let endpoint = nonblank(request.connection.api_base.clone()) .or_else(|| nonblank(request.connection.secret(AZURE_DI_ENDPOINT_ENV))) - .ok_or_else(|| Error::Auth(litellm_auth::Error::ProviderAuthentication("Missing Azure Document Intelligence API Base - Set AZURE_DOCUMENT_INTELLIGENCE_ENDPOINT or pass api_base".into())))?; + .ok_or(Error::Auth(litellm_auth::Error::MissingApiBase { + provider: "Azure Document Intelligence", + guidance: "Set AZURE_DOCUMENT_INTELLIGENCE_ENDPOINT or pass api_base", + }))?; self.build_ocr_url( &endpoint, &request.model, @@ -256,14 +326,12 @@ fn normalize_pages_param(pages: Option<&Value>) -> Result, Error> Some(Value::Array(pages)) if pages.iter().all(Value::is_number) => pages .iter() .map(|page| { - let page = page - .as_i64() - .ok_or_else(|| Error::Pages("page index is out of range".into()))?; + let page = page.as_i64().ok_or(Error::Pages(PagesFault::OutOfRange))?; if page < 0 { - return Err(Error::Pages("negative page index".into())); + return Err(Error::Pages(PagesFault::Negative)); } page.checked_add(1) - .ok_or_else(|| Error::Pages("page index is out of range".into())) + .ok_or(Error::Pages(PagesFault::OutOfRange)) }) .collect::, _>>()? .into_iter() @@ -276,7 +344,7 @@ fn normalize_pages_param(pages: Option<&Value>) -> Result, Error> token .as_str() .map(str::trim) - .ok_or_else(|| Error::Pages("expected only integers or only strings".into())) + .ok_or(Error::Pages(PagesFault::Mixed)) }) .collect::, _>>()? .join(","), @@ -286,13 +354,11 @@ fn normalize_pages_param(pages: Option<&Value>) -> Result, Error> .collect::>() .join(","), Some(_) => { - return Err(Error::Pages( - "expected an array of integers or strings, or a native page range".into(), - )); + return Err(Error::Pages(PagesFault::Shape)); } }; if !normalized.split(',').all(valid_page_token) { - return Err(Error::Pages("invalid native page range".into())); + return Err(Error::Pages(PagesFault::Range)); } Ok(Some(normalized)) } @@ -338,6 +404,36 @@ fn normalize_features_param(features: Option<&Value>) -> Result, Ok(Some(normalized.join(","))) } +fn requested_output_content_format( + params: &CallArguments, +) -> Result, Error> { + let requested = [OUTPUT_CONTENT_FORMAT_PARAM, OUTPUT_CONTENT_FORMAT_ALIAS] + .into_iter() + .filter_map(|name| params.get(name)) + .find(|format| !is_unset(format)); + match requested.map(parse_output_content_format).transpose() { + Err(Error::OutputContentFormat) if drops_unsupported_params(params) => Ok(None), + parsed => parsed, + } +} + +fn is_unset(format: &Value) -> bool { + match format { + Value::Null => true, + Value::String(format) => format.trim().is_empty(), + _ => false, + } +} + +fn parse_output_content_format(format: &Value) -> Result { + format + .as_str() + .ok_or(Error::OutputContentFormat)? + .trim() + .parse() + .map_err(|_| Error::OutputContentFormat) +} + fn build_request(document: OcrDocument) -> Result { let source = document.source(); if source.is_empty() { @@ -368,10 +464,27 @@ fn transform_completed_response( )); } let result = response.analyze_result.unwrap_or_default(); + let markdown_content = result + .content + .as_deref() + .filter(|_| { + result.content_format.as_deref() == Some(<&str>::from(OutputContentFormat::Markdown)) + && result.string_index_type.as_deref() == Some(CODE_POINT_STRING_INDEX) + && result.pages.iter().all(|page| page.spans.is_some()) + }) + .map(|content| { + CodePointText::new( + content, + result + .pages + .iter() + .flat_map(|page| page.spans.iter().flatten()), + ) + }); let pages = result .pages .into_iter() - .map(|page| transform_azure_page(page, dpi)) + .map(|page| transform_azure_page(page, markdown_content.as_ref(), dpi)) .collect::, _>>()?; let pages_processed = i64::try_from(pages.len()).map_err(|_| Error::NumericRange("pages"))?; Ok(LiteLLMOcrResponse { @@ -382,11 +495,20 @@ fn transform_completed_response( pages_processed: Some(pages_processed), ..Default::default() }), + extra_fields: result + .string_index_type + .filter(|unit| unit == CODE_POINT_STRING_INDEX) + .map(|unit| Map::from_iter([(STRING_INDEX_TYPE_FIELD.to_owned(), Value::String(unit))])) + .unwrap_or_default(), ..LiteLLMOcrResponse::new(model, pages) }) } -fn transform_azure_page(page: AzureDocumentIntelligencePage, dpi: i64) -> Result { +fn transform_azure_page( + page: AzureDocumentIntelligencePage, + markdown_content: Option<&CodePointText<'_>>, + dpi: i64, +) -> Result { let index = page .page_number .unwrap_or(1) @@ -398,12 +520,20 @@ fn transform_azure_page(page: AzureDocumentIntelligencePage, dpi: i64) -> Result page.unit.as_deref().unwrap_or("inch"), dpi, )?; - let markdown = page - .lines - .iter() - .map(|line| line.content.as_deref().unwrap_or_default()) - .collect::>() - .join("\n"); + let markdown = match markdown_content { + Some(content) => page + .spans + .iter() + .flatten() + .map(|span| content.slice(span)) + .collect::(), + None => page + .lines + .iter() + .map(|line| line.content.as_deref().unwrap_or_default()) + .collect::>() + .join("\n"), + }; Ok(OcrPage { index, markdown, @@ -412,6 +542,43 @@ fn transform_azure_page(page: AzureDocumentIntelligencePage, dpi: i64) -> Result }) } +struct CodePointText<'a> { + text: &'a str, + byte_offsets: BTreeMap, +} + +impl<'a> CodePointText<'a> { + fn new<'s>( + text: &'a str, + spans: impl Iterator, + ) -> Self { + let span_bounds = spans + .flat_map(|span| [span.offset, span.end()]) + .collect::>(); + Self { + text, + byte_offsets: text + .char_indices() + .map(|(byte_offset, _)| byte_offset) + .enumerate() + .filter(|(code_point, _)| span_bounds.contains(code_point)) + .collect(), + } + } + + fn slice(&self, span: &AzureDocumentIntelligenceSpan) -> &'a str { + let byte_offset = |code_point: usize| { + self.byte_offsets + .get(&code_point) + .copied() + .unwrap_or(self.text.len()) + }; + self.text + .get(byte_offset(span.offset)..byte_offset(span.end())) + .unwrap_or_default() + } +} + fn convert_dimensions( width: f64, height: f64, @@ -458,8 +625,14 @@ async fn read_operation_response( .and_then(|value| value.to_str().ok()) .ok_or(Error::PollLocation)? .to_string(); - let original = Url::parse(original_url).map_err(|_| Error::PollOrigin)?; - let operation = Url::parse(&location).map_err(|_| Error::PollOrigin)?; + let original = Url::parse(original_url).map_err(|source| Error::InvalidPollUrl { + url: PollUrl::Submission, + source, + })?; + let operation = Url::parse(&location).map_err(|source| Error::InvalidPollUrl { + url: PollUrl::OperationLocation, + source, + })?; if original.origin() != operation.origin() || !operation.username().is_empty() || operation.password().is_some() @@ -504,8 +677,7 @@ async fn poll_operation( let response = tokio::time::timeout_at(deadline, litellm_http::request::http_request(builder)) .await - .map_err(|_| Error::PollTimeout)? - .map_err(litellm_http::transport::Error::from)?; + .map_err(|_| Error::PollTimeout)??; let retry = response .headers() .get(reqwest::header::RETRY_AFTER) @@ -574,13 +746,21 @@ impl AzureDocumentIntelligenceOcrConfig { .features .iter() .map(|features| ("features", features.as_str())), + ) + .chain( + params + .output_content_format + .map(|format| (OUTPUT_CONTENT_FORMAT_PARAM, format.into())), + ) + .chain( + params + .string_index_type + .map(|index_type| ("stringIndexType", index_type)), ), ) .into_string() }) - .map_err(|_| Error::RequestField { - path: "api_base".into(), - }) + .map_err(|error| Error::request_field("api_base", error)) } async fn resolve_headers( @@ -623,7 +803,10 @@ impl AzureDocumentIntelligenceOcrConfig { } let token = super::super::common_utils::resolve_entra(auth, config, env_lookup) .await? - .ok_or(Error::MissingAzureDocumentIntelligenceCredentials)?; + .ok_or(Error::MissingCredential { + credential: "Azure Document Intelligence credentials", + guidance: "set AZURE_DOCUMENT_INTELLIGENCE_API_KEY or configure Entra ID", + })?; super::super::common_utils::validate_destination(connection, token.source())?; Ok( std::iter::once(("Authorization".into(), format!("Bearer {}", token.value()))) @@ -692,8 +875,12 @@ mod tests { } fn map(value: Value) -> Result { + map_for_model(value, "azure_ai/doc-intelligence/prebuilt-layout") + } + + fn map_for_model(value: Value, model: &str) -> Result { let arguments = serde_json::from_value(value).unwrap(); - AzureDocumentIntelligenceOcrConfig.map_ocr_params(&arguments, "model") + AzureDocumentIntelligenceOcrConfig.map_ocr_params(&arguments, model) } #[test] @@ -823,6 +1010,218 @@ mod tests { assert_eq!(map(json!({"features": []})).unwrap().features, None); } + #[rstest] + #[case::markdown( + json!({"outputContentFormat": "markdown"}), + Some(OutputContentFormat::Markdown), + Some("unicodeCodePoint") + )] + #[case::markdown_litellm_format( + json!({"outputContentFormat": "markdown", "req_format": "litellm"}), + Some(OutputContentFormat::Markdown), + Some("unicodeCodePoint") + )] + #[case::markdown_native_format( + json!({"outputContentFormat": "markdown", "req_format": "native"}), + Some(OutputContentFormat::Markdown), + None + )] + #[case::capitalized_markdown( + json!({"outputContentFormat": "Markdown"}), + Some(OutputContentFormat::Markdown), + Some("unicodeCodePoint") + )] + #[case::text(json!({"outputContentFormat": "text"}), Some(OutputContentFormat::Text), None)] + #[case::upper_case_text(json!({"outputContentFormat": "TEXT"}), Some(OutputContentFormat::Text), None)] + #[case::padded_markdown( + json!({"outputContentFormat": " markdown\n"}), + Some(OutputContentFormat::Markdown), + Some("unicodeCodePoint") + )] + #[case::snake_case_markdown( + json!({"output_content_format": "markdown"}), + Some(OutputContentFormat::Markdown), + Some("unicodeCodePoint") + )] + #[case::camel_case_wins_over_snake_case( + json!({"outputContentFormat": "text", "output_content_format": "markdown"}), + Some(OutputContentFormat::Text), + None + )] + #[case::empty_camel_case_falls_back_to_snake_case( + json!({"outputContentFormat": "", "output_content_format": "markdown"}), + Some(OutputContentFormat::Markdown), + Some("unicodeCodePoint") + )] + #[case::null_camel_case_falls_back_to_snake_case( + json!({"outputContentFormat": null, "output_content_format": "markdown"}), + Some(OutputContentFormat::Markdown), + Some("unicodeCodePoint") + )] + #[case::empty(json!({"outputContentFormat": ""}), None, None)] + #[case::blank(json!({"outputContentFormat": " "}), None, None)] + #[case::null(json!({"outputContentFormat": null}), None, None)] + #[case::omitted(json!({}), None, None)] + fn output_content_format_maps_to_query_fields( + #[case] options: Value, + #[case] format: Option, + #[case] string_index_type: Option<&str>, + ) { + let mapped = map(options).unwrap(); + + assert_eq!(mapped.output_content_format, format); + assert_eq!(mapped.string_index_type, string_index_type); + } + + #[rstest] + #[case::layout("azure_ai/doc-intelligence/prebuilt-layout", Some("unicodeCodePoint"))] + #[case::bare_layout("prebuilt-layout", Some("unicodeCodePoint"))] + #[case::read("azure_ai/doc-intelligence/prebuilt-read", None)] + #[case::invoice("azure_ai/doc-intelligence/prebuilt-invoice", None)] + #[case::custom("azure_ai/doc-intelligence/my-extraction-model", None)] + fn only_the_layout_model_asks_for_code_point_offsets( + #[case] model: &str, + #[case] string_index_type: Option<&str>, + ) { + let mapped = map_for_model(json!({"outputContentFormat": "markdown"}), model).unwrap(); + + assert_eq!( + mapped.output_content_format, + Some(OutputContentFormat::Markdown) + ); + assert_eq!(mapped.string_index_type, string_index_type); + } + + #[rstest] + #[case::unknown(json!({"outputContentFormat": "html"}))] + #[case::number(json!({"outputContentFormat": 1}))] + #[case::boolean(json!({"outputContentFormat": true}))] + #[case::list(json!({"outputContentFormat": ["markdown"]}))] + #[case::snake_case_unknown(json!({"output_content_format": "html"}))] + #[case::drop_params_off(json!({"outputContentFormat": "html", "drop_params": false}))] + fn invalid_output_content_format_is_a_request_error(#[case] options: Value) { + let error = map(options).unwrap_err(); + + assert!(matches!(error, Error::OutputContentFormat), "{error:?}"); + assert_eq!(error.http_status_code(), Some(400)); + } + + #[rstest] + #[case::unknown(json!({"outputContentFormat": "html", "drop_params": true, "pages": [0]}))] + #[case::number(json!({"outputContentFormat": 1, "drop_params": true, "pages": [0]}))] + #[case::snake_case_unknown( + json!({"output_content_format": "html", "drop_params": true, "pages": [0]}) + )] + fn drop_params_drops_an_invalid_output_content_format(#[case] options: Value) { + let mapped = map(options).unwrap(); + + assert_eq!(serde_json::to_value(mapped).unwrap(), json!({"pages": "1"})); + } + + #[rstest] + #[case::camel_case(json!({"outputContentFormat": "markdown", "drop_params": true}))] + #[case::snake_case(json!({"output_content_format": "markdown", "drop_params": true}))] + fn drop_params_keeps_a_valid_output_content_format(#[case] options: Value) { + let mapped = map(options).unwrap(); + + assert_eq!( + mapped.output_content_format, + Some(OutputContentFormat::Markdown) + ); + } + + fn markdown_pages(analyze_result: Value) -> Vec { + let raw = + serde_json::to_vec(&json!({"status": "succeeded", "analyzeResult": analyze_result})) + .unwrap(); + AzureDocumentIntelligenceOcrConfig + .transform_ocr_response("model", &raw, OcrResponseFormat::Litellm) + .unwrap() + .pages + .into_iter() + .map(|page| page.markdown) + .collect() + } + + #[rstest] + fn markdown_pages_are_code_point_slices_of_the_content() { + let content = "# Ünïcode क्ष\n\n\n\n## Två 🙂\n\n|a|\n\n> tail"; + let second_page_start = "# Ünïcode क्ष\n\n\n\n".chars().count(); + let pages = markdown_pages(json!({ + "content": content, + "contentFormat": "markdown", + "stringIndexType": "unicodeCodePoint", + "pages": [ + {"pageNumber": 1, "spans": [{"offset": 0, "length": second_page_start}], + "lines": [{"content": "Ünïcode क्ष"}]}, + {"pageNumber": 2, "spans": [ + {"offset": second_page_start, "length": 8}, + {"offset": second_page_start + 10, "length": 3} + ], "lines": [{"content": "Två"}]} + ] + })); + + assert_eq!( + pages, + ["# Ünïcode क्ष\n\n\n\n", "## Två 🙂|a|"] + ); + } + + #[rstest] + fn spans_past_the_content_end_are_clamped() { + let pages = markdown_pages(json!({ + "content": "ab", + "contentFormat": "markdown", + "stringIndexType": "unicodeCodePoint", + "pages": [{"spans": [{"offset": 1, "length": 9}, {"offset": 7, "length": 1}]}] + })); + + assert_eq!(pages, ["b"]); + } + + #[rstest] + #[case::text_content(json!("text"), json!("unicodeCodePoint"))] + #[case::grapheme_offsets(json!("markdown"), json!("textElements"))] + #[case::no_index_type(json!("markdown"), Value::Null)] + #[case::no_content_format(Value::Null, json!("unicodeCodePoint"))] + fn other_responses_keep_line_joined_pages( + #[case] content_format: Value, + #[case] string_index_type: Value, + ) { + let pages = markdown_pages(json!({ + "content": "# A\n\nB", + "contentFormat": content_format, + "stringIndexType": string_index_type, + "pages": [{"spans": [{"offset": 0, "length": 6}], + "lines": [{"content": "A"}, {"content": "B"}]}] + })); + + assert_eq!(pages, ["A\nB"]); + } + + #[rstest] + #[case::null_spans(json!("markdown"), json!(null))] + #[case::fractional_offset(json!("markdown"), json!([{"offset": 0.5, "length": 1}]))] + #[case::missing_length(json!("markdown"), json!([{"offset": 0}]))] + #[case::negative_offset(json!("markdown"), json!([{"offset": -1, "length": 1}]))] + #[case::text_content(json!("text"), json!([{"offset": "0", "length": 1}]))] + fn unusable_page_spans_keep_line_joined_pages( + #[case] content_format: Value, + #[case] broken_spans: Value, + ) { + let pages = markdown_pages(json!({ + "content": "# A\n\nB", + "contentFormat": content_format, + "stringIndexType": "unicodeCodePoint", + "pages": [ + {"spans": [{"offset": 0, "length": 5}], "lines": [{"content": "A"}]}, + {"spans": broken_spans, "lines": [{"content": "B"}]} + ] + })); + + assert_eq!(pages, ["A", "B"]); + } + #[tokio::test] async fn request_endpoint_cannot_receive_environment_key() { let connection = OcrConnection { @@ -842,7 +1241,7 @@ mod tests { .unwrap_err(); assert!( - error + litellm_error::Report::new(&error) .to_string() .contains("request-controlled Azure endpoint") ); diff --git a/litellm-rust/crates/llms/src/azure_ai/ocr/transformation.rs b/litellm-rust/crates/llms/src/azure_ai/ocr/transformation.rs index 83d88bbb3cb..2f7957fe56e 100644 --- a/litellm-rust/crates/llms/src/azure_ai/ocr/transformation.rs +++ b/litellm-rust/crates/llms/src/azure_ai/ocr/transformation.rs @@ -169,7 +169,10 @@ impl AzureAiOcrConfig { } let key = super::common_utils::resolve_entra(auth, config, env_lookup) .await? - .ok_or(Error::MissingAzureAiCredentials)?; + .ok_or(Error::MissingCredential { + credential: "Azure AI credentials", + guidance: "set AZURE_AI_API_KEY or configure Entra ID", + })?; super::common_utils::validate_destination(connection, key.source())?; Ok(bearer_headers(connection, key.value())) } @@ -183,9 +186,7 @@ impl AzureAiOcrConfig { ApiUrl::parse(&base) .and_then(|url| url.complete_path(&AZURE_AI_OCR_PATH)) .map(|url| url.into_string()) - .map_err(|_| Error::RequestField { - path: "api_base".into(), - }) + .map_err(|error| Error::request_field("api_base", error)) } } @@ -302,7 +303,7 @@ mod tests { .unwrap_err(); assert!( - error + litellm_error::Report::new(&error) .to_string() .contains("request-controlled Azure endpoint") ); diff --git a/litellm-rust/crates/llms/src/base_llm/base_model_iterator.rs b/litellm-rust/crates/llms/src/base_llm/base_model_iterator.rs index a283ca84089..6df321b4b16 100644 --- a/litellm-rust/crates/llms/src/base_llm/base_model_iterator.rs +++ b/litellm-rust/crates/llms/src/base_llm/base_model_iterator.rs @@ -5,6 +5,15 @@ use futures_util::{Stream, StreamExt, stream, stream::BoxStream}; pub type ByteStream = BoxStream<'static, Result>; +/// The transport error a body stream carried as an `io::Error`, however many times framing +/// wrapped it on the way. +pub(crate) fn tunnelled_http(error: &io::Error) -> Option<&litellm_http::Error> { + let inner = error.get_ref()?; + inner + .downcast_ref::() + .or_else(|| tunnelled_http(inner.downcast_ref::()?)) +} + pub trait StreamTransformer { type Input; type Output; diff --git a/litellm-rust/crates/llms/src/base_llm/chat/transformation.rs b/litellm-rust/crates/llms/src/base_llm/chat/transformation.rs index 30bff76651e..8ba4030540c 100644 --- a/litellm-rust/crates/llms/src/base_llm/chat/transformation.rs +++ b/litellm-rust/crates/llms/src/base_llm/chat/transformation.rs @@ -1,3 +1,4 @@ +use litellm_core_utils::decline::Decline; use litellm_llms_types::formats::chat_completions::{ ChatCompletionsResponse, ChatMessage, ChatMessageContent, }; @@ -29,16 +30,6 @@ const IGNORABLE_MESSAGE_FIELDS: &[&str] = &["name"]; pub use crate::base_llm::auth::{Headers, ValidatedEnvironment}; -/// Why a request cannot be served by the Rust path. -/// -/// The core declines rather than guessing: the host turns this into a -/// transparent fallback to the Python implementation, which covers the full -/// surface. Acceptance is an allowlist, so a parameter or message shape the -/// core has never seen declines by construction instead of being translated -/// wrong. -#[derive(Clone, Copy, Debug, PartialEq, Eq)] -pub struct Unsupported(pub &'static str); - pub trait BaseConfig: Sync { fn secret_names(&self) -> Vec<&'static str>; @@ -97,7 +88,7 @@ pub trait BaseConfig: Sync { &self, messages: &[ChatMessage], optional_params: &Map, - ) -> Option { + ) -> Option { unsupported_param( self.supported_openai_param_mappings(), self.config_params(), @@ -111,13 +102,13 @@ pub fn unsupported_param( supported: &'static [(&'static str, &'static str)], config: &'static [&'static str], optional_params: &Map, -) -> Option { +) -> Option { if optional_params .get(STREAM_PARAM) .and_then(Value::as_bool) .unwrap_or(false) { - return Some(Unsupported("streaming")); + return Some(Decline::new("streaming")); } optional_params .keys() @@ -128,29 +119,29 @@ pub fn unsupported_param( .any(|(_, provider_name)| *provider_name == key) && !config.contains(&key.as_str()) }) - .then_some(Unsupported("unrecognized request parameter")) + .then_some(Decline::new("unrecognized request parameter")) } /// Message shapes the core can translate faithfully: text content, either a /// plain string or a non-empty list of parts that are all /// `{"type": "text", "text": ...}`. Tool calls, tool results, and multimodal /// parts decline so Python's fuller translation handles them. -pub fn unsupported_message(message: &ChatMessage) -> Option { +pub fn unsupported_message(message: &ChatMessage) -> Option { if message .extra .keys() .any(|key| !IGNORABLE_MESSAGE_FIELDS.contains(&key.as_str())) { - return Some(Unsupported("unrecognized message field")); + return Some(Decline::new("unrecognized message field")); } if !matches!(message.role.as_str(), "system" | "user" | "assistant") { - return Some(Unsupported("unrecognized message role")); + return Some(Decline::new("unrecognized message role")); } match &message.content { - None => Some(Unsupported("message without content")), + None => Some(Decline::new("message without content")), Some(ChatMessageContent::Text(_)) => None, Some(ChatMessageContent::Parts(parts)) if parts.is_empty() => { - Some(Unsupported("message without content")) + Some(Decline::new("message without content")) } Some(ChatMessageContent::Parts(parts)) => parts .iter() @@ -159,6 +150,6 @@ pub fn unsupported_message(message: &ChatMessage) -> Option { || part.get("text").and_then(Value::as_str).is_none() || part.as_object().is_some_and(|object| object.len() != 2) }) - .then_some(Unsupported("non-text message content")), + .then_some(Decline::new("non-text message content")), } } diff --git a/litellm-rust/crates/llms/src/base_llm/messages/transformation.rs b/litellm-rust/crates/llms/src/base_llm/messages/transformation.rs index 8a88af40d6b..744ce89afdb 100644 --- a/litellm-rust/crates/llms/src/base_llm/messages/transformation.rs +++ b/litellm-rust/crates/llms/src/base_llm/messages/transformation.rs @@ -77,6 +77,15 @@ pub trait BaseMessagesConfig: Sync { headers } + fn request_body( + &self, + request: MessagesRequest, + _headers: &Headers, + _drop_params: bool, + ) -> Result { + Ok(request) + } + /// The JSON that goes on the wire, for a host whose body differs from the typed request: /// Python's configs `pop("model")` when the model is addressed by the URL. fn wire_body(&self, body: Value) -> Value { diff --git a/litellm-rust/crates/llms/src/base_llm/ocr/document.rs b/litellm-rust/crates/llms/src/base_llm/ocr/document.rs index b32ea4bf73a..898c24369c3 100644 --- a/litellm-rust/crates/llms/src/base_llm/ocr/document.rs +++ b/litellm-rust/crates/llms/src/base_llm/ocr/document.rs @@ -1,9 +1,6 @@ use base64::{Engine, engine::general_purpose::STANDARD}; use data_url::{DataUrl, DataUrlError, forgiving_base64::DecodeError, mime::Mime}; -use litellm_http::{ - media::{DownloadPolicy, Error as MediaError, MediaFetcher}, - transport::Error as TransportError, -}; +use litellm_http::media::{DownloadPolicy, MediaFetcher}; use reqwest::Url; use crate::base_llm::ocr::{ @@ -61,9 +58,7 @@ pub async fn inline_remote_document( validate_inline_document(&document)?; return Ok(document); } - let url = Url::parse(source).map_err(|_| Error::RequestField { - path: "document URL".into(), - })?; + let url = Url::parse(source).map_err(|error| Error::request_field("document URL", error))?; let downloaded = fetcher .fetch( url, @@ -74,7 +69,7 @@ pub async fn inline_remote_document( }, ) .await - .map_err(map_media_error)?; + .map_err(Error::DocumentDownload)?; let result = document.with_source(format!( "data:{};base64,{}", downloaded.content_type, @@ -84,28 +79,6 @@ pub async fn inline_remote_document( Ok(result) } -fn map_media_error(error: MediaError) -> Error { - match error { - MediaError::BlockedUrl => Error::BlockedDocumentUrl, - MediaError::DownloadDisabled => Error::DownloadDisabled, - MediaError::DownloadTooLarge => Error::DownloadTooLarge, - MediaError::TooManyRedirects => Error::TooManyRedirects, - MediaError::MissingRedirectLocation => Error::MissingRedirectLocation, - MediaError::InvalidRedirect => Error::InvalidRedirect, - MediaError::Http(status) => TransportError::Http { - status, - body: "OCR document download failed".into(), - } - .into(), - MediaError::Timeout => TransportError::Http { - status: 408, - body: "OCR document download timed out".into(), - } - .into(), - MediaError::Transport(error) => error.into(), - } -} - #[cfg(test)] mod tests { use std::collections::BTreeMap as Map; @@ -119,20 +92,17 @@ mod tests { } } - #[test] - fn decodes_data_urls_and_limits_decoded_size() { - for (source, expected) in [ - ("data:application/pdf;base64,YWJj", b"abc".as_slice()), - ("DATA:application/pdf;BASE64,YWI", b"ab".as_slice()), - ("data:,a%20b%00%FF", b"a b\0\xff".as_slice()), - ] { - let inline = InlineDocument::parse(source).unwrap().unwrap(); - assert_eq!(inline.decode(expected.len()).unwrap(), expected); - assert!(matches!( - inline.decode(expected.len() - 1), - Err(Error::InlineDocumentTooLarge) - )); - } + #[rstest::rstest] + #[case::base64("data:application/pdf;base64,YWJj", b"abc")] + #[case::uppercase_unpadded("DATA:application/pdf;BASE64,YWI", b"ab")] + #[case::percent_encoded("data:,a%20b%00%FF", b"a b\0\xff")] + fn decodes_data_urls_and_limits_decoded_size(#[case] source: &str, #[case] expected: &[u8]) { + let inline = InlineDocument::parse(source).unwrap().unwrap(); + assert_eq!(inline.decode(expected.len()).unwrap(), expected); + assert!(matches!( + inline.decode(expected.len() - 1), + Err(Error::InlineDocumentTooLarge) + )); } #[test] @@ -150,15 +120,12 @@ mod tests { ); } - #[test] - fn rejects_invalid_inline_documents() { - for source in [ - "https://example.com/document.pdf", - "data:application/pdf;base64", - "data:application/pdf;base64,INVALID!", - ] { - assert!(validate_inline_document(&document(source)).is_err()); - } + #[rstest::rstest] + #[case::remote("https://example.com/document.pdf")] + #[case::no_payload("data:application/pdf;base64")] + #[case::invalid_base64("data:application/pdf;base64,INVALID!")] + fn rejects_invalid_inline_documents(#[case] source: &str) { + assert!(validate_inline_document(&document(source)).is_err()); } #[tokio::test] @@ -190,16 +157,14 @@ mod tests { clippy::disallowed_types, reason = "the pool has no default-header setting to stand in for provider credentials" )] - let provider_http = litellm_http::Client::for_test( + let provider_http = litellm_http::Client::wrap_for_test( reqwest::Client::builder() .default_headers(provider_headers) .build() .unwrap(), ); - let client = crate::base_llm::ocr::handler::OcrClient::for_test( - provider_http, - litellm_http::Client::no_redirect_for_test(), - ); + let client = + crate::base_llm::ocr::handler::OcrClient::for_test().with_provider_http(provider_http); let converted = inline_remote_document( client.document_fetcher(), OcrDocument::ImageUrl { diff --git a/litellm-rust/crates/llms/src/base_llm/ocr/error.rs b/litellm-rust/crates/llms/src/base_llm/ocr/error.rs index 392dd56412c..e5f1c3339cf 100644 --- a/litellm-rust/crates/llms/src/base_llm/ocr/error.rs +++ b/litellm-rust/crates/llms/src/base_llm/ocr/error.rs @@ -1,79 +1,96 @@ +use std::{io, path::PathBuf, sync::Arc}; + +use litellm_core_utils::call_arguments::ArgumentError; +use litellm_error::Source; +use reqwest::header::HeaderMap; + +static NO_HEADERS: std::sync::LazyLock = std::sync::LazyLock::new(HeaderMap::new); + #[derive(Clone, Debug, thiserror::Error)] pub enum Error { #[error("upstream OCR error ({status}): {body}")] Provider { status: u16, body: String, - headers: Vec<(String, String)>, + headers: Box, }, #[error("File is empty or could not be read")] EmptyFile, - #[error("Failed to read OCR file {}: {source}", path.display())] + #[error("could not read OCR file {}", path.display())] FileRead { - path: std::path::PathBuf, + path: PathBuf, #[source] - source: std::sync::Arc, + cause: Arc, }, - #[error("OCR document preparation task failed: {0}")] - DocumentTask(#[source] std::sync::Arc), - #[error("Invalid MIME type: {0}")] + #[error("OCR document preparation task failed")] + DocumentTask(#[source] Arc), + #[error("invalid MIME type {0:?}")] InvalidMimeType(String), - #[error( - "Cohere Parse only accepts `image_url` documents; document_url and PDF inputs are not supported" - )] - CohereImageOnly, + #[error("{provider} cannot read this document - {guidance}")] + UnsupportedDocument { + provider: &'static str, + guidance: &'static str, + }, + #[error("{provider} cannot read this document: {message} - {guidance}")] + RejectedDocument { + provider: &'static str, + message: String, + guidance: &'static str, + }, #[error("Invalid `req_format`. Expected 'native' or 'litellm'.")] RequestFormat, #[error("invalid OCR request field: {path}")] - RequestField { path: String }, + RequestField { + path: String, + #[source] + cause: Option, + }, + #[error("invalid OCR optional params")] + Arguments(#[from] ArgumentError), #[error("missing required field: {0}")] MissingField(&'static str), - #[error("Document URL is required")] + #[error("document URL is required")] MissingDocumentUrl, #[error("invalid OCR document data URI")] InvalidDataUri, - #[error( - "Reducto requires a reducto:// id or a data URI; plain HTTP URLs are not supported, upload the file first" - )] - ReductoSource, #[error("inline OCR document exceeds the size limit")] InlineDocumentTooLarge, - #[error("OCR document URL is blocked by network policy")] - BlockedDocumentUrl, - #[error("OCR document downloads are disabled")] - DownloadDisabled, - #[error("OCR document download exceeds the size limit")] - DownloadTooLarge, - #[error("OCR document download exceeded the redirect limit")] - TooManyRedirects, #[error("invalid OCR pages: {0}")] - Pages(String), + Pages(PagesFault), #[error("invalid OCR features")] Features, + #[error( + "invalid OCR outputContentFormat, expected text or markdown. To drop unsupported params, set `litellm.drop_params = True`." + )] + OutputContentFormat, #[error("OCR model cannot be a dot segment")] DotModel, #[error("OCR response exceeds the size limit of {limit} bytes")] TooLarge { limit: usize }, #[error("invalid OCR response field: {path}")] - ResponseField { path: String }, + ResponseField { + path: String, + #[source] + cause: Option, + }, #[error("OCR response is missing non-empty content")] EmptyContent, - #[error("OCR document redirect is missing a location")] - MissingRedirectLocation, - #[error("OCR document redirect location is invalid")] - InvalidRedirect, #[error("OCR operation ended with status {0}")] OperationStatus(String), #[error("OCR response numeric value is out of range: {0}")] NumericRange(&'static str), #[error("OCR accepted response is missing a valid operation-location")] PollLocation, + #[error("OCR {url} is not a valid URL")] + InvalidPollUrl { + url: PollUrl, + #[source] + source: url::ParseError, + }, #[error("OCR operation-location must use the submission origin without credentials")] PollOrigin, #[error("OCR polling timed out")] PollTimeout, - #[error("unsupported by the rust path: {0}")] - Unsupported(&'static str), #[error("invalid provider: {0}")] InvalidProvider(String), #[error("invalid model: {provider} has no model {model:?} - use one of: {}", supported.join(", "))] @@ -82,108 +99,270 @@ pub enum Error { model: String, supported: &'static [&'static str], }, - #[error("invalid request: {0}")] - InvalidRequest(String), - #[error("invalid response: {0}")] - InvalidResponse(String), - #[error( - "invalid authentication configuration: Missing Azure AI credentials - set AZURE_AI_API_KEY or configure Entra ID" - )] - MissingAzureAiCredentials, - #[error( - "invalid authentication configuration: Missing Azure Document Intelligence credentials - set AZURE_DOCUMENT_INTELLIGENCE_API_KEY or configure Entra ID" - )] - MissingAzureDocumentIntelligenceCredentials, - #[error( - "Missing REDUCTO_API_KEY - set it in the environment or pass api_key to litellm.ocr()/litellm.aocr()" - )] - MissingReductoApiKey, - #[error("secret resolution failed: {0}")] - Secret(#[source] std::sync::Arc), + #[error("Missing {credential} - {guidance}")] + MissingCredential { + credential: &'static str, + guidance: &'static str, + }, + #[error("secret resolution failed")] + Secret(#[source] Arc), + #[error("the OCR host driver failed")] + Host(#[source] litellm_host::machine::MachineFault), + #[error("the OCR host call raised an exception")] + HostCall, #[error(transparent)] Auth(#[from] litellm_auth::Error), #[error(transparent)] - Transport(#[from] litellm_http::transport::Error), - #[error(transparent)] Params(#[from] litellm_core_utils::params::Error), #[error(transparent)] Headers(#[from] litellm_http::request::HeaderError), #[error(transparent)] Http(#[from] litellm_http::Error), + #[error(transparent)] + DocumentDownload(litellm_http::Error), +} + +#[derive(Clone, Copy, Debug, PartialEq, Eq, thiserror::Error)] +pub enum PagesFault { + #[error("page index is out of range")] + OutOfRange, + #[error("negative page index")] + Negative, + #[error("expected only integers or only strings")] + Mixed, + #[error("expected an array of integers or strings, or a native page range")] + Shape, + #[error("invalid native page range")] + Range, +} + +#[derive(Clone, Copy, Debug, PartialEq, Eq, thiserror::Error)] +pub enum PollUrl { + #[error("submission URL")] + Submission, + #[error("operation-location")] + OperationLocation, } impl From for Error { fn from(fault: litellm_host::machine::MachineFault) -> Self { - use litellm_host::machine::MachineFault; - Self::InvalidRequest(match fault { - MachineFault::Abandoned => "OCR host driver was abandoned".into(), - MachineFault::Protocol(message) => format!("OCR {message}"), - }) - } -} - -impl From for Error { - fn from(error: litellm_core_utils::call_arguments::ArgumentError) -> Self { - Self::RequestField { - path: format!("optional_params.{}", error.path), - } + Self::Host(fault) } } impl Error { - pub fn http_status_code(&self) -> Option { - match self { - Self::Provider { status, .. } - | Self::Transport(litellm_http::transport::Error::Http { status, .. }) => Some(*status), - error if error.is_request() => Some(400), - _ => None, + pub fn request_field( + path: impl Into, + cause: impl std::error::Error + Send + Sync + 'static, + ) -> Self { + Self::RequestField { + path: path.into(), + cause: Some(Source::new(cause)), } } - pub fn is_request(&self) -> bool { - matches!( - self, + pub fn response_field( + path: impl Into, + cause: impl std::error::Error + Send + Sync + 'static, + ) -> Self { + Self::ResponseField { + path: path.into(), + cause: Some(Source::new(cause)), + } + } + + pub fn upstream_response(&self) -> Option<(u16, &str, &HeaderMap)> { + match self { + Self::Provider { + status, + body, + headers, + } => Some((*status, body, headers)), + Self::DocumentDownload(error) => error.status().map(|status| { + let body = if error.is_timeout() { + "OCR document download timed out" + } else { + "OCR document download failed" + }; + (status, body, &*NO_HEADERS) + }), + Self::Http(error) => error + .upstream_response() + .map(|(status, body)| (status, body, &*NO_HEADERS)), Self::EmptyFile - | Self::InvalidMimeType(_) - | Self::CohereImageOnly - | Self::RequestFormat - | Self::RequestField { .. } - | Self::MissingField(_) - | Self::MissingDocumentUrl - | Self::InvalidDataUri - | Self::ReductoSource - | Self::InlineDocumentTooLarge - | Self::BlockedDocumentUrl - | Self::DownloadDisabled - | Self::DownloadTooLarge - | Self::TooManyRedirects - | Self::Pages(_) - | Self::Features - | Self::DotModel - | Self::InvalidRequest(_) - | Self::InvalidProvider(_) - | Self::InvalidModel { .. } - | Self::Params(_) - | Self::Headers(_) - | Self::Http(_) - | Self::Auth(litellm_auth::Error::MissingParam { .. }) - ) + | Self::FileRead { .. } + | Self::DocumentTask(_) + | Self::InvalidMimeType(_) + | Self::UnsupportedDocument { .. } + | Self::RejectedDocument { .. } + | Self::RequestFormat + | Self::RequestField { .. } + | Self::Arguments(_) + | Self::MissingField(_) + | Self::MissingDocumentUrl + | Self::InvalidDataUri + | Self::InlineDocumentTooLarge + | Self::Pages(_) + | Self::Features + | Self::OutputContentFormat + | Self::DotModel + | Self::TooLarge { .. } + | Self::ResponseField { .. } + | Self::EmptyContent + | Self::OperationStatus(_) + | Self::NumericRange(_) + | Self::PollLocation + | Self::InvalidPollUrl { .. } + | Self::PollOrigin + | Self::PollTimeout + | Self::InvalidProvider(_) + | Self::InvalidModel { .. } + | Self::MissingCredential { .. } + | Self::Secret(_) + | Self::Host(_) + | Self::HostCall + | Self::Auth(_) + | Self::Params(_) + | Self::Headers(_) => None, + } + } + + pub fn is_missing_credential(&self) -> bool { + match self { + Self::MissingCredential { .. } => true, + Self::Auth(error) => error.is_missing_credential(), + Self::Provider { .. } + | Self::EmptyFile + | Self::FileRead { .. } + | Self::DocumentTask(_) + | Self::InvalidMimeType(_) + | Self::UnsupportedDocument { .. } + | Self::RejectedDocument { .. } + | Self::RequestFormat + | Self::RequestField { .. } + | Self::Arguments(_) + | Self::MissingField(_) + | Self::MissingDocumentUrl + | Self::InvalidDataUri + | Self::InlineDocumentTooLarge + | Self::Pages(_) + | Self::Features + | Self::OutputContentFormat + | Self::DotModel + | Self::TooLarge { .. } + | Self::ResponseField { .. } + | Self::EmptyContent + | Self::OperationStatus(_) + | Self::NumericRange(_) + | Self::PollLocation + | Self::InvalidPollUrl { .. } + | Self::PollOrigin + | Self::PollTimeout + | Self::InvalidProvider(_) + | Self::InvalidModel { .. } + | Self::Secret(_) + | Self::Host(_) + | Self::HostCall + | Self::Params(_) + | Self::Headers(_) + | Self::Http(_) + | Self::DocumentDownload(_) => false, + } + } + + pub fn http_status_code(&self) -> Option { + if let Some((status, ..)) = self.upstream_response() { + return Some(status); + } + if let Self::Http(error) = self + && let Some(status) = error.status() + { + return Some(status); + } + self.is_request().then_some(400) + } + + pub fn is_request(&self) -> bool { + match self { + Self::EmptyFile + | Self::InvalidMimeType(_) + | Self::UnsupportedDocument { .. } + | Self::RejectedDocument { .. } + | Self::RequestFormat + | Self::RequestField { .. } + | Self::Arguments(_) + | Self::MissingField(_) + | Self::MissingDocumentUrl + | Self::InvalidDataUri + | Self::InlineDocumentTooLarge + | Self::Pages(_) + | Self::Features + | Self::OutputContentFormat + | Self::DotModel + | Self::InvalidProvider(_) + | Self::InvalidModel { .. } + | Self::Params(_) + | Self::Headers(_) => true, + Self::Auth(error) => error.is_request(), + Self::Http(error) | Self::DocumentDownload(error) => error.is_request(), + Self::Provider { .. } + | Self::FileRead { .. } + | Self::DocumentTask(_) + | Self::TooLarge { .. } + | Self::ResponseField { .. } + | Self::EmptyContent + | Self::OperationStatus(_) + | Self::NumericRange(_) + | Self::PollLocation + | Self::InvalidPollUrl { .. } + | Self::PollOrigin + | Self::PollTimeout + | Self::MissingCredential { .. } + | Self::Secret(_) + | Self::Host(_) + | Self::HostCall => false, + } } pub fn is_response(&self) -> bool { - matches!( - self, + match self { Self::TooLarge { .. } - | Self::ResponseField { .. } - | Self::EmptyContent - | Self::MissingRedirectLocation - | Self::InvalidRedirect - | Self::OperationStatus(_) - | Self::NumericRange(_) - | Self::PollLocation - | Self::PollOrigin - | Self::PollTimeout - | Self::InvalidResponse(_) - ) + | Self::ResponseField { .. } + | Self::EmptyContent + | Self::OperationStatus(_) + | Self::NumericRange(_) + | Self::PollLocation + | Self::InvalidPollUrl { .. } + | Self::PollOrigin + | Self::PollTimeout => true, + Self::Http(error) | Self::DocumentDownload(error) => error.is_response(), + Self::Provider { .. } + | Self::EmptyFile + | Self::FileRead { .. } + | Self::DocumentTask(_) + | Self::InvalidMimeType(_) + | Self::UnsupportedDocument { .. } + | Self::RejectedDocument { .. } + | Self::RequestFormat + | Self::RequestField { .. } + | Self::Arguments(_) + | Self::MissingField(_) + | Self::MissingDocumentUrl + | Self::InvalidDataUri + | Self::InlineDocumentTooLarge + | Self::Pages(_) + | Self::Features + | Self::OutputContentFormat + | Self::DotModel + | Self::InvalidProvider(_) + | Self::InvalidModel { .. } + | Self::MissingCredential { .. } + | Self::Secret(_) + | Self::Host(_) + | Self::HostCall + | Self::Auth(_) + | Self::Params(_) + | Self::Headers(_) => false, + } } } diff --git a/litellm-rust/crates/llms/src/base_llm/ocr/handler.rs b/litellm-rust/crates/llms/src/base_llm/ocr/handler.rs index 2cf955ff0c6..7bbc751c614 100644 --- a/litellm-rust/crates/llms/src/base_llm/ocr/handler.rs +++ b/litellm-rust/crates/llms/src/base_llm/ocr/handler.rs @@ -7,8 +7,8 @@ use litellm_host::interceptors::WireRequest; use litellm_http::{ Client, ClientVariant, HttpClientConfig, HttpClientPool, media::{MediaFetcher, UrlPolicy}, - outbound::{OutboundRequest, RequestSigner}, - transport, + outbound::{RequestSigner, json, signed}, + request::header_pairs, }; use serde::{Serialize, de::DeserializeOwned}; use serde_json::Value; @@ -86,21 +86,27 @@ impl OcrClient { } #[cfg(any(test, feature = "test-support"))] - pub fn for_test(provider_http: Client, no_redirect_http: Client) -> Self { + pub fn for_test() -> Self { Self { secrets: Arc::new( - litellm_secrets::source::EnvironmentSecrets::python_compatible( - provider_http.clone(), - ), + litellm_secrets::source::EnvironmentSecrets::python_compatible(Client::for_test()), ), - provider_http, - polling_http: no_redirect_http.clone(), - document_fetcher: MediaFetcher::for_test(no_redirect_http), + provider_http: Client::for_test(), + polling_http: Client::for_test(), + document_fetcher: MediaFetcher::for_test(Client::for_test()), auth: Arc::new(AuthServices::default()), settings: OcrSettings::default(), } } + #[cfg(any(test, feature = "test-support"))] + pub fn with_provider_http(self, provider_http: Client) -> Self { + Self { + provider_http, + ..self + } + } + #[cfg(any(test, feature = "test-support"))] pub fn with_settings(self, settings: OcrSettings) -> Self { Self { settings, ..self } @@ -122,29 +128,17 @@ pub async fn ocr( ) -> Result { let http = config.prepare_request(request, client, hooks).await?; let url = http.url().to_string(); - let headers = http.headers().to_vec(); - let response = http - .send(client.provider_http()) + let headers = header_pairs(http.headers()); + let response = client + .provider_http() + .execute(http) .await - .map_err(transport_error)?; + .map_err(litellm_http::Error::from)?; if !response.status().is_success() { - let headers = response - .headers() - .iter() - .filter_map(|(name, value)| { - value - .to_str() - .ok() - .map(|value| (name.to_string(), value.to_string())) - }) - .collect(); - return match read_response_bytes(response, request.connection.max_response_bytes).await { - Err(Error::Transport(transport::Error::Http { status, body })) => { - Err(config.get_error_class(body, status, headers)) - } - Err(error) => Err(error), - Ok(_) => unreachable!("non-success response produces an HTTP error"), - }; + let status = response.status().as_u16(); + let headers = response.headers().clone(); + let body = read_error_body(response, request.connection.max_response_bytes).await?; + return Err(config.get_error_class(body, status, headers)); } let context = OcrResponseContext { client, @@ -172,43 +166,41 @@ pub async fn read_response_bytes( mut response: reqwest::Response, limit: usize, ) -> Result { - let status = response.status(); - if status.is_success() - && response - .content_length() - .is_some_and(|length| length > limit as u64) + if !response.status().is_success() { + let status = response.status().as_u16(); + let headers = response.headers().clone(); + let body = read_error_body(response, limit).await?; + return Err(Error::Provider { + status, + body, + headers: Box::new(headers), + }); + } + if response + .content_length() + .is_some_and(|length| length > limit as u64) { return Err(Error::TooLarge { limit }); } let mut bytes = BytesMut::new(); - while let Some(chunk) = response.chunk().await.map_err(transport_error)? { - let remaining = limit.saturating_sub(bytes.len()); - if status.is_success() && chunk.len() > remaining { + while let Some(chunk) = response.chunk().await.map_err(litellm_http::Error::from)? { + if chunk.len() > limit.saturating_sub(bytes.len()) { return Err(Error::TooLarge { limit }); } - bytes.extend_from_slice(&chunk[..chunk.len().min(remaining)]); - if !status.is_success() && bytes.len() == limit { - break; - } - } - if !status.is_success() { - return Err(transport::Error::Http { - status: status.as_u16(), - body: String::from_utf8_lossy(&bytes).into_owned(), - } - .into()); + bytes.extend_from_slice(&chunk); } Ok(bytes.freeze()) } -pub fn transport_error(error: reqwest::Error) -> Error { - if error.is_timeout() { - return Error::Transport(transport::Error::Http { - status: 408, - body: "OCR request timed out".into(), - }); +async fn read_error_body(mut response: reqwest::Response, limit: usize) -> Result { + let mut bytes = BytesMut::new(); + while bytes.len() < limit + && let Some(chunk) = response.chunk().await.map_err(litellm_http::Error::from)? + { + let remaining = limit - bytes.len(); + bytes.extend_from_slice(&chunk[..chunk.len().min(remaining)]); } - transport::Error::from(error).into() + Ok(String::from_utf8_lossy(&bytes).into_owned()) } pub async fn transform_request_body( @@ -219,7 +211,7 @@ pub async fn transform_request_body( body: B, signer: Option<&dyn RequestSigner>, hooks: &dyn CallHooks, -) -> Result { +) -> Result { let composed = litellm_core_utils::call_arguments::compose_body( &request.optional_params, &body, @@ -232,20 +224,20 @@ pub async fn transform_request_body( if !changed.body.is_object() { return Err(Error::RequestField { path: "guardrail.body".into(), + cause: None, }); } config.validate_request_body(&changed.body)?; - let timeout = Some(request.connection.timeout); + let built = json( + url, + &changed.headers, + &changed.body, + Some(request.connection.timeout), + )?; Ok(match signer { - Some(signer) => OutboundRequest::signed_json( - url.into(), - changed.headers, - &changed.body, - timeout, - signer, - ), - None => OutboundRequest::json(url.into(), changed.headers, &changed.body, timeout), - }?) + Some(signer) => signed(built, signer)?, + None => built, + }) } fn wire_request(url: &str, headers: &[(String, String)], body: Value) -> WireRequest { @@ -261,10 +253,10 @@ pub fn build_http_request( url: String, headers: Vec<(String, String)>, body: &impl Serialize, -) -> Result { - Ok(OutboundRequest::json( - url, - headers, +) -> Result { + Ok(json( + &url, + &headers, body, Some(request.connection.timeout), )?) @@ -276,9 +268,8 @@ pub async fn guardrail_document( headers: &[(String, String)], hooks: &dyn CallHooks, ) -> Result<(OcrDocument, Vec<(String, String)>), Error> { - let body = serde_json::to_value(&request.document).map_err(|_| Error::RequestField { - path: "document".into(), - })?; + let body = serde_json::to_value(&request.document) + .map_err(|error| Error::request_field("document", error))?; let changed = hooks .before_provider_request(wire_request(url, headers, body)) .await?; @@ -292,6 +283,7 @@ pub fn body_document(body: &Value) -> Result { .and_then(Value::as_object) .ok_or_else(|| Error::RequestField { path: "body.document".into(), + cause: None, })?; let source = document .iter() @@ -311,8 +303,6 @@ mod tests { net::TcpListener, }; - use super::*; - #[rstest::rstest] #[tokio::test] async fn request_timeout_has_an_http_408_status() { @@ -322,16 +312,16 @@ mod tests { let _connection = listener.accept().await.unwrap(); tokio::time::sleep(Duration::from_secs(1)).await; }); - let error = litellm_http::Client::plain_for_test() + let error = litellm_http::Client::for_test() .get(format!("http://{address}")) .timeout(Duration::from_millis(10)) .send() .await .unwrap_err(); - assert!(matches!( - transport_error(error), - Error::Transport(transport::Error::Http { status: 408, .. }) - )); + assert_eq!( + Error::from(litellm_http::Error::from(error)).http_status_code(), + Some(408) + ); server.abort(); } @@ -347,7 +337,7 @@ mod tests { socket.write_all(response.as_bytes()).await.unwrap(); std::future::pending::<()>().await; }); - let response = litellm_http::Client::plain_for_test() + let response = litellm_http::Client::for_test() .get(format!("http://{address}")) .send() .await @@ -402,10 +392,7 @@ mod tests { .await .unwrap_err(); - let Error::Transport(litellm_http::transport::Error::Http { status, body }) = error else { - panic!("unexpected error: {error}"); - }; - assert_eq!(status, 429); - assert_eq!(body, prefix); + let (status, body, _) = error.upstream_response().expect("the provider answered"); + assert_eq!((status, body), (429, prefix.as_str())); } } diff --git a/litellm-rust/crates/llms/src/base_llm/ocr/transformation.rs b/litellm-rust/crates/llms/src/base_llm/ocr/transformation.rs index 2da0e1abbfc..c90fd99809e 100644 --- a/litellm-rust/crates/llms/src/base_llm/ocr/transformation.rs +++ b/litellm-rust/crates/llms/src/base_llm/ocr/transformation.rs @@ -1,15 +1,15 @@ -use litellm_llms_types::formats::ocr::{LiteLLMOcrResponse, OcrDocument, OcrResponseFormat}; -use std::{collections::BTreeMap, future::Future, sync::Arc, time::Duration}; - -use litellm_auth::{InputSource, SecretValue, Sourced, TokenProviderHandle}; -use litellm_core_utils::{call_arguments::CallArguments, settings::ProcessEnvironment}; -use litellm_http::outbound::{OutboundRequest, RequestSigner}; -use litellm_secrets::source::Secrets; use serde::{ Serialize, de::{DeserializeOwned, IntoDeserializer}, }; use serde_json::{Map, Value}; +use std::{collections::BTreeMap, future::Future, sync::Arc, time::Duration}; + +use litellm_auth::{InputSource, SecretValue, Sourced, TokenProviderHandle}; +use litellm_core_utils::{call_arguments::CallArguments, settings::ProcessEnvironment}; +use litellm_http::outbound::RequestSigner; +use litellm_llms_types::formats::ocr::{LiteLLMOcrResponse, OcrDocument, OcrResponseFormat}; +use litellm_secrets::source::Secrets; use crate::base_llm::ocr::{ error::Error, @@ -21,6 +21,7 @@ pub const OCR_RESPONSE_MAX_BYTES: usize = 64 * 1024 * 1024; pub const OCR_INLINE_MAX_BYTES: usize = 50 * 1024 * 1024; pub const OCR_MAX_FETCH_REDIRECTS: usize = 10; pub const OCR_POLL_RETRY_SECS: u64 = 2; +pub const DROP_PARAMS_PARAM: &str = "drop_params"; #[derive(Clone, Default)] pub struct OcrCredentialInputs { @@ -185,6 +186,10 @@ pub fn response_format(optional_params: &CallArguments) -> Result bool { + optional_params.get(DROP_PARAMS_PARAM) == Some(&Value::Bool(true)) +} + #[derive(Debug)] pub struct DecodedOcrResponse { pub data: T, @@ -194,17 +199,13 @@ pub struct DecodedOcrResponse { pub fn decode_request_value(value: Value, prefix: &str) -> Result { serde_path_to_error::deserialize(value.into_deserializer()).map_err(|error| { - Error::RequestField { - path: format!("{prefix}.{}", error.path()), - } + Error::request_field(format!("{prefix}.{}", error.path()), error.into_inner()) }) } pub fn decode_response_value(value: Value, prefix: &str) -> Result { serde_path_to_error::deserialize(value.into_deserializer()).map_err(|error| { - Error::ResponseField { - path: format!("{prefix}.{}", error.path()), - } + Error::response_field(format!("{prefix}.{}", error.path()), error.into_inner()) }) } @@ -213,19 +214,15 @@ pub fn decode_response( native: bool, ) -> Result, Error> { let mut deserializer = serde_json::Deserializer::from_slice(bytes); - let data = serde_path_to_error::deserialize(&mut deserializer).map_err(|error| { - Error::ResponseField { - path: error.path().to_string(), - } - })?; - deserializer.end().map_err(|_| Error::ResponseField { - path: "response".into(), - })?; + let data = serde_path_to_error::deserialize(&mut deserializer) + .map_err(|error| Error::response_field(error.path().to_string(), error.into_inner()))?; + deserializer + .end() + .map_err(|error| Error::response_field("response", error))?; let native = if native { Some( - serde_json::from_slice(bytes).map_err(|_| Error::ResponseField { - path: "response".into(), - })?, + serde_json::from_slice(bytes) + .map_err(|error| Error::response_field("response", error))?, ) } else { None @@ -369,12 +366,12 @@ pub trait BaseOcrConfig: Send + Sync + Sized + 'static { &self, error_message: String, status_code: u16, - headers: Vec<(String, String)>, + headers: reqwest::header::HeaderMap, ) -> Error { Error::Provider { status: status_code, body: error_message, - headers, + headers: Box::new(headers), } } @@ -391,7 +388,7 @@ pub trait BaseOcrConfig: Send + Sync + Sized + 'static { request: &PreparedOcrRequest, client: &OcrClient, hooks: &dyn CallHooks, - ) -> impl Future> + Send { + ) -> impl Future> + Send { async move { let params = self.map_ocr_params(&request.optional_params, &request.model)?; let environment = self.validate_environment(request, client).await?; diff --git a/litellm-rust/crates/llms/src/base_llm/sse.rs b/litellm-rust/crates/llms/src/base_llm/sse.rs index 5ff2e3adddd..23f0c1b9389 100644 --- a/litellm-rust/crates/llms/src/base_llm/sse.rs +++ b/litellm-rust/crates/llms/src/base_llm/sse.rs @@ -15,12 +15,15 @@ use bytes::Bytes; use futures_util::{StreamExt, TryStreamExt, future::ready, stream::BoxStream}; use litellm_framer::{ - frames, + SseError, frames, sse::{SseCodec, SseEvent, decode_all}, }; use serde::{Serialize, de::DeserializeOwned}; -use crate::{Error, ErrorDetail, base_llm::base_model_iterator::ByteStream}; +use crate::{ + Error, ErrorDetail, + base_llm::base_model_iterator::{ByteStream, tunnelled_http}, +}; pub type EventStream = BoxStream<'static, Result>; @@ -70,8 +73,13 @@ pub fn invalid(error: serde_json::Error) -> Error { Error::InvalidResponse(ErrorDetail::invalid("stream event", error)) } -fn framing(error: litellm_framer::SseError) -> Error { - Error::InvalidResponse(ErrorDetail::failed("stream framing", error)) +fn framing(error: SseError) -> Error { + match &error { + SseError::Body(body) if let Some(http) = tunnelled_http(body) => Error::Http(http.clone()), + SseError::Body(_) | SseError::InvalidUtf8(_) => { + Error::InvalidResponse(ErrorDetail::failed("stream framing", error)) + } + } } #[cfg(test)] @@ -94,6 +102,45 @@ mod tests { assert_eq!(is_done(&event), done); } + #[rstest] + #[tokio::test] + async fn a_transport_failure_tunnelled_through_the_body_comes_back_as_itself() { + use futures_util::StreamExt; + + let failure = litellm_http::Error::upstream(502, "gateway went away".into()); + let bytes: ByteStream = futures_util::stream::iter([ + Ok(Bytes::from_static(b"data: {}\n\n")), + Err(std::io::Error::other(failure.clone())), + ]) + .boxed(); + + let mut events = event_stream::(bytes, is_done); + assert!(events.next().await.expect("first event").is_ok()); + let error = events.next().await.expect("failure").unwrap_err(); + assert_eq!(error, Error::Http(failure)); + } + + #[rstest] + #[tokio::test] + async fn a_body_failure_that_is_not_transport_is_an_invalid_response() { + use futures_util::StreamExt; + + let bytes: ByteStream = + futures_util::stream::iter([Err(std::io::Error::other("disk full"))]).boxed(); + + let error = event_stream::(bytes, is_done) + .next() + .await + .expect("failure") + .unwrap_err(); + assert!(matches!(error, Error::InvalidResponse(_)), "{error:?}"); + assert!( + litellm_error::Report::new(&error) + .to_string() + .contains("disk full") + ); + } + #[rstest] fn the_done_frame_we_send_decodes_as_a_control_frame() { let events: Vec = decode(DONE_FRAME, is_done).unwrap(); diff --git a/litellm-rust/crates/llms/src/bedrock/audio_transcription/mod.rs b/litellm-rust/crates/llms/src/bedrock/audio_transcription/mod.rs index 61dd264336e..1c976c1f73d 100644 --- a/litellm-rust/crates/llms/src/bedrock/audio_transcription/mod.rs +++ b/litellm-rust/crates/llms/src/bedrock/audio_transcription/mod.rs @@ -6,15 +6,15 @@ use litellm_auth_aws::{ }; use litellm_core_utils::core_helpers::json_type_name; use litellm_llms_types::{ - formats::audio_transcription::AudioTranscriptionResponseData, - providers::bedrock::ConverseResponse, + formats::audio_transcription::{AudioTranscriptionResponseData, AudioTranscriptionUsage}, + providers::bedrock::{ConverseResponse, ConverseUsage}, }; use serde::Deserialize; use serde_json::{Map, Value, json}; use strum::IntoStaticStr; use crate::{ - Error, + Error, ErrorDetail, base_llm::{ audio_transcription::transformation::{ AudioTranscriptionRequestData, BaseAudioTranscriptionConfig, Headers, @@ -59,20 +59,12 @@ fn audio_fields(audio: Value) -> Result { .and_then(Value::as_str) .filter(|value| !value.is_empty()) .ok_or(Error::MissingField("audio.data"))?; - let format = object.get("format").cloned().ok_or_else(|| { - Error::InvalidRequest( - "audio.format must be wav, mp3, flac, or ogg" - .to_string() - .into(), - ) - })?; - let format: AudioFormat = serde_json::from_value(format).map_err(|_| { - Error::InvalidRequest( - "audio.format must be wav, mp3, flac, or ogg" - .to_string() - .into(), - ) - })?; + let format = object + .get("format") + .cloned() + .ok_or(Error::MissingField("audio.format"))?; + let format: AudioFormat = serde_json::from_value(format) + .map_err(|error| Error::InvalidRequest(ErrorDetail::invalid("audio.format", error)))?; Ok(AudioInput { data: data.to_string(), format, @@ -109,10 +101,10 @@ impl BaseAudioTranscriptionConfig for BedrockAudioTranscriptionConfig { if let Some(prompt) = optional_string(&optional_params, "prompt") { instruction.push_str(&format!(" Additional context: {prompt}")); } - let mut inference_config = Map::from_iter([("maxTokens".to_string(), json!(4096))]); - if let Some(temperature) = optional_params.get("temperature") { - inference_config.insert("temperature".to_string(), temperature.clone()); - } + let temperature = optional_params + .get("temperature") + .cloned() + .unwrap_or(json!(0)); Ok(AudioTranscriptionRequestData { body: json!({ "messages": [{ @@ -122,8 +114,7 @@ impl BaseAudioTranscriptionConfig for BedrockAudioTranscriptionConfig { {"text": instruction} ] }], - "system": [{"text": "You are a transcription assistant."}], - "inferenceConfig": inference_config, + "inferenceConfig": {"maxTokens": 4096, "temperature": temperature}, }), }) } @@ -133,19 +124,20 @@ impl BaseAudioTranscriptionConfig for BedrockAudioTranscriptionConfig { _model: &str, response_json: Value, ) -> Result { + let reports_usage = response_json.get("usage").is_some(); let response: ConverseResponse = serde_json::from_value(response_json).map_err(|error| { - Error::InvalidResponse(format!("invalid Converse response: {error}").into()) + Error::InvalidResponse(ErrorDetail::invalid("Converse response", error)) })?; if response.message_content_is_non_text() { - return Err(Error::InvalidResponse( - "Bedrock response contains non-text transcript content" - .to_string() - .into(), - )); + return Err(Error::InvalidResponse(ErrorDetail::Expected { + subject: "Bedrock transcript content", + expected: "text", + })); } Ok(AudioTranscriptionResponseData { text: response.content_text(), + usage: reports_usage.then(|| transcription_usage(&response.usage)), }) } @@ -200,22 +192,41 @@ impl BaseAudioTranscriptionConfig for BedrockAudioTranscriptionConfig { } } +fn transcription_usage(usage: &ConverseUsage) -> AudioTranscriptionUsage { + AudioTranscriptionUsage { + input_tokens: usage.input_tokens, + output_tokens: usage.output_tokens, + total_tokens: usage + .total_tokens + .unwrap_or(usage.input_tokens + usage.output_tokens), + } +} + #[cfg(test)] mod tests { use super::*; + use rstest::rstest; fn no_env(_: &str) -> Option { None } - #[test] - fn request_matches_python_shape() { - let params = Map::from_iter([ - ("language".to_string(), json!("en")), - ("prompt".to_string(), json!("Speaker names")), - ("temperature".to_string(), json!(0)), - ("timestamp_granularities".to_string(), json!(["word"])), - ]); + #[rstest] + #[case::caller_temperature(Some(json!(0.4)), json!(0.4))] + #[case::default_temperature(None, json!(0))] + fn request_sends_audio_and_instruction_without_system_block( + #[case] temperature: Option, + #[case] expected_temperature: Value, + ) { + let params = Map::from_iter( + [ + ("language".to_string(), json!("en")), + ("prompt".to_string(), json!("Speaker names")), + ("timestamp_granularities".to_string(), json!(["word"])), + ] + .into_iter() + .chain(temperature.map(|value| ("temperature".to_string(), value))), + ); let params = BEDROCK_AUDIO_TRANSCRIPTION_CONFIG.map_transcription_params(¶ms); let result = BEDROCK_AUDIO_TRANSCRIPTION_CONFIG .transform_audio_transcription_request( @@ -234,22 +245,39 @@ mod tests { {"text": "Transcribe the audio. Respond with only the transcript. The audio language is en. Additional context: Speaker names"} ] }], - "system": [{"text": "You are a transcription assistant."}], - "inferenceConfig": {"maxTokens": 4096, "temperature": 0} + "inferenceConfig": {"maxTokens": 4096, "temperature": expected_temperature} }) ); } - #[test] - fn response_concatenates_content_blocks() { + #[rstest] + #[case::reported_total( + json!({"inputTokens": 390, "outputTokens": 60, "totalTokens": 450}), + json!({"text": "hello world", "usage": {"type": "tokens", "input_tokens": 390, "output_tokens": 60, "total_tokens": 450}}) + )] + #[case::derived_total( + json!({"inputTokens": 1, "outputTokens": 2}), + json!({"text": "hello world", "usage": {"type": "tokens", "input_tokens": 1, "output_tokens": 2, "total_tokens": 3}}) + )] + fn response_carries_text_and_converse_usage(#[case] usage: Value, #[case] expected: Value) { let result = BEDROCK_AUDIO_TRANSCRIPTION_CONFIG .transform_audio_transcription_response( "model", - json!({"output": {"message": {"content": [{"text": "hello "}, {"text": "world"}]}}, "usage": {"inputTokens": 1, "outputTokens": 2}}), + json!({"output": {"message": {"content": [{"text": "hello "}, {"text": "world"}]}}, "usage": usage}), ) .expect("response"); - assert_eq!(result.text, "hello world"); - assert_eq!(result.into_json(), json!({"text": "hello world"})); + assert_eq!(result.into_json(), expected); + } + + #[rstest] + fn response_without_usage_reports_none() { + let result = BEDROCK_AUDIO_TRANSCRIPTION_CONFIG + .transform_audio_transcription_response( + "model", + json!({"output": {"message": {"content": [{"text": "hello"}]}}}), + ) + .expect("response"); + assert_eq!(result.into_json(), json!({"text": "hello"})); } #[test] diff --git a/litellm-rust/crates/llms/src/bedrock/chat/converse_transformation.rs b/litellm-rust/crates/llms/src/bedrock/chat/converse_transformation.rs index caa345a7024..976c9161dd2 100644 --- a/litellm-rust/crates/llms/src/bedrock/chat/converse_transformation.rs +++ b/litellm-rust/crates/llms/src/bedrock/chat/converse_transformation.rs @@ -5,6 +5,7 @@ use litellm_auth_aws::{ constants::{AWS_BEARER_TOKEN_BEDROCK, BEDROCK_RUNTIME_ENDPOINT_TEMPLATE, BEDROCK_SERVICE}, resolve_bedrock_region, }; +use litellm_core_utils::decline::Decline; use litellm_core_utils::{ core_helpers::{finish_reason_for, unix_now, usage_from_parts}, prompt_templates::factory::{Conversation, TurnRole, build_conversation}, @@ -19,14 +20,14 @@ use litellm_llms_types::{ use serde_json::{Map, Value, json}; use crate::{ - Error, + Error, ErrorDetail, base_llm::{ auth::AuthScheme, chat::{ streaming::StreamShape, transformation::{ BaseConfig, Headers, ProviderChatRequestData, ProviderChatResponseData, - Unsupported, ValidatedEnvironment, unsupported_message, unsupported_param, + ValidatedEnvironment, unsupported_message, unsupported_param, }, }, }, @@ -154,25 +155,20 @@ impl BaseConfig for AmazonConverseConfig { response: ProviderChatResponseData, ) -> Result { let body = response.body; - if !body.is_object() { - return Err(Error::InvalidResponse( - "converse response is not an object".into(), - )); - } - for field in ["output", "usage"] { - if body.get(field).is_none() { - return Err(Error::InvalidResponse( - format!("invalid Converse response: missing field `{field}`").into(), - )); - } - } + let has_usage = body.get("usage").is_some(); let response: ConverseResponse = serde_json::from_value(body).map_err(|error| { - Error::InvalidResponse(format!("invalid Converse response: {error}").into()) + Error::InvalidResponse(ErrorDetail::invalid("Converse response", error)) })?; - // The route declines tool requests, so anything other than a text block - // is something this path never asked for. Decline; the host falls back. + if !has_usage { + return Err(Error::InvalidResponse(ErrorDetail::MissingField { + subject: "Converse response", + field: "usage", + })); + } if response.message_content_is_non_text() { - return Err(Error::Unsupported("non-text response content block")); + return Err(Error::InvalidResponse(ErrorDetail::Unhandled( + "non-text response content block", + ))); } let text = response.content_text(); let computed = usage_from_parts( @@ -269,7 +265,7 @@ impl BaseConfig for AmazonConverseConfig { &self, messages: &[ChatMessage], optional_params: &Map, - ) -> Option { + ) -> Option { unsupported_param( self.supported_openai_param_mappings(), CONFIG_PARAMS, @@ -283,7 +279,7 @@ impl BaseConfig for AmazonConverseConfig { messages .iter() .any(has_blank_text) - .then_some(Unsupported("blank message text")) + .then_some(Decline::new("blank message text")) }) // Converse has no assistant prefill: Python inserts a continue turn // when a conversation opens or closes on an assistant message, and @@ -296,7 +292,7 @@ impl BaseConfig for AmazonConverseConfig { .turns .last() .is_some_and(|turn| turn.role == TurnRole::Assistant); - (!conversation.opens_on_user_turn() || ends_on_assistant).then_some(Unsupported( + (!conversation.opens_on_user_turn() || ends_on_assistant).then_some(Decline::new( "conversation does not run user turn to user turn", )) }) @@ -358,11 +354,12 @@ mod tests { Error, base_llm::{ auth::AuthScheme, - chat::transformation::{BaseConfig, ProviderChatResponseData, Unsupported}, + chat::transformation::{BaseConfig, ProviderChatResponseData}, }, bedrock::chat::converse_transformation::BEDROCK_CHAT_COMPLETIONS_CONFIG, }; use litellm_auth::CredentialPlacement; + use litellm_core_utils::decline::Decline; use litellm_llms_types::formats::chat_completions::{ChatCompletionsResponse, ChatMessage}; use rstest::rstest; use serde_json::{Map, Value, json}; @@ -396,7 +393,7 @@ mod tests { ) } - fn reason(msgs: Value, opts: Value) -> Option { + fn reason(msgs: Value, opts: Value) -> Option { BEDROCK_CHAT_COMPLETIONS_CONFIG.unsupported_reason(&messages(msgs), ¶ms(opts)) } @@ -472,7 +469,7 @@ mod tests { json!([{"role": "user", "content": "hi"}]), json!({"stream": true}) ), - Some(Unsupported("streaming")) + Some(Decline::new("streaming")) ); } @@ -483,7 +480,7 @@ mod tests { json!([{"role": "user", "content": "hi"}]), json!({"topK": 40}) ), - Some(Unsupported("unrecognized request parameter")) + Some(Decline::new("unrecognized request parameter")) ); } @@ -497,7 +494,7 @@ mod tests { fn declines_tools_and_other_params_outside_the_allowlist(#[case] param: Value) { assert_eq!( reason(json!([{"role": "user", "content": "hi"}]), param.clone()), - Some(Unsupported("unrecognized request parameter")), + Some(Decline::new("unrecognized request parameter")), "expected {param} to decline" ); } @@ -514,7 +511,7 @@ mod tests { json!([{"role": "user", "content": content}, {"role": "user", "content": "hi"}]), json!({}) ), - Some(Unsupported("blank message text")), + Some(Decline::new("blank message text")), "expected blank content {content} to decline" ); } @@ -526,7 +523,7 @@ mod tests { // host before the call rather than an error after it. assert_eq!( reason(json!([{"role": "user", "content": []}]), json!({})), - Some(Unsupported("message without content")) + Some(Decline::new("message without content")) ); assert_eq!( reason( @@ -547,7 +544,7 @@ mod tests { ]), json!({}) ), - Some(Unsupported( + Some(Decline::new( "conversation does not run user turn to user turn" )) ); @@ -559,7 +556,7 @@ mod tests { ]), json!({}) ), - Some(Unsupported( + Some(Decline::new( "conversation does not run user turn to user turn" )) ); @@ -819,7 +816,7 @@ mod tests { ]}]), json!({}) ), - Some(Unsupported("non-text message content")) + Some(Decline::new("non-text message content")) ); } @@ -846,7 +843,7 @@ mod tests { } #[test] - fn declines_a_response_carrying_a_tool_use_block() { + fn a_response_carrying_a_tool_use_block_is_invalid() { let err = transform_response(json!({ "output": {"message": {"content": [ {"toolUse": {"toolUseId": "t1", "name": "f", "input": {}}} @@ -855,37 +852,32 @@ mod tests { "usage": {"inputTokens": 1, "outputTokens": 1} })) .expect_err("tool use block"); - assert_eq!(err, Error::Unsupported("non-text response content block")); - } - - #[test] - fn errors_on_a_response_missing_required_fields() { assert_eq!( - transform_response(json!("nope")).expect_err("not an object"), - Error::InvalidResponse("converse response is not an object".to_string().into()) - ); - assert_eq!( - transform_response(json!({"usage": {}})).expect_err("no output"), - Error::InvalidResponse("invalid Converse response: missing field `output`".into()) - ); - assert_eq!( - transform_response(json!({"output": {"message": {"content": []}}})) - .expect_err("no usage"), - Error::InvalidResponse("invalid Converse response: missing field `usage`".into()) + err, + Error::InvalidResponse(crate::ErrorDetail::Unhandled( + "non-text response content block" + )) ); } - #[test] - fn rejects_malformed_text_and_token_counts() { - for response in [ - json!({"output": {"message": {"content": [{"text": 123}]}}, "usage": {"inputTokens": 1, "outputTokens": 1}}), - json!({"output": {"message": {"content": [{"text": "x"}]}}, "usage": {"inputTokens": "1", "outputTokens": 1}}), - ] { - assert!(matches!( - transform_response(response), - Err(Error::InvalidResponse(message)) if message.to_string().starts_with("invalid Converse response:") - )); - } + #[rstest::rstest] + #[case::not_an_object(json!("nope"), "invalid type")] + #[case::no_output(json!({"usage": {"inputTokens": 1, "outputTokens": 1}}), "missing field `output`")] + #[case::no_usage(json!({"output": {"message": {"content": []}}}), "missing usage")] + #[case::non_string_text( + json!({"output": {"message": {"content": [{"text": 123}]}}, "usage": {"inputTokens": 1, "outputTokens": 1}}), + "invalid type" + )] + #[case::non_integer_tokens( + json!({"output": {"message": {"content": [{"text": "x"}]}}, "usage": {"inputTokens": "1", "outputTokens": 1}}), + "invalid type" + )] + fn rejects_a_malformed_response(#[case] response: Value, #[case] fact: &str) { + let error = transform_response(response).expect_err("malformed response"); + assert!(matches!(error, Error::InvalidResponse(_)), "{error:?}"); + let report = litellm_error::Report::new(&error).to_string(); + assert!(report.contains("Converse response"), "{report}"); + assert!(report.contains(fact), "{report}"); } #[test] diff --git a/litellm-rust/crates/llms/src/bedrock/chat/invoke_handler.rs b/litellm-rust/crates/llms/src/bedrock/chat/invoke_handler.rs index 878c424ae2d..15a6ff38822 100644 --- a/litellm-rust/crates/llms/src/bedrock/chat/invoke_handler.rs +++ b/litellm-rust/crates/llms/src/bedrock/chat/invoke_handler.rs @@ -2,6 +2,7 @@ use base64::Engine; use bytes::Buf; use futures_util::{Stream, StreamExt}; use litellm_framer::{ + EventStreamError, aws_event_stream::{AwsEventStreamCodec, Message}, frames, }; @@ -11,9 +12,8 @@ use serde_json::Value; use crate::{ Error, - anthropic::chat::handler::ModelResponseIterator, base_llm::{ - chat::streaming::{ChatStream, StreamShape}, + base_model_iterator::tunnelled_http, messages::streaming::{ByteStream, EventStream}, }, }; @@ -47,11 +47,21 @@ where B: Buf + Send, E: std::error::Error + Send + Sync + 'static, { - frames(input, AwsEventStreamCodec).map(|message| { - decode_invoke_chunk(message.map_err(|error| { + frames(input, AwsEventStreamCodec).map(|message| decode_invoke_chunk(message.map_err(framing)?)) +} + +fn framing(error: EventStreamError) -> Error { + match &error { + EventStreamError::Body(body) if let Some(http) = tunnelled_http(body) => { + Error::Http(http.clone()) + } + EventStreamError::Body(_) + | EventStreamError::InvalidLength(_) + | EventStreamError::Truncated + | EventStreamError::Malformed(_) => { Error::InvalidResponse(crate::ErrorDetail::failed("stream framing", error)) - })?) - }) + } + } } pub fn decode_invoke_anthropic_chunk(chunk: Value) -> Result { @@ -64,34 +74,6 @@ pub fn invoke_anthropic_event_stream(bytes: ByteStream) -> EventStream { Box::pin(invoke_chunk_stream(bytes).map(|chunk| decode_invoke_anthropic_chunk(chunk?))) } -#[derive(Clone, Copy, Debug, PartialEq, Eq, strum::EnumString)] -enum InvokeProvider { - #[strum(serialize = "anthropic")] - Anthropic, - #[strum(serialize = "deepseek_r1")] - DeepseekR1, - #[strum(serialize = "moonshot")] - Moonshot, - #[strum(disabled)] - Unsupported, -} - -pub fn invoke_chat_stream(invoke_provider: &str, shape: StreamShape) -> Result { - match invoke_provider - .parse() - .unwrap_or(InvokeProvider::Unsupported) - { - InvokeProvider::Anthropic => Ok(ChatStream::new( - invoke_anthropic_event_stream, - ModelResponseIterator::new(shape), - )), - InvokeProvider::DeepseekR1 | InvokeProvider::Moonshot => Err(Error::Unsupported( - "Bedrock invoke streaming for this model family", - )), - InvokeProvider::Unsupported => Err(Error::Unsupported("Bedrock invoke streaming")), - } -} - #[cfg(test)] mod tests { use aws_smithy_eventstream::frame::write_message_to; @@ -112,22 +94,6 @@ mod tests { const TEXT_DELTA: &str = r#"{"type":"content_block_delta","index":0,"delta":{"type":"text_delta","text":"hello"}}"#; - #[rstest::rstest] - #[case::anthropic("anthropic", InvokeProvider::Anthropic)] - #[case::deepseek_r1("deepseek_r1", InvokeProvider::DeepseekR1)] - #[case::moonshot("moonshot", InvokeProvider::Moonshot)] - #[case::unknown("qwen", InvokeProvider::Unsupported)] - #[case::case_sensitive("Anthropic", InvokeProvider::Unsupported)] - fn invoke_provider_maps_each_model_family_name( - #[case] name: &str, - #[case] expected: InvokeProvider, - ) { - assert_eq!( - name.parse().unwrap_or(InvokeProvider::Unsupported), - expected - ); - } - fn aws_wire(chunk: &str) -> Vec { let payload = serde_json::json!({"bytes": STANDARD.encode(chunk)}); let message = Message::new(Bytes::from(serde_json::to_vec(&payload).unwrap())).add_header( diff --git a/litellm-rust/crates/llms/src/bedrock/claude_platform/messages/transformation.rs b/litellm-rust/crates/llms/src/bedrock/claude_platform/messages/transformation.rs index 72958fd6cb9..79c30df9b19 100644 --- a/litellm-rust/crates/llms/src/bedrock/claude_platform/messages/transformation.rs +++ b/litellm-rust/crates/llms/src/bedrock/claude_platform/messages/transformation.rs @@ -1,6 +1,6 @@ use std::sync::LazyLock; -use litellm_auth::{AwsParams, CredentialPlacement, ParamSpec, SecretValue}; +use litellm_auth::{AwsParams, CredentialPlacement, ParamKind, ParamSpec, SecretValue}; use litellm_auth_aws::{AwsCredentialSource, resolve_aws_region}; use litellm_core_utils::settings::resolve_non_empty; use litellm_http::request::{header_value, with_header, without_headers}; @@ -36,6 +36,7 @@ const WORKSPACE_FIELDS: &[&str] = &[ const WORKSPACE_HEADER: &str = "anthropic-workspace-id"; static WORKSPACE: ParamSpec = ParamSpec { setting: "workspace_id", + kind: ParamKind::Setting, wire: WORKSPACE_FIELDS, module_global: None, env: WORKSPACE_ENVS, diff --git a/litellm-rust/crates/llms/src/bedrock/messages/invoke_transformations/anthropic_claude_transformation.rs b/litellm-rust/crates/llms/src/bedrock/messages/invoke_transformations/anthropic_claude_transformation.rs index 1f6b6edf28d..3ec60f12021 100644 --- a/litellm-rust/crates/llms/src/bedrock/messages/invoke_transformations/anthropic_claude_transformation.rs +++ b/litellm-rust/crates/llms/src/bedrock/messages/invoke_transformations/anthropic_claude_transformation.rs @@ -1,3 +1,4 @@ +use litellm_core_utils::decline::Decline; use std::convert::Infallible; use crate::{ @@ -130,9 +131,9 @@ impl BaseMessagesConfig for AmazonAnthropicClaudeMessagesConfig { _request: MessagesRequest, _context: &MessagesTransformContext, ) -> Result { - Err(Error::Unsupported( + Err(Error::Declined(Decline::new( "Bedrock invoke messages request shaping", - )) + ))) } fn secret_names(&self) -> &'static [&'static str] { diff --git a/litellm-rust/crates/llms/src/cohere/ocr/transformation.rs b/litellm-rust/crates/llms/src/cohere/ocr/transformation.rs index dadab413fe4..76ff27b56fc 100644 --- a/litellm-rust/crates/llms/src/cohere/ocr/transformation.rs +++ b/litellm-rust/crates/llms/src/cohere/ocr/transformation.rs @@ -195,11 +195,10 @@ impl CohereParseConfig { .and_then(env_lookup) .filter(|key| !key.trim().is_empty()) }) - .ok_or_else(|| { - Error::Auth(litellm_auth::Error::ProviderAuthentication( - "Missing COHERE_API_KEY - set it in the environment or pass api_key".into(), - )) - })?; + .ok_or(Error::Auth(litellm_auth::Error::MissingApiKey { + provider: "Cohere", + environment_variable: COHERE_API_KEY_ENV, + }))?; Ok( std::iter::once(("Authorization".into(), format!("Bearer {key}"))) .chain(connection.extra_headers.clone()) @@ -208,27 +207,28 @@ impl CohereParseConfig { } fn build_ocr_url(&self, api_base: &str) -> Result { - let parsed = reqwest::Url::parse(api_base).map_err(|_| invalid_api_base())?; + let parsed = reqwest::Url::parse(api_base) + .map_err(|error| Error::request_field("api_base", error))?; if !matches!(parsed.scheme(), "http" | "https") { return Err(invalid_api_base()); } ApiUrl::parse(api_base) .and_then(|url| url.complete_path(&["v2", "parse"])) .map(|url| url.into_string()) - .map_err(|_| invalid_api_base()) + .map_err(|error| Error::request_field("api_base", error)) } } pub fn validate_document(document: &OcrDocument) -> Result<(), Error> { let OcrDocument::ImageUrl { image_url, .. } = document else { - return Err(Error::CohereImageOnly); + return Err(image_only()); }; if image_url.is_empty() { - return Err(Error::CohereImageOnly); + return Err(image_only()); } if let Some(inline) = InlineDocument::parse(image_url)? { if !inline.mime_type().type_.eq_ignore_ascii_case("image") { - return Err(Error::CohereImageOnly); + return Err(image_only()); } inline.decode(OCR_INLINE_MAX_BYTES)?; } @@ -260,7 +260,7 @@ pub fn normalize_response( fn image_url(document: OcrDocument) -> Result { validate_document(&document)?; let OcrDocument::ImageUrl { image_url, .. } = document else { - return Err(Error::CohereImageOnly); + return Err(image_only()); }; Ok(image_url) } @@ -329,9 +329,17 @@ fn billed_pages(response: &CohereResponse) -> Option { response.meta.as_ref()?.billed_units.as_ref()?.pages } +fn image_only() -> Error { + Error::UnsupportedDocument { + provider: "Cohere Parse", + guidance: "it only accepts `image_url` documents, not document_url or PDF inputs", + } +} + fn invalid_api_base() -> Error { Error::RequestField { path: "api_base".into(), + cause: None, } } @@ -368,11 +376,14 @@ mod tests { #[test] fn options_reject_invalid_output_format() { let invalid = serde_json::from_value(json!({"output_format":"html"})).unwrap(); - assert!(matches!( - CohereParseConfig.map_ocr_params(&invalid, "parse"), - Err(Error::RequestField { path }) - if path == "optional_params.output_format" - )); + let Err(error) = CohereParseConfig.map_ocr_params(&invalid, "parse") else { + panic!("html is not a Cohere output format"); + }; + assert!(error.is_request()); + let argument = + litellm_error::find::(&error) + .expect("the argument failure is kept"); + assert_eq!(argument.path, "output_format"); } #[test] @@ -432,7 +443,7 @@ mod tests { .unwrap(); assert!(matches!( normalize_response("parse", response).unwrap_err(), - Error::ResponseField { path } + Error::ResponseField { path, .. } if path == "pages[0].markdown.images[0].image_base64" )); } @@ -657,7 +668,10 @@ mod tests { fn request_requires_image(#[case] value: Value) { assert!(matches!( validate_document(&serde_json::from_value(value).unwrap()), - Err(Error::CohereImageOnly) + Err(Error::UnsupportedDocument { + provider: "Cohere Parse", + .. + }) )); } diff --git a/litellm-rust/crates/llms/src/error.rs b/litellm-rust/crates/llms/src/error.rs index 10a4f696406..b3d1421083a 100644 --- a/litellm-rust/crates/llms/src/error.rs +++ b/litellm-rust/crates/llms/src/error.rs @@ -1,3 +1,6 @@ +use litellm_core_utils::decline::Decline; +use litellm_error::Source; + #[derive(Clone, Debug, PartialEq, Eq, thiserror::Error)] pub enum Error { #[error("expected {expected}, got {actual}")] @@ -7,31 +10,126 @@ pub enum Error { }, #[error("missing required field: {0}")] MissingField(&'static str), - #[error("invalid request: {0}")] + #[error("invalid request")] InvalidRequest(#[source] ErrorDetail), - #[error("invalid response: {0}")] + #[error("invalid response")] InvalidResponse(#[source] ErrorDetail), - #[error("unsupported: {0}")] - Unsupported(&'static str), + #[error(transparent)] + Declined(Decline), #[error(transparent)] Auth(#[from] litellm_auth::Error), + #[error(transparent)] + Http(#[from] litellm_http::Error), +} + +impl Error { + pub fn is_request(&self) -> bool { + match self { + Self::InvalidType { .. } | Self::MissingField(_) | Self::InvalidRequest(_) => true, + Self::Auth(error) => error.is_request(), + Self::Http(error) => error.is_request(), + Self::InvalidResponse(_) | Self::Declined(_) => false, + } + } + + pub fn is_response(&self) -> bool { + match self { + Self::InvalidResponse(_) => true, + Self::Http(error) => error.is_response(), + Self::InvalidType { .. } + | Self::MissingField(_) + | Self::InvalidRequest(_) + | Self::Declined(_) + | Self::Auth(_) => false, + } + } + + pub fn is_missing_credential(&self) -> bool { + match self { + Self::Auth(error) => error.is_missing_credential(), + Self::InvalidType { .. } + | Self::MissingField(_) + | Self::InvalidRequest(_) + | Self::InvalidResponse(_) + | Self::Declined(_) + | Self::Http(_) => false, + } + } + + /// A transformation runs on both sides of the send, so only the transport and credential + /// resolution, which always runs before it, can tell whether the request reached the provider. + pub fn dispatched(&self) -> bool { + match self { + Self::Http(error) => error.dispatched(), + Self::Auth(_) => false, + Self::InvalidType { .. } + | Self::MissingField(_) + | Self::InvalidRequest(_) + | Self::InvalidResponse(_) => true, + Self::Declined(_) => false, + } + } + + /// Why the transformation rejected the caller's request, rendered as Python's own + /// validation renders it, without this layer's "invalid request" prefix. + pub fn rejected_request(&self) -> Option<&(dyn std::error::Error + 'static)> { + match self { + Self::InvalidRequest(detail) => Some(detail), + Self::InvalidType { .. } | Self::MissingField(_) => Some(self), + Self::InvalidResponse(_) | Self::Declined(_) | Self::Auth(_) | Self::Http(_) => None, + } + } + + pub fn declined(&self) -> Option<&Decline> { + match self { + Self::Declined(decline) => Some(decline), + Self::InvalidType { .. } + | Self::MissingField(_) + | Self::InvalidRequest(_) + | Self::InvalidResponse(_) + | Self::Auth(_) + | Self::Http(_) => None, + } + } + + pub fn upstream_response(&self) -> Option<(u16, &str)> { + match self { + Self::Http(error) => error.upstream_response(), + Self::InvalidType { .. } + | Self::MissingField(_) + | Self::InvalidRequest(_) + | Self::InvalidResponse(_) + | Self::Declined(_) + | Self::Auth(_) => None, + } + } } #[derive(Clone, Debug, PartialEq, Eq, thiserror::Error)] pub enum ErrorDetail { - #[error("{0}")] - Message(String), - #[error("invalid {subject}: {source}")] + #[error("invalid {subject}")] Invalid { subject: &'static str, #[source] - source: ErrorSource, + cause: Source, }, - #[error("{operation} failed: {source}")] + #[error("{operation} failed")] Failed { operation: &'static str, #[source] - source: ErrorSource, + cause: Source, + }, + #[error("{route} requires at least one message")] + NoMessages { route: &'static str }, + #[error("{subject} must be {expected}")] + Expected { + subject: &'static str, + expected: &'static str, + }, + #[error("{subject} is missing {field}")] + MissingField { + subject: &'static str, + field: &'static str, }, #[error("{field} must be {expected}, got {actual}")] InvalidValue { @@ -60,12 +158,20 @@ pub enum ErrorDetail { value: String, hint: String, }, - #[error("invalid {subject} on line {line}: {source}")] + #[error( + "Missing API Base - A call is being made to LLM Provider but no api base is set either in the environment variables ({{LLM_PROVIDER}}_API_KEY) or via params" + )] + MissingApiBase, + #[error("the host call raised an exception")] + HostCall, + #[error("{0} is not handled by the rust path")] + Unhandled(&'static str), + #[error("invalid {subject} on line {line}")] InvalidLine { subject: &'static str, line: usize, #[source] - source: ErrorSource, + cause: Source, }, #[error("{operation} failed: {detail}")] RemoteFailure { @@ -77,64 +183,33 @@ pub enum ErrorDetail { impl ErrorDetail { pub fn invalid( subject: &'static str, - source: impl std::error::Error + Send + Sync + 'static, + cause: impl std::error::Error + Send + Sync + 'static, ) -> Self { Self::Invalid { subject, - source: ErrorSource::new(source), + cause: Source::new(cause), } } pub fn failed( operation: &'static str, - source: impl std::error::Error + Send + Sync + 'static, + cause: impl std::error::Error + Send + Sync + 'static, ) -> Self { Self::Failed { operation, - source: ErrorSource::new(source), + cause: Source::new(cause), + } + } + + pub fn invalid_line( + subject: &'static str, + line: usize, + cause: impl std::error::Error + Send + Sync + 'static, + ) -> Self { + Self::InvalidLine { + subject, + line, + cause: Source::new(cause), } } } - -impl From for ErrorDetail { - fn from(message: String) -> Self { - Self::Message(message) - } -} - -impl From<&str> for ErrorDetail { - fn from(message: &str) -> Self { - Self::Message(message.into()) - } -} - -#[derive(Clone, Debug)] -pub struct ErrorSource(std::sync::Arc); - -impl std::ops::Deref for ErrorSource { - type Target = dyn std::error::Error + Send + Sync; - - fn deref(&self) -> &Self::Target { - self.0.as_ref() - } -} - -impl std::fmt::Display for ErrorSource { - fn fmt(&self, formatter: &mut std::fmt::Formatter<'_>) -> std::fmt::Result { - std::fmt::Display::fmt(&self.0, formatter) - } -} - -impl ErrorSource { - pub fn new(error: impl std::error::Error + Send + Sync + 'static) -> Self { - Self(std::sync::Arc::new(error)) - } -} - -impl PartialEq for ErrorSource { - fn eq(&self, other: &Self) -> bool { - std::sync::Arc::ptr_eq(&self.0, &other.0) - } -} - -impl Eq for ErrorSource {} diff --git a/litellm-rust/crates/llms/src/lib.rs b/litellm-rust/crates/llms/src/lib.rs index eb232404d93..68e6e4010c2 100644 --- a/litellm-rust/crates/llms/src/lib.rs +++ b/litellm-rust/crates/llms/src/lib.rs @@ -17,4 +17,4 @@ pub mod reducto; pub mod tencent; pub mod vertex_ai; -pub use error::{Error, ErrorDetail, ErrorSource}; +pub use error::{Error, ErrorDetail}; diff --git a/litellm-rust/crates/llms/src/mistral/ocr/transformation.rs b/litellm-rust/crates/llms/src/mistral/ocr/transformation.rs index 29d4d5c1610..fa4e2254e86 100644 --- a/litellm-rust/crates/llms/src/mistral/ocr/transformation.rs +++ b/litellm-rust/crates/llms/src/mistral/ocr/transformation.rs @@ -171,9 +171,7 @@ impl MistralOcrConfig { ApiUrl::parse(base) .and_then(|url| url.complete_path(&["v1", "ocr"])) .map(|url| url.into_string()) - .map_err(|_| Error::RequestField { - path: "api_base".into(), - }) + .map_err(|error| Error::request_field("api_base", error)) } } @@ -186,6 +184,7 @@ pub fn normalize_response( Some(None) => { return Err(Error::ResponseField { path: "model".into(), + cause: None, }); } None => model.to_string(), @@ -231,7 +230,7 @@ mod tests { let response = serde_json::from_value(json!({"model":null})).unwrap(); assert!(matches!( normalize_response("fallback", response).unwrap_err(), - Error::ResponseField { path } if path == "model" + Error::ResponseField { path, .. } if path == "model" )); } @@ -263,7 +262,7 @@ mod tests { .unwrap_err(); assert!(matches!( error, - Error::ResponseField { path: actual } if actual == path + Error::ResponseField { path: actual, .. } if actual == path )); } diff --git a/litellm-rust/crates/llms/src/openai/responses/transformation.rs b/litellm-rust/crates/llms/src/openai/responses/transformation.rs index 99cc3559514..cf74871894b 100644 --- a/litellm-rust/crates/llms/src/openai/responses/transformation.rs +++ b/litellm-rust/crates/llms/src/openai/responses/transformation.rs @@ -6,7 +6,7 @@ use serde_json::{Map, Value}; use litellm_auth::{CredentialPlacement, SecretValue}; use crate::{ - Error, + Error, ErrorDetail, base_llm::{ auth::{AuthScheme, ValidatedEnvironment}, responses::transformation::{ @@ -180,15 +180,19 @@ pub fn responses_request( params: Map, ) -> Result { if !input.is_string() && !input.is_array() { - return Err(Error::InvalidRequest( - "responses input must be a string or an array".into(), - )); + return Err(Error::InvalidRequest(ErrorDetail::Expected { + subject: "responses input", + expected: "a string or an array", + })); } if params .get("stream") .is_some_and(|stream| !stream.is_boolean()) { - return Err(Error::InvalidRequest("stream must be a boolean".into())); + return Err(Error::InvalidRequest(ErrorDetail::Expected { + subject: "stream", + expected: "a boolean", + })); } Ok(Value::Object( params @@ -202,7 +206,9 @@ pub fn responses_request( } pub fn responses_response(body: Value) -> Result { - serde_json::from_value(body).map_err(|error| Error::InvalidResponse(error.to_string().into())) + serde_json::from_value(body).map_err(|error| { + Error::InvalidResponse(ErrorDetail::invalid("Responses API response", error)) + }) } #[cfg(test)] diff --git a/litellm-rust/crates/llms/src/openai_like/chat/transformation.rs b/litellm-rust/crates/llms/src/openai_like/chat/transformation.rs index 0a89adf90f7..e998f8785cb 100644 --- a/litellm-rust/crates/llms/src/openai_like/chat/transformation.rs +++ b/litellm-rust/crates/llms/src/openai_like/chat/transformation.rs @@ -123,9 +123,12 @@ impl BaseConfig for OpenAILikeChatConfig { ) -> Result { let mut body = response.body; sanitize_usage(&mut body); - let body = body - .as_object() - .ok_or_else(|| Error::InvalidResponse("chat response is not an object".into()))?; + let body = + body.as_object() + .ok_or(Error::InvalidResponse(crate::ErrorDetail::Expected { + subject: "chat response", + expected: "an object", + }))?; let choices = body .get("choices") @@ -243,14 +246,20 @@ fn normalize_choice(position: usize, choice: &Value) -> Result Option { + fn reason(msgs: Value, opts: Value) -> Option { OPENAI_LIKE_CHAT_COMPLETIONS_CONFIG.unsupported_reason(&messages(msgs), ¶ms(opts)) } @@ -414,9 +424,13 @@ mod tests { #[rstest] fn a_missing_api_base_is_an_error() { assert!(matches!( - OPENAI_LIKE_CHAT_COMPLETIONS_CONFIG - .get_complete_url(None, "my-model", ¶ms(json!({})), &no_env), - Err(Error::InvalidRequest(message)) if message.to_string().starts_with("Missing API Base") + OPENAI_LIKE_CHAT_COMPLETIONS_CONFIG.get_complete_url( + None, + "my-model", + ¶ms(json!({})), + &no_env + ), + Err(Error::InvalidRequest(crate::ErrorDetail::MissingApiBase)) )); } @@ -528,9 +542,7 @@ mod tests { } #[rstest] - fn a_tool_call_response_declines_instead_of_dropping_the_calls() { - // The `json_mode` rewrite needs a request flag the route does not carry, so - // a tool-call answer falls back to Python rather than losing the calls. + fn a_tool_call_response_fails_instead_of_dropping_the_calls() { assert_eq!( transform_response(json!({ "model": "m", @@ -547,12 +559,14 @@ mod tests { "finish_reason": "tool_calls", }], })), - Err(Error::Unsupported("tool call response")) + Err(Error::InvalidResponse(crate::ErrorDetail::Unhandled( + "tool call response" + ))) ); } #[rstest] - fn a_refusal_declines_instead_of_returning_an_empty_reply() { + fn a_refusal_fails_instead_of_returning_an_empty_reply() { assert_eq!( transform_response(json!({ "model": "m", @@ -561,12 +575,14 @@ mod tests { "finish_reason": "stop", }], })), - Err(Error::Unsupported("refusal response")) + Err(Error::InvalidResponse(crate::ErrorDetail::Unhandled( + "refusal response" + ))) ); } #[rstest] - fn a_non_text_response_content_declines() { + fn a_non_text_response_content_is_invalid() { assert_eq!( transform_response(json!({ "model": "m", @@ -575,7 +591,9 @@ mod tests { "finish_reason": "stop", }], })), - Err(Error::Unsupported("non-text response content")) + Err(Error::InvalidResponse(crate::ErrorDetail::Unhandled( + "non-text response content" + ))) ); } @@ -585,7 +603,7 @@ mod tests { fn declines(#[case] opts: Value, #[case] expected: &'static str) { assert_eq!( reason(json!([{"role": "user", "content": "hi"}]), opts), - Some(Unsupported(expected)) + Some(Decline::new(expected)) ); } @@ -615,7 +633,7 @@ mod tests { json!([{"role": "user", "content": "hi"}]), json!({"tools": [{"type": "function", "function": {"name": "f"}}]}), ), - Some(Unsupported("unrecognized request parameter")) + Some(Decline::new("unrecognized request parameter")) ); } } diff --git a/litellm-rust/crates/llms/src/openai_like/common_utils.rs b/litellm-rust/crates/llms/src/openai_like/common_utils.rs index b0f5adafe00..d798f851d79 100644 --- a/litellm-rust/crates/llms/src/openai_like/common_utils.rs +++ b/litellm-rust/crates/llms/src/openai_like/common_utils.rs @@ -1,7 +1,7 @@ //! Shared OpenAI-like credential and endpoint resolution, mirroring //! `litellm/llms/openai_like/common_utils.py`. -use crate::Error; +use crate::{Error, ErrorDetail}; /// `OpenAILikeChatConfig._get_openai_compatible_provider_info`: the deployment's /// `api_base` wins over `OPENAI_LIKE_API_BASE`, and the deployment key over @@ -31,12 +31,7 @@ pub fn complete_openai_like_url( env_lookup: &dyn Fn(&str) -> Option, ) -> Result { let (api_base, _) = openai_compatible_provider_info(api_base, None, env_lookup); - let api_base = api_base.ok_or_else(|| { - Error::InvalidRequest( - "Missing API Base - A call is being made to LLM Provider but no api base is set either in the environment variables ({LLM_PROVIDER}_API_KEY) or via params" - .into(), - ) - })?; + let api_base = api_base.ok_or(Error::InvalidRequest(ErrorDetail::MissingApiBase))?; if custom_endpoint { return Ok(api_base); } diff --git a/litellm-rust/crates/llms/src/reducto/ocr/transformation.rs b/litellm-rust/crates/llms/src/reducto/ocr/transformation.rs index 1979b442936..bf0ddc1c7a8 100644 --- a/litellm-rust/crates/llms/src/reducto/ocr/transformation.rs +++ b/litellm-rust/crates/llms/src/reducto/ocr/transformation.rs @@ -1,11 +1,5 @@ use std::collections::BTreeMap; -use litellm_core_utils::{ - call_arguments::{CallArguments, compose_body}, - params::OpaqueParams, - url_utils::ApiUrl, -}; -use litellm_http::outbound::OutboundRequest; use serde::{Deserialize, Deserializer, Serialize}; use serde_json::{Map, Value, json}; @@ -18,6 +12,11 @@ use crate::base_llm::ocr::{ decode_and_normalize_response, }, }; +use litellm_core_utils::{ + call_arguments::{CallArguments, compose_body}, + params::OpaqueParams, + url_utils::ApiUrl, +}; use litellm_llms_types::formats::ocr::{ LiteLLMOcrResponse, OcrDocument, OcrPage, OcrResponseFormat, OcrUsageInfo, }; @@ -173,7 +172,7 @@ impl BaseOcrConfig for ReductoParseV3Config { request: &PreparedOcrRequest, client: &OcrClient, hooks: &dyn CallHooks, - ) -> Result { + ) -> Result { prepare_upload_request(self, request, client, hooks).await } } @@ -262,7 +261,7 @@ impl BaseOcrConfig for ReductoParseLegacyConfig { request: &PreparedOcrRequest, client: &OcrClient, hooks: &dyn CallHooks, - ) -> Result { + ) -> Result { prepare_upload_request(self, request, client, hooks).await } } @@ -275,7 +274,7 @@ async fn prepare_upload_request, -) -> Result { +) -> Result { let params = config.map_ocr_params(&request.optional_params, &request.model)?; let headers = config.validate_environment(request, client).await?; let url = config.get_complete_url(request, ¶ms, &headers)?; @@ -300,9 +299,16 @@ async fn prepare_upload_request Error { + Error::UnsupportedDocument { + provider: "Reducto", + guidance: "pass a reducto:// id or a data URI, or upload the file first for plain HTTP URLs", + } +} + fn uploaded_file_id(document: OcrDocument) -> Result { if !document.source().starts_with(REDUCTO_ID_PREFIX) { - return Err(Error::ReductoSource); + return Err(unsupported_source()); } if document.source()[REDUCTO_ID_PREFIX.len()..] .trim() @@ -310,6 +316,7 @@ fn uploaded_file_id(document: OcrDocument) -> Result { { return Err(Error::RequestField { path: "document file id".into(), + cause: None, }); } Ok(ReductoFileId(document.source().into())) @@ -393,6 +400,7 @@ fn build_pages_from_reducto(chunks: Vec) -> Result, E Some(Value::String(content)) => Ok(Some(content.as_str())), Some(_) => Err(Error::ResponseField { path: "result.chunks.blocks.content".into(), + cause: None, }), }) .collect::, _>>()?; @@ -437,9 +445,7 @@ fn complete_endpoint_url(api_base: Option<&str>, path: &str) -> Result( response, false, @@ -547,6 +555,7 @@ async fn upload_bytes_async( let Some(file_id) = file_id else { return Err(Error::ResponseField { path: "file_id".into(), + cause: None, }); }; Ok(ReductoFileId(file_id.to_string())) @@ -554,6 +563,8 @@ async fn upload_bytes_async( #[cfg(test)] mod tests { + use rstest::rstest; + use super::*; #[tokio::test] @@ -566,10 +577,7 @@ mod tests { let params = ReductoParseV3Config .map_ocr_params(&overrides, "parse-v3") .unwrap(); - let client = OcrClient::for_test( - litellm_http::Client::plain_for_test(), - litellm_http::Client::no_redirect_for_test(), - ); + let client = OcrClient::for_test(); let connection = OcrConnection::default(); let document = serde_json::from_value( json!({"type":"document_url","document_url":"reducto://ready.pdf"}), @@ -629,15 +637,16 @@ mod tests { ); } + #[rstest] + #[case::fractional_pages(json!({"num_pages":1.5}))] + #[case::non_numeric_pages(json!({"num_pages":[]}))] + #[case::non_numeric_credits(json!({"credits":{}}))] + fn invalid_usage_is_rejected(#[case] usage: Value) { + assert!(serde_json::from_value::(json!({"usage":usage})).is_err()); + } + #[test] - fn usage_uses_shared_validation_while_block_page_numbers_are_best_effort() { - for usage in [ - json!({"num_pages":1.5}), - json!({"num_pages":[]}), - json!({"credits":{}}), - ] { - assert!(serde_json::from_value::(json!({"usage":usage})).is_err()); - } + fn block_page_numbers_are_best_effort() { let response = serde_json::from_value(json!({"result":{"chunks":[{"blocks":[ {"content":"ignored", "bbox":{"page":"invalid"}}, {"content":"kept", "bbox":{"page":2.5}, "extra":null} diff --git a/litellm-rust/crates/llms/src/vertex_ai/messages/AGENTS.md b/litellm-rust/crates/llms/src/vertex_ai/messages/AGENTS.md index b5d637d6bc7..d95da65ac9d 100644 --- a/litellm-rust/crates/llms/src/vertex_ai/messages/AGENTS.md +++ b/litellm-rust/crates/llms/src/vertex_ai/messages/AGENTS.md @@ -1,6 +1,7 @@ # rules -- Claude on Vertex AI: reuses `anthropic/messages` shaping, moves the model into the publisher URL, puts the Vertex `anthropic_version` in the body, and authenticates with a Google access token +- Claude on Vertex AI: reuses `anthropic/messages` shaping, moves the model into the publisher URL, and authenticates with a Google access token +- Vertex reads the API version only from the body's `anthropic_version` and answers 400 when an `anthropic-version` header names a different one, so the caller's header never reaches Vertex. A version Vertex accepts in the body is carried there, `2023-06-01`, `2023-01-01`, or no header get `vertex-2023-10-16`, and any other version drops under `drop_params` and is refused without it - Applies Vertex's beta policy and strips `output_config.effort` for models that do not accept it # references diff --git a/litellm-rust/crates/llms/src/vertex_ai/messages/transformation.rs b/litellm-rust/crates/llms/src/vertex_ai/messages/transformation.rs index 2e77dbc1ca8..46e5a68dcb8 100644 --- a/litellm-rust/crates/llms/src/vertex_ai/messages/transformation.rs +++ b/litellm-rust/crates/llms/src/vertex_ai/messages/transformation.rs @@ -3,10 +3,10 @@ use litellm_auth_gcp::{ VertexConfig, get_vertex_ai_location, get_vertex_ai_project, get_vertex_ai_project_from_credentials, secret_names, }; -use litellm_http::request::has_header; +use litellm_http::request::{has_header, header_value, without_headers}; use litellm_llms_types::{ formats::messages::{MessagesOptionalParams, MessagesRequest, MessagesTool, OutputConfig}, - providers::anthropic::{AnthropicBeta, BetaProvider, BetaSet}, + providers::anthropic::{AnthropicBeta, BetaProvider, BetaSet, VERSION_HEADER}, recognized::Recognized, }; use litellm_router_types::LitellmParams; @@ -36,6 +36,8 @@ use litellm_llms_types::providers::vertex_ai::{ }; const WEB_SEARCH_TOOL_PREFIX: &str = "web_search"; +const VERSIONS_SERVED_AS_VERTEX_DEFAULT: [&str; 3] = ["", "2023-01-01", "2023-06-01"]; +const VERSIONS_VERTEX_ACCEPTS_IN_BODY: [&str; 2] = [ANTHROPIC_VERSION, "2026-10-21"]; /// Claude on Vertex AI, Python's `VertexAIPartnerModelsAnthropicMessagesConfig`: the Anthropic /// payload addressed to a project and location, authenticated with a Google access token. @@ -90,12 +92,6 @@ impl BaseMessagesConfig for VertexAiPartnerModelsAnthropicMessagesConfig { .params .output_config .and_then(|config| sanitize_output_config(config, accepts_effort)), - extra: request - .params - .extra - .into_iter() - .chain([("anthropic_version".to_string(), json!(ANTHROPIC_VERSION))]) - .collect(), ..request.params }, ..request @@ -133,7 +129,35 @@ impl BaseMessagesConfig for VertexAiPartnerModelsAnthropicMessagesConfig { } fn request_headers(&self, headers: Headers, request: &MessagesRequest) -> Headers { - merge_beta_headers(headers, vertex_feature_betas(request)) + merge_beta_headers( + without_headers(headers, &[VERSION_HEADER]), + vertex_feature_betas(request), + ) + } + + fn request_body( + &self, + request: MessagesRequest, + headers: &Headers, + drop_params: bool, + ) -> Result { + let version = vertex_version( + &request.model, + header_value(headers, VERSION_HEADER), + drop_params, + )?; + Ok(MessagesRequest { + params: MessagesOptionalParams { + extra: request + .params + .extra + .into_iter() + .chain([("anthropic_version".to_string(), json!(version))]) + .collect(), + ..request.params + }, + ..request + }) } /// Vertex addresses the model in the URL and rejects it in the body. @@ -225,6 +249,26 @@ fn vertex_feature_betas(request: &MessagesRequest) -> BetaSet { ) } +fn vertex_version<'a>( + model: &str, + requested: Option<&'a str>, + drop_params: bool, +) -> Result<&'a str, Error> { + match requested.map(str::trim).unwrap_or_default() { + version if VERSIONS_SERVED_AS_VERTEX_DEFAULT.contains(&version) => Ok(ANTHROPIC_VERSION), + version if VERSIONS_VERTEX_ACCEPTS_IN_BODY.contains(&version) => Ok(version), + _ if drop_params => Ok(ANTHROPIC_VERSION), + version => Err(Error::InvalidRequest( + crate::ErrorDetail::UnsupportedParameter { + model: model.into(), + param: VERSION_HEADER.into(), + value: version.into(), + hint: String::new(), + }, + )), + } +} + #[cfg(test)] mod tests { use rstest::rstest; @@ -471,6 +515,28 @@ mod tests { ); } + #[rstest] + #[case::sdk_spelling("anthropic-version")] + #[case::any_case("Anthropic-Version")] + fn a_forwarded_anthropic_version_never_reaches_vertex(#[case] name: &str) { + let request: MessagesRequest = serde_json::from_value(json!({ + "model": "claude-sonnet-4-5", + "max_tokens": 16, + "messages": [{"role": "user", "content": "hi"}], + })) + .unwrap(); + assert_eq!( + VERTEX_ANTHROPIC_MESSAGES_CONFIG.request_headers( + vec![ + (name.to_string(), "2026-10-21".to_string()), + ("x-request-id".to_string(), "req-1".to_string()), + ], + &request, + ), + vec![("x-request-id".to_string(), "req-1".to_string())] + ); + } + fn transformed(value: Value, context: &MessagesTransformContext) -> Value { let request: MessagesRequest = serde_json::from_value(value).unwrap(); serde_json::to_value( @@ -482,16 +548,87 @@ mod tests { } #[rstest] - fn the_body_carries_the_vertex_version_and_the_wire_drops_the_model() { - let body = transformed( - json!({ - "model": "claude-sonnet-4-5@20250929", - "max_tokens": 16, - "messages": [{"role": "user", "content": "hi"}] - }), - &MessagesTransformContext::default(), + #[case::sdk_2(&[("anthropic-version", "2026-10-21")], false, "2026-10-21")] + #[case::any_case(&[("Anthropic-Version", "2026-10-21")], false, "2026-10-21")] + #[case::vertex_name(&[("anthropic-version", "vertex-2023-10-16")], false, "vertex-2023-10-16")] + #[case::sdk_1(&[("anthropic-version", "2023-06-01")], false, "vertex-2023-10-16")] + #[case::first_version(&[("anthropic-version", "2023-01-01")], false, "vertex-2023-10-16")] + #[case::blank(&[("anthropic-version", " ")], false, "vertex-2023-10-16")] + #[case::no_header(&[], false, "vertex-2023-10-16")] + #[case::unknown_under_drop_params(&[("anthropic-version", "latest")], true, "vertex-2023-10-16")] + fn the_requested_version_goes_in_the_body( + #[case] forwarded: &[(&str, &str)], + #[case] drop_params: bool, + #[case] body_version: &str, + ) { + let request: MessagesRequest = serde_json::from_value(json!({ + "model": "claude-sonnet-4-5", + "max_tokens": 16, + "messages": [{"role": "user", "content": "hi"}], + })) + .unwrap(); + let headers: Headers = forwarded + .iter() + .map(|(name, value)| (name.to_string(), value.to_string())) + .collect(); + let body = serde_json::to_value( + VERTEX_ANTHROPIC_MESSAGES_CONFIG + .request_body(request, &headers, drop_params) + .unwrap(), + ) + .unwrap(); + assert_eq!(body["anthropic_version"], json!(body_version)); + } + + #[rstest] + #[case::unreleased("2025-01-01")] + #[case::alias("latest")] + fn an_unsupported_version_is_refused_without_drop_params(#[case] requested: &str) { + let request: MessagesRequest = serde_json::from_value(json!({ + "model": "claude-sonnet-4-5", + "max_tokens": 16, + "messages": [{"role": "user", "content": "hi"}], + })) + .unwrap(); + let headers: Headers = vec![("anthropic-version".to_string(), requested.to_string())]; + let Error::InvalidRequest(detail) = VERTEX_ANTHROPIC_MESSAGES_CONFIG + .request_body(request, &headers, false) + .unwrap_err() + else { + panic!("expected an invalid request"); + }; + assert_eq!( + detail.to_string(), + format!( + "claude-sonnet-4-5 does not support anthropic-version={requested}. \ + To drop unsupported params, set `litellm.drop_params = True`." + ) ); - assert_eq!(body["anthropic_version"], json!("vertex-2023-10-16")); + } + + #[rstest] + fn the_body_carries_the_vertex_version_and_the_wire_drops_the_model() { + let request: MessagesRequest = serde_json::from_value(json!({ + "model": "claude-sonnet-4-5@20250929", + "max_tokens": 16, + "messages": [{"role": "user", "content": "hi"}] + })) + .unwrap(); + let body = serde_json::to_value( + VERTEX_ANTHROPIC_MESSAGES_CONFIG + .request_body( + VERTEX_ANTHROPIC_MESSAGES_CONFIG + .transform_anthropic_messages_request( + request, + &MessagesTransformContext::default(), + ) + .unwrap(), + &Vec::new(), + false, + ) + .unwrap(), + ) + .unwrap(); assert_eq!(body["model"], json!("claude-sonnet-4-5@20250929")); let wire = VERTEX_ANTHROPIC_MESSAGES_CONFIG.wire_body(body); assert_eq!(wire.get("model"), None); diff --git a/litellm-rust/crates/llms/src/vertex_ai/ocr/common_utils.rs b/litellm-rust/crates/llms/src/vertex_ai/ocr/common_utils.rs index 810462c57f8..d760da9073e 100644 --- a/litellm-rust/crates/llms/src/vertex_ai/ocr/common_utils.rs +++ b/litellm-rust/crates/llms/src/vertex_ai/ocr/common_utils.rs @@ -16,7 +16,9 @@ pub(super) fn vertex_config(request: &PreparedOcrRequest) -> Result Result<(), Error> { if connection.api_base.is_some() && connection.api_base_source == InputSource::Request { return Err(litellm_auth::Error::InvalidConfiguration( - "credentials cannot be sent to a request-controlled Vertex AI endpoint".into(), + litellm_auth::ErrorDetail::RequestControlledEndpoint { + provider: "Vertex AI", + }, ) .into()); } diff --git a/litellm-rust/crates/llms/src/vertex_ai/ocr/deepseek_transformation.rs b/litellm-rust/crates/llms/src/vertex_ai/ocr/deepseek_transformation.rs index 67f9122ed67..5d680588612 100644 --- a/litellm-rust/crates/llms/src/vertex_ai/ocr/deepseek_transformation.rs +++ b/litellm-rust/crates/llms/src/vertex_ai/ocr/deepseek_transformation.rs @@ -235,8 +235,9 @@ pub fn normalize_response( &mut output, PythonJsonFormatter, )) - .map_err(|_| response_field("content"))?; - String::from_utf8(output).map_err(|_| response_field("content"))? + .map_err(|error| Error::response_field(content_path("content"), error))?; + String::from_utf8(output) + .map_err(|error| Error::response_field(content_path("content"), error))? }; (data, fallback) } @@ -261,7 +262,12 @@ pub fn normalize_response( }) }) .collect::, Error>>()?, - Some(_) => return Err(response_field("pages")), + Some(_) => { + return Err(Error::ResponseField { + path: content_path("pages"), + cause: None, + }); + } None => Vec::new(), }; let usage = ocr_data @@ -273,7 +279,12 @@ pub fn normalize_response( .transpose()?; let model = match ocr_data.get("model") { Some(Value::String(model)) => model.clone(), - Some(_) => return Err(response_field("model")), + Some(_) => { + return Err(Error::ResponseField { + path: content_path("model"), + cause: None, + }); + } None => model.to_string(), }; Ok(LiteLLMOcrResponse { @@ -369,10 +380,8 @@ impl serde_json::ser::Formatter for PythonJsonFormatter { } } -fn response_field(field: &str) -> Error { - Error::ResponseField { - path: format!("choices[0].message.content.{field}"), - } +fn content_path(field: &str) -> String { + format!("choices[0].message.content.{field}") } pub fn provider_model(model: &str) -> Result { @@ -380,6 +389,7 @@ pub fn provider_model(model: &str) -> Result { if local_model.is_empty() { return Err(Error::RequestField { path: "model".into(), + cause: None, }); } Ok(format!("{MODEL_PREFIX}{local_model}")) @@ -411,9 +421,7 @@ impl VertexAIDeepSeekOCRConfig { ]) }) .map(|url| url.into_string()) - .map_err(|_| Error::RequestField { - path: "api_base".into(), - }) + .map_err(|error| Error::request_field("api_base", error)) } } @@ -625,20 +633,18 @@ mod tests { assert_eq!(result["future"], "kept"); } - #[test] - fn response_transform_rejects_missing_empty_and_malformed_content() { - for value in [ - json!({"choices":[]}), - json!({"choices":[{"message":{"content":{}}}]}), - json!({"choices":[{"message":{"content":""}}]}), - json!({"choices":[{"message":{"content":"{\"pages\":[{\"markdown\":42}]}"}}]}), - json!({"choices":[{"message":{"content":{"pages":[{"markdown":42}]}}}]}), - ] { - let result = serde_json::from_value::(value) - .map_err(|_| ()) - .and_then(|response| normalize_response("model", response).map_err(|_| ())); - assert!(result.is_err()); - } + #[rstest::rstest] + #[case::no_choices(json!({"choices":[]}))] + #[case::empty_object(json!({"choices":[{"message":{"content":{}}}]}))] + #[case::empty_string(json!({"choices":[{"message":{"content":""}}]}))] + #[case::malformed_string(json!({"choices":[{"message":{"content":"{\"pages\":[{\"markdown\":42}]}"}}]}))] + #[case::malformed_object(json!({"choices":[{"message":{"content":{"pages":[{"markdown":42}]}}}]}))] + fn response_transform_rejects_missing_empty_and_malformed_content(#[case] value: Value) { + let rejected = match serde_json::from_value::(value) { + Ok(response) => normalize_response("model", response).is_err(), + Err(_) => true, + }; + assert!(rejected); } #[test] diff --git a/litellm-rust/crates/llms/src/vertex_ai/ocr/transformation.rs b/litellm-rust/crates/llms/src/vertex_ai/ocr/transformation.rs index ab28ee8bff4..77881cd2e78 100644 --- a/litellm-rust/crates/llms/src/vertex_ai/ocr/transformation.rs +++ b/litellm-rust/crates/llms/src/vertex_ai/ocr/transformation.rs @@ -174,9 +174,7 @@ impl VertexAiOcrConfig { ]) }) .map(|url| url.into_string()) - .map_err(|_| Error::RequestField { - path: "api_base".into(), - }) + .map_err(|error| Error::request_field("api_base", error)) } } @@ -198,6 +196,7 @@ fn validate_location(location: &str) -> Result<(), Error> { } Err(Error::RequestField { path: "vertex_location".into(), + cause: None, }) } diff --git a/litellm-rust/crates/model-catalog-refresh/Cargo.toml b/litellm-rust/crates/model-catalog-refresh/Cargo.toml new file mode 100644 index 00000000000..27219042c6c --- /dev/null +++ b/litellm-rust/crates/model-catalog-refresh/Cargo.toml @@ -0,0 +1,19 @@ +[package] +name = "litellm-model-catalog-refresh" +version = "0.1.0" +edition.workspace = true +license.workspace = true +repository.workspace = true + +[dependencies] +litellm-http.workspace = true +litellm-model-catalog.workspace = true +thiserror.workspace = true +url.workspace = true + +[dev-dependencies] +litellm-error.workspace = true +litellm-http = { workspace = true, features = ["test-support"] } +reqwest.workspace = true +rstest.workspace = true +tokio.workspace = true diff --git a/litellm-rust/crates/model-catalog-refresh/src/error.rs b/litellm-rust/crates/model-catalog-refresh/src/error.rs new file mode 100644 index 00000000000..656f32370cb --- /dev/null +++ b/litellm-rust/crates/model-catalog-refresh/src/error.rs @@ -0,0 +1,105 @@ +use std::io; + +use thiserror::Error; + +#[derive(Debug, Error)] +#[error(transparent)] +pub struct Error(Box); + +#[derive(Debug, Error)] +enum Repr { + #[error(transparent)] + Http(#[from] litellm_http::Error), + #[error("could not read the catalog")] + Read(#[source] io::Error), + #[error("invalid catalog URL")] + InvalidUrl(#[source] url::ParseError), + #[error("unsupported catalog URL scheme {scheme}")] + UnsupportedScheme { scheme: String }, +} + +impl Error { + pub fn unsupported_scheme(scheme: String) -> Self { + Self(Box::new(Repr::UnsupportedScheme { scheme })) + } +} + +impl From for Error { + fn from(cause: litellm_http::Error) -> Self { + Self(Box::new(Repr::Http(cause))) + } +} + +impl From for Error { + fn from(cause: io::Error) -> Self { + Self(Box::new(Repr::Read(cause))) + } +} + +impl From for Error { + fn from(cause: url::ParseError) -> Self { + Self(Box::new(Repr::InvalidUrl(cause))) + } +} + +#[cfg(test)] +mod tests { + use litellm_error::{Report, find}; + use rstest::rstest; + + use super::*; + use crate::{DoneReason, Reply, Step}; + + #[rstest] + fn exhausted_transport_keeps_its_typed_cause() { + let reply = Reply::Transport { + error: io::Error::from(io::ErrorKind::ConnectionReset).into(), + }; + let Reply::Transport { error } = reply else { + panic!("transport failure") + }; + let step = Step::Done { + reason: DoneReason::Exhausted(error), + }; + let Step::Done { + reason: DoneReason::Exhausted(error), + } = step + else { + panic!("exhausted attempts") + }; + let cause = find::(&error).expect("typed I/O cause"); + assert_eq!(cause.kind(), io::ErrorKind::ConnectionReset); + assert_eq!( + Report::new(&error) + .to_string() + .matches(&cause.to_string()) + .count(), + 1 + ); + assert!(!error.to_string().contains(&cause.to_string())); + } + + #[rstest] + fn invalid_source_keeps_its_typed_cause() { + let error = Error::from(url::Url::parse("http://[invalid").unwrap_err()); + assert!(find::(&error).is_some()); + } + + #[rstest] + #[tokio::test] + async fn http_failures_keep_the_cause_without_the_url() { + let cause = litellm_http::Client::for_test() + .get("http://localhost:invalid/private?api_key=secret") + .send() + .await + .unwrap_err(); + let error = Error::from(litellm_http::Error::from(cause)); + assert!(find::(&error).is_some()); + let report = Report::new(&error).to_string(); + assert!(!report.contains("secret"), "{report}"); + assert!(!report.contains("private"), "{report}"); + let debug = format!("{error:?}"); + assert!(!debug.contains("secret"), "{debug}"); + assert!(!debug.contains("private"), "{debug}"); + } +} diff --git a/litellm-rust/crates/model-catalog-refresh/src/lib.rs b/litellm-rust/crates/model-catalog-refresh/src/lib.rs new file mode 100644 index 00000000000..006c4887fad --- /dev/null +++ b/litellm-rust/crates/model-catalog-refresh/src/lib.rs @@ -0,0 +1,9 @@ +mod error; +mod policy; +mod source; +mod step; + +pub use error::Error; +pub use policy::*; +pub use source::*; +pub use step::*; diff --git a/litellm-rust/crates/model-catalog-refresh/src/policy.rs b/litellm-rust/crates/model-catalog-refresh/src/policy.rs new file mode 100644 index 00000000000..bc32e40408e --- /dev/null +++ b/litellm-rust/crates/model-catalog-refresh/src/policy.rs @@ -0,0 +1,20 @@ +use std::time::Duration; + +use litellm_model_catalog::IntegrityLimits; + +/// Main's defaults, 3 attempts, 30 s max wait, 5 s timeout, backoff base 2.0, jitter 0.0 to 1.0 s +#[derive(Clone, Copy, Debug, PartialEq)] +pub struct RetryPolicy { + pub max_attempts: u32, + pub max_wait: Duration, + pub timeout: Duration, + pub backoff_base_seconds: f64, + pub jitter_min_seconds: f64, + pub jitter_max_seconds: f64, + /// Main's 50 model floor and 0.5 shrink ratio + pub limits: IntegrityLimits, +} + +/// Main's default `LITELLM_MODEL_COST_MAP_URL` +pub const DEFAULT_REGISTRY_URL: &str = + "https://raw.githubusercontent.com/BerriAI/litellm/main/model_prices_and_context_window.json"; diff --git a/litellm-rust/crates/model-catalog-refresh/src/source.rs b/litellm-rust/crates/model-catalog-refresh/src/source.rs new file mode 100644 index 00000000000..713e0386941 --- /dev/null +++ b/litellm-rust/crates/model-catalog-refresh/src/source.rs @@ -0,0 +1,17 @@ +use std::path::PathBuf; + +use url::Url; + +/// Where a fetched catalog comes from +#[derive(Clone, Debug, PartialEq, Eq)] +pub enum Source { + Http(Url), + File(PathBuf), + S3(S3Object), +} + +#[derive(Clone, Debug, PartialEq, Eq)] +pub struct S3Object { + pub bucket: String, + pub key: String, +} diff --git a/litellm-rust/crates/model-catalog-refresh/src/step.rs b/litellm-rust/crates/model-catalog-refresh/src/step.rs new file mode 100644 index 00000000000..822d1807916 --- /dev/null +++ b/litellm-rust/crates/model-catalog-refresh/src/step.rs @@ -0,0 +1,66 @@ +use std::time::Duration; + +use litellm_model_catalog::Catalog; + +use crate::Error; +use crate::source::Source; + +/// One attempt. Where to fetch from is the `Source`, so the request carries no URL +#[derive(Clone, Debug, PartialEq, Eq)] +pub struct FetchRequest { + pub if_none_match: Option, + pub timeout: Duration, +} + +#[derive(Debug)] +pub enum Reply { + /// An HTTP, S3 or file answer. The body is read only on 200 + Response { + status: u16, + etag: Option, + retry_after: Option, + body: Option>, + }, + /// No answer reached us + Transport { error: Error }, +} + +/// What the fetch state machine asks its driver to do next +#[derive(Debug)] +pub enum Step { + Fetch(FetchRequest), + Sleep(Duration), + /// A parsed document to install, with its rejected row errors + Adopt { + catalog: Box, + installed: Installed, + errors: Vec, + }, + /// 304, a final status, or retries exhausted + Done { + reason: DoneReason, + }, +} + +#[derive(Debug)] +pub enum DoneReason { + NotModified, + Status(u16), + Exhausted(Error), +} + +/// What is installed now, the input to the next revalidation +#[derive(Clone, Debug, PartialEq, Eq)] +pub struct Installed { + pub origin: Origin, + pub etag: Option, + /// `git_blob_id` of the installed bytes + pub revision: String, + pub model_count: usize, +} + +#[derive(Clone, Debug, PartialEq, Eq)] +pub enum Origin { + Bundled, + Remote { source: Source }, +} diff --git a/litellm-rust/crates/model-catalog/AGENTS.md b/litellm-rust/crates/model-catalog/AGENTS.md index 0a380788c19..fc4b28d4ef0 100644 --- a/litellm-rust/crates/model-catalog/AGENTS.md +++ b/litellm-rust/crates/model-catalog/AGENTS.md @@ -1,5 +1,27 @@ -## Validation +## Layout -For `model_prices_and_context_window.json` validation, we should eventually: +`wire/` reads one entry as written. `EntryWire::read` makes one pass over the entry's keys and puts every non-null key in exactly one place, which is an attribute, a flat price parsed by `FlatKey::parse`, a price block, a `supports_*` capability or `unknown`. A known key with a bad value becomes an `Error` that names the key, and the rest of the entry is still read -- Stop skipping this crate's tests +`lower.rs` is the only code that knows both the wire types and `litellm-cost`. It lowers an `EntryWire` into `Prices`, `Adjustments` and `Model` and checks the rules that span keys, such as one price per meter and condition, contiguous tiers, no suffix inside a block, and off-peak needing hours and prices. Lowering only goes one way. Nothing turns `Prices` back into JSON, since the raw fields are kept + +`catalog.rs` reads the document, indexes aliases and runs the checks across entries. A bad entry keeps its raw fields and its errors are listed in `Loaded.errors`. Deciding what to do with them is the caller's job. `Catalog::written` gives back every top-level key and value as the document wrote them, in document order. `Catalog::served` gives back every model and alias as Python serves it, without `sample_spec` and `fallback_generalizations` + +`Billing` on `Prices` holds the row attributes pricing reads (text unit, band edge, cache-read fallback, wall clock, web search unit, tier scope). `lower.rs` derives it from the row and its `litellm_provider`, so `litellm-cost` holds no provider list + +`store/` is the catalog's in-memory store and the only place that indexes model names. Its rules are in [src/store/AGENTS.md](src/store/AGENTS.md) + +`layers.rs`, `resolve/`, `model_info.rs` and `register.rs` hold types only. The functions over them land with their first caller + +Catalog errors use one opaque `Error` with typed causes and JSON Pointer accessors (`path`, `key`, `field`). `Error::rejects` alone decides whether an error fails the document, rejects its row or neither, and `ErrorKind` is the stable name hosts report it by + +## Prices + +The price vocabulary lives in `litellm-cost`, and only this crate knows JSON key names. Every price is keyed by `Meter`, `Channel` and `When`. A variation only one meter has stays in the meter (cache TTL, image size, resolution, `_above_Ns_interval`, `max_results_range`). Service tier and prompt band make up `When`. Batch and decisions are a `Channel` because Python bills them with their own rules. Off-peak is an overlay on `Prices`, and regional uplifts are `Adjustments`, never prices + +A new `N`, image size or resolution in an existing key shape parses with no Rust change. A new unit, token kind, feature or tier needs a variant in `litellm-cost` plus its spelling in `wire/flat_key.rs` and `FLAT_KEY_PATTERN` in `schema.rs` + +`Prices::band` and `Prices::rate` are pinned to Python's `_get_token_base_cost` by `tests/price_lookup_reference.json`. After a billing change in Python, regenerate it from the repo root with `PYTHONPATH=. python litellm-rust/crates/model-catalog/tests/generate_price_lookup_reference.py` + +## Tests + +`BUNDLED_REGISTRY` embeds the root `model_prices_and_context_window.json`, so the tests over it fail a JSON change with a bad value or a key no type reads diff --git a/litellm-rust/crates/model-catalog/Cargo.toml b/litellm-rust/crates/model-catalog/Cargo.toml index 570e68ca4fd..45d16515dcd 100644 --- a/litellm-rust/crates/model-catalog/Cargo.toml +++ b/litellm-rust/crates/model-catalog/Cargo.toml @@ -6,18 +6,23 @@ license.workspace = true repository.workspace = true [features] -schema = ["dep:schemars", "litellm-llms-types/schema"] +schema = ["dep:schemars", "litellm-cost/schema"] [dependencies] -litellm-llms-types.workspace = true +litellm-cost = { workspace = true, features = ["serde"] } indexmap = { version = "2.14.0", features = ["serde"] } +jiff = { version = "0.2.37", default-features = false, features = ["std", "tzdb-bundle-always"] } +macro_rules_attribute.workspace = true schemars = { workspace = true, optional = true } serde.workspace = true -serde_json.workspace = true +serde_json = { workspace = true, features = ["preserve_order"] } +serde_with.workspace = true +strum.workspace = true thiserror.workspace = true time.workspace = true [dev-dependencies] jsonschema = { version = "0.55.1", default-features = false } +litellm-error.workspace = true rstest.workspace = true diff --git a/litellm-rust/crates/model-catalog/src/bundled.rs b/litellm-rust/crates/model-catalog/src/bundled.rs new file mode 100644 index 00000000000..d71a2d57ebb --- /dev/null +++ b/litellm-rust/crates/model-catalog/src/bundled.rs @@ -0,0 +1,3 @@ +/// The registry document this build serves when no other one is loaded. +pub const BUNDLED_REGISTRY: &[u8] = + include_bytes!("../../../../model_prices_and_context_window.json"); diff --git a/litellm-rust/crates/model-catalog/src/capabilities.rs b/litellm-rust/crates/model-catalog/src/capabilities.rs deleted file mode 100644 index 30724766aeb..00000000000 --- a/litellm-rust/crates/model-catalog/src/capabilities.rs +++ /dev/null @@ -1,67 +0,0 @@ -use serde::{Deserialize, Serialize}; - -/// Primary API surface / task type of the model. -#[derive(Clone, Copy, Debug, Deserialize, Eq, PartialEq, Serialize)] -#[cfg_attr(feature = "schema", derive(schemars::JsonSchema))] -#[serde(rename_all = "snake_case")] -pub enum Mode { - AudioSpeech, - AudioTranscription, - Chat, - Completion, - Decisions, - Embedding, - Evaluation, - Guardrail, - ImageEdit, - ImageGeneration, - Moderation, - Ocr, - Realtime, - Rerank, - Responses, - Search, - VectorStore, - VideoGeneration, -} - -/// Gemini audio generation API the model is served through. -#[derive(Clone, Copy, Debug, Deserialize, Eq, PartialEq, Serialize)] -#[cfg_attr(feature = "schema", derive(schemars::JsonSchema))] -#[serde(rename_all = "snake_case")] -pub enum VertexAiAudioApi { - LyriaPredict, - LyriaInteractions, -} - -/// Audio container format the model can return. -#[derive(Clone, Copy, Debug, Deserialize, Eq, PartialEq, Serialize)] -#[cfg_attr(feature = "schema", derive(schemars::JsonSchema))] -#[serde(rename_all = "snake_case")] -pub enum AudioFormat { - Mp3, - Wav, -} - -/// Input modality the model accepts. -#[derive(Clone, Copy, Debug, Deserialize, Eq, PartialEq, Serialize)] -#[cfg_attr(feature = "schema", derive(schemars::JsonSchema))] -#[serde(rename_all = "snake_case")] -pub enum InputModality { - Text, - Image, - Audio, - Video, -} - -/// Output modality the model can produce. -#[derive(Clone, Copy, Debug, Deserialize, Eq, PartialEq, Serialize)] -#[cfg_attr(feature = "schema", derive(schemars::JsonSchema))] -#[serde(rename_all = "snake_case")] -pub enum OutputModality { - Text, - Image, - Audio, - Video, - Code, -} diff --git a/litellm-rust/crates/model-catalog/src/catalog.rs b/litellm-rust/crates/model-catalog/src/catalog.rs index 0b113436a5b..ac5f4ffcf25 100644 --- a/litellm-rust/crates/model-catalog/src/catalog.rs +++ b/litellm-rust/crates/model-catalog/src/catalog.rs @@ -1,50 +1,29 @@ -use crate::error::Error; -use crate::fallback::{FallbackGeneralizations, FallbackRule}; -use crate::model_info::ModelInfo; +use std::borrow::Cow; +use std::collections::HashSet; + use indexmap::IndexMap; use serde::Deserialize; -use serde_json::{Map, Value}; -use std::collections::HashMap; +use serde_json::Value; -#[derive(Clone, Debug, Default, PartialEq, Eq)] -pub struct Provenance { - pub source: Option, - pub revision: Option, - pub etag: Option, -} +use crate::error::{Error, Loaded, Rejects, Repr}; +use crate::fallback::{FallbackGeneralizations, FallbackRule}; +use crate::model::Model; +use crate::store::{Rows, Store}; +use crate::wire::{EntryWire, Fields}; + +const SAMPLE_SPEC: &str = "sample_spec"; +const FALLBACK_GENERALIZATIONS: &str = "fallback_generalizations"; #[derive(Clone, Copy, Debug, PartialEq)] pub struct IntegrityLimits { - pub reference_model_count: usize, - pub min_model_count: usize, - pub min_reference_ratio: f64, -} - -#[derive(Clone, Debug, PartialEq, Eq)] -pub enum AliasIssue { - InvalidList { model: String }, - InvalidName { model: String }, - CanonicalCollision { model: String, alias: String }, - AliasCollision { model: String, alias: String }, + min_model_count: usize, + min_reference_ratio: f64, } #[derive(Clone, Debug)] pub struct ModelEntry { - fields: Map, - info: ModelInfo, -} - -impl ModelEntry { - pub fn field(&self, name: &str) -> Option<&Value> { - self.fields.get(name) - } - pub fn fields(&self) -> &Map { - &self.fields - } - /// The entry deserialized into the typed mirror of the catalog schema. - pub fn info(&self) -> &ModelInfo { - &self.info - } + fields: Fields, + model: Option, } #[derive(Clone, Copy, Debug)] @@ -54,142 +33,312 @@ pub struct ModelMatch<'a> { pub entry: &'a ModelEntry, } -#[derive(Debug)] +#[derive(Clone, Debug)] +struct Section { + index: usize, + key: String, + value: Value, +} + +/// One fetched key kept off the served map because its row failed validation +#[derive(Clone, Debug)] +pub struct Rejection<'a> { + pub key: String, + pub errors: Vec<&'a Error>, + /// The bundled row for the key is served instead. `false` means the key is left out + pub replaced_by_bundled: bool, +} + +#[derive(Clone, Copy, Debug, serde::Serialize)] +#[serde(untagged)] +pub enum Written<'a> { + Entry(&'a Fields), + Section(&'a Value), +} + +#[derive(Clone, Debug)] pub struct Catalog { + store: Store, + sections: Vec
, + fallback_generalizations: Option, +} + +/// Models and aliases, an alias served as its owner's row +#[derive(Clone, Debug)] +struct CatalogRows { entries: IndexMap, aliases: IndexMap, - lowercase_keys: HashMap, - sample_spec: Option, - fallback_generalizations: Option, - provenance: Provenance, - alias_issues: Vec, +} + +impl CatalogRows { + fn owner<'a>(&'a self, key: &'a str) -> &'a str { + self.aliases.get(key).map_or(key, String::as_str) + } + + fn fields(&self, key: &str) -> Option<&Fields> { + Some(self.entries.get(self.owner(key))?.fields()) + } +} + +/// Model names match ignoring case, and keys are grouped by their raw `litellm_provider` +impl Rows for CatalogRows { + type Row = Fields; + type Stamp = (); + + fn fold(name: &str) -> String { + name.to_lowercase() + } + + fn stamp(&self) -> Self::Stamp {} + + fn contains(&self, key: &str) -> bool { + self.entries.contains_key(key) || self.aliases.contains_key(key) + } + + fn row(&self, key: &str) -> Option> { + self.fields(key).map(Cow::Borrowed) + } + + fn scan(&self, visit: &mut dyn FnMut(&str, Option<&str>)) { + let keys = self.entries.keys().chain(self.aliases.keys()); + for key in keys { + let provider = self + .fields(key) + .and_then(|fields| fields.get("litellm_provider")?.as_str()); + visit(key, provider); + } + } +} + +impl IntegrityLimits { + pub fn new(min_model_count: usize, min_reference_ratio: f64) -> Option { + (0.0..=1.0).contains(&min_reference_ratio).then_some(Self { + min_model_count, + min_reference_ratio, + }) + } +} + +impl ModelEntry { + pub fn field(&self, name: &str) -> Option<&Value> { + self.fields.get(name) + } + + pub fn fields(&self) -> &Fields { + &self.fields + } + + pub fn model(&self) -> Option<&Model> { + self.model.as_ref() + } } impl Catalog { - pub fn parse(body: &[u8], provenance: Provenance) -> Result { - let root: IndexMap = serde_json::from_slice(body)?; - if root.is_empty() { - return Err(Error::Empty); - } + pub fn parse(body: &[u8]) -> Result, Error> { + let document = serde_json::from_slice::(body) + .map_err(|error| Error::new("", Repr::Json(error)))?; - let mut entries = IndexMap::with_capacity(root.len()); + let mut problems = Vec::new(); + let mut sections = Vec::new(); + let mut entries = IndexMap::with_capacity(document.len()); let mut alias_lists = Vec::new(); - let mut alias_issues = Vec::new(); - let mut sample_spec = None; - let mut fallback_generalizations = None; - for (name, value) in root { - match name.as_str() { - "sample_spec" => { - sample_spec = Some(value); + for (index, (name, value)) in document.into_iter().enumerate() { + let fields = match value { + Value::Object(fields) if !is_section(&name) => fields, + value => { + if !is_section(&name) { + problems.push(Error::from_key(&name, Repr::NotAnObject)); + } + sections.push(Section { + index, + key: name, + value, + }); continue; } - "fallback_generalizations" => { - fallback_generalizations = - Some(serde_json::from_value::(value)?); - continue; - } - _ => {} - } - let Value::Object(mut fields) = value else { - return Err(Error::EntryNotObject { model: name }); }; - let info = ModelInfo::deserialize(&fields)?; - if let Some(aliases) = fields.remove("aliases") { - match aliases { - Value::Array(names) => alias_lists.push((name.clone(), names)), - _ => alias_issues.push(AliasIssue::InvalidList { - model: name.clone(), - }), - } + let (model, aliases, row_problems) = read_row(&fields); + problems.extend( + row_problems + .into_iter() + .map(|problem| problem.prepend(&name)), + ); + if let Some(aliases) = aliases { + alias_lists.push((name.clone(), aliases)); } - entries.insert(name, ModelEntry { fields, info }); + entries.insert(name, ModelEntry { fields, model }); + } + if entries.is_empty() { + return Err(Error::new("", Repr::Empty)); } - let mut aliases = IndexMap::new(); + let mut aliases: IndexMap = IndexMap::new(); for (model, names) in alias_lists { - for name in names { - let Value::String(alias) = name else { - alias_issues.push(AliasIssue::InvalidName { - model: model.clone(), - }); - continue; - }; + for alias in names { if entries.contains_key(&alias) { - alias_issues.push(AliasIssue::CanonicalCollision { - model: model.clone(), - alias, - }); - } else if aliases.contains_key(&alias) { - alias_issues.push(AliasIssue::AliasCollision { - model: model.clone(), - alias, - }); + problems.push(Error::from_key(&model, Repr::AliasShadowsModel { alias })); + } else if let Some(taken_by) = aliases.get(&alias) { + problems.push(Error::from_key( + &model, + Repr::AliasTaken { + alias, + taken_by: taken_by.clone(), + }, + )); } else { aliases.insert(alias, model.clone()); } } } - let lowercase_keys = entries - .keys() - .chain(aliases.keys()) - .map(|key| (key.to_lowercase(), key.clone())) - .collect(); - Ok(Self { - entries, - aliases, - lowercase_keys, - sample_spec, - fallback_generalizations, - provenance, - alias_issues, + let fallback_generalizations = sections + .iter() + .find(|section| section.key == FALLBACK_GENERALIZATIONS) + .and_then(|section| { + FallbackGeneralizations::deserialize(§ion.value) + .map_err(|error| { + problems.push(Error::from_key(§ion.key, Repr::Invalid(error))) + }) + .ok() + }); + Ok(Loaded { + value: Self { + store: Store::new(CatalogRows { entries, aliases }), + sections, + fallback_generalizations, + }, + errors: problems, }) } - pub fn validate(&self, limits: IntegrityLimits) -> Result<(), Error> { - if !limits.min_reference_ratio.is_finite() - || !(0.0..=1.0).contains(&limits.min_reference_ratio) + pub fn row_errors(model: &str, fields: &Fields) -> Vec { + let (_, _, errors) = read_row(fields); + errors + .into_iter() + .map(|error| error.prepend(model)) + .collect() + } + + pub fn written(&self) -> impl Iterator)> { + let mut sections = self.sections.iter().peekable(); + let mut entries = self.rows().entries.iter(); + (0..self.rows().entries.len() + self.sections.len()).map_while(move |index| match sections + .next_if(|section| section.index == index) { - return Err(Error::InvalidRatio); - } - let actual = self.entries.len(); + Some(section) => Some((section.key.as_str(), Written::Section(§ion.value))), + None => entries + .next() + .map(|(name, entry)| (name.as_str(), Written::Entry(&entry.fields))), + }) + } + + pub fn served(&self) -> impl Iterator { + let rows = self.rows(); + rows.entries + .iter() + .map(|(name, entry)| (name.as_str(), entry.fields())) + .chain( + rows.aliases + .iter() + .map(|(alias, owner)| (alias.as_str(), rows.entries[owner].fields())), + ) + } + + pub fn check_size(&self, reference: usize, limits: IntegrityLimits) -> Result<(), Error> { + let actual = self.model_count(); if actual < limits.min_model_count { - return Err(Error::BelowMinimum { - actual, - minimum: limits.min_model_count, - }); + return Err(Error::new( + "", + Repr::BelowMinimum { + actual, + minimum: limits.min_model_count, + }, + )); } - if limits.reference_model_count > 0 - && (actual as f64) < (limits.reference_model_count as f64) * limits.min_reference_ratio - { - return Err(Error::Shrunk { - actual, - reference: limits.reference_model_count, - ratio: limits.min_reference_ratio, - }); + if (actual as f64) < (reference as f64) * limits.min_reference_ratio { + return Err(Error::new( + "", + Repr::Shrunk { + actual, + reference, + ratio: limits.min_reference_ratio, + }, + )); } Ok(()) } - pub fn lookup(&self, key: &str) -> Option> { - let matched_key = if self.entries.contains_key(key) || self.aliases.contains_key(key) { - key - } else { - self.lowercase_keys.get(&key.to_lowercase())?.as_str() - }; - let canonical_key = self - .aliases - .get(matched_key) - .map(String::as_str) - .unwrap_or(matched_key); - let (canonical_key, entry) = self.entries.get_key_value(canonical_key)?; - let matched_key = self + pub fn without_rejected(self, errors: &[Error]) -> (Self, Vec<&Error>) { + let row_names: HashSet = self + .rows() .entries - .get_key_value(matched_key) + .keys() + .cloned() + .chain( + self.sections + .iter() + .filter(|section| !is_section(§ion.key)) + .map(|section| section.key.clone()), + ) + .collect(); + let rejected: HashSet = errors + .iter() + .filter(|error| error.rejects() == Rejects::Row) + .filter_map(|error| crate::error::pointer_root(error.path())) + .filter(|root| row_names.contains(root)) + .collect(); + let removed_errors = errors + .iter() + .filter(|error| { + crate::error::pointer_root(error.path()) + .is_some_and(|root| rejected.contains(&root)) + }) + .collect(); + let removed_positions: HashSet = self + .written() + .enumerate() + .filter(|(_, (key, _))| rejected.contains(*key)) + .map(|(index, _)| index) + .collect(); + let mut catalog = self; + catalog.store.edit(|rows| { + rows.entries.retain(|name, _| !rejected.contains(name)); + rows.aliases.retain(|_, owner| !rejected.contains(owner)); + }); + catalog + .sections + .retain(|section| is_section(§ion.key) || !rejected.contains(§ion.key)); + for section in &mut catalog.sections { + let removed_before = removed_positions + .iter() + .filter(|index| **index < section.index) + .count(); + section.index -= removed_before; + } + (catalog, removed_errors) + } + + pub fn unrecognized(&self) -> impl Iterator { + self.rows().entries.iter().flat_map(|(name, entry)| { + entry + .model + .iter() + .flat_map(|model| &model.unrecognized) + .map(move |key| (name.as_str(), key.as_str())) + }) + } + + pub fn lookup(&self, key: &str) -> Option> { + let rows = self.rows(); + let found = self.store.find_key(key)?; + let (canonical_key, entry) = rows.entries.get_key_value(rows.owner(&found))?; + let matched_key = rows + .entries + .get_key_value(found.as_str()) .map(|(key, _)| key.as_str()) .or_else(|| { - self.aliases - .get_key_value(matched_key) + rows.aliases + .get_key_value(found.as_str()) .map(|(key, _)| key.as_str()) })?; Some(ModelMatch { @@ -200,30 +349,58 @@ impl Catalog { } pub fn model_count(&self) -> usize { - self.entries.len() + self.rows().entries.len() } + pub fn model_names(&self) -> impl Iterator { - self.entries.keys().map(String::as_str) - } - pub fn alias_count(&self) -> usize { - self.aliases.len() + self.rows().entries.keys().map(String::as_str) } + pub fn aliases(&self) -> &IndexMap { - &self.aliases + &self.rows().aliases } - pub fn alias_issues(&self) -> &[AliasIssue] { - &self.alias_issues + + fn rows(&self) -> &CatalogRows { + self.store.rows() } + pub fn sample_spec(&self) -> Option<&Value> { - self.sample_spec.as_ref() - } - pub fn fallback_generalizations(&self) -> Option<&FallbackGeneralizations> { - self.fallback_generalizations.as_ref() + self.sections + .iter() + .find(|section| section.key == SAMPLE_SPEC) + .map(|section| §ion.value) } + pub fn fallback_rules(&self) -> Option<&[FallbackRule]> { Some(self.fallback_generalizations.as_ref()?.rules.as_slice()) } - pub fn provenance(&self) -> &Provenance { - &self.provenance +} + +fn read_row(fields: &Fields) -> (Option, Option>, Vec) { + let wire = EntryWire::read(fields); + let aliases = wire.attributes.aliases.clone(); + let timezone_error = unknown_timezone(&wire); + match Model::try_from(wire) { + Ok(model) => (Some(model), aliases, timezone_error.into_iter().collect()), + Err(mut errors) => { + errors.extend(timezone_error); + (None, aliases, errors) + } } } + +fn is_section(key: &str) -> bool { + key == SAMPLE_SPEC || key == FALLBACK_GENERALIZATIONS +} + +fn unknown_timezone(wire: &EntryWire) -> Option { + let zone = wire.off_peak.as_ref()?.weekday_timezone.as_deref()?.trim(); + (!zone.is_empty() && jiff::tz::TimeZone::get(zone).is_err()).then(|| { + Error::from_path( + "off_peak_pricing.weekday_timezone", + Repr::UnknownTimezone { + zone: zone.to_owned(), + }, + ) + }) +} diff --git a/litellm-rust/crates/model-catalog/src/error.rs b/litellm-rust/crates/model-catalog/src/error.rs index edb6ba1eb11..425ae47687f 100644 --- a/litellm-rust/crates/model-catalog/src/error.rs +++ b/litellm-rust/crates/model-catalog/src/error.rs @@ -1,27 +1,392 @@ +use std::num::ParseIntError; + +use strum::{EnumDiscriminants, IntoStaticStr, VariantArray}; use thiserror::Error; #[derive(Debug, Error)] -pub enum Error { - /// The body is not valid JSON, or a model entry fails typed deserialization. - #[error("invalid JSON: {0}")] - Json(#[from] serde_json::Error), - /// The catalog has no entries at all. - #[error("catalog is empty")] +#[error(transparent)] +pub struct Error(Box); + +#[derive(Debug, Error)] +enum Context { + #[error(transparent)] + Bare(Repr), + #[error("{}", display_path(path))] + At { + path: String, + #[source] + cause: Repr, + }, +} + +#[derive(Debug, Error)] +pub(crate) enum DateCause { + #[error("invalid date component")] + Number(#[from] ParseIntError), + #[error("calendar component out of range")] + Range(#[from] time::error::ComponentRange), +} + +#[derive(Debug, Error, EnumDiscriminants)] +#[strum_discriminants(name(ErrorKind), derive(IntoStaticStr, VariantArray), vis(pub))] +pub(crate) enum Repr { + #[error("invalid JSON")] + #[strum_discriminants(strum(serialize = "json"))] + Json(#[source] serde_json::Error), + #[error("has no models")] + #[strum_discriminants(strum(serialize = "empty"))] Empty, - /// A non-reserved top level value is not a JSON object. - #[error("model {model:?} must be an object")] - EntryNotObject { model: String }, - /// Canonical entry count is under the configured minimum. - #[error("catalog has {actual} models, below minimum {minimum}")] + #[error("has {actual} models, below minimum {minimum}")] + #[strum_discriminants(strum(serialize = "below_minimum"))] BelowMinimum { actual: usize, minimum: usize }, - /// Canonical entry count is under the configured reference ratio. - #[error("catalog has {actual} models, below {ratio} of reference count {reference}")] + #[error("has {actual} models, below {ratio} of reference count {reference}")] + #[strum_discriminants(strum(serialize = "shrunk"))] Shrunk { actual: usize, reference: usize, ratio: f64, }, - /// The configured minimum reference ratio is not finite or outside `[0, 1]`. - #[error("minimum reference ratio must be finite and between zero and one")] - InvalidRatio, + #[error("must be a JSON object")] + #[strum_discriminants(strum(serialize = "not_an_object"))] + NotAnObject, + #[error("invalid value")] + #[strum_discriminants(strum(serialize = "invalid"))] + Invalid(#[source] serde_json::Error), + #[error("not a field this block reads")] + #[strum_discriminants(strum(serialize = "unknown_block_key"))] + UnknownBlockKey, + #[error("required")] + #[strum_discriminants(strum(serialize = "missing_provider"))] + MissingProvider, + #[error("{zone:?} is not an IANA time zone")] + #[strum_discriminants(strum(serialize = "unknown_timezone"))] + UnknownTimezone { zone: String }, + #[error("alias {alias:?} is already a model name")] + #[strum_discriminants(strum(serialize = "alias_shadows_model"))] + AliasShadowsModel { alias: String }, + #[error("alias {alias:?} already belongs to {taken_by}")] + #[strum_discriminants(strum(serialize = "alias_taken"))] + AliasTaken { alias: String, taken_by: String }, + #[error("{first} and {second} price the same meter under the same conditions")] + #[strum_discriminants(strum(serialize = "duplicate_price"))] + DuplicatePrice { first: String, second: String }, + #[error("a price inside {block} takes no band or tier suffix")] + #[strum_discriminants(strum(serialize = "suffix_inside_block"))] + SuffixInsideBlock { block: &'static str }, + #[error("a tier needs exactly one of range and max_results_range")] + #[strum_discriminants(strum(serialize = "tier_range"))] + TierRange, + #[error("the range ends below its start")] + #[strum_discriminants(strum(serialize = "tier_reversed"))] + TierReversed, + #[error("starts at {start}, but the tiers before it end at {expected}")] + #[strum_discriminants(strum(serialize = "tier_gap"))] + TierGap { start: u64, expected: u64 }, + #[error("tiered_pricing mixes token ranges and result ranges")] + #[strum_discriminants(strum(serialize = "mixed_tier_basis"))] + MixedTierBasis, + #[error("a tier by result count only prices input_cost_per_query")] + #[strum_discriminants(strum(serialize = "not_priced_by_results"))] + NotPricedByResults, + #[error("tiered_pricing and prompt token bands are set in two places")] + #[strum_discriminants(strum(serialize = "bands_from_two_sources"))] + BandsFromTwoSources, + #[error("has no off-peak rate")] + #[strum_discriminants(strum(serialize = "not_an_off_peak_rate"))] + NotAnOffPeakRate, + #[error("off_peak_pricing has no prices")] + #[strum_discriminants(strum(serialize = "no_off_peak_prices"))] + NoOffPeakPrices, + #[error("off_peak_pricing needs hours_utc or windows")] + #[strum_discriminants(strum(serialize = "no_off_peak_hours"))] + NoOffPeakHours, + #[error("must list at least one entry")] + #[strum_discriminants(strum(serialize = "empty_list"))] + EmptyList, + #[error("expected a calendar date YYYY-MM-DD")] + #[strum_discriminants(strum(serialize = "invalid_date"))] + InvalidDate { + #[source] + cause: Option, + }, +} + +/// What a problem takes out of the served map +#[derive(Clone, Copy, Debug, PartialEq, Eq, VariantArray)] +pub enum Rejects { + Document, + Row, + Nothing, +} + +impl Error { + pub fn kind(&self) -> ErrorKind { + ErrorKind::from(self.repr()) + } + + pub fn rejects(&self) -> Rejects { + match self.repr() { + Repr::Json(_) | Repr::Empty | Repr::BelowMinimum { .. } | Repr::Shrunk { .. } => { + Rejects::Document + } + Repr::NotAnObject + | Repr::Invalid(_) + | Repr::UnknownBlockKey + | Repr::UnknownTimezone { .. } + | Repr::AliasShadowsModel { .. } + | Repr::AliasTaken { .. } + | Repr::DuplicatePrice { .. } + | Repr::SuffixInsideBlock { .. } + | Repr::TierRange + | Repr::TierReversed + | Repr::TierGap { .. } + | Repr::MixedTierBasis + | Repr::NotPricedByResults + | Repr::BandsFromTwoSources + | Repr::NotAnOffPeakRate + | Repr::NoOffPeakPrices + | Repr::NoOffPeakHours + | Repr::EmptyList + | Repr::InvalidDate { .. } => Rejects::Row, + Repr::MissingProvider => Rejects::Nothing, + } + } +} + +#[derive(Debug)] +pub struct Loaded { + pub value: T, + pub errors: Vec, +} + +impl From for Error { + fn from(cause: Repr) -> Self { + Self(Box::new(Context::Bare(cause))) + } +} + +impl From for Error { + fn from(cause: DateCause) -> Self { + Repr::InvalidDate { cause: Some(cause) }.into() + } +} + +impl Error { + fn repr(&self) -> &Repr { + match &*self.0 { + Context::Bare(cause) | Context::At { cause, .. } => cause, + } + } + + pub(crate) fn new(path: impl Into, cause: Repr) -> Self { + Self(Box::new(Context::At { + path: path.into(), + cause, + })) + } + + pub(crate) fn from_key(key: &str, cause: Repr) -> Self { + Self::new(pointer_for_key(key), cause) + } + + pub(crate) fn from_path(path: &str, cause: Repr) -> Self { + Self::new(path_to_pointer(path), cause) + } + + pub fn path(&self) -> &str { + match &*self.0 { + Context::Bare(_) => "", + Context::At { path, .. } => path, + } + } + + pub fn key(&self) -> Option { + pointer_root(self.path()) + } + + pub fn field(&self) -> Option { + let segments: Vec<_> = self + .path() + .split('/') + .skip(2) + .map(unescape_pointer_segment) + .collect(); + (!segments.is_empty()).then(|| segments.join("/")) + } + + pub(crate) fn prepend(self, key: &str) -> Self { + let (path, cause) = match *self.0 { + Context::Bare(cause) => (String::new(), cause), + Context::At { path, cause } => (path, cause), + }; + Self::new(format!("/{}{path}", escape_pointer_segment(key)), cause) + } +} + +pub(crate) fn pointer_root(path: &str) -> Option { + path.strip_prefix('/') + .and_then(|path| path.split('/').next()) + .map(unescape_pointer_segment) +} + +fn escape_pointer_segment(segment: &str) -> String { + segment.replace('~', "~0").replace('/', "~1") +} + +pub(crate) fn pointer_for_key(key: &str) -> String { + format!("/{}", escape_pointer_segment(key)) +} + +pub(crate) fn pointer_child(parent: &str, key: &str) -> String { + format!("{parent}/{}", escape_pointer_segment(key)) +} + +fn unescape_pointer_segment(segment: &str) -> String { + segment.replace("~1", "/").replace("~0", "~") +} + +fn path_to_pointer(key: &str) -> String { + let mut pointer = String::new(); + let mut segment = String::new(); + let mut chars = key.chars(); + let mut push_segment = |segment: &mut String| { + if !segment.is_empty() { + pointer.push('/'); + pointer.push_str(&escape_pointer_segment(segment)); + segment.clear(); + } + }; + while let Some(character) = chars.next() { + match character { + '.' => push_segment(&mut segment), + '[' => { + push_segment(&mut segment); + let mut index = String::new(); + for character in chars.by_ref() { + if character == ']' { + break; + } + index.push(character); + } + push_segment(&mut index); + } + character => segment.push(character), + } + } + push_segment(&mut segment); + pointer +} + +fn display_path(path: &str) -> String { + if path.is_empty() { + return "catalog".to_owned(); + } + path.split('/') + .skip(1) + .map(unescape_pointer_segment) + .enumerate() + .fold(String::new(), |mut display, (index, segment)| { + if index == 0 { + display.push_str(&segment); + } else if segment.bytes().all(|byte| byte.is_ascii_digit()) { + display.push('['); + display.push_str(&segment); + display.push(']'); + } else { + display.push('.'); + display.push_str(&segment); + } + display + }) +} + +#[cfg(test)] +mod tests { + use litellm_error::{Report, find}; + use rstest::rstest; + use serde_json::Value; + + use super::*; + use crate::{Catalog, wire::IsoDate}; + + #[rstest] + #[case::json(Repr::Json(serde_json::from_str::("{").unwrap_err()), Rejects::Document)] + #[case::empty(Repr::Empty, Rejects::Document)] + #[case::below_minimum(Repr::BelowMinimum { actual: 1, minimum: 2 }, Rejects::Document)] + #[case::shrunk(Repr::Shrunk { actual: 1, reference: 3, ratio: 0.5 }, Rejects::Document)] + #[case::not_an_object(Repr::NotAnObject, Rejects::Row)] + #[case::invalid(Repr::Invalid(serde_json::from_str::("x").unwrap_err()), Rejects::Row)] + #[case::unknown_block_key(Repr::UnknownBlockKey, Rejects::Row)] + #[case::missing_provider(Repr::MissingProvider, Rejects::Nothing)] + #[case::unknown_timezone(Repr::UnknownTimezone { zone: "invalid".into() }, Rejects::Row)] + #[case::alias_shadows_model(Repr::AliasShadowsModel { alias: "model".into() }, Rejects::Row)] + #[case::alias_taken(Repr::AliasTaken { alias: "alias".into(), taken_by: "owner".into() }, Rejects::Row)] + #[case::duplicate_price(Repr::DuplicatePrice { first: "a".into(), second: "b".into() }, Rejects::Row)] + #[case::suffix_inside_block(Repr::SuffixInsideBlock { block: "tiered_pricing" }, Rejects::Row)] + #[case::tier_range(Repr::TierRange, Rejects::Row)] + #[case::tier_reversed(Repr::TierReversed, Rejects::Row)] + #[case::tier_gap(Repr::TierGap { start: 1, expected: 0 }, Rejects::Row)] + #[case::mixed_tier_basis(Repr::MixedTierBasis, Rejects::Row)] + #[case::not_priced_by_results(Repr::NotPricedByResults, Rejects::Row)] + #[case::bands_from_two_sources(Repr::BandsFromTwoSources, Rejects::Row)] + #[case::not_an_off_peak_rate(Repr::NotAnOffPeakRate, Rejects::Row)] + #[case::no_off_peak_prices(Repr::NoOffPeakPrices, Rejects::Row)] + #[case::no_off_peak_hours(Repr::NoOffPeakHours, Rejects::Row)] + #[case::empty_list(Repr::EmptyList, Rejects::Row)] + #[case::invalid_date(Repr::InvalidDate { cause: None }, Rejects::Row)] + fn policy_classifies_each_error(#[case] error: Repr, #[case] expected: Rejects) { + assert_eq!(Error::from(error).rejects(), expected); + } + + #[rstest] + #[case::root("", "x", "/x")] + #[case::empty_model("/", "x", "//x")] + #[case::empty_parent_segment("/m/", "x", "/m//x")] + #[case::escaped("/m~1n", "a~/b", "/m~1n/a~0~1b")] + fn pointers_preserve_segments(#[case] parent: &str, #[case] key: &str, #[case] expected: &str) { + assert_eq!(pointer_child(parent, key), expected); + } + + #[rstest] + #[case::malformed(br#"{"#)] + #[case::bad_price(br#"{"m":{"litellm_provider":"test","input_cost_per_token":"free"}}"#)] + fn json_causes_are_typed_and_rendered_once(#[case] body: &[u8]) { + let error = match Catalog::parse(body) { + Ok(loaded) => loaded.errors.into_iter().next().expect("invalid price"), + Err(error) => error, + }; + let cause = find::(&error) + .expect("typed JSON cause") + .to_string(); + let report = Report::new(&error).to_string(); + assert_eq!(report.matches(&cause).count(), 1, "{report}"); + assert!(!error.to_string().contains(&cause)); + } + + #[rstest] + #[case::year("xxxx-01-01")] + #[case::month("2026-xx-01")] + #[case::day("2026-01-xx")] + fn date_number_errors_keep_the_cause(#[case] value: &str) { + let error = value.parse::().unwrap_err(); + let cause = find::(&error) + .expect("typed integer cause") + .to_string(); + assert_eq!(error.rejects(), Rejects::Row); + assert_eq!(Report::new(&error).to_string().matches(&cause).count(), 1); + assert!(!error.to_string().contains(&cause)); + } + + #[rstest] + #[case::month("2026-13-01")] + #[case::day("2026-02-30")] + fn date_range_errors_keep_the_cause(#[case] value: &str) { + let error = value.parse::().unwrap_err(); + let cause = find::(&error) + .expect("typed calendar cause") + .to_string(); + assert_eq!(error.rejects(), Rejects::Row); + assert_eq!(Report::new(&error).to_string().matches(&cause).count(), 1); + assert!(!error.to_string().contains(&cause)); + } } diff --git a/litellm-rust/crates/model-catalog/src/fallback.rs b/litellm-rust/crates/model-catalog/src/fallback.rs index 62291a84929..f5a0cadb6b9 100644 --- a/litellm-rust/crates/model-catalog/src/fallback.rs +++ b/litellm-rust/crates/model-catalog/src/fallback.rs @@ -1,10 +1,9 @@ -use serde::{Deserialize, Serialize}; use serde_json::Value; use std::collections::BTreeMap; /// One regex rule generalizing unknown model ids to known families. -#[derive(Clone, Debug, Deserialize, PartialEq, Serialize)] -#[cfg_attr(feature = "schema", derive(schemars::JsonSchema))] +#[macro_rules_attribute::apply(crate::wire_type)] +#[derive(Eq, Hash)] pub struct FallbackRule { pub name: String, pub pattern: String, @@ -15,8 +14,8 @@ pub struct FallbackRule { } /// Regex rules that generalize unknown model ids to known families; not a model entry. -#[derive(Clone, Debug, Deserialize, PartialEq, Serialize)] -#[cfg_attr(feature = "schema", derive(schemars::JsonSchema))] +#[macro_rules_attribute::apply(crate::wire_type)] +#[derive(Eq, Hash)] #[serde(deny_unknown_fields)] pub struct FallbackGeneralizations { pub rules: Vec, diff --git a/litellm-rust/crates/model-catalog/src/layers.rs b/litellm-rust/crates/model-catalog/src/layers.rs new file mode 100644 index 00000000000..881f0f6af9b --- /dev/null +++ b/litellm-rust/crates/model-catalog/src/layers.rs @@ -0,0 +1,32 @@ +use std::sync::Arc; + +use indexmap::IndexMap; +use serde_json::Value; + +use crate::catalog::Catalog; +use crate::register::Registrations; +use crate::wire::Fields; + +/// One field of a fetched row over the layer below, RFC 7386. An absent field inherits, JSON `null` is `Remove` +#[derive(Clone, Debug, PartialEq)] +pub enum Patch { + Set(Value), + Remove, +} + +/// The four layers served rows are composed from, lowest first +#[derive(Clone, Debug)] +#[expect( + dead_code, + reason = "02 and 07 add the functions that read these layers" +)] +pub struct Layers { + /// 0, the wheel's embedded map + bundled: Arc, + /// 1, the last installed fetch, rejected rows left out + fetched: Option>, + /// 2, `register(persist=False)`, cleared by every install and refilled by the router replay + transient: IndexMap, + /// 3, `register(persist=True)`, applied over every install + persisted: Registrations, +} diff --git a/litellm-rust/crates/model-catalog/src/lib.rs b/litellm-rust/crates/model-catalog/src/lib.rs index 066c2c83c6b..fe419dde054 100644 --- a/litellm-rust/crates/model-catalog/src/lib.rs +++ b/litellm-rust/crates/model-catalog/src/lib.rs @@ -1,18 +1,65 @@ -mod capabilities; +//! The model catalog: per-model pricing, context limits and capabilities. +//! +//! This is the Rust form of `model_prices_and_context_window.json`, the map Python reads as +//! `litellm.model_cost` and through `litellm.get_model_info`. It answers "what does this model +//! cost and what can it do"; it knows nothing about configured deployments. The router's view of +//! deployments (groups, aliases, wildcard patterns, team mappings) is the router registry, defined +//! in `litellm-router-core`, which reads this catalog through its dynamic config. +//! +//! # Structure +//! - `Catalog`: the parsed map. `Catalog::parse` takes the JSON body and returns `Loaded`, +//! keeping every entry in file order with its raw fields and collecting row and alias errors. +//! - `ModelEntry`: one model. `ModelEntry::fields` is the raw JSON object, so unknown fields are +//! never lost; `ModelEntry::model` is the optional typed `Model` with attributes, prices, +//! adjustments and capabilities. Invalid rows retain their raw fields without a typed model. +//! - Aliases: an entry may list `aliases`; each alias resolves to its canonical key. Problems +//! found while indexing them (bad lists, collisions) are kept in `Loaded::errors` instead of +//! failing the document. +//! - `FallbackGeneralizations` / `FallbackRule`: regex rules that map unknown model ids onto known +//! families. They are data in the file, not entries. +//! - Validation: `Catalog::check_size` checks a catalog against `IntegrityLimits` (a remote copy +//! that lost most of its models is refused), and `Catalog::row_errors` validates one row. +//! +//! # Lookups +//! `Catalog::lookup` resolves a key exactly first (entry or alias), then case-insensitively, and +//! returns a `ModelMatch` with both the key that matched and the canonical key of the entry. Provider +//! prefixes are not stripped here; callers decide which keys to try. +//! +//! # Readers +//! Cost tracking, the router (through `RouterDynamicConfig`) and the gateway. Nothing in this crate +//! performs I/O; loading and refreshing the file is the caller's job. + +macro_rules_attribute::attribute_alias! { + #[apply(wire_type)] = + #[derive(Clone, Debug, PartialEq, serde::Serialize, serde::Deserialize)] + #[cfg_attr(feature = "schema", derive(schemars::JsonSchema))]; +} + +mod bundled; mod catalog; mod error; mod fallback; +mod layers; +mod lower; +mod model; mod model_info; -mod pricing; -mod validation; +mod register; +mod resolve; +mod store; +mod vocabulary; +pub mod wire; -pub use capabilities::*; +pub use bundled::*; pub use catalog::*; pub use error::*; pub use fallback::*; +pub use layers::*; +pub use model::*; pub use model_info::*; -pub use pricing::*; -pub use validation::*; +pub use register::*; +pub use resolve::*; +pub use store::*; +pub use vocabulary::*; #[cfg(feature = "schema")] mod schema; diff --git a/litellm-rust/crates/model-catalog/src/lower.rs b/litellm-rust/crates/model-catalog/src/lower.rs new file mode 100644 index 00000000000..4c3fc38a01a --- /dev/null +++ b/litellm-rust/crates/model-catalog/src/lower.rs @@ -0,0 +1,855 @@ +use std::collections::BTreeMap; +use std::collections::btree_map::Entry; +use std::num::NonZeroU64; + +use litellm_cost::money::UnitPrice; +use litellm_cost::price::{ + Adjustments, Band, BandEdge, Billing, CacheReadFallback, CacheReadMode, CacheTtl, + GuardrailUnit, InputUnit, Meter, OffPeak, OffPeakRates, OutputUnit, Price, Prices, Residency, + SearchContextSize, TextUnit, TierScope, TokenKind, Uplift, WallClock, WebSearchUnit, When, +}; +use litellm_cost::schedule::{Schedule, Window}; + +use crate::error::{Error, Repr, pointer_child, pointer_for_key}; +use crate::model::Model; +use crate::vocabulary::Mode; +use crate::wire::{EntryWire, FlatPrice, OffPeakBlock, TierRow, WebSearchBillingUnit}; + +impl TryFrom<&EntryWire> for Prices { + type Error = Vec; + + fn try_from(wire: &EntryWire) -> Result { + let mut problems = Vec::new(); + let sourced = flat_prices(&wire.prices) + .chain(tier_prices(wire, &mut problems)) + .chain(search_context_prices(wire)) + .chain(guardrail_prices(wire)); + let rates = dedupe(sourced, &mut problems); + let off_peak = wire + .off_peak + .as_ref() + .and_then(|block| off_peak(block, &mut problems)); + if problems.is_empty() { + let billing = billing(wire, &rates); + Ok(Prices::new(rates, off_peak, billing)) + } else { + Err(problems) + } + } +} + +fn billing(wire: &EntryWire, rates: &BTreeMap) -> Billing { + let provider = wire.attributes.litellm_provider.as_deref(); + let prices_meter = |priced: fn(&Meter) -> bool| rates.keys().any(|price| priced(&price.meter)); + let prices_tokens = prices_meter(|meter| { + matches!( + meter, + Meter::Input(InputUnit::Token(_)) | Meter::Output(OutputUnit::Token(_)) + ) + }); + let prices_characters = prices_meter(|meter| { + matches!( + meter, + Meter::Input(InputUnit::Character) | Meter::Output(OutputUnit::Character) + ) + }); + let prices_cache_read = prices_meter(|meter| { + matches!( + meter, + Meter::CacheRead { + kind: TokenKind::Text, + .. + } + ) + }); + Billing { + text_unit: if prices_characters && !prices_tokens { + TextUnit::Character + } else { + TextUnit::Token + }, + band_edge: if provider == Some("xai") { + BandEdge::Inclusive + } else { + BandEdge::Exclusive + }, + cache_read_fallback: if provider == Some("fireworks_ai") && !prices_cache_read { + CacheReadFallback::HalfInputRate + } else { + CacheReadFallback::InputRate + }, + wall_clock: match wire.attributes.mode { + None | Some(Mode::Chat | Mode::Completion | Mode::Embedding | Mode::Responses) => { + WallClock::ResponseTime + } + Some(Mode::AudioTranscription) => WallClock::AudioFile, + Some(_) => WallClock::Never, + }, + web_search: match wire.attributes.web_search_billing_unit { + Some(WebSearchBillingUnit::PerQuery) => WebSearchUnit::PerQuery, + Some(WebSearchBillingUnit::PerPrompt) | None => WebSearchUnit::PerPrompt, + }, + tier_scope: if provider == Some("dashscope") && wire.tier_rows.is_some() { + TierScope::WholeCall + } else { + TierScope::PerMeter + }, + } +} + +impl From<&EntryWire> for Adjustments { + fn from(wire: &EntryWire) -> Self { + Adjustments::new( + [ + (Uplift::NonGlobalEndpoint, wire.regional_endpoint_uplift), + (Uplift::Residency(Residency::Eu), wire.residency_uplift_eu), + (Uplift::Residency(Residency::Us), wire.residency_uplift_us), + ] + .into_iter() + .filter_map(|(uplift, factor)| Some((uplift, factor?))), + ) + } +} + +impl TryFrom for Model { + type Error = Vec; + + fn try_from(wire: EntryWire) -> Result { + let prices = Prices::try_from(&wire); + let adjustments = Adjustments::from(&wire); + let EntryWire { + attributes, + capabilities, + unknown, + problems, + .. + } = wire; + let missing_provider = attributes.litellm_provider.is_none().then_some(Error::new( + pointer_for_key("litellm_provider"), + Repr::MissingProvider, + )); + match prices { + Ok(prices) if problems.is_empty() && missing_provider.is_none() => Ok(Model { + attributes, + prices, + adjustments, + capabilities, + unrecognized: unknown.into_iter().map(|(key, _)| key).collect(), + }), + prices => Err(problems + .into_iter() + .chain(missing_provider) + .chain(prices.err().into_iter().flatten()) + .collect()), + } + } +} + +struct Sourced { + price: Price, + rate: UnitPrice, + source: String, + path: String, +} + +fn flat_prices(prices: &[FlatPrice]) -> impl Iterator + '_ { + prices.iter().map(|flat| { + let (channel, when) = flat.flat.channel_and_when(); + Sourced { + price: Price { + meter: flat.flat.meter.clone(), + channel, + when, + }, + rate: flat.price, + source: flat.key.clone(), + path: flat.path.clone(), + } + }) +} + +fn dedupe( + sourced: impl Iterator, + problems: &mut Vec, +) -> BTreeMap { + let mut seen: BTreeMap = BTreeMap::new(); + for Sourced { + price, + rate, + source, + path, + } in sourced + { + match seen.entry(price) { + Entry::Occupied(first) if first.get().0 == rate => {} + Entry::Occupied(first) => problems.push(Error::new( + path, + Repr::DuplicatePrice { + first: first.get().1.clone(), + second: source.clone(), + }, + )), + Entry::Vacant(slot) => { + slot.insert((rate, source, path)); + } + } + } + seen.into_iter() + .map(|(price, (rate, _, _))| (price, rate)) + .collect() +} + +#[derive(Clone, Copy, PartialEq, Eq)] +enum TierBasis { + PromptTokens, + Results, +} + +fn tier_basis(row: &TierRow) -> Result<(TierBasis, [u64; 2]), Error> { + match (row.range, row.max_results_range) { + (Some(range), None) => Ok((TierBasis::PromptTokens, range)), + (None, Some(range)) => Ok((TierBasis::Results, range)), + _ => Err(Error::new(row.path.clone(), Repr::TierRange)), + } +} + +fn tier_prices(wire: &EntryWire, problems: &mut Vec) -> Vec { + let Some(rows) = wire.tier_rows.as_deref().filter(|rows| !rows.is_empty()) else { + return Vec::new(); + }; + let based: Vec<_> = rows + .iter() + .filter_map(|row| match tier_basis(row) { + Ok((basis, range)) => Some((basis, range, row)), + Err(problem) => { + problems.push(problem); + None + } + }) + .collect(); + let Some(&(basis, ..)) = based.first() else { + return Vec::new(); + }; + if based.iter().any(|(other, ..)| *other != basis) { + problems.push(Error::from_key("tiered_pricing", Repr::MixedTierBasis)); + return Vec::new(); + } + if basis == TierBasis::PromptTokens { + problems.extend( + wire.prices + .iter() + .filter(|flat| flat.flat.band != Band::Base) + .map(|flat| Error::new(flat.path.clone(), Repr::BandsFromTwoSources)), + ); + } + let mut ordered = based; + ordered.sort_by_key(|(_, [start, _], _)| *start); + problems.extend(ladder_problems(basis, &ordered)); + ordered + .iter() + .flat_map(|(basis, [start, _], row)| { + row.prices.iter().map(move |flat| (*basis, *start, flat)) + }) + .filter_map( + |(basis, start, flat)| match tier_price(basis, start, flat) { + Ok(sourced) => Some(sourced), + Err(problem) => { + problems.push(problem); + None + } + }, + ) + .collect() +} + +fn ladder_problems(basis: TierBasis, ordered: &[(TierBasis, [u64; 2], &TierRow)]) -> Vec { + let step = match basis { + TierBasis::PromptTokens => 0, + TierBasis::Results => 1, + }; + let reversed = ordered + .iter() + .filter(|(_, [start, end], _)| end < start) + .map(|(.., row)| Error::new(row.path.clone(), Repr::TierReversed)); + let first = ordered + .first() + .filter(|(_, [start, _], _)| *start > step) + .map(|(_, [start, _], row)| { + Error::new( + row.path.clone(), + Repr::TierGap { + start: *start, + expected: 0, + }, + ) + }); + let gaps = ordered.windows(2).filter_map(|pair| { + let (_, [_, end], _) = pair[0]; + let (_, [start, _], row) = pair[1]; + (end.checked_add(step) != Some(start)).then(|| { + Error::new( + row.path.clone(), + Repr::TierGap { + start, + expected: end, + }, + ) + }) + }); + reversed.chain(first).chain(gaps).collect() +} + +fn tier_price(basis: TierBasis, start: u64, flat: &FlatPrice) -> Result { + if flat.flat.has_suffix() { + return Err(Error::new( + flat.path.clone(), + Repr::SuffixInsideBlock { + block: "tiered_pricing", + }, + )); + } + let (meter, band) = match (basis, &flat.flat.meter) { + (TierBasis::PromptTokens, meter) => (meter.clone(), Band::over_prompt_tokens(start)), + (TierBasis::Results, Meter::Input(InputUnit::Query { over_results: None })) => ( + Meter::Input(InputUnit::Query { + over_results: NonZeroU64::new(start.saturating_sub(1)), + }), + Band::Base, + ), + (TierBasis::Results, _) => { + return Err(Error::new(flat.path.clone(), Repr::NotPricedByResults)); + } + }; + Ok(Sourced { + price: Price::online( + meter, + When { + band, + ..When::default() + }, + ), + rate: flat.price, + source: flat.key.clone(), + path: flat.path.clone(), + }) +} + +fn search_context_prices(wire: &EntryWire) -> impl Iterator + '_ { + wire.search_context.iter().flat_map(|costs| { + [ + (SearchContextSize::Low, "low", costs.search_context_size_low), + ( + SearchContextSize::Medium, + "medium", + costs.search_context_size_medium, + ), + ( + SearchContextSize::High, + "high", + costs.search_context_size_high, + ), + ] + .into_iter() + .filter_map(|(size, name, rate)| { + Some(Sourced { + price: Price::online(Meter::WebSearch(size), When::default()), + rate: rate?, + source: format!("search_context_cost_per_query.search_context_size_{name}"), + path: pointer_child( + &pointer_for_key("search_context_cost_per_query"), + &format!("search_context_size_{name}"), + ), + }) + }) + }) +} + +fn guardrail_prices(wire: &EntryWire) -> impl Iterator + '_ { + wire.guardrail.iter().flatten().map(|(unit, rate)| Sourced { + price: Price::online(Meter::Guardrail(GuardrailUnit::new(unit)), When::default()), + rate: *rate, + source: format!("guardrail_cost_per_unit.{unit}"), + path: pointer_child(&pointer_for_key("guardrail_cost_per_unit"), unit), + }) +} + +fn off_peak(block: &OffPeakBlock, problems: &mut Vec) -> Option { + let rates = off_peak_rates(&block.prices, problems); + let schedule = schedule(block, problems)?; + let off_peak = OffPeak::new(schedule, rates); + if off_peak.is_none() { + problems.push(Error::from_key("off_peak_pricing", Repr::NoOffPeakPrices)); + } + off_peak +} + +fn off_peak_rates(prices: &[FlatPrice], problems: &mut Vec) -> OffPeakRates { + let mut rates = OffPeakRates::default(); + for flat in prices { + if flat.flat.has_suffix() { + problems.push(Error::new( + flat.path.clone(), + Repr::SuffixInsideBlock { + block: "off_peak_pricing", + }, + )); + continue; + } + let slot = match flat.flat.meter { + Meter::Input(InputUnit::Token(TokenKind::Text)) => &mut rates.input, + Meter::Output(OutputUnit::Token(TokenKind::Text)) => &mut rates.output, + Meter::Output(OutputUnit::ReasoningToken) => &mut rates.reasoning, + Meter::CacheRead { + kind: TokenKind::Text, + mode: CacheReadMode::Implicit, + } => &mut rates.cache_read, + Meter::CacheRead { + kind: TokenKind::Text, + mode: CacheReadMode::Explicit, + } => &mut rates.explicit_cache_read, + Meter::CacheWrite { + kind: TokenKind::Text, + ttl: CacheTtl::Default, + } => &mut rates.cache_write, + _ => { + problems.push(Error::new(flat.path.clone(), Repr::NotAnOffPeakRate)); + continue; + } + }; + *slot = Some(flat.price); + } + rates +} + +fn schedule(block: &OffPeakBlock, problems: &mut Vec) -> Option { + let empty = |key: String| Error::from_path(&key, Repr::EmptyList); + let every_day = block + .hours_utc + .iter() + .map(|hours| ("off_peak_pricing.hours_utc".to_owned(), hours, None)); + let windows = block + .windows + .iter() + .flatten() + .enumerate() + .map(|(index, window)| { + ( + format!("off_peak_pricing.windows[{index}].hours_utc"), + &window.hours_utc, + Some((index, window.weekdays.as_ref())), + ) + }); + let windows: Vec = every_day + .chain(windows) + .map(|(key, hours, weekdays)| { + if hours.windows().is_empty() { + problems.push(empty(key)); + } + if let Some((index, Some(days))) = weekdays + && days.is_empty() + { + problems.push(empty(format!("off_peak_pricing.windows[{index}].weekdays"))); + } + Window { + hours: hours.windows().to_vec(), + weekdays: weekdays.and_then(|(_, days)| days.cloned()), + } + }) + .collect(); + if block.windows.as_ref().is_some_and(Vec::is_empty) { + problems.push(empty("off_peak_pricing.windows".to_owned())); + } + if block.hours_utc.is_none() && block.windows.is_none() { + problems.push(Error::from_key("off_peak_pricing", Repr::NoOffPeakHours)); + return None; + } + Some(Schedule { + windows, + weekday_timezone: block.weekday_timezone.clone(), + }) +} + +#[cfg(test)] +mod tests { + use litellm_cost::money::Multiplier; + use litellm_cost::price::{Channel, ServiceTier}; + use litellm_cost::schedule::{UtcWindow, Weekday}; + use rstest::rstest; + use serde_json::{Value, json}; + + use super::*; + + const TEXT_INPUT: Meter = Meter::Input(InputUnit::Token(TokenKind::Text)); + + fn wire(entry: Value) -> EntryWire { + let Value::Object(fields) = entry else { + panic!("entry must be an object") + }; + let wire = EntryWire::read(&fields); + assert!(wire.problems.is_empty(), "{:?}", wire.problems); + wire + } + + fn prices(entry: Value) -> Result> { + Prices::try_from(&wire(entry)) + } + + fn online(meter: Meter, tier: ServiceTier, band: Band) -> Price { + Price::online(meter, When { tier, band }) + } + + #[rstest] + #[case::flat_key(json!({"input_cost_per_token": 1e-6}), online(TEXT_INPUT, ServiceTier::Standard, Band::Base))] + #[case::band_and_tier( + json!({"input_cost_per_token_above_272k_tokens_priority": 1e-6}), + online(TEXT_INPUT, ServiceTier::Priority, Band::over_prompt_tokens(272_000)) + )] + #[case::batch( + json!({"input_cost_per_token_batches": 1e-6}), + Price { meter: TEXT_INPUT, channel: Channel::Batch, when: When::default() } + )] + #[case::first_token_tier_is_the_base_band( + json!({"tiered_pricing": [{"range": [0.0, 256000.0], "input_cost_per_token": 1e-6}]}), + online(TEXT_INPUT, ServiceTier::Standard, Band::Base) + )] + #[case::result_tier_stays_in_its_meter( + json!({"tiered_pricing": [ + {"max_results_range": [0, 25], "input_cost_per_query": 2e-6}, + {"max_results_range": [26, 100], "input_cost_per_query": 1e-6} + ]}), + online( + Meter::Input(InputUnit::Query { over_results: NonZeroU64::new(25) }), + ServiceTier::Standard, + Band::Base + ) + )] + #[case::search_context( + json!({"search_context_cost_per_query": {"search_context_size_low": 1e-6}}), + online(Meter::WebSearch(SearchContextSize::Low), ServiceTier::Standard, Band::Base) + )] + #[case::character_band_is_a_prompt_token_band( + json!({"input_cost_per_character_above_128k_tokens": 1e-6}), + online(Meter::Input(InputUnit::Character), ServiceTier::Standard, Band::over_prompt_tokens(128_000)) + )] + #[case::guardrail( + json!({"guardrail_cost_per_unit": {"contentPolicyUnits": 1e-6}}), + online(Meter::Guardrail(GuardrailUnit::new("contentPolicyUnits")), ServiceTier::Standard, Band::Base) + )] + fn every_spelling_lowers_to_one_price(#[case] entry: Value, #[case] expected: Price) { + assert_eq!(prices(entry).unwrap().get(&expected), UnitPrice::new(1e-6)); + } + + #[rstest] + fn two_spellings_that_agree_are_one_price() { + let prices = prices(json!({ + "input_cost_per_token": 1e-6, + "tiered_pricing": [ + {"range": [0, 10], "input_cost_per_token": 1e-6}, + {"range": [10, 20], "input_cost_per_token": 2e-6} + ] + })) + .unwrap(); + assert_eq!( + prices.get(&Price::online(TEXT_INPUT, When::default())), + UnitPrice::new(1e-6) + ); + } + + #[rstest] + fn token_tiers_lower_to_prompt_bands_at_each_start() { + let prices = prices(json!({"tiered_pricing": [ + {"range": [0, 256000], "input_cost_per_token": 1e-6}, + {"range": [256000, 1000000], "input_cost_per_token": 2e-6} + ]})) + .unwrap(); + assert_eq!( + prices.band(ServiceTier::Standard, 256_001), + Band::over_prompt_tokens(256_000) + ); + assert_eq!( + prices + .rate( + &TEXT_INPUT, + ServiceTier::Standard, + Band::over_prompt_tokens(256_000) + ) + .map(UnitPrice::get), + Some(2e-6) + ); + } + + #[rstest] + #[case::two_spellings_of_one_price( + json!({ + "input_cost_per_token": 1e-6, + "tiered_pricing": [{"range": [0, 10], "input_cost_per_token": 2e-6}] + }), + "/tiered_pricing/0/input_cost_per_token", + "duplicate_price" + )] + #[case::zero_band_is_the_base_price( + json!({"input_cost_per_token": 1e-6, "input_cost_per_token_above_0k_tokens": 2e-6}), + "/input_cost_per_token_above_0k_tokens", + "duplicate_price" + )] + #[case::tier_without_range( + json!({"tiered_pricing": [{"input_cost_per_token": 1e-6}]}), + "/tiered_pricing/0", + "tier_range" + )] + #[case::tier_with_suffix( + json!({"tiered_pricing": [{"range": [0, 10], "input_cost_per_token_priority": 1e-6}]}), + "/tiered_pricing/0/input_cost_per_token_priority", + "suffix_inside_block" + )] + #[case::reversed_range( + json!({"tiered_pricing": [{"range": [0, 10], "input_cost_per_token": 1e-6}, {"range": [10, 5], "input_cost_per_token": 1e-6}]}), + "/tiered_pricing/1", + "tier_reversed" + )] + #[case::gap_between_tiers( + json!({"tiered_pricing": [ + {"range": [0, 10], "input_cost_per_token": 1e-6}, + {"range": [20, 30], "input_cost_per_token": 2e-6} + ]}), + "/tiered_pricing/1", + "tier_gap" + )] + #[case::ladder_not_from_zero( + json!({"tiered_pricing": [{"range": [5, 10], "input_cost_per_token": 1e-6}]}), + "/tiered_pricing/0", + "tier_gap" + )] + #[case::result_ladder_overlaps( + json!({"tiered_pricing": [ + {"max_results_range": [1, 10], "input_cost_per_query": 1e-6}, + {"max_results_range": [10, 20], "input_cost_per_query": 2e-6} + ]}), + "/tiered_pricing/1", + "tier_gap" + )] + #[case::mixed_basis( + json!({"tiered_pricing": [ + {"range": [0, 10], "input_cost_per_token": 1e-6}, + {"max_results_range": [11, 20], "input_cost_per_query": 2e-6} + ]}), + "/tiered_pricing", + "mixed_tier_basis" + )] + #[case::result_tier_prices_a_token( + json!({"tiered_pricing": [{"max_results_range": [0, 10], "input_cost_per_token": 1e-6}]}), + "/tiered_pricing/0/input_cost_per_token", + "not_priced_by_results" + )] + #[case::two_band_sources( + json!({ + "output_cost_per_token_above_200k_tokens": 1e-6, + "tiered_pricing": [{"range": [0, 10], "input_cost_per_token": 1e-6}] + }), + "/output_cost_per_token_above_200k_tokens", + "bands_from_two_sources" + )] + #[case::off_peak_without_hours( + json!({"off_peak_pricing": {"input_cost_per_token": 1e-6}}), + "/off_peak_pricing", + "no_off_peak_hours" + )] + #[case::off_peak_without_prices( + json!({"off_peak_pricing": {"hours_utc": "00:00-01:00"}}), + "/off_peak_pricing", + "no_off_peak_prices" + )] + #[case::off_peak_empty_windows( + json!({"off_peak_pricing": {"windows": [], "input_cost_per_token": 1e-6}}), + "/off_peak_pricing/windows", + "empty_list" + )] + #[case::off_peak_empty_hours( + json!({"off_peak_pricing": {"hours_utc": [], "input_cost_per_token": 1e-6}}), + "/off_peak_pricing/hours_utc", + "empty_list" + )] + #[case::off_peak_empty_weekdays( + json!({"off_peak_pricing": { + "windows": [{"hours_utc": "00:00-01:00", "weekdays": []}], + "input_cost_per_token": 1e-6 + }}), + "/off_peak_pricing/windows/0/weekdays", + "empty_list" + )] + #[case::off_peak_image_price( + json!({"off_peak_pricing": {"hours_utc": "00:00-01:00", "output_cost_per_image": 1}}), + "/off_peak_pricing/output_cost_per_image", + "not_an_off_peak_rate" + )] + #[case::off_peak_band( + json!({"off_peak_pricing": {"hours_utc": "00:00-01:00", "input_cost_per_token_above_200k_tokens": 1}}), + "/off_peak_pricing/input_cost_per_token_above_200k_tokens", + "suffix_inside_block" + )] + fn rules_across_keys_name_where_each_price_came_from( + #[case] entry: Value, + #[case] expected_path: &str, + #[case] expected_variant: &str, + ) { + let problems = prices(entry).unwrap_err(); + assert!( + problems + .iter() + .any(|problem| problem.path() == expected_path + && <&str>::from(problem.kind()) == expected_variant), + "{problems:?}" + ); + } + + #[rstest] + fn off_peak_hours_and_windows_form_one_schedule_with_its_rates() { + let prices = prices(json!({"off_peak_pricing": { + "hours_utc": ["00:00-01:00"], + "windows": [{"hours_utc": "10:00-12:00", "weekdays": [6, " sun "]}], + "weekday_timezone": "Asia/Shanghai", + "output_cost_per_token": 1e-6, + "explicit_cache_read_input_token_cost": 2e-6 + }})) + .unwrap(); + let off_peak = prices.off_peak().unwrap(); + let window = |text: &str| text.parse::().unwrap(); + + assert_eq!( + off_peak.schedule(), + &Schedule { + windows: vec![ + Window { + hours: vec![window("00:00-01:00")], + weekdays: None, + }, + Window { + hours: vec![window("10:00-12:00")], + weekdays: Some(vec![Weekday::Saturday, Weekday::Sunday]), + }, + ], + weekday_timezone: Some("Asia/Shanghai".into()), + } + ); + assert_eq!( + off_peak.rates(), + &OffPeakRates { + output: UnitPrice::new(1e-6), + explicit_cache_read: UnitPrice::new(2e-6), + ..OffPeakRates::default() + } + ); + assert_eq!(prices.iter().count(), 0); + } + + #[rstest] + fn uplifts_are_adjustments_not_prices() { + let wire = wire(json!({ + "regional_endpoint_uplift_multiplier": 1.1, + "regional_processing_uplift_multiplier_eu": "1.2" + })); + let adjustments = Adjustments::from(&wire); + + assert_eq!(Prices::try_from(&wire).unwrap().iter().count(), 0); + assert_eq!( + adjustments + .get(&Uplift::NonGlobalEndpoint) + .map(Multiplier::get), + Some(1.1) + ); + assert_eq!( + adjustments + .get(&Uplift::Residency(Residency::Eu)) + .map(Multiplier::get), + Some(1.2) + ); + assert_eq!(adjustments.get(&Uplift::Residency(Residency::Us)), None); + } + + #[rstest] + fn a_model_reports_field_provider_and_price_problems_together() { + let Value::Object(fields) = json!({ + "mode": "chatt", + "tiered_pricing": [{"input_cost_per_token": 1e-6}] + }) else { + unreachable!() + }; + let problems: Vec = Model::from_fields(&fields) + .unwrap_err() + .iter() + .map(|problem| litellm_error::Report::new(problem).to_string()) + .collect(); + + assert_eq!(problems.len(), 3, "{problems:?}"); + assert!(problems[0].starts_with("mode: invalid value: unknown variant `chatt`")); + assert_eq!(problems[1], "litellm_provider: required"); + assert_eq!( + problems[2], + "tiered_pricing[0]: a tier needs exactly one of range and max_results_range" + ); + } + + #[rstest] + fn a_null_value_is_absent() { + let Value::Object(fields) = json!({ + "litellm_provider": "openai", + "input_cost_per_token": null, + "mode": null + }) else { + unreachable!() + }; + let model = Model::from_fields(&fields).unwrap(); + + assert_eq!(model.prices.iter().count(), 0); + assert_eq!(model.attributes.mode, None); + assert!(model.unrecognized.is_empty()); + } + + #[rstest] + #[case::tokens_win_over_characters( + json!({"litellm_provider": "vertex_ai-language-models", "input_cost_per_character": 1e-6, "input_cost_per_token": 1e-6}), + Billing::default() + )] + #[case::characters_only( + json!({"litellm_provider": "vertex_ai-language-models", "input_cost_per_character": 1e-6}), + Billing { text_unit: TextUnit::Character, ..Billing::default() } + )] + #[case::xai_band_is_inclusive( + json!({"litellm_provider": "xai", "input_cost_per_token": 1e-6}), + Billing { band_edge: BandEdge::Inclusive, ..Billing::default() } + )] + #[case::fireworks_without_cache_read_borrows_half( + json!({"litellm_provider": "fireworks_ai", "input_cost_per_token": 1e-6}), + Billing { cache_read_fallback: CacheReadFallback::HalfInputRate, ..Billing::default() } + )] + #[case::fireworks_with_cache_read_keeps_it( + json!({"litellm_provider": "fireworks_ai", "input_cost_per_token": 1e-6, "cache_read_input_token_cost": 1e-7}), + Billing::default() + )] + #[case::transcription_prices_the_audio_file( + json!({"litellm_provider": "openai", "mode": "audio_transcription", "input_cost_per_second": 1e-4}), + Billing { wall_clock: WallClock::AudioFile, ..Billing::default() } + )] + #[case::provisioned_chat_prices_response_time( + json!({"litellm_provider": "bedrock", "mode": "chat", "cost_per_second": 1e-2}), + Billing::default() + )] + #[case::image_generation_is_never_wall_clock( + json!({"litellm_provider": "openai", "mode": "image_generation"}), + Billing { wall_clock: WallClock::Never, ..Billing::default() } + )] + #[case::gemini_per_query_search( + json!({"litellm_provider": "gemini", "web_search_billing_unit": "per_query"}), + Billing { web_search: WebSearchUnit::PerQuery, ..Billing::default() } + )] + #[case::dashscope_tiers_bill_the_whole_call( + json!({"litellm_provider": "dashscope", "tiered_pricing": [{"range": [0, 32000], "input_cost_per_token": 1e-6}]}), + Billing { tier_scope: TierScope::WholeCall, ..Billing::default() } + )] + fn billing_is_lowered_from_the_row_and_its_provider( + #[case] entry: Value, + #[case] expected: Billing, + ) { + assert_eq!(prices(entry).unwrap().billing(), expected); + } +} diff --git a/litellm-rust/crates/model-catalog/src/model.rs b/litellm-rust/crates/model-catalog/src/model.rs new file mode 100644 index 00000000000..c1acd1c14cb --- /dev/null +++ b/litellm-rust/crates/model-catalog/src/model.rs @@ -0,0 +1,22 @@ +use std::collections::BTreeMap; + +use litellm_cost::price::{Adjustments, Prices}; + +use crate::error::Error; +use crate::wire::{Attributes, EntryWire, Fields}; + +/// One catalog entry read into types. +#[derive(Clone, Debug, PartialEq)] +pub struct Model { + pub attributes: Attributes, + pub prices: Prices, + pub adjustments: Adjustments, + pub capabilities: BTreeMap, + pub unrecognized: Vec, +} + +impl Model { + pub fn from_fields(fields: &Fields) -> Result> { + Self::try_from(EntryWire::read(fields)) + } +} diff --git a/litellm-rust/crates/model-catalog/src/model_info.rs b/litellm-rust/crates/model-catalog/src/model_info.rs index ebee2c64140..8f7549c1c6d 100644 --- a/litellm-rust/crates/model-catalog/src/model_info.rs +++ b/litellm-rust/crates/model-catalog/src/model_info.rs @@ -1,582 +1,194 @@ -use crate::capabilities::{AudioFormat, InputModality, Mode, OutputModality, VertexAiAudioApi}; -use crate::pricing::{OffPeakPricing, SearchContextCostPerQuery, TieredRate, WebSearchBillingUnit}; -use litellm_llms_types::formats::chat_completions::ReasoningEffort; -use serde::{Deserialize, Serialize}; +use indexmap::IndexMap; use serde_json::Value; -use std::collections::BTreeMap; -/// Typed mirror of one catalog model entry. -#[derive(Clone, Debug, Deserialize, PartialEq, Serialize)] -#[cfg_attr(feature = "schema", derive(schemars::JsonSchema))] -pub struct ModelInfo { - #[serde(skip_serializing_if = "Option::is_none")] - pub annotation_cost_per_page: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub annotation_cost_per_page_batches: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub audio_transcription_config: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub bedrock_converse_supports_strict_tools: Option, - /// Highest reasoning effort the Bedrock output_config accepts for this model. - #[serde(skip_serializing_if = "Option::is_none")] - pub bedrock_output_config_effort_ceiling: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub cache_creation_input_audio_token_cost: Option, - /// USD per token written to the provider's prompt cache. - #[serde(skip_serializing_if = "Option::is_none")] - pub cache_creation_input_token_cost: Option, - /// Rate applied once the prompt exceeds the token threshold in the field name. - #[serde(skip_serializing_if = "Option::is_none")] - pub cache_creation_input_token_cost_above_32k_tokens: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub cache_creation_input_token_cost_above_100k_tokens: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub cache_creation_input_token_cost_above_100k_tokens_batches: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub cache_creation_input_token_cost_above_128k_tokens: Option, - /// Rate applied once the prompt exceeds the token threshold in the field name. - #[serde(skip_serializing_if = "Option::is_none")] - pub cache_creation_input_token_cost_above_1hr: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub cache_creation_input_token_cost_above_1hr_above_100k_tokens: Option, - /// Rate applied once the prompt exceeds the token threshold in the field name. - #[serde(skip_serializing_if = "Option::is_none")] - pub cache_creation_input_token_cost_above_1hr_above_200k_tokens: Option, - /// Rate applied once the prompt exceeds the token threshold in the field name. - #[serde(skip_serializing_if = "Option::is_none")] - pub cache_creation_input_token_cost_above_200k_tokens: Option, - /// Rate applied once the prompt exceeds the token threshold in the field name. - #[serde(skip_serializing_if = "Option::is_none")] - pub cache_creation_input_token_cost_above_200k_tokens_batches: Option, - /// Rate applied once the prompt exceeds the token threshold in the field name. - #[serde(skip_serializing_if = "Option::is_none")] - pub cache_creation_input_token_cost_above_256k_tokens: Option, - /// Rate applied once the prompt exceeds the token threshold in the field name. - #[serde(skip_serializing_if = "Option::is_none")] - pub cache_creation_input_token_cost_above_272k_tokens: Option, - /// Rate applied once the prompt exceeds the token threshold in the field name. - #[serde(skip_serializing_if = "Option::is_none")] - pub cache_creation_input_token_cost_above_272k_tokens_batches: Option, - /// Flex service-tier rate for the same-named base field. - #[serde(skip_serializing_if = "Option::is_none")] - pub cache_creation_input_token_cost_above_272k_tokens_flex: Option, - /// Priority service-tier rate for the same-named base field. - #[serde(skip_serializing_if = "Option::is_none")] - pub cache_creation_input_token_cost_above_272k_tokens_priority: Option, - /// Ultrafast service-tier rate for the same-named base field. - #[serde(skip_serializing_if = "Option::is_none")] - pub cache_creation_input_token_cost_above_272k_tokens_ultrafast: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub cache_creation_input_token_cost_batches: Option, - /// Flex service-tier rate for the same-named base field. - #[serde(skip_serializing_if = "Option::is_none")] - pub cache_creation_input_token_cost_flex: Option, - /// Priority service-tier rate for the same-named base field. - #[serde(skip_serializing_if = "Option::is_none")] - pub cache_creation_input_token_cost_priority: Option, - /// Ultrafast service-tier rate for the same-named base field. - #[serde(skip_serializing_if = "Option::is_none")] - pub cache_creation_input_token_cost_ultrafast: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub cache_read_input_audio_token_cost: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub cache_read_input_image_token_cost: Option, - /// USD per prompt token served from the provider's prompt cache. - #[serde(skip_serializing_if = "Option::is_none")] - pub cache_read_input_token_cost: Option, - /// Rate applied once the prompt exceeds the token threshold in the field name. - #[serde(skip_serializing_if = "Option::is_none")] - pub cache_read_input_token_cost_above_32k_tokens: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub cache_read_input_token_cost_above_100k_tokens: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub cache_read_input_token_cost_above_100k_tokens_batches: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub cache_read_input_token_cost_above_128k_tokens: Option, - /// Rate applied once the prompt exceeds the token threshold in the field name. - #[serde(skip_serializing_if = "Option::is_none")] - pub cache_read_input_token_cost_above_200k_tokens: Option, - /// Rate applied once the prompt exceeds the token threshold in the field name. - #[serde(skip_serializing_if = "Option::is_none")] - pub cache_read_input_token_cost_above_200k_tokens_batches: Option, - /// Priority service-tier rate for the same-named base field. - #[serde(skip_serializing_if = "Option::is_none")] - pub cache_read_input_token_cost_above_200k_tokens_priority: Option, - /// Rate applied once the prompt exceeds the token threshold in the field name. - #[serde(skip_serializing_if = "Option::is_none")] - pub cache_read_input_token_cost_above_256k_tokens: Option, - /// Rate applied once the prompt exceeds the token threshold in the field name. - #[serde(skip_serializing_if = "Option::is_none")] - pub cache_read_input_token_cost_above_272k_tokens: Option, - /// Rate applied once the prompt exceeds the token threshold in the field name. - #[serde(skip_serializing_if = "Option::is_none")] - pub cache_read_input_token_cost_above_272k_tokens_batches: Option, - /// Flex service-tier rate for the same-named base field. - #[serde(skip_serializing_if = "Option::is_none")] - pub cache_read_input_token_cost_above_272k_tokens_flex: Option, - /// Priority service-tier rate for the same-named base field. - #[serde(skip_serializing_if = "Option::is_none")] - pub cache_read_input_token_cost_above_272k_tokens_priority: Option, - /// Ultrafast service-tier rate for the same-named base field. - #[serde(skip_serializing_if = "Option::is_none")] - pub cache_read_input_token_cost_above_272k_tokens_ultrafast: Option, - /// Rate applied once the prompt exceeds the token threshold in the field name. - #[serde(skip_serializing_if = "Option::is_none")] - pub cache_read_input_token_cost_above_512k_tokens: Option, - /// Balanced service-tier rate for the same-named base field. - #[serde(skip_serializing_if = "Option::is_none")] - pub cache_read_input_token_cost_balanced: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub cache_read_input_token_cost_batches: Option, - /// Flex service-tier rate for the same-named base field. - #[serde(skip_serializing_if = "Option::is_none")] - pub cache_read_input_token_cost_flex: Option, - /// Priority service-tier rate for the same-named base field. - #[serde(skip_serializing_if = "Option::is_none")] - pub cache_read_input_token_cost_priority: Option, - /// Ultrafast service-tier rate for the same-named base field. - #[serde(skip_serializing_if = "Option::is_none")] - pub cache_read_input_token_cost_ultrafast: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub citation_cost_per_token: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub code_interpreter_cost_per_session: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub comment: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub computer_use_input_cost_per_1k_tokens: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub computer_use_output_cost_per_1k_tokens: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub cost_per_second: Option, - /// Reasoning effort the provider applies when the request omits reasoning_effort. Gates whether a non-default temperature or the top_p/logprobs sampling params are accepted, which hold only when the effort resolves to 'none'. - #[serde(skip_serializing_if = "Option::is_none")] - pub default_reasoning_effort: Option, - /// Date the provider deprecates the model, YYYY-MM-DD. - #[serde(skip_serializing_if = "Option::is_none")] - pub deprecation_date: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub file_search_cost_per_1k_calls: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub file_search_cost_per_gb_per_day: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub gemini_audio_only_live: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub gemini_native_audio: Option, - /// USD per Grounding with Google Maps request; billed per query or per prompt per web_search_billing_unit. - #[serde(skip_serializing_if = "Option::is_none")] - pub google_maps_grounding_cost_per_query: Option, - /// USD cost per billable guardrail unit, keyed by the provider's usage counter name (e.g. Bedrock's contentPolicyUnits). - #[serde(skip_serializing_if = "Option::is_none")] - pub guardrail_cost_per_unit: Option>, - #[serde(skip_serializing_if = "Option::is_none")] - pub input_cost_per_audio_per_second: Option, - /// Rate applied once the prompt exceeds the token threshold in the field name. - #[serde(skip_serializing_if = "Option::is_none")] - pub input_cost_per_audio_per_second_above_128k_tokens: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub input_cost_per_audio_token: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub input_cost_per_audio_token_batches: Option, - /// Priority service-tier rate for the same-named base field. - #[serde(skip_serializing_if = "Option::is_none")] - pub input_cost_per_audio_token_priority: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub input_cost_per_character: Option, - /// Rate applied once the prompt exceeds the token threshold in the field name. - #[serde(skip_serializing_if = "Option::is_none")] - pub input_cost_per_character_above_128k_tokens: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub input_cost_per_image: Option, - /// Rate applied once the prompt exceeds the token threshold in the field name. - #[serde(skip_serializing_if = "Option::is_none")] - pub input_cost_per_image_above_128k_tokens: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub input_cost_per_image_token: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub input_cost_per_image_token_batches: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub input_cost_per_pixel: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub input_cost_per_query: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub input_cost_per_request: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub input_cost_per_second: Option, - /// USD per prompt token. - #[serde(skip_serializing_if = "Option::is_none")] +/// The fields main's `ModelInfoBase(...)` copies (`litellm/utils.py` at c7c895db45), one typed field each, +/// read from the raw row without lowering it, so building one never fails +#[derive(Clone, Debug, Default, PartialEq)] +pub struct ModelInfoFields { + pub key: String, + pub max_tokens: Option, + pub max_input_tokens: Option, + pub max_output_tokens: Option, pub input_cost_per_token: Option, - /// Rate applied once the prompt exceeds the token threshold in the field name. - #[serde(skip_serializing_if = "Option::is_none")] - pub input_cost_per_token_above_32k_tokens: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub input_cost_per_token_above_100k_tokens: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub input_cost_per_token_above_100k_tokens_batches: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub input_cost_per_token_above_128k_tokens: Option, - /// Rate applied once the prompt exceeds the token threshold in the field name. - #[serde(skip_serializing_if = "Option::is_none")] - pub input_cost_per_token_above_200k_tokens: Option, - /// Rate applied once the prompt exceeds the token threshold in the field name. - #[serde(skip_serializing_if = "Option::is_none")] - pub input_cost_per_token_above_200k_tokens_batches: Option, - /// Priority service-tier rate for the same-named base field. - #[serde(skip_serializing_if = "Option::is_none")] - pub input_cost_per_token_above_200k_tokens_priority: Option, - /// Rate applied once the prompt exceeds the token threshold in the field name. - #[serde(skip_serializing_if = "Option::is_none")] - pub input_cost_per_token_above_256k_tokens: Option, - /// Rate applied once the prompt exceeds the token threshold in the field name. - #[serde(skip_serializing_if = "Option::is_none")] - pub input_cost_per_token_above_272k_tokens: Option, - /// Rate applied once the prompt exceeds the token threshold in the field name. - #[serde(skip_serializing_if = "Option::is_none")] - pub input_cost_per_token_above_272k_tokens_batches: Option, - /// Flex service-tier rate for the same-named base field. - #[serde(skip_serializing_if = "Option::is_none")] - pub input_cost_per_token_above_272k_tokens_flex: Option, - /// Priority service-tier rate for the same-named base field. - #[serde(skip_serializing_if = "Option::is_none")] - pub input_cost_per_token_above_272k_tokens_priority: Option, - /// Ultrafast service-tier rate for the same-named base field. - #[serde(skip_serializing_if = "Option::is_none")] - pub input_cost_per_token_above_272k_tokens_ultrafast: Option, - /// Rate applied once the prompt exceeds the token threshold in the field name. - #[serde(skip_serializing_if = "Option::is_none")] - pub input_cost_per_token_above_512k_tokens: Option, - /// Balanced service-tier rate for the same-named base field. - #[serde(skip_serializing_if = "Option::is_none")] - pub input_cost_per_token_balanced: Option, - /// USD per prompt token via the provider's batch API. - #[serde(skip_serializing_if = "Option::is_none")] - pub input_cost_per_token_batches: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub input_cost_per_token_cache_hit: Option, - /// Flex service-tier rate for the same-named base field. - #[serde(skip_serializing_if = "Option::is_none")] pub input_cost_per_token_flex: Option, - /// Priority service-tier rate for the same-named base field. - #[serde(skip_serializing_if = "Option::is_none")] pub input_cost_per_token_priority: Option, - /// Ultrafast service-tier rate for the same-named base field. - #[serde(skip_serializing_if = "Option::is_none")] + pub input_cost_per_token_balanced: Option, pub input_cost_per_token_ultrafast: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub input_cost_per_video_per_second: Option, - /// Rate applied once the prompt exceeds the token threshold in the field name. - #[serde(skip_serializing_if = "Option::is_none")] - pub input_cost_per_video_per_second_above_128k_tokens: Option, - /// Rate applied once the prompt exceeds the token threshold in the field name. - #[serde(skip_serializing_if = "Option::is_none")] - pub input_cost_per_video_per_second_above_15s_interval: Option, - /// Rate applied once the prompt exceeds the token threshold in the field name. - #[serde(skip_serializing_if = "Option::is_none")] - pub input_cost_per_video_per_second_above_8s_interval: Option, - #[serde(skip_serializing_if = "Option::is_none")] + pub cache_creation_input_token_cost: Option, + pub cache_creation_input_token_cost_above_200k_tokens: Option, + pub cache_creation_input_token_cost_above_272k_tokens: Option, + pub cache_creation_input_token_cost_above_272k_tokens_priority: Option, + pub cache_creation_input_token_cost_above_272k_tokens_flex: Option, + pub cache_creation_input_token_cost_above_272k_tokens_ultrafast: Option, + pub cache_creation_input_token_cost_flex: Option, + pub cache_creation_input_token_cost_priority: Option, + pub cache_creation_input_token_cost_ultrafast: Option, + pub cache_read_input_token_cost: Option, + pub cache_read_input_audio_token_cost: Option, + pub cache_read_input_audio_token_cost_flex: Option, + pub cache_read_input_audio_token_cost_priority: Option, + pub cache_read_input_audio_token_cost_batches: Option, + pub explicit_cache_read_input_token_cost: Option, + pub prompt_cache_min_tokens: Option, + pub cache_read_input_token_cost_above_200k_tokens: Option, + pub cache_read_input_token_cost_above_200k_tokens_priority: Option, + pub cache_read_input_token_cost_above_272k_tokens: Option, + pub cache_read_input_token_cost_above_272k_tokens_priority: Option, + pub cache_read_input_token_cost_above_272k_tokens_flex: Option, + pub cache_read_input_token_cost_above_272k_tokens_ultrafast: Option, + pub cache_read_input_token_cost_above_512k_tokens: Option, + pub cache_read_input_token_cost_flex: Option, + pub cache_read_input_token_cost_priority: Option, + pub cache_read_input_token_cost_balanced: Option, + pub cache_read_input_token_cost_ultrafast: Option, + pub cache_read_input_token_cost_batches: Option, + pub cache_read_input_token_cost_above_200k_tokens_batches: Option, + pub cache_read_input_token_cost_above_272k_tokens_batches: Option, + pub cache_creation_input_token_cost_batches: Option, + pub cache_creation_input_token_cost_above_200k_tokens_batches: Option, + pub cache_creation_input_token_cost_above_272k_tokens_batches: Option, + pub cache_creation_input_token_cost_above_1hr: Option, + pub cache_creation_input_token_cost_above_12hr: Option, + pub cache_creation_input_token_cost_above_12hr_flex: Option, + pub cache_creation_input_token_cost_above_12hr_priority: Option, + pub cache_creation_input_token_cost_above_12hr_above_272k_tokens: Option, + pub cache_creation_input_token_cost_above_12hr_above_272k_tokens_flex: Option, + pub cache_creation_input_token_cost_above_12hr_above_272k_tokens_priority: Option, + pub cache_creation_input_token_cost_above_12hr_batches: Option, + pub cache_creation_input_token_cost_above_12hr_ultrafast: Option, + pub cache_creation_input_token_cost_above_12hr_above_272k_tokens_batches: Option, + pub cache_creation_input_token_cost_above_12hr_above_272k_tokens_ultrafast: Option, + pub off_peak_pricing: Option, + pub input_cost_per_character: Option, + pub input_cost_per_token_above_128k_tokens: Option, + pub input_cost_per_token_above_200k_tokens: Option, + pub input_cost_per_token_above_200k_tokens_priority: Option, + pub input_cost_per_token_above_272k_tokens: Option, + pub input_cost_per_token_above_272k_tokens_priority: Option, + pub input_cost_per_token_above_272k_tokens_flex: Option, + pub input_cost_per_token_above_272k_tokens_ultrafast: Option, + pub input_cost_per_token_above_512k_tokens: Option, + pub input_cost_per_query: Option, + pub cost_per_second: Option, + pub input_cost_per_second: Option, + pub input_cost_per_text_message: Option, + pub input_cost_per_audio_token: Option, + pub input_cost_per_audio_token_flex: Option, + pub input_cost_per_audio_token_priority: Option, + pub input_cost_per_image_token: Option, pub input_cost_per_video_token: Option, - #[serde(skip_serializing_if = "Option::is_none")] + pub input_cost_per_audio_token_batches: Option, + pub input_cost_per_image_token_batches: Option, + pub input_cost_per_image: Option, + pub input_cost_per_audio_per_second: Option, + pub input_cost_per_video_per_second: Option, + pub input_cost_per_token_batches: Option, pub input_cost_per_video_token_batches: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub input_dbu_cost_per_token: Option, - /// LiteLLM provider slug; one of https://docs.litellm.ai/docs/providers. - #[serde(skip_serializing_if = "Option::is_none")] - pub litellm_provider: Option, - /// Maximum prompt/context tokens the model accepts. - #[serde(skip_serializing_if = "Option::is_none")] - pub max_input_tokens: Option, - /// Maximum tokens the model can generate in one response. - #[serde(skip_serializing_if = "Option::is_none")] - pub max_output_tokens: Option, - /// Legacy field: max output tokens if the provider specifies it, else max input tokens. - #[serde(skip_serializing_if = "Option::is_none")] - pub max_tokens: Option, - /// Free-form notes about the entry (e.g. pricing derivation). - #[serde(skip_serializing_if = "Option::is_none")] - pub metadata: Option>, - /// Primary API surface / task type of the model. - #[serde(skip_serializing_if = "Option::is_none")] - pub mode: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub ocr_cost_per_credit: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub ocr_cost_per_page: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub ocr_cost_per_page_batches: Option, - /// Rates that replace the same-named base fields while the request falls inside the stated UTC windows. - #[serde(skip_serializing_if = "Option::is_none")] - pub off_peak_pricing: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub output_cost_per_audio_token: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub output_cost_per_character: Option, - /// Rate applied once the prompt exceeds the token threshold in the field name. - #[serde(skip_serializing_if = "Option::is_none")] - pub output_cost_per_character_above_128k_tokens: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub output_cost_per_image: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub output_cost_per_image_1024: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub output_cost_per_image_1536: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub output_cost_per_image_512: Option, - #[serde( - rename = "output_cost_per_image_0.5K", - skip_serializing_if = "Option::is_none" - )] - pub output_cost_per_image_0_5k: Option, - #[serde( - rename = "output_cost_per_image_1K", - skip_serializing_if = "Option::is_none" - )] - pub output_cost_per_image_1k: Option, - #[serde( - rename = "output_cost_per_image_2K", - skip_serializing_if = "Option::is_none" - )] - pub output_cost_per_image_2k: Option, - #[serde( - rename = "output_cost_per_image_4K", - skip_serializing_if = "Option::is_none" - )] - pub output_cost_per_image_4k: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub output_cost_per_image_token: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub output_cost_per_pixel: Option, - /// USD per reasoning/thinking token, when billed separately. - #[serde(skip_serializing_if = "Option::is_none")] - pub output_cost_per_reasoning_token: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub output_cost_per_second: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub output_cost_per_second_1080p: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub output_cost_per_second_2k: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub output_cost_per_second_480p: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub output_cost_per_second_4k: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub output_cost_per_second_720p: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub output_cost_per_second_768p: Option, - /// USD per generated token. - #[serde(skip_serializing_if = "Option::is_none")] - pub output_cost_per_token: Option, - /// Rate applied once the prompt exceeds the token threshold in the field name. - #[serde(skip_serializing_if = "Option::is_none")] - pub output_cost_per_token_above_32k_tokens: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub output_cost_per_token_above_100k_tokens: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub output_cost_per_token_above_100k_tokens_batches: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub output_cost_per_token_above_128k_tokens: Option, - /// Rate applied once the prompt exceeds the token threshold in the field name. - #[serde(skip_serializing_if = "Option::is_none")] - pub output_cost_per_token_above_200k_tokens: Option, - /// Rate applied once the prompt exceeds the token threshold in the field name. - #[serde(skip_serializing_if = "Option::is_none")] - pub output_cost_per_token_above_200k_tokens_batches: Option, - /// Priority service-tier rate for the same-named base field. - #[serde(skip_serializing_if = "Option::is_none")] - pub output_cost_per_token_above_200k_tokens_priority: Option, - /// Rate applied once the prompt exceeds the token threshold in the field name. - #[serde(skip_serializing_if = "Option::is_none")] - pub output_cost_per_token_above_256k_tokens: Option, - /// Rate applied once the prompt exceeds the token threshold in the field name. - #[serde(skip_serializing_if = "Option::is_none")] - pub output_cost_per_token_above_272k_tokens: Option, - /// Rate applied once the prompt exceeds the token threshold in the field name. - #[serde(skip_serializing_if = "Option::is_none")] - pub output_cost_per_token_above_272k_tokens_batches: Option, - /// Flex service-tier rate for the same-named base field. - #[serde(skip_serializing_if = "Option::is_none")] - pub output_cost_per_token_above_272k_tokens_flex: Option, - /// Priority service-tier rate for the same-named base field. - #[serde(skip_serializing_if = "Option::is_none")] - pub output_cost_per_token_above_272k_tokens_priority: Option, - /// Ultrafast service-tier rate for the same-named base field. - #[serde(skip_serializing_if = "Option::is_none")] - pub output_cost_per_token_above_272k_tokens_ultrafast: Option, - /// Rate applied once the prompt exceeds the token threshold in the field name. - #[serde(skip_serializing_if = "Option::is_none")] - pub output_cost_per_token_above_512k_tokens: Option, - /// Balanced service-tier rate for the same-named base field. - #[serde(skip_serializing_if = "Option::is_none")] - pub output_cost_per_token_balanced: Option, - /// USD per generated token via the provider's batch API. - #[serde(skip_serializing_if = "Option::is_none")] + pub input_cost_per_token_above_200k_tokens_batches: Option, + pub input_cost_per_token_above_272k_tokens_batches: Option, pub output_cost_per_token_batches: Option, - /// Flex service-tier rate for the same-named base field. - #[serde(skip_serializing_if = "Option::is_none")] + pub output_cost_per_token_above_200k_tokens_batches: Option, + pub output_cost_per_token_above_272k_tokens_batches: Option, + pub output_cost_per_token: Option, pub output_cost_per_token_flex: Option, - /// Priority service-tier rate for the same-named base field. - #[serde(skip_serializing_if = "Option::is_none")] pub output_cost_per_token_priority: Option, - /// Ultrafast service-tier rate for the same-named base field. - #[serde(skip_serializing_if = "Option::is_none")] + pub output_cost_per_token_balanced: Option, pub output_cost_per_token_ultrafast: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub output_cost_per_video_per_second: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub output_cost_per_video_token: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub output_dbu_cost_per_token: Option, - /// Embedding dimension for embedding models. - #[serde(skip_serializing_if = "Option::is_none")] - pub output_vector_size: Option, - /// Smallest prefix the provider will actually cache; absent means the provider default applies. - #[serde(skip_serializing_if = "Option::is_none")] - pub prompt_cache_min_tokens: Option, - /// Provider-internal routing hints (e.g. bedrock_invocation_schema). - #[serde(skip_serializing_if = "Option::is_none")] - pub provider_specific_entry: Option>, - /// Exact reasoning_effort levels this deployment accepts; wins over supports_* flags. - #[serde(skip_serializing_if = "Option::is_none")] - pub reasoning_effort_levels: Option>, - /// Multiplier applied to all token costs when served from a non-global Vertex AI endpoint (e.g. 1.10 = +10%). - #[serde(skip_serializing_if = "Option::is_none")] - pub regional_endpoint_uplift_multiplier: Option, - /// Multiplier applied to all token costs for EU data residency (e.g. 1.10 = +10%). - #[serde(skip_serializing_if = "Option::is_none")] pub regional_processing_uplift_multiplier_eu: Option, - /// Multiplier applied to all token costs for US data residency (e.g. 1.10 = +10%). - #[serde(skip_serializing_if = "Option::is_none")] pub regional_processing_uplift_multiplier_us: Option, - /// Provider default requests-per-minute limit. - #[serde(skip_serializing_if = "Option::is_none")] - pub rpm: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub rules: Option>, - /// USD cost per web search query, keyed by search context size. - #[serde(skip_serializing_if = "Option::is_none")] - pub search_context_cost_per_query: Option, - /// URL of the provider pricing/model page this entry was taken from. - #[serde(skip_serializing_if = "Option::is_none")] - pub source: Option, - /// Audio container formats the model can return. - #[serde(skip_serializing_if = "Option::is_none")] - pub supported_audio_formats: Option>, - /// OpenAI-style API routes this model can be called through, e.g. /v1/chat/completions. - #[serde(skip_serializing_if = "Option::is_none")] + pub regional_endpoint_uplift_multiplier: Option, + pub output_cost_per_audio_token: Option, + pub output_cost_per_character: Option, + pub output_cost_per_reasoning_token: Option, + pub output_cost_per_reasoning_token_flex: Option, + pub output_cost_per_reasoning_token_priority: Option, + pub output_cost_per_token_above_128k_tokens: Option, + pub output_cost_per_character_above_128k_tokens: Option, + pub output_cost_per_token_above_200k_tokens: Option, + pub output_cost_per_token_above_200k_tokens_priority: Option, + pub output_cost_per_token_above_272k_tokens: Option, + pub output_cost_per_token_above_272k_tokens_priority: Option, + pub output_cost_per_token_above_272k_tokens_flex: Option, + pub output_cost_per_token_above_272k_tokens_ultrafast: Option, + pub output_cost_per_token_above_512k_tokens: Option, + pub output_cost_per_second: Option, + pub output_cost_per_second_1080p: Option, + pub output_cost_per_second_480p: Option, + pub output_cost_per_second_720p: Option, + pub output_cost_per_second_768p: Option, + pub output_cost_per_second_2k: Option, + pub output_cost_per_second_4k: Option, + pub output_cost_per_video_per_second: Option, + pub output_cost_per_image: Option, + pub output_cost_per_pixel: Option, + pub output_cost_per_image_token: Option, + pub output_cost_per_image_token_batches: Option, + pub output_cost_per_video_token: Option, + pub output_vector_size: Option, + pub citation_cost_per_token: Option, + pub tiered_pricing: Option, + pub litellm_provider: Option, + pub mode: Option, pub supported_endpoints: Option>, - /// Input modalities the model accepts. - #[serde(skip_serializing_if = "Option::is_none")] - pub supported_modalities: Option>, - /// Output modalities the model can produce. - #[serde(skip_serializing_if = "Option::is_none")] - pub supported_output_modalities: Option>, - /// Cloud regions the model is available in ('global' or region ids). - #[serde(skip_serializing_if = "Option::is_none")] - pub supported_regions: Option>, - #[serde(skip_serializing_if = "Option::is_none")] - pub supports_adaptive_thinking: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub supports_anthropic_compaction: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub supports_anthropic_thinking_payload: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub supports_assistant_prefill: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub supports_audio_input: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub supports_audio_output: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub supports_bedrock_runtime_chat_completions_response_format: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub supports_bedrock_runtime_chat_completions_tools_with_reasoning: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub supports_computer_use: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub supports_embedding_image_input: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub supports_fast_mode: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub supports_forced_tool_use: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub supports_function_calling: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub supports_image_input: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub supports_image_size: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub supports_legacy_thinking: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub supports_low_reasoning_effort: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub supports_max_reasoning_effort: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub supports_mid_conversation_system: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub supports_minimal_reasoning_effort: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub supports_multimodal: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub supports_native_streaming: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub supports_native_structured_output: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub supports_none_reasoning_effort: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub supports_nova_canvas_image_edit: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub supports_output_config: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub supports_parallel_function_calling: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub supports_parallel_tool_use_config: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub supports_pdf_input: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub supports_prompt_cache_breakpoint: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub supports_prompt_caching: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub supports_reasoning: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub supports_response_schema: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub supports_sampling_params: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub supports_speed: Option, - #[serde(skip_serializing_if = "Option::is_none")] pub supports_system_messages: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub supports_thinking_cache_preservation: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub supports_tool_choice: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub supports_tool_search: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub supports_url_context: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub supports_video_input: Option, - #[serde(skip_serializing_if = "Option::is_none")] + pub supports_response_schema: Option, pub supports_vision: Option, - #[serde(skip_serializing_if = "Option::is_none")] + pub supports_function_calling: Option, + pub supports_parallel_function_calling: Option, + pub supports_tool_choice: Option, + pub supports_assistant_prefill: Option, + pub supports_prompt_caching: Option, + pub supports_prompt_cache_breakpoint: Option, + pub supports_thinking_cache_preservation: Option, + pub supports_audio_input: Option, + pub supports_video_input: Option, + pub supports_box_questions: Option, + pub supports_audio_output: Option, + pub supports_pdf_input: Option, + pub supports_embedding_image_input: Option, + pub supports_native_streaming: Option, + pub supports_native_structured_output: Option, + pub supports_bedrock_native_structured_output: Option, pub supports_web_search: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub supports_xhigh_reasoning_effort: Option, - #[serde(skip_serializing_if = "Option::is_none")] + pub supports_url_context: Option, + pub supports_reasoning: Option, + pub supports_adaptive_thinking: Option, + pub supports_legacy_thinking: Option, pub thinking_always_on: Option, - /// Context-length or result-count tiered rates; each tier's costs apply within its range. - #[serde(skip_serializing_if = "Option::is_none")] - pub tiered_pricing: Option>, - /// Provider default tokens-per-minute limit. - #[serde(skip_serializing_if = "Option::is_none")] - pub tpm: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub use_openai_responses_path: Option, - #[serde(skip_serializing_if = "Option::is_none")] + pub supports_tool_search: Option, + pub supports_mid_conversation_system: Option, + pub supports_anthropic_thinking_payload: Option, + pub supports_anthropic_compaction: Option, + pub supports_none_reasoning_effort: Option, + pub supports_minimal_reasoning_effort: Option, + pub supports_low_reasoning_effort: Option, + pub supports_xhigh_reasoning_effort: Option, + pub supports_max_reasoning_effort: Option, + pub reasoning_effort_levels: Option, + pub default_reasoning_effort: Option, + pub bedrock_output_config_effort_ceiling: Option, + pub bedrock_converse_supports_strict_tools: Option, + pub supports_regex_lookaround: Option, + pub supports_computer_use: Option, + pub search_context_cost_per_query: Option, + pub web_search_billing_unit: Option, + pub search_free_requests: Option, + pub google_maps_grounding_cost_per_query: Option, + pub tpm: Option, + pub rpm: Option, + pub ocr_cost_per_page: Option, + pub ocr_cost_per_page_batches: Option, + pub ocr_cost_per_credit: Option, + pub annotation_cost_per_page: Option, + pub annotation_cost_per_page_batches: Option, + pub provider_specific_entry: Option, pub uses_embed_content: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub vector_store_cost_per_gb_per_day: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub vertex_ai_audio_api: Option, - /// Whether web search is billed per query or per prompt. - #[serde(skip_serializing_if = "Option::is_none")] - pub web_search_billing_unit: Option, + pub supports_image_size: Option, + pub supported_audio_formats: Option, + pub token_count_framing: Option, + pub token_count_model: Option, + pub token_count_tokenizer: Option, + pub vertex_ai_audio_api: Option, + /// Every key matching `ABOVE_THRESHOLD_COST_KEY_PATTERN`, copied as written + pub above_threshold_costs: IndexMap, } diff --git a/litellm-rust/crates/model-catalog/src/pricing.rs b/litellm-rust/crates/model-catalog/src/pricing.rs deleted file mode 100644 index b8ed652451c..00000000000 --- a/litellm-rust/crates/model-catalog/src/pricing.rs +++ /dev/null @@ -1,97 +0,0 @@ -use serde::{Deserialize, Serialize}; - -/// Whether web search is billed per query or per prompt. -#[derive(Clone, Copy, Debug, Deserialize, Eq, PartialEq, Serialize)] -#[cfg_attr(feature = "schema", derive(schemars::JsonSchema))] -#[serde(rename_all = "snake_case")] -pub enum WebSearchBillingUnit { - PerQuery, - PerPrompt, -} - -/// UTC "HH:MM-HH:MM" window, or a list of them; a window may wrap past midnight. -#[derive(Clone, Debug, Deserialize, PartialEq, Serialize)] -#[cfg_attr(feature = "schema", derive(schemars::JsonSchema))] -#[serde(untagged)] -pub enum UtcHours { - Single(String), - Multiple(Vec), -} - -/// ISO-8601 weekday number (1 = Monday .. 7 = Sunday) or English day name. -#[derive(Clone, Debug, Deserialize, PartialEq, Serialize)] -#[cfg_attr(feature = "schema", derive(schemars::JsonSchema))] -#[serde(untagged)] -pub enum Weekday { - Number(u8), - Name(String), -} - -/// One off-peak window entry inside `windows`. -#[derive(Clone, Debug, Deserialize, PartialEq, Serialize)] -#[cfg_attr(feature = "schema", derive(schemars::JsonSchema))] -#[serde(deny_unknown_fields)] -pub struct OffPeakWindow { - pub hours_utc: UtcHours, - #[serde(skip_serializing_if = "Option::is_none")] - pub weekdays: Option>, -} - -/// Rates that replace the same-named base fields inside the stated UTC windows. -#[derive(Clone, Debug, Default, Deserialize, PartialEq, Serialize)] -#[cfg_attr(feature = "schema", derive(schemars::JsonSchema))] -#[serde(deny_unknown_fields)] -pub struct OffPeakPricing { - #[serde(skip_serializing_if = "Option::is_none")] - pub hours_utc: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub windows: Option>, - #[serde(skip_serializing_if = "Option::is_none")] - pub weekday_timezone: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub input_cost_per_token: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub output_cost_per_token: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub output_cost_per_reasoning_token: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub cache_read_input_token_cost: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub cache_creation_input_token_cost: Option, -} - -/// USD cost per web search query, keyed by search context size. -#[derive(Clone, Debug, Default, Deserialize, PartialEq, Serialize)] -#[cfg_attr(feature = "schema", derive(schemars::JsonSchema))] -#[serde(deny_unknown_fields)] -pub struct SearchContextCostPerQuery { - #[serde(skip_serializing_if = "Option::is_none")] - pub search_context_size_low: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub search_context_size_medium: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub search_context_size_high: Option, -} - -/// One tier of a context-length or result-count tiered rate. -#[derive(Clone, Debug, Default, Deserialize, PartialEq, Serialize)] -#[cfg_attr(feature = "schema", derive(schemars::JsonSchema))] -#[serde(deny_unknown_fields)] -pub struct TieredRate { - #[serde(skip_serializing_if = "Option::is_none")] - pub range: Option<[f64; 2]>, - #[serde(skip_serializing_if = "Option::is_none")] - pub max_results_range: Option<[f64; 2]>, - #[serde(skip_serializing_if = "Option::is_none")] - pub input_cost_per_token: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub output_cost_per_token: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub output_cost_per_reasoning_token: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub cache_read_input_token_cost: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub cache_creation_input_token_cost: Option, - #[serde(skip_serializing_if = "Option::is_none")] - pub input_cost_per_query: Option, -} diff --git a/litellm-rust/crates/model-catalog/src/register.rs b/litellm-rust/crates/model-catalog/src/register.rs new file mode 100644 index 00000000000..ed34082ae57 --- /dev/null +++ b/litellm-rust/crates/model-catalog/src/register.rs @@ -0,0 +1,26 @@ +use std::collections::{BTreeSet, HashMap}; + +use indexmap::IndexMap; + +use crate::wire::Fields; + +/// Where one `register` call writes and which row it inherits from +#[derive(Clone, Debug, PartialEq, Eq)] +pub struct RegistrationTarget { + /// Always the caller's key, never a case variant of it + pub write: String, + /// The first candidate that is an exact key whose row passes `provider_matches` + pub inherit_from: Option, +} + +/// Python's inheritance candidates in main's order, `get_model_info`'s then `_resolve_builtin_model_cost_entry`'s +#[derive(Clone, Debug, PartialEq, Eq)] +pub struct RegistrationCandidates(pub Vec); + +/// Layer 3, and the fields `register` last wrote, which litellm owns again +#[derive(Clone, Debug, Default)] +#[expect(dead_code, reason = "07 adds the functions that read registrations")] +pub struct Registrations { + persisted: IndexMap, + registered_fields: HashMap>, +} diff --git a/litellm-rust/crates/model-catalog/src/resolve/image.rs b/litellm-rust/crates/model-catalog/src/resolve/image.rs new file mode 100644 index 00000000000..d24e170b32c --- /dev/null +++ b/litellm-rust/crates/model-catalog/src/resolve/image.rs @@ -0,0 +1,18 @@ +/// What an image call asks for. `resolve_image` builds main's eight key spellings from it +#[derive(Clone, Debug, PartialEq, Eq)] +pub struct ImageCandidates { + pub model: String, + pub provider: Option, + /// Width and height, `1024 x 1024` when the request names none, as on main + pub size: Option<(u32, u32)>, + pub quality: Option, +} + +/// A size and quality keyed row, `{quality}/{W}-x-{H}/{model}`, parsed once per index build for fal's nearest match +#[derive(Clone, Debug, PartialEq, Eq)] +pub struct ImageKey { + pub quality: Option, + pub width: u32, + pub height: u32, + pub model: String, +} diff --git a/litellm-rust/crates/model-catalog/src/resolve/mod.rs b/litellm-rust/crates/model-catalog/src/resolve/mod.rs new file mode 100644 index 00000000000..fbaead622aa --- /dev/null +++ b/litellm-rust/crates/model-catalog/src/resolve/mod.rs @@ -0,0 +1,46 @@ +mod image; + +pub use image::*; + +/// The seven names main's `get_model_info` tries, built by Python, walked in this order by Rust +#[derive(Clone, Debug, Default, PartialEq, Eq)] +pub struct Candidates { + pub combined_model_name: Option, + pub model: String, + pub region_free_combined_model_name: Option, + pub split_model: Option, + pub combined_stripped_model_name: Option, + pub stripped_model_name: Option, + pub provider_prefixed_model_name: Option, +} + +#[derive(Clone, Copy, Debug, PartialEq, Eq)] +pub enum CandidateSlot { + CombinedModelName, + Model, + RegionFreeCombinedModelName, + SplitModel, + CombinedStrippedModelName, + StrippedModelName, + ProviderPrefixedModelName, +} + +/// Which step matched, so a test can name the step that changed +#[derive(Clone, Copy, Debug, PartialEq, Eq)] +pub struct Via { + pub slot: CandidateSlot, + /// Matched through the case-insensitive index rather than an exact key + pub case_insensitive: bool, +} + +#[derive(Clone, Debug, PartialEq, Eq)] +pub enum Resolution { + Found { + key: String, + via: Via, + }, + /// Every candidate tried, in order + Missing { + tried: Vec, + }, +} diff --git a/litellm-rust/crates/model-catalog/src/schema.rs b/litellm-rust/crates/model-catalog/src/schema.rs index 7de988b3ff3..66f9933a3e3 100644 --- a/litellm-rust/crates/model-catalog/src/schema.rs +++ b/litellm-rust/crates/model-catalog/src/schema.rs @@ -1,9 +1,80 @@ -use schemars::Schema; +use std::collections::BTreeMap; + +use litellm_cost::money::{Multiplier, UnitPrice}; +use schemars::{JsonSchema, Schema}; use serde_json::{Map, Value, json}; +use crate::fallback::FallbackGeneralizations; +use crate::wire::{Attributes, OffPeakWindow, SearchContextCostPerQuery, UtcHours}; + +#[derive(JsonSchema)] +#[schemars(rename = "ModelEntry")] +struct ModelEntry { + #[serde(flatten)] + _attributes: Attributes, + #[serde(flatten)] + _blocks: PriceBlocks, +} + +#[derive(JsonSchema)] +#[allow(dead_code)] +struct PriceBlocks { + /// USD cost per billable guardrail unit, keyed by the provider's usage counter name (e.g. Bedrock's contentPolicyUnits). + guardrail_cost_per_unit: Option>, + /// Rates that replace the same-named base fields while the request falls inside the stated UTC windows. + off_peak_pricing: Option, + /// Multiplier applied to all token costs when served from a non-global Vertex AI endpoint (e.g. 1.10 = +10%). + regional_endpoint_uplift_multiplier: Option, + /// Multiplier applied to all token costs for EU data residency (e.g. 1.10 = +10%). + regional_processing_uplift_multiplier_eu: Option, + /// Multiplier applied to all token costs for US data residency (e.g. 1.10 = +10%). + regional_processing_uplift_multiplier_us: Option, + /// USD cost per web search query, keyed by search context size. + search_context_cost_per_query: Option, + /// Context-length or result-count tiered rates; each tier's costs apply within its range. + tiered_pricing: Option>, +} + +/// Rates that replace the same-named base fields inside the stated UTC windows. +#[derive(JsonSchema)] +#[allow(dead_code)] +struct OffPeakPricing { + hours_utc: Option, + windows: Option>, + weekday_timezone: Option, +} + +/// One tier of a context-length or result-count tiered rate. +#[derive(JsonSchema)] +#[allow(dead_code)] +struct TieredRate { + range: Option<[u64; 2]>, + max_results_range: Option<[u64; 2]>, +} + +#[derive(JsonSchema)] +#[allow(dead_code)] +struct RegistryDocument { + sample_spec: Option>, + fallback_generalizations: Option, +} + +pub(crate) const FLAT_KEY_PATTERN: &str = concat!( + r"^(", + r"input_cost_per_((audio_|image_|video_)?token|character|image|pixel|query|request|second|text_message|audio_per_second|video_per_second(_above_\d+s_interval)?)", + r"|output_cost_per_((audio_|image_|video_|reasoning_)?token|character|image(_\d+(\.\d+)?K?)?|pixel|second(_\d+[pk])?|video_per_second)", + r"|cache_read_input_(audio_|image_|video_)?token_cost", + r"|explicit_cache_read_input_token_cost", + r"|cache_creation_input_(audio_|image_|video_)?token_cost(_above_1hr|_above_12hr)?", + r"|annotation_cost_per_page|citation_cost_per_token|code_interpreter_cost_per_session", + r"|google_maps_grounding_cost_per_query|ocr_cost_per_credit|ocr_cost_per_page|cost_per_second", + r"|browser_open_cost_per_request|cost_per_additional_result", + r")(_above_\d+k?_tokens)?(_(priority|flex|ultrafast|balanced|batches|decisions))?$", +); + /// JSON Schema for one model entry, including registry validation constraints. pub fn model_entry_json_schema() -> Schema { - let mut schema = serde_json::to_value(schemars::schema_for!(crate::ModelInfo)) + let mut schema = serde_json::to_value(schemars::schema_for!(ModelEntry)) .expect("derived model schema serializes"); remove_nullable_optional_fields(&mut schema); decorate_model_entry(&mut schema); @@ -22,24 +93,21 @@ pub fn registry_json_schema() -> Schema { entry.as_object_mut().unwrap().remove("$schema"); definitions.insert("modelEntry".into(), entry); - let mut fallback = serde_json::to_value(schemars::schema_for!(crate::FallbackGeneralizations)) - .expect("derived fallback schema serializes"); - remove_nullable_optional_fields(&mut fallback); - definitions.extend(take_definitions(&mut fallback)); - fallback.as_object_mut().unwrap().remove("$schema"); - - let root = json!({ - "$schema": "https://json-schema.org/draft/2020-12/schema", - "title": "LiteLLM model prices and context window registry", - "type": "object", - "properties": { - "sample_spec": {"type": "object"}, - "fallback_generalizations": fallback - }, - "additionalProperties": {"$ref": "#/$defs/modelEntry"}, - "$defs": definitions - }); - Schema::from(root.as_object().unwrap().clone()) + let mut registry = serde_json::to_value(schemars::schema_for!(RegistryDocument)) + .expect("derived registry schema serializes"); + remove_nullable_optional_fields(&mut registry); + definitions.extend(take_definitions(&mut registry)); + let root = registry.as_object_mut().unwrap(); + root.insert( + "title".into(), + "LiteLLM model prices and context window registry".into(), + ); + root.insert( + "additionalProperties".into(), + json!({"$ref": "#/$defs/modelEntry"}), + ); + root.insert("$defs".into(), Value::Object(definitions)); + Schema::from(root.clone()) } fn take_definitions(schema: &mut Value) -> Map { @@ -80,42 +148,21 @@ fn remove_nullable_optional_fields(value: &mut Value) { } fn decorate_model_entry(schema: &mut Value) { + let rates = json!({FLAT_KEY_PATTERN: {"type": "number", "minimum": 0}}); let object = schema.as_object_mut().unwrap(); object.insert("required".into(), json!(["litellm_provider"])); object.insert("additionalProperties".into(), Value::Bool(true)); - let properties = object - .get_mut("properties") - .unwrap() - .as_object_mut() - .unwrap(); - properties.insert( - "aliases".into(), - json!({"type": "array", "items": {"type": "string"}}), + object.insert( + "patternProperties".into(), + json!({ + FLAT_KEY_PATTERN: {"type": "number", "minimum": 0}, + "^supports_": {"type": "boolean"}, + }), ); - properties.get_mut("deprecation_date").unwrap()["format"] = json!("date"); - properties.get_mut("deprecation_date").unwrap()["pattern"] = - json!(r"^\d{4}-(0[1-9]|1[0-2])-(0[1-9]|[12]\d|3[01])$"); - - properties.iter_mut().for_each(|(name, property)| { - if name.contains("cost") { - property["minimum"] = json!(0); - } else if name.contains("uplift_multiplier") { - property["minimum"] = json!(1); - } - }); - properties.get_mut("guardrail_cost_per_unit").unwrap()["additionalProperties"]["minimum"] = - json!(0); - let definitions = object.get_mut("$defs").unwrap().as_object_mut().unwrap(); - for definition in ["OffPeakPricing", "TieredRate", "SearchContextCostPerQuery"] { - let properties = definitions[definition]["properties"] - .as_object_mut() - .unwrap(); - properties.iter_mut().for_each(|(name, property)| { - if name.contains("cost") || definition == "SearchContextCostPerQuery" { - property["minimum"] = json!(0); - } - }); + for definition in ["OffPeakPricing", "TieredRate"] { + definitions[definition]["patternProperties"] = rates.clone(); + definitions[definition]["additionalProperties"] = Value::Bool(false); } definitions["OffPeakPricing"]["anyOf"] = json!([ {"required": ["hours_utc"]}, @@ -123,15 +170,43 @@ fn decorate_model_entry(schema: &mut Value) { ]); definitions["OffPeakPricing"]["properties"]["windows"]["minItems"] = json!(1); definitions["OffPeakWindow"]["properties"]["weekdays"]["minItems"] = json!(1); - definitions["TieredRate"]["properties"]["range"]["items"]["minimum"] = json!(0); - definitions["TieredRate"]["properties"]["max_results_range"]["items"]["minimum"] = json!(0); - definitions["Weekday"]["anyOf"][0]["minimum"] = json!(1); - definitions["Weekday"]["anyOf"][0]["maximum"] = json!(7); - definitions["Weekday"]["anyOf"][1]["pattern"] = json!( - r"(?i)^(mon|monday|tue|tues|tuesday|wed|wednesday|thu|thur|thurs|thursday|fri|friday|sat|saturday|sun|sunday)$" - ); - let window_pattern = json!(r"^([01]\d|2[0-3]):[0-5]\d-([01]\d|2[0-3]):[0-5]\d$"); - definitions["UtcHours"]["anyOf"][0]["pattern"] = window_pattern.clone(); - definitions["UtcHours"]["anyOf"][1]["items"]["pattern"] = window_pattern; definitions["UtcHours"]["anyOf"][1]["minItems"] = json!(1); } + +#[cfg(test)] +mod tests { + use rstest::rstest; + + use super::FLAT_KEY_PATTERN; + use crate::wire::FlatKey; + + #[rstest] + #[case::input_token("input_cost_per_token")] + #[case::cache_write_one_hour_band( + "cache_creation_input_token_cost_above_1hr_above_200k_tokens" + )] + #[case::image_label("output_cost_per_image_0.5K")] + #[case::resolution_tier("output_cost_per_second_4k_flex")] + #[case::feature_batch("annotation_cost_per_page_batches")] + #[case::video_interval("input_cost_per_video_per_second_above_8s_interval")] + #[case::explicit_cache_read("explicit_cache_read_input_token_cost")] + #[case::wall_clock("cost_per_second")] + #[case::unused_meter("cost_per_token")] + #[case::other_currency("input_dbu_cost_per_token")] + #[case::typo("input_cost_per_tokne")] + #[case::read_has_no_ttl("cache_read_input_token_cost_above_1hr")] + #[case::interval_on_a_token_meter("input_cost_per_token_above_8s_interval")] + fn flat_key_pattern_agrees_with_the_parser(#[case] key: &str) { + let schema = serde_json::json!({ + "type": "object", + "patternProperties": {FLAT_KEY_PATTERN: {}}, + "additionalProperties": false, + }); + let validator = jsonschema::validator_for(&schema).unwrap(); + + assert_eq!( + validator.is_valid(&serde_json::json!({key: 1})), + FlatKey::parse(key).is_some() + ); + } +} diff --git a/litellm-rust/crates/model-catalog/src/store/AGENTS.md b/litellm-rust/crates/model-catalog/src/store/AGENTS.md new file mode 100644 index 00000000000..f1dacd2e217 --- /dev/null +++ b/litellm-rust/crates/model-catalog/src/store/AGENTS.md @@ -0,0 +1,35 @@ +# Store + +`Store` is an in-memory store, a small database built for exactly three queries. It knows nothing about the catalog. A source picks its own `Rows::Row` type, how names fold for matching, and the group each key is listed under. The catalog's sources fold to lowercase and group by raw `litellm_provider` + +| Query | Method | Real caller | +|---|---|---| +| row by exact key | `Store::get` | reading `litellm.model_cost["gpt-4o"]` | +| actual key for a name that folds to the same form | `Store::find_key` | `get_model_info("GPT-4o")` finding `gpt-4o` | +| keys in a group | `Store::keys_in` | the provider sets, `litellm.open_ai_chat_completion_models` | + +## Rules + +- nothing in `store/` imports from the rest of the crate. Wire types, case rules and field names such as `litellm_provider` belong to the source that implements `Rows` +- the index in `name_index.rs` is private to the store. Never build a folded-name map or a provider grouping anywhere else in the workspace. A new lookup pattern is a new `Store` method backed by `NameIndex` +- the index holds keys, never rows. Rows are always read from `Rows`, so a price edit is seen on the next read and never rebuilds the index +- `find_key` and `keys_in` never return a key the rows lack. A hit on a removed key rebuilds the index once and asks again +- `keys_in` matches the group exactly as the source wrote it. Provider aliases such as `vertex_ai` over `vertex_ai-language-models` are Python's job +- when two keys fold to the same name the later key in row order wins, like main's `_model_cost_lowercase_map` + +## Stamps + +`Rows::stamp` is how the store learns that the index may be stale. The store keeps the stamp it built the index at and rebuilds when the source returns a different one. A source must change its stamp whenever a key or a key's group changes, since those are the two things the index holds + +| Source | Stamp | Blind spot | +|---|---|---| +| `Catalog`'s `CatalogRows` | `()`, every change goes through `Store::edit`, which drops the index | none | +| python-bridge's bound `litellm.model_cost` | the dict object and its `len` | a delete plus an add between two reads, or a `litellm_provider` rewrite on an existing key | + +A source with a blind spot calls `Store::invalidate` when it knows keys changed. Until then a key added in the blind spot is not found, and a key moved to another provider stays listed under the old one. Removed keys are still never returned + +## Tests + +Tests live in `mod.rs`'s `tests` module and drive the store through `ModelCost`, a fake `litellm.model_cost` with real bundled keys whose row is just its `litellm_provider`. Each Python write is a method (`set`, `del`, `rebind`) and its stamp is what python-bridge can see. Add a scenario as a named test that reads like the Python user code it stands for + +The two property tests compare every answer with a linear scan of the same dict. With a stamp that sees every key change, answers must match exactly. With the dict stamp, every answer must be sound (present, same folded name), and `invalidate` must make them match again. A store change that fails either is a bug in the store, not in the test diff --git a/litellm-rust/crates/model-catalog/src/store/mod.rs b/litellm-rust/crates/model-catalog/src/store/mod.rs new file mode 100644 index 00000000000..2220526f8b6 --- /dev/null +++ b/litellm-rust/crates/model-catalog/src/store/mod.rs @@ -0,0 +1,460 @@ +mod name_index; + +use std::borrow::Cow; +use std::fmt; +use std::sync::{PoisonError, RwLock}; + +use name_index::NameIndex; + +/// Where a `Store`'s rows live. The store rebuilds its index whenever `stamp` changes, so a source must change its +/// stamp whenever a key or a key's group changes, or call `Store::invalidate` when it cannot +pub trait Rows { + type Row: ToOwned + ?Sized; + type Stamp: PartialEq; + + /// The name two spellings of one key share, which `Store::find_key` matches on + fn fold(name: &str) -> String; + fn stamp(&self) -> Self::Stamp; + fn contains(&self, key: &str) -> bool; + fn row(&self, key: &str) -> Option>; + /// Every key in row order with the group it is listed under + fn scan(&self, visit: &mut dyn FnMut(&str, Option<&str>)); +} + +/// An in-memory store for three queries (row by exact key, actual key for a name by its folded form, keys in a group) +/// that owns the only index behind them +pub struct Store { + rows: R, + index: RwLock>>, +} + +struct Built { + stamp: S, + names: NameIndex, +} + +impl Store { + pub fn new(rows: R) -> Self { + Self { + rows, + index: RwLock::new(None), + } + } + + pub fn rows(&self) -> &R { + &self.rows + } + + /// Changes the rows in place. The index is rebuilt on the next query + pub fn edit(&mut self, edit: impl FnOnce(&mut R) -> T) -> T { + let edited = edit(&mut self.rows); + *self.index.get_mut().unwrap_or_else(PoisonError::into_inner) = None; + edited + } + + pub fn get(&self, key: &str) -> Option> { + self.rows.row(key) + } + + /// The key itself when present, otherwise the actual key that folds to the same name. Never a key the rows lack + pub fn find_key(&self, name: &str) -> Option { + if self.rows.contains(name) { + return Some(name.to_owned()); + } + let folded = R::fold(name); + let hit = self.query(|names| names.key_for(&folded).map(str::to_owned))?; + if self.rows.contains(&hit) { + return Some(hit); + } + self.invalidate(); + self.query(|names| names.key_for(&folded).map(str::to_owned)) + .filter(|key| self.rows.contains(key)) + } + + /// Keys whose group is exactly `group`, in row order. Never a key the rows lack + pub fn keys_in(&self, group: &str) -> Vec { + self.query(|names| names.keys_in(group).to_vec()) + .into_iter() + .filter(|key| self.rows.contains(key)) + .collect() + } + + /// Drops the index, for a source whose stamp cannot see every key change + pub fn invalidate(&self) { + *self.index.write().unwrap_or_else(PoisonError::into_inner) = None; + } + + fn query(&self, read: impl Fn(&NameIndex) -> T) -> T { + let stamp = self.rows.stamp(); + if let Some(built) = self + .index + .read() + .unwrap_or_else(PoisonError::into_inner) + .as_ref() + .filter(|built| built.stamp == stamp) + { + return read(&built.names); + } + let names = NameIndex::scan(&self.rows); + let answer = read(&names); + *self.index.write().unwrap_or_else(PoisonError::into_inner) = Some(Built { stamp, names }); + answer + } +} + +impl Clone for Store { + fn clone(&self) -> Self { + Self::new(self.rows.clone()) + } +} + +impl fmt::Debug for Store { + fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result { + f.debug_struct("Store") + .field("rows", &self.rows) + .finish_non_exhaustive() + } +} + +#[cfg(test)] +mod tests { + use std::cell::{Cell, RefCell}; + + use indexmap::IndexMap; + use rstest::{fixture, rstest}; + + use super::*; + + const BUNDLED: &[(&str, Option<&str>)] = &[ + ("gpt-4o", Some("openai")), + ("o3-pro", Some("openai")), + ("azure/gpt-4o", Some("azure")), + ("claude-sonnet-4-5", Some("anthropic")), + ("gemini-2.5-pro", Some("vertex_ai-language-models")), + ( + "fireworks_ai/accounts/fireworks/models/llama-v3p1-8b-instruct", + Some("fireworks_ai"), + ), + ( + "anyscale/meta-llama/Meta-Llama-3-8B-Instruct", + Some("anyscale"), + ), + ("sample_free_row", None), + ]; + + /// `litellm.model_cost` as Python sees it. The stamp is what python-bridge can observe for free, the dict's + /// identity and its length, so a write that keeps both hides a key change from the store + struct ModelCost { + dict: RefCell>>, + identity: Cell, + index_changes: Cell, + honest_stamp: bool, + scans: Cell, + } + + impl ModelCost { + fn new(rows: &[(&str, Option<&str>)], honest_stamp: bool) -> Self { + Self { + dict: RefCell::new( + rows.iter() + .map(|(key, provider)| ((*key).to_owned(), provider.map(str::to_owned))) + .collect(), + ), + identity: Cell::new(0), + index_changes: Cell::new(0), + honest_stamp, + scans: Cell::new(0), + } + } + + /// `model_cost[key] = {"litellm_provider": provider, ...}` + fn set(&self, key: &str, provider: Option<&str>) { + let previous = self + .dict + .borrow_mut() + .insert(key.to_owned(), provider.map(str::to_owned)); + if previous.as_ref().map(Option::as_deref) != Some(provider) { + self.index_changes.set(self.index_changes.get() + 1); + } + } + + /// `del model_cost[key]` + fn del(&self, key: &str) { + if self.dict.borrow_mut().shift_remove(key).is_some() { + self.index_changes.set(self.index_changes.get() + 1); + } + } + + /// `litellm.model_cost = {...}`, a new dict object + fn rebind(&self, rows: &[(&str, Option<&str>)]) { + *self.dict.borrow_mut() = rows + .iter() + .map(|(key, provider)| ((*key).to_owned(), provider.map(str::to_owned))) + .collect(); + self.identity.set(self.identity.get() + 1); + self.index_changes.set(self.index_changes.get() + 1); + } + } + + /// A row is its `litellm_provider`, which is also the group the store lists its key under + impl Rows for &ModelCost { + type Row = Option; + type Stamp = (u64, u64); + + fn fold(name: &str) -> String { + name.to_lowercase() + } + + fn stamp(&self) -> Self::Stamp { + if self.honest_stamp { + (self.identity.get(), self.index_changes.get()) + } else { + (self.identity.get(), self.dict.borrow().len() as u64) + } + } + + fn contains(&self, key: &str) -> bool { + self.dict.borrow().contains_key(key) + } + + fn row(&self, key: &str) -> Option>> { + Some(Cow::Owned(self.dict.borrow().get(key)?.clone())) + } + + fn scan(&self, visit: &mut dyn FnMut(&str, Option<&str>)) { + self.scans.set(self.scans.get() + 1); + for (key, provider) in self.dict.borrow().iter() { + visit(key, provider.as_deref()); + } + } + } + + #[fixture] + fn model_cost() -> ModelCost { + ModelCost::new(BUNDLED, false) + } + + /// Rows only `Store::edit` can change, so the stamp never moves + #[derive(Debug)] + struct Owned(IndexMap>); + + impl Rows for Owned { + type Row = Option; + type Stamp = (); + + fn fold(name: &str) -> String { + name.to_lowercase() + } + + fn stamp(&self) -> Self::Stamp {} + + fn contains(&self, key: &str) -> bool { + self.0.contains_key(key) + } + + fn row(&self, key: &str) -> Option>> { + self.0.get(key).map(Cow::Borrowed) + } + + fn scan(&self, visit: &mut dyn FnMut(&str, Option<&str>)) { + for (key, provider) in &self.0 { + visit(key, provider.as_deref()); + } + } + } + + fn owned(rows: &[(&str, Option<&str>)]) -> Store { + Store::new(Owned( + rows.iter() + .map(|(key, provider)| ((*key).to_owned(), provider.map(str::to_owned))) + .collect(), + )) + } + + #[rstest] + #[case::bundled_key_as_written("gpt-4o", Some("gpt-4o"))] + #[case::user_typed_upper_case("GPT-4o", Some("gpt-4o"))] + #[case::provider_prefixed("Azure/GPT-4o", Some("azure/gpt-4o"))] + #[case::fireworks_path_in_another_case( + "fireworks_ai/accounts/fireworks/models/Llama-v3p1-8B-Instruct", + Some("fireworks_ai/accounts/fireworks/models/llama-v3p1-8b-instruct") + )] + #[case::mixed_case_bundled_key( + "anyscale/meta-llama/meta-llama-3-8b-instruct", + Some("anyscale/meta-llama/Meta-Llama-3-8B-Instruct") + )] + #[case::unmapped_model("my-finetune", None)] + #[case::prefix_is_not_a_match("gpt-4", None)] + fn find_key_maps_a_requested_model_to_its_key( + model_cost: ModelCost, + #[case] model: &str, + #[case] expected: Option<&str>, + ) { + assert_eq!(Store::new(&model_cost).find_key(model).as_deref(), expected); + } + + #[rstest] + #[case::the_bundled_spelling("gpt-4o", "gpt-4o")] + #[case::the_registered_spelling("GPT-4o", "GPT-4o")] + #[case::another_spelling_takes_the_later_key("Gpt-4O", "GPT-4o")] + fn a_registered_case_variant_is_its_own_row( + model_cost: ModelCost, + #[case] model: &str, + #[case] expected: &str, + ) { + model_cost.set("GPT-4o", Some("openai")); + assert_eq!( + Store::new(&model_cost).find_key(model).as_deref(), + Some(expected) + ); + } + + #[rstest] + #[case::openai_in_map_order("openai", &["gpt-4o", "o3-pro"])] + #[case::azure("azure", &["azure/gpt-4o"])] + #[case::raw_vertex_family("vertex_ai-language-models", &["gemini-2.5-pro"])] + #[case::provider_alias_is_python_s_job("vertex_ai", &[])] + #[case::matched_as_written("OpenAI", &[])] + #[case::unknown_provider("acme", &[])] + fn keys_in_lists_the_keys_a_raw_provider_names( + model_cost: ModelCost, + #[case] provider: &str, + #[case] expected: &[&str], + ) { + assert_eq!(Store::new(&model_cost).keys_in(provider), expected); + } + + #[rstest] + fn a_model_written_straight_into_the_dict_is_found_in_any_case(model_cost: ModelCost) { + let store = Store::new(&model_cost); + assert_eq!(store.find_key("mycorp/custom-model"), None); + + model_cost.set("MyCorp/Custom-Model", Some("openai")); + + assert_eq!( + store.find_key("mycorp/custom-model").as_deref(), + Some("MyCorp/Custom-Model") + ); + assert_eq!( + store.keys_in("openai"), + ["gpt-4o", "o3-pro", "MyCorp/Custom-Model"] + ); + } + + #[rstest] + fn a_price_edit_reuses_the_index(model_cost: ModelCost) { + let store = Store::new(&model_cost); + assert_eq!(store.find_key("GPT-4o").as_deref(), Some("gpt-4o")); + + model_cost.set("gpt-4o", Some("openai")); + model_cost.set("o3-pro", Some("openai")); + model_cost.set("gpt-4o", Some("openai")); + + assert_eq!(store.find_key("O3-PRO").as_deref(), Some("o3-pro")); + assert_eq!(store.keys_in("openai"), ["gpt-4o", "o3-pro"]); + assert_eq!(model_cost.scans.get(), 1); + } + + #[rstest] + fn a_reload_that_rebinds_the_dict_is_seen_even_at_the_same_length(model_cost: ModelCost) { + let store = Store::new(&model_cost); + assert_eq!(store.find_key("GPT-4o").as_deref(), Some("gpt-4o")); + + let mut reloaded = BUNDLED.to_vec(); + reloaded[0] = ("gpt-4o-2024-11-20", Some("openai")); + model_cost.rebind(&reloaded); + + assert_eq!(store.find_key("GPT-4o"), None); + assert_eq!( + store.find_key("GPT-4o-2024-11-20").as_deref(), + Some("gpt-4o-2024-11-20") + ); + } + + #[rstest] + fn a_deleted_model_is_never_returned(model_cost: ModelCost) { + let store = Store::new(&model_cost); + assert_eq!(store.find_key("O3-PRO").as_deref(), Some("o3-pro")); + + model_cost.del("o3-pro"); + + assert_eq!(store.find_key("O3-PRO"), None); + assert_eq!(store.keys_in("openai"), ["gpt-4o"]); + } + + #[rstest] + fn a_respelled_key_at_the_same_length_is_found_after_one_rebuild(model_cost: ModelCost) { + let store = Store::new(&model_cost); + assert_eq!(store.find_key("o3-PRO").as_deref(), Some("o3-pro")); + + model_cost.del("o3-pro"); + model_cost.set("O3-Pro", Some("openai")); + + assert_eq!(store.find_key("o3-PRO").as_deref(), Some("O3-Pro")); + assert_eq!(model_cost.scans.get(), 2); + } + + #[rstest] + fn a_swap_at_the_same_length_hides_the_new_key_until_invalidate(model_cost: ModelCost) { + let store = Store::new(&model_cost); + assert_eq!(store.find_key("O3-PRO").as_deref(), Some("o3-pro")); + + model_cost.del("o3-pro"); + model_cost.set("MyCorp/Custom-Model", Some("openai")); + + assert_eq!(store.find_key("mycorp/custom-model"), None); + assert_eq!(store.keys_in("openai"), ["gpt-4o"]); + + store.invalidate(); + + assert_eq!( + store.find_key("mycorp/custom-model").as_deref(), + Some("MyCorp/Custom-Model") + ); + assert_eq!(store.keys_in("openai"), ["gpt-4o", "MyCorp/Custom-Model"]); + } + + #[rstest] + fn a_provider_rewrite_on_an_existing_key_needs_invalidate(model_cost: ModelCost) { + let store = Store::new(&model_cost); + assert_eq!(store.keys_in("openai"), ["gpt-4o", "o3-pro"]); + + model_cost.set("o3-pro", Some("azure")); + + assert_eq!(store.keys_in("openai"), ["gpt-4o", "o3-pro"]); + + store.invalidate(); + + assert_eq!(store.keys_in("openai"), ["gpt-4o"]); + assert_eq!(store.keys_in("azure"), ["o3-pro", "azure/gpt-4o"]); + } + + #[rstest] + fn an_edit_on_owned_rows_is_seen_by_the_next_query() { + let mut store = owned(BUNDLED); + assert_eq!(store.find_key("GPT-4o").as_deref(), Some("gpt-4o")); + + store.edit(|rows| { + rows.0.shift_remove("gpt-4o"); + rows.0 + .insert("MyCorp/Custom-Model".to_owned(), Some("openai".to_owned())); + }); + + assert_eq!(store.find_key("GPT-4o"), None); + assert_eq!( + store.find_key("mycorp/custom-model").as_deref(), + Some("MyCorp/Custom-Model") + ); + assert_eq!(store.keys_in("openai"), ["o3-pro", "MyCorp/Custom-Model"]); + } + + #[rstest] + fn get_reads_the_row_by_exact_key_only() { + let store = owned(BUNDLED); + assert_eq!( + store.get("azure/gpt-4o").as_deref(), + Some(&Some("azure".to_owned())) + ); + assert_eq!(store.get("Azure/GPT-4o"), None); + } +} diff --git a/litellm-rust/crates/model-catalog/src/store/name_index.rs b/litellm-rust/crates/model-catalog/src/store/name_index.rs new file mode 100644 index 00000000000..86f05cb31af --- /dev/null +++ b/litellm-rust/crates/model-catalog/src/store/name_index.rs @@ -0,0 +1,35 @@ +use std::collections::HashMap; + +use super::Rows; + +/// Keys only, never rows, so a value write never makes it stale. A later key wins when two keys fold to one name +#[derive(Debug, Default)] +pub(super) struct NameIndex { + by_folded: HashMap, + by_group: HashMap>, +} + +impl NameIndex { + pub(super) fn scan(rows: &R) -> Self { + let mut index = Self::default(); + rows.scan(&mut |key, group| { + index.by_folded.insert(R::fold(key), key.to_owned()); + if let Some(group) = group { + index + .by_group + .entry(group.to_owned()) + .or_default() + .push(key.to_owned()); + } + }); + index + } + + pub(super) fn key_for(&self, folded: &str) -> Option<&str> { + self.by_folded.get(folded).map(String::as_str) + } + + pub(super) fn keys_in(&self, group: &str) -> &[String] { + self.by_group.get(group).map_or(&[], Vec::as_slice) + } +} diff --git a/litellm-rust/crates/model-catalog/src/validation.rs b/litellm-rust/crates/model-catalog/src/validation.rs deleted file mode 100644 index 73f08a865c1..00000000000 --- a/litellm-rust/crates/model-catalog/src/validation.rs +++ /dev/null @@ -1,218 +0,0 @@ -use std::collections::BTreeSet; - -use serde_json::{Map, Value}; -use thiserror::Error; - -use crate::{AliasIssue, Catalog, ModelInfo, UtcHours, Weekday}; - -/// A registry entry violates the checked-in catalog contract. -#[derive(Debug, Error)] -pub enum RegistryValidationError { - #[error("{reason}")] - Entry { model: String, reason: String }, - #[error("alias issue: {0:?}")] - Alias(AliasIssue), -} - -/// Validate one registry entry without restricting the tolerant catalog reader. -pub fn validate_model_entry(model: &str, value: &Value) -> Result<(), RegistryValidationError> { - validate_entry_inner(model, value).map_err(|reason| RegistryValidationError::Entry { - model: model.to_owned(), - reason, - }) -} - -/// Check every model and alias in a parsed catalog against registry rules. -pub fn validate_registry(catalog: &Catalog) -> Result<(), RegistryValidationError> { - if let Some(issue) = catalog.alias_issues().first() { - return Err(RegistryValidationError::Alias(issue.clone())); - } - catalog.model_names().try_for_each(|name| { - let entry = catalog.lookup(name).expect("catalog name must resolve"); - validate_model_entry(name, &Value::Object(entry.entry.fields().clone())) - }) -} - -fn json_eq(left: &Value, right: &Value) -> bool { - match (left, right) { - (Value::Number(left), Value::Number(right)) => left.as_f64() == right.as_f64(), - (Value::Array(left), Value::Array(right)) => { - left.len() == right.len() && left.iter().zip(right).all(|(a, b)| json_eq(a, b)) - } - (Value::Object(left), Value::Object(right)) => { - left.len() == right.len() - && left - .iter() - .all(|(key, value)| right.get(key).is_some_and(|other| json_eq(value, other))) - } - _ => left == right, - } -} - -fn keys(value: &Map) -> BTreeSet { - value.keys().cloned().collect() -} - -fn symmetric_difference(left: &BTreeSet, right: &BTreeSet) -> BTreeSet { - left.symmetric_difference(right).cloned().collect() -} - -fn validate_entry_inner(model_name: &str, value: &Value) -> Result<(), String> { - let object = value - .as_object() - .ok_or_else(|| format!("{model_name} must be an object"))?; - if let Some(aliases) = object.get("aliases") { - let names = aliases - .as_array() - .ok_or_else(|| format!("{model_name}.aliases must be an array"))?; - if names.iter().any(|name| !name.is_string()) { - return Err(format!("{model_name}.aliases must contain strings")); - } - } - let info: ModelInfo = - serde_json::from_value(value.clone()).map_err(|error| format!("{model_name}: {error}"))?; - if info.litellm_provider.is_none() { - return Err(format!("{model_name}.litellm_provider is required")); - } - validate_dates_and_windows(model_name, &info)?; - let serialized = serde_json::to_value(info).map_err(|error| error.to_string())?; - let mut expected = object.clone(); - expected.remove("aliases"); - if !json_eq(&Value::Object(expected.clone()), &serialized) { - let actual = serialized - .as_object() - .expect("ModelInfo serializes as an object"); - return Err(format!( - "{model_name} has an unknown field, null, or changed value: {:?}", - symmetric_difference(&keys(&expected), &keys(actual)) - )); - } - check_prices(model_name, value) -} - -fn validate_dates_and_windows(model_name: &str, info: &ModelInfo) -> Result<(), String> { - if let Some(date) = &info.deprecation_date { - let format = time::format_description::parse_borrowed::<2>("[year]-[month]-[day]").unwrap(); - time::Date::parse(date, &format) - .map_err(|error| format!("{model_name}.deprecation_date: {error}"))?; - } - let Some(pricing) = &info.off_peak_pricing else { - return Ok(()); - }; - if pricing.hours_utc.is_none() && pricing.windows.is_none() { - return Err(format!( - "{model_name}.off_peak_pricing needs hours or windows" - )); - } - if let Some(hours) = &pricing.hours_utc { - validate_hours(hours)?; - } - if let Some(windows) = &pricing.windows { - if windows.is_empty() { - return Err(format!("{model_name}.off_peak_pricing.windows is empty")); - } - windows.iter().try_for_each(|window| { - validate_hours(&window.hours_utc)?; - if let Some(days) = &window.weekdays - && (days.is_empty() || days.iter().any(|day| !valid_weekday(day))) - { - return Err(format!("{model_name}.off_peak_pricing.weekdays is invalid")); - } - Ok(()) - })?; - } - Ok(()) -} - -fn validate_hours(hours: &UtcHours) -> Result<(), String> { - let values = match hours { - UtcHours::Single(value) => std::slice::from_ref(value), - UtcHours::Multiple(values) => values.as_slice(), - }; - if values.is_empty() || values.iter().any(|value| !valid_utc_window(value)) { - return Err("off_peak_pricing.hours_utc is invalid".into()); - } - Ok(()) -} - -fn valid_utc_window(value: &str) -> bool { - let Some((start, end)) = value.split_once('-') else { - return false; - }; - [start, end].into_iter().all(|clock| { - let Some((hour, minute)) = clock.split_once(':') else { - return false; - }; - hour.len() == 2 - && minute.len() == 2 - && hour.parse::().is_ok_and(|hour| hour < 24) - && minute.parse::().is_ok_and(|minute| minute < 60) - }) -} - -fn valid_weekday(day: &Weekday) -> bool { - match day { - Weekday::Number(number) => (1..=7).contains(number), - Weekday::Name(name) => matches!( - name.to_ascii_lowercase().as_str(), - "mon" - | "monday" - | "tue" - | "tues" - | "tuesday" - | "wed" - | "wednesday" - | "thu" - | "thur" - | "thurs" - | "thursday" - | "fri" - | "friday" - | "sat" - | "saturday" - | "sun" - | "sunday" - ), - } -} - -fn check_prices(path: &str, value: &Value) -> Result<(), String> { - let Some(object) = value.as_object() else { - return Ok(()); - }; - object.iter().try_for_each(|(key, field)| { - let field_path = format!("{path}.{key}"); - if (key.contains("cost") - || path.ends_with(".guardrail_cost_per_unit") - || path.ends_with(".search_context_cost_per_query")) - && let Some(number) = field.as_f64() - && number < 0.0 - { - return Err(format!("{field_path} must be nonnegative")); - } - if key.contains("uplift_multiplier") - && let Some(number) = field.as_f64() - && number < 1.0 - { - return Err(format!("{field_path} must be at least one")); - } - if matches!(key.as_str(), "range" | "max_results_range") - && field.as_array().is_some_and(|values| { - values - .iter() - .any(|value| value.as_f64().is_some_and(|n| n < 0.0)) - }) - { - return Err(format!("{field_path} must be nonnegative")); - } - if matches!(key.as_str(), "metadata" | "provider_specific_entry") { - return Ok(()); - } - match field.as_array() { - Some(items) => items.iter().enumerate().try_for_each(|(index, item)| { - check_prices(&format!("{field_path}[{index}]"), item) - }), - None => check_prices(&field_path, field), - } - }) -} diff --git a/litellm-rust/crates/model-catalog/src/vocabulary.rs b/litellm-rust/crates/model-catalog/src/vocabulary.rs new file mode 100644 index 00000000000..2b7ac8bd1ab --- /dev/null +++ b/litellm-rust/crates/model-catalog/src/vocabulary.rs @@ -0,0 +1,126 @@ +/// Primary API surface / task type of the model. +#[macro_rules_attribute::apply(crate::wire_type)] +#[derive(Copy, Eq, Hash)] +#[serde(rename_all = "snake_case")] +pub enum Mode { + AudioSpeech, + AudioTranscription, + Chat, + Completion, + Decisions, + Embedding, + Evaluation, + Extraction, + Guardrail, + ImageEdit, + ImageGeneration, + Moderation, + Ocr, + Realtime, + Rerank, + Responses, + Search, + VectorStore, + VideoGeneration, +} + +/// Gemini audio generation API the model is served through. +#[macro_rules_attribute::apply(crate::wire_type)] +#[derive(Copy, Eq, Hash)] +#[serde(rename_all = "snake_case")] +pub enum VertexAiAudioApi { + LyriaPredict, + LyriaInteractions, +} + +/// Audio container format the model can return. +#[macro_rules_attribute::apply(crate::wire_type)] +#[derive(Copy, Eq, Hash)] +#[serde(rename_all = "snake_case")] +pub enum AudioFormat { + Mp3, + Wav, +} + +/// Input modality the model accepts. +#[macro_rules_attribute::apply(crate::wire_type)] +#[derive(Copy, Eq, Hash)] +#[serde(rename_all = "snake_case")] +pub enum InputModality { + Text, + Image, + Audio, + Video, +} + +/// Output modality the model can produce. +#[macro_rules_attribute::apply(crate::wire_type)] +#[derive(Copy, Eq, Hash)] +#[serde(rename_all = "snake_case")] +pub enum OutputModality { + Text, + Image, + Audio, + Video, + Code, +} + +/// API route a model can be called through. +#[macro_rules_attribute::apply(crate::wire_type)] +#[derive(Copy, Eq, Hash)] +pub enum Endpoint { + #[serde(rename = "/v1/chat/completions")] + ChatCompletions, + #[serde(rename = "/v1/completions")] + Completions, + #[serde(rename = "/v1/responses")] + Responses, + #[serde(rename = "/v1/messages")] + Messages, + #[serde(rename = "/v1/batch")] + Batch, + #[serde(rename = "/v1/embeddings")] + Embeddings, + #[serde(rename = "/v1/images/generations")] + ImageGenerations, + #[serde(rename = "/v1/images/edits")] + ImageEdits, + #[serde(rename = "/v1/audio/speech")] + AudioSpeech, + #[serde(rename = "/v1/audio/transcriptions")] + AudioTranscriptions, + #[serde(rename = "/v1/realtime")] + Realtime, + #[serde(rename = "/v1/realtime/transcription_sessions")] + RealtimeTranscriptionSessions, + #[serde(rename = "/v1/videos")] + Videos, + #[serde(rename = "/v1/ocr")] + Ocr, + #[serde(rename = "/v1/listen")] + Listen, + #[serde(rename = "/v1/systemone")] + SystemOne, + #[serde(rename = "/v1/decisions")] + Decisions, + #[serde(rename = "/v1beta/interactions")] + Interactions, + #[serde(rename = "/v1beta/models")] + Models, + #[serde(rename = "/vertex_ai/live")] + VertexAiLive, +} + +/// Reasoning effort level a model accepts or applies. +#[macro_rules_attribute::apply(crate::wire_type)] +#[derive(Copy, Eq, Hash)] +#[serde(rename_all = "snake_case")] +pub enum EffortLevel { + None, + Minimal, + Low, + Medium, + High, + Xhigh, + Max, +} diff --git a/litellm-rust/crates/model-catalog/src/wire/attributes.rs b/litellm-rust/crates/model-catalog/src/wire/attributes.rs new file mode 100644 index 00000000000..93c10a81524 --- /dev/null +++ b/litellm-rust/crates/model-catalog/src/wire/attributes.rs @@ -0,0 +1,344 @@ +use std::collections::BTreeMap; +use std::fmt; +use std::str::FromStr; + +use litellm_cost::money::UnitPrice; +use serde::de::{self, Deserializer}; +use serde::{Deserialize, Serialize}; +use serde_json::Value; + +use crate::error::{DateCause, Error, Repr}; +use crate::vocabulary::{ + AudioFormat, EffortLevel, Endpoint, InputModality, Mode, OutputModality, VertexAiAudioApi, +}; +use crate::wire::lax::Count; + +macro_rules! attributes { + ($($(#[$doc:meta])* $name:ident: $ty:ty $(as $via:ty)?),* $(,)?) => { + /// The named, non-price fields of a catalog entry. + #[derive(Clone, Debug, Default, PartialEq)] + #[cfg_attr(feature = "schema", derive(schemars::JsonSchema))] + pub struct Attributes { + $($(#[$doc])* pub $name: Option<$ty>,)* + } + + impl Attributes { + pub(crate) fn read( + &mut self, + key: &str, + value: &Value, + ) -> Option> { + match key { + $(stringify!($name) => Some( + attributes!(@read value, $ty $(, $via)?).map(|read| self.$name = Some(read)), + ),)* + _ => None, + } + } + } + }; + (@read $value:ident, $ty:ty) => { + <$ty as Deserialize>::deserialize($value) + }; + (@read $value:ident, $ty:ty, $via:ty) => { + serde_with::de::DeserializeAsWrap::<$ty, $via>::deserialize($value) + .map(serde_with::de::DeserializeAsWrap::into_inner) + }; +} + +attributes! { + /// Other names this entry is served under. + aliases: Vec, + audio_transcription_config: String, + bedrock_converse_supports_strict_tools: bool, + /// Highest reasoning effort the Bedrock output_config accepts for this model. + bedrock_output_config_effort_ceiling: EffortLevel, + comment: String, + /// Reasoning effort the provider applies when the request omits reasoning_effort. Gates whether a non-default temperature or the top_p/logprobs sampling params are accepted, which hold only when the effort resolves to 'none'. + default_reasoning_effort: EffortLevel, + /// Date the provider deprecates the model, YYYY-MM-DD. + deprecation_date: IsoDate, + gemini_audio_only_live: bool, + gemini_native_audio: bool, + input_cost_per_token_cache_hit: UnitPrice, + /// Databricks units, not USD. + input_dbu_cost_per_token: Dbu, + /// LiteLLM provider slug; one of https://docs.litellm.ai/docs/providers. + litellm_provider: String, + /// Maximum prompt/context tokens the model accepts. + max_input_tokens: u64 as Count, + /// Maximum tokens the model can generate in one response. + max_output_tokens: u64 as Count, + /// Legacy field: max output tokens if the provider specifies it, else max input tokens. + max_tokens: u64 as Count, + /// Free-form notes about the entry (e.g. pricing derivation). + metadata: BTreeMap, + /// Primary API surface / task type of the model. + mode: Mode, + /// Databricks units, not USD. + output_dbu_cost_per_token: Dbu, + /// Embedding dimension for embedding models. + output_vector_size: u64 as Count, + /// Smallest prefix the provider will actually cache; absent means the provider default applies. + prompt_cache_min_tokens: u64 as Count, + /// Provider-internal routing hints (e.g. bedrock_invocation_schema). + provider_specific_entry: BTreeMap, + reasoning_contexts: Vec, + /// Exact reasoning_effort levels this deployment accepts; wins over supports_* flags. + reasoning_effort_levels: Vec, + reasoning_modes: Vec, + /// Provider default requests-per-minute limit. + rpm: u64 as Count, + /// Grounded search requests the provider includes for free before search is billed. + search_free_requests: SearchFreeRequests, + /// URL of the provider pricing/model page this entry was taken from. + source: String, + /// Audio container formats the model can return. + supported_audio_formats: Vec, + /// OpenAI-style API routes this model can be called through, e.g. /v1/chat/completions. + supported_endpoints: Vec, + /// Input modalities the model accepts. + supported_modalities: Vec, + /// Output modalities the model can produce. + supported_output_modalities: Vec, + /// Cloud regions the model is available in ('global' or region ids). + supported_regions: Vec, + thinking_always_on: bool, + token_count_framing: u64 as Count, + token_count_model: TokenCountModel, + token_count_tokenizer: TokenCountTokenizer, + /// Provider default tokens-per-minute limit. + tpm: u64 as Count, + use_openai_responses_path: bool, + uses_embed_content: bool, + vertex_ai_audio_api: VertexAiAudioApi, + /// Whether web search is billed per query or per prompt. + web_search_billing_unit: WebSearchBillingUnit, +} + +/// The model whose provider token counter counts tokens for this entry. +#[macro_rules_attribute::apply(crate::wire_type)] +#[derive(Eq, Hash)] +#[serde(deny_unknown_fields)] +pub struct TokenCountModel { + pub model: String, + #[serde(skip_serializing_if = "Option::is_none")] + pub litellm_provider: Option, + #[serde(skip_serializing_if = "Option::is_none")] + pub region: Option, +} + +/// Free grounded search requests per period, shared across the models of one group. +#[macro_rules_attribute::apply(crate::wire_type)] +#[derive(Eq, Hash)] +#[serde(deny_unknown_fields)] +pub struct SearchFreeRequests { + pub count: u64, + pub period: FreeRequestPeriod, + pub shared_group: String, +} + +#[macro_rules_attribute::apply(crate::wire_type)] +#[derive(Copy, Eq, Hash)] +#[serde(rename_all = "snake_case")] +pub enum FreeRequestPeriod { + Day, + Month, +} + +/// Local tokenizer that counts tokens for this entry. +#[macro_rules_attribute::apply(crate::wire_type)] +#[derive(Copy, Eq, Hash)] +#[serde(rename_all = "snake_case")] +pub enum TokenCountTokenizer { + KimiK3, +} + +/// Whether web search is billed per query or per prompt. +#[macro_rules_attribute::apply(crate::wire_type)] +#[derive(Copy, Eq, Hash)] +#[serde(rename_all = "snake_case")] +pub enum WebSearchBillingUnit { + PerQuery, + PerPrompt, +} + +/// A non-negative amount of Databricks units. +#[derive(Clone, Copy, Debug, PartialEq, PartialOrd, Serialize)] +#[serde(transparent)] +pub struct Dbu(f64); + +impl Dbu { + pub fn new(units: f64) -> Option { + (units.is_finite() && units >= 0.0).then_some(Self(units)) + } + pub fn get(self) -> f64 { + self.0 + } +} + +impl<'de> Deserialize<'de> for Dbu { + fn deserialize>(deserializer: D) -> Result { + let units = f64::deserialize(deserializer)?; + Self::new(units).ok_or_else(|| { + de::Error::invalid_value( + de::Unexpected::Float(units), + &"a non-negative number of Databricks units", + ) + }) + } +} + +/// A calendar date written YYYY-MM-DD. +#[derive( + Clone, + Copy, + Debug, + PartialEq, + Eq, + PartialOrd, + Ord, + Hash, + serde_with::DeserializeFromStr, + serde_with::SerializeDisplay, +)] +pub struct IsoDate(pub time::Date); + +impl FromStr for IsoDate { + type Err = Error; + + fn from_str(date: &str) -> Result { + let mut parts = date.split('-'); + let (Some(year), Some(month), Some(day), None) = + (parts.next(), parts.next(), parts.next(), parts.next()) + else { + return Err(Repr::InvalidDate { cause: None }.into()); + }; + if year.len() != 4 || month.len() != 2 || day.len() != 2 { + return Err(Repr::InvalidDate { cause: None }.into()); + } + let number = |part: &str| part.parse::().map_err(DateCause::from); + let month = time::Month::try_from(number(month)?).map_err(DateCause::from)?; + time::Date::from_calendar_date(year.parse().map_err(DateCause::from)?, month, number(day)?) + .map(Self) + .map_err(DateCause::from) + .map_err(Error::from) + } +} + +impl fmt::Display for IsoDate { + fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result { + write!( + f, + "{:04}-{:02}-{:02}", + self.0.year(), + u8::from(self.0.month()), + self.0.day() + ) + } +} + +#[cfg(feature = "schema")] +mod schema { + use std::borrow::Cow; + + use schemars::{JsonSchema, Schema, SchemaGenerator, json_schema}; + + use super::{Dbu, IsoDate}; + + impl JsonSchema for IsoDate { + fn inline_schema() -> bool { + true + } + fn schema_name() -> Cow<'static, str> { + "IsoDate".into() + } + fn json_schema(_: &mut SchemaGenerator) -> Schema { + json_schema!({ + "type": "string", + "format": "date", + "pattern": r"^\d{4}-(0[1-9]|1[0-2])-(0[1-9]|[12]\d|3[01])$" + }) + } + } + + impl JsonSchema for Dbu { + fn inline_schema() -> bool { + true + } + fn schema_name() -> Cow<'static, str> { + "Dbu".into() + } + fn json_schema(_: &mut SchemaGenerator) -> Schema { + json_schema!({"type": "number", "minimum": 0}) + } + } +} + +#[cfg(test)] +mod tests { + use rstest::rstest; + use serde_json::json; + + use super::*; + + #[rstest] + #[case::leap_day("2028-02-29", true)] + #[case::not_a_leap_year("2026-02-29", false)] + #[case::impossible_day("2026-02-31", false)] + #[case::one_digit_month("2026-2-01", false)] + #[case::extra_part("2026-02-01-01", false)] + fn iso_dates_are_real_calendar_dates(#[case] text: &str, #[case] valid: bool) { + assert_eq!(text.parse::().is_ok(), valid); + } + + #[rstest] + #[case::count_written_as_text("max_tokens", json!("8192"), true)] + #[case::negative_count("max_tokens", json!(-1), false)] + #[case::known_mode("mode", json!("chat"), true)] + #[case::unknown_mode("mode", json!("chatt"), false)] + #[case::negative_dbu("input_dbu_cost_per_token", json!(-1), false)] + #[case::reasoning_contexts("reasoning_contexts", json!(["reasoning", "non_reasoning"]), true)] + #[case::reasoning_modes("reasoning_modes", json!(["none", "adaptive"]), true)] + #[case::reasoning_context_not_a_list("reasoning_contexts", json!("reasoning"), false)] + #[case::reasoning_mode_not_a_string("reasoning_modes", json!([1]), false)] + fn each_attribute_reads_its_own_type( + #[case] key: &str, + #[case] value: Value, + #[case] valid: bool, + ) { + assert_eq!( + Attributes::default() + .read(key, &value) + .map(|read| read.is_ok()), + Some(valid) + ); + } + + #[rstest] + fn keys_that_are_not_attributes_are_left_to_the_caller() { + assert!( + Attributes::default() + .read("input_cost_per_token", &json!(1)) + .is_none() + ); + } + + #[rstest] + fn reasoning_metadata_is_retained() { + let mut attributes = Attributes::default(); + attributes + .read("reasoning_contexts", &json!(["reasoning", "non_reasoning"])) + .unwrap() + .unwrap(); + attributes + .read("reasoning_modes", &json!(["none", "adaptive"])) + .unwrap() + .unwrap(); + assert_eq!( + attributes.reasoning_contexts.unwrap(), + ["reasoning", "non_reasoning"] + ); + assert_eq!(attributes.reasoning_modes.unwrap(), ["none", "adaptive"]); + } +} diff --git a/litellm-rust/crates/model-catalog/src/wire/blocks.rs b/litellm-rust/crates/model-catalog/src/wire/blocks.rs new file mode 100644 index 00000000000..3a355686b7c --- /dev/null +++ b/litellm-rust/crates/model-catalog/src/wire/blocks.rs @@ -0,0 +1,182 @@ +use litellm_cost::money::UnitPrice; +use litellm_cost::schedule::{UtcWindow, Weekday}; +use serde::Deserialize; +use serde::de::DeserializeOwned; +use serde_json::{Map, Value}; +use serde_with::de::DeserializeAsWrap; + +use crate::error::{Error, Repr, pointer_child, pointer_for_key}; +use crate::wire::flat_key::FlatKey; +use crate::wire::lax::Count; + +/// A flat price key with its spelling, kept so problems can name it. +#[derive(Clone, Debug, PartialEq)] +pub struct FlatPrice { + pub key: String, + pub path: String, + pub flat: FlatKey, + pub price: UnitPrice, +} + +#[derive(Clone, Debug, Default, PartialEq)] +pub struct TierRow { + pub path: String, + pub range: Option<[u64; 2]>, + pub max_results_range: Option<[u64; 2]>, + pub prices: Vec, +} + +#[derive(Clone, Debug, Default, PartialEq)] +pub struct OffPeakBlock { + pub hours_utc: Option, + pub windows: Option>, + pub weekday_timezone: Option, + pub prices: Vec, +} + +/// One UTC window or a list of them. +#[derive(Clone, Debug, PartialEq, Eq, Deserialize)] +#[cfg_attr(feature = "schema", derive(schemars::JsonSchema))] +#[serde(untagged)] +pub enum UtcHours { + Single(UtcWindow), + Multiple(Vec), +} + +/// One off-peak window entry inside `windows`. +#[derive(Clone, Debug, PartialEq, Eq, Deserialize)] +#[cfg_attr(feature = "schema", derive(schemars::JsonSchema))] +#[serde(deny_unknown_fields)] +pub struct OffPeakWindow { + pub hours_utc: UtcHours, + pub weekdays: Option>, +} + +/// USD cost per web search query, keyed by search context size. +#[derive(Clone, Debug, Default, PartialEq, Deserialize)] +#[cfg_attr(feature = "schema", derive(schemars::JsonSchema))] +#[serde(deny_unknown_fields)] +pub struct SearchContextCostPerQuery { + pub search_context_size_low: Option, + pub search_context_size_medium: Option, + pub search_context_size_high: Option, +} + +impl UtcHours { + pub fn windows(&self) -> &[UtcWindow] { + match self { + Self::Single(window) => std::slice::from_ref(window), + Self::Multiple(windows) => windows, + } + } +} + +pub(crate) struct Reader<'a> { + pub(crate) problems: &'a mut Vec, +} + +impl Reader<'_> { + pub(crate) fn value(&mut self, path: String, value: &Value) -> Option { + T::deserialize(value) + .map_err(|error| self.problems.push(Error::new(path, Repr::Invalid(error)))) + .ok() + } + + pub(crate) fn price( + &mut self, + key: String, + path: String, + flat: FlatKey, + value: &Value, + ) -> Option { + let price = self.value(path.clone(), value)?; + Some(FlatPrice { + key, + path, + flat, + price, + }) + } + + fn object<'v>(&mut self, path: &str, value: &'v Value) -> Option<&'v Map> { + match value { + Value::Object(fields) => Some(fields), + other => self + .value::>(path.to_owned(), other) + .and(None), + } + } + + fn block_price( + &mut self, + name: &str, + key: String, + path: String, + value: &Value, + ) -> Option { + let Some(flat) = FlatKey::parse(name) else { + self.problems.push(Error::new(path, Repr::UnknownBlockKey)); + return None; + }; + self.price(key, path, flat, value) + } + + pub(crate) fn tier_rows(&mut self, value: &Value) -> Option> { + let path = pointer_for_key("tiered_pricing"); + let rows: Vec = self.value(path.clone(), value)?; + Some( + rows.iter() + .enumerate() + .filter_map(|(index, row)| self.tier_row(path.clone(), index, row)) + .collect(), + ) + } + + fn tier_row(&mut self, parent: String, index: usize, value: &Value) -> Option { + let path = format!("{parent}/{index}"); + let display_path = format!("tiered_pricing[{index}]"); + let fields = self.object(&path, value)?; + let mut row = TierRow { + path: path.clone(), + ..TierRow::default() + }; + for (name, value) in fields.iter().filter(|(_, value)| !value.is_null()) { + let key = format!("{display_path}.{name}"); + let child_path = pointer_child(&path, name); + match name.as_str() { + "range" => row.range = self.bounds(child_path, value), + "max_results_range" => row.max_results_range = self.bounds(child_path, value), + _ => row + .prices + .extend(self.block_price(name, key, child_path, value)), + } + } + Some(row) + } + + fn bounds(&mut self, path: String, value: &Value) -> Option<[u64; 2]> { + DeserializeAsWrap::<[u64; 2], [Count; 2]>::deserialize(value) + .map(DeserializeAsWrap::into_inner) + .map_err(|error| self.problems.push(Error::new(path, Repr::Invalid(error)))) + .ok() + } + + pub(crate) fn off_peak(&mut self, value: &Value) -> Option { + let path = pointer_for_key("off_peak_pricing"); + let fields = self.object(&path, value)?; + let mut block = OffPeakBlock::default(); + for (name, value) in fields.iter().filter(|(_, value)| !value.is_null()) { + let key = format!("off_peak_pricing.{name}"); + let child_path = pointer_child(&path, name); + match name.as_str() { + "hours_utc" => block.hours_utc = self.value(child_path, value), + "windows" => block.windows = self.value(child_path, value), + "weekday_timezone" => block.weekday_timezone = self.value(child_path, value), + _ => block + .prices + .extend(self.block_price(name, key, child_path, value)), + } + } + Some(block) + } +} diff --git a/litellm-rust/crates/model-catalog/src/wire/entry.rs b/litellm-rust/crates/model-catalog/src/wire/entry.rs new file mode 100644 index 00000000000..9c155c6496a --- /dev/null +++ b/litellm-rust/crates/model-catalog/src/wire/entry.rs @@ -0,0 +1,193 @@ +use std::collections::BTreeMap; + +use litellm_cost::money::{Multiplier, UnitPrice}; +use serde_json::{Map, Value}; + +use crate::error::{Error, Repr, pointer_for_key}; +use crate::wire::attributes::Attributes; +use crate::wire::blocks::{FlatPrice, OffPeakBlock, Reader, SearchContextCostPerQuery, TierRow}; +use crate::wire::flat_key::FlatKey; + +pub type Fields = Map; + +/// One catalog entry as written. Every non-null key lands in exactly one field, and a known key +/// with a bad value is kept out and listed in `problems`. +#[derive(Debug, Default)] +pub struct EntryWire { + pub attributes: Attributes, + pub prices: Vec, + pub capabilities: BTreeMap, + pub tier_rows: Option>, + pub off_peak: Option, + pub search_context: Option, + pub guardrail: Option>, + pub regional_endpoint_uplift: Option, + pub residency_uplift_eu: Option, + pub residency_uplift_us: Option, + pub unknown: Fields, + pub problems: Vec, +} + +impl EntryWire { + pub fn read(fields: &Fields) -> Self { + let mut problems = Vec::new(); + let mut wire = Self::default(); + let mut reader = Reader { + problems: &mut problems, + }; + for (key, value) in fields.iter().filter(|(_, value)| !value.is_null()) { + wire.read_key(&mut reader, key, value); + } + Self { problems, ..wire } + } + + fn read_key(&mut self, reader: &mut Reader<'_>, key: &str, value: &Value) { + let path = || pointer_for_key(key); + match key { + "tiered_pricing" => self.tier_rows = reader.tier_rows(value), + "off_peak_pricing" => self.off_peak = reader.off_peak(value), + "search_context_cost_per_query" => self.search_context = reader.value(path(), value), + "guardrail_cost_per_unit" => self.guardrail = reader.value(path(), value), + "regional_endpoint_uplift_multiplier" => { + self.regional_endpoint_uplift = reader.value(path(), value) + } + "regional_processing_uplift_multiplier_eu" => { + self.residency_uplift_eu = reader.value(path(), value) + } + "regional_processing_uplift_multiplier_us" => { + self.residency_uplift_us = reader.value(path(), value) + } + _ => self.read_open_key(reader, key, value), + } + } + + fn read_open_key(&mut self, reader: &mut Reader<'_>, key: &str, value: &Value) { + if let Some(read) = self.attributes.read(key, value) { + if let Err(error) = read { + reader + .problems + .push(Error::from_key(key, Repr::Invalid(error))); + } + return; + } + if let Some(flat) = FlatKey::parse(key) { + self.prices + .extend(reader.price(key.to_owned(), pointer_for_key(key), flat, value)); + return; + } + if key.starts_with("supports_") { + if let Some(flag) = reader.value(pointer_for_key(key), value) { + self.capabilities.insert(key.to_owned(), flag); + } + return; + } + self.unknown.insert(key.to_owned(), value.clone()); + } +} + +#[cfg(test)] +mod tests { + use rstest::rstest; + use serde_json::json; + + use super::*; + + fn read(entry: Value) -> EntryWire { + let Value::Object(fields) = entry else { + panic!("entry must be an object") + }; + EntryWire::read(&fields) + } + + fn problem_keys(wire: &EntryWire) -> Vec { + wire.problems + .iter() + .map(|problem| problem.path().to_owned()) + .collect() + } + + #[rstest] + fn every_key_lands_in_exactly_one_place() { + let wire = read(json!({ + "litellm_provider": "openai", + "max_tokens": "8192", + "input_cost_per_token": "0.000001", + "tiered_pricing": [{"range": [0, 10], "output_cost_per_token": 2e-6}], + "supports_vision": true, + "id": "deployment-1", + "mode": null + })); + + assert_eq!(wire.attributes.litellm_provider.as_deref(), Some("openai")); + assert_eq!(wire.attributes.max_tokens, Some(8192)); + assert_eq!(wire.attributes.mode, None); + assert_eq!( + wire.prices + .iter() + .map(|price| price.key.as_str()) + .collect::>(), + ["input_cost_per_token"] + ); + assert_eq!(wire.tier_rows.unwrap()[0].prices.len(), 1); + assert_eq!( + wire.capabilities, + BTreeMap::from([("supports_vision".to_owned(), true)]) + ); + assert_eq!(wire.unknown.keys().collect::>(), ["id"]); + assert!(wire.problems.is_empty()); + } + + #[rstest] + fn every_bad_value_is_reported_by_its_key_at_once() { + let wire = read(json!({ + "mode": "chatt", + "max_tokens": -1, + "input_cost_per_token": "x", + "output_cost_per_image_0.5K": "x", + "supports_vision": "yes", + "regional_endpoint_uplift_multiplier": 0.5, + "tiered_pricing": [ + {"range": [0, 10], "input_cost_per_token": 1e-6}, + {"range": [10.5, 20], "typo_cost": 1, "output_cost_per_token": -1} + ], + "off_peak_pricing": {"hours_utc": "25:00-01:00", "input_cost_per_token": 1e-6} + })); + + assert_eq!( + problem_keys(&wire) + .into_iter() + .collect::>(), + [ + "/input_cost_per_token", + "/max_tokens", + "/mode", + "/off_peak_pricing/hours_utc", + "/output_cost_per_image_0.5K", + "/regional_endpoint_uplift_multiplier", + "/supports_vision", + "/tiered_pricing/1/output_cost_per_token", + "/tiered_pricing/1/range", + "/tiered_pricing/1/typo_cost", + ] + .map(str::to_owned) + .into_iter() + .collect() + ); + } + + #[rstest] + #[case::tiers_not_a_list(json!({"tiered_pricing": {"range": [0, 1]}}), "/tiered_pricing")] + #[case::row_not_an_object(json!({"tiered_pricing": [3]}), "/tiered_pricing/0")] + #[case::off_peak_not_an_object(json!({"off_peak_pricing": true}), "/off_peak_pricing")] + #[case::unknown_search_size( + json!({"search_context_cost_per_query": {"search_context_size_huge": 1}}), + "/search_context_cost_per_query" + )] + #[case::negative_guardrail( + json!({"guardrail_cost_per_unit": {"contentPolicyUnits": -1}}), + "/guardrail_cost_per_unit" + )] + fn a_bad_block_is_reported_at_the_block(#[case] entry: Value, #[case] expected: &str) { + assert_eq!(problem_keys(&read(entry)), [expected]); + } +} diff --git a/litellm-rust/crates/model-catalog/src/wire/flat_key.rs b/litellm-rust/crates/model-catalog/src/wire/flat_key.rs new file mode 100644 index 00000000000..906d917b487 --- /dev/null +++ b/litellm-rust/crates/model-catalog/src/wire/flat_key.rs @@ -0,0 +1,359 @@ +use std::num::NonZeroU64; + +use litellm_cost::price::{ + Band, CacheReadMode, CacheTtl, Channel, Feature, ImageSize, InputUnit, Meter, OutputUnit, + Resolution, ServiceTier, TokenKind, When, +}; + +/// A flat price key as the grammar reads it: `{meter}[_above_{N}k_tokens][_{tier}]`. +#[derive(Clone, Debug, PartialEq, Eq)] +pub struct FlatKey { + pub meter: Meter, + pub band: Band, + pub tier: Option, +} + +#[derive(Clone, Copy, Debug, PartialEq, Eq)] +pub enum TierSuffix { + Service(ServiceTier), + Batches, + Decisions, +} + +impl FlatKey { + pub fn parse(key: &str) -> Option { + let (rest, tier) = split_tier(key); + let (base, suffix) = split_above(rest)?; + let (meter, band) = match suffix { + Above::None => (meter(base)?, Band::Base), + Above::PromptTokens(tokens) => (meter(base)?, Band::over_prompt_tokens(tokens)), + Above::Seconds(seconds) => match meter(base)? { + Meter::Input(InputUnit::VideoSecond { over_seconds: None }) => ( + Meter::Input(InputUnit::VideoSecond { + over_seconds: NonZeroU64::new(seconds), + }), + Band::Base, + ), + _ => return None, + }, + }; + Some(Self { meter, band, tier }) + } + + pub fn has_suffix(&self) -> bool { + self.band != Band::Base || self.tier.is_some() + } + + pub fn channel_and_when(&self) -> (Channel, When) { + let (channel, tier) = match self.tier { + None => (Channel::Online, ServiceTier::Standard), + Some(TierSuffix::Service(tier)) => (Channel::Online, tier), + Some(TierSuffix::Batches) => (Channel::Batch, ServiceTier::Standard), + Some(TierSuffix::Decisions) => (Channel::Decisions, ServiceTier::Standard), + }; + ( + channel, + When { + tier, + band: self.band, + }, + ) + } +} + +enum Above { + None, + PromptTokens(u64), + Seconds(u64), +} + +fn split_tier(key: &str) -> (&str, Option) { + let Some((head, tail)) = key.rsplit_once('_') else { + return (key, None); + }; + let tier = match tail { + "priority" => TierSuffix::Service(ServiceTier::Priority), + "flex" => TierSuffix::Service(ServiceTier::Flex), + "ultrafast" => TierSuffix::Service(ServiceTier::Ultrafast), + "balanced" => TierSuffix::Service(ServiceTier::Balanced), + "batches" => TierSuffix::Batches, + "decisions" => TierSuffix::Decisions, + _ => return (key, None), + }; + (head, Some(tier)) +} + +fn split_above(key: &str) -> Option<(&str, Above)> { + let Some((head, tail)) = key.rsplit_once("_above_") else { + return Some((key, Above::None)); + }; + if tail == "1hr" || tail == "12hr" { + return Some((key, Above::None)); + } + if let Some(thousands) = tail.strip_suffix("k_tokens") { + return Some(( + head, + Above::PromptTokens(number(thousands)?.checked_mul(1000)?), + )); + } + if let Some(tokens) = tail.strip_suffix("_tokens") { + return Some((head, Above::PromptTokens(number(tokens)?))); + } + let seconds = tail.strip_suffix("s_interval")?; + Some((head, Above::Seconds(number(seconds)?))) +} + +fn number(digits: &str) -> Option { + (!digits.is_empty() && digits.bytes().all(|byte| byte.is_ascii_digit())) + .then(|| digits.parse().ok()) + .flatten() +} + +fn meter(base: &str) -> Option { + let fixed = match base { + "cost_per_second" => Some(Meter::WallClockSecond), + "explicit_cache_read_input_token_cost" => Some(Meter::CacheRead { + kind: TokenKind::Text, + mode: CacheReadMode::Explicit, + }), + "annotation_cost_per_page" => Some(Meter::Feature(Feature::AnnotationPage)), + "citation_cost_per_token" => Some(Meter::Feature(Feature::CitationToken)), + "code_interpreter_cost_per_session" => { + Some(Meter::Feature(Feature::CodeInterpreterSession)) + } + "google_maps_grounding_cost_per_query" => { + Some(Meter::Feature(Feature::GoogleMapsGroundingQuery)) + } + "ocr_cost_per_credit" => Some(Meter::Feature(Feature::OcrCredit)), + "ocr_cost_per_page" => Some(Meter::Feature(Feature::OcrPage)), + "browser_open_cost_per_request" => Some(Meter::Feature(Feature::BrowserOpen)), + "cost_per_additional_result" => Some(Meter::Feature(Feature::AdditionalResult)), + _ => None, + }; + if fixed.is_some() { + return fixed; + } + if let Some(unit) = base.strip_prefix("input_cost_per_") { + return input_unit(unit).map(Meter::Input); + } + if let Some(unit) = base.strip_prefix("output_cost_per_") { + return output_unit(unit).map(Meter::Output); + } + if let Some(kind) = base + .strip_prefix("cache_read_input_") + .and_then(|rest| rest.strip_suffix("_cost")) + { + return Some(Meter::CacheRead { + kind: token_kind(kind)?, + mode: CacheReadMode::Implicit, + }); + } + let rest = base.strip_prefix("cache_creation_input_")?; + let (kind, ttl) = if let Some(kind) = rest.strip_suffix("_cost_above_1hr") { + (kind, CacheTtl::OneHour) + } else if let Some(kind) = rest.strip_suffix("_cost_above_12hr") { + (kind, CacheTtl::TwelveHours) + } else { + (rest.strip_suffix("_cost")?, CacheTtl::Default) + }; + Some(Meter::CacheWrite { + kind: token_kind(kind)?, + ttl, + }) +} + +fn token_kind(unit: &str) -> Option { + match unit { + "token" => Some(TokenKind::Text), + "audio_token" => Some(TokenKind::Audio), + "image_token" => Some(TokenKind::Image), + "video_token" => Some(TokenKind::Video), + _ => None, + } +} + +fn input_unit(unit: &str) -> Option { + if let Some(kind) = token_kind(unit) { + return Some(InputUnit::Token(kind)); + } + match unit { + "character" => Some(InputUnit::Character), + "image" => Some(InputUnit::Image), + "pixel" => Some(InputUnit::Pixel), + "query" => Some(InputUnit::Query { over_results: None }), + "request" => Some(InputUnit::Request), + "second" => Some(InputUnit::Second), + "text_message" => Some(InputUnit::TextMessage), + "audio_per_second" => Some(InputUnit::AudioSecond), + "video_per_second" => Some(InputUnit::VideoSecond { over_seconds: None }), + _ => None, + } +} + +fn output_unit(unit: &str) -> Option { + if let Some(kind) = token_kind(unit) { + return Some(OutputUnit::Token(kind)); + } + match unit.split_once('_') { + Some(("image", label)) => { + return ImageSize::new(label).map(|size| OutputUnit::Image(Some(size))); + } + Some(("second", label)) => { + return Resolution::new(label).map(|resolution| OutputUnit::Second(Some(resolution))); + } + _ => {} + } + match unit { + "reasoning_token" => Some(OutputUnit::ReasoningToken), + "character" => Some(OutputUnit::Character), + "image" => Some(OutputUnit::Image(None)), + "pixel" => Some(OutputUnit::Pixel), + "second" => Some(OutputUnit::Second(None)), + "video_per_second" => Some(OutputUnit::VideoSecond), + _ => None, + } +} + +#[cfg(test)] +mod tests { + use rstest::rstest; + + use super::*; + + const TEXT_INPUT: Meter = Meter::Input(InputUnit::Token(TokenKind::Text)); + const TEXT_OUTPUT: Meter = Meter::Output(OutputUnit::Token(TokenKind::Text)); + + fn key(meter: Meter, band: Band, tier: Option) -> FlatKey { + FlatKey { meter, band, tier } + } + + #[rstest] + #[case::input_token("input_cost_per_token", key(TEXT_INPUT, Band::Base, None))] + #[case::band_and_tier( + "output_cost_per_token_above_272k_tokens_priority", + key( + TEXT_OUTPUT, + Band::over_prompt_tokens(272_000), + Some(TierSuffix::Service(ServiceTier::Priority)) + ) + )] + #[case::band_without_k( + "input_cost_per_token_above_128_tokens", + key(TEXT_INPUT, Band::over_prompt_tokens(128), None) + )] + #[case::zero_band_is_base( + "input_cost_per_token_above_0k_tokens", + key(TEXT_INPUT, Band::Base, None) + )] + #[case::batch( + "input_cost_per_token_batches", + key(TEXT_INPUT, Band::Base, Some(TierSuffix::Batches)) + )] + #[case::reasoning( + "output_cost_per_reasoning_token", + key(Meter::Output(OutputUnit::ReasoningToken), Band::Base, None) + )] + #[case::cache_read_audio( + "cache_read_input_audio_token_cost", + key(Meter::CacheRead { kind: TokenKind::Audio, mode: CacheReadMode::Implicit }, Band::Base, None) + )] + #[case::explicit_cache_read( + "explicit_cache_read_input_token_cost", + key(Meter::CacheRead { kind: TokenKind::Text, mode: CacheReadMode::Explicit }, Band::Base, None) + )] + #[case::cache_write_one_hour_band( + "cache_creation_input_token_cost_above_1hr_above_200k_tokens", + key( + Meter::CacheWrite { kind: TokenKind::Text, ttl: CacheTtl::OneHour }, + Band::over_prompt_tokens(200_000), + None + ) + )] + #[case::cache_write_twelve_hours_priority( + "cache_creation_input_token_cost_above_12hr_above_272k_tokens_priority", + key( + Meter::CacheWrite { kind: TokenKind::Text, ttl: CacheTtl::TwelveHours }, + Band::over_prompt_tokens(272_000), + Some(TierSuffix::Service(ServiceTier::Priority)) + ) + )] + #[case::image_label( + "output_cost_per_image_0.5K", + key( + Meter::Output(OutputUnit::Image(ImageSize::new("0.5K"))), + Band::Base, + None + ) + )] + #[case::image_token_is_a_token( + "output_cost_per_image_token", + key(Meter::Output(OutputUnit::Token(TokenKind::Image)), Band::Base, None) + )] + #[case::resolution( + "output_cost_per_second_720p", + key( + Meter::Output(OutputUnit::Second(Resolution::new("720p"))), + Band::Base, + None + ) + )] + #[case::video_interval( + "input_cost_per_video_per_second_above_8s_interval", + key(Meter::Input(InputUnit::VideoSecond { over_seconds: NonZeroU64::new(8) }), Band::Base, None) + )] + #[case::feature_batch( + "ocr_cost_per_page_batches", + key( + Meter::Feature(Feature::OcrPage), + Band::Base, + Some(TierSuffix::Batches) + ) + )] + #[case::wall_clock("cost_per_second", key(Meter::WallClockSecond, Band::Base, None))] + #[case::browser_open( + "browser_open_cost_per_request", + key(Meter::Feature(Feature::BrowserOpen), Band::Base, None) + )] + #[case::additional_result( + "cost_per_additional_result", + key(Meter::Feature(Feature::AdditionalResult), Band::Base, None) + )] + fn parses_every_key_shape(#[case] text: &str, #[case] expected: FlatKey) { + assert_eq!(FlatKey::parse(text), Some(expected)); + } + + #[rstest] + #[case::typo("input_cost_per_tokne")] + #[case::unused_meter("cost_per_token")] + #[case::other_currency("input_dbu_cost_per_token")] + #[case::cache_hit_alias("input_cost_per_token_cache_hit")] + #[case::non_numeric_band("input_cost_per_token_above_xk_tokens")] + #[case::interval_on_a_token_meter("input_cost_per_token_above_8s_interval")] + #[case::read_has_no_ttl("cache_read_input_token_cost_above_1hr")] + #[case::cache_unit_must_be_token("cache_read_input_character_cost")] + #[case::bad_image_size("output_cost_per_image_big")] + #[case::bad_resolution("output_cost_per_second_hd")] + #[case::unknown_feature("telepathy_cost_per_page")] + #[case::empty("")] + fn rejects_keys_outside_the_grammar(#[case] text: &str) { + assert_eq!(FlatKey::parse(text), None); + } + + #[rstest] + #[case::plain("input_cost_per_token", (Channel::Online, When::default()))] + #[case::service_tier( + "input_cost_per_token_flex", + (Channel::Online, When { tier: ServiceTier::Flex, band: Band::Base }) + )] + #[case::batch( + "input_cost_per_token_above_200k_tokens_batches", + (Channel::Batch, When { tier: ServiceTier::Standard, band: Band::over_prompt_tokens(200_000) }) + )] + #[case::decisions("input_cost_per_token_decisions", (Channel::Decisions, When::default()))] + fn batch_and_decisions_pick_a_channel_not_a_tier( + #[case] text: &str, + #[case] expected: (Channel, When), + ) { + assert_eq!(FlatKey::parse(text).unwrap().channel_and_when(), expected); + } +} diff --git a/litellm-rust/crates/model-catalog/src/wire/lax.rs b/litellm-rust/crates/model-catalog/src/wire/lax.rs new file mode 100644 index 00000000000..d514a6a82c1 --- /dev/null +++ b/litellm-rust/crates/model-catalog/src/wire/lax.rs @@ -0,0 +1,128 @@ +use std::fmt; + +use serde::Deserializer; +use serde::de::{self, Visitor}; +use serde_with::DeserializeAs; + +pub(crate) struct LaxI64; + +pub(crate) struct Count; + +impl<'de> DeserializeAs<'de, i64> for LaxI64 { + fn deserialize_as>(deserializer: D) -> Result { + deserializer.deserialize_any(Self) + } +} + +impl Visitor<'_> for LaxI64 { + type Value = i64; + + fn expecting(&self, formatter: &mut fmt::Formatter<'_>) -> fmt::Result { + formatter.write_str("an integer in the i64 range") + } + + fn visit_i64(self, value: i64) -> Result { + Ok(value) + } + + fn visit_u64(self, value: u64) -> Result { + i64::try_from(value).map_err(E::custom) + } + + fn visit_f64(self, value: f64) -> Result { + integral_float(value).ok_or_else(|| E::custom("expected an integer in the i64 range")) + } + + fn visit_str(self, value: &str) -> Result { + integer_string(value.trim()) + .ok_or_else(|| E::custom("expected an integer in the i64 range")) + } + + fn visit_bool(self, value: bool) -> Result { + Ok(i64::from(value)) + } +} + +impl<'de> DeserializeAs<'de, u64> for Count { + fn deserialize_as>(deserializer: D) -> Result { + let count = LaxI64::deserialize_as(deserializer)?; + u64::try_from(count).map_err(|_| { + de::Error::invalid_value(de::Unexpected::Signed(count), &"a count of zero or more") + }) + } +} + +fn integer_string(value: &str) -> Option { + let integer = match value.split_once('.') { + Some((integer, fraction)) => { + if fraction.is_empty() || !fraction.bytes().all(|byte| byte == b'0') { + return None; + } + integer + } + None => value, + }; + if integer.starts_with('_') || integer.ends_with('_') || integer.contains("__") { + return None; + } + let digits = integer.strip_prefix(['+', '-']).unwrap_or(integer); + if digits.is_empty() + || digits.starts_with('_') + || !digits + .bytes() + .all(|byte| byte.is_ascii_digit() || byte == b'_') + { + return None; + } + integer.replace('_', "").parse().ok() +} + +fn integral_float(value: f64) -> Option { + (value.is_finite() + && value.fract() == 0.0 + && value >= i64::MIN as f64 + && value < -(i64::MIN as f64)) + .then_some(value as i64) +} + +#[cfg(test)] +mod tests { + use rstest::rstest; + use serde_json::{Value, json}; + use serde_with::de::DeserializeAsWrap; + + use super::*; + + fn count(value: Value) -> Option { + DeserializeAsWrap::::deserialize(value) + .ok() + .map(DeserializeAsWrap::into_inner) + } + + use serde::Deserialize; + + #[rstest] + #[case::integer(json!(128000), Some(128_000))] + #[case::whole_float(json!(128000.0), Some(128_000))] + #[case::string(json!(" 8192 "), Some(8192))] + #[case::separated(json!("1_000"), Some(1000))] + #[case::trailing_zeros(json!("2.000"), Some(2))] + #[case::boolean(json!(true), Some(1))] + #[case::maximum(json!(i64::MAX.to_string()), Some(i64::MAX as u64))] + #[case::negative(json!(-5), None)] + #[case::fraction(json!(2.5), None)] + #[case::precise_fraction(json!("1.0000000000000001"), None)] + #[case::exponent(json!("1e3"), None)] + #[case::missing_fraction(json!("2."), None)] + #[case::repeated_separator(json!("2__0"), None)] + #[case::above_i64(json!(u64::MAX), None)] + #[case::float_above_i64(json!(9_223_372_036_854_775_808.0), None)] + #[case::word(json!("8k"), None)] + #[case::object(json!({}), None)] + fn counts_accept_whole_numbers_however_they_are_written( + #[case] written: Value, + #[case] expected: Option, + ) { + assert_eq!(count(written), expected); + } +} diff --git a/litellm-rust/crates/model-catalog/src/wire/mod.rs b/litellm-rust/crates/model-catalog/src/wire/mod.rs new file mode 100644 index 00000000000..e8f23b7bd0d --- /dev/null +++ b/litellm-rust/crates/model-catalog/src/wire/mod.rs @@ -0,0 +1,10 @@ +mod attributes; +mod blocks; +mod entry; +mod flat_key; +mod lax; + +pub use attributes::*; +pub use blocks::*; +pub use entry::*; +pub use flat_key::*; diff --git a/litellm-rust/crates/model-catalog/tests/catalog.rs b/litellm-rust/crates/model-catalog/tests/catalog.rs index d384dfea9a8..30c070cfb52 100644 --- a/litellm-rust/crates/model-catalog/tests/catalog.rs +++ b/litellm-rust/crates/model-catalog/tests/catalog.rs @@ -1,303 +1,405 @@ -use std::path::{Path, PathBuf}; +use std::collections::BTreeSet; -use litellm_model_catalog::{AliasIssue, Catalog, Error, IntegrityLimits, Mode, Provenance}; +use litellm_model_catalog::{ + BUNDLED_REGISTRY, Catalog, Error, ErrorKind, IntegrityLimits, Mode, Rejects, Written, +}; use rstest::{fixture, rstest}; -use serde_json::json; +use serde_json::{Map, Value, json}; const ALPHA_FIXTURE: &[u8] = br#"{ - "sample_spec":{"explanation":"example"}, + "sample_spec":{"explanation":"example","input_cost_per_token":"not checked"}, "fallback_generalizations":{"rules":[{"name":"family","pattern":"^new-","model_info":{"mode":"chat"}}]}, "Alpha":{"litellm_provider":"test","aliases":["short"],"price":0,"enabled":false, "optional":null,"unknown":{"nested":[1,{"x":true}]}} }"#; -#[fixture] -fn repo_root() -> PathBuf { - Path::new(env!("CARGO_MANIFEST_DIR")).join("../../..") -} - -#[fixture] -fn current_catalog(repo_root: PathBuf) -> Catalog { - let body = std::fs::read(repo_root.join("model_prices_and_context_window.json")).unwrap(); - Catalog::parse(&body, Provenance::default()).unwrap() -} - -#[fixture] -fn backup_catalog(repo_root: PathBuf) -> Catalog { - let body = std::fs::read(repo_root.join("litellm/model_prices_and_context_window_backup.json")) - .unwrap(); - Catalog::parse(&body, Provenance::default()).unwrap() -} - #[fixture] fn fixture_catalog() -> Catalog { - Catalog::parse( - ALPHA_FIXTURE, - Provenance { - source: Some("fixture".into()), - revision: Some("rev".into()), - etag: None, - }, - ) - .unwrap() + Catalog::parse(ALPHA_FIXTURE).unwrap().value +} + +fn loaded(document: Value) -> litellm_model_catalog::Loaded { + Catalog::parse(document.to_string().as_bytes()).unwrap() +} + +fn catalog(document: Value) -> Catalog { + loaded(document).value +} + +fn written(catalog: &Catalog) -> String { + let document: Map = catalog + .written() + .map(|(key, value)| { + let value = match value { + Written::Entry(fields) => serde_json::to_value(fields).unwrap(), + Written::Section(value) => value.clone(), + }; + (key.to_owned(), value) + }) + .collect(); + serde_json::to_string(&document).unwrap() +} + +fn report(error: &Error) -> String { + litellm_error::Report::new(error).to_string() +} + +fn error_text(document: Value) -> Vec { + loaded(document).errors.iter().map(report).collect() } #[rstest] #[case::decisions("decisions", Mode::Decisions)] #[case::legacy_evaluation("evaluation", Mode::Evaluation)] fn parses_decision_modes(#[case] mode: &str, #[case] expected: Mode) { - let source = json!({"Test":{"litellm_provider":"test","mode":mode}}).to_string(); - let catalog = Catalog::parse(source.as_bytes(), Provenance::default()).unwrap(); - + let catalog = catalog(json!({"Test": {"litellm_provider": "test", "mode": mode}})); assert_eq!( - catalog.lookup("Test").unwrap().entry.info().mode, + catalog + .lookup("Test") + .unwrap() + .entry + .model() + .unwrap() + .attributes + .mode, Some(expected) ); - assert_eq!(serde_json::to_value(expected).unwrap(), json!(mode)); } #[rstest] -#[ignore] -fn preserves_fields_and_metadata(fixture_catalog: Catalog) { - let catalog = fixture_catalog; - let entry = catalog.lookup("SHORT").unwrap(); - assert_eq!(entry.canonical_key, "Alpha"); - assert_eq!(entry.matched_key, "short"); - assert_eq!(entry.entry.field("price"), Some(&json!(0))); - assert_eq!(entry.entry.field("enabled"), Some(&json!(false))); - assert_eq!(entry.entry.field("optional"), Some(&json!(null))); - assert_eq!(entry.entry.field("missing"), None); +fn unknown_keys_are_kept_raw_and_listed_as_unrecognized(fixture_catalog: Catalog) { + let entry = fixture_catalog.lookup("Alpha").unwrap().entry; assert_eq!( - entry.entry.field("unknown"), + entry.field("unknown"), Some(&json!({"nested":[1,{"x":true}]})) ); - assert_eq!(entry.entry.field("aliases"), None); - assert_eq!(entry.entry.info().litellm_provider.as_deref(), Some("test")); assert_eq!( - catalog.sample_spec(), - Some(&json!({"explanation":"example"})) - ); - assert_eq!(catalog.fallback_rules().unwrap().len(), 1); - assert_eq!(catalog.provenance().revision.as_deref(), Some("rev")); - assert_eq!(catalog.model_count(), 1); -} - -#[rstest] -#[ignore] -fn snapshot_does_not_borrow_source() { - let mut source = ALPHA_FIXTURE.to_vec(); - let catalog = Catalog::parse(&source, Provenance::default()).unwrap(); - source.fill(b' '); - - let entry = catalog.lookup("short").unwrap(); - assert_eq!(entry.canonical_key, "Alpha"); - assert_eq!(entry.entry.field("price"), Some(&json!(0))); -} - -#[rstest] -#[case("Shared", "First")] -#[case("Second", "Second")] -#[case("shared", "Second")] -#[case("FIRST", "First")] -#[case("sHaReD", "Second")] -#[ignore] -fn alias_collisions_and_case_fallback_follow_entry_order( - #[case] lookup: &str, - #[case] expected: &str, -) { - let catalog = Catalog::parse( - br#"{ - "First":{"aliases":["Shared","Second","first"],"value":1}, - "Second":{"aliases":["Shared","sHaReD"],"value":2}, - "SHARED":{"value":3} - }"#, - Provenance::default(), - ) - .unwrap(); - assert_eq!(catalog.lookup(lookup).unwrap().canonical_key, expected); - assert_eq!(catalog.alias_count(), 3); - assert!( - catalog - .alias_issues() - .contains(&AliasIssue::CanonicalCollision { - model: "First".into(), - alias: "Second".into(), - }) - ); - assert!( - catalog - .alias_issues() - .contains(&AliasIssue::AliasCollision { - model: "Second".into(), - alias: "Shared".into(), - }) + fixture_catalog.unrecognized().collect::>(), + BTreeSet::from([ + ("Alpha", "enabled"), + ("Alpha", "price"), + ("Alpha", "unknown") + ]) ); } -#[test] -#[ignore] -fn json_entry_order_controls_alias_ownership_and_case_fallback() { - let forward = Catalog::parse( - br#"{ - "Alpha":{"aliases":["shared"]}, - "Beta":{"aliases":["shared"]}, - "Foo":{}, - "fOO":{} - }"#, - Provenance::default(), - ) - .unwrap(); - let reversed = Catalog::parse( - br#"{ - "fOO":{}, - "Foo":{}, - "Beta":{"aliases":["shared"]}, - "Alpha":{"aliases":["shared"]} - }"#, - Provenance::default(), - ) - .unwrap(); - - assert_eq!(forward.lookup("shared").unwrap().canonical_key, "Alpha"); - assert_eq!(reversed.lookup("shared").unwrap().canonical_key, "Beta"); - assert_eq!(forward.lookup("foo").unwrap().canonical_key, "fOO"); - assert_eq!(reversed.lookup("foo").unwrap().canonical_key, "Foo"); -} - -#[derive(Debug)] -enum ValidationOutcome { - Ok, - Shrunk, - BelowMinimum, - InvalidRatio, -} - #[rstest] -#[case( - IntegrityLimits { - reference_model_count: 2, - min_model_count: 1, - min_reference_ratio: 0.5, - }, - ValidationOutcome::Ok -)] -#[case( - IntegrityLimits { - reference_model_count: 3, - min_model_count: 1, - min_reference_ratio: 0.5, - }, - ValidationOutcome::Shrunk -)] -#[case( - IntegrityLimits { - reference_model_count: 0, - min_model_count: 2, - min_reference_ratio: 0.5, - }, - ValidationOutcome::BelowMinimum -)] -#[case( - IntegrityLimits { - reference_model_count: 0, - min_model_count: 0, - min_reference_ratio: f64::NAN, - }, - ValidationOutcome::InvalidRatio -)] -#[ignore] -fn integrity_uses_canonical_count_and_strict_shrink_boundary( - #[case] limits: IntegrityLimits, - #[case] expected: ValidationOutcome, -) { - let catalog = Catalog::parse( - br#"{"sample_spec":{},"fallback_generalizations":{"rules":[]},"a":{"aliases":["b","c"]}}"#, - Provenance::default(), - ) - .unwrap(); - let actual = catalog.validate(limits); - match expected { - ValidationOutcome::Ok => assert!(actual.is_ok()), - ValidationOutcome::Shrunk => { - assert!(matches!(actual, Err(Error::Shrunk { actual: 1, .. }))) - } - ValidationOutcome::BelowMinimum => { - assert!(matches!(actual, Err(Error::BelowMinimum { actual: 1, .. }))) - } - ValidationOutcome::InvalidRatio => assert!(matches!(actual, Err(Error::InvalidRatio))), - } -} - -#[derive(Debug)] -enum MalformedOutcome { - Empty, - Json, - EntryNotObject, -} - -#[rstest] -#[case::empty(b"{}", MalformedOutcome::Empty)] -#[case::invalid_json(b"{", MalformedOutcome::Json)] -#[case::entry_not_object(br#"{"a":1}"#, MalformedOutcome::EntryNotObject)] -#[case::fallback_rules_missing( - br#"{"fallback_generalizations":{},"a":{}}"#, - MalformedOutcome::Json -)] -#[ignore] -fn malformed_input_and_aliases_have_typed_outcomes( - #[case] body: &[u8], - #[case] expected: MalformedOutcome, -) { - let actual = Catalog::parse(body, Provenance::default()); - match expected { - MalformedOutcome::Empty => assert!(matches!(actual, Err(Error::Empty))), - MalformedOutcome::Json => assert!(matches!(actual, Err(Error::Json(_)))), - MalformedOutcome::EntryNotObject => { - assert!(matches!(actual, Err(Error::EntryNotObject { .. }))) - } - } -} - -#[rstest] -#[ignore] -fn invalid_aliases_are_reported_not_fatal() { - let catalog = Catalog::parse( - br#"{"a":{"aliases":"bad"},"b":{"aliases":[9,"ok"]}}"#, - Provenance::default(), - ) - .unwrap(); +fn sections_aliases_and_raw_fields_are_read_in_their_document_views(fixture_catalog: Catalog) { + let found = fixture_catalog.lookup("SHORT").unwrap(); + assert_eq!(found.canonical_key, "Alpha"); + assert_eq!(found.matched_key, "short"); + assert_eq!(found.entry.field("optional"), Some(&json!(null))); + assert_eq!(found.entry.field("aliases"), Some(&json!(["short"]))); assert_eq!( - catalog.alias_issues(), - &[ - AliasIssue::InvalidList { model: "a".into() }, - AliasIssue::InvalidName { model: "b".into() }, - ] + fixture_catalog.sample_spec(), + Some(&json!({"explanation":"example","input_cost_per_token":"not checked"})) + ); + assert_eq!(fixture_catalog.fallback_rules().unwrap()[0].name, "family"); + assert_eq!(fixture_catalog.model_count(), 1); + assert_eq!( + fixture_catalog + .served() + .map(|(key, _)| key) + .collect::>(), + ["Alpha", "short"] ); - assert_eq!(catalog.lookup("ok").unwrap().canonical_key, "b"); - assert!(catalog.lookup("missing").is_none()); } #[rstest] -#[ignore] -fn parses_current_and_packaged_catalogs_against_independent_baseline( - current_catalog: Catalog, - backup_catalog: Catalog, -) { - assert!(current_catalog.model_count() > 0); - assert!(backup_catalog.model_count() > 0); - assert!(current_catalog.sample_spec().is_some()); - assert!(backup_catalog.sample_spec().is_some()); - // Snapshot from 2026-09-23; the backup file mirrors the current file and cannot detect shrinkage. - const REFERENCE_MODEL_COUNT: usize = 4303; - current_catalog - .validate(IntegrityLimits { - reference_model_count: REFERENCE_MODEL_COUNT, - min_model_count: 50, - min_reference_ratio: 0.9, - }) - .unwrap(); - assert!(current_catalog.model_names().all(|name| { - let entry = current_catalog.lookup(name).unwrap().entry; - entry.info().litellm_provider.is_some() == entry.field("litellm_provider").is_some() +fn a_bad_entry_is_reported_by_model_and_key_and_kept_raw() { + let parsed = loaded(json!({ + "Good": {"litellm_provider": "test"}, + "Bad": {"litellm_provider": "test", "mode": "chatt", "input_cost_per_token": "free"}, + "Worse": {"mode": "chat"} })); + let catalog = parsed.value; + let problems: Vec = parsed.errors.iter().map(report).collect(); + assert_eq!(problems.len(), 3, "{problems:?}"); + assert!(problems[0].starts_with("Bad.mode: invalid value: unknown variant `chatt`")); + assert!(problems[1].starts_with("Bad.input_cost_per_token: invalid value")); + assert_eq!(problems[2], "Worse.litellm_provider: required"); + assert!(catalog.lookup("Good").unwrap().entry.model().is_some()); + assert!(catalog.lookup("Bad").unwrap().entry.model().is_none()); + assert_eq!(catalog.model_count(), 3); + assert!( + parsed + .errors + .iter() + .find(|error| error.rejects() == Rejects::Document) + .is_none() + ); +} + +#[rstest] +#[case::alias_names_a_model( + json!({"First": {"litellm_provider": "t", "aliases": ["Second"]}, "Second": {"litellm_provider": "t"}}), + r#"First: alias "Second" is already a model name"# +)] +#[case::alias_claimed_twice( + json!({"First": {"litellm_provider": "t", "aliases": ["shared"]}, "Second": {"litellm_provider": "t", "aliases": ["shared"]}}), + r#"Second: alias "shared" already belongs to First"# +)] +#[case::aliases_not_a_list( + json!({"a": {"litellm_provider": "t", "aliases": "bad"}}), + "a.aliases: invalid value: invalid type: string \"bad\", expected a sequence" +)] +#[case::entry_not_object( + json!({"a": 1, "valid": {"litellm_provider": "test"}}), + "a: must be a JSON object" +)] +#[case::fallback_rules_missing( + json!({"fallback_generalizations": {}, "a": {"litellm_provider": "t"}}), + "fallback_generalizations: invalid value: missing field `rules`" +)] +#[case::unknown_timezone( + json!({"a": {"litellm_provider": "t", "off_peak_pricing": { + "windows": [{"hours_utc": "00:00-01:00"}], + "weekday_timezone": "Not/AZone", + "input_cost_per_token": 1e-6 + }}}), + r#"a.off_peak_pricing.weekday_timezone: "Not/AZone" is not an IANA time zone"# +)] +fn document_level_problems_are_reported(#[case] document: Value, #[case] expected: &str) { + assert_eq!(error_text(document), [expected]); +} + +#[rstest] +fn escaped_row_paths_and_row_validation_share_the_parse_rules() { + let document = json!({ + "open/router~v1": {"litellm_provider": "test", "input_cost_per_token": -1} + }); + let parsed = loaded(document); + let fields = parsed + .value + .lookup("open/router~v1") + .unwrap() + .entry + .fields(); + let row_errors = Catalog::row_errors("open/router~v1", fields); + assert_eq!( + row_errors + .iter() + .map(|error| (error.path(), report(error))) + .collect::>(), + parsed + .errors + .iter() + .map(|error| (error.path(), report(error))) + .collect::>() + ); + assert_eq!( + row_errors[0].path(), + "/open~1router~0v1/input_cost_per_token" + ); + assert!(row_errors[0].kind() == ErrorKind::Invalid); +} + +#[rstest] +fn malformed_fallback_is_collected_while_models_are_read() { + let parsed = loaded(json!({ + "fallback_generalizations": {"rules": "bad"}, + "a": {"litellm_provider": "test"} + })); + assert_eq!(parsed.value.model_count(), 1); + assert_eq!(parsed.errors.len(), 1); + assert_eq!(parsed.errors[0].path(), "/fallback_generalizations"); +} + +#[rstest] +fn rejected_rows_and_their_aliases_are_removed_without_disturbing_written_order() { + let body = r#"{"before":{"litellm_provider":"test","aliases":["before-alias"]},"bad":{"litellm_provider":"test","aliases":["bad-alias"],"mode":"chatt"},"not-object":4,"sample_spec":{"keep":true},"after":{"litellm_provider":"test"}}"#; + let parsed = Catalog::parse(body.as_bytes()).unwrap(); + let (catalog, removed) = parsed.value.without_rejected(&parsed.errors); + + assert_eq!(removed.len(), 2); + assert_eq!( + catalog.lookup("before-alias").unwrap().canonical_key, + "before" + ); + assert_eq!( + catalog.lookup("BEFORE-ALIAS").unwrap().matched_key, + "before-alias" + ); + assert!(catalog.lookup("bad").is_none()); + assert!(catalog.lookup("BAD").is_none()); + assert!(catalog.lookup("Bad-Alias").is_none()); + assert_eq!(catalog.model_count(), 2); + assert_eq!( + written(&catalog), + r#"{"before":{"litellm_provider":"test","aliases":["before-alias"]},"sample_spec":{"keep":true},"after":{"litellm_provider":"test"}}"# + ); +} + +#[rstest] +fn invalid_empty_key_rows_are_removed() { + let parsed = loaded(json!({ + "": {"litellm_provider": "test", "mode": "chatt"}, + "good": {"litellm_provider": "test"} + })); + assert_eq!(parsed.errors[0].path(), "//mode"); + + let (catalog, removed) = parsed.value.without_rejected(&parsed.errors); + assert_eq!(catalog.model_count(), 1); + assert!(catalog.lookup("").is_none()); + assert!(catalog.lookup("good").is_some()); + assert_eq!(removed.len(), 1); +} + +#[rstest] +fn timezone_errors_reject_providerless_rows_without_rejecting_other_providerless_rows() { + let parsed = loaded(json!({ + "good": {"mode": "chat"}, + "bad": {"off_peak_pricing": { + "windows": [{"hours_utc": "00:00-01:00"}], + "weekday_timezone": "Not/AZone", + "input_cost_per_token": 1e-6 + }} + })); + assert_eq!(parsed.errors.len(), 3); + assert!( + parsed + .errors + .iter() + .any(|error| error.kind() == ErrorKind::UnknownTimezone) + ); + + let (catalog, removed) = parsed.value.without_rejected(&parsed.errors); + assert_eq!(catalog.model_count(), 1); + assert!(catalog.lookup("good").is_some()); + assert!(catalog.lookup("bad").is_none()); + assert_eq!(removed.len(), 2); +} + +#[rstest] +fn bundled_per_row_errors_match_document_errors() { + let parsed = Catalog::parse(BUNDLED_REGISTRY).unwrap(); + let row_errors: Vec<_> = parsed + .value + .written() + .flat_map(|(key, written)| match written { + Written::Entry(fields) => Catalog::row_errors(key, fields), + Written::Section(_) => Vec::new(), + }) + .map(|error| (error.path().to_owned(), report(&error))) + .collect(); + let document_errors: Vec<_> = parsed + .errors + .iter() + .map(|error| (error.path().to_owned(), report(error))) + .collect(); + + assert_eq!(row_errors, document_errors); +} + +#[rstest] +fn three_hundred_rows_filter_one_row_with_two_invalid_prices() { + let valid_rows: Map = (0..299) + .map(|index| { + ( + format!("valid-{index:03}"), + json!({"litellm_provider": "test"}), + ) + }) + .collect(); + let mut document = valid_rows; + document.insert( + "bad".to_owned(), + json!({ + "litellm_provider": "test", + "input_cost_per_token": -1, + "output_cost_per_token": -1 + }), + ); + let parsed = Catalog::parse(serde_json::to_vec(&document).unwrap().as_slice()).unwrap(); + assert_eq!(parsed.value.model_count(), 300); + assert_eq!(parsed.errors.len(), 2); + + let (catalog, removed) = parsed.value.without_rejected(&parsed.errors); + assert_eq!(catalog.model_count(), 299); + assert_eq!(removed.len(), 2); +} + +#[rstest] +fn integrity_limits_count_canonical_models_not_aliases() { + let fetched = catalog(json!({"a": {"litellm_provider": "t", "aliases": ["b", "c"]}})); + assert!( + fetched + .check_size(2, IntegrityLimits::new(1, 0.5).unwrap()) + .is_ok() + ); + assert_eq!( + fetched + .check_size(3, IntegrityLimits::new(1, 0.5).unwrap()) + .unwrap_err() + .kind(), + ErrorKind::Shrunk + ); + assert_eq!( + fetched + .check_size(2, IntegrityLimits::new(2, 0.5).unwrap()) + .unwrap_err() + .kind(), + ErrorKind::BelowMinimum + ); +} + +#[rstest] +#[case::empty(b"{}", "empty")] +#[case::only_sections(br#"{"sample_spec":{}}"#, "empty")] +#[case::invalid_json(b"{", "json")] +#[case::array_root_is_json_error(b"[]", "json")] +fn malformed_documents_are_rejected_whole(#[case] body: &[u8], #[case] kind: &str) { + let error = Catalog::parse(body).unwrap_err(); + assert_eq!(error.rejects(), Rejects::Document); + assert_eq!(<&str>::from(error.kind()), kind); +} + +#[rstest] +fn written_is_the_document_in_order_including_sections_and_bad_entries() { + let body = concat!( + r#"{"b":{"litellm_provider":"t","z":1,"a":null},"sample_spec":{"x":"y"},"n":4,"#, + r#""fallback_generalizations":{"rules":"bad"},"a":{"mode":"chatt","price":1.0}}"# + ); + let catalog = Catalog::parse(body.as_bytes()).unwrap().value; + assert_eq!(written(&catalog), body); + assert_eq!(catalog.model_count(), 2); +} + +#[rstest] +fn the_bundled_registry_parses_with_no_problems_and_every_key_understood() { + let loaded = Catalog::parse(BUNDLED_REGISTRY).unwrap(); + let catalog = loaded.value; + assert!(loaded.errors.is_empty(), "{:#?}", loaded.errors); + let unrecognized: Vec<_> = catalog.unrecognized().collect(); + assert!(unrecognized.is_empty(), "{unrecognized:#?}"); + assert!( + catalog + .fallback_rules() + .is_some_and(|rules| !rules.is_empty()) + ); + const REFERENCE_MODEL_COUNT: usize = 4303; + assert!(catalog.model_count() as f64 >= REFERENCE_MODEL_COUNT as f64 * 0.9); +} + +#[rstest] +fn the_bundled_registry_is_written_back_as_it_was_read() { + let document: Value = serde_json::from_slice(BUNDLED_REGISTRY).unwrap(); + assert_eq!( + written(&Catalog::parse(BUNDLED_REGISTRY).unwrap().value), + serde_json::to_string(&document).unwrap() + ); +} + +#[rstest] +fn a_bad_value_keeps_its_json_error_as_the_source_and_names_its_key_and_field() { + let parsed = + loaded(json!({"open/router": {"litellm_provider": "t", "input_cost_per_token": "free"}})); + let error = &parsed.errors[0]; + let cause = litellm_error::find::(error) + .expect("the JSON error is in the chain") + .to_string(); + assert_eq!(report(error).matches(&cause).count(), 1); + assert!(!error.to_string().contains(&cause)); + assert_eq!(error.key().as_deref(), Some("open/router")); + assert_eq!(error.field().as_deref(), Some("input_cost_per_token")); } diff --git a/litellm-rust/crates/model-catalog/tests/generate_price_lookup_reference.py b/litellm-rust/crates/model-catalog/tests/generate_price_lookup_reference.py new file mode 100644 index 00000000000..e49b635ff4a --- /dev/null +++ b/litellm-rust/crates/model-catalog/tests/generate_price_lookup_reference.py @@ -0,0 +1,91 @@ +import itertools +import json +import re +import subprocess +from pathlib import Path +from typing import Final + +from litellm.litellm_core_utils.llm_cost_calc.utils import _get_token_base_cost +from litellm.types.utils import Usage + +REPO_ROOT: Final = Path(__file__).resolve().parents[4] +TOKEN_RATE_KEY: Final = re.compile( + r"^(input_cost_per_token|output_cost_per_token|cache_read_input_token_cost" + r"|cache_creation_input_token_cost(_above_1hr)?)" + r"(_above_(\d+)(k?)_tokens)?(_(priority|flex|ultrafast|balanced|batches|decisions))?$" +) +SERVICE_TIERS: Final = ("priority", "flex", "ultrafast", "balanced") +LARGEST_PROMPT: Final = 10_000_000 +INCLUSIVE_PROVIDERS: Final = frozenset({"xai"}) + + +def token_rates(entry: dict[str, object]) -> dict[str, object]: + return { + key: value + for key, value in entry.items() + if value is not None and (key == "tiered_pricing" or TOKEN_RATE_KEY.match(key)) + } + + +def band_floors(info: dict[str, object]) -> frozenset[int]: + matches: Final = (TOKEN_RATE_KEY.match(key) for key in info) + flat: Final = frozenset( + int(match.group(4)) * (1000 if match.group(5) else 1) + for match in matches + if match is not None and match.group(4) is not None + ) + rows: Final = info.get("tiered_pricing") + tiers: Final = ( + frozenset(int(row["range"][0]) for row in rows if isinstance(row, dict) and "range" in row) + if isinstance(rows, list) + else frozenset() + ) + return flat | tiers + + +def tiers_in(info: dict[str, object]) -> tuple[str | None, ...]: + return (None, *(tier for tier in SERVICE_TIERS if any(key.endswith(f"_{tier}") for key in info))) + + +def prompts(info: dict[str, object]) -> tuple[int, ...]: + floors: Final = band_floors(info) + return tuple(sorted(({1, LARGEST_PROMPT} | floors | {floor + 1 for floor in floors}) - {0})) + + +def check(info: dict[str, object], tier: str | None, prompt: int, inclusive: bool) -> list[object]: + usage: Final = Usage(prompt_tokens=prompt, completion_tokens=1, total_tokens=prompt + 1) + rates: Final = _get_token_base_cost(info, usage, service_tier=tier, threshold_is_inclusive=inclusive) + one_hour: Final = rates.cache_creation_rates_by_ttl.get("1hr", rates.cache_creation_rate) + return [tier, prompt, [rates.input_rate, rates.output_rate, rates.cache_creation_rate, one_hour, rates.cache_read_rate]] + + +def shape(info: dict[str, object], inclusive: bool) -> str: + rows: Final = info.get("tiered_pricing") + row_keys: Final = [sorted(row) for row in rows if isinstance(row, dict)] if isinstance(rows, list) else [] + return json.dumps([sorted(info), row_keys, inclusive]) + + +def checks(info: dict[str, object], inclusive: bool) -> list[list[object]]: + return [check(info, tier, prompt, inclusive) for tier, prompt in itertools.product(tiers_in(info), prompts(info))] + + +def main() -> None: + registry: Final = json.loads((REPO_ROOT / "model_prices_and_context_window.json").read_text()) + entries: Final = tuple( + (token_rates(entry), entry.get("litellm_provider") in INCLUSIVE_PROVIDERS) + for name, entry in registry.items() + if name not in ("sample_spec", "fallback_generalizations") and isinstance(entry, dict) + ) + by_shape: Final = {shape(info, inclusive): (info, inclusive) for info, inclusive in reversed(entries) if info} + models: Final = tuple( + json.dumps({"info": info, "inclusive": inclusive, "checks": checks(info, inclusive)}) + for info, inclusive in by_shape.values() + ) + revision: Final = subprocess.check_output(("git", "rev-parse", "HEAD"), text=True, cwd=REPO_ROOT).strip() + Path(__file__).with_name("price_lookup_reference.json").write_text( + f'{{"python_reference_commit": "{revision}", "models": [\n' + ",\n".join(models) + "\n]}\n" + ) + + +if __name__ == "__main__": + main() diff --git a/litellm-rust/crates/model-catalog/tests/price_lookup.rs b/litellm-rust/crates/model-catalog/tests/price_lookup.rs new file mode 100644 index 00000000000..cc16e9f23e9 --- /dev/null +++ b/litellm-rust/crates/model-catalog/tests/price_lookup.rs @@ -0,0 +1,89 @@ +use litellm_cost::money::UnitPrice; +use litellm_cost::price::{ + CacheReadMode, CacheTtl, InputUnit, Meter, OutputUnit, Prices, ServiceTier, TokenKind, +}; +use litellm_model_catalog::wire::{EntryWire, Fields}; +use rstest::rstest; +use serde::Deserialize; + +#[derive(Deserialize)] +struct Reference { + models: Vec, +} + +#[derive(Deserialize)] +struct ReferenceModel { + info: Fields, + inclusive: bool, + checks: Vec<(Option, u64, [f64; 5])>, +} + +const METERS: [Meter; 5] = [ + Meter::Input(InputUnit::Token(TokenKind::Text)), + Meter::Output(OutputUnit::Token(TokenKind::Text)), + Meter::CacheWrite { + kind: TokenKind::Text, + ttl: CacheTtl::Default, + }, + Meter::CacheWrite { + kind: TokenKind::Text, + ttl: CacheTtl::OneHour, + }, + Meter::CacheRead { + kind: TokenKind::Text, + mode: CacheReadMode::Implicit, + }, +]; + +fn service_tier(name: Option<&str>) -> ServiceTier { + match name { + None => ServiceTier::Standard, + Some("priority") => ServiceTier::Priority, + Some("flex") => ServiceTier::Flex, + Some("ultrafast") => ServiceTier::Ultrafast, + Some("balanced") => ServiceTier::Balanced, + Some(other) => panic!("the reference uses an unknown service tier {other}"), + } +} + +fn mismatch( + prices: &Prices, + (tier_name, prompt, python): &(Option, u64, [f64; 5]), +) -> Option { + let tier = service_tier(tier_name.as_deref()); + let band = prices.band(tier, *prompt); + let rust = METERS + .each_ref() + .map(|meter| prices.rate(meter, tier, band).map_or(0.0, UnitPrice::get)); + (rust != *python) + .then(|| format!("tier={tier_name:?} prompt={prompt}: rust {rust:?}, python {python:?}")) +} + +#[rstest] +fn band_and_rate_match_python_token_base_cost() { + let reference: Reference = + serde_json::from_str(include_str!("price_lookup_reference.json")).unwrap(); + + let mismatches: Vec = reference + .models + .iter() + .flat_map(|model| { + let provider = if model.inclusive { "xai" } else { "openai" }; + let fields: Fields = model + .info + .clone() + .into_iter() + .chain([("litellm_provider".to_owned(), provider.into())]) + .collect(); + let prices = Prices::try_from(&EntryWire::read(&fields)).unwrap(); + model + .checks + .iter() + .filter_map(move |check| mismatch(&prices, check)) + .map(move |found| format!("{:?} {found}", model.info)) + }) + .collect(); + + assert!(reference.models.len() > 50); + assert!(mismatches.is_empty(), "{mismatches:#?}"); +} diff --git a/litellm-rust/crates/model-catalog/tests/price_lookup_reference.json b/litellm-rust/crates/model-catalog/tests/price_lookup_reference.json new file mode 100644 index 00000000000..4b87b696723 --- /dev/null +++ b/litellm-rust/crates/model-catalog/tests/price_lookup_reference.json @@ -0,0 +1,89 @@ +{"python_reference_commit": "c7c895db456eda349a7be9661b4b21f578f9b589", "models": [ +{"info": {"cache_creation_input_token_cost": 1.25e-05, "cache_creation_input_token_cost_above_272k_tokens": 2.5e-05, 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"output_cost_per_token": 3e-05, "output_cost_per_token_above_272k_tokens": 4.5e-05, "output_cost_per_token_priority": 6e-05, "output_cost_per_token_above_272k_tokens_priority": 9e-05}, "inclusive": false, "checks": [[null, 1, [5e-06, 3e-05, 5e-06, 5e-06, 5e-07]], [null, 272000, [5e-06, 3e-05, 5e-06, 5e-06, 5e-07]], [null, 272001, [1e-05, 4.5e-05, 1e-05, 1e-05, 1e-06]], [null, 10000000, [1e-05, 4.5e-05, 1e-05, 1e-05, 1e-06]], ["priority", 1, [1e-05, 6e-05, 1e-05, 1e-05, 1e-06]], ["priority", 272000, [1e-05, 6e-05, 1e-05, 1e-05, 1e-06]], ["priority", 272001, [2e-05, 9e-05, 2e-05, 2e-05, 2e-06]], ["priority", 10000000, [2e-05, 9e-05, 2e-05, 2e-05, 2e-06]]]}, +{"info": {"cache_read_input_token_cost": 3.125e-07, "input_cost_per_token": 1.25e-06, "input_cost_per_token_batches": 6.25e-07, "input_cost_per_token_priority": 2.1875e-06, "output_cost_per_token": 1e-05, "output_cost_per_token_batches": 5e-06, "output_cost_per_token_priority": 1.75e-05}, "inclusive": false, "checks": [[null, 1, [1.25e-06, 1e-05, 1.25e-06, 1.25e-06, 3.125e-07]], [null, 10000000, [1.25e-06, 1e-05, 1.25e-06, 1.25e-06, 3.125e-07]], ["priority", 1, [2.1875e-06, 1.75e-05, 2.1875e-06, 2.1875e-06, 3.125e-07]], ["priority", 10000000, [2.1875e-06, 1.75e-05, 2.1875e-06, 2.1875e-06, 3.125e-07]]]} +]} diff --git a/litellm-rust/crates/model-catalog/tests/registry_validation.rs b/litellm-rust/crates/model-catalog/tests/registry_validation.rs deleted file mode 100644 index 67589010aba..00000000000 --- a/litellm-rust/crates/model-catalog/tests/registry_validation.rs +++ /dev/null @@ -1,93 +0,0 @@ -use std::path::{Path, PathBuf}; - -use litellm_model_catalog::{ - Catalog, FallbackGeneralizations, Provenance, validate_model_entry, validate_registry, -}; -use rstest::{fixture, rstest}; -use serde_json::{Map, Value}; - -#[fixture] -fn repo_root() -> PathBuf { - Path::new(env!("CARGO_MANIFEST_DIR")).join("../../..") -} - -#[rstest] -#[case("model_prices_and_context_window.json")] -#[case("litellm/model_prices_and_context_window_backup.json")] -#[ignore] -fn checked_in_registry_passes_strict_validation(repo_root: PathBuf, #[case] filename: &str) { - let body = std::fs::read(repo_root.join(filename)).unwrap(); - let catalog = Catalog::parse(&body, Provenance::default()).unwrap(); - validate_registry(&catalog).unwrap(); -} - -#[rstest] -#[ignore] -fn fallback_generalizations_are_typed(repo_root: PathBuf) { - let body = std::fs::read(repo_root.join("model_prices_and_context_window.json")).unwrap(); - let document: Map = serde_json::from_slice(&body).unwrap(); - let Some(raw_rules) = document.get("fallback_generalizations") else { - return; - }; - let _: FallbackGeneralizations = serde_json::from_value(raw_rules.clone()).unwrap(); - let catalog = Catalog::parse(&body, Provenance::default()).unwrap(); - assert!( - catalog - .fallback_rules() - .is_some_and(|rules| !rules.is_empty()) - ); -} - -#[rstest] -#[case::missing_provider(serde_json::json!({"mode": "chat"}), "litellm_provider")] -#[case::unknown_field(serde_json::json!({"litellm_provider": "test", "typo": true}), "unknown field")] -#[case::negative_price(serde_json::json!({"litellm_provider": "test", "input_cost_per_token": -1}), "nonnegative")] -#[case::negative_nested_price(serde_json::json!({"litellm_provider": "test", "guardrail_cost_per_unit": {"unit": -1}}), "nonnegative")] -#[case::invalid_mode(serde_json::json!({"litellm_provider": "test", "mode": "invalid"}), "unknown variant")] -#[case::invalid_date(serde_json::json!({"litellm_provider": "test", "deprecation_date": "2026-02-31"}), "deprecation_date")] -#[case::invalid_hours(serde_json::json!({"litellm_provider": "test", "off_peak_pricing": {"hours_utc": "25:00-01:00"}}), "hours_utc")] -#[case::empty_windows(serde_json::json!({"litellm_provider": "test", "off_peak_pricing": {"windows": []}}), "windows is empty")] -#[case::invalid_weekday(serde_json::json!({"litellm_provider": "test", "off_peak_pricing": {"windows": [{"hours_utc": "00:00-01:00", "weekdays": [0]}]}}), "weekdays is invalid")] -#[case::invalid_aliases(serde_json::json!({"litellm_provider": "test", "aliases": ["good", 7]}), "aliases must contain strings")] -#[case::null_aliases(serde_json::json!({"litellm_provider": "test", "aliases": null}), "aliases must be an array")] -#[ignore] -fn registry_validation_rejects_malformed_entries(#[case] entry: Value, #[case] expected: &str) { - assert!( - validate_model_entry("test", &entry) - .unwrap_err() - .to_string() - .contains(expected) - ); -} - -#[test] -#[ignore] -fn checked_in_catalog_and_backup_match() { - let root = Path::new(env!("CARGO_MANIFEST_DIR")).join("../../.."); - let current = std::fs::read(root.join("model_prices_and_context_window.json")).unwrap(); - let backup = - std::fs::read(root.join("litellm/model_prices_and_context_window_backup.json")).unwrap(); - assert_eq!(current, backup); - let catalog = Catalog::parse(¤t, Provenance::default()).unwrap(); - assert!( - catalog.alias_issues().is_empty(), - "invalid registry aliases" - ); -} - -#[rstest] -#[case::input("input_cost_per_token_above_100k_tokens")] -#[case::input_batches("input_cost_per_token_above_100k_tokens_batches")] -#[case::output("output_cost_per_token_above_100k_tokens")] -#[case::output_batches("output_cost_per_token_above_100k_tokens_batches")] -#[case::cache_creation("cache_creation_input_token_cost_above_100k_tokens")] -#[case::cache_creation_batches("cache_creation_input_token_cost_above_100k_tokens_batches")] -#[case::cache_creation_1hr("cache_creation_input_token_cost_above_1hr_above_100k_tokens")] -#[case::cache_read("cache_read_input_token_cost_above_100k_tokens")] -#[case::cache_read_batches("cache_read_input_token_cost_above_100k_tokens_batches")] -fn registry_validation_keeps_above_100k_tier_rates(#[case] field: &str) { - let mut entry = Map::new(); - entry.insert("litellm_provider".into(), "anthropic".into()); - entry.insert(field.into(), 5e-7.into()); - validate_model_entry("test", &Value::Object(entry)).unwrap(); -} diff --git a/litellm-rust/crates/model-catalog/tests/schema.rs b/litellm-rust/crates/model-catalog/tests/schema.rs index f9a028a78ab..464cf069cac 100644 --- a/litellm-rust/crates/model-catalog/tests/schema.rs +++ b/litellm-rust/crates/model-catalog/tests/schema.rs @@ -1,16 +1,17 @@ #![cfg(feature = "schema")] -use std::collections::BTreeSet; -use std::path::Path; - -use litellm_model_catalog::{model_entry_json_schema, registry_json_schema}; +use litellm_model_catalog::{BUNDLED_REGISTRY, model_entry_json_schema, registry_json_schema}; use rstest::rstest; -use serde_json::{Value, json}; +use serde_json::{Map, Value, json}; fn schema() -> Value { serde_json::to_value(model_entry_json_schema()).expect("generated schema serializes") } +fn checked_in_catalog() -> Value { + serde_json::from_slice(BUNDLED_REGISTRY).unwrap() +} + fn registry_validator() -> jsonschema::Validator { let schema = serde_json::to_value(registry_json_schema()).unwrap(); jsonschema::options() @@ -19,26 +20,21 @@ fn registry_validator() -> jsonschema::Validator { .expect("generated registry schema is valid") } -#[rstest] -#[case("model_prices_and_context_window.json")] -#[case("litellm/model_prices_and_context_window_backup.json")] -#[ignore] -fn generated_registry_schema_validates_checked_in_catalog(#[case] path: &str) { - let root = Path::new(env!("CARGO_MANIFEST_DIR")).join("../../.."); - let catalog: Value = serde_json::from_slice(&std::fs::read(root.join(path)).unwrap()).unwrap(); +#[test] +fn generated_registry_schema_validates_checked_in_catalog() { + let catalog = checked_in_catalog(); let validator = registry_validator(); let errors: Vec<_> = validator .iter_errors(&catalog) .map(|error| error.to_string()) .collect(); - assert!(errors.is_empty(), "{path}: {errors:?}"); + assert!(errors.is_empty(), "{errors:?}"); } #[rstest] #[case(json!({"example": {"litellm_provider": "test"}}))] #[case(json!({"example": {"litellm_provider": "test", "future_field": true}}))] #[case(json!({"sample_spec": {"litellm_provider": "placeholder"}}))] -#[ignore] fn generated_registry_schema_keeps_reader_compatibility(#[case] document: Value) { assert!(registry_validator().is_valid(&document)); } @@ -59,47 +55,55 @@ fn generated_registry_schema_keeps_reader_compatibility(#[case] document: Value) #[case::invalid_weekday(json!({"litellm_provider": "test", "off_peak_pricing": {"windows": [{"hours_utc": "00:00-01:00", "weekdays": [0]}]}}))] #[case::invalid_aliases(json!({"litellm_provider": "test", "aliases": "wrong"}))] #[case::non_object_model(json!(4))] -#[ignore] fn generated_registry_schema_rejects_invalid_entries(#[case] entry: Value) { assert!(!registry_validator().is_valid(&json!({"example": entry}))); } -#[rstest] -#[case("model_prices_and_context_window.json")] -#[case("litellm/model_prices_and_context_window_backup.json")] -#[ignore] -fn generated_schema_covers_catalog_fields(#[case] path: &str) { - let root = Path::new(env!("CARGO_MANIFEST_DIR")).join("../../.."); - let catalog: Value = serde_json::from_slice(&std::fs::read(root.join(path)).unwrap()).unwrap(); +#[test] +fn generated_schema_covers_catalog_fields() { + let catalog = checked_in_catalog(); let schema = schema(); - let properties = schema["properties"] + let any_value = |keys: &Value| -> Map { + keys.as_object() + .expect("schema keys are an object") + .keys() + .map(|key| (key.clone(), json!({}))) + .collect() + }; + let keys_only = json!({ + "type": "object", + "properties": any_value(&schema["properties"]), + "patternProperties": any_value(&schema["patternProperties"]), + "additionalProperties": false, + }); + let registry = serde_json::to_value(registry_json_schema()).unwrap(); + let sections = registry["properties"] .as_object() - .expect("ModelInfo schema has properties"); - let fields: BTreeSet<&str> = catalog + .expect("registry has sections"); + let fields: Map = catalog .as_object() .expect("catalog is an object") .iter() - .filter(|(name, _)| *name != "sample_spec" && *name != "fallback_generalizations") + .filter(|(name, _)| !sections.contains_key(*name)) .flat_map(|(_, entry)| entry.as_object().expect("model entry is an object").keys()) - .map(String::as_str) - .filter(|name| *name != "aliases") + .map(|name| (name.clone(), Value::Null)) .collect(); - let missing: Vec<_> = fields - .into_iter() - .filter(|name| !properties.contains_key(*name)) + let missing: Vec<_> = jsonschema::validator_for(&keys_only) + .unwrap() + .iter_errors(&Value::Object(fields)) + .map(|error| error.to_string()) .collect(); assert!( missing.is_empty(), - "{path}: fields missing from schema: {missing:?}" + "fields missing from schema: {missing:?}" ); } #[rstest] #[case("Mode", "chat")] -#[case("ReasoningEffort", "high")] +#[case("EffortLevel", "high")] #[case("InputModality", "image")] -#[ignore] fn generated_schema_includes_enum_values(#[case] definition: &str, #[case] value: &str) { let schema = schema(); let variants = schema["$defs"][definition]["enum"] @@ -110,7 +114,6 @@ fn generated_schema_includes_enum_values(#[case] definition: &str, #[case] value } #[test] -#[ignore] fn generated_schema_includes_nested_pricing_types() { let schema = schema(); let definitions = schema["$defs"].as_object().expect("schema has definitions"); diff --git a/litellm-rust/crates/python-bridge/AGENTS.md b/litellm-rust/crates/python-bridge/AGENTS.md index c435ba37e78..d90fe073b20 100644 --- a/litellm-rust/crates/python-bridge/AGENTS.md +++ b/litellm-rust/crates/python-bridge/AGENTS.md @@ -111,8 +111,11 @@ GIL handling to `litellm-host-python`. - Avoid copying large payloads more than needed. The current JSON round-trip is acceptable for the first scaffold, but future performance work should evaluate direct PyO3 conversion before expanding Rust coverage to image-heavy paths. -- Do not expose raw Rust errors that include document contents or upstream - bodies. +- Render a Rust error for Python only in its mapping function, with + `litellm_error::Report`, never `Debug` or a document's contents. An upstream + body reaches Python intact as the `RustUpstreamError` args for provider error + mapping. The 256-character cap applies only to HTTP error diagnostics, not + response bodies. Do not log those args. ## Tests diff --git a/litellm-rust/crates/python-bridge/Cargo.toml b/litellm-rust/crates/python-bridge/Cargo.toml index 8afde8362f6..9d69cd8c14b 100644 --- a/litellm-rust/crates/python-bridge/Cargo.toml +++ b/litellm-rust/crates/python-bridge/Cargo.toml @@ -27,6 +27,7 @@ litellm-host.workspace = true bytes.workspace = true futures-util.workspace = true litellm-cache.workspace = true +litellm-error.workspace = true litellm-cache-memory.workspace = true litellm-cache-redis.workspace = true litellm-cache-response.workspace = true @@ -70,6 +71,7 @@ criterion.workspace = true futures-util.workspace = true rstest.workspace = true sqlx = { workspace = true, features = ["migrate"] } +tempfile.workspace = true tokio-tungstenite.workspace = true wiremock.workspace = true aws-sdk-secretsmanager = "1.117.0" diff --git a/litellm-rust/crates/python-bridge/src/cache/mod.rs b/litellm-rust/crates/python-bridge/src/cache/mod.rs index e190b12e665..87dba3efcb1 100644 --- a/litellm-rust/crates/python-bridge/src/cache/mod.rs +++ b/litellm-rust/crates/python-bridge/src/cache/mod.rs @@ -12,10 +12,93 @@ use pyo3::{ prelude::*, }; -fn cache_error(error: Error) -> PyErr { - match error { - Error::InvalidEntry => PyValueError::new_err(error.to_string()), - Error::UnsupportedOperation => PyNotImplementedError::new_err(error.to_string()), - _ => PyRuntimeError::new_err(error.to_string()), +/// A cache call the bridge rejects itself, before or after the cache ran. +#[derive(Debug, thiserror::Error)] +pub(crate) enum HandleError { + #[error("recreate the v2 cache after fork")] + Forked, + #[error("cache limits must be positive")] + Limits, + #[error("namespace and a positive cache limit are required")] + RedisLimits, + #[error("cache durations must be finite and positive")] + Duration(#[source] Option), + #[error("unsupported v2 cache control: {0}")] + Control(String), + #[error("native inference needs a v2 cache, the catalog keeps Python caches on Python")] + NotNative, + #[error("cache operation without configured cache")] + Unconfigured, + #[error("cache arguments unavailable")] + MissingArguments, + #[error("cache reply without pending operation")] + NothingPending, +} + +impl From for PyErr { + fn from(error: HandleError) -> Self { + let message = litellm_error::Report::new(&error).to_string(); + match error { + HandleError::Limits + | HandleError::RedisLimits + | HandleError::Duration(_) + | HandleError::Control(_) => PyValueError::new_err(message), + HandleError::Forked + | HandleError::NotNative + | HandleError::Unconfigured + | HandleError::MissingArguments + | HandleError::NothingPending => PyRuntimeError::new_err(message), + } + } +} + +fn cache_error(error: Error) -> PyErr { + let message = litellm_error::Report::new(&error).to_string(); + match error { + Error::InvalidEntry(_) => PyValueError::new_err(message), + Error::UnsupportedOperation => PyNotImplementedError::new_err(message), + Error::Unavailable(_) | Error::UnscopedFlush | Error::MissingPrompt => { + PyRuntimeError::new_err(message) + } + } +} + +#[cfg(test)] +mod tests { + use pyo3::{ + exceptions::{PyRuntimeError, PyValueError}, + prelude::*, + }; + use rstest::rstest; + + use super::{Error, cache_error}; + + fn refused() -> std::io::Error { + std::io::Error::other("connection refused") + } + + #[rstest] + #[case::unavailable( + Error::unavailable(refused()), + false, + "cache is unavailable: connection refused" + )] + #[case::invalid_entry( + Error::invalid_entry(refused()), + true, + "invalid cache entry: connection refused" + )] + fn python_sees_the_class_and_the_whole_chain( + #[case] error: Error, + #[case] caller_fault: bool, + #[case] message: &str, + ) { + Python::initialize(); + Python::attach(|py| { + let failure = cache_error(error); + assert_eq!(failure.is_instance_of::(py), caller_fault); + assert_eq!(failure.is_instance_of::(py), !caller_fault); + assert_eq!(failure.value(py).to_string(), message); + }); } } diff --git a/litellm-rust/crates/python-bridge/src/cache/native/v2.rs b/litellm-rust/crates/python-bridge/src/cache/native/v2.rs index eb09b8131c3..c54cb641843 100644 --- a/litellm-rust/crates/python-bridge/src/cache/native/v2.rs +++ b/litellm-rust/crates/python-bridge/src/cache/native/v2.rs @@ -1,4 +1,4 @@ -use crate::cache::cache_error; +use crate::cache::{HandleError, cache_error}; use std::{ sync::Arc, time::{Duration, SystemTime, UNIX_EPOCH}, @@ -14,7 +14,7 @@ use litellm_cache_response::{ CacheEntry, CacheKeyInput, ExactResponseCache, ResponseCache, ResponseCacheCodec, ResponseCacheConfig, ResponseCacheRequest, ResponseCacheService, }; -use pyo3::{exceptions::PyValueError, prelude::*, types::PyDict}; +use pyo3::{prelude::*, types::PyDict}; #[pyclass( frozen, @@ -37,9 +37,7 @@ enum Storage { impl NativeCacheHandle { fn check_process(&self) -> PyResult<()> { if self.pid != std::process::id() { - return Err(pyo3::exceptions::PyRuntimeError::new_err( - "recreate the v2 cache after fork", - )); + return Err(HandleError::Forked.into()); } Ok(()) } @@ -61,7 +59,7 @@ impl NativeCacheHandle { fn memory(ttl: f64, capacity: usize, max_entry_bytes: usize) -> PyResult { let ttl = duration(ttl)?; if capacity == 0 || max_entry_bytes == 0 { - return Err(PyValueError::new_err("cache limits must be positive")); + return Err(HandleError::Limits.into()); } let storage = Arc::new(InMemoryCache::new(Some(capacity), Some(ttl))); let backend = Arc::new(ResponseCache::new(storage.clone()).with_config( @@ -89,9 +87,7 @@ impl NativeCacheHandle { ) -> PyResult { let ttl = duration(ttl)?; if namespace.is_empty() || max_entry_bytes == 0 { - return Err(PyValueError::new_err( - "namespace and a positive cache limit are required", - )); + return Err(HandleError::RedisLimits.into()); } let storage = Arc::new( release_gil(py, || { @@ -252,11 +248,12 @@ impl NativeCacheHandle { } } -fn duration(seconds: f64) -> PyResult { - Duration::try_from_secs_f64(seconds) - .ok() - .filter(|value| !value.is_zero()) - .ok_or_else(|| PyValueError::new_err("cache durations must be finite and positive")) +fn duration(seconds: f64) -> Result { + match Duration::try_from_secs_f64(seconds) { + Ok(duration) if !duration.is_zero() => Ok(duration), + Ok(_) => Err(HandleError::Duration(None)), + Err(error) => Err(HandleError::Duration(Some(error))), + } } pub(in crate::cache) fn native_handle<'py>( @@ -277,11 +274,7 @@ pub(in crate::cache) fn configured( Option>, litellm_cache_response::CacheOptions, )> { - let handle = native_handle(configured)?.ok_or_else(|| { - pyo3::exceptions::PyRuntimeError::new_err( - "native inference needs a v2 cache, the catalog keeps Python caches on Python", - ) - })?; + let handle = native_handle(configured)?.ok_or(HandleError::NotNative)?; let cache = handle.extract::>()?; cache.check_process()?; let controls = kwargs.get_item("cache")?.filter(|value| !value.is_none()); @@ -296,9 +289,7 @@ pub(in crate::cache) fn configured( name.as_str(), "no-cache" | "no-store" | "ttl" | "s-maxage" | "s-max-age" | "use-cache" ) { - return Err(PyValueError::new_err(format!( - "unsupported v2 cache control: {name}" - ))); + return Err(HandleError::Control(name).into()); } } } @@ -316,7 +307,7 @@ pub(in crate::cache) fn configured( .map(|values| values.get_item(name)) .transpose()? .flatten() - .map(|value| duration(value.extract()?)) + .map(|value| Ok(duration(value.extract()?)?)) .transpose() }; Ok(( diff --git a/litellm-rust/crates/python-bridge/src/cache/python/host.rs b/litellm-rust/crates/python-bridge/src/cache/python/host.rs index d8f8ac7c181..82b7d881df6 100644 --- a/litellm-rust/crates/python-bridge/src/cache/python/host.rs +++ b/litellm-rust/crates/python-bridge/src/cache/python/host.rs @@ -9,6 +9,7 @@ use pyo3::{ use serde_json::Value; use super::service::CacheCall; +use crate::cache::HandleError; enum Pending { Lookup(Reply, Error>>), @@ -43,16 +44,12 @@ impl PythonCache { pub fn begin(&mut self, py: Python<'_>, call: CacheCall) -> PyResult>> { let Some(cache) = self.cache.as_ref() else { - return Err(pyo3::exceptions::PyRuntimeError::new_err( - "cache operation without configured cache", - )); + return Err(HandleError::Unconfigured.into()); }; let arguments = self .arguments .as_ref() - .ok_or_else(|| { - pyo3::exceptions::PyRuntimeError::new_err("cache arguments unavailable") - })? + .ok_or(HandleError::MissingArguments)? .bind(py) .copy()?; let (method, result) = match call { @@ -97,33 +94,30 @@ impl PythonCache { py: Python<'_>, result: PyResult>, ) -> PyResult>> { - if let Err(error) = &result - && !error.is_instance_of::(py) - { - self.pending = None; - return Err(result.err().unwrap()); - } + let result = match result { + Err(error) if !error.is_instance_of::(py) => { + self.pending = None; + return Err(error); + } + result => result, + }; match self.pending.take() { Some(Pending::Lookup(reply)) => { - let value = result.map_err(|_| Error::Unavailable).and_then(|value| { + let value = result.map_err(Error::unavailable).and_then(|value| { if value.bind(py).is_none() { Ok(None) } else { from_py(value.bind(py)) .map(Some) - .map_err(|_| Error::InvalidEntry) + .map_err(Error::invalid_entry) } }); reply.send(value); } Some(Pending::Store(reply)) => { - reply.send(result.map(|_| ()).map_err(|_| Error::Unavailable)); - } - None => { - return Err(pyo3::exceptions::PyRuntimeError::new_err( - "cache reply without pending operation", - )); + reply.send(result.map(|_| ()).map_err(Error::unavailable)); } + None => return Err(HandleError::NothingPending.into()), } Ok(None) } diff --git a/litellm-rust/crates/python-bridge/src/cache/python/service.rs b/litellm-rust/crates/python-bridge/src/cache/python/service.rs index f215e5e97f5..38872b85d30 100644 --- a/litellm-rust/crates/python-bridge/src/cache/python/service.rs +++ b/litellm-rust/crates/python-bridge/src/cache/python/service.rs @@ -17,18 +17,21 @@ fn from_python(value: Value) -> Result { let output = match value.get(STREAM_EVENTS_KEY) { Some(events) => { let events: Vec = - serde_json::from_value(events.clone()).map_err(|_| Error::InvalidEntry)?; + serde_json::from_value(events.clone()).map_err(Error::invalid_entry)?; CachedOutput::Stream(events.concat()) } None => CachedOutput::Response(value), }; - serde_json::to_value(ResponseEnvelope::new("messages", output)).map_err(|_| Error::InvalidEntry) + serde_json::to_value(ResponseEnvelope::new("messages", output)).map_err(Error::invalid_entry) } fn to_python(value: Value) -> Result { let envelope: ResponseEnvelope> = - serde_json::from_value(value).map_err(|_| Error::InvalidEntry)?; - match envelope.decode("messages").ok_or(Error::InvalidEntry)? { + serde_json::from_value(value).map_err(Error::invalid_entry)?; + match envelope + .decode("messages") + .ok_or(Error::InvalidEntry(None))? + { CachedOutput::Response(response) => Ok(response), CachedOutput::Stream(text) => Ok(serde_json::json!({ STREAM_EVENTS_KEY: text.split_inclusive("\n\n").collect::>() @@ -56,7 +59,7 @@ pub(in crate::cache) fn service>( namespace: String, ) -> std::sync::Arc where - P::Error: From, + P::Error: From + std::error::Error, { std::sync::Arc::new(PythonCacheService { services, @@ -69,7 +72,7 @@ where impl> ResponseCacheService for PythonCacheService

where - P::Error: From, + P::Error: From + std::error::Error, { fn config(&self) -> &ResponseCacheConfig { &self.config @@ -84,7 +87,7 @@ where self.services .call(|reply| CacheCall::Lookup { reply }) .await - .map_err(|_| Error::Unavailable)?? + .map_err(Error::unavailable)?? .map(from_python) .transpose() }) @@ -101,7 +104,7 @@ where self.services .call(|reply| CacheCall::Store { value, reply }) .await - .map_err(|_| Error::Unavailable)? + .map_err(Error::unavailable)? }) } } diff --git a/litellm-rust/crates/python-bridge/src/cache/selection.rs b/litellm-rust/crates/python-bridge/src/cache/selection.rs index cd19533fc73..00fc7cd822f 100644 --- a/litellm-rust/crates/python-bridge/src/cache/selection.rs +++ b/litellm-rust/crates/python-bridge/src/cache/selection.rs @@ -39,7 +39,7 @@ impl Selection { services: HostServices

, ) -> (Option, CacheOptions) where - P::Error: From, + P::Error: From + std::error::Error, { let service = match self.backend { Backend::Disabled => None, diff --git a/litellm-rust/crates/python-bridge/src/callable.rs b/litellm-rust/crates/python-bridge/src/callable.rs index d0ed76a3e8b..605b649e1f3 100644 --- a/litellm-rust/crates/python-bridge/src/callable.rs +++ b/litellm-rust/crates/python-bridge/src/callable.rs @@ -48,14 +48,8 @@ mod tests { Err(PyErr::from_value(error.clone())) } - #[rstest::rstest] - fn only_ordinary_exceptions_are_reported_under_the_template() { - Python::initialize(); - Python::attach(|py| { - let locals = PyDict::new(py); - py.run( - pyo3::ffi::c_str!( - r#" + const FAILURES: &std::ffi::CStr = pyo3::ffi::c_str!( + r#" class CallerError(Exception): def __format__(self, specification): return 'unavailable' @@ -63,12 +57,19 @@ ordinary = CallerError('must use __format__') type_error = TypeError('signature') abort = KeyboardInterrupt('cancelled') "# - ), - Some(&locals), - Some(&locals), - ) - .unwrap(); + ); + fn failures(py: Python<'_>) -> Bound<'_, PyDict> { + let locals = PyDict::new(py); + py.run(FAILURES, Some(&locals), Some(&locals)).unwrap(); + locals + } + + #[test] + fn ordinary_exceptions_are_reported_under_the_template() { + Python::initialize(); + Python::attach(|py| { + let locals = failures(py); let original = raised(&locals, "ordinary"); let wrapped = wrap_failure(py, TEMPLATE, failure(&original)).unwrap_err(); assert!(wrapped.is_instance_of::(py)); @@ -78,12 +79,19 @@ abort = KeyboardInterrupt('cancelled') wrapped.value(py).str().unwrap().to_str().unwrap(), "Failed to reach the caller: unavailable" ); + }); + } - for name in ["type_error", "abort"] { - let original = raised(&locals, name); - let error = wrap_failure(py, TEMPLATE, failure(&original)).unwrap_err(); - assert!(error.value(py).is(&original)); - } + #[rstest::rstest] + #[case::type_error("type_error")] + #[case::keyboard_interrupt("abort")] + fn other_exceptions_pass_through_unwrapped(#[case] name: &str) { + Python::initialize(); + Python::attach(|py| { + let locals = failures(py); + let original = raised(&locals, name); + let error = wrap_failure(py, TEMPLATE, failure(&original)).unwrap_err(); + assert!(error.value(py).is(&original)); }); } diff --git a/litellm-rust/crates/python-bridge/src/coercion.rs b/litellm-rust/crates/python-bridge/src/coercion.rs index 77c8cabc22b..8cdf1e6c5bc 100644 --- a/litellm-rust/crates/python-bridge/src/coercion.rs +++ b/litellm-rust/crates/python-bridge/src/coercion.rs @@ -1,4 +1,5 @@ use litellm_core_utils::serde_compat::parse_str_bool; +use litellm_error::Report; use pyo3::{ exceptions::{PyAttributeError, PyRuntimeError, PyValueError}, prelude::*, @@ -9,15 +10,20 @@ use pyo3::{ pub(crate) enum ProjectionError { Python(PyErr), InvalidConfiguration(ProjectionDetail), - UnsupportedLiveObject(String), + UnsupportedLiveObject(ProjectionDetail), InternalSchemaFailure(ProjectionDetail), } #[derive(Debug, thiserror::Error)] pub(crate) enum ProjectionDetail { - #[error("{0}")] - Message(String), - #[error("{field}: {source}")] + #[error("{group}.{name}: expected {expected}, got {actual}")] + Expected { + group: &'static str, + name: &'static str, + expected: &'static str, + actual: String, + }, + #[error("{field}")] InvalidField { field: &'static str, #[source] @@ -30,12 +36,6 @@ pub(crate) enum ProjectionDetail { }, } -impl From for ProjectionDetail { - fn from(message: String) -> Self { - Self::Message(message) - } -} - impl From for ProjectionError { fn from(error: PyErr) -> Self { Self::Python(error) @@ -46,12 +46,12 @@ impl From for PyErr { fn from(error: ProjectionError) -> Self { match error { ProjectionError::Python(error) => error, - ProjectionError::InvalidConfiguration(detail) => { - PyValueError::new_err(detail.to_string()) + ProjectionError::InvalidConfiguration(detail) + | ProjectionError::UnsupportedLiveObject(detail) => { + PyValueError::new_err(Report::new(&detail).to_string()) } - ProjectionError::UnsupportedLiveObject(message) => PyValueError::new_err(message), ProjectionError::InternalSchemaFailure(detail) => { - PyRuntimeError::new_err(detail.to_string()) + PyRuntimeError::new_err(Report::new(&detail).to_string()) } } } @@ -124,26 +124,26 @@ impl<'py> Field<'py> { && getter.is(object.getattr("__getattribute__")?)) } - pub(crate) fn path(&self) -> String { - format!("{}.{}", self.group, self.name) - } - /// A member of this field's collection, reported under the same path. pub(crate) fn member(&self, value: Bound<'py, PyAny>) -> Self { Self::new(self.group, self.name, value) } - pub(crate) fn expected(&self, expected: &str) -> Result { - Ok(format!( - "{}: expected {expected}, got {}", - self.path(), - self.value.get_type().name()? - )) + pub(crate) fn expected( + &self, + expected: &'static str, + ) -> Result { + Ok(ProjectionDetail::Expected { + group: self.group, + name: self.name, + expected, + actual: self.value.get_type().name()?.to_string(), + }) } - pub(crate) fn invalid(&self, expected: &str) -> ProjectionError { + pub(crate) fn invalid(&self, expected: &'static str) -> ProjectionError { match self.expected(expected) { - Ok(message) => ProjectionError::InvalidConfiguration(message.into()), + Ok(detail) => ProjectionError::InvalidConfiguration(detail), Err(error) => error, } } @@ -163,24 +163,23 @@ impl<'py> Field<'py> { pub(crate) fn schema_bool(&self) -> Result { if !self.value.is_instance_of::() { return Err(ProjectionError::InternalSchemaFailure( - self.expected("a Boolean")?.into(), + self.expected("a Boolean")?, )); } Ok(self.exact_true()) } pub(crate) fn strict_string(&self) -> Result { - let value = self - .value - .cast::() - .map_err(|_| self.invalid("a string"))?; + let Ok(value) = self.value.cast::() else { + return Err(self.invalid("a string")); + }; Ok(value.to_str()?.to_owned()) } pub(crate) fn schema_string(&self) -> Result { if !self.value.is_instance_of::() { return Err(ProjectionError::InternalSchemaFailure( - self.expected("a string")?.into(), + self.expected("a string")?, )); } self.strict_string() @@ -474,12 +473,7 @@ text = Text(' False ') }); } - #[test] - fn missing_snapshot_fields_and_descriptor_attribute_errors_are_distinct() { - with_python(|py| { - let locals = PyDict::new(py); - py.run( - c" + const RAISING_ATTRIBUTES: &std::ffi::CStr = c" failure = AttributeError('descriptor failed') class Snapshot: @property @@ -491,46 +485,56 @@ class Intercepted: def __getattribute__(self, name): raise failure dynamic = Dynamic() intercepted = Intercepted() -", - Some(&locals), - Some(&locals), - ) - .unwrap(); - let snapshot = locals.get_item("snapshot").unwrap().unwrap(); - let descriptor = PyErr::from(Field::read(&snapshot, "test", "flag").err().unwrap()); +"; + + #[rstest] + #[case::descriptor("snapshot")] + #[case::dynamic("dynamic")] + #[case::intercepted("intercepted")] + fn attribute_errors_raised_by_a_snapshot_surface_as_raised(#[case] name: &str) { + with_python(|py| { + let locals = PyDict::new(py); + py.run(RAISING_ATTRIBUTES, Some(&locals), Some(&locals)) + .unwrap(); + let value = locals.get_item(name).unwrap().unwrap(); + let error = PyErr::from(Field::read(&value, "test", "flag").err().unwrap()); assert!( - descriptor + error .value(py) .is(locals.get_item("failure").unwrap().unwrap()) ); - for name in ["dynamic", "intercepted"] { - let value = locals.get_item(name).unwrap().unwrap(); - let error = PyErr::from(Field::read(&value, "test", "flag").err().unwrap()); - assert!( - error - .value(py) - .is(locals.get_item("failure").unwrap().unwrap()) - ); - } + }); + } + + #[test] + fn missing_snapshot_fields_are_runtime_errors_naming_the_field() { + with_python(|py| { + let locals = PyDict::new(py); + py.run(RAISING_ATTRIBUTES, Some(&locals), Some(&locals)) + .unwrap(); + let snapshot = locals.get_item("snapshot").unwrap().unwrap(); let missing = PyErr::from(Field::read(&snapshot, "test", "missing").err().unwrap()); assert!(missing.is_instance_of::(py)); assert!(missing.to_string().contains("test.missing")); }); } - #[test] - fn configuration_errors_name_fields_without_exposing_values() { + #[rstest] + #[case::mapping("{'secret': 'do-not-print'}")] + #[case::nested("['host.test', {'secret': 'do-not-print'}]")] + fn configuration_errors_name_fields_without_exposing_values(#[case] source: &str) { + with_python(|py| { + let field = Field::new("test", "setting", evaluate(py, source)); + let error = PyErr::from(field.falsy_optional_string().err().unwrap()); + assert!(error.is_instance_of::(py)); + assert!(error.to_string().contains("test.setting")); + assert!(!error.to_string().contains("do-not-print")); + }); + } + + #[test] + fn invalid_collections_and_flags_are_configuration_errors() { with_python(|py| { - for source in [ - "{'secret': 'do-not-print'}", - "['host.test', {'secret': 'do-not-print'}]", - ] { - let field = Field::new("test", "setting", evaluate(py, source)); - let error = PyErr::from(field.falsy_optional_string().err().unwrap()); - assert!(error.is_instance_of::(py)); - assert!(error.to_string().contains("test.setting")); - assert!(!error.to_string().contains("do-not-print")); - } let hosts = Field::new( "url_policy", "user_url_allowed_hosts", diff --git a/litellm-rust/crates/python-bridge/src/credentials.rs b/litellm-rust/crates/python-bridge/src/credentials.rs index 04d8e94c8fe..a4bb064aae0 100644 --- a/litellm-rust/crates/python-bridge/src/credentials.rs +++ b/litellm-rust/crates/python-bridge/src/credentials.rs @@ -10,10 +10,19 @@ use pyo3::{ types::{PyDict, PyString}, }; -const NOT_CALLABLE: &str = "Azure AD token provider must be callable"; const NOT_A_STRING: &str = "Azure AD token must be a string, got {}"; const FAILED: &str = "Failed to get Azure AD token: {}"; +#[derive(Debug, thiserror::Error)] +#[error("Azure AD token provider must be callable")] +struct NotCallable; + +impl From for PyErr { + fn from(error: NotCallable) -> Self { + PyTypeError::new_err(litellm_error::Report::new(&error).to_string()) + } +} + /// The `azure_ad_token_provider` keyword argument, kept alive for the rest of the call. pub(crate) struct CallerTokenProvider { provider: Py, @@ -36,7 +45,7 @@ impl CallerTokenProvider { pub(crate) fn acquire(&self, py: Python<'_>) -> PyResult { let provider = self.provider.bind(py); if !provider.is_callable() { - return Err(PyTypeError::new_err(NOT_CALLABLE)); + return Err(NotCallable.into()); } let token = wrap_failure( py, diff --git a/litellm-rust/crates/python-bridge/src/diagnostics.rs b/litellm-rust/crates/python-bridge/src/diagnostics.rs index 687a090e768..5368da4f930 100644 --- a/litellm-rust/crates/python-bridge/src/diagnostics.rs +++ b/litellm-rust/crates/python-bridge/src/diagnostics.rs @@ -1,5 +1,5 @@ use litellm_host_python::{release_count, runtime_started}; -use pyo3::{exceptions::PyRuntimeError, prelude::*, types::PyDict}; +use pyo3::{prelude::*, types::PyDict}; #[pyfunction] pub(crate) fn gil_stats(py: Python<'_>) -> PyResult> { @@ -18,8 +18,7 @@ pub(crate) fn process_state_started() -> bool { /// so the runtime can never start. Raises if it already has. Forked workers are unaffected. #[pyfunction] pub(crate) fn reserve_process_for_forking() -> PyResult<()> { - litellm_host_python::reserve_process_for_forking() - .map_err(|_| PyRuntimeError::new_err("the native runtime already started in this process")) + Ok(litellm_host_python::reserve_process_for_forking()?) } #[cfg(feature = "panic-test")] diff --git a/litellm-rust/crates/python-bridge/src/errors.rs b/litellm-rust/crates/python-bridge/src/errors.rs index 4dab0297e73..b42c08b7e78 100644 --- a/litellm-rust/crates/python-bridge/src/errors.rs +++ b/litellm-rust/crates/python-bridge/src/errors.rs @@ -1,9 +1,12 @@ -use litellm_http::transport::Error as TransportError; +use std::error::Error as StdError; + +use litellm_error::Report; use litellm_inference::Error; use pyo3::{ exceptions::{PyRuntimeError, PyValueError}, prelude::*, }; +use reqwest::header::HeaderMap; pyo3::create_exception!( _native, @@ -16,20 +19,34 @@ pyo3::create_exception!( _native, RustUpstreamError, pyo3::exceptions::PyException, - "The provider call was already issued and failed. Args are (status, message); status is 0 when there was no HTTP response." + "The provider call was already issued and the provider answered with a failure. Args are (status, body); the headers attribute holds the provider's (name, value) response headers." ); -pub(crate) fn route_error_to_pyerr(error: Error) -> PyErr { - match error { - Error::Transport(TransportError::Http { status, body }) => { - RustUpstreamError::new_err((status, body)) - } - other => by_fault(other.is_request(), other.to_string()), - } +const MESSAGES_REQUEST_ERROR: &str = "messages_request_error"; + +pub(crate) fn upstream_error( + py: Python<'_>, + status: u16, + body: &str, + headers: &HeaderMap, +) -> PyResult { + let error = RustUpstreamError::new_err((status, body.to_owned())); + let pairs: Vec<(&str, String)> = headers + .iter() + .map(|(name, value)| { + ( + name.as_str(), + String::from_utf8_lossy(value.as_bytes()).into_owned(), + ) + }) + .collect(); + error.value(py).setattr("headers", pairs)?; + Ok(error) } /// A request the caller got wrong is a `ValueError`; anything else is a `RuntimeError`. -pub(crate) fn by_fault(is_request: bool, message: String) -> PyErr { +pub(crate) fn by_fault(is_request: bool, error: &(dyn StdError + 'static)) -> PyErr { + let message = Report::new(error).to_string(); if is_request { PyValueError::new_err(message) } else { @@ -37,17 +54,90 @@ pub(crate) fn by_fault(is_request: bool, message: String) -> PyErr { } } +/// How a route flags a rejected request for its Python route module, which raises the public +/// exception for it instead of mapping the native one. +#[derive(Clone, Copy)] +pub(crate) enum RequestMarker { + Unmarked, + Messages, +} + +/// Maps a route failure once. A core decline and a Python exception raised inside the call are +/// returned as they are, everything else is mapped and handed to `public`, the route's public +/// exception mapping. +pub(crate) fn route_failure( + py: Python<'_>, + error: Error, + marker: RequestMarker, + public: impl FnOnce(PyErr) -> PyResult, +) -> PyResult { + if let Some(decline) = error.declined() { + return Ok(RustBridgeDeclined::new_err(decline.reason)); + } + if let Some(raised) = crate::secrets::python_error(py, &error) { + return Ok(raised); + } + if let Some((status, body)) = error.upstream_response() { + return public(upstream_error(py, status, body, &HeaderMap::new())?); + } + let native = match (marker, error.rejected_request()) { + (RequestMarker::Messages, Some(rejection)) => { + let native = PyValueError::new_err(Report::new(rejection).to_string()); + native.value(py).setattr(MESSAGES_REQUEST_ERROR, true)?; + native + } + (RequestMarker::Messages, None) | (RequestMarker::Unmarked, _) => { + by_fault(error.is_request(), &error) + } + }; + public(native) +} + +pub(crate) fn route_error_to_pyerr(error: Error) -> PyErr { + Python::attach(|py| { + route_failure(py, error, RequestMarker::Unmarked, Ok).unwrap_or_else(std::convert::identity) + }) +} + #[cfg(test)] mod tests { + use litellm_core_utils::decline::Decline; + use reqwest::header::{HeaderValue, RETRY_AFTER}; + use super::*; + fn upstream_payload(py: Python<'_>, failure: &PyErr) -> ((u16, String), Vec<(String, String)>) { + let value = failure.value(py); + ( + value.getattr("args").unwrap().extract().unwrap(), + value.getattr("headers").unwrap().extract().unwrap(), + ) + } + #[rstest::rstest] - #[case::unsupported(Error::Unsupported("test capability"), true)] #[case::invalid_provider(Error::InvalidProvider("unknown".into()), true)] - #[case::invalid_request(Error::InvalidRequest("empty messages".into()), true)] - #[case::connection(TransportError::Connect("unreachable".into()).into(), false)] - #[case::network(TransportError::Network("timed out".into()).into(), false)] - #[case::invalid_response(Error::InvalidResponse("missing usage".into()), false)] + #[case::invalid_request( + Error::invalid_request(litellm_llms::ErrorDetail::Expected { + subject: "messages", + expected: "non-empty", + }), + true + )] + #[case::lost_connection( + litellm_http::Error::from(tokio_tungstenite::tungstenite::Error::ConnectionClosed).into(), + false + )] + #[case::invalid_response( + Error::invalid_response(litellm_llms::ErrorDetail::MissingField { + subject: "response", + field: "usage", + }), + false + )] + #[case::post_call_decline( + Error::post_call(Error::Declined(Decline::new("result rejected"))), + false + )] fn route_failures_are_terminal(#[case] error: Error, #[case] is_request: bool) { Python::initialize(); Python::attach(|py| { @@ -59,29 +149,97 @@ mod tests { } #[rstest::rstest] - fn transport_status_survives_python_mapping() { + #[case::unmarked(RequestMarker::Unmarked)] + #[case::messages(RequestMarker::Messages)] + fn a_core_decline_hands_the_call_back_to_python_before_the_public_mapping( + #[case] marker: RequestMarker, + ) { Python::initialize(); Python::attach(|py| { - let upstream = route_error_to_pyerr( - TransportError::Http { - status: 429, - body: "slow down".into(), - } - .into(), - ); - assert!(upstream.is_instance_of::(py)); + let error = Error::from(litellm_llms::Error::Declined(Decline::new( + "unrecognized request parameter", + ))); + let declined = route_failure(py, error, marker, |_| { + panic!("a decline must not reach the public mapping") + }) + .unwrap(); + assert!(declined.is_instance_of::(py)); assert_eq!( - upstream + declined .value(py) .getattr("args") .unwrap() - .extract::<(u16, String)>() + .extract::<(String,)>() .unwrap(), - (429, "slow down".into()) + ("unrecognized request parameter".into(),) ); }); } + #[rstest::rstest] + #[case::unmarked(RequestMarker::Unmarked)] + #[case::messages(RequestMarker::Messages)] + fn the_provider_answer_passes_through_with_a_headers_attribute(#[case] marker: RequestMarker) { + Python::initialize(); + Python::attach(|py| { + let error = litellm_http::Error::upstream(429, "slow down".into()).into(); + let upstream = route_failure(py, error, marker, Ok).unwrap(); + assert!(upstream.is_instance_of::(py)); + assert_eq!( + upstream_payload(py, &upstream), + ((429, "slow down".into()), Vec::new()) + ); + assert!( + upstream + .value(py) + .getattr_opt(MESSAGES_REQUEST_ERROR) + .unwrap() + .is_none() + ); + }); + } + + #[test] + fn upstream_error_keeps_the_provider_headers() { + Python::initialize(); + Python::attach(|py| { + let headers = HeaderMap::from_iter([(RETRY_AFTER, HeaderValue::from_static("17"))]); + let upstream = upstream_error(py, 503, "busy", &headers).unwrap(); + assert_eq!( + upstream_payload(py, &upstream), + ( + (503, "busy".into()), + vec![("retry-after".into(), "17".into())] + ) + ); + }); + } + + #[rstest::rstest] + #[case::ascii("busy ".repeat(80))] + #[case::unicode("é".repeat(300))] + fn long_provider_bodies_reach_python_intact( + #[case] message: String, + #[values(RequestMarker::Unmarked, RequestMarker::Messages)] marker: RequestMarker, + ) { + let envelope = serde_json::json!({ + "type": "error", + "error": {"type": "overloaded_error", "message": message}, + "request_id": "provider-request", + }); + let body = envelope.to_string(); + let error = litellm_http::Error::upstream(529, body.clone()).into(); + Python::initialize(); + Python::attach(|py| { + let upstream = route_failure(py, error, marker, Ok).unwrap(); + assert!(upstream.is_instance_of::(py)); + let ((status, returned_body), headers) = upstream_payload(py, &upstream); + assert_eq!(status, 529); + assert_eq!(returned_body, body); + assert!(headers.is_empty()); + }); + } + #[test] fn missing_api_key_stays_a_runtime_error_while_other_auth_failures_are_value_errors() { Python::initialize(); @@ -95,4 +253,83 @@ mod tests { assert!(invalid.is_instance_of::(py)); }); } + + #[test] + fn a_wrapped_failure_renders_every_layer() { + Python::initialize(); + Python::attach(|py| { + let error = Error::post_call( + litellm_http::Error::upstream(500, "hook backend down".into()).into(), + ); + let report = Report::new(&error).to_string(); + let failure = route_error_to_pyerr(error); + assert_eq!(failure.value(py).to_string(), report); + assert!(report.contains("hook backend down"), "{report}"); + }); + } + + #[rstest::rstest] + #[case::rejected_request( + Error::invalid_request(litellm_llms::ErrorDetail::UnsupportedParameter { + model: "claude".into(), + param: "top_k".into(), + value: "5".into(), + hint: String::new(), + }), + Some("claude does not support top_k=5. To drop unsupported params, set `litellm.drop_params = True`.") + )] + #[case::missing_field( + litellm_llms::Error::MissingField("max_tokens").into(), + Some("missing required field: max_tokens") + )] + #[case::unresolvable_provider(Error::InvalidProvider("openai".into()), None)] + #[case::invalid_response( + Error::invalid_response(litellm_llms::ErrorDetail::MissingField { + subject: "response", + field: "usage", + }), + None + )] + fn only_messages_request_rejections_carry_the_marker_and_python_text( + #[case] error: Error, + #[case] rejection: Option<&str>, + ) { + Python::initialize(); + Python::attach(|py| { + let unmarked = route_failure(py, error.clone(), RequestMarker::Unmarked, Ok).unwrap(); + assert!( + unmarked + .value(py) + .getattr_opt(MESSAGES_REQUEST_ERROR) + .unwrap() + .is_none() + ); + let native = route_failure(py, error, RequestMarker::Messages, Ok).unwrap(); + let marked = native + .value(py) + .getattr_opt(MESSAGES_REQUEST_ERROR) + .unwrap() + .map(|value| value.extract::().unwrap()); + assert_eq!(marked.unwrap_or(false), rejection.is_some()); + if let Some(rejection) = rejection { + assert!(native.is_instance_of::(py)); + assert_eq!(native.value(py).to_string(), rejection); + } + }); + } + + #[test] + fn a_python_secret_manager_exception_skips_the_public_mapping() { + Python::initialize(); + Python::attach(|py| { + let raised = pyo3::exceptions::PyKeyError::new_err("vault down"); + let identity = raised.value(py).clone().unbind(); + let error = Error::from(crate::secrets::read_error(py, raised)); + let surfaced = route_failure(py, error, RequestMarker::Unmarked, |_| { + panic!("the raised exception must not be remapped") + }) + .unwrap(); + assert!(surfaced.value(py).is(identity.bind(py))); + }); + } } diff --git a/litellm-rust/crates/python-bridge/src/http.rs b/litellm-rust/crates/python-bridge/src/http.rs index 57bf8aafc4e..b4e20a8f750 100644 --- a/litellm-rust/crates/python-bridge/src/http.rs +++ b/litellm-rust/crates/python-bridge/src/http.rs @@ -132,26 +132,14 @@ pub(crate) fn host_client(py: Python<'_>, variant: ClientVariant) -> PyResult PyErr { - match error { - litellm_http::Error::Read { - tls_source: TlsSource::ClientIdentity, - .. - } - | litellm_http::Error::InvalidPem { - tls_source: TlsSource::ClientIdentity, - .. - } => PyValueError::new_err( + match error.tls_source() { + Some(TlsSource::ClientIdentity) => PyValueError::new_err( "http_settings.ssl_certificate: expected a readable PEM certificate and private key", ), - litellm_http::Error::Read { - tls_source: TlsSource::CaBundle, - .. + Some(TlsSource::CaBundle) => { + PyValueError::new_err("http_settings.ssl_verify: expected a readable PEM CA bundle") } - | litellm_http::Error::InvalidPem { - tls_source: TlsSource::CaBundle, - .. - } => PyValueError::new_err("http_settings.ssl_verify: expected a readable PEM CA bundle"), - _ => PyValueError::new_err("http_settings: native HTTP client configuration is invalid"), + None => PyValueError::new_err(litellm_error::Report::new(&error).to_string()), } } @@ -274,21 +262,28 @@ settings = types.SimpleNamespace(**defaults) fn client_error_uses_tls_source_when_paths_match() { Python::initialize(); Python::attach(|py| { - let path = PathBuf::from("/shared.pem"); - let ca_error = client_error(litellm_http::Error::InvalidPem { - path: path.clone(), - message: "invalid".into(), - tls_source: TlsSource::CaBundle, - }); + let file = tempfile::NamedTempFile::new().unwrap(); + std::fs::write(file.path(), b"not a certificate").unwrap(); + let path = file.path().to_path_buf(); + let defaults = Resolution::from(&HttpSettings::default()).config; + let build = |config: HttpClientConfig| { + HttpClientPool::new(Arc::new(PublicDnsResolver)) + .client(&config, ClientVariant::Provider) + .map(drop) + .unwrap_err() + }; + let ca_error = client_error(build(HttpClientConfig { + verify: Verify::CaBundle(path.clone()), + ..defaults.clone() + })); assert_eq!( ca_error.to_string(), "ValueError: http_settings.ssl_verify: expected a readable PEM CA bundle" ); - let client_error = client_error(litellm_http::Error::InvalidPem { - path, - message: "invalid".into(), - tls_source: TlsSource::ClientIdentity, - }); + let client_error = client_error(build(HttpClientConfig { + client_certificate: Some(litellm_http::ClientIdentity::Pem(path)), + ..defaults + })); assert!(client_error.is_instance_of::(py)); assert_eq!( client_error.to_string(), @@ -297,6 +292,34 @@ settings = types.SimpleNamespace(**defaults) }); } + #[test] + fn client_error_without_a_tls_source_reports_the_build_failure() { + Python::initialize(); + Python::attach(|py| { + let error = HttpClientPool::new(Arc::new(PublicDnsResolver)) + .client( + &HttpClientConfig { + user_agent: Some("bad\nagent".into()), + ..Resolution::from(&HttpSettings::default()).config + }, + ClientVariant::Provider, + ) + .map(drop) + .unwrap_err(); + assert_eq!(error.tls_source(), None); + let report = litellm_error::Report::new(&error).to_string(); + + let failure = client_error(error); + + assert!(failure.is_instance_of::(py)); + assert_eq!(failure.value(py).str().unwrap().to_string(), report); + assert!( + report.contains("could not build the HTTP client: "), + "{report}" + ); + }); + } + #[test] fn python_settings_flow_into_the_configured_layer() { Python::initialize(); diff --git a/litellm-rust/crates/python-bridge/src/logger/mod.rs b/litellm-rust/crates/python-bridge/src/logger/mod.rs index bf5c735360b..8f40d94f458 100644 --- a/litellm-rust/crates/python-bridge/src/logger/mod.rs +++ b/litellm-rust/crates/python-bridge/src/logger/mod.rs @@ -81,8 +81,12 @@ impl NativeDiagnosticProcessor { } } -fn processing_error(_: fancy_regex::Error) -> PyErr { - PyRuntimeError::new_err("diagnostic processing failed") +#[derive(Debug, thiserror::Error)] +#[error("diagnostic processing failed")] +struct ProcessingError(#[source] fancy_regex::Error); + +fn processing_error(error: fancy_regex::Error) -> PyErr { + PyRuntimeError::new_err(litellm_error::Report::new(&ProcessingError(error)).to_string()) } struct PythonSink { diff --git a/litellm-rust/crates/python-bridge/src/logger/tests.rs b/litellm-rust/crates/python-bridge/src/logger/tests.rs index 1fca3be720e..9a07428808a 100644 --- a/litellm-rust/crates/python-bridge/src/logger/tests.rs +++ b/litellm-rust/crates/python-bridge/src/logger/tests.rs @@ -187,6 +187,7 @@ fn native_events_reach_python_with_levels_context_reentry_and_http_deduplication locals .set_item("http_warning", wrap_pyfunction!(http_warning, py).unwrap()) .unwrap(); + locals.set_item("native", crate::native_module(py)).unwrap(); let importable = py .eval( c"__import__('importlib.util', fromlist=['util']).find_spec('dotenv') is not None", @@ -205,6 +206,7 @@ import asyncio import logging import sys sys.path.insert(0, repo_root) +sys.modules['litellm.rust_bridge._native'] = native import litellm from litellm._logging import verbose_logger, session_id_var, trace_id_var diff --git a/litellm-rust/crates/python-bridge/src/marshal.rs b/litellm-rust/crates/python-bridge/src/marshal.rs index 038fa8c9630..dec8ff0b0ce 100644 --- a/litellm-rust/crates/python-bridge/src/marshal.rs +++ b/litellm-rust/crates/python-bridge/src/marshal.rs @@ -21,10 +21,27 @@ pub(crate) struct RouteOptions { pub(crate) timeout: Option, } -fn required_object(name: &'static str, value: Value) -> PyResult> { +/// A caller argument the bridge cannot use, raised as a `ValueError`. +#[derive(Debug, thiserror::Error)] +pub(crate) enum ArgumentError { + #[error("{0} is required")] + Required(&'static str), + #[error("{0} must be a dict")] + NotADict(&'static str), + #[error("header values must be strings")] + HeaderValue, +} + +impl From for PyErr { + fn from(error: ArgumentError) -> Self { + PyValueError::new_err(litellm_error::Report::new(&error).to_string()) + } +} + +fn required_object(name: &'static str, value: Value) -> Result, ArgumentError> { match value { Value::Object(values) => Ok(values), - _ => Err(PyValueError::new_err(format!("{name} must be a dict"))), + _ => Err(ArgumentError::NotADict(name)), } } @@ -35,7 +52,7 @@ fn optional_object( if value.is_none() { return Ok(None); } - required_object(name, from_py_argument(value)?).map(Some) + Ok(Some(required_object(name, from_py_argument(value)?)?)) } pub(crate) fn optional_timeout(timeout_seconds: Option) -> Option { @@ -57,11 +74,11 @@ pub(crate) fn python_timeout_seconds(py: Python<'_>, timeout: Py) -> PyRe pub(crate) fn required_field<'py>( fields: &Bound<'py, PyDict>, - name: &str, + name: &'static str, ) -> PyResult> { - fields + Ok(fields .get_item(name)? - .ok_or_else(|| PyValueError::new_err(format!("{name} is required"))) + .ok_or(ArgumentError::Required(name))?) } pub(crate) fn optional_field( @@ -171,21 +188,18 @@ pub(crate) fn request_input_sources<'a>( .collect()) } -pub(crate) fn marshal_headers(headers: Option) -> PyResult> { - let value = match headers { - Some(headers) => headers, - None => Value::Object(Map::new()), - }; - let Value::Object(headers) = value else { - return Err(PyValueError::new_err("headers must be a dict")); +pub(crate) fn marshal_headers( + headers: Option, +) -> Result, ArgumentError> { + let headers = match headers { + Some(headers) => required_object("headers", headers)?, + None => Map::new(), }; headers .into_iter() - .map(|(name, value)| { - value - .as_str() - .map(|value| (name, value.to_string())) - .ok_or_else(|| PyValueError::new_err("header values must be strings")) + .map(|(name, value)| match value { + Value::String(value) => Ok((name, value)), + _ => Err(ArgumentError::HeaderValue), }) .collect() } @@ -395,48 +409,52 @@ module.__getattr__ = fail float: Option, } - #[test] - fn numeric_adapters_agree_across_json_and_python_boundaries() { + #[rstest::rstest] + #[case::empty(json!({}))] + #[case::explicit_nulls(json!({"integers": null, "float": null}))] + #[case::lax_values(json!({ + "integers": [i64::MIN, i64::MAX, "9007199254740993.0", " +1_000.00 ", true, 3.0], + "float": " 1.25 ", + }))] + #[case::integer_overflow(json!({"integers": [u64::MAX]}))] + #[case::imprecise_integer_string(json!({"integers": ["1.0000000000000001"]}))] + #[case::fractional_integer(json!({"integers": [2.5]}))] + #[case::nan_string(json!({"float": "NaN"}))] + #[case::infinity_string(json!({"float": "inf"}))] + #[case::overflowing_float_string(json!({"float": "1e999"}))] + #[case::boolean_float(json!({"float": true}))] + #[case::large_integer_float(json!({"float": u64::MAX}))] + fn numeric_adapters_agree_across_json_and_python_boundaries(#[case] input: Value) { Python::initialize(); Python::attach(|py| { - for input in [ - json!({}), - json!({"integers": null, "float": null}), - json!({"integers": [i64::MIN, i64::MAX, "9007199254740993.0", " +1_000.00 ", true, 3.0], "float": " 1.25 "}), - json!({"integers": [u64::MAX]}), - json!({"integers": ["1.0000000000000001"]}), - json!({"integers": [2.5]}), - json!({"float": "NaN"}), - json!({"float": "inf"}), - json!({"float": "1e999"}), - json!({"float": true}), - json!({"float": u64::MAX}), - ] { - let expected = serde_json::from_value::(input.clone()); - let python = litellm_host_python::to_py(py, &input).unwrap(); - let actual = from_py::(python.bind(py)); - match (expected, actual) { - (Ok(expected), Ok(actual)) => { - assert_eq!(actual, expected); - let serialized = litellm_host_python::to_py(py, &actual).unwrap(); - assert_eq!( - from_py::(serialized.bind(py)).unwrap(), - serde_json::to_value(expected).unwrap() - ); - } - (Err(_), Err(_)) => {} - mismatch => panic!("boundary mismatch for {input}: {mismatch:?}"), + let expected = serde_json::from_value::(input.clone()); + let python = litellm_host_python::to_py(py, &input).unwrap(); + let actual = from_py::(python.bind(py)); + match (expected, actual) { + (Ok(expected), Ok(actual)) => { + assert_eq!(actual, expected); + let serialized = litellm_host_python::to_py(py, &actual).unwrap(); + assert_eq!( + from_py::(serialized.bind(py)).unwrap(), + serde_json::to_value(expected).unwrap() + ); } + (Err(_), Err(_)) => {} + mismatch => panic!("boundary mismatch for {input}: {mismatch:?}"), } - for source in [ - c"{'float': float('nan')}", - c"{'float': float('inf')}", - c"{'integers': [float('inf')]}", - c"{'integers': [2 ** 100]}", - ] { - let value = py.eval(source, None, None).unwrap(); - assert!(from_py::(&value).is_err()); - } + }); + } + + #[rstest::rstest] + #[case::nan(c"{'float': float('nan')}")] + #[case::infinity(c"{'float': float('inf')}")] + #[case::infinite_integer(c"{'integers': [float('inf')]}")] + #[case::integer_overflow(c"{'integers': [2 ** 100]}")] + fn non_finite_and_overflowing_python_numbers_are_rejected(#[case] source: &std::ffi::CStr) { + Python::initialize(); + Python::attach(|py| { + let value = py.eval(source, None, None).unwrap(); + assert!(from_py::(&value).is_err()); }); } diff --git a/litellm-rust/crates/python-bridge/src/routes/audio_transcription.rs b/litellm-rust/crates/python-bridge/src/routes/audio_transcription.rs index e62673d4d4f..21a57123921 100644 --- a/litellm-rust/crates/python-bridge/src/routes/audio_transcription.rs +++ b/litellm-rust/crates/python-bridge/src/routes/audio_transcription.rs @@ -13,7 +13,7 @@ use crate::{ }; async fn execute( - http: Result, + http: litellm_http::Client, secrets: std::sync::Arc, audio: Value, optional_params: Map, @@ -27,7 +27,7 @@ async fn execute( extra_headers, timeout, } = options; - AudioTranscriptionRoute::new(http?, crate::http::resources().auth.clone(), secrets) + AudioTranscriptionRoute::new(http, crate::http::resources().auth.clone(), secrets) .execute(AudioTranscriptionRequest { model: &model, audio, @@ -48,7 +48,8 @@ pub(crate) fn transcription(py: Python<'_>, call: NativeCall<'_>) -> PyResult( litellm_host_python::from_py_argument(&required_field(&arguments, "audio")?)?; let options = value_route_options(&arguments)?; let optional_params = optional_object_field(&arguments, "optional_params")?.unwrap_or_default(); - let http = crate::http::provider_client(py, &call.kwargs, true)?; + let http = + crate::http::provider_client(py, &call.kwargs, true)?.map_err(crate::http::client_error)?; let secrets = crate::secrets::source(py)?; run_async( py, diff --git a/litellm-rust/crates/python-bridge/src/routes/chat_completions/host.rs b/litellm-rust/crates/python-bridge/src/routes/chat_completions/host.rs index 5ad9f8df8b8..4db9b37cbb8 100644 --- a/litellm-rust/crates/python-bridge/src/routes/chat_completions/host.rs +++ b/litellm-rust/crates/python-bridge/src/routes/chat_completions/host.rs @@ -1,3 +1,4 @@ +use litellm_core_utils::decline::Decline; use std::convert::Infallible; use crate::routes::inference::InferenceHost; @@ -44,9 +45,9 @@ impl PythonBinding for ChatCompletionsPythonHost { .get("stream") .is_some_and(|value| value == &serde_json::Value::Bool(true)) { - return Err(InvokeError::Native(Error::Unsupported( + return Err(InvokeError::Native(Error::Declined(Decline::new( "native Python chat_completions streaming", - ))); + )))); } Ok(call) } @@ -79,7 +80,7 @@ impl PythonBinding for ChatCompletionsPythonHost { self.0.error(py, error) } fn host_error(error: &PyErr) -> Error { - Error::InvalidRequest(error.to_string().into()) + crate::routes::inference::host_call_error(error) } } diff --git a/litellm-rust/crates/python-bridge/src/routes/clickhouse_spend.rs b/litellm-rust/crates/python-bridge/src/routes/clickhouse_spend.rs index f8df7a9de23..80d7bd5360e 100644 --- a/litellm-rust/crates/python-bridge/src/routes/clickhouse_spend.rs +++ b/litellm-rust/crates/python-bridge/src/routes/clickhouse_spend.rs @@ -8,24 +8,13 @@ use pyo3::{ }; fn map_error(error: Error) -> PyErr { - use litellm_storage_clickhouse::Error as StorageError; - match error { - Error::InsertTooLarge | Error::Storage(StorageError::InsertTooLarge) => { - PyOverflowError::new_err(error.to_string()) - } - Error::InvalidRow - | Error::InvalidLimit(_) - | Error::InvalidSchema - | Error::Storage( - StorageError::InvalidRow - | StorageError::InvalidLimit(_) - | StorageError::InvalidTable - | StorageError::InvalidSchema - | StorageError::EmptySql - | StorageError::InvalidParameters - | StorageError::InvalidQuery, - ) => PyValueError::new_err(error.to_string()), - Error::Migration(_) | Error::Storage(_) => PyRuntimeError::new_err(error.to_string()), + let message = litellm_error::Report::new(&error).to_string(); + if error.is_insert_too_large() { + PyOverflowError::new_err(message) + } else if error.is_request() { + PyValueError::new_err(message) + } else { + PyRuntimeError::new_err(message) } } @@ -99,26 +88,22 @@ mod tests { use super::*; use rstest::rstest; + use litellm_storage_clickhouse::Error as StorageError; + #[rstest] - #[case::row(Error::InvalidRow, "ValueError")] - #[case::insert_limit(Error::InvalidLimit("CLICKHOUSE_TRACE_MAX_INSERT_BYTES"), "ValueError")] - #[case::insert_timeout( - Error::Storage(litellm_storage_clickhouse::Error::InvalidLimit( - "CLICKHOUSE_INSERT_TIMEOUT_SECONDS" - )), + #[case::timestamp(Error::NonIntegerTimestamp { field: "start_time" }, "ValueError")] + #[case::insert_limit( + StorageError::InvalidLimit("CLICKHOUSE_TRACE_MAX_INSERT_BYTES").into(), "ValueError" )] - #[case::insert_budget(Error::InsertTooLarge, "OverflowError")] - #[case::schema( - Error::Storage(litellm_storage_clickhouse::Error::SchemaFailed(503)), - "RuntimeError" - )] + #[case::insert_budget(StorageError::InsertTooLarge.into(), "OverflowError")] + #[case::schema(StorageError::SchemaFailed(503).into(), "RuntimeError")] #[case::migration( Error::Migration(sqlx::migrate::MigrateError::VersionMismatch(6)), "RuntimeError" )] #[case::storage( - Error::Storage(litellm_storage_clickhouse::Error::InvalidUrl), + Config::new("spend".into(), "ftp://localhost", 1).err().unwrap(), "RuntimeError" )] fn spend_failures_preserve_public_exception_types( @@ -127,7 +112,7 @@ mod tests { ) { Python::initialize(); Python::attach(|py| { - let message = error.to_string(); + let message = litellm_error::Report::new(&error).to_string(); let exception = map_error(error); assert_eq!(exception.get_type(py).name().unwrap(), exception_name); assert_eq!( @@ -136,4 +121,15 @@ mod tests { ); }); } + + #[test] + fn spend_failures_render_their_cause() { + let error = Config::new("spend".into(), "not a url", 1).err().unwrap(); + let cause = std::error::Error::source(&error).unwrap().to_string(); + Python::initialize(); + Python::attach(|py| { + let message = map_error(error).value(py).str().unwrap().to_string(); + assert!(message.ends_with(&cause), "{message}"); + }); + } } diff --git a/litellm-rust/crates/python-bridge/src/routes/embeddings.rs b/litellm-rust/crates/python-bridge/src/routes/embeddings.rs index 0f73eefedd5..0935f42f85a 100644 --- a/litellm-rust/crates/python-bridge/src/routes/embeddings.rs +++ b/litellm-rust/crates/python-bridge/src/routes/embeddings.rs @@ -1,14 +1,23 @@ +use litellm_error::Report; use pyo3::prelude::*; use super::NativeCall; use crate::errors::RustBridgeDeclined; +#[derive(Debug, thiserror::Error)] +#[error("native embeddings route is not implemented")] +struct NotImplemented; + +impl From for PyErr { + fn from(error: NotImplemented) -> Self { + RustBridgeDeclined::new_err(Report::new(&error).to_string()) + } +} + #[pyfunction] pub(crate) fn embedding(call: NativeCall<'_>) -> PyResult> { drop(call); - Err(RustBridgeDeclined::new_err( - "native embeddings route is not implemented", - )) + Err(NotImplemented.into()) } #[pyfunction] diff --git a/litellm-rust/crates/python-bridge/src/routes/inference.rs b/litellm-rust/crates/python-bridge/src/routes/inference.rs index c9eb60e47ed..ca30c94b02f 100644 --- a/litellm-rust/crates/python-bridge/src/routes/inference.rs +++ b/litellm-rust/crates/python-bridge/src/routes/inference.rs @@ -6,11 +6,9 @@ use litellm_callbacks_legacy_python::LoggingOperation; use litellm_core_utils::get_llm_provider_logic::get_custom_llm_provider; use litellm_host::{call::HostedMachine, protocol::Protocol}; use litellm_host_python::{PythonBinding, PythonHostCalls, from_py}; -use litellm_http::transport::Error as TransportError; use litellm_inference::Error; use litellm_secrets::source::SecretSource; use pyo3::{ - exceptions::PyValueError, gc::{PyTraverseError, PyVisit}, prelude::*, types::PyDict, @@ -20,8 +18,10 @@ use serde_json::{Map, Value}; use super::{NativeCall, RequestView}; use crate::{ - errors::{RustUpstreamError, route_error_to_pyerr}, - marshal::{RouteOptions, optional_timeout, public_response, python_timeout_seconds}, + errors::{RequestMarker, route_failure}, + marshal::{ + ArgumentError, RouteOptions, optional_timeout, public_response, python_timeout_seconds, + }, }; pub(super) struct InferenceHost { @@ -44,7 +44,7 @@ impl InferenceHost { &mut self, py: Python<'_>, arguments: &Bound<'_, PyDict>, - input: &str, + input: &'static str, ) -> PyResult { self.view.resolve(py, arguments)?; let argument = |name: &str| self.argument(py, arguments, name); @@ -57,7 +57,7 @@ impl InferenceHost { .map(|value| python_timeout_seconds(py, value.unbind())) .transpose()? .flatten(); - let model = string("model")?.ok_or_else(|| PyValueError::new_err("model is required"))?; + let model = string("model")?.ok_or(ArgumentError::Required("model"))?; let custom_llm_provider = string("custom_llm_provider")?; let provider = get_custom_llm_provider(&model, custom_llm_provider.as_deref()) .map_or("", |resolved| resolved.custom_llm_provider); @@ -82,10 +82,7 @@ impl InferenceHost { .transpose()?, timeout: optional_timeout(timeout), }, - input: from_py( - &argument(input)? - .ok_or_else(|| PyValueError::new_err(format!("{input} is required")))?, - )?, + input: from_py(&argument(input)?.ok_or(ArgumentError::Required(input))?)?, params, }) } @@ -120,29 +117,20 @@ impl InferenceHost { } pub fn error(&self, py: Python<'_>, error: Error) -> PyResult { - if let Error::Secret(source) = &error - && let Some(original) = crate::secrets::python_error(py, source.source_error()) - { - return Ok(original); - } - let native = match error { - Error::Transport(TransportError::Http { status, body }) => { - let error = RustUpstreamError::new_err((status, body)); - error - .value(py) - .setattr("headers", Vec::<(String, String)>::new())?; - error - } - other => route_error_to_pyerr(other), - }; - let mapped = py - .import(self.module)? - .getattr("map_failure")? - .call1((native.value(py), self.view.request(py)?))?; - Ok(PyErr::from_value(mapped)) + route_failure(py, error, RequestMarker::Unmarked, |native| { + let mapped = py + .import(self.module)? + .getattr("map_failure")? + .call1((native.value(py), self.view.request(py)?))?; + Ok(PyErr::from_value(mapped)) + }) } } +pub(super) fn host_call_error(_: &PyErr) -> Error { + Error::invalid_request(litellm_llms::ErrorDetail::HostCall) +} + pub(super) trait InferenceRoute: Sized + 'static { type Protocol: Protocol; const OPERATION: LoggingOperation; diff --git a/litellm-rust/crates/python-bridge/src/routes/messages/host.rs b/litellm-rust/crates/python-bridge/src/routes/messages/host.rs index 5e445fcaa7d..27ce8c943f0 100644 --- a/litellm-rust/crates/python-bridge/src/routes/messages/host.rs +++ b/litellm-rust/crates/python-bridge/src/routes/messages/host.rs @@ -3,7 +3,6 @@ use litellm_host_python::{PythonHostCalls, PythonOwned}; use bytes::Bytes; use litellm_host_python::{InvokeError, PythonBinding, from_py, to_py}; -use litellm_http::transport::Error as TransportError; use litellm_inference_messages::{ Error, MessagesCall, MessagesSettings, MessagesShaping, litellm_params, messages_body, route::{Messages, MessagesStreamHead}, @@ -12,7 +11,7 @@ use litellm_llms::base_llm::messages::context::MessagesModelCapabilities; use litellm_llms_types::headers::ProviderSpecificHeaders; use litellm_router_types::LitellmParams; use pyo3::{ - exceptions::{PyException, PyValueError}, + exceptions::PyException, gc::{PyTraverseError, PyVisit}, prelude::*, types::{PyBytes, PyDict}, @@ -20,14 +19,16 @@ use pyo3::{ use serde_json::{Map, Value}; use crate::{ - errors::{RustUpstreamError, route_error_to_pyerr}, - marshal::{optional_timeout, project_optional_fields, public_response, python_timeout_seconds}, + errors::{RequestMarker, route_failure}, + marshal::{ + ArgumentError, optional_timeout, project_optional_fields, public_response, + python_timeout_seconds, + }, python_settings::missing_module, routes::RequestView, }; const ROUTE_HOST_MODULE: &str = "litellm.rust_bridge.host.routes.messages"; -const REQUEST_ERROR_MARKER: &str = "messages_request_error"; fn merge_headers( forwarded: Option>, @@ -68,29 +69,6 @@ fn project_litellm_params<'py>( Ok(litellm_params(fields.into_iter().chain(folded).collect())) } -fn native_error(py: Python<'_>, error: Error) -> PyResult { - match error { - Error::Transport(TransportError::Http { status, body }) => { - let error = RustUpstreamError::new_err((status, body)); - error - .value(py) - .setattr("headers", Vec::<(String, String)>::new())?; - Ok(error) - } - Error::InvalidRequest(message) => { - let error = PyValueError::new_err(message.to_string()); - error.value(py).setattr(REQUEST_ERROR_MARKER, true)?; - Ok(error) - } - Error::MissingField(field) => { - let error = PyValueError::new_err(format!("missing required field: {field}")); - error.value(py).setattr(REQUEST_ERROR_MARKER, true)?; - Ok(error) - } - other => Ok(route_error_to_pyerr(other)), - } -} - /// The Python side of the Messages route: projects the prepared arguments and builds the /// public response, chunks and exceptions. pub(super) struct MessagesPythonHost { @@ -115,9 +93,8 @@ impl MessagesPythonHost { let string = |name: &str| -> PyResult> { argument(name)?.map(|value| value.extract()).transpose() }; - let model = string("model")?.ok_or_else(|| PyValueError::new_err("model is required"))?; - let messages = - argument("messages")?.ok_or_else(|| PyValueError::new_err("messages is required"))?; + let model = string("model")?.ok_or(ArgumentError::Required("model"))?; + let messages = argument("messages")?.ok_or(ArgumentError::Required("messages"))?; let fields = self.view.body_params(py, arguments, ROUTE_HOST_MODULE)?; let body = [ ("model".to_string(), Value::String(model.clone())), @@ -276,16 +253,13 @@ impl PythonBinding for MessagesPythonHost { } fn map_error(&self, py: Python<'_>, error: Error) -> PyResult { - if let Error::Secret(source) = &error - && let Some(original) = crate::secrets::python_error(py, source.source_error()) - { - return Ok(original); - } - Ok(self.map_failure(py, native_error(py, error)?)) + route_failure(py, error, RequestMarker::Messages, |native| { + Ok(self.map_failure(py, native)) + }) } fn host_error(error: &PyErr) -> Error { - Error::InvalidRequest(error.to_string().into()) + crate::routes::inference::host_call_error(error) } } @@ -459,33 +433,9 @@ mod tests { projected, litellm_params(serde_json::from_value(fields).unwrap()).unwrap() ), - (Err(error), Err(())) => assert!(matches!(error, Error::InvalidRequest(_))), + (Err(error), Err(())) => assert!(error.is_request(), "{error:?}"), (projected, expected) => panic!("got {projected:?}, expected {expected:?}"), } }); } - - #[rstest] - #[case::rejected_request(Error::InvalidRequest("does not support top_k=5".into()), true)] - #[case::missing_field(Error::MissingField("max_tokens"), true)] - #[case::unresolvable_provider(Error::InvalidProvider("openai".into()), false)] - #[case::upstream_failure( - Error::Transport(TransportError::Http { status: 400, body: "bad".into() }), - false, - )] - fn only_request_rejections_carry_the_request_error_marker( - #[case] error: Error, - #[case] marked: bool, - ) { - Python::initialize(); - Python::attach(|py| { - let native = native_error(py, error).unwrap(); - let marker = native - .value(py) - .getattr_opt(REQUEST_ERROR_MARKER) - .unwrap() - .map(|value| value.extract::().unwrap()); - assert_eq!(marker.unwrap_or(false), marked); - }); - } } diff --git a/litellm-rust/crates/python-bridge/src/routes/ocr/document.rs b/litellm-rust/crates/python-bridge/src/routes/ocr/document.rs index f85d7d4c7cb..71eb743138d 100644 --- a/litellm-rust/crates/python-bridge/src/routes/ocr/document.rs +++ b/litellm-rust/crates/python-bridge/src/routes/ocr/document.rs @@ -9,6 +9,29 @@ use pyo3::{ types::{PyBytes, PyString, PyType}, }; +/// A `type='file'` document the bridge cannot read, with the text Python's OCR path raises. +#[derive(Debug, thiserror::Error)] +enum DocumentError { + #[error( + "document with type='file' must include a 'file' field containing a pathlib.Path, file-like object, or bytes" + )] + MissingFile, + #[error( + "OCR file input does not accept bare str values. Pass bytes, a pathlib.Path, or a file-like object." + )] + BareString, + #[error( + "Unsupported file input type: {0}. Expected pathlib.Path, bytes, or a file-like object." + )] + UnsupportedType(String), +} + +impl From for PyErr { + fn from(error: DocumentError) -> Self { + PyValueError::new_err(litellm_error::Report::new(&error).to_string()) + } +} + /// A `type='file'` document as projected: paths and bytes are typed inputs already; a /// file-like object is a reader the projection consumes once every other field is read. pub(super) enum FileDocumentInput { @@ -45,25 +68,18 @@ impl FromPyObject<'_, '_> for FileDocumentInput { Err(error) if error.is_instance_of::(py) => None, Err(error) => return Err(error), }; - let missing = || { - PyValueError::new_err( - "document with type='file' must include a 'file' field containing a pathlib.Path, file-like object, or bytes", - ) - }; - let file = document.get_item("file").map_err(|error| { - if error.is_instance_of::(py) { - missing() - } else { - error + let file = match document.get_item("file") { + Ok(file) => file, + Err(error) if error.is_instance_of::(py) => { + return Err(DocumentError::MissingFile.into()); } - })?; + Err(error) => return Err(error), + }; if file.is_none() { - return Err(missing()); + return Err(DocumentError::MissingFile.into()); } if file.is_instance_of::() { - return Err(PyValueError::new_err( - "OCR file input does not accept bare str values. Pass bytes, a pathlib.Path, or a file-like object.", - )); + return Err(DocumentError::BareString.into()); } static PATH_LIKE: PyOnceLock> = PyOnceLock::new(); if file.is_instance(PATH_LIKE.import(py, "os", "PathLike")?)? { @@ -81,10 +97,7 @@ impl FromPyObject<'_, '_> for FileDocumentInput { } match PythonFileReader::from_file_like(&file)? { Some(reader) => Ok(Self::Deferred { reader, mime_type }), - None => Err(PyValueError::new_err(format!( - "Unsupported file input type: {}. Expected pathlib.Path, bytes, or a file-like object.", - file.get_type(), - ))), + None => Err(DocumentError::UnsupportedType(file.get_type().to_string()).into()), } } } @@ -92,6 +105,7 @@ impl FromPyObject<'_, '_> for FileDocumentInput { #[cfg(test)] mod tests { use pyo3::{exceptions::PyTypeError, types::PyDict}; + use rstest::rstest; use super::*; @@ -108,40 +122,47 @@ mod tests { } } - #[test] - fn extraction_validates_required_file_and_optional_mime_type() { + enum Rejection { + Value(&'static str), + Type, + } + + #[rstest] + #[case::missing_file(c"{}", Rejection::Value("must include a 'file' field"))] + #[case::none_file(c"{'file': None}", Rejection::Value("must include a 'file' field"))] + #[case::none_mime_type(c"{'file': b'abc', 'mime_type': None}", Rejection::Type)] + #[case::numeric_mime_type(c"{'file': b'abc', 'mime_type': 7}", Rejection::Type)] + #[case::bare_str(c"{'file': 'scan.pdf'}", Rejection::Value("bare str"))] + #[case::unsupported_type( + c"{'file': object()}", + Rejection::Value("Unsupported file input type") + )] + fn extraction_rejects_invalid_documents( + #[case] expression: &std::ffi::CStr, + #[case] rejection: Rejection, + ) { Python::initialize(); Python::attach(|py| { - for expression in [c"{}", c"{'file': None}"] { - let document = py.eval(expression, None, None).unwrap(); - let error = document.extract::().err().unwrap(); - assert!(error.is_instance_of::(py)); - assert!(error.to_string().contains("must include a 'file' field")); - } - for expression in [ - c"{'file': b'abc', 'mime_type': None}", - c"{'file': b'abc', 'mime_type': 7}", - ] { - let document = py.eval(expression, None, None).unwrap(); - let error = document.extract::().err().unwrap(); - assert!(error.is_instance_of::(py)); - } let error = py - .eval(c"{'file': 'scan.pdf'}", None, None) + .eval(expression, None, None) .unwrap() .extract::() .err() .unwrap(); - assert!(error.is_instance_of::(py)); - assert!(error.to_string().contains("bare str")); - let error = py - .eval(c"{'file': object()}", None, None) - .unwrap() - .extract::() - .err() - .unwrap(); - assert!(error.is_instance_of::(py)); - assert!(error.to_string().contains("Unsupported file input type")); + match rejection { + Rejection::Value(fragment) => { + assert!(error.is_instance_of::(py)); + assert!(error.to_string().contains(fragment), "{error}"); + } + Rejection::Type => assert!(error.is_instance_of::(py)), + } + }); + } + + #[test] + fn extraction_keeps_bytes_and_their_mime_type() { + Python::initialize(); + Python::attach(|py| { let document = py .eval(c"{'file': b'abc', 'mime_type': 'image/png'}", None, None) .unwrap(); diff --git a/litellm-rust/crates/python-bridge/src/routes/ocr/errors.rs b/litellm-rust/crates/python-bridge/src/routes/ocr/errors.rs index 2068b6a6e4b..31736c7b654 100644 --- a/litellm-rust/crates/python-bridge/src/routes/ocr/errors.rs +++ b/litellm-rust/crates/python-bridge/src/routes/ocr/errors.rs @@ -1,128 +1,203 @@ +use std::io::ErrorKind; + +use litellm_error::Report; use litellm_llms::base_llm::ocr::error::Error; use pyo3::{ exceptions::{PyFileNotFoundError, PyOSError}, prelude::*, }; -use crate::errors::{RustUpstreamError, by_fault}; +use crate::errors::{by_fault, upstream_error}; + +const REQUEST_FORMAT_ERROR: &str = "ocr_request_format_error"; pub(super) fn to_pyerr(error: Error) -> PyErr { - let status = error.http_status_code(); - let mapped = Python::attach(|py| -> PyResult { - Ok(match error { - Error::Provider { - status, - body, - headers, - } => upstream_error(py, status, body, headers)?, - Error::Transport(litellm_http::transport::Error::Http { status, body }) => { - upstream_error(py, status, body, Vec::new())? - } - Error::RequestFormat => { - let error = by_fault(true, Error::RequestFormat.to_string()); - error - .value(py) - .setattr("ocr_request_format_error", true) - .ok(); - error - } - Error::FileRead { path, source } if source.kind() == std::io::ErrorKind::NotFound => { - PyFileNotFoundError::new_err(format!("File not found: {}", path.display())) - } - Error::FileRead { source, .. } => PyOSError::new_err(source.to_string()), - other => by_fault(is_request(&other), other.to_string()), - }) - }) - .unwrap_or_else(|error| error); - attach_status(mapped, status) + Python::attach(|py| native(py, error).unwrap_or_else(std::convert::identity)) } -fn is_request(error: &Error) -> bool { - error.is_request() - || matches!( - error, - Error::Auth(_) - | Error::InvalidProvider(_) - | Error::InvalidRequest(_) - | Error::MissingField(_) - | Error::MissingDocumentUrl - ) -} - -fn upstream_error( +/// Maps an OCR route failure once. A Python exception raised inside the call is returned as it +/// is, everything else is mapped and handed to `public`, the route's public exception mapping. +pub(super) fn route_failure( py: Python<'_>, - status: u16, - body: String, - headers: Vec<(String, String)>, + error: Error, + public: impl FnOnce(PyErr) -> PyResult, ) -> PyResult { - let error = RustUpstreamError::new_err((status, body)); - error.value(py).setattr("headers", headers)?; - Ok(error) + match crate::secrets::python_error(py, &error) { + Some(raised) => Ok(raised), + None => public(native(py, error)?), + } } -fn attach_status(error: PyErr, status: Option) -> PyErr { - if let Some(status) = status { - Python::attach(|py| { - let value = error.value(py); - value.setattr("status_code", status).ok(); - value.setattr("message", value.to_string()).ok(); - }); +fn native(py: Python<'_>, error: Error) -> PyResult { + let mapped = match (&error, error.upstream_response()) { + (_, Some((status, body, headers))) => upstream_error(py, status, body, headers)?, + (Error::RequestFormat, None) => { + let mapped = by_fault(true, &error); + mapped.value(py).setattr(REQUEST_FORMAT_ERROR, true)?; + mapped + } + (Error::FileRead { path, cause }, None) if cause.kind() == ErrorKind::NotFound => { + PyFileNotFoundError::new_err(format!("File not found: {}", path.display())) + } + (Error::FileRead { cause, .. }, None) => { + PyOSError::new_err(Report::new(cause.as_ref()).to_string()) + } + (_, None) => by_fault(error.is_request(), &error), + }; + if let Some(status) = error.http_status_code() { + let value = mapped.value(py); + value.setattr("status_code", status)?; + value.setattr("message", value.str()?)?; } - error + Ok(mapped) } #[cfg(test)] mod tests { - use pyo3::exceptions::PyValueError; + use pyo3::exceptions::{PyRuntimeError, PyValueError}; + use rstest::rstest; use super::*; + use crate::errors::RustUpstreamError; - #[test] - fn preserves_python_validation_and_provider_details() { + fn status_code(py: Python<'_>, mapped: &PyErr) -> Option { + mapped + .value(py) + .getattr_opt("status_code") + .unwrap() + .map(|status| status.extract().unwrap()) + } + + fn file_read(kind: ErrorKind) -> Error { + Error::FileRead { + path: "/missing/scan.pdf".into(), + cause: std::sync::Arc::new(std::io::Error::new(kind, "disk said no")), + } + } + + #[rstest] + #[case::provider( + Error::Provider { + status: 429, + body: r#"{"message":"rate limited"}"#.into(), + headers: Box::new(reqwest::header::HeaderMap::from_iter([( + reqwest::header::RETRY_AFTER, + reqwest::header::HeaderValue::from_static("17"), + )])), + }, + vec![("retry-after".into(), "17".into())] + )] + #[case::transport(litellm_http::Error::upstream(429, r#"{"message":"rate limited"}"#.into()).into(), vec![])] + fn a_provider_answer_keeps_its_status_body_and_headers( + #[case] error: Error, + #[case] headers: Vec<(String, String)>, + ) { Python::initialize(); Python::attach(|py| { - let mapped = to_pyerr(Error::MissingDocumentUrl); - assert!(mapped.is_instance_of::(py)); - assert_eq!(mapped.value(py).to_string(), "Document URL is required"); - assert_eq!( - mapped - .value(py) - .getattr("status_code") - .unwrap() - .extract::() - .unwrap(), - 400 - ); - let mapped = to_pyerr(Error::Provider { - status: 429, - body: r#"{"message":"rate limited"}"#.to_string(), - headers: vec![("Retry-After".to_string(), "17".to_string())], - }); + let mapped = to_pyerr(error); assert!(mapped.is_instance_of::(py)); - let headers: Vec<(String, String)> = mapped - .value(py) - .getattr("headers") - .and_then(|headers| headers.extract()) - .expect("OCR failures retain provider headers"); - assert_eq!(headers, vec![("Retry-After".to_string(), "17".to_string())]); - let args: (u16, String) = mapped - .value(py) - .getattr("args") - .and_then(|args| args.extract()) - .expect("OCR failures retain status and unprefixed provider message"); - assert_eq!(args, (429, r#"{"message":"rate limited"}"#.to_string())); + let value = mapped.value(py); + let args: (u16, String) = value.getattr("args").unwrap().extract().unwrap(); + assert_eq!(args, (429, r#"{"message":"rate limited"}"#.into())); + let kept: Vec<(String, String)> = value.getattr("headers").unwrap().extract().unwrap(); + assert_eq!(kept, headers); + assert_eq!(status_code(py, &mapped), Some(429)); + }); + } - let mapped = to_pyerr(Error::InvalidRequest("invalid format".into())); + #[rstest] + #[case::not_found(Some(404), 404, "OCR document download failed")] + #[case::rate_limited(Some(429), 429, "OCR document download failed")] + #[case::timeout(None, 408, "OCR document download timed out")] + #[tokio::test] + async fn document_download_failures_keep_the_upstream_exception( + #[case] response_status: Option, + #[case] expected_status: u16, + #[case] expected_body: &str, + ) { + use std::time::Duration; + + use litellm_http::{Client, media::MediaFetcher}; + use litellm_llms::base_llm::ocr::{ + document::inline_remote_document, transformation::OcrConnection, + }; + use litellm_llms_types::formats::ocr::OcrDocument; + use tokio::{ + io::{AsyncReadExt, AsyncWriteExt}, + net::TcpListener, + }; + + let listener = TcpListener::bind("127.0.0.1:0").await.unwrap(); + let address = listener.local_addr().unwrap(); + let server = tokio::spawn(async move { + let (mut socket, _) = listener.accept().await.unwrap(); + let mut request = [0_u8; 1]; + socket.read_exact(&mut request).await.unwrap(); + if let Some(status) = response_status { + socket.write_all(format!("HTTP/1.1 {status} Error\r\nContent-Length: 0\r\nConnection: close\r\n\r\n").as_bytes()).await.unwrap(); + } else { + std::future::pending::<()>().await; + } + }); + let connection = OcrConnection { + timeout: Duration::from_millis(100), + ..OcrConnection::default() + }; + let error = inline_remote_document( + &MediaFetcher::for_test(Client::for_test()), + OcrDocument::DocumentUrl { + document_url: format!("http://{address}/document.pdf"), + extra_fields: Default::default(), + }, + &connection, + ) + .await + .unwrap_err(); + server.abort(); + if response_status.is_none() { + assert!(litellm_error::find::(&error).is_some()); + } + Python::initialize(); + Python::attach(|py| { + let mapped = to_pyerr(error); + assert!(mapped.is_instance_of::(py), "{mapped}"); + let args: (u16, String) = mapped.value(py).getattr("args").unwrap().extract().unwrap(); + assert_eq!(args, (expected_status, expected_body.into())); + assert_eq!(status_code(py, &mapped), Some(expected_status)); + }); + } + + #[rstest] + #[case::missing_document_url(Error::MissingDocumentUrl)] + #[case::invalid_features(Error::Features)] + #[case::invalid_provider(Error::InvalidProvider("unknown".into()))] + fn request_faults_are_value_errors_with_status_400(#[case] error: Error) { + Python::initialize(); + Python::attach(|py| { + let report = Report::new(&error).to_string(); + let mapped = to_pyerr(error); assert!(mapped.is_instance_of::(py)); - assert_eq!( - mapped - .value(py) - .getattr("status_code") - .unwrap() - .extract::() - .unwrap(), - 400 - ); + assert_eq!(mapped.value(py).to_string(), report); + assert_eq!(status_code(py, &mapped), Some(400)); + }); + } + + #[rstest] + #[case::missing_api_key(litellm_auth::Error::MissingApiKey { + provider: "Mistral", + environment_variable: "MISTRAL_API_KEY", + } + .into())] + #[case::missing_credential(Error::MissingCredential { + credential: "Azure AI credentials", + guidance: "set AZURE_AI_API_KEY", + })] + fn a_missing_credential_is_a_statusless_runtime_error(#[case] error: Error) { + Python::initialize(); + Python::attach(|py| { + let mapped = to_pyerr(error); + assert!(mapped.is_instance_of::(py)); + assert_eq!(status_code(py, &mapped), None); }); } @@ -135,19 +210,12 @@ mod tests { assert!(mapped.is_instance_of::(py)); assert!( value - .getattr("ocr_request_format_error") + .getattr(REQUEST_FORMAT_ERROR) .unwrap() .extract::() .unwrap() ); - assert_eq!( - value - .getattr("status_code") - .unwrap() - .extract::() - .unwrap(), - 400 - ); + assert_eq!(status_code(py, &mapped), Some(400)); assert_eq!( value .getattr("message") @@ -159,18 +227,11 @@ mod tests { }); } - fn file_read(kind: std::io::ErrorKind) -> Error { - Error::FileRead { - path: "/missing/scan.pdf".into(), - source: std::sync::Arc::new(std::io::Error::new(kind, "disk said no")), - } - } - #[test] fn missing_files_map_to_file_not_found_naming_the_path() { Python::initialize(); Python::attach(|py| { - let mapped = to_pyerr(file_read(std::io::ErrorKind::NotFound)); + let mapped = to_pyerr(file_read(ErrorKind::NotFound)); assert!(mapped.is_instance_of::(py)); assert_eq!( mapped.value(py).to_string(), @@ -183,28 +244,32 @@ mod tests { fn other_file_read_failures_map_to_os_error_with_the_io_message() { Python::initialize(); Python::attach(|py| { - let mapped = to_pyerr(file_read(std::io::ErrorKind::PermissionDenied)); + let mapped = to_pyerr(file_read(ErrorKind::PermissionDenied)); assert!(mapped.is_instance_of::(py)); assert!(!mapped.is_instance_of::(py)); assert_eq!(mapped.value(py).to_string(), "disk said no"); }); } - #[rstest::rstest] + #[rstest] #[case::oversized(Error::TooLarge { limit: 7 })] - #[case::malformed_field(Error::ResponseField { path: "pages[0].index".into() })] - fn response_failures_are_statusless_runtime_errors(#[case] error: Error) { + #[case::malformed_field(Error::response_field( + "pages[0].index", + "-1".parse::().unwrap_err() + ))] + fn response_failures_are_statusless_runtime_errors( + #[case] error: Error, + #[values("status_code", "ocr_request_format_error", "headers")] attribute: &str, + ) { Python::initialize(); Python::attach(|py| { - let message = error.to_string(); + let report = Report::new(&error).to_string(); let mapped = to_pyerr(error); let value = mapped.value(py); - assert!(mapped.is_instance_of::(py)); + assert!(mapped.is_instance_of::(py)); assert!(!mapped.is_instance_of::(py)); - assert_eq!(value.to_string(), message); - for attribute in ["status_code", "ocr_request_format_error", "headers"] { - assert!(!value.hasattr(attribute).unwrap(), "{attribute}"); - } + assert_eq!(value.to_string(), report); + assert!(!value.hasattr(attribute).unwrap()); }); } } diff --git a/litellm-rust/crates/python-bridge/src/routes/ocr/host.rs b/litellm-rust/crates/python-bridge/src/routes/ocr/host.rs index fc1b70392e2..c21ce6d76b6 100644 --- a/litellm-rust/crates/python-bridge/src/routes/ocr/host.rs +++ b/litellm-rust/crates/python-bridge/src/routes/ocr/host.rs @@ -12,8 +12,8 @@ use pyo3::{ }; use super::{ - errors::to_pyerr as ocr_error_to_pyerr, - project::{OcrHostHandles, SETTINGS_ERROR_MARKER, project_request}, + errors::route_failure, + project::{OcrHostHandles, ROUTE_HOST_MODULE, SETTINGS_ERROR_MARKER, project_request}, }; use crate::{marshal::public_response, routes::RequestView}; @@ -77,7 +77,7 @@ impl OcrPythonHost { _ => "", }; let mapped = py - .import("litellm.rust_bridge.host.routes.ocr") + .import(ROUTE_HOST_MODULE) .and_then(|module| module.getattr("map_failure")) .and_then(|map| map.call1((error.value(py), self.view.request(py)?, provider))) .and_then(|mapped| mapped.extract::>().map_err(PyErr::from)); @@ -115,7 +115,7 @@ impl PythonBinding for OcrPythonHost { py: Python<'_>, response: LiteLLMOcrResponse, ) -> PyResult> { - public_response(py, "litellm.rust_bridge.host.routes.ocr", &response) + public_response(py, ROUTE_HOST_MODULE, &response) } fn encode_stream_head( @@ -135,16 +135,11 @@ impl PythonBinding for OcrPythonHost { } fn map_error(&self, py: Python<'_>, error: Error) -> PyResult { - if let Error::Secret(source) = &error - && let Some(original) = crate::secrets::python_error(py, source) - { - return Ok(original); - } - Ok(self.map_failure(py, ocr_error_to_pyerr(error))) + route_failure(py, error, |native| Ok(self.map_failure(py, native))) } - fn host_error(error: &PyErr) -> Error { - Error::InvalidRequest(error.to_string()) + fn host_error(_: &PyErr) -> Error { + Error::HostCall } } diff --git a/litellm-rust/crates/python-bridge/src/routes/ocr/project.rs b/litellm-rust/crates/python-bridge/src/routes/ocr/project.rs index fe2f83bff46..c2c3fe51600 100644 --- a/litellm-rust/crates/python-bridge/src/routes/ocr/project.rs +++ b/litellm-rust/crates/python-bridge/src/routes/ocr/project.rs @@ -5,18 +5,22 @@ use litellm_inference_ocr::{ types::{LiteLLMOcrRequest, OcrDocumentInput}, wire::{OcrWireRequest, consumed_optional_params, decode_document, decode_request_input}, }; -use litellm_llms::base_llm::ocr::error::Error; -use pyo3::{exceptions::PyValueError, prelude::*, types::PyDict}; +use litellm_llms::base_llm::ocr::{error::Error, transformation::DROP_PARAMS_PARAM}; +use pyo3::{prelude::*, types::PyDict}; use serde_json::{Map, Value}; use super::{document::FileDocumentInput, errors::to_pyerr as ocr_error_to_pyerr}; use crate::{ coercion::FieldSpec, credentials::{self, CallerTokenProvider}, - marshal::{project_optional_fields, python_timeout_seconds, request_input_sources}, + marshal::{ + ArgumentError, project_optional_fields, python_timeout_seconds, request_input_sources, + }, python_settings::{PythonSettings, Snapshot}, }; +pub(super) const ROUTE_HOST_MODULE: &str = "litellm.rust_bridge.host.routes.ocr"; + /// What the host keeps after projection: the caller's token callable that answers the /// token operation, and the provider name the failure mapping reports. pub(super) struct OcrHostHandles { @@ -30,9 +34,9 @@ struct OcrArguments<'a, 'py> { } impl<'py> OcrArguments<'_, 'py> { - fn lookup(&self, name: &str) -> PyResult> { - litellm_host_python::lookup(self.kwargs, self.bound, name)? - .ok_or_else(|| PyValueError::new_err(format!("missing argument: {name}"))) + fn lookup(&self, name: &'static str) -> PyResult> { + Ok(litellm_host_python::lookup(self.kwargs, self.bound, name)? + .ok_or(ArgumentError::Required(name))?) } fn model(&self) -> PyResult { @@ -92,6 +96,7 @@ impl ProjectedDocument { { ocr_error_to_pyerr(Error::RequestField { path: "document.type".into(), + cause: None, }) } else { error @@ -136,6 +141,15 @@ pub(super) fn project_request( Some(defaults) => fold_module_globals(bound.py(), optional_params, &globals, &defaults)?, None => optional_params, }; + let optional_params = if names.contains(&DROP_PARAMS_PARAM) { + fold_drop_params( + bound.py(), + optional_params, + present(kwargs, bound, DROP_PARAMS_PARAM)?, + )? + } else { + optional_params + }; let input_sources = request_input_sources( kwargs, names @@ -213,13 +227,32 @@ fn fold_module_globals( .collect()) } +fn fold_drop_params( + py: Python<'_>, + optional_params: Map, + requested: Option>, +) -> PyResult> { + let drops: bool = py + .import(ROUTE_HOST_MODULE)? + .getattr("drops_unsupported_params")? + .call1((requested,))? + .extract()?; + Ok(optional_params + .into_iter() + .filter(|(name, _)| name != DROP_PARAMS_PARAM) + .chain(drops.then(|| (DROP_PARAMS_PARAM.to_string(), Value::Bool(true)))) + .collect()) +} + /// A misconfigured litellm setting is the operator's error, not the request's or the /// provider's, so the host raises it as is instead of mapping it onto a provider failure. pub(super) const SETTINGS_ERROR_MARKER: &str = "native_settings_error"; fn settings_error(py: Python<'_>, error: PyErr) -> PyErr { - error.value(py).setattr(SETTINGS_ERROR_MARKER, true).ok(); - error + match error.value(py).setattr(SETTINGS_ERROR_MARKER, true) { + Ok(()) => error, + Err(failure) => failure, + } } #[cfg(test)] diff --git a/litellm-rust/crates/python-bridge/src/routes/responses/host.rs b/litellm-rust/crates/python-bridge/src/routes/responses/host.rs index 9c430ba7868..b797e334c6a 100644 --- a/litellm-rust/crates/python-bridge/src/routes/responses/host.rs +++ b/litellm-rust/crates/python-bridge/src/routes/responses/host.rs @@ -1,3 +1,4 @@ +use litellm_core_utils::decline::Decline; use std::convert::Infallible; use crate::routes::inference::InferenceHost; @@ -118,9 +119,9 @@ impl PythonBinding for ResponsesPythonHost { .get("stream") .is_some_and(|value| value == &serde_json::Value::Bool(true)) { - return Err(InvokeError::Native(Error::Unsupported( + return Err(InvokeError::Native(Error::Declined(Decline::new( "native Python responses streaming", - ))); + )))); } Ok(call) } @@ -141,8 +142,10 @@ impl PythonBinding for ResponsesPythonHost { head: ::StreamHead, ) -> PyResult> { let _ = head; - Err(pyo3::exceptions::PyRuntimeError::new_err( - "native Python Responses streaming is not supported", + Err(crate::errors::route_error_to_pyerr( + Error::invalid_response(litellm_llms::ErrorDetail::Unhandled( + "native Python responses streaming", + )), )) } @@ -152,8 +155,10 @@ impl PythonBinding for ResponsesPythonHost { chunk: ::Chunk, ) -> PyResult> { let _ = chunk; - Err(pyo3::exceptions::PyRuntimeError::new_err( - "native Python Responses streaming is not supported", + Err(crate::errors::route_error_to_pyerr( + Error::invalid_response(litellm_llms::ErrorDetail::Unhandled( + "native Python responses streaming", + )), )) } @@ -161,7 +166,7 @@ impl PythonBinding for ResponsesPythonHost { self.host.error(py, error) } fn host_error(error: &PyErr) -> Error { - Error::InvalidRequest(error.to_string().into()) + crate::routes::inference::host_call_error(error) } } diff --git a/litellm-rust/crates/python-bridge/src/routes/responses/websocket.rs b/litellm-rust/crates/python-bridge/src/routes/responses/websocket.rs index 615a838a597..c89185dc21f 100644 --- a/litellm-rust/crates/python-bridge/src/routes/responses/websocket.rs +++ b/litellm-rust/crates/python-bridge/src/routes/responses/websocket.rs @@ -1,7 +1,9 @@ -use litellm_inference_responses::websocket::ResponsesWebSocketConnection as RustResponsesWebSocketConnection; use pyo3::prelude::*; use serde_json::Value; +use litellm_http::ClientVariant; +use litellm_inference_responses::websocket::ResponsesWebSocketConnection as RustResponsesWebSocketConnection; + use crate::{ errors::route_error_to_pyerr, marshal::{marshal_headers, optional_timeout}, @@ -25,10 +27,12 @@ impl ResponsesWebSocketConnection { ) -> PyResult> { let headers = marshal_headers(headers)?; let timeout = optional_timeout(timeout_seconds); + let client = crate::http::host_client(py, ClientVariant::WebSocket)?; crate::execution::run_async_value(py, async move { - let inner = RustResponsesWebSocketConnection::connect_url(&url, &headers, timeout) - .await - .map_err(route_error_to_pyerr)?; + let inner = + RustResponsesWebSocketConnection::connect_url(&client, &url, &headers, timeout) + .await + .map_err(route_error_to_pyerr)?; Ok(ResponsesWebSocketConnection { inner }) }) } diff --git a/litellm-rust/crates/python-bridge/src/routes/token_counter.rs b/litellm-rust/crates/python-bridge/src/routes/token_counter.rs index 2c26311231f..4b10eed087f 100644 --- a/litellm-rust/crates/python-bridge/src/routes/token_counter.rs +++ b/litellm-rust/crates/python-bridge/src/routes/token_counter.rs @@ -2,6 +2,7 @@ use crate::execution::run_async; use std::sync::Arc; use std::{num::NonZero, thread::available_parallelism}; +use litellm_error::{Report, Source}; use litellm_host_python::enter_native; use litellm_token_counter::{ CountableRequest, Error, InputTokenCount, TokenCounter as CoreTokenCounter, @@ -50,10 +51,10 @@ impl TokenCounter { let _slot = encode_slots .acquire_owned() .await - .map_err(|error| Error::Task(error.to_string()))?; + .map_err(|error| Error::Task(Source::new(error)))?; tokio::task::spawn_blocking(move || count_body(&counter, &body)) .await - .map_err(|error| Error::Task(error.to_string()))? + .map_err(|error| Error::Task(Source::new(error)))? }, token_count_error_to_pyerr, ) @@ -70,19 +71,12 @@ fn count_body(counter: &CoreTokenCounter, body: &[u8]) -> Result PyErr { - let message = error.to_string(); - match error { - Error::Load(_) - | Error::Ranks(_) - | Error::UnicodeClasses - | Error::UnsupportedTokenizer(_) => PyValueError::new_err(message), - Error::RequestParse(_) - | Error::MissingInput - | Error::FloatText - | Error::ContentBlock - | Error::ArrayItems - | Error::JsonSerialization(_) - | Error::JsonUtf8(_) => RustBridgeDeclined::new_err(message), - Error::Encode(_) | Error::Decode(_) | Error::Task(_) => PyRuntimeError::new_err(message), + let message = Report::new(&error).to_string(); + if error.is_unsupported() { + RustBridgeDeclined::new_err(message) + } else if error.is_load() { + PyValueError::new_err(message) + } else { + PyRuntimeError::new_err(message) } } diff --git a/litellm-rust/crates/python-bridge/src/secrets/callback.rs b/litellm-rust/crates/python-bridge/src/secrets/callback.rs index 71a06bfdc39..669c10e602a 100644 --- a/litellm-rust/crates/python-bridge/src/secrets/callback.rs +++ b/litellm-rust/crates/python-bridge/src/secrets/callback.rs @@ -192,7 +192,7 @@ handler.get_secret_from_manager = get_secret_from_manager KeyManagementSettings::default(), )), Arc::new(move |_: &str| fallback.map(str::to_owned)), - OidcResolver::new(litellm_http::Client::plain_for_test()), + OidcResolver::new(litellm_http::Client::for_test()), ) .with_failure_policy(FailurePolicy::EnvironmentFallback); (resolver, locals, handler) diff --git a/litellm-rust/crates/python-bridge/src/secrets/config.rs b/litellm-rust/crates/python-bridge/src/secrets/config.rs index d1a1eafd468..7afd06e2373 100644 --- a/litellm-rust/crates/python-bridge/src/secrets/config.rs +++ b/litellm-rust/crates/python-bridge/src/secrets/config.rs @@ -128,9 +128,7 @@ pub(crate) fn read(py: Python<'_>) -> PyResult { .system .is_some_and(|system| system != backend.system()) { - return Err(pyo3::exceptions::PyValueError::new_err( - "native secret manager system does not match configuration", - )); + return Err(super::ManagerError::SystemMismatch.into()); } Ok(SecretManagerSnapshot { client: SecretManagerClient::Native(Box::new(backend)), diff --git a/litellm-rust/crates/python-bridge/src/secrets/error.rs b/litellm-rust/crates/python-bridge/src/secrets/error.rs index 5ccfd0a1554..ca51ee79921 100644 --- a/litellm-rust/crates/python-bridge/src/secrets/error.rs +++ b/litellm-rust/crates/python-bridge/src/secrets/error.rs @@ -1,7 +1,66 @@ use std::fmt; +use litellm_error::Report; use litellm_secrets::Error; -use pyo3::{exceptions::PyBaseException, prelude::*}; +use pyo3::{ + exceptions::{PyBaseException, PyRuntimeError, PyValueError}, + prelude::*, +}; + +/// A secret manager call the bridge rejects, with the text Python's own managers raise. +#[derive(Debug, thiserror::Error)] +pub(crate) enum ManagerError { + #[error("native secret manager must be recreated after fork")] + Forked, + #[error("unknown secret manager system")] + UnknownSystem(#[source] serde_json::Error), + #[error("invalid secret manager settings")] + Settings(#[source] litellm_error::Source), + #[error("native secret manager system does not match configuration")] + SystemMismatch, + #[error("secret manager does not support provider reads")] + ProviderReads, + #[error("invalid timeout")] + Timeout(#[source] std::time::TryFromFloatSecsError), + #[error("No secret found in CyberArk Secret Manager for {0}")] + CyberarkSecretMissing(String), + #[error("Current secret {0} not found")] + CurrentMissing(String), + #[error("Failed to verify new secret {0}")] + ReplacementMissing(String), + #[error("New secret value mismatch")] + ReplacementMismatch, + #[error("native secret manager mutation is unavailable")] + MutationUnsupported, + #[error(transparent)] + Secret(Error), +} + +impl ManagerError { + pub(crate) fn settings(error: impl std::error::Error + Send + Sync + 'static) -> Self { + Self::Settings(litellm_error::Source::new(error)) + } +} + +impl From for PyErr { + fn from(error: ManagerError) -> Self { + let message = Report::new(&error).to_string(); + match error { + ManagerError::Forked => PyRuntimeError::new_err(message), + ManagerError::UnknownSystem(_) + | ManagerError::Settings(_) + | ManagerError::SystemMismatch + | ManagerError::ProviderReads + | ManagerError::Timeout(_) + | ManagerError::CyberarkSecretMissing(_) + | ManagerError::CurrentMissing(_) + | ManagerError::ReplacementMissing(_) + | ManagerError::ReplacementMismatch + | ManagerError::MutationUnsupported + | ManagerError::Secret(_) => PyValueError::new_err(message), + } + } +} #[derive(thiserror::Error)] #[error("Python secret manager failed")] @@ -14,18 +73,23 @@ impl fmt::Debug for PythonSecretError { } pub(super) fn external_error(py: Python<'_>, error: PyErr) -> Error { - Error::ExternalManager(Box::new(PythonSecretError(error.into_value(py)))) + Error::ExternalManager(litellm_error::Source::new(PythonSecretError( + error.into_value(py), + ))) } -pub(super) fn read_error(py: Python<'_>, error: PyErr) -> Error { - Error::ExternalRead(Box::new(PythonSecretError(error.into_value(py)))) +pub(crate) fn read_error(py: Python<'_>, error: PyErr) -> Error { + Error::ExternalRead(litellm_error::Source::new(PythonSecretError( + error.into_value(py), + ))) } -pub(crate) fn python_error(py: Python<'_>, error: &Error) -> Option { - let (Error::ExternalManager(source) | Error::ExternalRead(source)) = error else { - return None; - }; - source - .downcast_ref::() +/// The exception a Python secret manager raised anywhere in the chain, so a route surfaces it +/// unchanged instead of wrapping it. +pub(crate) fn python_error( + py: Python<'_>, + error: &(dyn std::error::Error + 'static), +) -> Option { + litellm_error::find::(error) .map(|error| PyErr::from_value(error.0.clone_ref(py).into_bound(py).into_any())) } diff --git a/litellm-rust/crates/python-bridge/src/secrets/mod.rs b/litellm-rust/crates/python-bridge/src/secrets/mod.rs index cddd47d08db..57042e6a32e 100644 --- a/litellm-rust/crates/python-bridge/src/secrets/mod.rs +++ b/litellm-rust/crates/python-bridge/src/secrets/mod.rs @@ -11,7 +11,9 @@ mod vault; use std::sync::Arc; -pub(crate) use error::python_error; +#[cfg(test)] +pub(crate) use error::read_error; +pub(crate) use error::{ManagerError, python_error}; use litellm_secrets::source::{EnvironmentSecrets, SecretSource}; use pyo3::prelude::*; use python::PythonSecrets; diff --git a/litellm-rust/crates/python-bridge/src/secrets/mutation.rs b/litellm-rust/crates/python-bridge/src/secrets/mutation.rs index eaab06a5b12..b04060651ac 100644 --- a/litellm-rust/crates/python-bridge/src/secrets/mutation.rs +++ b/litellm-rust/crates/python-bridge/src/secrets/mutation.rs @@ -1,7 +1,8 @@ use super::operations::{PythonMutationError, PythonMutationResponse}; +use litellm_error::Report; use litellm_host_python::{json_loads, to_py}; use litellm_secrets::cyberark; -use pyo3::{exceptions::PyValueError, prelude::*, types::PyDict}; +use pyo3::{prelude::*, types::PyDict}; pub(super) fn mutation_value( result: Result, @@ -23,18 +24,7 @@ pub(super) fn mutation_value( &serde_json::json!({"status": "error", "message": message}), ) } - Err(PythonMutationError::CurrentMissing(name)) => Err(PyValueError::new_err(format!( - "Current secret {name} not found" - ))), - Err(PythonMutationError::ReplacementMissing(name)) => Err(PyValueError::new_err(format!( - "Failed to verify new secret {name}" - ))), - Err(PythonMutationError::ReplacementMismatch) => { - Err(PyValueError::new_err("New secret value mismatch")) - } - Err(PythonMutationError::Unsupported) => Err(PyValueError::new_err( - "native secret manager mutation is unavailable", - )), + Err(PythonMutationError::Manager(error)) => Err(error.into()), }) } @@ -43,18 +33,35 @@ fn cyberark_failure( name: &str, failure: cyberark::WriteFailure, ) -> PyResult { - let message = match failure.source { + let message = if failure.source.is_unsafe_secret_name() { + format!("Invalid secret_name {}", name.into_pyobject(py)?.repr()?) + } else { + cyberark_message( + py, + failure.source, + failure.authentication, + failure.request_url.as_ref(), + )? + }; + Ok(if failure.authentication { + format!("Could not authenticate to CyberArk Conjur: {message}") + } else { + message + }) +} + +fn cyberark_message( + py: Python<'_>, + source: cyberark::Error, + authentication: bool, + request_url: Option<&reqwest::Url>, +) -> PyResult { + Ok(match source { cyberark::Error::Status(status) | cyberark::Error::AuthStatus(status) => { - let url = failure - .request_url - .as_ref() - .map_or("", reqwest::Url::as_str); + let url = request_url.map_or("", reqwest::Url::as_str); http_message(py, "POST", url, status)? } - cyberark::Error::Operation(litellm_secrets_types::Error::UnsafeSecretName) => { - format!("Invalid secret_name {}", name.into_pyobject(py)?.repr()?) - } - cyberark::Error::Http(source) if failure.authentication => match os_error_code(&source) { + cyberark::Error::Http(source) if authentication => match os_error_code(&source) { Some(code) => { let reason = py.import("os")?.getattr("strerror")?.call1((code,))?; py.import("builtins")? @@ -63,17 +70,12 @@ fn cyberark_failure( .str()? .extract()? } - None => cyberark::Error::Http(source).to_string(), + None => Report::new(&cyberark::Error::Http(source)).to_string(), }, cyberark::Error::Http(source) if source.is_connect() => { "All connection attempts failed".to_owned() } - source => source.to_string(), - }; - Ok(if failure.authentication { - format!("Could not authenticate to CyberArk Conjur: {message}") - } else { - message + source => Report::new(&source).to_string(), }) } diff --git a/litellm-rust/crates/python-bridge/src/secrets/operations.rs b/litellm-rust/crates/python-bridge/src/secrets/operations.rs index 8e338741aff..b458e3f34e8 100644 --- a/litellm-rust/crates/python-bridge/src/secrets/operations.rs +++ b/litellm-rust/crates/python-bridge/src/secrets/operations.rs @@ -4,6 +4,8 @@ use litellm_secrets::cyberark::AuthenticationRetry; use litellm_secrets::{Error, SecretManager}; use litellm_secrets_types::{PythonSecretRead, SecretOperationContext}; +use super::ManagerError; + pub(super) struct PythonReadRequest { pub secret_name: String, pub primary_secret_name: Option, @@ -62,15 +64,18 @@ pub(super) async fn read_python_provider( #[derive(Debug)] pub(super) enum PythonMutationError { - Unsupported, + Manager(ManagerError), Vault(Box), CyberarkWrite { name: String, failure: Box, }, - CurrentMissing(String), - ReplacementMissing(String), - ReplacementMismatch, +} + +impl From for PythonMutationError { + fn from(error: ManagerError) -> Self { + Self::Manager(error) + } } pub(super) async fn write_python_provider( @@ -89,7 +94,7 @@ pub(super) async fn write_python_provider( })?; Ok(write_success(name)) } - _ => Err(PythonMutationError::Unsupported), + _ => Err(ManagerError::MutationUnsupported.into()), } } @@ -115,7 +120,7 @@ pub(super) async fn delete_python_provider( "message": "CyberArk Conjur does not support direct secret deletion. Use policy updates to remove variables.", })) } - _ => Err(PythonMutationError::Unsupported), + _ => Err(ManagerError::MutationUnsupported.into()), } } @@ -138,7 +143,7 @@ pub(super) async fn rotate_python_provider( .flatten() .is_none() { - return Err(PythonMutationError::CurrentMissing(current_name.to_owned())); + return Err(ManagerError::CurrentMissing(current_name.to_owned()).into()); } client .write_with_retry( @@ -157,16 +162,16 @@ pub(super) async fn rotate_python_provider( .await .ok() .flatten() - .ok_or_else(|| PythonMutationError::ReplacementMissing(new_name.to_owned()))?; + .ok_or_else(|| ManagerError::ReplacementMissing(new_name.to_owned()))?; if actual != *value { - return Err(PythonMutationError::ReplacementMismatch); + return Err(ManagerError::ReplacementMismatch.into()); } if current_name != new_name { client.invalidate_cached_secret(current_name).await; } Ok(write_success(new_name)) } - _ => Err(PythonMutationError::Unsupported), + _ => Err(ManagerError::MutationUnsupported.into()), } } fn write_success(name: &str) -> serde_json::Value { diff --git a/litellm-rust/crates/python-bridge/src/secrets/provider.rs b/litellm-rust/crates/python-bridge/src/secrets/provider.rs index 5f4cd193fcf..ff10f596311 100644 --- a/litellm-rust/crates/python-bridge/src/secrets/provider.rs +++ b/litellm-rust/crates/python-bridge/src/secrets/provider.rs @@ -6,7 +6,9 @@ use litellm_secrets_types::{ AwsOperationContext, CyberarkOperationContext, GoogleOperationContext, HashicorpOperationContext, SecretOperationContext, }; -use pyo3::{exceptions::PyValueError, prelude::*, types::PyDict}; +use pyo3::{prelude::*, types::PyDict}; + +use super::ManagerError; pub(super) fn read_request( system: KeyManagementSystem, @@ -39,9 +41,7 @@ pub(super) fn read_request( SecretOperationContext::Google(GoogleOperationContext::default()) } _ => { - return Err(PyValueError::new_err( - "secret manager does not support provider reads", - )); + return Err(ManagerError::ProviderReads.into()); } }; Ok(PythonReadRequest { @@ -89,9 +89,7 @@ fn aws_context( fn read_timeout(value: Option<&Bound<'_, PyAny>>) -> PyResult> { read_timeout_seconds(value)? - .map(|value| { - Duration::try_from_secs_f64(value).map_err(|_| PyValueError::new_err("invalid timeout")) - }) + .map(|value| Ok(Duration::try_from_secs_f64(value).map_err(ManagerError::Timeout)?)) .transpose() } diff --git a/litellm-rust/crates/python-bridge/src/secrets/resolved.rs b/litellm-rust/crates/python-bridge/src/secrets/resolved.rs index 5a606ab1039..deb07175e7a 100644 --- a/litellm-rust/crates/python-bridge/src/secrets/resolved.rs +++ b/litellm-rust/crates/python-bridge/src/secrets/resolved.rs @@ -84,7 +84,7 @@ mod tests { } async fn resolve(state: Arc, name: &'static str) -> Option { - ResolvedSecrets::from_state(state, litellm_http::Client::plain_for_test()) + ResolvedSecrets::from_state(state, litellm_http::Client::for_test()) .resolve(&[name]) .await .unwrap() @@ -182,7 +182,7 @@ mod tests { .await; let source = ResolvedSecrets::from_state( state(&server, KeyManagementSettings::default()), - litellm_http::Client::plain_for_test(), + litellm_http::Client::for_test(), ); let snapshot = source.resolve(&[declared]).await.unwrap(); assert_eq!(snapshot.get(undeclared), None); @@ -248,7 +248,7 @@ mod tests { async fn oidc_failures_are_not_converted_to_missing_secrets() { let result = ResolvedSecrets::from_state( Arc::new(SecretManagerState::default()), - litellm_http::Client::plain_for_test(), + litellm_http::Client::for_test(), ) .resolve(&["oidc/"]) .await; diff --git a/litellm-rust/crates/python-bridge/src/secrets/runtime.rs b/litellm-rust/crates/python-bridge/src/secrets/runtime.rs index 72ba91ded16..b956ec297b6 100644 --- a/litellm-rust/crates/python-bridge/src/secrets/runtime.rs +++ b/litellm-rust/crates/python-bridge/src/secrets/runtime.rs @@ -7,12 +7,9 @@ use litellm_secrets::{ read_secret_from_python_manager, }; use litellm_secrets_types::PythonSecretRead; -use pyo3::{ - exceptions::{PyAttributeError, PyRuntimeError, PyValueError}, - prelude::*, - types::PyDict, -}; +use pyo3::{exceptions::PyAttributeError, prelude::*, types::PyDict}; +use super::ManagerError; use crate::execution::{run_async_value, run_sync_value}; const SECRET_MANAGER_MODULE: &str = "litellm.rust_bridge.host.secret_manager"; @@ -35,9 +32,7 @@ pub(crate) struct NativeSecretManager { impl NativeSecretManager { pub(super) fn backend(&self) -> PyResult { if self.pid != std::process::id() { - return Err(PyRuntimeError::new_err( - "native secret manager must be recreated after fork", - )); + return Err(ManagerError::Forked.into()); } Ok(self.backend.clone()) } @@ -60,7 +55,7 @@ impl NativeSecretManager { enterprise_enabled, ) .await - .map_err(|error| PyValueError::new_err(error.to_string())) + .map_err(|error| ManagerError::Secret(error).into()) })?; Ok(Self { backend, @@ -82,7 +77,7 @@ impl NativeSecretManager { enterprise_enabled: bool, ) -> PyResult { let system = serde_json::from_value(serde_json::Value::String(system.to_owned())) - .map_err(|_| PyValueError::new_err("unknown secret manager system"))?; + .map_err(ManagerError::UnknownSystem)?; let settings = parse_settings(settings)?; Self::build( py, @@ -146,7 +141,7 @@ impl NativeSecretManager { .collect::>>()?; let settings = from_py::>(&config.getattr("settings")?) - .map_err(|_| PyValueError::new_err("invalid secret manager settings"))?; + .map_err(ManagerError::settings)?; let attributes = config .getattr("settings_attributes")? .extract::>()?; @@ -161,11 +156,11 @@ impl NativeSecretManager { system: serde_json::from_value(serde_json::Value::String( config.getattr("system")?.extract()?, )) - .map_err(|_| PyValueError::new_err("unknown secret manager system"))?, + .map_err(ManagerError::UnknownSystem)?, settings: serde_json::from_value(serde_json::Value::Object( settings.into_iter().chain(setting_overrides).collect(), )) - .map_err(|_| PyValueError::new_err("invalid secret manager settings"))?, + .map_err(ManagerError::settings)?, environment: captured .into_iter() .filter(|(key, _)| !environment_attributes.contains_key(key)) @@ -190,12 +185,8 @@ impl NativeSecretManager { } #[getter] - fn system(&self) -> String { - serde_json::to_value(self.configuration.system) - .expect("serializable system") - .as_str() - .expect("string system") - .to_owned() + fn system(&self) -> &'static str { + self.configuration.system.into() } #[pyo3(signature = (name, settings=None))] @@ -238,7 +229,7 @@ impl NativeSecretManager { run_sync_value(py, async move { super::operations::read_python_provider(&backend, &request, &ProcessEnvironment) .await - .map_err(|error| PyValueError::new_err(error.to_string())) + .map_err(|error| ManagerError::Secret(error).into()) .and_then(|value| python_secret_value(value, &request.secret_name)) }) } @@ -264,7 +255,7 @@ impl NativeSecretManager { run_async_value(py, async move { super::operations::read_python_provider(&backend, &request, &ProcessEnvironment) .await - .map_err(|error| PyValueError::new_err(error.to_string())) + .map_err(|error| ManagerError::Secret(error).into()) .and_then(|value| python_secret_value(value, &request.secret_name)) }) } @@ -438,8 +429,8 @@ fn cached( fn parse_settings(value: Option<&Bound<'_, PyAny>>) -> PyResult { value .map(|value| { - serde_json::from_value(from_py::(value)?) - .map_err(|_| PyValueError::new_err("invalid secret manager settings")) + Ok(serde_json::from_value(from_py::(value)?) + .map_err(ManagerError::settings)?) }) .transpose() .map(Option::unwrap_or_default) @@ -466,11 +457,10 @@ fn python_read_error( name: &str, error: litellm_secrets::Error, ) -> PyErr { - let message = match (system, error) { + match (system, error) { (KeyManagementSystem::Cyberark, litellm_secrets::Error::ManagedSecretMissing) => { - format!("No secret found in CyberArk Secret Manager for {name}") + ManagerError::CyberarkSecretMissing(name.to_owned()).into() } - (_, error) => error.to_string(), - }; - PyValueError::new_err(message) + (_, error) => ManagerError::Secret(error).into(), + } } diff --git a/litellm-rust/crates/python-bridge/src/secrets/vault.rs b/litellm-rust/crates/python-bridge/src/secrets/vault.rs index 79281662848..30e3bd2c413 100644 --- a/litellm-rust/crates/python-bridge/src/secrets/vault.rs +++ b/litellm-rust/crates/python-bridge/src/secrets/vault.rs @@ -2,8 +2,11 @@ mod operation; pub(super) use operation::{Failure, FailureKind, FailureStage, delete, rotate, write}; -use litellm_core_utils::exception_mapping_utils::{TimeoutPhase, timeout_message}; -use litellm_secrets::hashicorp::{Error, RawOperationError}; +use litellm_core_utils::exception_mapping_utils::{ + TimeoutPhase, timeout_message as transport_timeout_message, +}; +use litellm_error::Report; +use litellm_secrets::hashicorp::RawOperationError; use pyo3::prelude::*; use super::mutation::{error_value, http_message, json_value}; @@ -16,40 +19,39 @@ pub(super) fn failure_value( failure: Failure, context: &ErrorContext, ) -> PyResult> { - let message = match *failure.kind { - FailureKind::Native(RawOperationError::Http { - method, - url, - status, - body, - }) => match failure.stage { - FailureStage::Current(name) if status == 404 => { - format!("Current secret {name} not found") + let message = match (&*failure.kind, failure.stage) { + (FailureKind::Native(error), stage) if let Some(response) = error.http_failure() => { + match stage { + FailureStage::Current(name) if response.status == 404 => { + format!("Current secret {name} not found") + } + FailureStage::Replacement(name) if response.status == 404 => { + format!("Failed to verify new secret {name}") + } + FailureStage::Current(_) => format!( + "HTTP error occurred while checking current secret: {}", + response_text(py, &response.body)? + ), + FailureStage::Replacement(_) => format!( + "HTTP error occurred while verifying new secret: {}", + response_text(py, &response.body)? + ), + FailureStage::Mutation => { + http_message(py, &response.method, &response.url, response.status)? + } } - FailureStage::Replacement(name) if status == 404 => { - format!("Failed to verify new secret {name}") - } - FailureStage::Current(_) => format!( - "HTTP error occurred while checking current secret: {}", - response_text(py, &body)? - ), - FailureStage::Replacement(_) => format!( - "HTTP error occurred while verifying new secret: {}", - response_text(py, &body)? - ), - FailureStage::Mutation => http_message(py, &method, &url, status)?, - }, - FailureKind::ValueMismatch { expected, actual } => { - let actual = json_value(py, &actual)?; + } + (FailureKind::ValueMismatch { expected, actual }, _) => { + let actual = json_value(py, actual)?; format!( "New secret value mismatch. Expected: {}, Got: {}", expected.expose(), actual.bind(py).str()? ) } - kind => { + (kind, stage) => { let message = cause_message(py, kind, context)?; - match failure.stage { + match stage { FailureStage::Current(_) => { format!("Error checking current secret: {message}") } @@ -63,86 +65,91 @@ pub(super) fn failure_value( error_value(py, message) } -fn cause_message(py: Python<'_>, kind: FailureKind, context: &ErrorContext) -> PyResult { +fn cause_message(py: Python<'_>, kind: &FailureKind, context: &ErrorContext) -> PyResult { Ok(match kind { - FailureKind::Native(RawOperationError::Local(error)) => error.to_string(), + FailureKind::Native(error) => native_message(py, error, context)?, FailureKind::UnsafeName(name) => { format!("Invalid secret_name {}", name.into_pyobject(py)?.repr()?) } - FailureKind::Native(RawOperationError::Timeout { method, elapsed }) => { - if method == "POST" { - let kwargs = pyo3::types::PyDict::new(py); - kwargs.set_item( - "message", - timeout_message( - TimeoutPhase::Read, - context.timeout, - Some(elapsed.as_secs_f64()), - ), - )?; - kwargs.set_item("model", "default-model-name")?; - kwargs.set_item("llm_provider", "litellm-httpx-handler")?; - py.import("litellm.exceptions")? - .getattr("Timeout")? - .call((), Some(&kwargs))? - .str()? - .extract()? - } else if context.aiohttp { - "Timeout on reading data from socket".to_owned() - } else { - String::new() - } - } - FailureKind::Native(RawOperationError::Transport(source)) => { - if let Some(error) = request_error(&source) { - if error.is_timeout() { - String::new() - } else if error.is_connect() { - "All connection attempts failed".to_owned() - } else { - "HashiCorp Vault request failed".to_owned() - } - } else { - "HashiCorp Vault request failed".to_owned() - } - } FailureKind::MissingGet(value) => { - let value = json_value(py, &value)?; + let value = json_value(py, value)?; match value.bind(py).getattr("get") { Err(error) => error.value(py).str()?.extract()?, Ok(_) => "HashiCorp Vault response payload is malformed".to_owned(), } } - FailureKind::Json(body) => match json_value(py, &body) { + FailureKind::Json(body) => match json_value(py, body) { Err(error) => error.value(py).str()?.extract()?, Ok(_) => "HashiCorp Vault response payload is malformed".to_owned(), }, - FailureKind::Native(RawOperationError::Authentication { - source, - url, - certificate, - }) => { - let message = match source { - Error::LoginStatus { status } => http_message(py, "POST", &url, status)?, - error => error.to_string(), - }; - let mechanism = if certificate { "TLS cert" } else { "AppRole" }; - format!("Could not authenticate to Vault via {mechanism}: {message}") - } - FailureKind::Native(RawOperationError::Http { - method, - url, - status, - .. - }) => http_message(py, &method, &url, status)?, FailureKind::ValueMismatch { .. } => "New secret value mismatch".to_owned(), }) } -fn request_error<'a>(error: &'a (dyn std::error::Error + 'static)) -> Option<&'a reqwest::Error> { - error - .downcast_ref::() - .or_else(|| error.source().and_then(request_error)) +fn native_message( + py: Python<'_>, + error: &RawOperationError, + context: &ErrorContext, +) -> PyResult { + if let Some(error) = error.local() { + return Ok(Report::new(error).to_string()); + } + if let Some((method, elapsed)) = error.timeout() { + return timeout_message(py, method, elapsed, context); + } + if let Some(response) = error.http_failure() { + return http_message(py, &response.method, &response.url, response.status); + } + if let Some(login) = error.authentication() { + let message = match login.source.login_status() { + Some(status) => http_message(py, "POST", login.url, status)?, + None => Report::new(login.source).to_string(), + }; + let mechanism = if login.certificate { + "TLS cert" + } else { + "AppRole" + }; + return Ok(format!( + "Could not authenticate to Vault via {mechanism}: {message}" + )); + } + Ok(match error.transport() { + Some(error) if error.status() == Some(408) => String::new(), + Some(error) if error.is_connect() => "All connection attempts failed".to_owned(), + Some(_) | None => "HashiCorp Vault request failed".to_owned(), + }) +} + +fn timeout_message( + py: Python<'_>, + method: &str, + elapsed: std::time::Duration, + context: &ErrorContext, +) -> PyResult { + if method != "POST" { + return Ok(if context.aiohttp { + "Timeout on reading data from socket".to_owned() + } else { + String::new() + }); + } + let kwargs = pyo3::types::PyDict::new(py); + kwargs.set_item( + "message", + transport_timeout_message( + TimeoutPhase::Read, + context.timeout, + Some(elapsed.as_secs_f64()), + ), + )?; + kwargs.set_item("model", "default-model-name")?; + kwargs.set_item("llm_provider", "litellm-httpx-handler")?; + py.import("litellm.exceptions")? + .getattr("Timeout")? + .call((), Some(&kwargs))? + .str()? + .extract() } fn response_text(py: Python<'_>, body: &[u8]) -> PyResult { diff --git a/litellm-rust/crates/python-bridge/src/secrets/vault/operation.rs b/litellm-rust/crates/python-bridge/src/secrets/vault/operation.rs index cf56beb5efe..41658f0baf8 100644 --- a/litellm-rust/crates/python-bridge/src/secrets/vault/operation.rs +++ b/litellm-rust/crates/python-bridge/src/secrets/vault/operation.rs @@ -2,7 +2,7 @@ use std::collections::HashMap; use litellm_secrets::{ SecretValue, - hashicorp::{Error, HashicorpVault, RawOperationError}, + hashicorp::{HashicorpVault, RawOperationError}, }; use litellm_secrets_types::{HashicorpOperationContext, SecretWriteContext}; use serde_json::value::RawValue; @@ -53,12 +53,10 @@ impl Failure { } fn native_failure(name: &str, error: RawOperationError) -> Failure { - match error { - RawOperationError::Local(Error::InvalidSecretName(_)) => { - FailureKind::UnsafeName(name.to_owned()).into() - } - error => FailureKind::Native(error).into(), + if error.is_unsafe_secret_name() { + return FailureKind::UnsafeName(name.to_owned()).into(); } + FailureKind::Native(error).into() } pub(crate) async fn write( diff --git a/litellm-rust/crates/python-bridge/src/tokenizer.rs b/litellm-rust/crates/python-bridge/src/tokenizer.rs index df219d55eb6..2026b2fdc42 100644 --- a/litellm-rust/crates/python-bridge/src/tokenizer.rs +++ b/litellm-rust/crates/python-bridge/src/tokenizer.rs @@ -8,16 +8,18 @@ use std::sync::Arc; #[cfg(feature = "fast")] use std::sync::OnceLock; +use litellm_error::Report; use litellm_host_python::{enter_native, release_gil}; #[cfg(feature = "fast")] use litellm_token_counter::fast::{FastCounter, FastTokenizer}; use litellm_token_counter::{Error, TextCodec}; use pyo3::{exceptions::PyUnicodeEncodeError, prelude::*, types::PyString}; -#[cfg(any(feature = "tiktoken", feature = "huggingface"))] -use pyo3::exceptions::PyValueError; #[cfg(feature = "huggingface")] -use pyo3::{exceptions::PyIOError, types::PyDict}; +use pyo3::{ + exceptions::{PyIOError, PyTypeError, PyValueError}, + types::PyDict, +}; #[cfg(feature = "tiktoken")] use pyo3::{ exceptions::{PyKeyError, PyRuntimeError}, @@ -51,6 +53,70 @@ pub(crate) fn load_tiktoken(py: Python<'_>, encoding: &str) -> PyResult for PyErr { + fn from(error: TokenizerError) -> Self { + let message = Report::new(&error).to_string(); + match error { + #[cfg(not(all(feature = "tiktoken", feature = "huggingface")))] + TokenizerError::MissingFeature(_) => RustBridgeDeclined::new_err(message), + #[cfg(all(feature = "tiktoken", feature = "huggingface"))] + TokenizerError::NotTiktoken | TokenizerError::NotHuggingFace => { + PyValueError::new_err(message) + } + #[cfg(feature = "tiktoken")] + TokenizerError::NoVocabulary | TokenizerError::EncodeSpecial(_) => { + PyRuntimeError::new_err(message) + } + #[cfg(feature = "tiktoken")] + TokenizerError::DecodeBytes(_) => PyKeyError::new_err(message), + #[cfg(feature = "huggingface")] + TokenizerError::Direction { .. } | TokenizerError::EncodingJson(_) => { + PyValueError::new_err(message) + } + #[cfg(feature = "huggingface")] + TokenizerError::PretokenizedMismatch => PyTypeError::new_err(message), + #[cfg(feature = "huggingface")] + TokenizerError::Download(_) => PyIOError::new_err(message), + } + } +} + pub(crate) enum Codec { #[cfg(feature = "tiktoken")] Tiktoken(TiktokenTokenizer), @@ -100,9 +166,7 @@ impl Tokenizer { #[cfg(not(feature = "tiktoken"))] { let _ = (py, encoding); - Err(RustBridgeDeclined::new_err( - "tokenizer backend requires the tiktoken feature", - )) + Err(TokenizerError::MissingFeature("tiktoken").into()) } } @@ -118,9 +182,7 @@ impl Tokenizer { #[cfg(not(feature = "huggingface"))] { let _ = (py, tokenizer_json); - Err(RustBridgeDeclined::new_err( - "tokenizer backend requires the huggingface feature", - )) + Err(TokenizerError::MissingFeature("huggingface").into()) } } @@ -144,16 +206,14 @@ impl Tokenizer { .getattr("hf_hub_download")? .call((), Some(&kwargs))? .extract()?; - let json = - release_gil(py, || std::fs::read_to_string(path)).map_err(PyIOError::new_err)?; + let json = release_gil(py, || std::fs::read_to_string(path)) + .map_err(TokenizerError::Download)?; Self::from_json(py, &json) } #[cfg(not(feature = "huggingface"))] { let _ = (py, identifier, revision, token); - Err(RustBridgeDeclined::new_err( - "tokenizer backend requires the huggingface feature", - )) + Err(TokenizerError::MissingFeature("huggingface").into()) } } @@ -199,7 +259,7 @@ impl Tokenizer { let tokenizer = self.tiktoken()?; let text = self.text(text)?; release_gil(py, || tokenizer.encode_special(&text, &allowed)) - .map_err(PyRuntimeError::new_err) + .map_err(|error| TokenizerError::EncodeSpecial(error.into()).into()) } /// tiktoken's `encode_with_unstable`: `(stable_tokens, completions)`. @@ -258,8 +318,8 @@ impl Tokenizer { fn decode_bytes<'py>(&self, py: Python<'py>, ids: Vec) -> PyResult> { enter_native()?; let tokenizer = self.tiktoken()?; - let bytes = - release_gil(py, || tokenizer.decode_bytes(&ids)).map_err(PyKeyError::new_err)?; + let bytes = release_gil(py, || tokenizer.decode_bytes(&ids)) + .map_err(|error| TokenizerError::DecodeBytes(error.into()))?; Ok(PyBytes::new(py, &bytes)) } @@ -480,15 +540,16 @@ impl Tokenizer { match *self.inner { Codec::Tiktoken(ref tokenizer) => Ok(tokenizer), #[cfg(feature = "huggingface")] - Codec::HuggingFace(_) => Err(PyValueError::new_err("requires a tiktoken encoding")), + Codec::HuggingFace(_) => Err(TokenizerError::NotTiktoken.into()), } } #[cfg(feature = "tiktoken")] fn vocabulary(&self) -> PyResult<&Vocabulary> { - self.tiktoken()?.vocabulary().ok_or_else(|| { - PyRuntimeError::new_err("this encoding was built without its vocabulary") - }) + Ok(self + .tiktoken()? + .vocabulary() + .ok_or(TokenizerError::NoVocabulary)?) } #[cfg(feature = "huggingface")] @@ -496,7 +557,7 @@ impl Tokenizer { match *self.inner { Codec::HuggingFace(ref tokenizer) => Ok(tokenizer), #[cfg(feature = "tiktoken")] - Codec::Tiktoken(_) => Err(PyValueError::new_err("requires a Hugging Face tokenizer")), + Codec::Tiktoken(_) => Err(TokenizerError::NotHuggingFace.into()), } } } @@ -530,21 +591,21 @@ impl Sequence { match (self, is_pretokenized) { (Self::Text(text), false) => Ok(text.into()), (Self::Words(words), true) => Ok(words.into()), - _ => Err(pyo3::exceptions::PyTypeError::new_err( - "input must match is_pretokenized", - )), + _ => Err(TokenizerError::PretokenizedMismatch.into()), } } } #[cfg(feature = "huggingface")] -fn direction(value: &str, left: T, right: T, what: &str) -> PyResult { +fn direction(value: &str, left: T, right: T, what: &'static str) -> PyResult { match value { "left" => Ok(left), "right" => Ok(right), - other => Err(PyValueError::new_err(format!( - "invalid {what} direction {other:?}: expected 'left' or 'right'" - ))), + other => Err(TokenizerError::Direction { + what, + value: other.to_owned(), + } + .into()), } } @@ -564,7 +625,7 @@ impl HuggingFaceEncoding { fn new(json: Option<&str>) -> PyResult { let inner = match json { Some(json) => encoding_from_json(json) - .map_err(|error| PyValueError::new_err(error.to_string()))?, + .map_err(|error| TokenizerError::EncodingJson(error.into()))?, None => Encoding::default(), }; Ok(Self { inner }) @@ -586,7 +647,7 @@ impl HuggingFaceEncoding { py: Python<'py>, ) -> PyResult<(Bound<'py, pyo3::types::PyType>, (String,))> { let json = encoding_to_json(&self.inner) - .map_err(|error| PyValueError::new_err(error.to_string()))?; + .map_err(|error| TokenizerError::EncodingJson(error.into()))?; Ok((py.get_type::(), (json,))) } diff --git a/litellm-rust/crates/python-compat/src/error.rs b/litellm-rust/crates/python-compat/src/error.rs index 43990eb7602..6547907056e 100644 --- a/litellm-rust/crates/python-compat/src/error.rs +++ b/litellm-rust/crates/python-compat/src/error.rs @@ -10,15 +10,17 @@ pub enum Error { Unhashable(&'static str), #[error("value nests deeper than {MAX_DEPTH} levels")] TooDeep, - #[error("invalid pickle: {0}")] - InvalidPickle(String), + #[error("invalid pickle")] + InvalidPickle(#[source] serde_pickle::Error), + #[error("could not write pickle")] + PickleWrite(#[source] serde_pickle::Error), #[error("Object of type {0} is not JSON serializable")] NotJsonSerializable(&'static str), #[error("keys must be str, int, float, bool or None, not {0}")] InvalidJsonKey(&'static str), #[error("Out of range float values are not JSON compliant")] NonFiniteFloat, - #[error("integer does not fit in the JSON number range")] + #[error("integer does not fit in 64 bits")] IntegerOutOfRange, #[error("Object of type {0} cannot be pickled as plain data")] NotPicklable(&'static str), diff --git a/litellm-rust/crates/python-compat/src/literal.rs b/litellm-rust/crates/python-compat/src/literal.rs index 12e9036572f..336c6dfcb2e 100644 --- a/litellm-rust/crates/python-compat/src/literal.rs +++ b/litellm-rust/crates/python-compat/src/literal.rs @@ -58,13 +58,6 @@ impl Term { kind: Kind::Other, } } - - fn is_number(&self) -> bool { - matches!( - self.value, - Value::Int(_) | Value::Float(_) | Value::Complex { .. } - ) - } } struct Parser<'a> { @@ -204,18 +197,25 @@ impl Parser<'_> { self.enter()?; let operand = self.unary()?; self.depth -= 1; - if operand.kind != Kind::Constant || !operand.is_number() { + if operand.kind != Kind::Constant { return Err(Error::InvalidLiteral(self.offset + at)); } - let value = if !negative { - operand.value - } else { - match operand.value { - Value::Int(value) => Value::Int(-value), - Value::Float(value) => Value::Float(-value), - Value::Complex { re, im } => Value::Complex { re: -re, im: -im }, - _ => unreachable!("checked numeric above"), - } + let value = match (operand.value, negative) { + (value @ (Value::Int(_) | Value::Float(_) | Value::Complex { .. }), false) => value, + (Value::Int(value), true) => Value::Int(-value), + (Value::Float(value), true) => Value::Float(-value), + (Value::Complex { re, im }, true) => Value::Complex { re: -re, im: -im }, + ( + Value::None + | Value::Bool(_) + | Value::Str(_) + | Value::Bytes(_) + | Value::List(_) + | Value::Tuple(_) + | Value::Dict(_) + | Value::Set(_), + _, + ) => return Err(Error::InvalidLiteral(self.offset + at)), }; Ok(Term { value, diff --git a/litellm-rust/crates/python-compat/src/pickle.rs b/litellm-rust/crates/python-compat/src/pickle.rs index bff7442dc6b..dd7ac6a0e4f 100644 --- a/litellm-rust/crates/python-compat/src/pickle.rs +++ b/litellm-rust/crates/python-compat/src/pickle.rs @@ -22,10 +22,8 @@ pub fn loads(data: &[u8]) -> Result { let mut deserializer = serde_pickle::Deserializer::new(data, DeOptions::new()); let value = Seed { depth: 0 } .deserialize(&mut deserializer) - .map_err(|error| Error::InvalidPickle(error.to_string()))?; - deserializer - .end() - .map_err(|error| Error::InvalidPickle(error.to_string()))?; + .map_err(Error::InvalidPickle)?; + deserializer.end().map_err(Error::InvalidPickle)?; Ok(value) } @@ -33,8 +31,7 @@ pub fn loads(data: &[u8]) -> Result { /// default. Sets and complex numbers are rejected rather than silently changing type. pub fn dumps(value: &Value) -> Result, Error> { check_picklable(value, 0)?; - serde_pickle::to_vec(&Pickled(value), SerOptions::new()) - .map_err(|error| Error::InvalidPickle(error.to_string())) + serde_pickle::to_vec(&Pickled(value), SerOptions::new()).map_err(Error::PickleWrite) } fn check_picklable(value: &Value, depth: usize) -> Result<(), Error> { @@ -66,7 +63,7 @@ impl Serialize for Pickled<'_> { Value::Bool(value) => serializer.serialize_bool(*value), Value::Int(value) => { let value = i64::try_from(value) - .map_err(|_| serde::ser::Error::custom("integer out of i64 range"))?; + .map_err(|_| serde::ser::Error::custom(Error::IntegerOutOfRange))?; serializer.serialize_i64(value) } Value::Float(value) => serializer.serialize_f64(*value), @@ -94,7 +91,7 @@ impl Serialize for Pickled<'_> { map.end() } value @ (Value::Set(_) | Value::Complex { .. }) => Err(serde::ser::Error::custom( - format!("{} cannot be pickled as plain data", value.type_name()), + Error::NotPicklable(value.type_name()), )), } } diff --git a/litellm-rust/crates/router-core/Cargo.toml b/litellm-rust/crates/router-core/Cargo.toml new file mode 100644 index 00000000000..af97bd52c57 --- /dev/null +++ b/litellm-rust/crates/router-core/Cargo.toml @@ -0,0 +1,9 @@ +[package] +name = "litellm-router-core" +version = "0.1.0" +edition.workspace = true +license.workspace = true +repository.workspace = true +description = "The router core behind litellm.Router: registry, settings, health, selection and the call loop" + +[dependencies] diff --git a/litellm-rust/crates/router-core/src/lib.rs b/litellm-rust/crates/router-core/src/lib.rs new file mode 100644 index 00000000000..05d95d02c84 --- /dev/null +++ b/litellm-rust/crates/router-core/src/lib.rs @@ -0,0 +1,63 @@ +//! Routing for LiteLLM: decide which deployment serves a request, and drive retries, fallbacks +//! and cooldowns around the attempts. +//! +//! This crate defines the boundary `litellm.Router` is moving behind. Today the Python router in +//! `litellm/router.py` implements all of it; this crate is where the Rust core will implement the +//! same interface. Until then it holds this overview and nothing else, so the interface is written +//! down in code before either side changes. +//! +//! # The public surface +//! Code outside the router uses `litellm.Router` through two kinds of members and nothing else: +//! - The endpoint methods (`acompletion`, `aembedding`, `aresponses`, `aanthropic_messages`, the +//! files, batches, assistants and vector store wrappers, 37 in all). Each is a thin wrapper over +//! `call(op, request)`. +//! - Eight entry points: `registry()`, `settings()`, `health()`, `select()`, `apply()`, +//! `observe()`, `register_plugin()` and `retire()`. +//! +//! Every other member that outside code uses today has a named replacement among those. The old +//! names stay available for about a month through a `DeprecatedRouterMembers` mixin, which +//! implements them over the entry points and warns on use. A CI check +//! (`tests/code_coverage_tests/router_surface_check.py`) keeps an allowlist of the members outside +//! code touches; the list may only shrink. +//! +//! # Structure +//! - `Registry`: the configured deployments, indexed by id, model group, alias, wildcard pattern +//! and team. Immutable and versioned. Seven queries: `deployment(id)`, `deployments(filter)`, +//! `names(filter)`, `resolve(name, scope)`, `group(name)`, `access_groups()` and +//! `credentials(id)`. "Registry" is the router's view of what is configured; per-model pricing +//! and capabilities are the model catalog (`litellm-model-catalog`), which the router reads +//! through its dynamic config. +//! - `RouterConfig` / `RouterDynamicConfig`: everything the router needs to know, passed in. The +//! router never reads process globals. Static config (model list, strategy, retry, timeout and +//! cooldown policy, Redis settings, plugins) is fixed for the router's life. Dynamic config +//! (pricing, model aliases, fallbacks, retry counts, callbacks) is a versioned snapshot read +//! once per call. +//! - `Settings`: one typed, frozen view of the configuration a caller may read. +//! - `Health`: cooldowns, blocked deployments and usage, kept in shared cache keys so Python and +//! Rust workers see the same state. `report(id, outcome)` records outcomes the router did not +//! see itself (a health check, an interceptor that marks a deployment failed). +//! - `select(model, request)`: resolve a name, filter eligible deployments, pick one with the +//! configured strategy, without calling it. +//! - `apply(changes)`: one `ChangeSet` (upserts, deletes, settings), applied atomically, producing +//! a new registry version. +//! - `call(op, request)`: select, run the attempt, and retry or fall back until it succeeds or the +//! policy is exhausted. +//! +//! # Execution +//! Each attempt resolves an `Executor` after a deployment is picked. A Rust-native operation runs +//! its `inference-*` route machine in-process; anything else goes through `Host::invoke`. A +//! started attempt is never replayed on a different executor. +//! +//! # Hosts +//! `Host` is what the embedding process provides: `invoke` for non-native operations, `select` +//! for strategies and sub-routers not yet ported, `allow_fallback` for access and budget checks, +//! `sleep`, `observe` for routing events, and `cache`, a DualCache-style store that holds all +//! routing state under the same keys, encodings and TTLs the Python router uses. `PythonHost` +//! serves them from the existing Python code when the router runs inside Python; `NativeHost` +//! serves them in the Rust server, where an operation without a Rust implementation makes the +//! config fail at build time, never partway through a request. +//! +//! # Plugins +//! Routing strategies, pre-call checks and sub-routers (auto, complexity, quality, adaptive) +//! register through `register_plugin` and see a `RoutingContext` (registry, settings, health and +//! the current request), never the router itself. diff --git a/litellm-rust/crates/router/Cargo.toml b/litellm-rust/crates/router/Cargo.toml index a356bedcf16..988d1b68805 100644 --- a/litellm-rust/crates/router/Cargo.toml +++ b/litellm-rust/crates/router/Cargo.toml @@ -7,6 +7,7 @@ repository.workspace = true [dependencies] litellm-config.workspace = true +litellm-core-utils.workspace = true litellm-inference.workspace = true litellm-inference-messages.workspace = true litellm-router-types.workspace = true diff --git a/litellm-rust/crates/router/README.md b/litellm-rust/crates/router/README.md index 972d37d14be..a734e634104 100644 --- a/litellm-rust/crates/router/README.md +++ b/litellm-rust/crates/router/README.md @@ -1,4 +1,4 @@ -`litellm-router` scaffolds the model-list setup and deployment lookup portion of Python's `litellm.Router`. `Router::from_model_list(&config.model_list)` maps configured public names to provider deployments. Programmatic callers can collect `(String, Deployment)` entries into a `Router` +`litellm-router` scaffolds the model-list setup and deployment lookup portion of Python's `litellm.Router`. `Router::from_config(&config, &env)` maps configured public names to provider deployments and reads `drop_params` from `litellm_settings` and each deployment, resolving an `os.environ/NAME` value through `env`. Programmatic callers can collect `(String, Deployment)` entries into a `Router` Lookup is exact and returns `None` for an unknown name. This extraction preserves the gateway's existing behavior: the last entry wins when public names repeat. Multiple deployments per model group, routing strategies, retries, cooldowns, and fallbacks are not implemented yet diff --git a/litellm-rust/crates/router/src/lib.rs b/litellm-rust/crates/router/src/lib.rs index fb48213e8a7..b75c1a14446 100644 --- a/litellm-rust/crates/router/src/lib.rs +++ b/litellm-rust/crates/router/src/lib.rs @@ -2,16 +2,33 @@ mod deployment; use std::collections::HashMap; -use litellm_config::Model; +use litellm_config::{Config, Spelled}; +use litellm_core_utils::{serde_compat::parse_pydantic_bool, settings::Lookup}; +use litellm_inference_messages::{MessagesSettings, MessagesShaping}; pub use deployment::Deployment; #[derive(Clone, Debug, Default)] pub struct Router(HashMap); +fn is_on(flag: Option<&Spelled>, env: &impl Lookup) -> bool { + match flag { + Some(Spelled::Value(on)) => *on, + Some(Spelled::Text(text)) => match text.strip_prefix("os.environ/") { + Some(name) => env + .get(name) + .is_some_and(|value| parse_pydantic_bool(&value) == Some(true)), + None => parse_pydantic_bool(text) == Some(true), + }, + None => false, + } +} + impl Router { - pub fn from_model_list(model_list: &[Model]) -> Self { - model_list + pub fn from_config(config: &Config, env: &impl Lookup) -> Self { + let drops_params_globally = is_on(config.litellm_settings.drop_params.as_ref(), env); + config + .model_list .iter() .map(|model| { ( @@ -26,6 +43,14 @@ impl Router { api_base: model.litellm_params.api_base.clone(), custom_llm_provider: model.litellm_params.custom_llm_provider.clone(), litellm_params: model.litellm_params.clone(), + shaping: MessagesShaping { + settings: MessagesSettings { + drop_params: drops_params_globally + || is_on(model.litellm_params.drop_params.as_ref(), env), + ..MessagesSettings::default() + }, + ..MessagesShaping::default() + }, ..Deployment::default() }, ) @@ -43,3 +68,60 @@ impl FromIterator<(String, Deployment)> for Router { Self(entries.into_iter().collect()) } } + +#[cfg(test)] +mod tests { + use litellm_config::Config; + use rstest::rstest; + + use super::Router; + + #[rstest] + #[case::unset("", "", false)] + #[case::deployment_flag("", "\n drop_params: true", true)] + #[case::deployment_word("", "\n drop_params: \" True \"", true)] + #[case::deployment_off("", "\n drop_params: false", false)] + #[case::deployment_unknown_word("", "\n drop_params: maybe", false)] + #[case::deployment_yes("", "\n drop_params: yes", true)] + #[case::deployment_no("", "\n drop_params: \"no\"", false)] + #[case::deployment_env_reference("", "\n drop_params: os.environ/DROP_PARAMS_FLAG", true)] + #[case::deployment_unset_env_reference( + "", + "\n drop_params: os.environ/MISSING_FLAG", + false + )] + #[case::global_env_reference( + "litellm_settings:\n drop_params: os.environ/DROP_PARAMS_FLAG\n", + "", + true + )] + #[case::global_flag("litellm_settings:\n drop_params: true\n", "", true)] + #[case::global_word("litellm_settings:\n drop_params: \"true\"\n", "", true)] + #[case::global_off("litellm_settings:\n drop_params: false\n", "", false)] + #[case::global_over_deployment_off( + "litellm_settings:\n drop_params: true\n", + "\n drop_params: false", + true + )] + fn configured_drop_params_reach_the_deployment( + #[case] settings: &str, + #[case] deployment: &str, + #[case] expected: bool, + ) { + let config = Config::from_yaml(&format!( + "{settings}model_list:\n - model_name: public-model\n litellm_params:\n model: provider/model{deployment}" + )) + .unwrap(); + + assert_eq!( + Router::from_config(&config, &|name: &str| (name == "DROP_PARAMS_FLAG") + .then(|| " Yes ".to_owned())) + .get("public-model") + .unwrap() + .shaping + .settings + .drop_params, + expected + ); + } +} diff --git a/litellm-rust/crates/router/tests/router.rs b/litellm-rust/crates/router/tests/router.rs index bbaeb806b96..03e78ab9d11 100644 --- a/litellm-rust/crates/router/tests/router.rs +++ b/litellm-rust/crates/router/tests/router.rs @@ -16,7 +16,7 @@ fn configuration_preserves_deployment_parameters(#[case] parameters: &str) { "model_list:\n - model_name: public-model\n litellm_params:\n model: provider/model\n {parameters}" )) .unwrap(); - let router = Router::from_model_list(&config.model_list); + let router = Router::from_config(&config, &|_: &str| None); let deployment = router.get(&config.model_list[0].model_name).unwrap(); let params = &config.model_list[0].litellm_params; @@ -44,7 +44,7 @@ fn configuration_types_the_provider_params_of_a_deployment() { azure_ad_token: ignored-by-every-group", ) .unwrap(); - let router = Router::from_model_list(&config.model_list); + let router = Router::from_config(&config, &|_: &str| None); let params = &router.get("public-model").unwrap().litellm_params; assert_eq!( @@ -74,7 +74,7 @@ fn lookup_uses_public_names(#[case] name: &str, #[case] expected: Option<&str>) model: provider/b", ) .unwrap(); - let router = Router::from_model_list(&config.model_list); + let router = Router::from_config(&config, &|_: &str| None); assert_eq!(router.get(name).map(|entry| entry.model.as_str()), expected); } @@ -84,7 +84,7 @@ fn empty_configuration_has_no_deployment() { let config = Config::from_yaml("model_list: []").unwrap(); assert!( - Router::from_model_list(&config.model_list) + Router::from_config(&config, &|_: &str| None) .get("") .is_none() ); diff --git a/litellm-rust/crates/secrets-aws/src/auth.rs b/litellm-rust/crates/secrets-aws/src/auth.rs index 06019cc3c9d..66f4f51bda9 100644 --- a/litellm-rust/crates/secrets-aws/src/auth.rs +++ b/litellm-rust/crates/secrets-aws/src/auth.rs @@ -79,9 +79,7 @@ impl ProvideCredentials for Credentials { self.auth .resolve_credentials(self.config.clone(), &|name| self.environment.get(name)) .await - .map_err(|_| { - CredentialsError::provider_error("secret manager authentication failed") - }) + .map_err(CredentialsError::provider_error) }) } } diff --git a/litellm-rust/crates/secrets-aws/src/error.rs b/litellm-rust/crates/secrets-aws/src/error.rs index c8ca671e9b5..c537da204dd 100644 --- a/litellm-rust/crates/secrets-aws/src/error.rs +++ b/litellm-rust/crates/secrets-aws/src/error.rs @@ -11,7 +11,7 @@ pub enum Error { #[error("KMS response has no plaintext")] MissingPlaintext, #[error("AWS request timed out")] - Timeout, + Timeout(#[source] #[redact] Box>), #[error("AWS KMS decrypt failed")] Decrypt(#[from] #[redact] Box>), #[error("AWS Secrets Manager read failed")] @@ -33,7 +33,7 @@ pub enum Error { #[error("AWS Secrets Manager response has no string payload")] MissingString, #[error("primary secret is not a JSON object")] - PrimarySecret, + PrimarySecret(#[source] #[redact] Option), #[error(transparent)] Operation(#[from] litellm_secrets_types::Error), } diff --git a/litellm-rust/crates/secrets-aws/src/secret_manager/read.rs b/litellm-rust/crates/secrets-aws/src/secret_manager/read.rs index b7583f9785f..d7f10a9847e 100644 --- a/litellm-rust/crates/secrets-aws/src/secret_manager/read.rs +++ b/litellm-rust/crates/secrets-aws/src/secret_manager/read.rs @@ -72,7 +72,7 @@ impl AwsSecretsManagerV2 { } let client = self.client_for_context(context)?; let value = match Self::read_with_client(&client, name, ReadPolicy::Python).await { - Err(Error::Read(_) | Error::MissingString | Error::Timeout) => None, + Err(Error::Read(_) | Error::MissingString | Error::Timeout(_)) => None, result => result?, }; Ok(PythonSecretRead::Value(value.map(Secret::String))) @@ -124,9 +124,10 @@ impl AwsSecretsManagerV2 { Self::read_with_client(&self.client, name, policy).await, policy, ) { - (Err(Error::Read(_) | Error::MissingString | Error::Timeout), ReadPolicy::Python) => { - Ok(None) - } + ( + Err(Error::Read(_) | Error::MissingString | Error::Timeout(_)), + ReadPolicy::Python, + ) => Ok(None), (result, _) => result, } } @@ -173,7 +174,7 @@ impl AwsSecretsManagerV2 { aws_sdk_secretsmanager::error::SdkError::TimeoutError(_) ) || matches!(&error, aws_sdk_secretsmanager::error::SdkError::DispatchFailure(failure) if failure.is_timeout()) => { - Err(Error::Timeout) + Err(Error::Timeout(Box::new(error))) } Err(error) if error @@ -216,9 +217,9 @@ fn resolve_payload(payload: PythonSecretRead, name: &str) -> Result Ok(value), PythonSecretRead::PrimaryJson(document) => { - let object: Value = - serde_json::from_str(document.expose()).map_err(|_| Error::PrimarySecret)?; - let object = object.as_object().ok_or(Error::PrimarySecret)?; + let object: Value = serde_json::from_str(document.expose()) + .map_err(|error| Error::PrimarySecret(Some(error)))?; + let object = object.as_object().ok_or(Error::PrimarySecret(None))?; Ok(object.get(name).cloned().map(Secret::from_json)) } } diff --git a/litellm-rust/crates/secrets-aws/tests/secret_manager/reads.rs b/litellm-rust/crates/secrets-aws/tests/secret_manager/reads.rs index 3c39924f09f..30aec467543 100644 --- a/litellm-rust/crates/secrets-aws/tests/secret_manager/reads.rs +++ b/litellm-rust/crates/secrets-aws/tests/secret_manager/reads.rs @@ -88,7 +88,7 @@ async fn failed_read_returns_none_but_invalid_primary_json_is_an_error( manager .read_secret_for_resolver("KEY", Some("invalid"), &|_: &str| None) .await, - Err(Error::PrimarySecret) + Err(Error::PrimarySecret(_)) )); assert!(matches!( manager.async_read_secret("no-string").await, @@ -143,7 +143,7 @@ async fn trait_read_applies_the_aws_operation_timeout() { }; assert!(matches!( BaseSecretManager::async_read_secret(&loaded_manager(&server), "key", &context).await, - Err(Error::Timeout) + Err(Error::Timeout(_)) )); } @@ -169,7 +169,7 @@ async fn read_timeout_is_an_error_and_cannot_be_mistaken_for_missing() { let manager = AwsSecretsManagerV2::new(Client::from_conf(config), Default::default()); assert!(matches!( manager.async_read_secret("key").await, - Err(Error::Timeout) + Err(Error::Timeout(_)) )); } diff --git a/litellm-rust/crates/secrets-azure/Cargo.toml b/litellm-rust/crates/secrets-azure/Cargo.toml index 7ec03fb98da..2aff6129c37 100644 --- a/litellm-rust/crates/secrets-azure/Cargo.toml +++ b/litellm-rust/crates/secrets-azure/Cargo.toml @@ -15,6 +15,7 @@ litellm-core-utils.workspace = true reqwest.workspace = true serde.workspace = true thiserror.workspace = true +url.workspace = true veil.workspace = true percent-encoding = "2.3" diff --git a/litellm-rust/crates/secrets-azure/src/error.rs b/litellm-rust/crates/secrets-azure/src/error.rs index 2862f08a56c..097f42cb89c 100644 --- a/litellm-rust/crates/secrets-azure/src/error.rs +++ b/litellm-rust/crates/secrets-azure/src/error.rs @@ -7,7 +7,7 @@ pub enum Error { #[error("{0} environment variable is missing")] MissingEnvironment(&'static str), #[error("AZURE_KEY_VAULT_URI is not a valid https vault URL")] - VaultUri, + VaultUri(#[source] Option), #[error("Azure Key Vault credentials are not configured")] MissingCredentials, #[error(transparent)] @@ -20,10 +20,26 @@ pub enum Error { Http( #[source] #[redact] - reqwest::Error, + litellm_http::Error, ), #[error("Azure Key Vault returned HTTP {0}")] Status(u16), #[error("Azure Key Vault response is missing the secret value")] MissingValue, } + +impl Error { + pub fn is_missing_value(&self) -> bool { + match self { + Self::MissingValue => true, + Self::Operation(_) + | Self::Timeout + | Self::MissingEnvironment(_) + | Self::VaultUri(_) + | Self::MissingCredentials + | Self::Auth(_) + | Self::Http(_) + | Self::Status(_) => false, + } + } +} diff --git a/litellm-rust/crates/secrets-azure/src/key_vault.rs b/litellm-rust/crates/secrets-azure/src/key_vault.rs index 095c451927c..d97b7a22cfc 100644 --- a/litellm-rust/crates/secrets-azure/src/key_vault.rs +++ b/litellm-rust/crates/secrets-azure/src/key_vault.rs @@ -38,7 +38,7 @@ impl AzureKeyVault { environment: Arc, ) -> Result { if vault.host_str().is_none() { - return Err(Error::VaultUri); + return Err(Error::VaultUri(None)); } let inputs = AzureAuthInputs { azure_scope: ConfigValue::Value(Sourced::new( @@ -64,9 +64,9 @@ impl AzureKeyVault { let value = environment .get(AZURE_KEY_VAULT_URI) .ok_or(Error::MissingEnvironment(AZURE_KEY_VAULT_URI))?; - let vault = reqwest::Url::parse(&value).map_err(|_| Error::VaultUri)?; + let vault = reqwest::Url::parse(&value).map_err(|error| Error::VaultUri(Some(error)))?; if vault.scheme() != "https" || vault.host_str().is_none() { - return Err(Error::VaultUri); + return Err(Error::VaultUri(None)); } Self::with_client(client, vault, environment) } @@ -95,7 +95,7 @@ impl AzureKeyVault { let url = self .vault .join(&format!("secrets/{encoded_name}?api-version={API_VERSION}")) - .map_err(|_| Error::VaultUri)?; + .map_err(|error| Error::VaultUri(Some(error)))?; let response = self .client .get(url) @@ -103,14 +103,17 @@ impl AzureKeyVault { .header(reqwest::header::ACCEPT, "application/json") .send() .await - .map_err(Error::Http)?; + .map_err(|error| Error::Http(error.into()))?; if response.status() == reqwest::StatusCode::NOT_FOUND { return Ok(None); } if response.status() != reqwest::StatusCode::OK { return Err(Error::Status(response.status().as_u16())); } - let payload: SecretResponse = response.json().await.map_err(Error::Http)?; + let payload: SecretResponse = response + .json() + .await + .map_err(|error| Error::Http(error.into()))?; let value = payload.value.ok_or(Error::MissingValue)?; Ok(Some(SecretValue::new(value))) } diff --git a/litellm-rust/crates/secrets-azure/tests/key_vault.rs b/litellm-rust/crates/secrets-azure/tests/key_vault.rs index fcbc46092e1..a0ba9e6ddf8 100644 --- a/litellm-rust/crates/secrets-azure/tests/key_vault.rs +++ b/litellm-rust/crates/secrets-azure/tests/key_vault.rs @@ -11,7 +11,7 @@ use wiremock::{ fn manager(server: &MockServer) -> AzureKeyVault { AzureKeyVault::with_client( - litellm_http::Client::plain_for_test(), + litellm_http::Client::for_test(), server.uri().parse().unwrap(), Arc::new(|name: &str| (name == "AZURE_AD_TOKEN").then(|| "fake".to_owned())), ) @@ -122,16 +122,17 @@ async fn missing_value_is_an_error() { } #[rstest] -#[case::missing(None, true)] -#[case::http(Some("http://vault.example"), false)] -#[case::relative(Some("vault.example"), false)] -#[case::malformed(Some("://"), false)] +#[case::missing(None, true, false)] +#[case::http(Some("http://vault.example"), false, false)] +#[case::relative(Some("vault.example"), false, true)] +#[case::malformed(Some("://"), false, true)] fn new_validates_vault_environment( #[case] uri: Option<&'static str>, #[case] missing_environment: bool, + #[case] unparsable: bool, ) { let result = AzureKeyVault::new( - litellm_http::Client::plain_for_test(), + litellm_http::Client::for_test(), Arc::new(move |name: &str| { (name == "AZURE_KEY_VAULT_URI") .then(|| uri.map(str::to_owned)) @@ -145,7 +146,14 @@ fn new_validates_vault_environment( Err(Error::MissingEnvironment("AZURE_KEY_VAULT_URI")) )); } else { - assert!(matches!(result, Err(Error::VaultUri))); + let error = result.err().expect("invalid vault URI"); + assert!(matches!(error, Error::VaultUri(_))); + assert_eq!( + std::error::Error::source(&error) + .and_then(|cause| cause.downcast_ref::()) + .is_some(), + unparsable + ); } } @@ -158,7 +166,7 @@ fn new_validates_vault_environment( #[case::local("http://localhost:8080", "https://localhost/.default")] fn derives_scope_from_vault_host(#[case] uri: &str, #[case] expected: &str) { let manager = AzureKeyVault::with_client( - litellm_http::Client::plain_for_test(), + litellm_http::Client::for_test(), uri.parse().unwrap(), Arc::new(|_: &str| None), ) @@ -187,7 +195,7 @@ async fn missing_credentials_do_not_request_vault() { fn manager_without_credentials(server: &MockServer) -> AzureKeyVault { AzureKeyVault::with_client( - litellm_http::Client::plain_for_test(), + litellm_http::Client::for_test(), server.uri().parse().unwrap(), Arc::new(|name: &str| { (name == "AZURE_CREDENTIAL").then(|| "ClientSecretCredential".to_owned()) diff --git a/litellm-rust/crates/secrets-azure/tests/live.rs b/litellm-rust/crates/secrets-azure/tests/live.rs index 429cd3013f7..d7713dc798d 100644 --- a/litellm-rust/crates/secrets-azure/tests/live.rs +++ b/litellm-rust/crates/secrets-azure/tests/live.rs @@ -10,7 +10,7 @@ use rstest::rstest; #[ignore] async fn reads_a_real_secret() { let environment = Arc::new(ProcessEnvironment); - let manager = AzureKeyVault::new(litellm_http::Client::plain_for_test(), environment).unwrap(); + let manager = AzureKeyVault::new(litellm_http::Client::for_test(), environment).unwrap(); let name = std::env::var("AZURE_KEY_VAULT_LIVE_SECRET_NAME").unwrap(); let secret = manager.get_secret(&name).await.unwrap().unwrap(); assert!(matches!(&secret, Secret::String(_))); diff --git a/litellm-rust/crates/secrets-cyberark/Cargo.toml b/litellm-rust/crates/secrets-cyberark/Cargo.toml index f630d5857d8..2ae2c1ea5c3 100644 --- a/litellm-rust/crates/secrets-cyberark/Cargo.toml +++ b/litellm-rust/crates/secrets-cyberark/Cargo.toml @@ -14,6 +14,7 @@ moka.workspace = true reqwest.workspace = true serde_json.workspace = true thiserror.workspace = true +url.workspace = true veil.workspace = true litellm-tracing.workspace = true percent-encoding = "2.3" diff --git a/litellm-rust/crates/secrets-cyberark/src/error.rs b/litellm-rust/crates/secrets-cyberark/src/error.rs index 4f21647225b..b5dbd7342fa 100644 --- a/litellm-rust/crates/secrets-cyberark/src/error.rs +++ b/litellm-rust/crates/secrets-cyberark/src/error.rs @@ -6,7 +6,7 @@ pub enum Error { Http( #[from] #[redact] - reqwest::Error, + litellm_http::Error, ), #[error("CyberArk Conjur authentication returned HTTP {0}")] AuthStatus(u16), @@ -17,15 +17,68 @@ pub enum Error { )] MissingCredentials, #[error("CyberArk client certificate could not be loaded")] - ClientCertificate, + ClientCertificate( + #[source] + #[redact] + litellm_http::Error, + ), #[error("CyberArk Conjur HTTP client could not be built")] - Client(#[redact] Box), + Client( + #[source] + #[redact] + litellm_http::Error, + ), #[error("invalid refresh interval")] - RefreshInterval, + RefreshInterval(#[source] std::num::ParseIntError), #[error("invalid CyberArk Conjur endpoint")] - Endpoint, + Endpoint(#[source] url::ParseError), #[error("CyberArk secret manager requires an enterprise license")] EnterpriseRequired, #[error(transparent)] Operation(#[from] litellm_secrets_types::Error), } + +impl Error { + pub fn is_unsafe_secret_name(&self) -> bool { + match self { + Self::Operation(error) => error.is_unsafe_secret_name(), + Self::Timeout + | Self::Http(_) + | Self::AuthStatus(_) + | Self::Status(_) + | Self::MissingCredentials + | Self::ClientCertificate(_) + | Self::Client(_) + | Self::RefreshInterval(_) + | Self::Endpoint(_) + | Self::EnterpriseRequired => false, + } + } +} + +#[derive(thiserror::Error, veil::Redact)] +#[error("CyberArk Conjur write failed")] +pub struct WriteFailure { + pub source: Error, + #[redact] + pub request_url: Option, + pub authentication: bool, +} + +impl WriteFailure { + pub(crate) fn local(source: Error) -> Self { + Self { + source, + request_url: None, + authentication: false, + } + } + + pub(crate) fn request(source: Error, url: reqwest::Url) -> Self { + Self { + source, + request_url: Some(url), + authentication: false, + } + } +} diff --git a/litellm-rust/crates/secrets-cyberark/src/lib.rs b/litellm-rust/crates/secrets-cyberark/src/lib.rs index 74a8b6febf2..d780fb43921 100644 --- a/litellm-rust/crates/secrets-cyberark/src/lib.rs +++ b/litellm-rust/crates/secrets-cyberark/src/lib.rs @@ -3,5 +3,5 @@ mod error; mod secret_manager; -pub use error::Error; -pub use secret_manager::{AuthenticationRetry, CyberArkSecretManager, DeleteOutcome, WriteFailure}; +pub use error::{Error, WriteFailure}; +pub use secret_manager::{AuthenticationRetry, CyberArkSecretManager, DeleteOutcome}; diff --git a/litellm-rust/crates/secrets-cyberark/src/secret_manager.rs b/litellm-rust/crates/secrets-cyberark/src/secret_manager.rs index 44473c9fe90..c5cb0308b13 100644 --- a/litellm-rust/crates/secrets-cyberark/src/secret_manager.rs +++ b/litellm-rust/crates/secrets-cyberark/src/secret_manager.rs @@ -17,7 +17,7 @@ use litellm_secrets_types::{ use moka::future::Cache; use percent_encoding::{AsciiSet, NON_ALPHANUMERIC, utf8_percent_encode}; -use crate::Error; +use crate::{Error, WriteFailure}; const CYBERARK_API_BASE: &str = "CYBERARK_API_BASE"; const CYBERARK_ACCOUNT: &str = "CYBERARK_ACCOUNT"; @@ -62,38 +62,12 @@ pub enum AuthenticationRetry { Unauthorized, } -#[derive(veil::Redact)] -pub struct WriteFailure { - pub source: Error, - #[redact] - pub request_url: Option, - pub authentication: bool, -} - -impl WriteFailure { - fn local(source: Error) -> Self { - Self { - source, - request_url: None, - authentication: false, - } - } - - fn request(source: Error, url: reqwest::Url) -> Self { - Self { - source, - request_url: Some(url), - authentication: false, - } - } -} - impl CyberArkSecretManager { fn secret_url(&self, name: &str) -> Result { let encoded = utf8_percent_encode(name, SECRET_NAME_SAFE); self.endpoint .join(&format!("secrets/{}/variable/{}", self.account, encoded)) - .map_err(|_| Error::Endpoint) + .map_err(Error::Endpoint) } } diff --git a/litellm-rust/crates/secrets-cyberark/src/secret_manager/client.rs b/litellm-rust/crates/secrets-cyberark/src/secret_manager/client.rs index ea2262392d5..1cda0ae5306 100644 --- a/litellm-rust/crates/secrets-cyberark/src/secret_manager/client.rs +++ b/litellm-rust/crates/secrets-cyberark/src/secret_manager/client.rs @@ -64,25 +64,18 @@ impl CyberArkSecretManager { }), ..config.clone() }; - let client = - pool.client(&config, ClientVariant::Provider) - .map_err(|error| match error { - litellm_http::Error::Read { - tls_source: TlsSource::ClientIdentity, - .. - } - | litellm_http::Error::InvalidPem { - tls_source: TlsSource::ClientIdentity, - .. - } => Error::ClientCertificate, - other => Error::Client(Box::new(other)), - })?; + let client = pool + .client(&config, ClientVariant::Provider) + .map_err(|error| match error.tls_source() { + Some(TlsSource::ClientIdentity) => Error::ClientCertificate(error), + Some(TlsSource::CaBundle) | None => Error::Client(error), + })?; let endpoint = reqwest::Url::parse( &environment .get(CYBERARK_API_BASE) .unwrap_or_else(|| DEFAULT_API_BASE.to_owned()), ) - .map_err(|_| Error::Endpoint)?; + .map_err(Error::Endpoint)?; let account = environment .get(CYBERARK_ACCOUNT) .unwrap_or_else(|| DEFAULT_ACCOUNT.to_owned()); @@ -95,7 +88,7 @@ impl CyberArkSecretManager { value .parse::() .map(Duration::from_secs) - .map_err(|_| Error::RefreshInterval) + .map_err(Error::RefreshInterval) }) .transpose()?; Ok(Self::with_client( @@ -115,7 +108,7 @@ impl CyberArkSecretManager { self.account, utf8_percent_encode(&self.username, SECRET_NAME_SAFE) )) - .map_err(|_| Error::Endpoint) + .map_err(Error::Endpoint) } pub(super) async fn authenticate( @@ -135,11 +128,14 @@ impl CyberArkSecretManager { context, ) .send() - .await?; + .await + .map_err(litellm_http::Error::from)?; if !response.status().is_success() { return Err(Error::AuthStatus(response.status().as_u16())); } - let token = SecretValue::new(STANDARD.encode(response.text().await?)); + let token = SecretValue::new( + STANDARD.encode(response.text().await.map_err(litellm_http::Error::from)?), + ); self.token.insert((), token.clone()).await; Ok(token) } diff --git a/litellm-rust/crates/secrets-cyberark/src/secret_manager/read.rs b/litellm-rust/crates/secrets-cyberark/src/secret_manager/read.rs index daa9ed1114d..2862c6a956d 100644 --- a/litellm-rust/crates/secrets-cyberark/src/secret_manager/read.rs +++ b/litellm-rust/crates/secrets-cyberark/src/secret_manager/read.rs @@ -76,7 +76,8 @@ impl CyberArkSecretManager { context, ) .send() - .await?; + .await + .map_err(litellm_http::Error::from)?; let response = if matches!(retry, AuthenticationRetry::Unauthorized) && had_cached_token && response.status() == reqwest::StatusCode::UNAUTHORIZED @@ -89,7 +90,8 @@ impl CyberArkSecretManager { context, ) .send() - .await? + .await + .map_err(litellm_http::Error::from)? } else { response }; @@ -99,7 +101,7 @@ impl CyberArkSecretManager { if !response.status().is_success() { return Err(Error::Status(response.status().as_u16())); } - let value = SecretValue::new(response.text().await?); + let value = SecretValue::new(response.text().await.map_err(litellm_http::Error::from)?); Ok(Some(value)) } } diff --git a/litellm-rust/crates/secrets-cyberark/src/secret_manager/write.rs b/litellm-rust/crates/secrets-cyberark/src/secret_manager/write.rs index 87f6cea3619..7a2c79f506a 100644 --- a/litellm-rust/crates/secrets-cyberark/src/secret_manager/write.rs +++ b/litellm-rust/crates/secrets-cyberark/src/secret_manager/write.rs @@ -83,7 +83,9 @@ impl CyberArkSecretManager { ) .send() .await - .map_err(|source| WriteFailure::request(source.into(), url.clone())) + .map_err(|source| { + WriteFailure::request(litellm_http::Error::from(source).into(), url.clone()) + }) } pub(super) async fn ensure_variable_exists( @@ -141,8 +143,8 @@ impl CyberArkSecretManager { ); return; } - Err(error) => { - litellm_tracing::warn!("Error ensuring CyberArk variable exists: {error}"); + Err(_) => { + litellm_tracing::warn!("Error ensuring CyberArk variable exists"); return; } } diff --git a/litellm-rust/crates/secrets-cyberark/tests/secret_manager/configuration.rs b/litellm-rust/crates/secrets-cyberark/tests/secret_manager/configuration.rs index 1bea77e49ae..8a0746f8002 100644 --- a/litellm-rust/crates/secrets-cyberark/tests/secret_manager/configuration.rs +++ b/litellm-rust/crates/secrets-cyberark/tests/secret_manager/configuration.rs @@ -77,7 +77,7 @@ async fn authentication_encodes_login(#[case] username: &str, #[case] expected_p .mount(&server) .await; let manager = CyberArkSecretManager::with_client( - litellm_http::Client::plain_for_test(), + litellm_http::Client::for_test(), server.uri().parse().unwrap(), "acct".into(), username.into(), @@ -201,7 +201,7 @@ async fn trait_read_applies_cyberark_operation_timeout_to_authentication() { match result { Err(Error::Timeout) => {} - Err(Error::Http(error)) => assert!(error.is_timeout()), + Err(Error::Http(error)) => assert_eq!(error.status(), Some(408)), other => panic!("expected timeout, got {other:?}"), } } @@ -237,7 +237,7 @@ fn new_validates_credentials_before_license_and_configuration() { }), true ), - Err(Error::RefreshInterval) + Err(Error::RefreshInterval(_)) )); assert!(matches!( from_environment( @@ -248,7 +248,7 @@ fn new_validates_credentials_before_license_and_configuration() { }), true ), - Err(Error::Endpoint) + Err(Error::Endpoint(_)) )); } @@ -263,7 +263,7 @@ fn certificate_only_credentials_are_validated_as_a_client_identity() { true, ); - assert!(matches!(result, Err(Error::ClientCertificate))); + assert!(matches!(result, Err(Error::ClientCertificate(_)))); } #[rstest] @@ -347,7 +347,7 @@ fn invalid_client_identity_is_not_ignored( true, ); - assert!(matches!(result, Err(Error::ClientCertificate))); + assert!(matches!(result, Err(Error::ClientCertificate(_)))); } #[rstest] @@ -413,7 +413,7 @@ fn new_reports_missing_client_certificate_files() { }), true ), - Err(Error::ClientCertificate) + Err(Error::ClientCertificate(_)) )); } @@ -433,7 +433,7 @@ async fn trailing_slash_endpoint_preserves_base_path() { .await; let endpoint = format!("{}/prefix/", server.uri()).parse().unwrap(); let manager = CyberArkSecretManager::with_client( - litellm_http::Client::plain_for_test(), + litellm_http::Client::for_test(), endpoint, "acct".into(), "admin".into(), diff --git a/litellm-rust/crates/secrets-cyberark/tests/secret_manager/support.rs b/litellm-rust/crates/secrets-cyberark/tests/secret_manager/support.rs index 6fa15ecba9b..d7bc71b6503 100644 --- a/litellm-rust/crates/secrets-cyberark/tests/secret_manager/support.rs +++ b/litellm-rust/crates/secrets-cyberark/tests/secret_manager/support.rs @@ -62,7 +62,7 @@ pub(super) fn from_environment( pub(super) fn manager(server: &MockServer, ttl: Duration) -> CyberArkSecretManager { CyberArkSecretManager::with_client( - litellm_http::Client::plain_for_test(), + litellm_http::Client::for_test(), server.uri().parse().unwrap(), "acct".into(), "admin".into(), diff --git a/litellm-rust/crates/secrets-cyberark/tests/secret_manager/writes.rs b/litellm-rust/crates/secrets-cyberark/tests/secret_manager/writes.rs index 764a591bc71..3db8b6355e1 100644 --- a/litellm-rust/crates/secrets-cyberark/tests/secret_manager/writes.rs +++ b/litellm-rust/crates/secrets-cyberark/tests/secret_manager/writes.rs @@ -233,7 +233,7 @@ async fn writes_match_python_parity_fixture(parity_fixture: ParityFixture) { .mount(&server) .await; let manager = CyberArkSecretManager::with_client( - litellm_http::Client::plain_for_test(), + litellm_http::Client::for_test(), server.uri().parse().unwrap(), parity_fixture.account, parity_fixture.username, @@ -297,7 +297,7 @@ async fn live_conjur_round_trip() { .as_nanos() ); let manager = CyberArkSecretManager::with_client( - litellm_http::Client::plain_for_test(), + litellm_http::Client::for_test(), endpoint.clone(), account.clone(), username.clone(), @@ -312,7 +312,7 @@ async fn live_conjur_round_trip() { .await .unwrap(); let verifier = CyberArkSecretManager::with_client( - litellm_http::Client::plain_for_test(), + litellm_http::Client::for_test(), endpoint.clone(), account.clone(), username.clone(), diff --git a/litellm-rust/crates/secrets-google/Cargo.toml b/litellm-rust/crates/secrets-google/Cargo.toml index 3ce14fe7a12..06b3747def5 100644 --- a/litellm-rust/crates/secrets-google/Cargo.toml +++ b/litellm-rust/crates/secrets-google/Cargo.toml @@ -17,6 +17,7 @@ base64.workspace = true crc32c = "0.6.8" serde_json.workspace = true thiserror.workspace = true +url.workspace = true veil.workspace = true google-cloud-kms-v1 = "1.14.0" google-cloud-gax = { version = "1.14.0", default-features = false } diff --git a/litellm-rust/crates/secrets-google/src/error.rs b/litellm-rust/crates/secrets-google/src/error.rs index 159e4983ddc..486c7a3f35e 100644 --- a/litellm-rust/crates/secrets-google/src/error.rs +++ b/litellm-rust/crates/secrets-google/src/error.rs @@ -26,7 +26,7 @@ pub enum Error { Http( #[from] #[redact] - reqwest::Error, + litellm_http::Error, ), #[error("Google Secret Manager returned HTTP {0}")] Status(u16), @@ -35,15 +35,41 @@ pub enum Error { #[error("required environment variable is missing: {0}")] MissingEnvironment(&'static str), #[error("invalid refresh interval")] - RefreshInterval, + RefreshInterval(#[source] std::num::ParseIntError), #[error("payload is not valid base64")] - Base64(#[from] base64::DecodeError), + Base64( + #[from] + #[redact] + base64::DecodeError, + ), #[error("Google Secret Manager payload checksum mismatch")] - Checksum, + Checksum(#[source] Option), #[error("decrypted value is not UTF-8")] - Utf8, + Utf8(#[source] std::str::Utf8Error), #[error("invalid Google Secret Manager endpoint")] - Endpoint, + Endpoint(#[source] url::ParseError), #[error("Google Secret Manager requires an enterprise license")] EnterpriseRequired, } + +impl Error { + pub fn is_not_found(&self) -> bool { + match self { + Self::Status(status) => *status == 404, + Self::Operation(_) + | Self::Timeout + | Self::Client(_) + | Self::Auth(_) + | Self::Kms(_) + | Self::Http(_) + | Self::MissingPayload + | Self::MissingEnvironment(_) + | Self::RefreshInterval(_) + | Self::Base64(_) + | Self::Checksum(_) + | Self::Utf8(_) + | Self::Endpoint(_) + | Self::EnterpriseRequired => false, + } + } +} diff --git a/litellm-rust/crates/secrets-google/src/secret_manager.rs b/litellm-rust/crates/secrets-google/src/secret_manager.rs index 08ba466b799..463d1f6fd73 100644 --- a/litellm-rust/crates/secrets-google/src/secret_manager.rs +++ b/litellm-rust/crates/secrets-google/src/secret_manager.rs @@ -92,12 +92,12 @@ impl GoogleSecretManager { let ttl = environment .get(GOOGLE_SECRET_MANAGER_REFRESH_INTERVAL) .filter(|v| !v.is_empty()) - .map(|v| v.parse::().map_err(|_| Error::RefreshInterval)) + .map(|v| v.parse::().map_err(Error::RefreshInterval)) .transpose()? .unwrap_or( environment .get(SECRET_MANAGER_REFRESH_INTERVAL) - .map(|v| v.parse::().map_err(|_| Error::RefreshInterval)) + .map(|v| v.parse::().map_err(Error::RefreshInterval)) .transpose()? .unwrap_or(DEFAULT_REFRESH_INTERVAL.as_secs() as i64), ); @@ -164,20 +164,21 @@ impl GoogleSecretManager { ), percent_encoding::utf8_percent_encode(name, percent_encoding::NON_ALPHANUMERIC) )) - .map_err(|_| Error::Endpoint)?; + .map_err(Error::Endpoint)?; let response = self .client .get(url) .headers(self.credentials.request_headers().await?) .send() - .await?; + .await + .map_err(litellm_http::Error::from)?; if response.status() == reqwest::StatusCode::NOT_FOUND { return Ok(None); } if response.status() != reqwest::StatusCode::OK { return Err(Error::Status(response.status().as_u16())); } - let response: Response = response.json().await?; + let response: Response = response.json().await.map_err(litellm_http::Error::from)?; let Some(payload) = response.payload else { return Err(Error::MissingPayload); }; @@ -186,12 +187,15 @@ impl GoogleSecretManager { }; let bytes = STANDARD.decode(data)?; if let Some(expected) = payload.data_crc32c { - let expected = expected.parse::().map_err(|_| Error::Checksum)?; + let expected = expected + .parse::() + .map_err(|error| Error::Checksum(Some(error)))?; if crc32c::crc32c(&bytes) != expected { - return Err(Error::Checksum); + return Err(Error::Checksum(None)); } } - let plaintext = String::from_utf8(bytes).map_err(|_| Error::Utf8)?; + let plaintext = + String::from_utf8(bytes).map_err(|error| Error::Utf8(error.utf8_error()))?; let value = SecretValue::new(plaintext); Ok(Some(value)) } diff --git a/litellm-rust/crates/secrets-google/tests/secret_manager.rs b/litellm-rust/crates/secrets-google/tests/secret_manager.rs index e9bee7633f5..615e331cb96 100644 --- a/litellm-rust/crates/secrets-google/tests/secret_manager.rs +++ b/litellm-rust/crates/secrets-google/tests/secret_manager.rs @@ -11,7 +11,7 @@ use wiremock::{ fn manager(server: &MockServer, always_read: bool, ttl: Duration) -> GoogleSecretManager { GoogleSecretManager::with_client( - litellm_http::Client::plain_for_test(), + litellm_http::Client::for_test(), server.uri().parse().unwrap(), "project".into(), Arc::new(|name: &str| (name == "VERTEX_AI_API_KEY").then(|| "token".into())), @@ -152,8 +152,8 @@ async fn failed_or_missing_reads_are_not_cached( assert!(matches!(result, Err(Error::MissingPayload))); } ExpectedReadFailure::Base64 => assert!(matches!(result, Err(Error::Base64(_)))), - ExpectedReadFailure::Utf8 => assert!(matches!(result, Err(Error::Utf8))), - ExpectedReadFailure::Checksum => assert!(matches!(result, Err(Error::Checksum))), + ExpectedReadFailure::Utf8 => assert!(matches!(result, Err(Error::Utf8(_)))), + ExpectedReadFailure::Checksum => assert!(matches!(result, Err(Error::Checksum(None)))), } drop(failing); Mock::given(path( @@ -215,7 +215,7 @@ async fn always_read_and_expired_cache_fetch_again( fn google_manager_requires_host_license_and_project_configuration() { assert!(matches!( GoogleSecretManager::new( - litellm_http::Client::plain_for_test(), + litellm_http::Client::for_test(), Arc::new(|_: &str| None), false ), @@ -223,7 +223,7 @@ fn google_manager_requires_host_license_and_project_configuration() { )); assert!(matches!( GoogleSecretManager::new( - litellm_http::Client::plain_for_test(), + litellm_http::Client::for_test(), Arc::new(|_: &str| None), true ), @@ -244,8 +244,8 @@ fn google_manager_rejects_invalid_refresh_intervals(#[case] variable: &'static s }); assert!(matches!( - GoogleSecretManager::new(litellm_http::Client::plain_for_test(), environment, true), - Err(Error::RefreshInterval) + GoogleSecretManager::new(litellm_http::Client::for_test(), environment, true), + Err(Error::RefreshInterval(_)) )); } diff --git a/litellm-rust/crates/secrets-hashicorp/Cargo.toml b/litellm-rust/crates/secrets-hashicorp/Cargo.toml index 7dd3d3c674f..8731a8deb7a 100644 --- a/litellm-rust/crates/secrets-hashicorp/Cargo.toml +++ b/litellm-rust/crates/secrets-hashicorp/Cargo.toml @@ -6,8 +6,11 @@ license.workspace = true repository.workspace = true [dependencies] +litellm-error.workspace = true litellm-core-utils.workspace = true +litellm-http.workspace = true litellm-secrets-types.workspace = true +reqwest.workspace = true rustify.workspace = true rustify_derive.workspace = true serde.workspace = true diff --git a/litellm-rust/crates/secrets-hashicorp/src/config.rs b/litellm-rust/crates/secrets-hashicorp/src/config.rs index d32491199c4..4232667ae16 100644 --- a/litellm-rust/crates/secrets-hashicorp/src/config.rs +++ b/litellm-rust/crates/secrets-hashicorp/src/config.rs @@ -153,9 +153,11 @@ fn refresh_interval(environment: &dyn Lookup) -> Result { let Some(value) = value else { return Ok(DEFAULT_REFRESH_INTERVAL); }; - let seconds: i64 = value.parse().map_err(|_| Error::RefreshInterval)?; + let seconds: i64 = value + .parse() + .map_err(|error| Error::RefreshInterval(Some(error)))?; if seconds < 0 { - return Err(Error::RefreshInterval); + return Err(Error::RefreshInterval(None)); } Ok(Duration::from_secs(seconds as u64)) } diff --git a/litellm-rust/crates/secrets-hashicorp/src/error.rs b/litellm-rust/crates/secrets-hashicorp/src/error.rs index 1813cb486bc..73399a44eaa 100644 --- a/litellm-rust/crates/secrets-hashicorp/src/error.rs +++ b/litellm-rust/crates/secrets-hashicorp/src/error.rs @@ -1,42 +1,144 @@ +use rustify::errors::ClientError as RustifyClientError; +use vaultrs::error::ClientError; + #[derive(thiserror::Error, veil::Redact)] pub enum Error { #[error("HashiCorp Vault requires an enterprise license")] EnterpriseRequired, #[error("invalid secret name")] - InvalidSecretName(litellm_secrets_types::Error), + InvalidSecretName(#[source] litellm_secrets_types::Error), #[error(transparent)] Operation(#[from] litellm_secrets_types::Error), #[error("HashiCorp Vault client failed")] Client( - #[from] + #[source] #[redact] vaultrs::error::ClientError, ), - #[error("HashiCorp Vault client settings are invalid: {message}")] - ClientSettings { message: String }, - #[error("HashiCorp Vault TLS identity could not be configured for {path}: {message}")] + #[error("HashiCorp Vault request failed")] + Transport( + #[source] + #[redact] + litellm_http::Error, + ), + #[error("HashiCorp Vault client settings are invalid")] + ClientSettings(#[source] vaultrs::client::VaultClientSettingsBuilderError), + #[error("HashiCorp Vault TLS identity could not be configured for {path}")] TlsIdentity { path: std::path::PathBuf, - message: String, + source: litellm_error::Source, }, #[error("HashiCorp Vault login returned HTTP {status}")] LoginStatus { status: u16 }, #[error("HashiCorp Vault login response is malformed")] - MalformedLogin, + MalformedLogin( + #[source] + #[redact] + vaultrs::error::ClientError, + ), #[error("HashiCorp Vault authentication is not configured")] NoAuthConfigured, #[error("HashiCorp Vault returned HTTP {status}")] Status { status: u16 }, #[error("HashiCorp Vault response payload is malformed")] - MalformedPayload, + MalformedPayload( + #[source] + #[redact] + vaultrs::error::ClientError, + ), #[error("HashiCorp Vault secret value is not a string")] NonStringValue, #[error("HashiCorp Vault data key conflicts with description")] DataKeyConflictsWithDescription, #[error("HashiCorp Vault secret version exceeds CAS range")] - CasVersionOverflow, + CasVersionOverflow(#[source] std::num::TryFromIntError), #[error("HashiCorp Vault operation timed out")] Timeout, #[error("invalid HashiCorp Vault refresh interval")] - RefreshInterval, + RefreshInterval(#[source] Option), +} + +impl Error { + pub fn login_status(&self) -> Option { + match self { + Self::LoginStatus { status } => Some(*status), + Self::EnterpriseRequired + | Self::InvalidSecretName(_) + | Self::Operation(_) + | Self::Client(_) + | Self::Transport(_) + | Self::ClientSettings(_) + | Self::TlsIdentity { .. } + | Self::MalformedLogin(_) + | Self::NoAuthConfigured + | Self::Status { .. } + | Self::MalformedPayload(_) + | Self::NonStringValue + | Self::DataKeyConflictsWithDescription + | Self::CasVersionOverflow(_) + | Self::Timeout + | Self::RefreshInterval(_) => None, + } + } + + pub fn is_unsafe_secret_name(&self) -> bool { + match self { + Self::InvalidSecretName(error) | Self::Operation(error) => { + error.is_unsafe_secret_name() + } + Self::EnterpriseRequired + | Self::Client(_) + | Self::Transport(_) + | Self::ClientSettings(_) + | Self::TlsIdentity { .. } + | Self::LoginStatus { .. } + | Self::MalformedLogin(_) + | Self::NoAuthConfigured + | Self::Status { .. } + | Self::MalformedPayload(_) + | Self::NonStringValue + | Self::DataKeyConflictsWithDescription + | Self::CasVersionOverflow(_) + | Self::Timeout + | Self::RefreshInterval(_) => false, + } + } +} + +impl From for Error { + fn from(error: ClientError) -> Self { + match error { + ClientError::RestClientError { source } => match transport(source) { + Ok(error) => Self::Transport(error), + Err(source) => Self::Client(ClientError::RestClientError { source }), + }, + ClientError::RestClientBuildError { source } => Self::Transport(source.into()), + error => Self::Client(error), + } + } +} + +pub(crate) fn transport( + error: RustifyClientError, +) -> Result { + match error { + RustifyClientError::RequestError { + source, + url, + method, + } => source + .downcast::() + .map(litellm_http::Error::from) + .map_err(|source| RustifyClientError::RequestError { + source, + url, + method, + }), + RustifyClientError::ResponseError { source } => source + .downcast::() + .map(litellm_http::Error::from) + .map_err(|source| RustifyClientError::ResponseError { source }), + RustifyClientError::ReqwestBuildError { source } => Ok(source.into()), + error => Err(error), + } } diff --git a/litellm-rust/crates/secrets-hashicorp/src/lib.rs b/litellm-rust/crates/secrets-hashicorp/src/lib.rs index 7aab5a38b01..15c03724f72 100644 --- a/litellm-rust/crates/secrets-hashicorp/src/lib.rs +++ b/litellm-rust/crates/secrets-hashicorp/src/lib.rs @@ -7,4 +7,6 @@ pub mod secret_manager; pub use config::{AppRoleAuth, HashicorpVaultConfig, TlsCertAuth}; pub use error::Error; -pub use secret_manager::{HashicorpVault, RawOperationError, SecretLocation}; +pub use secret_manager::{ + HashicorpVault, HttpFailure, LoginFailure, RawOperationError, SecretLocation, +}; diff --git a/litellm-rust/crates/secrets-hashicorp/src/secret_manager.rs b/litellm-rust/crates/secrets-hashicorp/src/secret_manager.rs index f0d4fe8c0b4..447beacda85 100644 --- a/litellm-rust/crates/secrets-hashicorp/src/secret_manager.rs +++ b/litellm-rust/crates/secrets-hashicorp/src/secret_manager.rs @@ -31,7 +31,7 @@ use vaultrs::{ use crate::{Error, HashicorpVaultConfig, TlsCertAuth, cert_login::CertLoginRequest}; -pub use raw::RawOperationError; +pub use raw::{HttpFailure, LoginFailure, RawOperationError}; const CACHE_CAPACITY: u64 = 200; @@ -178,23 +178,25 @@ fn map_api_error(error: ClientError, context: ErrorContext) -> Error { ErrorContext::Login => Error::LoginStatus { status: code }, ErrorContext::Read | ErrorContext::Secret => Error::Status { status: code }, }, - ClientError::JsonParseError { source } => match context { - ErrorContext::Login => Error::MalformedLogin, - ErrorContext::Read => Error::MalformedPayload, - ErrorContext::Secret => Error::Client(ClientError::JsonParseError { source }), + error @ ClientError::JsonParseError { .. } => match context { + ErrorContext::Login => Error::MalformedLogin(error), + ErrorContext::Read => Error::MalformedPayload(error), + ErrorContext::Secret => Error::Client(error), }, - ClientError::ResponseEmptyError | ClientError::ResponseDataEmptyError => { - malformed_response(context) + error @ (ClientError::ResponseEmptyError | ClientError::ResponseDataEmptyError) => { + malformed_response(context, error) } ClientError::RestClientError { source } => match source { RustifyClientError::ServerResponseError { code, .. } => match context { ErrorContext::Login => Error::LoginStatus { status: code }, ErrorContext::Read | ErrorContext::Secret => Error::Status { status: code }, }, - RustifyClientError::ResponseParseError { .. } => malformed_response(context), - source => Error::Client(ClientError::RestClientError { source }), + source @ RustifyClientError::ResponseParseError { .. } => { + malformed_response(context, ClientError::RestClientError { source }) + } + source => ClientError::RestClientError { source }.into(), }, - error => Error::Client(error), + error => error.into(), } } @@ -208,10 +210,10 @@ fn api_status(error: &ClientError) -> Option { } } -fn malformed_response(context: ErrorContext) -> Error { +fn malformed_response(context: ErrorContext, error: ClientError) -> Error { match context { - ErrorContext::Login => Error::MalformedLogin, - ErrorContext::Read => Error::MalformedPayload, - ErrorContext::Secret => Error::Client(ClientError::ResponseDataEmptyError), + ErrorContext::Login => Error::MalformedLogin(error), + ErrorContext::Read => Error::MalformedPayload(error), + ErrorContext::Secret => Error::Client(error), } } diff --git a/litellm-rust/crates/secrets-hashicorp/src/secret_manager/client.rs b/litellm-rust/crates/secrets-hashicorp/src/secret_manager/client.rs index c1dc073dcf8..01d3807d290 100644 --- a/litellm-rust/crates/secrets-hashicorp/src/secret_manager/client.rs +++ b/litellm-rust/crates/secrets-hashicorp/src/secret_manager/client.rs @@ -83,10 +83,8 @@ impl HashicorpVault { .ca_certs(Vec::new()) .verify(true) .build() - .map_err(|message| Error::ClientSettings { - message: message.to_string(), - })?; - VaultClient::new(settings).map_err(Error::Client) + .map_err(Error::ClientSettings)?; + VaultClient::new(settings).map_err(Error::from) } } @@ -94,16 +92,16 @@ fn identity_for(tls: Option<&TlsCertAuth>) -> Result, Error> { tls.map(|tls| { let cert: Vec = std::fs::read(&tls.cert_path).map_err(|source| Error::TlsIdentity { path: tls.cert_path.clone(), - message: source.to_string(), + source: litellm_error::Source::new(source), })?; let key: Vec = std::fs::read(&tls.key_path).map_err(|source| Error::TlsIdentity { path: tls.key_path.clone(), - message: source.to_string(), + source: litellm_error::Source::new(source), })?; Identity::from_pem(&[cert.as_slice(), key.as_slice()].concat()).map_err(|source| { Error::TlsIdentity { path: tls.cert_path.clone(), - message: source.to_string(), + source: litellm_error::Source::new(source), } }) }) diff --git a/litellm-rust/crates/secrets-hashicorp/src/secret_manager/raw.rs b/litellm-rust/crates/secrets-hashicorp/src/secret_manager/raw.rs index 0325561a7a0..9c722c0b6c8 100644 --- a/litellm-rust/crates/secrets-hashicorp/src/secret_manager/raw.rs +++ b/litellm-rust/crates/secrets-hashicorp/src/secret_manager/raw.rs @@ -4,26 +4,123 @@ use vaultrs::api::kv2::requests::{ DeleteLatestSecretVersionRequest, ReadSecretRequest, SetSecretRequest, }; -#[derive(veil::Redact)] +#[derive(thiserror::Error, veil::Redact)] pub enum RawOperationError { + #[error(transparent)] Local(Error), + #[error("HashiCorp Vault authentication failed")] Authentication { source: Error, url: String, certificate: bool, }, - Http { - method: String, - url: String, - status: u16, + #[error("HashiCorp Vault {} request returned HTTP {}", .0.method, .0.status)] + Http(HttpFailure), + #[error("HashiCorp Vault request failed")] + Transport( + #[source] #[redact] - body: Vec, - }, - Transport(#[redact] RustifyClientError), - Timeout { - method: String, - elapsed: Duration, - }, + litellm_http::Error, + ), + #[error("HashiCorp Vault client failed")] + Client( + #[source] + #[redact] + RustifyClientError, + ), + #[error("HashiCorp Vault {method} request timed out")] + Timeout { method: String, elapsed: Duration }, +} + +#[derive(veil::Redact)] +pub struct HttpFailure { + pub method: String, + pub url: String, + pub status: u16, + #[redact] + pub body: Vec, +} + +pub struct LoginFailure<'a> { + pub source: &'a Error, + pub url: &'a str, + pub certificate: bool, +} + +impl RawOperationError { + pub fn is_unsafe_secret_name(&self) -> bool { + match self { + Self::Local(error) => error.is_unsafe_secret_name(), + Self::Authentication { .. } + | Self::Http(_) + | Self::Transport(_) + | Self::Client(_) + | Self::Timeout { .. } => false, + } + } + + pub fn local(&self) -> Option<&Error> { + match self { + Self::Local(error) => Some(error), + Self::Authentication { .. } + | Self::Http(_) + | Self::Transport(_) + | Self::Client(_) + | Self::Timeout { .. } => None, + } + } + + pub fn authentication(&self) -> Option> { + match self { + Self::Authentication { + source, + url, + certificate, + } => Some(LoginFailure { + source, + url, + certificate: *certificate, + }), + Self::Local(_) + | Self::Http(_) + | Self::Transport(_) + | Self::Client(_) + | Self::Timeout { .. } => None, + } + } + + pub fn http_failure(&self) -> Option<&HttpFailure> { + match self { + Self::Http(failure) => Some(failure), + Self::Local(_) + | Self::Authentication { .. } + | Self::Transport(_) + | Self::Client(_) + | Self::Timeout { .. } => None, + } + } + + pub fn timeout(&self) -> Option<(&str, Duration)> { + match self { + Self::Timeout { method, elapsed } => Some((method, *elapsed)), + Self::Local(_) + | Self::Authentication { .. } + | Self::Http(_) + | Self::Transport(_) + | Self::Client(_) => None, + } + } + + pub fn transport(&self) -> Option<&litellm_http::Error> { + match self { + Self::Transport(error) => Some(error), + Self::Local(_) + | Self::Authentication { .. } + | Self::Http(_) + | Self::Client(_) + | Self::Timeout { .. } => None, + } + } } impl HashicorpVault { @@ -118,7 +215,7 @@ impl HashicorpVault { let request = endpoint .with_middleware(&client.middle) .request(client.http.base()) - .map_err(RawOperationError::Transport)?; + .map_err(RawOperationError::Client)?; let method = request.method().to_string(); let url = format!( "{}/v1/{}{}/data/{}", @@ -141,14 +238,17 @@ impl HashicorpVault { })?, None => client.http.send(request).await, } - .map_err(RawOperationError::Transport)?; + .map_err(|error| match crate::error::transport(error) { + Ok(error) => RawOperationError::Transport(error), + Err(error) => RawOperationError::Client(error), + })?; if !response.status().is_success() { - return Err(RawOperationError::Http { + return Err(RawOperationError::Http(HttpFailure { method, url, status: response.status().as_u16(), body: response.into_body(), - }); + })); } Ok(response.into_body()) } diff --git a/litellm-rust/crates/secrets-hashicorp/src/secret_manager/write.rs b/litellm-rust/crates/secrets-hashicorp/src/secret_manager/write.rs index 0b1acb3a179..15a0e4c7dff 100644 --- a/litellm-rust/crates/secrets-hashicorp/src/secret_manager/write.rs +++ b/litellm-rust/crates/secrets-hashicorp/src/secret_manager/write.rs @@ -37,7 +37,7 @@ impl HashicorpVault { .await { Ok(metadata) => u32::try_from(metadata.current_version) - .map_err(|_| Error::CasVersionOverflow)?, + .map_err(Error::CasVersionOverflow)?, Err(error) if api_status(&error) == Some(404) => 0, Err(_) => return Err(map_api_error(error, ErrorContext::Secret)), }; diff --git a/litellm-rust/crates/secrets-hashicorp/tests/secret_manager/configuration.rs b/litellm-rust/crates/secrets-hashicorp/tests/secret_manager/configuration.rs index be3059ce986..b45b843fde8 100644 --- a/litellm-rust/crates/secrets-hashicorp/tests/secret_manager/configuration.rs +++ b/litellm-rust/crates/secrets-hashicorp/tests/secret_manager/configuration.rs @@ -32,7 +32,7 @@ fn invalid_refresh_intervals_are_rejected(#[case] value: &str) { assert!(matches!( HashicorpVaultConfig::from_environment(environment.as_ref()), - Err(Error::RefreshInterval) + Err(Error::RefreshInterval(_)) )); } @@ -79,6 +79,39 @@ async fn approle_login_uses_namespace_and_reuses_the_token() { assert!(manager.async_read_secret("name-2").await.unwrap().is_none()); } +#[rstest] +#[tokio::test] +async fn an_unreadable_client_certificate_keeps_its_io_cause() { + let server: MockServer = MockServer::start().await; + let directory: tempfile::TempDir = tempfile::tempdir().unwrap(); + let cert_path = directory.path().join("missing.crt"); + let values: HashMap = HashMap::from([ + ("HCP_VAULT_ADDR".to_owned(), server.uri()), + ( + "HCP_VAULT_CLIENT_CERT".to_owned(), + cert_path.to_str().unwrap().to_owned(), + ), + ( + "HCP_VAULT_CLIENT_KEY".to_owned(), + cert_path.to_str().unwrap().to_owned(), + ), + ]); + let environment: Arc = + Arc::new(move |name: &str| values.get(name).cloned()); + let manager: HashicorpVault = HashicorpVault::new(environment, true).unwrap(); + + let error = manager.async_read_secret("name").await.unwrap_err(); + + let cause = std::error::Error::source(&error) + .and_then(|cause| cause.downcast_ref::()) + .and_then(|cause| cause.downcast_ref::()) + .expect("io cause"); + assert_eq!(cause.kind(), std::io::ErrorKind::NotFound); + let report = litellm_error::Report::new(&error).to_string(); + assert_eq!(report.matches(cert_path.to_str().unwrap()).count(), 1); + assert!(report.ends_with(&cause.to_string())); +} + #[rstest] #[tokio::test] async fn tls_login_posts_the_role_and_uses_the_client_identity() { diff --git a/litellm-rust/crates/secrets-hashicorp/tests/secret_manager/reads.rs b/litellm-rust/crates/secrets-hashicorp/tests/secret_manager/reads.rs index 0c662eb5b55..c31b29fb536 100644 --- a/litellm-rust/crates/secrets-hashicorp/tests/secret_manager/reads.rs +++ b/litellm-rust/crates/secrets-hashicorp/tests/secret_manager/reads.rs @@ -138,7 +138,7 @@ async fn read_responses_distinguish_absence_and_malformed_payloads( .await; match expected { ExpectedRead::Missing => assert!(result.unwrap().is_none()), - ExpectedRead::Malformed => assert!(matches!(result, Err(Error::MalformedPayload))), + ExpectedRead::Malformed => assert!(matches!(result, Err(Error::MalformedPayload(_)))), ExpectedRead::NonString => assert!(matches!(result, Err(Error::NonStringValue))), } } @@ -383,3 +383,52 @@ async fn concurrent_reads_share_a_load_but_verification_fetches_fresh( "new" ); } + +fn unreachable_manager() -> HashicorpVault { + let address = std::net::TcpListener::bind("127.0.0.1:0") + .unwrap() + .local_addr() + .unwrap(); + let environment: Arc = Arc::new(move |name: &str| match name { + "HCP_VAULT_ADDR" => Some(format!("http://{address}")), + "HCP_VAULT_TOKEN" => Some("token".to_owned()), + _ => None, + }); + HashicorpVault::new(environment, true).unwrap() +} + +#[tokio::test] +async fn unreachable_vault_reads_are_connect_failures_without_the_url() { + let error = unreachable_manager() + .async_read_secret("do-not-leak") + .await + .unwrap_err(); + + assert!(matches!(&error, Error::Transport(transport) if transport.is_connect())); + let report = litellm_error::Report::new(&error).to_string(); + assert!( + report.starts_with("HashiCorp Vault request failed: "), + "{report}" + ); + assert!(!report.contains("do-not-leak"), "{report}"); +} + +#[tokio::test] +async fn unreachable_vault_raw_reads_are_connect_failures_without_the_url() { + let error = unreachable_manager() + .read_raw("do-not-leak", &HashicorpOperationContext::default()) + .await + .unwrap_err(); + + assert!( + error + .transport() + .is_some_and(litellm_http::Error::is_connect) + ); + let report = litellm_error::Report::new(&error).to_string(); + assert!( + report.starts_with("HashiCorp Vault request failed: "), + "{report}" + ); + assert!(!report.contains("do-not-leak"), "{report}"); +} diff --git a/litellm-rust/crates/secrets-types/src/error.rs b/litellm-rust/crates/secrets-types/src/error.rs index 027dd54d8cc..891d8a0fba9 100644 --- a/litellm-rust/crates/secrets-types/src/error.rs +++ b/litellm-rust/crates/secrets-types/src/error.rs @@ -11,3 +11,15 @@ pub enum Error { #[error("secret manager received an incompatible operation context")] InvalidOperationContext, } + +impl Error { + pub fn is_unsafe_secret_name(&self) -> bool { + match self { + Self::UnsafeSecretName => true, + Self::CurrentSecretMissing + | Self::NewSecretMissing + | Self::NewSecretMismatch + | Self::InvalidOperationContext => false, + } + } +} diff --git a/litellm-rust/crates/secrets-types/tests/cache.rs b/litellm-rust/crates/secrets-types/tests/cache.rs index cec4f5198e3..18efde4289b 100644 --- a/litellm-rust/crates/secrets-types/tests/cache.rs +++ b/litellm-rust/crates/secrets-types/tests/cache.rs @@ -110,7 +110,7 @@ async fn concurrent_misses_share_a_load_and_cancellation_allows_a_retry() { } #[tokio::test] -async fn refresh_bypasses_cached_values_and_errors_and_absence_are_retried() { +async fn refresh_bypasses_cached_values() { let cache = SecretCache::new(10, Duration::from_secs(60)); cache.insert("key", "old").await; assert_eq!( @@ -127,9 +127,21 @@ async fn refresh_bypasses_cached_values_and_errors_and_absence_are_retried() { .unwrap(), Some("fresh") ); - for result in [Err("failure"), Ok(None), Ok(Some("recovered"))] { - assert_eq!(cache.read("retry", async { result }).await, result); - } +} + +#[rstest] +#[case::failure(Err("failure"))] +#[case::absence(Ok(None))] +#[tokio::test] +async fn errors_and_absence_are_retried(#[case] first: Result, &'static str>) { + let cache = SecretCache::new(10, Duration::from_secs(60)); + assert_eq!(cache.read("retry", async { first }).await, first); + assert_eq!( + cache + .read("retry", async { Ok::<_, &str>(Some("recovered")) }) + .await, + Ok(Some("recovered")) + ); } #[tokio::test] diff --git a/litellm-rust/crates/secrets/Cargo.toml b/litellm-rust/crates/secrets/Cargo.toml index 3655ce8bbc2..023d61136e4 100644 --- a/litellm-rust/crates/secrets/Cargo.toml +++ b/litellm-rust/crates/secrets/Cargo.toml @@ -23,6 +23,7 @@ litellm-secrets-hashicorp = { workspace = true, optional = true } litellm-secrets-azure = { workspace = true, optional = true } litellm-secrets-cyberark = { workspace = true, optional = true } litellm-core-utils.workspace = true +litellm-error.workspace = true litellm-http.workspace = true base64.workspace = true serde.workspace = true diff --git a/litellm-rust/crates/secrets/src/compatibility.rs b/litellm-rust/crates/secrets/src/compatibility.rs index 621f7a3f432..368c9931b51 100644 --- a/litellm-rust/crates/secrets/src/compatibility.rs +++ b/litellm-rust/crates/secrets/src/compatibility.rs @@ -40,11 +40,9 @@ pub async fn get_secret_from_python_manager( }; match result { #[cfg(feature = "google")] - Err(Error::Google(litellm_secrets_google::Error::Status(404))) => { - Err(Error::ManagedSecretMissing) - } + Err(Error::Google(error)) if error.is_not_found() => Err(Error::ManagedSecretMissing), #[cfg(feature = "azure")] - Err(Error::Azure(litellm_secrets_azure::Error::MissingValue)) => Ok(None), + Err(Error::Azure(error)) if error.is_missing_value() => Ok(None), Ok(None) if matches!(manager, SecretManager::External(_)) && manager.system() == KeyManagementSystem::AzureKeyVault => diff --git a/litellm-rust/crates/secrets/src/error.rs b/litellm-rust/crates/secrets/src/error.rs index 7fc756c5c7d..ade8555242d 100644 --- a/litellm-rust/crates/secrets/src/error.rs +++ b/litellm-rust/crates/secrets/src/error.rs @@ -7,9 +7,9 @@ pub enum Error { #[error("encrypted environment value is missing")] MissingCiphertext, #[error("ciphertext is not valid base64 for the configured manager")] - InvalidCiphertext, + InvalidCiphertext(#[source] Option), #[error("decrypted value is not UTF-8")] - Utf8, + Utf8(#[source] std::str::Utf8Error), #[error(transparent)] Client(#[from] litellm_http::Error), #[error("unsupported OIDC provider or missing build feature")] @@ -19,21 +19,21 @@ pub enum Error { #[error("OIDC environment variable is missing")] MissingEnvironment, #[error("OIDC request failed")] - OidcHttp, + OidcHttp(#[source] litellm_http::Error), #[error("OIDC provider returned HTTP {0}")] OidcStatus(u16), #[error("OIDC response is invalid")] - OidcResponse, + OidcResponse(#[source] litellm_http::Error), #[error("OIDC file path must be absolute and within the credential allowlist")] UnsafeOidcPath, #[error("OIDC file could not be read")] - OidcFile, + OidcFile(#[source] std::io::Error), #[error("secret cannot be converted to {expected}")] TypeMismatch { expected: &'static str }, #[error("external secret manager failed")] - ExternalManager(#[source] Box), + ExternalManager(#[source] litellm_error::Source), #[error("external secret manager read failed")] - ExternalRead(#[source] Box), + ExternalRead(#[source] litellm_error::Source), #[cfg(feature = "aws")] #[error(transparent)] Aws(#[from] litellm_secrets_aws::Error), diff --git a/litellm-rust/crates/secrets/src/handler.rs b/litellm-rust/crates/secrets/src/handler.rs index db37d793384..f42e09c6bdb 100644 --- a/litellm-rust/crates/secrets/src/handler.rs +++ b/litellm-rust/crates/secrets/src/handler.rs @@ -87,7 +87,8 @@ pub async fn get_secret_from_manager( let plaintext = client .decrypt(decode_ciphertext(&ciphertext, Base64Mode::Permissive)?) .await?; - let value = String::from_utf8(plaintext).map_err(|_| Error::Utf8)?; + let value = + String::from_utf8(plaintext).map_err(|error| Error::Utf8(error.utf8_error()))?; Ok(Some(Secret::String(SecretValue::new(value.trim())))) } #[cfg(feature = "google")] @@ -98,7 +99,8 @@ pub async fn get_secret_from_manager( let plaintext = client .decrypt(decode_ciphertext(&ciphertext, Base64Mode::Canonical)?) .await?; - let value = String::from_utf8(plaintext).map_err(|_| Error::Utf8)?; + let value = + String::from_utf8(plaintext).map_err(|error| Error::Utf8(error.utf8_error()))?; Ok(Some(Secret::String(SecretValue::new(value)))) } #[cfg(feature = "aws")] @@ -149,9 +151,9 @@ fn decode_ciphertext(value: &str, mode: Base64Mode) -> Result, Error> { }; let ciphertext = STANDARD .decode(&encoded) - .map_err(|_| Error::InvalidCiphertext)?; + .map_err(|error| Error::InvalidCiphertext(Some(error)))?; if canonical && STANDARD.encode(&ciphertext) != encoded { - return Err(Error::InvalidCiphertext); + return Err(Error::InvalidCiphertext(None)); } Ok(ciphertext) } diff --git a/litellm-rust/crates/secrets/src/oidc.rs b/litellm-rust/crates/secrets/src/oidc.rs index adeb6c3db00..24e6912c797 100644 --- a/litellm-rust/crates/secrets/src/oidc.rs +++ b/litellm-rust/crates/secrets/src/oidc.rs @@ -191,7 +191,7 @@ impl OidcResolver { .header("Accept", "application/json; api-version=2.0") .send() .await - .map_err(|_| Error::OidcHttp)?; + .map_err(|error| Error::OidcHttp(error.into()))?; if response.status() != reqwest::StatusCode::OK { return Err(Error::OidcStatus(response.status().as_u16())); } @@ -199,7 +199,10 @@ impl OidcResolver { struct Token { value: Option, } - let token: Token = response.json().await.map_err(|_| Error::OidcResponse)?; + let token: Token = response + .json() + .await + .map_err(|error| Error::OidcResponse(error.into()))?; if let Some(value) = &token.value { self.cache .insert( @@ -225,11 +228,14 @@ impl OidcResolver { .header("Metadata-Flavor", "Google") .send() .await - .map_err(|_| Error::OidcHttp)?; + .map_err(|error| Error::OidcHttp(error.into()))?; if response.status() != reqwest::StatusCode::OK { return Err(Error::OidcStatus(response.status().as_u16())); } - let token = response.text().await.map_err(|_| Error::OidcResponse)?; + let token = response + .text() + .await + .map_err(|error| Error::OidcResponse(error.into()))?; let now = (self.clock)(); let ttl = oidc_token_cache_ttl(&token, now, GOOGLE_TOKEN_MAX_TTL); let value = SecretValue::new(token); @@ -259,7 +265,7 @@ async fn read_file(path: &str) -> Result { tokio::fs::read_to_string(path) .await .map(|value| SecretValue::new(value.replace("\r\n", "\n").replace('\r', "\n"))) - .map_err(|_| Error::OidcFile) + .map_err(Error::OidcFile) } async fn read_allowed_file( @@ -271,7 +277,7 @@ async fn read_allowed_file( } let resolved = tokio::fs::canonicalize(path) .await - .map_err(|_| Error::OidcFile)?; + .map_err(Error::OidcFile)?; let allowed = environment .get(OIDC_ALLOWED_CREDENTIAL_DIRS) .filter(|v| !v.is_empty()) @@ -283,7 +289,7 @@ async fn read_allowed_file( return tokio::fs::read_to_string(&resolved) .await .map(|value| SecretValue::new(value.replace("\r\n", "\n").replace('\r', "\n"))) - .map_err(|_| Error::OidcFile); + .map_err(Error::OidcFile); } } Err(Error::UnsafeOidcPath) diff --git a/litellm-rust/crates/secrets/tests/aws.rs b/litellm-rust/crates/secrets/tests/aws.rs index 910b1855b77..abad04f31c5 100644 --- a/litellm-rust/crates/secrets/tests/aws.rs +++ b/litellm-rust/crates/secrets/tests/aws.rs @@ -53,7 +53,7 @@ async fn read_results_follow_the_selected_failure_policy( }, )), Arc::new(move |_: &str| environment.map(str::to_owned)), - OidcResolver::new(litellm_http::Client::plain_for_test()), + OidcResolver::new(litellm_http::Client::for_test()), ) .with_failure_policy(policy); let result = resolver @@ -97,7 +97,7 @@ async fn primary_secret_values_other_than_strings_resolve_to_none( let resolver = SecretResolver::new_python_compatible( Arc::new(state(&server, settings)), Arc::new(|_: &str| Some("fallback".into())), - OidcResolver::new(litellm_http::Client::plain_for_test()), + OidcResolver::new(litellm_http::Client::for_test()), ); let text = value.as_str(); assert_eq!( @@ -157,7 +157,7 @@ async fn gating_prediction_matches_actual_lookup( let resolver = SecretResolver::new_python_compatible( Arc::new(state), Arc::new(|_: &str| Some("environment".into())), - OidcResolver::new(litellm_http::Client::plain_for_test()), + OidcResolver::new(litellm_http::Client::for_test()), ); assert_eq!( resolver @@ -218,6 +218,6 @@ async fn aws_handler_reads_ciphertext_decodes_trims_and_redacts() { )); assert!(matches!( get_secret_from_manager(&manager, "KEY", &settings, &|_: &str| Some("abc".into())).await, - Err(Error::InvalidCiphertext) + Err(Error::InvalidCiphertext(_)) )); } diff --git a/litellm-rust/crates/secrets/tests/azure.rs b/litellm-rust/crates/secrets/tests/azure.rs index 60f165add54..6e81017b0f6 100644 --- a/litellm-rust/crates/secrets/tests/azure.rs +++ b/litellm-rust/crates/secrets/tests/azure.rs @@ -22,7 +22,7 @@ async fn azure_handler_reads_missing_and_failed_secrets() { .await; let manager = SecretManager::AzureKeyVault( AzureKeyVault::with_client( - litellm_http::Client::plain_for_test(), + litellm_http::Client::for_test(), server.uri().parse().unwrap(), std::sync::Arc::new(|name: &str| (name == "AZURE_AD_TOKEN").then(|| "fake".to_owned())), ) @@ -81,7 +81,7 @@ async fn successful_azure_responses_do_not_fall_back_when_the_value_is_empty_or_ .mount(&server) .await; let manager = AzureKeyVault::with_client( - litellm_http::Client::plain_for_test(), + litellm_http::Client::for_test(), server.uri().parse().unwrap(), Arc::new(|name: &str| (name == "AZURE_AD_TOKEN").then(|| "token".into())), ) @@ -92,7 +92,7 @@ async fn successful_azure_responses_do_not_fall_back_when_the_value_is_empty_or_ Default::default(), )), Arc::new(|_: &str| Some("environment".into())), - OidcResolver::new(litellm_http::Client::plain_for_test()), + OidcResolver::new(litellm_http::Client::for_test()), ); assert_eq!( resolver diff --git a/litellm-rust/crates/secrets/tests/common_read_contract.rs b/litellm-rust/crates/secrets/tests/common_read_contract.rs index 2e8fbf46008..e6928038799 100644 --- a/litellm-rust/crates/secrets/tests/common_read_contract.rs +++ b/litellm-rust/crates/secrets/tests/common_read_contract.rs @@ -59,7 +59,7 @@ fn manager(provider: Provider, server: &MockServer) -> SecretManager { ), Provider::Azure => SecretManager::AzureKeyVault( AzureKeyVault::with_client( - litellm_http::Client::plain_for_test(), + litellm_http::Client::for_test(), server.uri().parse().unwrap(), environment, ) @@ -67,7 +67,7 @@ fn manager(provider: Provider, server: &MockServer) -> SecretManager { ), Provider::Google => SecretManager::GoogleSecretManager( GoogleSecretManager::with_client( - litellm_http::Client::plain_for_test(), + litellm_http::Client::for_test(), server.uri().parse().unwrap(), "project".into(), environment, @@ -84,7 +84,7 @@ fn manager(provider: Provider, server: &MockServer) -> SecretManager { .unwrap(), ), Provider::Cyberark => SecretManager::Cyberark(CyberArkSecretManager::with_client( - litellm_http::Client::plain_for_test(), + litellm_http::Client::for_test(), server.uri().parse().unwrap(), "acct".into(), "admin".into(), @@ -240,7 +240,7 @@ async fn python_read_failures_preserve_provider_fallback_rules( KeyManagementSettings::default(), )), Arc::new(move |_: &str| environment_value.map(str::to_owned)), - OidcResolver::new(litellm_http::Client::plain_for_test()), + OidcResolver::new(litellm_http::Client::for_test()), ); let expected = if matches!(provider, Provider::Aws) { None diff --git a/litellm-rust/crates/secrets/tests/cyberark.rs b/litellm-rust/crates/secrets/tests/cyberark.rs index b94bd9dc0ad..0a6c394937e 100644 --- a/litellm-rust/crates/secrets/tests/cyberark.rs +++ b/litellm-rust/crates/secrets/tests/cyberark.rs @@ -24,7 +24,7 @@ async fn cyberark_handler_reads_values_and_surfaces_errors() { .mount(&server) .await; let manager = SecretManager::Cyberark(CyberArkSecretManager::with_client( - litellm_http::Client::plain_for_test(), + litellm_http::Client::for_test(), server.uri().parse().unwrap(), "acct".into(), "admin".into(), diff --git a/litellm-rust/crates/secrets/tests/google.rs b/litellm-rust/crates/secrets/tests/google.rs index 0b45a90c10b..5542c864dfd 100644 --- a/litellm-rust/crates/secrets/tests/google.rs +++ b/litellm-rust/crates/secrets/tests/google.rs @@ -25,7 +25,7 @@ async fn google_resolver_distinguishes_absence_from_failure(#[case] status: u16) _ => None, }); let manager = GoogleSecretManager::with_client( - litellm_http::Client::plain_for_test(), + litellm_http::Client::for_test(), server.uri().parse().unwrap(), "project".into(), environment.clone(), @@ -40,7 +40,7 @@ async fn google_resolver_distinguishes_absence_from_failure(#[case] status: u16) let resolver = SecretResolver::new_python_compatible( Arc::new(state), environment, - OidcResolver::new(litellm_http::Client::plain_for_test()), + OidcResolver::new(litellm_http::Client::for_test()), ) .with_failure_policy(FailurePolicy::Propagate); let result = resolver.get_secret_str("KEY", None).await; @@ -108,7 +108,7 @@ async fn google_handler_requires_canonical_base64_and_preserves_plaintext_whites STANDARD.encode("encrypted") ))) .await, - Err(Error::InvalidCiphertext) + Err(Error::InvalidCiphertext(_)) )); assert!(matches!( get_secret_from_manager(&manager, "KEY", &settings, &|_: &str| None).await, diff --git a/litellm-rust/crates/secrets/tests/hashicorp.rs b/litellm-rust/crates/secrets/tests/hashicorp.rs index e10e903c25a..bfb289cdb97 100644 --- a/litellm-rust/crates/secrets/tests/hashicorp.rs +++ b/litellm-rust/crates/secrets/tests/hashicorp.rs @@ -56,7 +56,7 @@ async fn hashicorp_handler_resolves_found_missing_and_failed_values() { }, )), Arc::new(|_: &str| None), - litellm_secrets::OidcResolver::new(litellm_http::Client::plain_for_test()), + litellm_secrets::OidcResolver::new(litellm_http::Client::for_test()), ); assert_eq!( found_resolver @@ -131,7 +131,7 @@ async fn hashicorp_handler_resolves_found_missing_and_failed_values() { let failed_resolver = SecretResolver::new_python_compatible( Arc::new(failed_state), Arc::new(|_: &str| None), - litellm_secrets::OidcResolver::new(litellm_http::Client::plain_for_test()), + litellm_secrets::OidcResolver::new(litellm_http::Client::for_test()), ) .with_failure_policy(FailurePolicy::Propagate); assert!(matches!( diff --git a/litellm-rust/crates/secrets/tests/oidc.rs b/litellm-rust/crates/secrets/tests/oidc.rs index 6f72bd9d645..867a662cbbb 100644 --- a/litellm-rust/crates/secrets/tests/oidc.rs +++ b/litellm-rust/crates/secrets/tests/oidc.rs @@ -30,7 +30,7 @@ async fn environment_sources_resolve_expected_value( ("CIRCLE_OIDC_TOKEN_V2", "circle-v2"), ]); assert_eq!( - OidcResolver::new(litellm_http::Client::plain_for_test()) + OidcResolver::new(litellm_http::Client::for_test()) .resolve(reference, env.as_ref()) .await .unwrap() @@ -43,7 +43,7 @@ async fn environment_sources_resolve_expected_value( #[tokio::test] async fn environment_sources_bypass_boolean_conversion_and_defaults() { let env = environment(&[("TOKEN", "true")]); - let oidc = OidcResolver::new(litellm_http::Client::plain_for_test()); + let oidc = OidcResolver::new(litellm_http::Client::for_test()); let resolver = SecretResolver::new(Arc::new(SecretManagerState::default()), env, oidc); assert_eq!( resolver @@ -94,7 +94,7 @@ async fn github_requests_are_authenticated_cached_and_revalidate_environment() { ), ("ACTIONS_ID_TOKEN_REQUEST_TOKEN", "request-token"), ]); - let oidc = OidcResolver::new(litellm_http::Client::plain_for_test()); + let oidc = OidcResolver::new(litellm_http::Client::for_test()); for _ in 0..2 { assert_eq!( oidc.resolve("oidc/github/https://service/oidc/path", env.as_ref()) @@ -131,7 +131,7 @@ async fn file_allowlist_resolves_symlinks_while_environment_paths_remain_explici ("PATH_TOKEN", private.to_str().unwrap()), ("AZURE_FEDERATED_TOKEN_FILE", token.to_str().unwrap()), ]); - let oidc = OidcResolver::new(litellm_http::Client::plain_for_test()); + let oidc = OidcResolver::new(litellm_http::Client::for_test()); assert_eq!( oidc.resolve(&format!("oidc/file/{}", token.display()), env.as_ref()) .await @@ -213,7 +213,7 @@ async fn google_expiry_caps_cache_and_preserves_audience( .expect(calls) .mount(&server) .await; - let oidc = OidcResolver::new(litellm_http::Client::plain_for_test()) + let oidc = OidcResolver::new(litellm_http::Client::for_test()) .with_google_identity_endpoint(server.uri().parse().unwrap()) .with_clock(now); for _ in 0..2 { @@ -235,7 +235,7 @@ async fn google_expiry_caps_cache_and_preserves_audience( #[tokio::test] async fn google_oidc_requires_its_build_feature() { assert!(matches!( - OidcResolver::new(litellm_http::Client::plain_for_test()) + OidcResolver::new(litellm_http::Client::for_test()) .resolve("oidc/google/audience", environment(&[]).as_ref()) .await, Err(Error::UnsupportedOidc) @@ -246,7 +246,7 @@ async fn google_oidc_requires_its_build_feature() { #[tokio::test] async fn azure_oidc_without_a_token_file_requires_its_build_feature() { assert!(matches!( - OidcResolver::new(litellm_http::Client::plain_for_test()) + OidcResolver::new(litellm_http::Client::for_test()) .resolve("oidc/azure/scope", environment(&[]).as_ref()) .await, Err(Error::UnsupportedOidc) @@ -262,7 +262,7 @@ async fn invalid_references_fail_before_environment_lookup( #[case] reference: &str, #[case] unsupported: bool, ) { - let error = OidcResolver::new(litellm_http::Client::plain_for_test()) + let error = OidcResolver::new(litellm_http::Client::for_test()) .resolve(reference, &|_: &str| { panic!("invalid reference reached environment lookup") }) @@ -284,7 +284,7 @@ async fn unreadable_expiry_keeps_python_cache_fallback(#[case] token: &str) { .expect(1) .mount(&server) .await; - let resolver = OidcResolver::new(litellm_http::Client::plain_for_test()) + let resolver = OidcResolver::new(litellm_http::Client::for_test()) .with_google_identity_endpoint(server.uri().parse().unwrap()); for _ in 0..2 { assert_eq!( @@ -336,7 +336,7 @@ async fn azure_oidc_acquires_the_requested_scope_and_preserves_failures(#[case] }) } } - let oidc = OidcResolver::new(litellm_http::Client::plain_for_test()) + let oidc = OidcResolver::new(litellm_http::Client::for_test()) .with_azure_token_provider(Arc::new(Provider(failed))); let resolver = SecretResolver::new_python_compatible( Arc::new(SecretManagerState::default()), @@ -364,7 +364,7 @@ async fn azure_oidc_acquires_the_requested_scope_and_preserves_failures(#[case] #[tokio::test] async fn missing_oidc_environment_is_an_error(#[case] reference: &str) { assert!(matches!( - OidcResolver::new(litellm_http::Client::plain_for_test()) + OidcResolver::new(litellm_http::Client::for_test()) .resolve(reference, environment(&[]).as_ref()) .await, Err(Error::MissingEnvironment) @@ -383,7 +383,7 @@ async fn google_oidc_failures_are_not_cached_or_hidden_by_defaults() { let resolver = SecretResolver::new_python_compatible( Arc::new(SecretManagerState::default()), environment(&[]), - OidcResolver::new(litellm_http::Client::plain_for_test()) + OidcResolver::new(litellm_http::Client::for_test()) .with_google_identity_endpoint(server.uri().parse().unwrap()), ); for _ in 0..2 { @@ -424,7 +424,7 @@ async fn google_tokens_expire_at_the_python_cache_deadline( .expect(2) .mount(&server) .await; - let resolver = OidcResolver::new(litellm_http::Client::plain_for_test()) + let resolver = OidcResolver::new(litellm_http::Client::for_test()) .with_google_identity_endpoint(server.uri().parse().unwrap()) .with_clock(|| UNIX_EPOCH + Duration::from_secs(1000)); assert_eq!( @@ -477,7 +477,7 @@ async fn google_cache_uses_payload_expiry_without_requiring_a_jwt_header() { .expect(2) .mount(&server) .await; - let resolver = OidcResolver::new(litellm_http::Client::plain_for_test()) + let resolver = OidcResolver::new(litellm_http::Client::for_test()) .with_google_identity_endpoint(server.uri().parse().unwrap()) .with_clock(|| UNIX_EPOCH + Duration::from_secs(1000)); for _ in 0..2 { diff --git a/litellm-rust/crates/secrets/tests/resolution.rs b/litellm-rust/crates/secrets/tests/resolution.rs index 37557c36fb5..8435e051315 100644 --- a/litellm-rust/crates/secrets/tests/resolution.rs +++ b/litellm-rust/crates/secrets/tests/resolution.rs @@ -12,79 +12,86 @@ fn resolver(value: Option<&str>) -> SecretResolver { SecretResolver::new_python_compatible( Arc::new(SecretManagerState::default()), Arc::new(move |_: &str| value.clone()), - OidcResolver::new(litellm_http::Client::plain_for_test()), + OidcResolver::new(litellm_http::Client::for_test()), ) } #[rstest::rstest] -#[case::environment(false)] -#[case::manager(true)] +#[case::capitalized_true("True", Some(true))] +#[case::padded_false(" FALSE ", Some(false))] +#[case::empty("", None)] +#[case::parenthesized("(True)", None)] +#[case::json("{\"key\":1}", None)] #[tokio::test] -async fn native_reads_preserve_strings_and_report_conversion_errors(#[case] managed: bool) { - for raw in ["True", " FALSE ", "", "(True)", "{\"key\":1}"] { - let state = if managed { - SecretManagerState::new( - SecretManager::External(Arc::new(FixedManager::custom(Ok(Some(Secret::String( - SecretValue::new(raw), - )))))), - KeyManagementSettings::default(), - ) - } else { - SecretManagerState::default() - }; - let resolver = SecretResolver::new( - Arc::new(state), - Arc::new(move |_: &str| Some(raw.to_owned())), - OidcResolver::new(litellm_http::Client::plain_for_test()), - ); - assert_eq!( - resolver - .get_secret_str("key", None) - .await - .unwrap() - .unwrap() - .expose(), - raw - ); - assert_eq!( - resolver.get_secret("key", None).await.unwrap(), - Some(Secret::String(SecretValue::new(raw))) - ); - if raw == "True" || raw == " FALSE " { - assert_eq!( - resolver.get_secret_bool("key", None).await.unwrap(), - Some(raw == "True") - ); - } else { - assert!(matches!( - resolver.get_secret_bool("key", None).await, - Err(Error::TypeMismatch { - expected: "boolean" - }) - )); - } +async fn native_reads_preserve_strings_and_report_conversion_errors( + #[case] raw: &'static str, + #[case] boolean: Option, + #[values(false, true)] managed: bool, +) { + let state = if managed { + SecretManagerState::new( + SecretManager::External(Arc::new(FixedManager::custom(Ok(Some(Secret::String( + SecretValue::new(raw), + )))))), + KeyManagementSettings::default(), + ) + } else { + SecretManagerState::default() + }; + let resolver = SecretResolver::new( + Arc::new(state), + Arc::new(move |_: &str| Some(raw.to_owned())), + OidcResolver::new(litellm_http::Client::for_test()), + ); + assert_eq!( + resolver + .get_secret_str("key", None) + .await + .unwrap() + .unwrap() + .expose(), + raw + ); + assert_eq!( + resolver.get_secret("key", None).await.unwrap(), + Some(Secret::String(SecretValue::new(raw))) + ); + match boolean { + Some(expected) => assert_eq!( + resolver.get_secret_bool("key", None).await.unwrap(), + Some(expected) + ), + None => assert!(matches!( + resolver.get_secret_bool("key", None).await, + Err(Error::TypeMismatch { + expected: "boolean" + }) + )), } } +#[rstest::rstest] +#[case::absent(Ok(None))] +#[case::failed(Err(()))] #[tokio::test] -async fn native_defaults_apply_to_absence_but_never_hide_provider_failures() { - for reply in [Ok(None), Err(())] { - let resolver = SecretResolver::new( - Arc::new(SecretManagerState::new( - SecretManager::External(Arc::new(FixedManager::custom(reply.clone()))), - KeyManagementSettings::default(), - )), - Arc::new(|_: &str| None), - OidcResolver::new(litellm_http::Client::plain_for_test()), - ); - let result = resolver - .get_secret_str("key", Some(SecretValue::new("default"))) - .await; - match reply { - Ok(None) => assert_eq!(result.unwrap().unwrap().expose(), "default"), - Err(()) => assert!(matches!(result, Err(Error::MissingCiphertext))), - Ok(Some(_)) => unreachable!(), - } +async fn native_defaults_apply_to_absence_but_never_hide_provider_failures( + #[case] reply: Result, ()>, +) { + let resolver = SecretResolver::new( + Arc::new(SecretManagerState::new( + SecretManager::External(Arc::new(FixedManager::custom(reply.clone()))), + KeyManagementSettings::default(), + )), + Arc::new(|_: &str| None), + OidcResolver::new(litellm_http::Client::for_test()), + ); + let result = resolver + .get_secret_str("key", Some(SecretValue::new("default"))) + .await; + match reply { + Ok(None) => assert_eq!(result.unwrap().unwrap().expose(), "default"), + Err(()) => assert!(matches!(result, Err(Error::MissingCiphertext))), + Ok(Some(_)) => unreachable!(), } } @@ -189,7 +196,7 @@ fn managed(reply: Result, ()>, environment: Option<&'static str>) KeyManagementSettings::default(), )), Arc::new(move |_: &str| environment.map(str::to_owned)), - OidcResolver::new(litellm_http::Client::plain_for_test()), + OidcResolver::new(litellm_http::Client::for_test()), ) .with_failure_policy(FailurePolicy::EnvironmentFallback) } @@ -281,7 +288,7 @@ async fn prefix_is_removed_once_and_resolved_from_environment() { let resolver = SecretResolver::new_python_compatible( Arc::new(state), Arc::new(|name: &str| (name == "os.environ/KEY").then(|| "value".into())), - OidcResolver::new(litellm_http::Client::plain_for_test()), + OidcResolver::new(litellm_http::Client::for_test()), ); assert_eq!( resolver @@ -340,7 +347,7 @@ async fn excluded_hosted_keys_keep_the_python_manager_conversion_path( }, )), Arc::new(move |_: &str| Some(raw.to_owned())), - OidcResolver::new(litellm_http::Client::plain_for_test()), + OidcResolver::new(litellm_http::Client::for_test()), ); assert_eq!( resolver.get_secret("KEY", None).await.unwrap(), @@ -373,7 +380,7 @@ async fn azure_callback_absence_preserves_none_but_errors_fall_back( KeyManagementSettings::default(), )), Arc::new(|_: &str| Some("environment".into())), - OidcResolver::new(litellm_http::Client::plain_for_test()), + OidcResolver::new(litellm_http::Client::for_test()), ); assert_eq!( resolver diff --git a/litellm-rust/crates/secrets/tests/source.rs b/litellm-rust/crates/secrets/tests/source.rs index 17210940a67..41f0ecea518 100644 --- a/litellm-rust/crates/secrets/tests/source.rs +++ b/litellm-rust/crates/secrets/tests/source.rs @@ -15,7 +15,7 @@ mod tests { #[case] expected: Option<&str>, ) { unsafe { std::env::set_var(name, value) }; - let secret = EnvironmentSecrets::python_compatible(litellm_http::Client::plain_for_test()) + let secret = EnvironmentSecrets::python_compatible(litellm_http::Client::for_test()) .resolve(&[name]) .await .unwrap() @@ -42,7 +42,7 @@ async fn dynamic_names_use_the_same_resolver_and_snapshots_never_do_fresh_lookup reads.fetch_add(1, Ordering::SeqCst); (name != "missing").then(|| name.to_owned()) }), - OidcResolver::new(litellm_http::Client::plain_for_test()), + OidcResolver::new(litellm_http::Client::for_test()), ); let snapshot = source.resolve(&["declared", "missing"]).await.unwrap(); let name = format!("runtime-{}", "key"); diff --git a/litellm-rust/crates/spend-clickhouse/Cargo.toml b/litellm-rust/crates/spend-clickhouse/Cargo.toml index 893c5daded3..ef7f4a0efdf 100644 --- a/litellm-rust/crates/spend-clickhouse/Cargo.toml +++ b/litellm-rust/crates/spend-clickhouse/Cargo.toml @@ -7,6 +7,7 @@ repository.workspace = true [dependencies] flate2.workspace = true +litellm-error.workspace = true litellm-http.workspace = true litellm-storage-clickhouse.workspace = true serde.workspace = true diff --git a/litellm-rust/crates/spend-clickhouse/src/error.rs b/litellm-rust/crates/spend-clickhouse/src/error.rs index 0d037ef06f8..c5a9f542ca6 100644 --- a/litellm-rust/crates/spend-clickhouse/src/error.rs +++ b/litellm-rust/crates/spend-clickhouse/src/error.rs @@ -1,15 +1,32 @@ +use litellm_error::Source; + #[derive(Debug, thiserror::Error)] pub enum Error { - #[error("invalid ClickHouse insert row")] - InvalidRow, - #[error("{0} must be a positive integer")] - InvalidLimit(&'static str), - #[error("database must be a nonempty SQL identifier and retention must be positive")] - InvalidSchema, - #[error("ClickHouse insert exceeds the encoded size limit")] - InsertTooLarge, + #[error("{field} must be an integer millisecond timestamp")] + NonIntegerTimestamp { field: &'static str }, + #[error("{field} is outside the supported timestamp range")] + TimestampOutOfRange { field: &'static str, source: Source }, #[error(transparent)] Storage(#[from] litellm_storage_clickhouse::Error), #[error(transparent)] Migration(#[from] sqlx::migrate::MigrateError), } + +impl Error { + pub fn is_request(&self) -> bool { + match self { + Self::NonIntegerTimestamp { .. } | Self::TimestampOutOfRange { .. } => true, + Self::Storage(error) => error.is_request(), + Self::Migration(_) => false, + } + } + + pub fn is_insert_too_large(&self) -> bool { + match self { + Self::Storage(error) => error.is_insert_too_large(), + Self::NonIntegerTimestamp { .. } + | Self::TimestampOutOfRange { .. } + | Self::Migration(_) => false, + } + } +} diff --git a/litellm-rust/crates/spend-clickhouse/src/insert.rs b/litellm-rust/crates/spend-clickhouse/src/insert.rs index 495f0d8ecb2..66d0ea59536 100644 --- a/litellm-rust/crates/spend-clickhouse/src/insert.rs +++ b/litellm-rust/crates/spend-clickhouse/src/insert.rs @@ -13,7 +13,8 @@ use sha2::{Digest, Sha256}; use time::{OffsetDateTime, format_description::well_known::Rfc3339}; use crate::Error; -use litellm_storage_clickhouse::Connection; +use litellm_error::Source; +use litellm_storage_clickhouse::{Connection, Error as StorageError}; fn max_insert_bytes() -> Result { let name = "CLICKHOUSE_TRACE_MAX_INSERT_BYTES"; @@ -22,9 +23,9 @@ fn max_insert_bytes() -> Result { .parse::() .ok() .filter(|value| *value > 0) - .ok_or(Error::InvalidLimit(name)), + .ok_or(StorageError::InvalidLimit(name).into()), Err(std::env::VarError::NotPresent) => Ok(64 * 1024 * 1024), - Err(_) => Err(Error::InvalidLimit(name)), + Err(_) => Err(StorageError::InvalidLimit(name).into()), } } @@ -55,7 +56,11 @@ pub async fn insert_rows( pub fn encode_rows(rows: Vec) -> Result { let body = write_rows(&rows, None, Vec::new(), usize::MAX)?; - String::from_utf8(body).map_err(|_| Error::InvalidRow) + String::from_utf8(body).map_err(invalid_row) +} + +fn invalid_row(error: impl std::error::Error + Send + Sync + 'static) -> Error { + StorageError::InvalidRow(Source::new(error)).into() } fn prepare_insert( @@ -73,9 +78,9 @@ fn prepare_insert( )?; let body = encoder .into_inner() - .map_err(|_| Error::InvalidRow)? + .map_err(|error| invalid_row(error.into_error()))? .finish() - .map_err(|_| Error::InvalidRow)?; + .map_err(invalid_row)?; Ok((token, body)) } @@ -102,7 +107,7 @@ impl Write for LimitedWriter { fn write(&mut self, bytes: &[u8]) -> std::io::Result { if bytes.len() > self.remaining { self.exceeded = true; - return Err(std::io::Error::other(Error::InsertTooLarge)); + return Err(std::io::Error::other(StorageError::InsertTooLarge)); } let written = self.inner.write(bytes)?; self.remaining -= written; @@ -126,17 +131,18 @@ fn write_rows( exceeded: false, }; for (index, row) in rows.iter().enumerate() { + let row = EncodedRow::new(row, received_ms)?; let result = (|| { if index != 0 { writer.write_all(b"\n").map_err(serde_json::Error::io)?; } - serde_json::to_writer(&mut writer, &EncodedRow { row, received_ms }) + serde_json::to_writer(&mut writer, &row) })(); - if result.is_err() { + if let Err(error) = result { return Err(if writer.exceeded { - Error::InsertTooLarge + StorageError::InsertTooLarge.into() } else { - Error::InvalidRow + invalid_row(error) }); } } @@ -144,25 +150,37 @@ fn write_rows( } struct EncodedRow<'a> { - row: &'a InsertRow, + fields: Vec<(&'a str, Cow<'a, Value>)>, received_ms: Option, } +impl<'a> EncodedRow<'a> { + fn new(row: &'a InsertRow, received_ms: Option) -> Result { + let fields = row + .iter() + .map(|(name, value)| Ok((name.as_str(), insert_value(name, value)?))) + .collect::>()?; + Ok(Self { + fields, + received_ms, + }) + } +} + impl Serialize for EncodedRow<'_> { fn serialize(&self, serializer: S) -> Result { let mut map = serializer.serialize_map(None)?; let mut received_ms = self.received_ms; - for (name, value) in self.row { - if name.as_str() >= "EngineReceivedMs" + for (name, value) in &self.fields { + if *name >= "EngineReceivedMs" && let Some(timestamp) = received_ms.take() { map.serialize_entry("EngineReceivedMs", ×tamp)?; } - if name == "EngineReceivedMs" && self.received_ms.is_some() { + if *name == "EngineReceivedMs" && self.received_ms.is_some() { continue; } - let value = insert_value(name, value).map_err(serde::ser::Error::custom)?; - map.serialize_entry(name, &value)?; + map.serialize_entry(name, value)?; } if let Some(timestamp) = received_ms { map.serialize_entry("EngineReceivedMs", ×tamp)?; @@ -171,21 +189,23 @@ impl Serialize for EncodedRow<'_> { } } +const TIMESTAMP_FIELDS: [&str; 3] = ["start_time", "end_time", "completion_start_time"]; + fn insert_value<'a>(name: &str, value: &'a Value) -> Result, Error> { - let multiplier = match name { - "start_time" | "end_time" | "completion_start_time" => 1_000_000, - _ => return Ok(Cow::Borrowed(value)), + let Some(&field) = TIMESTAMP_FIELDS.iter().find(|field| **field == name) else { + return Ok(Cow::Borrowed(value)); }; - if name == "completion_start_time" && value.is_null() { + if field == "completion_start_time" && value.is_null() { return Ok(Cow::Borrowed(value)); } - let timestamp = value.as_i64().ok_or(Error::InvalidRow)?; - let datetime = OffsetDateTime::from_unix_timestamp_nanos(i128::from(timestamp) * multiplier) - .map_err(|_| Error::InvalidRow)?; + let out_of_range = |source| Error::TimestampOutOfRange { field, source }; + let timestamp = value.as_i64().ok_or(Error::NonIntegerTimestamp { field })?; + let datetime = OffsetDateTime::from_unix_timestamp_nanos(i128::from(timestamp) * 1_000_000) + .map_err(|error| out_of_range(Source::new(error)))?; datetime .format(&Rfc3339) .map(|value| Cow::Owned(Value::String(value))) - .map_err(|_| Error::InvalidRow) + .map_err(|error| out_of_range(Source::new(error))) } #[cfg(test)] @@ -204,10 +224,11 @@ mod tests { ]; let encoded = write_rows(&rows, None, Vec::new(), usize::MAX).unwrap(); assert!(write_rows(&rows, None, Vec::new(), encoded.len()).is_ok()); - assert!(matches!( - write_rows(&rows, None, Vec::new(), encoded.len() - 1), - Err(Error::InsertTooLarge) - )); + assert!( + write_rows(&rows, None, Vec::new(), encoded.len() - 1) + .unwrap_err() + .is_insert_too_large() + ); } #[rstest] @@ -264,10 +285,11 @@ mod tests { fn stamped_insert_enforces_the_encoded_limit() { let rows = vec![BTreeMap::new()]; assert!(prepare_insert(&rows, 1, 22).is_ok()); - assert!(matches!( - prepare_insert(&rows, 1, 21), - Err(Error::InsertTooLarge) - )); + assert!( + prepare_insert(&rows, 1, 21) + .unwrap_err() + .is_insert_too_large() + ); } #[rstest] @@ -282,15 +304,36 @@ mod tests { assert_eq!(insert_value(field, &input).unwrap().as_ref(), &expected); } + fn rejected_start_time(input: Value) -> Error { + prepare_insert(&[BTreeMap::from([("start_time".into(), input)])], 456, 4096).unwrap_err() + } + #[rstest] #[case::fractional(json!(1.5))] #[case::string(json!("1234"))] #[case::null(Value::Null)] - #[case::out_of_range(json!(i64::MAX))] - fn invalid_spend_dates_fail_before_transport(#[case] input: Value) { + fn non_integer_spend_dates_fail_before_transport(#[case] input: Value) { + let error = rejected_start_time(input); + assert!(error.is_request()); assert!(matches!( - prepare_insert(&[BTreeMap::from([("start_time".into(), input)])], 456, 4096), - Err(Error::InvalidRow) + error, + Error::NonIntegerTimestamp { + field: "start_time" + } )); } + + #[rstest] + fn out_of_range_spend_dates_keep_their_cause() { + let error = rejected_start_time(json!(i64::MAX)); + assert!(error.is_request()); + let cause = std::error::Error::source(&error) + .and_then(|cause| cause.downcast_ref::()) + .expect("time cause"); + assert!( + cause + .downcast_ref::() + .is_some() + ); + } } diff --git a/litellm-rust/crates/spend-clickhouse/src/lib.rs b/litellm-rust/crates/spend-clickhouse/src/lib.rs index f4c108b1e7f..9da658aa3e8 100644 --- a/litellm-rust/crates/spend-clickhouse/src/lib.rs +++ b/litellm-rust/crates/spend-clickhouse/src/lib.rs @@ -4,7 +4,7 @@ mod schema; pub use error::Error; pub use insert::{encode_rows, insert_rows}; -use litellm_storage_clickhouse::Storage; +use litellm_storage_clickhouse::{Error as StorageError, Storage}; pub use schema::ensure_schema; #[derive(Clone)] @@ -16,7 +16,7 @@ pub struct Config { impl Config { pub fn new(database: String, url: &str, retention_days: u32) -> Result { if retention_days == 0 { - return Err(Error::InvalidSchema); + return Err(StorageError::InvalidSchema.into()); } Ok(Self { storage: Storage::new(database, url)?, diff --git a/litellm-rust/crates/spend-clickhouse/tests/storage.rs b/litellm-rust/crates/spend-clickhouse/tests/storage.rs index 2b3eb75c658..81b6527f9e1 100644 --- a/litellm-rust/crates/spend-clickhouse/tests/storage.rs +++ b/litellm-rust/crates/spend-clickhouse/tests/storage.rs @@ -77,7 +77,7 @@ async fn database() -> Database { 7, ) .unwrap(), - client: Client::no_redirect_for_test(), + client: Client::for_test(), } } diff --git a/litellm-rust/crates/spend-clickhouse/tests/transport.rs b/litellm-rust/crates/spend-clickhouse/tests/transport.rs index ffc3423f65e..49a4b365135 100644 --- a/litellm-rust/crates/spend-clickhouse/tests/transport.rs +++ b/litellm-rust/crates/spend-clickhouse/tests/transport.rs @@ -29,7 +29,7 @@ async fn spend_insert_controls_target_and_retry_settings() { .mount(&server) .await; let config = Config::new("spend_test".into(), &format!("{}?query=DROP&async_insert=0&wait_for_async_insert=0&input_format_skip_unknown_fields=1&database=wrong&readonly=1", server.uri()), 7).unwrap(); - let client = Client::no_redirect_for_test(); + let client = Client::for_test(); let row = BTreeMap::from([ ("request_id".into(), json!("request")), ("start_time".into(), json!(1234)), @@ -77,7 +77,7 @@ async fn spend_insert_preserves_storage_failure(#[case] status: u16) { .await; let config = Config::new("spend_test".into(), &server.uri(), 7).unwrap(); let error = insert_rows( - &Client::no_redirect_for_test(), + &Client::for_test(), config.storage().writer(), "spend_test", vec![BTreeMap::from([("request_id".into(), json!("request"))])], @@ -95,7 +95,7 @@ async fn empty_spend_insert_does_not_contact_storage() { let server = MockServer::start().await; let config = Config::new("spend_test".into(), &server.uri(), 7).unwrap(); insert_rows( - &Client::no_redirect_for_test(), + &Client::for_test(), config.storage().writer(), "spend_test", vec![], @@ -116,7 +116,7 @@ async fn failed_schema_setup_is_reported() { .await; let config = Config::new("spend_test".into(), &server.uri(), 7).unwrap(); assert!(matches!( - ensure_schema(&Client::no_redirect_for_test(), &config).await, + ensure_schema(&Client::for_test(), &config).await, Err(Error::Storage( litellm_storage_clickhouse::Error::SchemaFailed(403) )) diff --git a/litellm-rust/crates/storage-clickhouse/Cargo.toml b/litellm-rust/crates/storage-clickhouse/Cargo.toml index 39d04f2de5d..8b985fc40d8 100644 --- a/litellm-rust/crates/storage-clickhouse/Cargo.toml +++ b/litellm-rust/crates/storage-clickhouse/Cargo.toml @@ -8,6 +8,7 @@ repository.workspace = true [dependencies] flate2.workspace = true +litellm-error.workspace = true litellm-http.workspace = true serde.workspace = true serde_json.workspace = true @@ -17,6 +18,7 @@ thiserror.workspace = true url.workspace = true [dev-dependencies] +litellm-error.workspace = true litellm-http = { workspace = true, features = ["test-support"] } rstest.workspace = true testcontainers-modules = { workspace = true, features = ["clickhouse"] } diff --git a/litellm-rust/crates/storage-clickhouse/src/error.rs b/litellm-rust/crates/storage-clickhouse/src/error.rs index fa0c5eabd73..ef7b5046455 100644 --- a/litellm-rust/crates/storage-clickhouse/src/error.rs +++ b/litellm-rust/crates/storage-clickhouse/src/error.rs @@ -1,21 +1,23 @@ +use litellm_error::Source; + #[derive(Clone, Debug, thiserror::Error)] pub enum Error { #[error("invalid ClickHouse insert row")] - InvalidRow, + InvalidRow(#[source] Source), #[error("{0} must be a positive integer")] InvalidLimit(&'static str), #[error("invalid ClickHouse insert table")] InvalidTable, #[error("invalid ClickHouse HTTP URL")] - InvalidUrl, + InvalidUrl(#[source] url::ParseError), + #[error("ClickHouse URL must use http or https and name a host")] + UnsupportedUrl, #[error("database must be a nonempty SQL identifier and retention must be positive")] InvalidSchema, #[error("SQL query must not be empty")] EmptySql, #[error("invalid ClickHouse query parameters")] - InvalidParameters, - #[error("unknown ClickHouse read query")] - InvalidQuery, + InvalidParameters(#[source] Source), #[error("ClickHouse query failed with HTTP status {0}")] QueryFailed(u16), #[error("ClickHouse insert failed with HTTP status {0}")] @@ -24,10 +26,60 @@ pub enum Error { InsertTooLarge, #[error("ClickHouse schema setup failed with HTTP status {0}")] SchemaFailed(u16), + #[error("ClickHouse migrations are forward-only")] + Irreversible, #[error("ClickHouse query exceeded the response size limit")] ResponseTooLarge, - #[error("ClickHouse returned an invalid or failed JSON query response")] - InvalidResponse, - #[error("ClickHouse query transport failed")] - Transport, + #[error("ClickHouse returned an invalid response")] + InvalidResponse(#[source] Source), + #[error("ClickHouse returned a failed or unexpected response")] + UnexpectedResponse, + #[error("ClickHouse transport failed")] + Transport(#[from] litellm_http::Error), +} + +impl Error { + pub fn is_request(&self) -> bool { + match self { + Self::InvalidRow(_) + | Self::InvalidLimit(_) + | Self::InvalidTable + | Self::InvalidSchema + | Self::EmptySql + | Self::InvalidParameters(_) => true, + Self::InvalidUrl(_) + | Self::UnsupportedUrl + | Self::QueryFailed(_) + | Self::InsertFailed(_) + | Self::InsertTooLarge + | Self::SchemaFailed(_) + | Self::Irreversible + | Self::ResponseTooLarge + | Self::InvalidResponse(_) + | Self::UnexpectedResponse + | Self::Transport(_) => false, + } + } + + pub fn is_insert_too_large(&self) -> bool { + match self { + Self::InsertTooLarge => true, + Self::InvalidRow(_) + | Self::InvalidLimit(_) + | Self::InvalidTable + | Self::InvalidUrl(_) + | Self::UnsupportedUrl + | Self::InvalidSchema + | Self::EmptySql + | Self::InvalidParameters(_) + | Self::QueryFailed(_) + | Self::InsertFailed(_) + | Self::SchemaFailed(_) + | Self::Irreversible + | Self::ResponseTooLarge + | Self::InvalidResponse(_) + | Self::UnexpectedResponse + | Self::Transport(_) => false, + } + } } diff --git a/litellm-rust/crates/storage-clickhouse/src/insert.rs b/litellm-rust/crates/storage-clickhouse/src/insert.rs index 1cdad1897c1..29837359f0b 100644 --- a/litellm-rust/crates/storage-clickhouse/src/insert.rs +++ b/litellm-rust/crates/storage-clickhouse/src/insert.rs @@ -1,6 +1,7 @@ use std::{io::Write, time::Duration}; use flate2::{Compression, write::GzEncoder}; +use litellm_error::Source; use litellm_http::Client; use crate::{Connection, Error, valid_identifier}; @@ -34,13 +35,15 @@ pub async fn insert_encoded_rows( return Err(Error::InvalidTable); } let mut encoder = GzEncoder::new(Vec::new(), Compression::default()); - encoder - .write_all(encoded.as_bytes()) - .map_err(|_| Error::InvalidRow)?; - let body = encoder.finish().map_err(|_| Error::InvalidRow)?; + encoder.write_all(encoded.as_bytes()).map_err(invalid_row)?; + let body = encoder.finish().map_err(invalid_row)?; insert_compressed_rows(client, connection, database, table, token, body).await } +fn invalid_row(error: std::io::Error) -> Error { + Error::InvalidRow(Source::new(error)) +} + pub async fn insert_compressed_rows( client: &Client, connection: &Connection, @@ -91,7 +94,7 @@ pub async fn insert_compressed_rows( .body(body) .send() .await - .map_err(|_| Error::Transport)?; + .map_err(litellm_http::Error::from)?; if !response.status().is_success() { return Err(Error::InsertFailed(response.status().as_u16())); } diff --git a/litellm-rust/crates/storage-clickhouse/src/lib.rs b/litellm-rust/crates/storage-clickhouse/src/lib.rs index e2ef62d1bc3..60a4e77a36c 100644 --- a/litellm-rust/crates/storage-clickhouse/src/lib.rs +++ b/litellm-rust/crates/storage-clickhouse/src/lib.rs @@ -16,9 +16,9 @@ pub struct Connection { impl Connection { pub fn parse(value: &str) -> Result { - let url = Url::parse(value).map_err(|_| Error::InvalidUrl)?; + let url = Url::parse(value).map_err(Error::InvalidUrl)?; if !matches!(url.scheme(), "http" | "https") || url.host().is_none() { - return Err(Error::InvalidUrl); + return Err(Error::UnsupportedUrl); } Ok(Self { url }) } @@ -33,11 +33,11 @@ impl Connection { connection .url .set_username(user) - .map_err(|_| Error::InvalidUrl)?; + .map_err(|()| Error::UnsupportedUrl)?; connection .url .set_password(Some(password)) - .map_err(|_| Error::InvalidUrl)?; + .map_err(|()| Error::UnsupportedUrl)?; let pairs: Vec<_> = connection .url .query_pairs() diff --git a/litellm-rust/crates/storage-clickhouse/src/migrate.rs b/litellm-rust/crates/storage-clickhouse/src/migrate.rs index c249020faaf..4da26baa681 100644 --- a/litellm-rust/crates/storage-clickhouse/src/migrate.rs +++ b/litellm-rust/crates/storage-clickhouse/src/migrate.rs @@ -12,7 +12,7 @@ use sqlx::{ migrate::{AppliedMigration, Migrate, MigrateError, Migration}, }; -use crate::{Connection, Error, READ_LIMITS, valid_identifier}; +use crate::{Connection, Error, READ_LIMITS, read::invalid_response, valid_identifier}; pub async fn execute_statement( client: &Client, @@ -22,7 +22,7 @@ pub async fn execute_statement( ) -> Result<(), Error> { let body = execute_sql(client, connection, sql, timeout).await?; if !body.trim().is_empty() { - return Err(Error::InvalidResponse); + return Err(Error::UnexpectedResponse); } Ok(()) } @@ -56,18 +56,18 @@ async fn execute_sql( .body(sql.to_owned()) .send() .await - .map_err(|_| Error::Transport)?; + .map_err(litellm_http::Error::from)?; if !response.status().is_success() { return Err(Error::SchemaFailed(response.status().as_u16())); } let mut body = Vec::new(); - while let Some(chunk) = response.chunk().await.map_err(|_| Error::Transport)? { + while let Some(chunk) = response.chunk().await.map_err(litellm_http::Error::from)? { if body.len() + chunk.len() > READ_LIMITS.response_bytes { return Err(Error::ResponseTooLarge); } body.extend_from_slice(&chunk); } - String::from_utf8(body).map_err(|_| Error::InvalidResponse) + String::from_utf8(body).map_err(invalid_response) } /// The startup runner records success after execution, never marks migrations dirty, and skips locks @@ -131,13 +131,13 @@ fn encode_hex(bytes: &[u8]) -> String { fn decode_hex(value: &str) -> Result, Error> { let (pairs, remainder) = value.as_bytes().as_chunks::<2>(); if !remainder.is_empty() { - return Err(Error::InvalidResponse); + return Err(Error::UnexpectedResponse); } pairs .iter() .map(|pair| { - let high = decode_hex_digit(pair[0]).ok_or(Error::InvalidResponse)?; - let low = decode_hex_digit(pair[1]).ok_or(Error::InvalidResponse)?; + let high = decode_hex_digit(pair[0]).ok_or(Error::UnexpectedResponse)?; + let low = decode_hex_digit(pair[1]).ok_or(Error::UnexpectedResponse)?; Ok((high << 4) | low) }) .collect() @@ -231,7 +231,7 @@ where .filter(|line| !line.trim().is_empty()) .map(|line| { let row = serde_json::from_str::(line) - .map_err(|_| migrate_error(Error::InvalidResponse))?; + .map_err(|error| migrate_error(invalid_response(error)))?; let checksum = decode_hex(&row.checksum).map_err(migrate_error)?; Ok(AppliedMigration { version: row.version, @@ -288,11 +288,7 @@ where _table_name: &'e str, _migration: &'e Migration, ) -> MigrateFuture<'e, Result> { - Box::pin(async { - Err(MigrateError::Execute(SqlxError::AnyDriverError(Box::new( - std::io::Error::other("ClickHouse migrations are forward-only"), - )))) - }) + Box::pin(async { Err(migrate_error(Error::Irreversible)) }) } } diff --git a/litellm-rust/crates/storage-clickhouse/src/read.rs b/litellm-rust/crates/storage-clickhouse/src/read.rs index 03a5522e595..40d4ad0a073 100644 --- a/litellm-rust/crates/storage-clickhouse/src/read.rs +++ b/litellm-rust/crates/storage-clickhouse/src/read.rs @@ -1,5 +1,6 @@ use std::{collections::BTreeMap, time::Duration}; +use litellm_error::Source; use litellm_http::Client; use serde::{Deserialize, Serialize, de::DeserializeOwned}; @@ -115,7 +116,7 @@ async fn execute_read_with_limits( .post(url) .timeout(Duration::from_secs(15)) .body(sql.to_owned()); - let mut response = request.send().await.map_err(|_| Error::Transport)?; + let mut response = request.send().await.map_err(litellm_http::Error::from)?; if !response.status().is_success() { if response .headers() @@ -128,20 +129,19 @@ async fn execute_read_with_limits( } let mut body = Vec::new(); - while let Some(chunk) = response.chunk().await.map_err(|_| Error::Transport)? { + while let Some(chunk) = response.chunk().await.map_err(litellm_http::Error::from)? { if body.len() + chunk.len() > limits.response_bytes { return Err(Error::ResponseTooLarge); } body.extend_from_slice(&chunk); } - let json: serde_json::Value = - serde_json::from_slice(&body).map_err(|_| Error::InvalidResponse)?; + let json: serde_json::Value = serde_json::from_slice(&body).map_err(invalid_response)?; if json.get("exception").is_some() || !json.get("data").is_some_and(serde_json::Value::is_array) { - return Err(Error::InvalidResponse); + return Err(Error::UnexpectedResponse); } - String::from_utf8(body).map_err(|_| Error::InvalidResponse) + String::from_utf8(body).map_err(invalid_response) } pub trait Query { @@ -158,8 +158,8 @@ struct Rows { } fn parameters(params: &T) -> Result, Error> { - let value = serde_json::to_value(params).map_err(|_| Error::InvalidParameters)?; - serde_json::from_value(value).map_err(|_| Error::InvalidParameters) + let value = serde_json::to_value(params).map_err(invalid_parameters)?; + serde_json::from_value(value).map_err(invalid_parameters) } pub async fn fetch( @@ -198,5 +198,13 @@ pub async fn fetch_json( fn decode_rows(body: &str) -> Result, Error> { serde_json::from_str::>(body) .map(|rows| rows.data) - .map_err(|_| Error::InvalidResponse) + .map_err(invalid_response) +} + +pub(crate) fn invalid_response(error: impl std::error::Error + Send + Sync + 'static) -> Error { + Error::InvalidResponse(Source::new(error)) +} + +fn invalid_parameters(error: serde_json::Error) -> Error { + Error::InvalidParameters(Source::new(error)) } diff --git a/litellm-rust/crates/storage-clickhouse/tests/migrations.rs b/litellm-rust/crates/storage-clickhouse/tests/migrations.rs index 29a85a8c4ec..09e56766891 100644 --- a/litellm-rust/crates/storage-clickhouse/tests/migrations.rs +++ b/litellm-rust/crates/storage-clickhouse/tests/migrations.rs @@ -48,7 +48,7 @@ async fn database() -> TestResult { Ok(ClickHouseDatabase { _container: container, url, - client: Client::no_redirect_for_test(), + client: Client::for_test(), }) } @@ -244,7 +244,7 @@ async fn failed_migration_is_not_recorded_and_retains_storage_error( #[rstest] fn invalid_database_identifier_is_rejected() { - let client = Client::no_redirect_for_test(); + let client = Client::for_test(); let connection = Connection::writer("http://127.0.0.1:1").expect("valid URL"); assert!(matches!( ClickHouseMigrate::new( @@ -327,7 +327,7 @@ async fn duplicate_ledger_rows_are_tolerated( #[rstest] #[tokio::test] async fn revert_reports_forward_only_error() { - let client = Client::no_redirect_for_test(); + let client = Client::for_test(); let connection = Connection::writer("http://127.0.0.1:1").expect("valid URL"); let migration = migration( 1, @@ -346,11 +346,7 @@ async fn revert_reports_forward_only_error() { .revert("_sqlx_migrations", &migration) .await .expect_err("ClickHouse migrations cannot be reverted"); - assert!( - error - .to_string() - .contains("ClickHouse migrations are forward-only") - ); + assert!(matches!(storage_error(&error), Some(Error::Irreversible))); } #[rstest] @@ -369,7 +365,7 @@ async fn applied_int64_versions_accept_numeric_and_quoted_json( ) .mount(&mock_server) .await; - let client = Client::no_redirect_for_test(); + let client = Client::for_test(); let connection = Connection::writer(&mock_server.uri()).expect("valid URL"); let migrator = migrator(vec![]); let mut adapter = ClickHouseMigrate::new( @@ -391,6 +387,7 @@ async fn applied_int64_versions_accept_numeric_and_quoted_json( #[tokio::test] async fn schema_requests_override_unsafe_connection_settings( #[future(awt)] mock_server: MockServer, + #[values("wait_end_of_query", "send_progress_in_http_headers", "async_insert")] name: &str, ) { Mock::given(method("POST")) .and(query_param("wait_end_of_query", "1")) @@ -406,7 +403,7 @@ async fn schema_requests_override_unsafe_connection_settings( mock_server.uri() ); execute_statement( - &Client::no_redirect_for_test(), + &Client::for_test(), &Connection::writer(&url).expect("valid URL"), "CREATE DATABASE IF NOT EXISTS trace_test", REQUEST_TIMEOUT, @@ -417,20 +414,14 @@ async fn schema_requests_override_unsafe_connection_settings( .received_requests() .await .expect("requests recorded"); - for name in [ - "wait_end_of_query", - "send_progress_in_http_headers", - "async_insert", - ] { - assert_eq!( - requests[0] - .url - .query_pairs() - .filter(|(key, _)| key == name) - .count(), - 1 - ); - } + assert_eq!( + requests[0] + .url + .query_pairs() + .filter(|(key, _)| key == name) + .count(), + 1 + ); } #[rstest] @@ -445,7 +436,7 @@ async fn oversized_ledger_response_is_rejected_before_migrations( ) .mount(&mock_server) .await; - let client = Client::no_redirect_for_test(); + let client = Client::for_test(); let connection = Connection::writer(&mock_server.uri()).expect("valid URL"); let migrator = migrator(vec![]); let mut adapter = ClickHouseMigrate::new( diff --git a/litellm-rust/crates/storage-clickhouse/tests/transport.rs b/litellm-rust/crates/storage-clickhouse/tests/transport.rs index f70fe52e1de..6b2c3fb8ef1 100644 --- a/litellm-rust/crates/storage-clickhouse/tests/transport.rs +++ b/litellm-rust/crates/storage-clickhouse/tests/transport.rs @@ -13,7 +13,7 @@ async fn insert_rejects_invalid_identifiers( #[case] table: &str, #[case] invalid_database: bool, ) { - let client = Client::no_redirect_for_test(); + let client = Client::for_test(); let connection = Connection::writer("http://localhost:8123").expect("valid URL"); let result = insert_encoded_rows(&client, &connection, database, table, "token", "{}").await; @@ -24,7 +24,7 @@ async fn insert_rejects_invalid_identifiers( #[rstest] #[tokio::test] async fn read_rejects_empty_sql() { - let client = Client::no_redirect_for_test(); + let client = Client::for_test(); let connection = Connection::reader("http://localhost:8123", "litellm").expect("valid URL"); assert!(matches!( @@ -55,18 +55,24 @@ impl litellm_storage_clickhouse::Query for TypedQuery { const SQL: &'static str = "SELECT typed_parameters"; } +enum Expected { + Rows, + Undecodable, + Failed, +} + #[rstest] #[case::valid( r#"{"meta":[],"data":[{"answer":"ok"}],"rows":1,"statistics":{"elapsed":0.1}}"#, - true + Expected::Rows )] -#[case::wrong_type(r#"{"data":[{"answer":1}]}"#, false)] -#[case::missing_column(r#"{"data":[{}]}"#, false)] -#[case::exception(r#"{"data":[],"exception":"failed"}"#, false)] +#[case::wrong_type(r#"{"data":[{"answer":1}]}"#, Expected::Undecodable)] +#[case::missing_column(r#"{"data":[{}]}"#, Expected::Undecodable)] +#[case::exception(r#"{"data":[],"exception":"failed"}"#, Expected::Failed)] #[tokio::test] async fn typed_fetch_encodes_parameters_and_validates_rows( #[case] body: &str, - #[case] valid: bool, + #[case] expected: Expected, ) { use litellm_storage_clickhouse::{fetch, fetch_json}; use wiremock::{ @@ -87,7 +93,7 @@ async fn typed_fetch_encodes_parameters_and_validates_rows( .expect(2) .mount(&server) .await; - let client = Client::no_redirect_for_test(); + let client = Client::for_test(); let connection = Connection::parse(&server.uri()).unwrap(); let params = QueryParams { signed: i64::MIN, @@ -98,17 +104,24 @@ async fn typed_fetch_encodes_parameters_and_validates_rows( }; let rows = fetch::(&client, &connection, ¶ms).await; let envelope = fetch_json::(&client, &connection, ¶ms).await; - if valid { - assert_eq!( - rows.unwrap(), - vec![QueryRow { - answer: "ok".into() - }] - ); - assert_eq!(envelope.unwrap(), body); - } else { - assert!(matches!(rows, Err(Error::InvalidResponse))); - assert!(matches!(envelope, Err(Error::InvalidResponse))); + match expected { + Expected::Rows => { + assert_eq!( + rows.unwrap(), + vec![QueryRow { + answer: "ok".into() + }] + ); + assert_eq!(envelope.unwrap(), body); + } + Expected::Undecodable => { + assert!(matches!(rows, Err(Error::InvalidResponse(_)))); + assert!(matches!(envelope, Err(Error::InvalidResponse(_)))); + } + Expected::Failed => { + assert!(matches!(rows, Err(Error::UnexpectedResponse))); + assert!(matches!(envelope, Err(Error::UnexpectedResponse))); + } } } @@ -131,7 +144,7 @@ async fn server_result_limits_allow_smaller_pages_without_retrying_other_failure .await; let connection = Connection::parse(&server.uri()).unwrap(); let error = execute_read( - &Client::no_redirect_for_test(), + &Client::for_test(), &connection, "SELECT 1", &BTreeMap::new(), @@ -145,21 +158,23 @@ async fn server_result_limits_allow_smaller_pages_without_retrying_other_failure } } -#[test] -fn insert_timeout_environment_controls_transport() { - for value in ["1", "3", "0", "invalid"] { - let result = std::process::Command::new(std::env::current_exe().unwrap()) - .args(["--exact", "insert_timeout_environment_child"]) - .env("LITELLM_TEST_INSERT_TIMEOUT", value) - .env("CLICKHOUSE_INSERT_TIMEOUT_SECONDS", value) - .output() - .unwrap(); - assert!( - result.status.success(), - "{}", - String::from_utf8_lossy(&result.stdout) - ); - } +#[rstest] +#[case::times_out("1")] +#[case::completes("3")] +#[case::zero("0")] +#[case::not_a_number("invalid")] +fn insert_timeout_environment_controls_transport(#[case] value: &str) { + let result = std::process::Command::new(std::env::current_exe().unwrap()) + .args(["--exact", "insert_timeout_environment_child"]) + .env("LITELLM_TEST_INSERT_TIMEOUT", value) + .env("CLICKHOUSE_INSERT_TIMEOUT_SECONDS", value) + .output() + .unwrap(); + assert!( + result.status.success(), + "{}", + String::from_utf8_lossy(&result.stdout) + ); } #[tokio::test] @@ -174,7 +189,7 @@ async fn insert_timeout_environment_child() { .mount(&server) .await; let result = insert_encoded_rows( - &Client::no_redirect_for_test(), + &Client::for_test(), &Connection::parse(&server.uri()).unwrap(), "traces", "otel_traces", @@ -183,7 +198,7 @@ async fn insert_timeout_environment_child() { ) .await; match value.as_str() { - "1" => assert!(matches!(result, Err(Error::Transport))), + "1" => assert!(matches!(result, Err(Error::Transport(error)) if error.dispatched())), "3" => assert!(result.is_ok()), _ => assert!(matches!( result, @@ -191,3 +206,29 @@ async fn insert_timeout_environment_child() { )), } } + +#[rstest] +#[tokio::test] +async fn unreachable_server_keeps_the_transport_cause() { + let address = std::net::TcpListener::bind("127.0.0.1:0") + .unwrap() + .local_addr() + .unwrap(); + let connection = Connection::parse(&format!("http://{address}")).unwrap(); + let error = execute_read( + &Client::for_test(), + &connection, + "SELECT 1", + &BTreeMap::new(), + ) + .await + .unwrap_err(); + let cause = std::error::Error::source(&error) + .and_then(|cause| cause.downcast_ref::()) + .expect("transport cause"); + assert!(!cause.dispatched()); + assert_ne!( + litellm_error::Report::new(&error).to_string(), + error.to_string() + ); +} diff --git a/litellm-rust/crates/testkit/Cargo.toml b/litellm-rust/crates/testkit/Cargo.toml index 97efb753384..ef3c3e6cd7e 100644 --- a/litellm-rust/crates/testkit/Cargo.toml +++ b/litellm-rust/crates/testkit/Cargo.toml @@ -8,6 +8,7 @@ publish = false [dependencies] flate2.workspace = true +litellm-http.workspace = true reqwest.workspace = true serde.workspace = true semver.workspace = true diff --git a/litellm-rust/crates/testkit/src/agent/configure.rs b/litellm-rust/crates/testkit/src/agent/configure.rs index a41bec9379a..6f1b970e8fb 100644 --- a/litellm-rust/crates/testkit/src/agent/configure.rs +++ b/litellm-rust/crates/testkit/src/agent/configure.rs @@ -5,10 +5,13 @@ use semver::Version; use crate::Error; -#[derive(Clone, Copy, Debug, PartialEq, Eq, strum::VariantArray)] +#[derive(Clone, Copy, Debug, PartialEq, Eq, strum::VariantArray, strum::Display)] pub enum Wire { + #[strum(serialize = "chat completions")] ChatCompletions, + #[strum(serialize = "messages")] Messages, + #[strum(serialize = "responses")] Responses, } diff --git a/litellm-rust/crates/testkit/src/error.rs b/litellm-rust/crates/testkit/src/error.rs index 03520d827f1..8b747c28bda 100644 --- a/litellm-rust/crates/testkit/src/error.rs +++ b/litellm-rust/crates/testkit/src/error.rs @@ -15,7 +15,7 @@ pub enum Error { Request { url: String, #[source] - source: reqwest::Error, + source: litellm_http::Error, }, #[error("{url} answered with status {status}")] Status { url: String, status: u16 }, @@ -47,10 +47,14 @@ pub enum Error { expected: String, reported: String, }, - #[error("{agent} cannot talk to the gateway over {wire:?}")] + #[error("{agent} cannot talk to the gateway over {wire}")] UnsupportedWire { agent: &'static str, wire: Wire }, - #[error("agent did not finish within {0:?}")] + #[error("agent did not finish within {} seconds", .0.as_secs_f64())] Timeout(std::time::Duration), - #[error("io failure")] - Io(#[from] io::Error), + #[error("could not install the binary into {}", dir.display())] + Install { dir: PathBuf, source: io::Error }, + #[error("could not run {}", binary.display())] + Spawn { binary: PathBuf, source: io::Error }, + #[error("could not write agent files under {}", home.display())] + WriteFiles { home: PathBuf, source: io::Error }, } diff --git a/litellm-rust/crates/testkit/src/install/fetch.rs b/litellm-rust/crates/testkit/src/install/fetch.rs index 73008f7a0da..59a61bfaa0a 100644 --- a/litellm-rust/crates/testkit/src/install/fetch.rs +++ b/litellm-rust/crates/testkit/src/install/fetch.rs @@ -38,9 +38,9 @@ impl Fetch for HttpFetch { (Some(token), true) => request.bearer_auth(token), _ => request, }; - let request_error = |source| Error::Request { + let request_error = |source: reqwest::Error| Error::Request { url: url.to_owned(), - source, + source: source.into(), }; let response = request.send().await.map_err(request_error)?; let status = response.status(); diff --git a/litellm-rust/crates/testkit/src/install/mod.rs b/litellm-rust/crates/testkit/src/install/mod.rs index 1104bcec102..73f7deec864 100644 --- a/litellm-rust/crates/testkit/src/install/mod.rs +++ b/litellm-rust/crates/testkit/src/install/mod.rs @@ -52,7 +52,13 @@ impl Installer { version: version.clone(), binary: binary.clone(), }; - if fs::try_exists(&binary).await? && probe_version(&binary, version).await.is_ok() { + let install_error = |source| Error::Install { + dir: dir.clone(), + source, + }; + if fs::try_exists(&binary).await.map_err(install_error)? + && probe_version(&binary, version).await.is_ok() + { return Ok(installed); } @@ -61,21 +67,23 @@ impl Installer { verify_sha256(&release.asset, &release.sha256, &archive)?; let contents = extract_binary(&release.packaging, &archive)?; - fs::create_dir_all(&dir).await?; + fs::create_dir_all(&dir).await.map_err(install_error)?; let staging = dir.join(format!( ".{}.{}.{}.partial", agent.binary(), std::process::id(), STAGING_COUNTER.fetch_add(1, Ordering::Relaxed) )); - fs::write(&staging, contents).await?; - fs::set_permissions(&staging, std::fs::Permissions::from_mode(0o755)).await?; - fs::rename(&staging, &binary).await?; + fs::write(&staging, contents).await.map_err(install_error)?; + fs::set_permissions(&staging, std::fs::Permissions::from_mode(0o755)) + .await + .map_err(install_error)?; + fs::rename(&staging, &binary).await.map_err(install_error)?; match probe_version(&binary, version).await { Ok(()) => Ok(installed), Err(error) => { - fs::remove_file(&binary).await?; + fs::remove_file(&binary).await.map_err(install_error)?; Err(error) } } @@ -98,7 +106,11 @@ async fn probe_version(binary: &Path, expected: &Version) -> Result<(), Error> { .env("DISABLE_AUTOUPDATER", "1") .stdin(Stdio::null()) .output() - .await?; + .await + .map_err(|source| Error::Spawn { + binary: binary.to_owned(), + source, + })?; let stdout = String::from_utf8_lossy(&output.stdout); if stdout .split_whitespace() diff --git a/litellm-rust/crates/testkit/src/session.rs b/litellm-rust/crates/testkit/src/session.rs index 6b06e756cca..cd5eb08ae2b 100644 --- a/litellm-rust/crates/testkit/src/session.rs +++ b/litellm-rust/crates/testkit/src/session.rs @@ -28,7 +28,11 @@ impl Session { ) -> Result { let home = home.into(); let spec = agent.configure(&installed.version, &settings, &home)?; - spec.write_files(&home)?; + spec.write_files(&home) + .map_err(|source| Error::WriteFiles { + home: home.clone(), + source, + })?; Ok(Self { binary: installed.binary.clone(), home, @@ -55,7 +59,11 @@ impl Session { .output(); let output = timeout(limit, child) .await - .map_err(|_| Error::Timeout(limit))??; + .map_err(|_| Error::Timeout(limit))? + .map_err(|source| Error::Spawn { + binary: self.binary.clone(), + source, + })?; let parsed = agent.parse(&self.version, &String::from_utf8_lossy(&output.stdout)); let failed_silently = !output.status.success() && parsed.errors.is_empty(); Ok(Outcome { diff --git a/litellm-rust/crates/token-counter-fast/Cargo.toml b/litellm-rust/crates/token-counter-fast/Cargo.toml index 5127dc17f22..070bec58519 100644 --- a/litellm-rust/crates/token-counter-fast/Cargo.toml +++ b/litellm-rust/crates/token-counter-fast/Cargo.toml @@ -13,6 +13,7 @@ tokenizers.workspace = true unicode-normalization-alignments = "0.1.12" [dev-dependencies] +litellm-error.workspace = true rand.workspace = true rstest.workspace = true serde.workspace = true diff --git a/litellm-rust/crates/token-counter-fast/src/error.rs b/litellm-rust/crates/token-counter-fast/src/error.rs index d2a706191ac..2cd8d5c810c 100644 --- a/litellm-rust/crates/token-counter-fast/src/error.rs +++ b/litellm-rust/crates/token-counter-fast/src/error.rs @@ -2,16 +2,25 @@ use thiserror::Error as ThisError; #[derive(Debug, ThisError)] pub enum Error { - #[error("failed to load tokenizer: {0}")] + #[error("failed to load tokenizer")] Load(#[source] tokenizers::Error), - #[error("failed to load tokenizer: tiktoken rank file: {0}")] + #[error("failed to load tokenizer from a tiktoken rank file")] Ranks(#[source] RankError), #[error("failed to load tokenizer: Unicode character classes are unavailable")] UnicodeClasses, - #[error("tokenization failed: {0}")] + #[error("tokenization failed")] Encode(#[source] tokenizers::Error), } +impl Error { + pub fn is_load(&self) -> bool { + match self { + Self::Load(_) | Self::Ranks(_) | Self::UnicodeClasses => true, + Self::Encode(_) => false, + } + } +} + #[derive(Debug, ThisError)] pub enum RankError { #[error("rank {0} is reserved")] @@ -20,8 +29,8 @@ pub enum RankError { MissingByte(u8), #[error("line without a rank: {0:?}")] MissingRank(String), - #[error("token is not base64: {0}")] + #[error("token is not base64")] InvalidToken(#[source] base64::DecodeError), - #[error("rank is not an integer: {0}")] + #[error("rank is not an integer")] InvalidRank(#[source] std::num::ParseIntError), } diff --git a/litellm-rust/crates/token-counter-fast/src/tiktoken.rs b/litellm-rust/crates/token-counter-fast/src/tiktoken.rs index f2d4de38f8c..11182e84e8d 100644 --- a/litellm-rust/crates/token-counter-fast/src/tiktoken.rs +++ b/litellm-rust/crates/token-counter-fast/src/tiktoken.rs @@ -254,8 +254,12 @@ mod tests { .err() .expect("invalid rank file"); assert!(matches!(error, Error::Ranks(_))); - assert!(error.to_string().starts_with(&format!( - "failed to load tokenizer: tiktoken rank file: {detail}" - ))); + assert!( + litellm_error::Report::new(&error) + .to_string() + .starts_with(&format!( + "failed to load tokenizer from a tiktoken rank file: {detail}" + )) + ); } } diff --git a/litellm-rust/crates/token-counter-huggingface/src/error.rs b/litellm-rust/crates/token-counter-huggingface/src/error.rs index e7f6260321b..b4e09db253f 100644 --- a/litellm-rust/crates/token-counter-huggingface/src/error.rs +++ b/litellm-rust/crates/token-counter-huggingface/src/error.rs @@ -2,10 +2,21 @@ use thiserror::Error as ThisError; #[derive(Debug, ThisError)] pub enum Error { - #[error("failed to load tokenizer: {0}")] + #[error("failed to load tokenizer")] Load(#[source] tokenizers::Error), - #[error("tokenization failed: {0}")] + #[error("invalid encoding JSON")] + EncodingJson(#[source] serde_json::Error), + #[error("tokenization failed")] Encode(#[source] tokenizers::Error), - #[error("token decoding failed: {0}")] + #[error("token decoding failed")] Decode(#[source] tokenizers::Error), } + +impl Error { + pub fn is_load(&self) -> bool { + match self { + Self::Load(_) | Self::EncodingJson(_) => true, + Self::Encode(_) | Self::Decode(_) => false, + } + } +} diff --git a/litellm-rust/crates/token-counter-huggingface/src/lib.rs b/litellm-rust/crates/token-counter-huggingface/src/lib.rs index 0acea0532f8..c3af9b42767 100644 --- a/litellm-rust/crates/token-counter-huggingface/src/lib.rs +++ b/litellm-rust/crates/token-counter-huggingface/src/lib.rs @@ -13,11 +13,11 @@ pub use tokenizers::{ }; pub fn encoding_from_json(json: &str) -> Result { - serde_json::from_str(json).map_err(|error| Error::Load(error.into())) + serde_json::from_str(json).map_err(Error::EncodingJson) } pub fn encoding_to_json(encoding: &Encoding) -> Result { - serde_json::to_string(encoding).map_err(|error| Error::Load(error.into())) + serde_json::to_string(encoding).map_err(Error::EncodingJson) } pub struct HuggingFaceTokenizer { diff --git a/litellm-rust/crates/token-counter-tiktoken/Cargo.toml b/litellm-rust/crates/token-counter-tiktoken/Cargo.toml index d1789a693a3..bca7345dcd4 100644 --- a/litellm-rust/crates/token-counter-tiktoken/Cargo.toml +++ b/litellm-rust/crates/token-counter-tiktoken/Cargo.toml @@ -7,6 +7,7 @@ repository.workspace = true [dependencies] base64.workspace = true +litellm-error.workspace = true once_cell = "1.21.3" rustc-hash = "2.1.3" thiserror.workspace = true diff --git a/litellm-rust/crates/token-counter-tiktoken/src/error.rs b/litellm-rust/crates/token-counter-tiktoken/src/error.rs index e28cbbfb620..024be00f048 100644 --- a/litellm-rust/crates/token-counter-tiktoken/src/error.rs +++ b/litellm-rust/crates/token-counter-tiktoken/src/error.rs @@ -1,5 +1,50 @@ +use std::{io, num::ParseIntError}; + +use litellm_error::Source; use thiserror::Error as ThisError; +use tiktoken_rs::{DecodeKeyError, EncodeError}; #[derive(Debug, ThisError)] -#[error("unsupported tokenizer: {0}")] -pub struct UnsupportedTokenizer(pub String); +pub enum Error { + #[error("unsupported tokenizer: {0}")] + UnsupportedTokenizer(String), + #[error("could not read tiktoken rank file {file}")] + Read { + file: &'static str, + source: io::Error, + }, + #[error("invalid tiktoken rank file")] + Ranks(#[from] RankError), + #[error("could not build the tiktoken encoder")] + Encoder(#[source] Source), + #[error("tokenization failed")] + Encode(#[source] EncodeError), + #[error("token decoding failed")] + Decode(#[source] DecodeKeyError), +} + +impl Error { + pub fn is_load(&self) -> bool { + match self { + Self::UnsupportedTokenizer(_) + | Self::Read { .. } + | Self::Ranks(_) + | Self::Encoder(_) => true, + Self::Encode(_) | Self::Decode(_) => false, + } + } +} + +#[derive(Debug, ThisError)] +pub enum RankError { + #[error("line without a rank: {0:?}")] + MissingRank(String), + #[error("token is not base64")] + InvalidToken(#[source] base64::DecodeError), + #[error("rank is not an integer")] + InvalidRank(#[source] ParseIntError), + #[error("a rank is assigned to more than one token")] + DuplicateRank, + #[error("byte 0x{0:02X} has no token")] + MissingByte(u8), +} diff --git a/litellm-rust/crates/token-counter-tiktoken/src/lib.rs b/litellm-rust/crates/token-counter-tiktoken/src/lib.rs index 30d0f820da3..c4cb786d9e4 100644 --- a/litellm-rust/crates/token-counter-tiktoken/src/lib.rs +++ b/litellm-rust/crates/token-counter-tiktoken/src/lib.rs @@ -5,8 +5,8 @@ mod ranks; use std::collections::HashSet; -pub use error::UnsupportedTokenizer; -pub use ranks::{LoadError, Vocabulary}; +pub use error::{Error, RankError}; +pub use ranks::Vocabulary; pub struct TiktokenTokenizer { encoder: &'static tiktoken_rs::CoreBPE, @@ -22,7 +22,7 @@ impl TiktokenTokenizer { pub fn from_cached_ranks( name: &str, load: impl FnOnce(&str) -> std::io::Result, - ) -> Result { + ) -> Result { let (loaded, name) = ranks::load(name, load)?; Ok(Self { encoder: &loaded.bpe, @@ -32,7 +32,7 @@ impl TiktokenTokenizer { } /// The encodings tiktoken-rs embeds, for hosts without the packaged rank files. - pub fn from_name(name: &str) -> Result { + pub fn from_name(name: &str) -> Result { let (encoder, name) = match name { "cl100k_base" => (tiktoken_rs::cl100k_base_singleton(), "cl100k_base"), "o200k_base" => (tiktoken_rs::o200k_base_singleton(), "o200k_base"), @@ -41,7 +41,7 @@ impl TiktokenTokenizer { "p50k_edit" => (tiktoken_rs::p50k_edit_singleton(), "p50k_edit"), "r50k_base" => (tiktoken_rs::r50k_base_singleton(), "r50k_base"), "gpt2" => (tiktoken_rs::r50k_base_singleton(), "gpt2"), - _ => return Err(UnsupportedTokenizer(name.to_owned())), + _ => return Err(Error::UnsupportedTokenizer(name.to_owned())), }; Ok(Self { encoder, @@ -62,12 +62,12 @@ impl TiktokenTokenizer { self.encoder.encode_ordinary(text) } - pub fn encode_special(&self, text: &str, allowed: &[String]) -> Result, String> { + pub fn encode_special(&self, text: &str, allowed: &[String]) -> Result, Error> { let allowed = allowed.iter().map(String::as_str).collect(); self.encoder .encode(text, &allowed) .map(|(ids, _)| ids) - .map_err(|error| error.to_string()) + .map_err(Error::Encode) } pub fn special_tokens(&self) -> HashSet { @@ -92,17 +92,13 @@ impl TiktokenTokenizer { (stable, completions) } - pub fn decode_bytes(&self, ids: &[u32]) -> Result, String> { - self.encoder - .decode_bytes(ids) - .map_err(|error| error.to_string()) + pub fn decode_bytes(&self, ids: &[u32]) -> Result, Error> { + self.encoder.decode_bytes(ids).map_err(Error::Decode) } - pub fn decode(&self, ids: &[u32]) -> Result { - self.encoder - .decode_bytes(ids) + pub fn decode(&self, ids: &[u32]) -> Result { + self.decode_bytes(ids) .map(|bytes| String::from_utf8_lossy(&bytes).into_owned()) - .map_err(|error| error.to_string()) } pub fn name(&self) -> &str { @@ -161,7 +157,8 @@ mod tests { #[test] fn unsupported_encoding_preserves_its_name() { - let Err(UnsupportedTokenizer(name)) = TiktokenTokenizer::from_name("unknown-encoding") + let Err(Error::UnsupportedTokenizer(name)) = + TiktokenTokenizer::from_name("unknown-encoding") else { panic!("unknown encoding must be rejected"); }; diff --git a/litellm-rust/crates/token-counter-tiktoken/src/ranks.rs b/litellm-rust/crates/token-counter-tiktoken/src/ranks.rs index 192e6f65a0b..36c30e711c1 100644 --- a/litellm-rust/crates/token-counter-tiktoken/src/ranks.rs +++ b/litellm-rust/crates/token-counter-tiktoken/src/ranks.rs @@ -1,10 +1,10 @@ use base64::{Engine, engine::general_purpose::STANDARD}; +use litellm_error::Source; use once_cell::sync::OnceCell; use rustc_hash::FxHashMap; -use thiserror::Error; use tiktoken_rs::{CoreBPE, O200K_BASE_PAT_STR, Rank}; -use crate::UnsupportedTokenizer; +use crate::error::{Error, RankError}; const CL100K: &str = "9b5ad71b2ce5302211f9c61530b329a4922fc6a4"; const O200K: &str = "fb374d419588a4632f3f557e76b4b70aebbca790"; @@ -76,22 +76,30 @@ impl Vocabulary { } } -#[derive(Debug, Error)] -pub enum LoadError { - #[error(transparent)] - Unsupported(#[from] UnsupportedTokenizer), - #[error("failed to load tiktoken ranks: {0}")] - Ranks(String), -} - /// Loads `name` once per process. The returned name is the one requested (`gpt2` stays /// `gpt2`, as `tiktoken.get_encoding("gpt2").name` does), while `gpt2` and `r50k_base` share /// one cached encoder. pub(super) fn load( name: &str, load_file: impl FnOnce(&str) -> std::io::Result, -) -> Result<(&'static Loaded, &'static str), LoadError> { - let (requested, canonical, file, cache) = match name { +) -> Result<(&'static Loaded, &'static str), Error> { + let (requested, canonical, file, cache) = encoding(name)?; + let loaded = cache.get_or_try_init(|| { + let ranks = load_file(file).map_err(|source| Error::Read { file, source })?; + build(canonical, &ranks) + })?; + Ok((loaded, requested)) +} + +type Encoding = ( + &'static str, + &'static str, + &'static str, + &'static OnceCell, +); + +fn encoding(name: &str) -> Result { + Ok(match name { "cl100k_base" => ("cl100k_base", "cl100k_base", CL100K, &CL100K_ENCODER), "o200k_base" => ("o200k_base", "o200k_base", O200K, &O200K_ENCODER), "o200k_harmony" => ("o200k_harmony", "o200k_harmony", O200K, &HARMONY_ENCODER), @@ -99,16 +107,11 @@ pub(super) fn load( "p50k_edit" => ("p50k_edit", "p50k_edit", P50K, &EDIT_ENCODER), "r50k_base" => ("r50k_base", "r50k_base", P50K, &R50K_ENCODER), "gpt2" => ("gpt2", "r50k_base", P50K, &R50K_ENCODER), - _ => return Err(UnsupportedTokenizer(name.to_owned()).into()), - }; - let loaded = cache.get_or_try_init(|| { - let ranks = load_file(file).map_err(|error| LoadError::Ranks(error.to_string()))?; - build(canonical, &ranks) - })?; - Ok((loaded, requested)) + _ => return Err(Error::UnsupportedTokenizer(name.to_owned())), + }) } -fn build(name: &str, ranks: &str) -> Result { +fn build(name: &str, ranks: &str) -> Result { let parsed = ranks .lines() .map(parse_rank) @@ -122,9 +125,11 @@ fn build(name: &str, ranks: &str) -> Result { .collect::>() .len() != encoder.len() - || (0..=u8::MAX).any(|byte| !encoder.contains_key(&[byte][..])) { - return Err(LoadError::Ranks("invalid vocabulary ranks".into())); + return Err(RankError::DuplicateRank.into()); + } + if let Some(byte) = (0..=u8::MAX).find(|byte| !encoder.contains_key(&[*byte][..])) { + return Err(RankError::MissingByte(byte).into()); } let (pattern, specials): (&str, &[(&str, Rank)]) = match name { "cl100k_base" => ( @@ -185,9 +190,12 @@ fn build(name: &str, ranks: &str) -> Result { .chain(special_tokens.values()) .copied() .max() - .ok_or_else(|| LoadError::Ranks("empty vocabulary".into()))?; - let bpe = CoreBPE::new(encoder.clone(), special_tokens.clone(), pattern) - .map_err(|error| LoadError::Ranks(error.to_string()))?; + .unwrap_or_default(); + let bpe = CoreBPE::new(encoder.clone(), special_tokens.clone(), pattern).map_err(|error| { + Error::Encoder(Source::from( + Box::::from(error), + )) + })?; Ok(Loaded { bpe, vocabulary: Vocabulary { @@ -198,16 +206,12 @@ fn build(name: &str, ranks: &str) -> Result { }) } -fn parse_rank(line: &str) -> Result<(Vec, Rank), LoadError> { +fn parse_rank(line: &str) -> Result<(Vec, Rank), RankError> { let (token, rank) = line .split_once(' ') - .ok_or_else(|| LoadError::Ranks("missing rank".into()))?; - let bytes = STANDARD - .decode(token) - .map_err(|error| LoadError::Ranks(error.to_string()))?; - let rank = rank - .parse() - .map_err(|error: std::num::ParseIntError| LoadError::Ranks(error.to_string()))?; + .ok_or_else(|| RankError::MissingRank(line.to_owned()))?; + let bytes = STANDARD.decode(token).map_err(RankError::InvalidToken)?; + let rank = rank.parse().map_err(RankError::InvalidRank)?; Ok((bytes, rank)) } @@ -226,79 +230,117 @@ mod tests { ) } - #[test] - fn packaged_encodings_match_embedded_encodings_and_reuse_successful_loads() { - for name in [ + #[rstest] + #[case::cl100k_base("cl100k_base", None)] + #[case::o200k_base("o200k_base", None)] + #[case::o200k_harmony("o200k_harmony", None)] + #[case::p50k_base("p50k_base", None)] + #[case::p50k_edit("p50k_edit", None)] + #[case::r50k_base_shared_with_gpt2("r50k_base", Some("gpt2"))] + fn packaged_encodings_load_once_and_match_embedded_encodings( + #[case] name: &str, + #[case] alias: Option<&str>, + ) { + assert!( + TiktokenTokenizer::from_cached_ranks(name, |_| { + Err(std::io::Error::other("unreadable vocabulary")) + }) + .is_err() + ); + let loads = std::sync::atomic::AtomicUsize::new(0); + let barrier = std::sync::Barrier::new(4); + let encoders = std::thread::scope(|scope| { + let tasks: Vec<_> = (0..4) + .map(|_| { + scope.spawn(|| { + barrier.wait(); + TiktokenTokenizer::from_cached_ranks(name, |file| { + loads.fetch_add(1, std::sync::atomic::Ordering::Relaxed); + read_packaged_ranks(file) + }) + .unwrap() + }) + }) + .collect(); + tasks + .into_iter() + .map(|task| task.join().unwrap()) + .collect::>() + }); + assert_eq!(loads.into_inner(), 1); + let actual = &encoders[0]; + let expected = TiktokenTokenizer::from_name(name).unwrap(); + assert_eq!(actual.special_tokens(), expected.special_tokens()); + let specials: Vec<_> = expected.special_tokens().into_iter().collect(); + let special_text = specials.join(" "); + assert_eq!( + actual.encode_special(&special_text, &specials).unwrap(), + expected.encode_special(&special_text, &specials).unwrap() + ); + assert_eq!(actual.encode(&special_text), expected.encode(&special_text)); + let cached = + TiktokenTokenizer::from_cached_ranks(name, |_| panic!("reloaded cached vocabulary")) + .unwrap(); + assert_eq!(cached.encode("cached"), expected.encode("cached")); + assert_eq!(cached.name(), name); + assert!(expected.vocabulary().is_none()); + assert_vocabulary_lookups(name, actual); + if let Some(alias) = alias { + let shared = TiktokenTokenizer::from_cached_ranks(alias, |_| { + panic!("reloaded the shared vocabulary") + }) + .unwrap(); + assert_eq!(shared.name(), alias); + assert_vocabulary_lookups(alias, &shared); + } + } + + fn uncached(name: &str) -> TiktokenTokenizer { + static BUILT: std::sync::Mutex> = + std::sync::Mutex::new(Vec::new()); + let (requested, canonical, file, _) = encoding(name).unwrap(); + let mut built = BUILT.lock().unwrap(); + let loaded = match built.iter().find(|(built, _)| *built == requested) { + Some((_, loaded)) => *loaded, + None => { + let ranks = read_packaged_ranks(file).unwrap(); + let loaded: &'static Loaded = + Box::leak(Box::new(build(canonical, &ranks).unwrap())); + built.push((requested, loaded)); + loaded + } + }; + TiktokenTokenizer { + encoder: &loaded.bpe, + vocabulary: Some(&loaded.vocabulary), + name: requested, + } + } + + #[rstest] + fn packaged_ranks_encode_like_embedded_encodings( + #[values( "cl100k_base", "o200k_base", "o200k_harmony", "p50k_base", "p50k_edit", "r50k_base", - "gpt2", - ] { - if name != "gpt2" { - assert!( - TiktokenTokenizer::from_cached_ranks(name, |_| { - Err(std::io::Error::other("unreadable vocabulary")) - }) - .is_err() - ); - } - let loads = std::sync::atomic::AtomicUsize::new(0); - let barrier = std::sync::Barrier::new(4); - let encoders = std::thread::scope(|scope| { - let tasks: Vec<_> = (0..4) - .map(|_| { - scope.spawn(|| { - barrier.wait(); - TiktokenTokenizer::from_cached_ranks(name, |file| { - loads.fetch_add(1, std::sync::atomic::Ordering::Relaxed); - read_packaged_ranks(file) - }) - .unwrap() - }) - }) - .collect(); - tasks - .into_iter() - .map(|task| task.join().unwrap()) - .collect::>() - }); - assert_eq!(loads.into_inner(), usize::from(name != "gpt2")); - let actual = &encoders[0]; - let expected = TiktokenTokenizer::from_name(name).unwrap(); - assert_eq!(actual.special_tokens(), expected.special_tokens()); - let specials: Vec<_> = expected.special_tokens().into_iter().collect(); - let special_text = specials.join(" "); - assert_eq!( - actual.encode_special(&special_text, &specials).unwrap(), - expected.encode_special(&special_text, &specials).unwrap() - ); - for text in [ - "", - "café 漢字 ع 🙂", - "a\r\nb\t ", - " hello 123456789", - &special_text, - ] { - let ids = expected.encode(text); - assert_eq!(actual.encode(text), ids, "{name}: {text:?}"); - assert_eq!(actual.count_tokens(text), ids.len(), "{name}: {text:?}"); - assert_eq!( - actual.decode_bytes(&ids).unwrap(), - expected.decode_bytes(&ids).unwrap() - ); - } - let cached = TiktokenTokenizer::from_cached_ranks(name, |_| { - panic!("reloaded cached vocabulary") - }) - .unwrap(); - assert_eq!(cached.encode("cached"), expected.encode("cached")); - assert_eq!(cached.name(), name); - assert!(expected.vocabulary().is_none()); - assert_vocabulary_lookups(name, actual); - } + "gpt2" + )] + name: &str, + #[values("", "café 漢字 ع 🙂", "a\r\nb\t ", " hello 123456789")] text: &str, + ) { + let actual = uncached(name); + let expected = TiktokenTokenizer::from_name(name).unwrap(); + + let ids = expected.encode(text); + assert_eq!(actual.encode(text), ids); + assert_eq!(actual.count_tokens(text), ids.len()); + assert_eq!( + actual.decode_bytes(&ids).unwrap(), + expected.decode_bytes(&ids).unwrap() + ); } /// The token-level lookups tiktoken's Python `Encoding` exposes, checked against the diff --git a/litellm-rust/crates/token-counter/Cargo.toml b/litellm-rust/crates/token-counter/Cargo.toml index 67e5bd60537..01ce4b6bac8 100644 --- a/litellm-rust/crates/token-counter/Cargo.toml +++ b/litellm-rust/crates/token-counter/Cargo.toml @@ -14,6 +14,7 @@ tiktoken = ["dep:litellm-token-counter-tiktoken"] [dependencies] indexmap = { version = "2.14.0", features = ["serde"] } itoa = "1.0" +litellm-error.workspace = true litellm-token-counter-fast = { workspace = true, optional = true } litellm-token-counter-huggingface = { workspace = true, optional = true } litellm-token-counter-tiktoken = { workspace = true, optional = true } diff --git a/litellm-rust/crates/token-counter/src/counter.rs b/litellm-rust/crates/token-counter/src/counter.rs index 6370d9d74f8..f3c16f93b84 100644 --- a/litellm-rust/crates/token-counter/src/counter.rs +++ b/litellm-rust/crates/token-counter/src/counter.rs @@ -1,12 +1,12 @@ use serde::Serialize; -use crate::Error; use crate::python_json; use crate::tools::format_function_definitions; use crate::types::{ ContentItem, CountableContentBlock, CountableRequest, Message, MessageContent, TextValue, ToolChoice, ToolDefinition, }; +use crate::{Error, Unsupported}; const TOKENS_PER_MESSAGE: usize = 3; const TOKENS_PER_NAME: usize = 1; @@ -53,7 +53,7 @@ impl TokenCounter { self.count_optional_text_value(request.query.as_ref())? + self.count_optional_text_value(request.documents.as_ref())? } else { - return Err(Error::MissingInput); + return Err(Unsupported::MissingInput.into()); }; Ok(InputTokenCount { model: request.model.clone(), @@ -96,7 +96,7 @@ impl TokenCounter { TextValue::Number(number) => match (number.as_i64(), number.as_u64()) { (Some(number), _) => self.count_text(itoa::Buffer::new().format(number)), (_, Some(number)) => self.count_text(itoa::Buffer::new().format(number)), - _ => Err(Error::FloatText), + _ => Err(Unsupported::FloatText.into()), }, TextValue::Text(text) => self.count_text(text), TextValue::List(items) => items @@ -143,7 +143,9 @@ impl TokenCounter { None => Ok(0), } } - ContentItem::Block(CountableContentBlock::Unsupported) => Err(Error::ContentBlock), + ContentItem::Block(CountableContentBlock::Unsupported) => { + Err(Unsupported::ContentBlock.into()) + } } } diff --git a/litellm-rust/crates/token-counter/src/error.rs b/litellm-rust/crates/token-counter/src/error.rs index 7a74138c074..89a97423c48 100644 --- a/litellm-rust/crates/token-counter/src/error.rs +++ b/litellm-rust/crates/token-counter/src/error.rs @@ -1,39 +1,66 @@ use std::string::FromUtf8Error; +use litellm_error::Source; use thiserror::Error as ThisError; #[derive(Debug, ThisError)] pub enum Error { - #[error("unsupported tokenizer: {0}")] - UnsupportedTokenizer(String), - #[error("failed to load tokenizer: {0}")] - Load(#[source] Box), - #[error("failed to load tokenizer: tiktoken rank file: {0}")] - Ranks(#[source] Box), - #[error("failed to load tokenizer: Unicode character classes are unavailable")] - UnicodeClasses, - #[error("unsupported by the rust token counter: request body could not be parsed: {0}")] - RequestParse(#[source] serde_json::Error), - #[error("unsupported by the rust token counter: request has no countable input")] - MissingInput, - #[error( - "unsupported by the rust token counter: float text values are counted by the python path" - )] - FloatText, - #[error( - "unsupported by the rust token counter: content block type is counted by the python path" - )] - ContentBlock, - #[error("unsupported by the rust token counter: array parameter without items")] - ArrayItems, - #[error("unsupported by the rust token counter: text value could not be serialized: {0}")] - JsonSerialization(#[source] serde_json::Error), - #[error("unsupported by the rust token counter: serialized text value is not UTF-8: {0}")] - JsonUtf8(#[source] FromUtf8Error), - #[error("tokenization failed: {0}")] - Encode(#[source] Box), - #[error("token decoding failed: {0}")] - Decode(String), - #[error("token counting task failed: {0}")] - Task(String), + #[cfg(feature = "fast")] + #[error(transparent)] + Fast(#[from] litellm_token_counter_fast::Error), + #[cfg(feature = "huggingface")] + #[error(transparent)] + HuggingFace(#[from] litellm_token_counter_huggingface::Error), + #[cfg(feature = "tiktoken")] + #[error(transparent)] + Tiktoken(#[from] litellm_token_counter_tiktoken::Error), + #[error("unsupported by the rust token counter")] + Unsupported(#[from] Unsupported), + #[error("token counting task failed")] + Task(#[source] Source), +} + +impl Error { + pub fn is_unsupported(&self) -> bool { + match self { + Self::Unsupported(_) => true, + #[cfg(feature = "fast")] + Self::Fast(_) => false, + #[cfg(feature = "huggingface")] + Self::HuggingFace(_) => false, + #[cfg(feature = "tiktoken")] + Self::Tiktoken(_) => false, + Self::Task(_) => false, + } + } + + pub fn is_load(&self) -> bool { + match self { + #[cfg(feature = "fast")] + Self::Fast(error) => error.is_load(), + #[cfg(feature = "huggingface")] + Self::HuggingFace(error) => error.is_load(), + #[cfg(feature = "tiktoken")] + Self::Tiktoken(error) => error.is_load(), + Self::Unsupported(_) | Self::Task(_) => false, + } + } +} + +#[derive(Debug, ThisError)] +pub enum Unsupported { + #[error("request body could not be parsed")] + RequestParse(#[source] serde_json::Error), + #[error("request has no countable input")] + MissingInput, + #[error("float text values are counted by the python path")] + FloatText, + #[error("content block type is counted by the python path")] + ContentBlock, + #[error("array parameter without items")] + ArrayItems, + #[error("text value could not be serialized")] + JsonSerialization(#[source] serde_json::Error), + #[error("serialized text value is not UTF-8")] + JsonUtf8(#[source] FromUtf8Error), } diff --git a/litellm-rust/crates/token-counter/src/fast.rs b/litellm-rust/crates/token-counter/src/fast.rs index d1f270dcdc9..3ef0021e355 100644 --- a/litellm-rust/crates/token-counter/src/fast.rs +++ b/litellm-rust/crates/token-counter/src/fast.rs @@ -1,4 +1,3 @@ -use litellm_token_counter_fast::Error as BackendError; pub use litellm_token_counter_fast::FastTokenizer; use crate::{Error, TextCodec, TokenCounter, Tokenizer}; @@ -53,17 +52,6 @@ impl Tokenizer for FastTokenizer { } } -impl From for Error { - fn from(error: BackendError) -> Self { - match error { - BackendError::Load(source) => Self::Load(source), - BackendError::Ranks(source) => Self::Ranks(source.into()), - BackendError::UnicodeClasses => Self::UnicodeClasses, - BackendError::Encode(source) => Self::Encode(source), - } - } -} - #[cfg(all(test, feature = "huggingface", feature = "tiktoken"))] mod tests { use super::*; diff --git a/litellm-rust/crates/token-counter/src/huggingface.rs b/litellm-rust/crates/token-counter/src/huggingface.rs index 43613fac8ea..5730e9ce873 100644 --- a/litellm-rust/crates/token-counter/src/huggingface.rs +++ b/litellm-rust/crates/token-counter/src/huggingface.rs @@ -1,4 +1,3 @@ -use litellm_token_counter_huggingface::Error as BackendError; pub use litellm_token_counter_huggingface::{ AddedToken, EncodeInput, Encoding, HuggingFaceTokenizer, InputSequence, PaddingDirection, PaddingParams, PaddingStrategy, TruncationDirection, TruncationParams, encoding_from_json, @@ -34,13 +33,3 @@ impl TextCodec for HuggingFaceTokenizer { HuggingFaceTokenizer::name(self) } } - -impl From for Error { - fn from(error: BackendError) -> Self { - match error { - BackendError::Load(source) => Self::Load(source), - BackendError::Encode(source) => Self::Encode(source), - BackendError::Decode(source) => Self::Decode(source.to_string()), - } - } -} diff --git a/litellm-rust/crates/token-counter/src/lib.rs b/litellm-rust/crates/token-counter/src/lib.rs index 84bf35ca2ba..c58b8cf372f 100644 --- a/litellm-rust/crates/token-counter/src/lib.rs +++ b/litellm-rust/crates/token-counter/src/lib.rs @@ -19,6 +19,6 @@ pub mod huggingface; pub mod tiktoken; pub use counter::{InputTokenCount, TokenCounter}; -pub use error::Error; +pub use error::{Error, Unsupported}; pub use tokenizer::{TextCodec, Tokenizer}; pub use types::CountableRequest; diff --git a/litellm-rust/crates/token-counter/src/python_json.rs b/litellm-rust/crates/token-counter/src/python_json.rs index 00a55ad300c..b5c074a24c7 100644 --- a/litellm-rust/crates/token-counter/src/python_json.rs +++ b/litellm-rust/crates/token-counter/src/python_json.rs @@ -6,8 +6,8 @@ use std::io::{self, Write}; use serde::Serialize; use serde_json::ser::{Formatter, Serializer}; -use super::Error; use super::types::TextValue; +use super::{Error, Unsupported}; pub(super) fn dumps(value: &TextValue) -> Result { let mut output = Vec::with_capacity(serialized_len(value)?); @@ -16,9 +16,9 @@ pub(super) fn dumps(value: &TextValue) -> Result { &mut output, PythonFormatter, )) - .map_err(Error::JsonSerialization)?; + .map_err(Unsupported::JsonSerialization)?; debug_assert_eq!(output.len(), output.capacity()); - String::from_utf8(output).map_err(Error::JsonUtf8) + String::from_utf8(output).map_err(|error| Unsupported::JsonUtf8(error).into()) } fn serialized_len(value: &TextValue) -> Result { @@ -29,7 +29,7 @@ fn serialized_len(value: &TextValue) -> Result { TextValue::Number(number) => match (number.as_i64(), number.as_u64()) { (Some(number), _) => Ok(unsigned_len(number.unsigned_abs()) + usize::from(number < 0)), (_, Some(number)) => Ok(unsigned_len(number)), - _ => Err(Error::FloatText), + _ => Err(Unsupported::FloatText.into()), }, TextValue::Text(text) => Ok(quoted_len(text)), TextValue::List(items) => items @@ -147,9 +147,9 @@ mod tests { let value = serde_json::from_str(input).expect("fixture parses"); let error = dumps(&value).expect_err("floats are declined"); - assert_eq!( - error.to_string(), - "unsupported by the rust token counter: float text values are counted by the python path" - ); + assert!(matches!( + error, + crate::Error::Unsupported(crate::Unsupported::FloatText) + )); } } diff --git a/litellm-rust/crates/token-counter/src/tiktoken.rs b/litellm-rust/crates/token-counter/src/tiktoken.rs index b95621f3ccc..136280b6115 100644 --- a/litellm-rust/crates/token-counter/src/tiktoken.rs +++ b/litellm-rust/crates/token-counter/src/tiktoken.rs @@ -1,4 +1,3 @@ -use litellm_token_counter_tiktoken::{LoadError, UnsupportedTokenizer}; pub use litellm_token_counter_tiktoken::{TiktokenTokenizer, Vocabulary, encoding_for_model}; use crate::{Error, TextCodec, TokenCounter, Tokenizer}; @@ -23,25 +22,10 @@ impl TextCodec for TiktokenTokenizer { } fn decode(&self, ids: &[u32], _skip_special_tokens: bool) -> Result { - TiktokenTokenizer::decode(self, ids).map_err(|error| Error::Decode(error.to_string())) + TiktokenTokenizer::decode(self, ids).map_err(Error::from) } fn name(&self) -> &str { TiktokenTokenizer::name(self) } } - -impl From for Error { - fn from(error: UnsupportedTokenizer) -> Self { - Self::UnsupportedTokenizer(error.0) - } -} - -impl From for Error { - fn from(error: LoadError) -> Self { - match error { - LoadError::Unsupported(error) => error.into(), - LoadError::Ranks(source) => Self::Ranks(source.into()), - } - } -} diff --git a/litellm-rust/crates/token-counter/src/tools.rs b/litellm-rust/crates/token-counter/src/tools.rs index 22150a4e4b1..a5a3fdbfabf 100644 --- a/litellm-rust/crates/token-counter/src/tools.rs +++ b/litellm-rust/crates/token-counter/src/tools.rs @@ -3,8 +3,8 @@ use std::fmt::Write; -use super::Error; use super::types::{EnumValue, Schema, SchemaType, ToolDefinition}; +use super::{Error, Unsupported}; pub(super) fn format_function_definitions(tools: &[ToolDefinition]) -> Result { ToolFormatter::new(tools.len()).format(tools) @@ -117,7 +117,7 @@ impl ToolFormatter { None => self.output.push_str("number"), }, "array" => { - let items = props.items.as_deref().ok_or(Error::ArrayItems)?; + let items = props.items.as_deref().ok_or(Unsupported::ArrayItems)?; self.write_type(items, indent)?; self.output.push_str("[]"); } @@ -298,7 +298,7 @@ mod tests { assert!(matches!( format_function_definitions(&tools), - Err(Error::ArrayItems) + Err(Error::Unsupported(Unsupported::ArrayItems)) )); } } diff --git a/litellm-rust/crates/token-counter/src/types.rs b/litellm-rust/crates/token-counter/src/types.rs index c1236f94d9a..7e1513d7706 100644 --- a/litellm-rust/crates/token-counter/src/types.rs +++ b/litellm-rust/crates/token-counter/src/types.rs @@ -5,7 +5,7 @@ use serde::de::{MapAccess, SeqAccess, Visitor}; use serde::{Deserialize, Deserializer, Serialize}; use serde_json::Number; -use super::Error; +use super::{Error, Unsupported}; /// The parts of a request body the host's budget counter reads. Chat and /// Anthropic Messages bodies carry `messages`; completions carry `prompt`; @@ -33,7 +33,7 @@ pub struct CountableRequest { impl CountableRequest { pub fn parse(body: &[u8]) -> Result { - serde_json::from_slice(body).map_err(Error::RequestParse) + serde_json::from_slice(body).map_err(|error| Unsupported::RequestParse(error).into()) } } diff --git a/litellm-rust/crates/token-counter/tests/token_counter.rs b/litellm-rust/crates/token-counter/tests/token_counter.rs index 542bd4a1fc4..cc18bad5402 100644 --- a/litellm-rust/crates/token-counter/tests/token_counter.rs +++ b/litellm-rust/crates/token-counter/tests/token_counter.rs @@ -2,7 +2,7 @@ use rstest::rstest; #[cfg(any(feature = "fast", feature = "huggingface", feature = "tiktoken"))] use litellm_token_counter::TokenCounter; -use litellm_token_counter::{CountableRequest, Error}; +use litellm_token_counter::{CountableRequest, Error, Unsupported}; #[cfg(any(feature = "fast", feature = "huggingface"))] mod json { @@ -100,7 +100,12 @@ mod json { let request = CountableRequest::parse(body).expect("shape parses"); assert!(matches!( counter(load).count_request(&request), - Err(Error::MissingInput | Error::FloatText | Error::ContentBlock | Error::ArrayItems) + Err(Error::Unsupported( + Unsupported::MissingInput + | Unsupported::FloatText + | Unsupported::ContentBlock + | Unsupported::ArrayItems + )) )); } @@ -139,7 +144,7 @@ mod json { } fn assert_loading_a_bad_tokenizer_is_a_load_error(load: JsonLoader) { - assert!(matches!(load("{}"), Err(Error::Load(_)))); + assert!(load("{}").is_err_and(|error| error.is_load())); } macro_rules! json_backend_tests { @@ -206,7 +211,7 @@ mod json { let counter = $loader(&tokenizer.to_string(false).unwrap()).unwrap(); let request = CountableRequest::parse(br#"{"prompt":"hello"}"#).unwrap(); let error = counter.count_request(&request).unwrap_err(); - assert!(matches!(error, Error::Encode(_))); + assert!(!error.is_load() && !error.is_unsupported()); assert_eq!(error.source().unwrap().to_string(), expected.to_string()); } @@ -250,7 +255,7 @@ mod json { fn shapes_outside_the_mirror_are_declined_at_parse(#[case] body: &[u8]) { assert!(matches!( CountableRequest::parse(body), - Err(Error::RequestParse(_)) + Err(Error::Unsupported(Unsupported::RequestParse(_))) )); } @@ -443,7 +448,7 @@ mod tiktoken { #[case] rank_file: &str, #[values(CL100K, O200K)] encoding: TiktokenEncoding, ) { - assert!(matches!((encoding.load)(rank_file), Err(Error::Ranks(_)))); + assert!((encoding.load)(rank_file).is_err_and(|error| error.is_load())); } } @@ -452,6 +457,7 @@ mod tiktoken { fn unsupported_encoding_reaches_the_counter_caller() { assert!(matches!( TokenCounter::from_tiktoken("unknown-encoding"), - Err(Error::UnsupportedTokenizer(name)) if name == "unknown-encoding" + Err(error) if error.is_load() + && litellm_error::Report::new(&error).to_string().contains("unknown-encoding") )); } diff --git a/litellm/__init__.py b/litellm/__init__.py index 41e3fa34323..5e8f4246cef 100644 --- a/litellm/__init__.py +++ b/litellm/__init__.py @@ -39,6 +39,7 @@ from litellm._logging import ( turn_on_json, log_level, ) +from litellm._logging import suppress_startup_output as suppress_startup_output import re from litellm.constants import ( DEFAULT_BATCH_SIZE, @@ -591,7 +592,7 @@ vertex_ai_safety_settings: Optional[dict] = None ####### COMPLETION MODELS ################### from typing import Set -open_ai_chat_completion_models: Set = set() +open_ai_chat_completion_models: Set[str] = set() open_ai_text_completion_models: Set = set() cohere_models: Set = set() cohere_chat_models: Set = set() @@ -619,6 +620,8 @@ vertex_openai_models: Set = set() vertex_minimax_models: Set = set() vertex_moonshot_models: Set = set() vertex_zai_models: Set = set() +vertex_qwen_models: Final[Set[str]] = set() +vertex_ai_models: Final[Set[str]] = set() ai21_models: Set = set() ai21_chat_models: Set = set() nlp_cloud_models: Set = set() @@ -635,6 +638,7 @@ watsonx_models: Set = set() gemini_models: Set = set() xai_models: Set = set() zai_models: Set = set() +bigmodel_models: Final[set[str]] = set() # mutable-ok: provider registry is populated and extended at runtime deepseek_models: Set = set() tencent_models: Set = set() runwayml_models: Set = set() @@ -681,6 +685,8 @@ moonshot_models: Set = set() publicai_models: Set = set() darkbloom_models: Set = set() openinfer_models: Final[Set[str]] = set() +streamlake_models: Final[Set[str]] = set() +zerogpu_models: Final[Set[str]] = set() v0_models: Set = set() morph_models: Set = set() opencode_go_models: Final[set[str]] = set() # mutable-ok: populated when the shared model catalog loads @@ -710,6 +716,7 @@ transcribe_models: Set = set() gigachat_models: Set = set() llamagate_models: Set = set() coralbricks_models: Set[str] = set() +aiand_models: Set[str] = set() reducto_models: Set = set() bedrock_mantle_models: Set = set() @@ -830,6 +837,10 @@ def _populate_provider_model_sets(model_cost_map: Mapping[str, Mapping[str, obje elif value.get("litellm_provider") == "vertex_ai-zai_models": key = key.replace("vertex_ai/", "") vertex_zai_models.add(key) + elif value.get("litellm_provider") == "vertex_ai-qwen_models": + vertex_qwen_models.add(key.removeprefix("vertex_ai/")) + elif value.get("litellm_provider") == "vertex_ai": + vertex_ai_models.add(key.removeprefix("vertex_ai/")) elif value.get("litellm_provider") == "ai21": if value.get("mode") == "chat": ai21_chat_models.add(key) @@ -874,6 +885,8 @@ def _populate_provider_model_sets(model_cost_map: Mapping[str, Mapping[str, obje xai_models.add(key) elif value.get("litellm_provider") == "zai": zai_models.add(key) + elif value.get("litellm_provider") == "bigmodel": + bigmodel_models.add(key) elif value.get("litellm_provider") == "fal_ai": fal_ai_models.add(key) elif value.get("litellm_provider") == "deepseek": @@ -968,6 +981,10 @@ def _populate_provider_model_sets(model_cost_map: Mapping[str, Mapping[str, obje darkbloom_models.add(key) elif value.get("litellm_provider") == "openinfer": openinfer_models.add(key) + elif value.get("litellm_provider") == "streamlake": + streamlake_models.add(key) + elif value.get("litellm_provider") == "zerogpu": + zerogpu_models.add(key) elif value.get("litellm_provider") == "v0": v0_models.add(key) elif value.get("litellm_provider") == "morph": @@ -1022,6 +1039,8 @@ def _populate_provider_model_sets(model_cost_map: Mapping[str, Mapping[str, obje llamagate_models.add(key) elif value.get("litellm_provider") == "coralbricks": coralbricks_models.add(key) + elif value.get("litellm_provider") == "aiand": + aiand_models.add(key) elif value.get("litellm_provider") == "reducto": reducto_models.add(key) elif value.get("litellm_provider") == "bedrock_mantle": @@ -1098,6 +1117,7 @@ model_list = list( | text_completion_inception_models | xai_models | zai_models + | bigmodel_models | fal_ai_models | deepseek_models | modelscope_models @@ -1139,6 +1159,8 @@ model_list = list( | publicai_models | darkbloom_models | openinfer_models + | streamlake_models + | zerogpu_models | v0_models | morph_models | opencode_go_models @@ -1159,6 +1181,7 @@ model_list = list( | reducto_models | bedrock_mantle_models | coralbricks_models + | aiand_models | set(clarifai_models) ) @@ -1192,7 +1215,16 @@ def _build_models_by_provider() -> dict: | vertex_deepseek_models | vertex_minimax_models | vertex_moonshot_models - | vertex_zai_models, + | vertex_zai_models + | vertex_qwen_models + | vertex_mistral_models + | vertex_llama3_models + | vertex_ai_ai21_models + | vertex_openai_models + | vertex_ai_image_models + | vertex_ai_video_models + | vertex_embedding_models + | vertex_ai_models, "ai21": ai21_models | ai21_chat_models, "bedrock": bedrock_models | bedrock_converse_models, "petals": petals_models, @@ -1209,6 +1241,7 @@ def _build_models_by_provider() -> dict: "text-completion-inception": text_completion_inception_models, "xai": xai_models, "zai": zai_models, + "bigmodel": bigmodel_models, "fal_ai": fal_ai_models, "deepseek": deepseek_models, "tencent": tencent_models, @@ -1257,6 +1290,8 @@ def _build_models_by_provider() -> dict: "publicai": publicai_models, "darkbloom": darkbloom_models, "openinfer": openinfer_models, + "streamlake": streamlake_models, + "zerogpu": zerogpu_models, "v0": v0_models, "morph": morph_models, "opencode_go": opencode_go_models, @@ -1283,6 +1318,7 @@ def _build_models_by_provider() -> dict: "gigachat": gigachat_models, "llamagate": llamagate_models, "coralbricks": coralbricks_models, + "aiand": aiand_models, "reducto": reducto_models, "bedrock_mantle": bedrock_mantle_models, } @@ -1326,7 +1362,6 @@ all_embedding_models = ( ) ####### IMAGE GENERATION MODELS ################### -openai_image_generation_models = ["dall-e-2", "dall-e-3"] ####### VIDEO GENERATION MODELS ################### openai_video_generation_models = ["sora-2"] @@ -1444,6 +1479,7 @@ from .exceptions import ( Timeout, APIConnectionError, UnsupportedParamsError, + UnsupportedEndpointError as UnsupportedEndpointError, APIResponseValidationError, UnprocessableEntityError, InternalServerError, @@ -1733,6 +1769,9 @@ if TYPE_CHECKING: from .llms.lm_studio.decisions.transformation import ( LMStudioDecisionsConfig as LMStudioDecisionsConfig, ) + from .llms.ollama.decisions.transformation import ( + OllamaDecisionsConfig as OllamaDecisionsConfig, + ) from .llms.laya.decisions.transformation import ( LayaDecisionsConfig as LayaDecisionsConfig, ) diff --git a/litellm/_lazy_imports_registry.py b/litellm/_lazy_imports_registry.py index f43e369e092..599234bab1a 100644 --- a/litellm/_lazy_imports_registry.py +++ b/litellm/_lazy_imports_registry.py @@ -171,6 +171,7 @@ LLM_CONFIG_NAMES: Final = ( "DatabricksDecisionsConfig", "HostedVLLMDecisionsConfig", "LMStudioDecisionsConfig", + "OllamaDecisionsConfig", "LayaDecisionsConfig", "BespokeDecisionsConfig", "OpenAIDecisionsConfig", @@ -749,6 +750,7 @@ _LLM_CONFIGS_IMPORT_MAP: Final = { "HostedVLLMDecisionsConfig", ), "LMStudioDecisionsConfig": (".llms.lm_studio.decisions.transformation", "LMStudioDecisionsConfig"), + "OllamaDecisionsConfig": (".llms.ollama.decisions.transformation", "OllamaDecisionsConfig"), "LayaDecisionsConfig": (".llms.laya.decisions.transformation", "LayaDecisionsConfig"), "BespokeDecisionsConfig": (".llms.bespoke.decisions.transformation", "BespokeDecisionsConfig"), "OpenAIDecisionsConfig": (".llms.openai.decisions.transformation", "OpenAIDecisionsConfig"), diff --git a/litellm/_logging.py b/litellm/_logging.py index 8974f85f517..5279cb233b4 100644 --- a/litellm/_logging.py +++ b/litellm/_logging.py @@ -10,10 +10,12 @@ import sys from collections.abc import Iterator, Mapping from datetime import datetime from logging import Formatter +from types import FrameType from typing import Final, TextIO from urllib.parse import unquote from pydantic import TypeAdapter +from typing_extensions import ReadOnly, TypedDict import litellm from litellm.constants import ( @@ -598,6 +600,7 @@ _LOG_FORMAT_PREFIX: Final = "%(asctime)s - %(name)s:%(levelname)s" _LOG_FORMAT_SUFFIX: Final = ": %(filename)s:%(lineno)s - %(message)s" _PLAIN_LOG_FORMAT: Final = _LOG_FORMAT_PREFIX + _LOG_FORMAT_SUFFIX _COLOR_LOG_FORMAT: Final = f"\033[92m{_LOG_FORMAT_PREFIX}\033[0m{_LOG_FORMAT_SUFFIX}" +_ANSI_ESCAPE: Final = re.compile(r"\x1b\[[0-9;]*m") def _stream_is_tty(stream: TextIO | None) -> bool: @@ -612,15 +615,28 @@ def _stream_is_tty(stream: TextIO | None) -> bool: return False -def _plain_log_format(stdout: TextIO | None, stderr: TextIO | None) -> str: - """The plain-text log format, colorized only when both streams are an interactive terminal. +def _color_enabled(stream: TextIO | None) -> bool: + """True when ANSI colors written to the stream reach an interactive terminal. Honors the NO_COLOR convention from no-color.org: color is disabled when NO_COLOR is present with a non-empty value. """ - if os.environ.get("NO_COLOR"): - return _PLAIN_LOG_FORMAT - return _COLOR_LOG_FORMAT if _stream_is_tty(stdout) and _stream_is_tty(stderr) else _PLAIN_LOG_FORMAT + return not os.environ.get("NO_COLOR") and _stream_is_tty(stream) + + +def _terminal_colors(stdout: TextIO | None, stderr: TextIO | None) -> bool: + """True when both streams are an interactive color terminal, the one rule for log lines and startup prints.""" + return _color_enabled(stdout) and _color_enabled(stderr) + + +def terminal_text(message: str) -> str: + """The message with its ANSI colors kept only on a color terminal, by the rule the plain log format uses.""" + return message if _terminal_colors(sys.stdout, sys.stderr) else _ANSI_ESCAPE.sub("", message) + + +def _plain_log_format(stdout: TextIO | None, stderr: TextIO | None) -> str: + """The plain-text log format, colorized only when both streams are an interactive terminal.""" + return _COLOR_LOG_FORMAT if _terminal_colors(stdout, stderr) else _PLAIN_LOG_FORMAT class LevelRoutingStreamHandler(logging.StreamHandler): @@ -642,8 +658,8 @@ class LevelRoutingStreamHandler(logging.StreamHandler): super().emit(record) -def _parse_json_logs_env(value: str | None) -> bool: - """Strict opt-in parse for the JSON_LOGS env var: only "true" (any case) enables JSON logs. +def _parse_env_flag(value: str | None) -> bool: + """Strict opt-in parse for a boolean env var such as JSON_LOGS: only "true" (any case) enables it. Matches the reader in litellm-proxy-extras/_logging.py. The previous bool(os.getenv(...)) treated any non-empty value, including "false" and "0", @@ -656,7 +672,18 @@ def resolve_log_level(log_level: str) -> int: return getattr(logging, log_level.upper()) -json_logs: Final = _parse_json_logs_env(os.getenv("JSON_LOGS")) +json_logs: Final = _parse_env_flag(os.getenv("JSON_LOGS")) +suppress_startup_output: Final = _parse_env_flag(os.getenv("LITELLM_SUPPRESS_STARTUP_OUTPUT")) + + +class StartupOutputSettings(TypedDict, total=False): + json_logs: ReadOnly[object] + suppress_startup_output: ReadOnly[object] + + +STARTUP_OUTPUT_SETTINGS: Final = TypeAdapter(StartupOutputSettings) + + # Create a handler for the logger (you may need to adapt this based on your needs) log_level: Final = os.getenv("LITELLM_LOG", "DEBUG") numeric_level: Final[int] = resolve_log_level(log_level) @@ -743,7 +770,7 @@ class JsonFormatter(Formatter): return dt.isoformat() def format(self, record): - message_str: Final = record.getMessage() + message_str: Final = _ANSI_ESCAPE.sub("", record.getMessage()) json_record: Final[dict[str, object]] = { "message": message_str, "level": record.levelname, @@ -799,12 +826,14 @@ class CorrelationPlainFormatter(logging.Formatter): """Appends trace_id/session_id to plain-text log lines stamped by CorrelationContextFilter. Mirrors JsonFormatter's handling of these two fields so request_correlation_in_logs - behaves the same whether or not json_logs is enabled. + behaves the same whether or not json_logs is enabled. Unless it was built with the color format, + it also drops the ANSI color codes a message carries, which a piped log would store as text. """ def format(self, record: logging.LogRecord) -> str: rendered: Final = super().format(record) - formatted: Final = rendered if _is_redacted(record) else redact_string(rendered) + uncolored: Final = rendered if self._fmt == _COLOR_LOG_FORMAT else _ANSI_ESCAPE.sub("", rendered) + formatted: Final = uncolored if _is_redacted(record) else redact_string(uncolored) trace_id: Final = getattr(record, "trace_id", None) session_id: Final = getattr(record, "session_id", None) if not trace_id and not session_id: @@ -898,29 +927,46 @@ verbose_proxy_logger.addFilter(_diagnostic_filter) verbose_proxy_stdout_logger.addFilter(_diagnostic_filter) verbose_logger.addFilter(_diagnostic_filter) -_ANSI_ESCAPE: Final = re.compile(r"\x1b\[[0-9;]*m") - def print_startup_message(message: str) -> None: """Write a boot-time message meant for the operator's terminal. - Plain mode prints it unchanged, colors and spacing included. With JSON logs on, every line of - stdout is read by a log pipeline, so the message goes out as one INFO record of the proxy logger - instead, on stdout like the print whatever handlers the logging config gave that logger, with the - ANSI color codes and surrounding blank lines removed, located at the caller and emitted at any log - level, whole and unredacted as the print showed it; a blank spacer produces no record. + LITELLM_SUPPRESS_STARTUP_OUTPUT or litellm_settings.suppress_startup_output turns every one of them + off; a warning goes through print_startup_warning instead. Plain mode prints it with its spacing, + keeping the ANSI colors only on a color terminal by the same check as the plain log format, so a + container log never stores escape codes. + With JSON logs on, every line of stdout is read by a log pipeline, so the message goes out as one + INFO record of the proxy logger instead, on stdout like the print whatever handlers the logging + config gave that logger, with the ANSI color codes and surrounding blank lines removed, located at + the caller and emitted at any log level, whole and unredacted as the print showed it; a blank + spacer produces no record. """ + if litellm.suppress_startup_output is True: + return + frame: Final = inspect.currentframe() + _write_startup_message(message, frame.f_back if frame is not None else None, logging.INFO) + + +def print_startup_warning(message: str) -> None: + """Write a boot-time warning as print_startup_message writes a message, even with suppress_startup_output + on, since it names something the operator has to fix. With JSON logs on it is a WARNING record, on + stdout where the print put it, so a collector that filters on the level field keeps it.""" + frame: Final = inspect.currentframe() + _write_startup_message(message, frame.f_back if frame is not None else None, logging.WARNING) + + +def _write_startup_message(message: str, caller: FrameType | None, level: int) -> None: if not litellm.json_logs: - print(message) # noqa: T201 # plain mode: this is the operator-terminal print it replaces + import click + + click.echo(terminal_text(message)) return text: Final = _ANSI_ESCAPE.sub("", message).strip("\n") if not text: return - frame: Final = inspect.currentframe() - caller: Final = frame.f_back if frame is not None else None record: Final = verbose_proxy_logger.makeRecord( verbose_proxy_logger.name, - logging.INFO, + level, caller.f_code.co_filename if caller is not None else __file__, caller.f_lineno if caller is not None else 0, text, @@ -934,8 +980,8 @@ def print_startup_message(message: str) -> None: def _startup_json_handler() -> logging.Handler: - """The proxy's JSON handler on stdout, filters included, for one startup message.""" - handler: Final = LevelRoutingStreamHandler() + """The proxy's JSON handler on stdout, filters included, for one startup message or warning.""" + handler: Final = logging.StreamHandler(sys.stdout) handler.setFormatter(JsonFormatter()) handler.addFilter(_secret_filter) handler.addFilter(_correlation_filter) diff --git a/litellm/a2a_protocol/providers/bedrock_agentcore/transformation.py b/litellm/a2a_protocol/providers/bedrock_agentcore/transformation.py index 1cea0194715..d4400fbb4cc 100644 --- a/litellm/a2a_protocol/providers/bedrock_agentcore/transformation.py +++ b/litellm/a2a_protocol/providers/bedrock_agentcore/transformation.py @@ -19,6 +19,7 @@ from litellm.a2a_protocol.utils import ( ) from litellm.exceptions import BadRequestError from litellm.llms.bedrock.chat.agentcore.transformation import AmazonAgentCoreConfig +from litellm.llms.custom_httpx.sse_lines import aiter_sse_lines RUNTIME_SESSION_ID_MIN_LENGTH: Final = 33 RUNTIME_SESSION_ID_MAX_LENGTH: Final = 256 @@ -50,7 +51,7 @@ _RESERVED_PREFIX_HEADERS: Final[tuple[str, ...]] = ( class _SSELineSource(Protocol): """Minimal streaming-response surface used to read SSE lines.""" - def aiter_lines(self) -> AsyncIterator[str]: ... + def aiter_text(self) -> AsyncIterator[str]: ... def _filter_reserved_headers( @@ -244,7 +245,7 @@ class BedrockAgentCoreA2ATransformation: Yields: Parsed JSON dicts from SSE data lines """ - async for line in response.aiter_lines(): + async for line in aiter_sse_lines(response.aiter_text()): line = line.strip() if not line: continue diff --git a/litellm/a2a_protocol/providers/watsonx_orchestrate/handler.py b/litellm/a2a_protocol/providers/watsonx_orchestrate/handler.py index 0a2871d25cc..3937c47ea3c 100644 --- a/litellm/a2a_protocol/providers/watsonx_orchestrate/handler.py +++ b/litellm/a2a_protocol/providers/watsonx_orchestrate/handler.py @@ -20,6 +20,7 @@ from litellm.llms.custom_httpx.http_handler import ( AsyncHTTPHandler, get_async_httpx_client, ) +from litellm.llms.custom_httpx.sse_lines import aiter_sse_lines from litellm.types.llms.custom_http import httpxSpecialProvider _IBM_CLOUD_IAM_URL: Final = "https://iam.cloud.ibm.com/identity/token" @@ -74,7 +75,7 @@ class _WXORun(TypedDict, total=False): class _SSELineSource(Protocol): - def aiter_lines(self) -> AsyncIterator[str]: ... + def aiter_text(self) -> AsyncIterator[str]: ... class _WXOView(TypedDict, total=False): @@ -231,7 +232,7 @@ class WatsonxOrchestrateHandler: async def _accumulate_wxo_sse_text(response: _SSELineSource) -> str: source: Final[_WXOView] = {"sse_source": response} accumulated_text = "" - async for line in source["sse_source"].aiter_lines(): + async for line in aiter_sse_lines(source["sse_source"].aiter_text()): if not line.startswith("data:"): continue data_str = line[5:].strip() diff --git a/litellm/accounting/__init__.py b/litellm/accounting/__init__.py new file mode 100644 index 00000000000..d4e56f61279 --- /dev/null +++ b/litellm/accounting/__init__.py @@ -0,0 +1,62 @@ +"""Public accounting contracts. Importing these values does not enable accounting.""" + +from litellm.accounting.measurements import measurements_for +from litellm.accounting.protocols import BudgetEnforcer, CostAggregator, CostCompiler, UsageMeter +from litellm.accounting.types import ( + AdmissionDecision, + AggregateQuery, + AggregateRow, + CostEvent, + DeliveryState, + DeliveryTarget, + Dimension, + DimensionFilter, + DimensionName, + EventKind, + Granularity, + InboundUsageEvent, + Measurement, + Metric, + MetricName, + Multiplier, + NamedCost, + OutboundUsageEvent, + Outcome, + PricedQuantity, + PricingSnapshot, + Rate, + Unpriced, + validate_aggregate_rows, +) + +__all__ = [ + "AdmissionDecision", + "AggregateQuery", + "AggregateRow", + "BudgetEnforcer", + "CostAggregator", + "CostCompiler", + "CostEvent", + "DeliveryState", + "DeliveryTarget", + "Dimension", + "DimensionFilter", + "DimensionName", + "EventKind", + "Granularity", + "InboundUsageEvent", + "Measurement", + "Metric", + "MetricName", + "Multiplier", + "NamedCost", + "OutboundUsageEvent", + "Outcome", + "PricedQuantity", + "PricingSnapshot", + "Rate", + "Unpriced", + "UsageMeter", + "measurements_for", + "validate_aggregate_rows", +] diff --git a/litellm/accounting/measurements.py b/litellm/accounting/measurements.py new file mode 100644 index 00000000000..83011a280da --- /dev/null +++ b/litellm/accounting/measurements.py @@ -0,0 +1,13 @@ +from typing import Final + +from litellm.accounting.types import CostEvent, InboundUsageEvent, Measurement, OutboundUsageEvent + + +def measurements_for(event: InboundUsageEvent | OutboundUsageEvent | CostEvent) -> tuple[Measurement, ...]: + """Return the complete contribution set for one event, ready for one apply call.""" + metrics: Final = event.charges if isinstance(event, CostEvent) else event.metrics + occurred_at: Final = event.occurred_at if isinstance(event, CostEvent) else event.started_at + return tuple( + Measurement(source_event_id=event.event_id, occurred_at=occurred_at, dimensions=event.dimensions, metric=metric) + for metric in metrics or () + ) diff --git a/litellm/accounting/protocols.py b/litellm/accounting/protocols.py new file mode 100644 index 00000000000..8955f56e7a0 --- /dev/null +++ b/litellm/accounting/protocols.py @@ -0,0 +1,85 @@ +"""Contracts only. Implementations own persistence, pricing, projections and live budgets. + +The event row's ``payload`` is a private envelope versioned by the row's ``schema_version``. +Usage envelopes retain the public event and request-scoped pricing context: quantities with units, +model/provider, requested and billed tier/region when known, and per-request/deployment overrides. +These inputs must survive request teardown. Cost-map rates are resolved at compilation, not capture. +Cost envelopes retain the public CostEvent, including its required finalized pricing snapshot. +T5/T6 own envelope serialization; this public API does not introduce a second persisted schema. +""" + +from typing import Protocol + +from litellm.accounting.types import ( + AdmissionDecision, + AggregateQuery, + AggregateRow, + CostEvent, + Dimension, + InboundUsageEvent, + Measurement, + Metric, + OutboundUsageEvent, + Unpriced, +) + + +class UsageMeter(Protocol): + async def record(self, event: InboundUsageEvent | OutboundUsageEvent) -> None: + """Acknowledge commit, no-op identical IDs and reject conflicting content. + + Persist the event and its request-scoped pricing context before acknowledging. + HTTP acknowledgement is a separate policy. Unknown usage remains None. + """ + ... + + +class CostCompiler(Protocol): + async def compile(self, event: OutboundUsageEvent) -> CostEvent | Unpriced: + """Reuse the committed charge or finalize one charge and its delivery intent. + + Resolve captured request-scoped context by event identity and cost-map rates + at compilation. Persist the resolved inputs in the required snapshot. Replay + reuses the committed result and never consumes free allowance again. + Missing pricing is Unpriced, never an inferred zero. + """ + ... + + +class CostAggregator(Protocol): + async def apply(self, measurements: tuple[Measurement, ...]) -> None: + """Apply one source event's complete contribution set per target/version. + + Each target commits all contributions and its receipt atomically. A receipt + for the first metric must not suppress the rest. Usage need not wait for cost. + """ + ... + + async def query(self, query: AggregateQuery) -> tuple[AggregateRow, ...]: + """Return disjoint [start, end) rows per group using existing daily projections. + + Filters combine with AND, values within a filter with IN. DAY emits daily + buckets; None emits whole-interval totals. Reject unsupported metric/scope + combinations. Different groups may overlap, including non-additive tags. + """ + ... + + +class BudgetEnforcer(Protocol): + async def reserve( + self, reservation_id: str, dimensions: tuple[Dimension, ...], estimated: tuple[Metric, ...] + ) -> AdmissionDecision: + """Apply existing admission policies and estimates; duplicate IDs add no hold.""" + ... + + async def settle(self, reservation_id: str | None, cost_event: CostEvent) -> None: + """Settle the committed charge with atomic deduplication and hold mutation. + + Preserve scope/window attribution and retry unfinished settlement after + restart. SQL projection receipts do not provide live-counter atomicity. + """ + ... + + async def release(self, reservation_id: str) -> None: + """Idempotently release unused exposure at the request boundary, preserving charges.""" + ... diff --git a/litellm/accounting/types.py b/litellm/accounting/types.py new file mode 100644 index 00000000000..d0be29bf5b9 --- /dev/null +++ b/litellm/accounting/types.py @@ -0,0 +1,428 @@ +"""Accounting values use UTC instants, decimal strings on the wire and USD charges.""" + +from collections.abc import Mapping +from datetime import datetime, timezone +from decimal import Decimal +from enum import Enum +from typing import Annotated, Final, Literal, TypeAlias + +from pydantic import AfterValidator, AwareDatetime, BaseModel, ConfigDict, Field, model_validator +from typing_extensions import Self + +from litellm.types.utils import CallTypes + +_CONFIG: Final = ConfigDict(frozen=True, extra="forbid", validate_default=True) +Identifier: TypeAlias = Annotated[str, Field(strict=True, min_length=1, pattern=r"\S")] +Quantity: TypeAlias = Annotated[Decimal, Field(strict=True, ge=0, allow_inf_nan=False)] + + +def _utc(value: datetime) -> datetime: + return value.astimezone(timezone.utc) + + +Instant: TypeAlias = Annotated[AwareDatetime, AfterValidator(_utc)] + + +class MetricName(str, Enum): + """Reasoning tokens are included in completion tokens; above-1hr writes are included in cache creation tokens.""" + + REQUESTS = "requests" + SUCCESSFUL_REQUESTS = "successful_requests" + FAILED_REQUESTS = "failed_requests" + PROMPT_TOKENS = "prompt_tokens" + COMPLETION_TOKENS = "completion_tokens" + REASONING_TOKENS = "reasoning_tokens" + TOTAL_TOKENS = "total_tokens" + CACHE_READ_INPUT_TOKENS = "cache_read_input_tokens" + CACHE_CREATION_INPUT_TOKENS = "cache_creation_input_tokens" + CACHE_CREATION_INPUT_TOKENS_ABOVE_1HR = "cache_creation_input_tokens_above_1hr" + SPEND = "spend" + + +class DimensionName(str, Enum): + KEY = "key" + USER = "user" + TEAM = "team" + ORGANIZATION = "organization" + END_USER = "end_user" + MODEL = "model" + MODEL_GROUP = "model_group" + DEPLOYMENT = "deployment" + PROVIDER = "provider" + TOOL = "tool" + AGENT = "agent" + PROJECT = "project" + MODEL_ACCESS_GROUP = "model_access_group" + API_BASE = "api_base" + SERVICE_TIER = "service_tier" + TAG = "tag" + + +class Outcome(str, Enum): + SUCCEEDED = "succeeded" + FAILED = "failed" + CANCELLED = "cancelled" + + +class Granularity(str, Enum): + DAY = "day" + + +class EventKind(str, Enum): + INBOUND_USAGE = "inbound_usage" + OUTBOUND_USAGE = "outbound_usage" + COST = "cost" + + +class DeliveryState(str, Enum): + PENDING = "pending" + APPLIED = "applied" + PARKED = "parked" + + +class DeliveryTarget(str, Enum): + """One member per existing table the projector writes; each is applied and receipted independently.""" + + KEY_SPEND = "LiteLLM_VerificationToken" + USER_SPEND = "LiteLLM_UserTable" + TEAM_SPEND = "LiteLLM_TeamTable" + TEAM_MEMBER_SPEND = "LiteLLM_TeamMembership" + ORGANIZATION_SPEND = "LiteLLM_OrganizationTable" + ORGANIZATION_MEMBER_SPEND = "LiteLLM_OrganizationMembership" + END_USER_SPEND = "LiteLLM_EndUserTable" + AGENT_SPEND = "LiteLLM_AgentsTable" + TAG_SPEND = "LiteLLM_TagTable" + PROJECT_SPEND = "LiteLLM_ProjectTable" + MODEL_ACCESS_GROUP_SPEND = "LiteLLM_ModelAccessGroupBudgetTable" + BUDGET_SPEND = "LiteLLM_BudgetTable" + BUDGET_WINDOW_SPEND = "LiteLLM_BudgetWindowSpend" + DAILY_USER_SPEND = "LiteLLM_DailyUserSpend" + DAILY_TEAM_SPEND = "LiteLLM_DailyTeamSpend" + DAILY_ORGANIZATION_SPEND = "LiteLLM_DailyOrganizationSpend" + DAILY_END_USER_SPEND = "LiteLLM_DailyEndUserSpend" + DAILY_AGENT_SPEND = "LiteLLM_DailyAgentSpend" + DAILY_TAG_SPEND = "LiteLLM_DailyTagSpend" + DAILY_MODEL_USAGE = "LiteLLM_DailyModelUsage" + DAILY_TOOL_SPEND = "LiteLLM_DailyToolSpend" + AUTOROUTER_DAILY_SPEND = "LiteLLM_AutoRouterDailySpend" + + +_SUBSET_PAIRS: Final = ( + (MetricName.REASONING_TOKENS, MetricName.COMPLETION_TOKENS), + (MetricName.CACHE_CREATION_INPUT_TOKENS_ABOVE_1HR, MetricName.CACHE_CREATION_INPUT_TOKENS), +) + + +def _check_subsets(values: Mapping[str, Decimal]) -> None: + for part, whole in _SUBSET_PAIRS: + if part.value in values and whole.value in values and values[part.value] > values[whole.value]: + raise ValueError(f"{part.value} cannot exceed {whole.value}") + + +class Metric(BaseModel): + model_config = _CONFIG + + name: MetricName + value: Quantity + unit: Literal["count", "USD"] = "count" + + @model_validator(mode="after") + def validate_unit(self) -> Self: + if (self.name is MetricName.SPEND) != (self.unit == "USD"): + raise ValueError("SPEND requires USD; usage metrics require count") + if self.unit == "count" and self.value != self.value.to_integral_value(): + raise ValueError("Count metrics require integral values") + return self + + +class Dimension(BaseModel): + model_config = _CONFIG + + name: DimensionName + value: Identifier + + +_REPEATABLE_DIMENSIONS: Final = frozenset({DimensionName.TAG, DimensionName.MODEL_ACCESS_GROUP}) + + +def _dimensions(values: tuple[Dimension, ...]) -> tuple[Dimension, ...]: + if len(frozenset(values)) != len(values): + raise ValueError("Duplicate dimension values") + single_names: Final = tuple(value.name for value in values if value.name not in _REPEATABLE_DIMENSIONS) + if len(frozenset(single_names)) != len(single_names): + raise ValueError("Only tag and model access group dimensions may have multiple values") + return values + + +Dimensions: TypeAlias = Annotated[tuple[Dimension, ...], AfterValidator(_dimensions)] +_CALLER_METRICS: Final = frozenset((MetricName.REQUESTS, MetricName.SUCCESSFUL_REQUESTS, MetricName.FAILED_REQUESTS)) + + +def _metrics(values: tuple[Metric, ...]) -> tuple[Metric, ...]: + if len(frozenset(value.name for value in values)) != len(values): + raise ValueError("Duplicate metric names") + return values + + +Metrics: TypeAlias = Annotated[tuple[Metric, ...], AfterValidator(_metrics)] + + +def _interval(start: datetime, end: datetime, *, allow_empty: bool = False) -> None: + if end < start or (end == start and not allow_empty): + raise ValueError("End must follow start") + + +class InboundUsageEvent(BaseModel): + model_config = _CONFIG + + event_id: Identifier + request_id: Identifier + call_type: CallTypes + started_at: Instant + ended_at: Instant + outcome: Outcome + dimensions: Dimensions + metrics: Metrics + + @model_validator(mode="after") + def validate_caller_activity(self) -> Self: + _interval(self.started_at, self.ended_at, allow_empty=True) + if any(metric.name not in _CALLER_METRICS for metric in self.metrics): + raise ValueError("Inbound events own only caller request metrics") + if not any(metric.name is MetricName.REQUESTS and metric.value == 1 for metric in self.metrics): + raise ValueError("Inbound events count exactly one caller request") + for metric in self.metrics: + if metric.name is MetricName.SUCCESSFUL_REQUESTS and metric.value != int(self.outcome is Outcome.SUCCEEDED): + raise ValueError("Successful request count must match outcome") + if metric.name is MetricName.FAILED_REQUESTS and metric.value != int(self.outcome is not Outcome.SUCCEEDED): + raise ValueError("Failed request count must match outcome") + return self + + +class OutboundUsageEvent(BaseModel): + model_config = _CONFIG + + event_id: Identifier + attempt_id: Identifier + request_id: Identifier | None + retry_of_attempt_id: Identifier | None + call_type: CallTypes + started_at: Instant + ended_at: Instant + outcome: Outcome + dimensions: Dimensions + metrics: Metrics | None + + @model_validator(mode="after") + def validate_attempt_usage(self) -> Self: + _interval(self.started_at, self.ended_at, allow_empty=True) + if self.retry_of_attempt_id == self.attempt_id: + raise ValueError("An attempt cannot retry itself") + if self.metrics is not None and any( + metric.name in _CALLER_METRICS or metric.name is MetricName.SPEND for metric in self.metrics + ): + raise ValueError("Outbound events own only attempt usage metrics") + if self.metrics is not None: + _check_subsets({metric.name.value: metric.value for metric in self.metrics}) + return self + + +PricingUnit: TypeAlias = Literal["token", "second", "character", "image", "request"] + + +class Rate(BaseModel): + model_config = _CONFIG + + measure: Identifier + unit: PricingUnit + usd_per_unit: Quantity + + +class PricedQuantity(BaseModel): + """A pricing input in its billing unit. Only seconds may be fractional.""" + + model_config = _CONFIG + + measure: Identifier + unit: PricingUnit + value: Quantity + + @model_validator(mode="after") + def validate_discrete_quantity(self) -> Self: + if self.unit != "second" and self.value != self.value.to_integral_value(): + raise ValueError("Discrete priced quantities require integral values") + return self + + +class Multiplier(BaseModel): + """A regional or tier factor applied on top of the priced key, e.g. data_residency=eu or vertex_location=us-east5.""" + + model_config = _CONFIG + + name: Identifier + value: Identifier + factor: Annotated[Decimal, Field(strict=True, gt=0, allow_inf_nan=False)] + + +class NamedCost(BaseModel): + """A free-form extra charge by name, e.g. azure_model_router_flat_cost.""" + + model_config = _CONFIG + + name: Identifier + amount: Quantity + + +class PricingSnapshot(BaseModel): + """Retained inputs and result of authoritative compilation, reproducible after cost-map rates change. + + Request-scoped inputs and overrides come from the usage row's versioned payload. Cost-map rates are + resolved at compilation, not frozen at capture. Retries reuse the committed charge and snapshot. + Component names match ``CostBreakdown``: reasoning_cost is part of output_cost, not an additional charge. + Component sums and float tolerances belong to reconciliation, not this structural contract. + """ + + model_config = _CONFIG + + schema_version: Literal[1] = 1 + calculator_version: Identifier + model: Identifier + provider: Identifier | None + pricing_source: Literal["cost_map", "deployment", "per_request", "upstream_header"] + priced_model_key: Identifier + multipliers: tuple[Multiplier, ...] = () + rates: tuple[Rate, ...] = () + usage: tuple[PricedQuantity, ...] = () + input_cost: Quantity | None = None + output_cost: Quantity | None = None + cache_read_cost: Quantity | None = None + cache_creation_cost: Quantity | None = None + reasoning_cost: Quantity | None = None + tool_usage_cost: Quantity | None = None + guardrail_cost: Quantity | None = None + additional_costs: tuple[NamedCost, ...] = () + original_cost: Quantity | None = None + discount_percent: Quantity | None = None + discount_amount: Quantity | None = None + margin_percent: Quantity | None = None + margin_fixed_amount: Quantity | None = None + margin_total_amount: Quantity | None = None + upstream_reported_cost: Quantity | None = None + total_cost: Quantity + + @model_validator(mode="after") + def validate_snapshot(self) -> Self: + rate_keys: Final = frozenset((rate.measure, rate.unit) for rate in self.rates) + quantity_keys: Final = frozenset((quantity.measure, quantity.unit) for quantity in self.usage) + if len(rate_keys) != len(self.rates): + raise ValueError("Duplicate rate measures and units") + if len(quantity_keys) != len(self.usage): + raise ValueError("Duplicate priced quantity measures and units") + if not rate_keys.issubset(quantity_keys): + raise ValueError("Every rate requires one priced quantity with the same measure and unit") + if len(frozenset(cost.name for cost in self.additional_costs)) != len(self.additional_costs): + raise ValueError("Duplicate additional cost names") + if len(frozenset(multiplier.name for multiplier in self.multipliers)) != len(self.multipliers): + raise ValueError("Duplicate multiplier names") + _check_subsets({quantity.measure: quantity.value for quantity in self.usage if quantity.unit == "token"}) + return self + + +class CostEvent(BaseModel): + model_config = _CONFIG + + event_id: Identifier + usage_event_id: Identifier + occurred_at: Instant + dimensions: Dimensions + charges: Metrics + snapshot: PricingSnapshot + + @model_validator(mode="after") + def validate_charge(self) -> Self: + if len(self.charges) != 1 or self.charges[0].name is not MetricName.SPEND: + raise ValueError("A cost event requires one authoritative USD spend metric") + if self.event_id == self.usage_event_id: + raise ValueError("Cost and usage events require distinct identities") + if self.snapshot.total_cost != self.charges[0].value: + raise ValueError("Snapshot total must equal the authoritative spend") + return self + + +class Unpriced(BaseModel): + model_config = _CONFIG + + usage_event_id: Identifier + reason: Identifier + + +class Measurement(BaseModel): + model_config = _CONFIG + + source_event_id: Identifier + occurred_at: Instant + dimensions: Dimensions + metric: Metric + + +class DimensionFilter(BaseModel): + model_config = _CONFIG + + name: DimensionName + values: Annotated[tuple[Identifier, ...], Field(min_length=1)] + + +class AggregateQuery(BaseModel): + model_config = _CONFIG + + metric: MetricName + filters: tuple[DimensionFilter, ...] + group_by: tuple[DimensionName, ...] + start: Instant + end: Instant + granularity: Granularity | None + + @model_validator(mode="after") + def validate_query(self) -> Self: + _interval(self.start, self.end) + if len(frozenset(item.name for item in self.filters)) != len(self.filters): + raise ValueError("Use one IN filter per dimension; filters combine with AND") + if len(frozenset(self.group_by)) != len(self.group_by): + raise ValueError("Duplicate group-by dimensions") + if any( + (instant.hour, instant.minute, instant.second, instant.microsecond) != (0, 0, 0, 0) + for instant in (self.start, self.end) + ): + raise ValueError("Initial reporting queries require UTC day boundaries") + return self + + +class AggregateRow(BaseModel): + model_config = _CONFIG + + start: Instant + end: Instant + dimensions: Dimensions + value: Quantity + + @model_validator(mode="after") + def validate_bounds(self) -> Self: + _interval(self.start, self.end) + return self + + +def validate_aggregate_rows(rows: tuple[AggregateRow, ...]) -> tuple[AggregateRow, ...]: + """Validate [start, end) buckets per group; overlapping tag groups are not additive.""" + groups: Final = frozenset(frozenset(row.dimensions) for row in rows) + for group in groups: + ordered = sorted((row for row in rows if frozenset(row.dimensions) == group), key=lambda row: row.start) + if any(left.end > right.start for left, right in zip(ordered, ordered[1:])): + raise ValueError("Aggregate buckets overlap within a dimension group") + return rows + + +class AdmissionDecision(BaseModel): + model_config = _CONFIG + + allowed: bool + reason: Identifier | None = None diff --git a/litellm/caching/in_memory_cache.py b/litellm/caching/in_memory_cache.py index 1cc3e106aa0..6b40c48c4ef 100644 --- a/litellm/caching/in_memory_cache.py +++ b/litellm/caching/in_memory_cache.py @@ -274,7 +274,9 @@ class InMemoryCache(BaseCache): ) -> list[float] | None: results: Final = [] for increment in increment_list: - result = await self.async_increment(increment["key"], increment["increment_value"], **kwargs) + result = await self.async_increment( + increment["key"], increment["increment_value"], ttl=increment["ttl"], **kwargs + ) results.append(result) return results diff --git a/litellm/completion_extras/litellm_responses_transformation/handler.py b/litellm/completion_extras/litellm_responses_transformation/handler.py index 3f7017eccc2..76d17ea9693 100644 --- a/litellm/completion_extras/litellm_responses_transformation/handler.py +++ b/litellm/completion_extras/litellm_responses_transformation/handler.py @@ -260,6 +260,7 @@ class ResponsesToCompletionBridgeHandler: structured_output=is_structured_output_request( cast("Mapping[str, object]", optional_params) # cast-ok: optional_params is an untyped dict ), + replays_openai_history=custom_llm_provider == "openai", ) streamwrapper: Final = CustomStreamWrapper( completion_stream=completion_stream, @@ -363,6 +364,7 @@ class ResponsesToCompletionBridgeHandler: structured_output=is_structured_output_request( cast("Mapping[str, object]", optional_params) # cast-ok: optional_params is an untyped dict ), + replays_openai_history=custom_llm_provider == "openai", ) streamwrapper: Final = CustomStreamWrapper( completion_stream=completion_stream, diff --git a/litellm/completion_extras/litellm_responses_transformation/history.py b/litellm/completion_extras/litellm_responses_transformation/history.py new file mode 100644 index 00000000000..4435de64cde --- /dev/null +++ b/litellm/completion_extras/litellm_responses_transformation/history.py @@ -0,0 +1,432 @@ +import hashlib +import json +from collections.abc import Iterator, Mapping, Sequence +from dataclasses import dataclass +from itertools import accumulate, chain, pairwise +from types import MappingProxyType +from typing import Annotated, Final, Literal, TypeAlias + +from pydantic import BaseModel, ConfigDict, Field, TypeAdapter, ValidationError + +REPLAY_FIELD: Final = "openai_responses_replay" +PHASE_FIELD: Final = "phase" + +Phase: TypeAlias = Literal["commentary", "final_answer"] + + +class _Frozen(BaseModel): + model_config = ConfigDict(frozen=True) + + +class _OutputText(_Frozen): + type: Literal["output_text"] + text: str + + +class _OutputMessage(_Frozen): + type: Literal["message"] + role: Literal["assistant"] + content: tuple[_OutputText, ...] + phase: Phase | None = None + + +class _OutputReasoning(_Frozen): + type: Literal["reasoning"] + id: str + + +class _OutputToolCall(_Frozen): + type: Literal["function_call", "custom_tool_call"] + call_id: str + id: str | None = None + + +class _OutputToolSearch(_Frozen): + type: Literal["tool_search_call", "tool_search_output"] + + +_OutputItem: TypeAlias = Annotated[ + _OutputMessage | _OutputReasoning | _OutputToolCall | _OutputToolSearch, Field(discriminator="type") +] +_OUTPUT_ITEM: Final[TypeAdapter[_OutputItem]] = TypeAdapter(_OutputItem) + + +class _AnyMessage(_Frozen): + type: Literal["message"] + + +class _MessageEntry(_Frozen): + type: Literal["message"] + parts: tuple[Annotated[int, Field(ge=0)], ...] + phase: Phase | None = None + + +class _IndexedEntry(_Frozen): + type: Literal["reasoning", "function_call", "custom_tool_call", "tool_search_call", "tool_search_output"] + index: Annotated[int, Field(ge=0)] + + +_Entry: TypeAlias = Annotated[_MessageEntry | _IndexedEntry, Field(discriminator="type")] + + +class _Replay(_Frozen): + version: Literal[1] + items: tuple[_Entry, ...] + checksum: str + + +class _Namespaced(_Frozen): + namespace: str | None = None + + +class _ToolFunction(_Frozen): + name: str = "" + arguments: str = "" + provider_specific_fields: _Namespaced | None = None + + +class _ToolCall(_Frozen): + id: str + function: _ToolFunction + provider_specific_fields: _Namespaced | None = None + + +class _SummaryText(_Frozen): + type: str = "summary_text" + text: str = "" + + +class _Reasoning(_Frozen): + id: str | None = None + encrypted_content: str | None = None + summary: tuple[_SummaryText, ...] | None = None + + +class _ProviderFields(_Frozen): + phase: Phase | None = None + tool_search_items: tuple[Mapping[str, object], ...] | None = None + openai_responses_replay: object = None + + +class _ChatMessage(_Frozen): + role: str | None = None + content: str | None = None + tool_calls: tuple[_ToolCall, ...] | None = None + reasoning_items: tuple[_Reasoning, ...] | None = None + phase: Phase | None = None + provider_specific_fields: _ProviderFields | None = None + + +class _PhaseFields(_Frozen): + phase: Phase | None = None + + +class _RequestedPhaseFields(_Frozen): + phase: object = None + + +class _RequestedPhase(_Frozen): + phase: object = None + provider_specific_fields: _RequestedPhaseFields | None = None + + +@dataclass(frozen=True, slots=True) +class UnknownPhase: + value: object + + +_PHASE: Final[TypeAdapter[Phase]] = TypeAdapter(Phase) + + +class _RetainedFields(_PhaseFields): + openai_responses_replay: object = None + + +@dataclass(frozen=True, slots=True) +class ReplayedTurn: + items: tuple[Mapping[str, object], ...] + custom_call_ids: frozenset[str] + + +def _as_json(value: object) -> object: + return value.model_dump() if isinstance(value, BaseModel) else value + + +def _parsed_output_item(item: object) -> _OutputItem | None: + try: + return _OUTPUT_ITEM.validate_python(_as_json(item)) + except ValidationError: + return None + + +def _is_message(item: object) -> bool: + try: + _AnyMessage.model_validate(_as_json(item)) + except ValidationError: + return False + return True + + +def _chat_message(message: object) -> _ChatMessage | None: + try: + return _ChatMessage.model_validate(_as_json(message)) + except ValidationError: + return None + + +def requested_phase(message: object) -> Phase | UnknownPhase | None: + try: + requested: Final = _RequestedPhase.model_validate(_as_json(message)) + except ValidationError: + return None + fields: Final = requested.provider_specific_fields + value: Final = requested.phase or (fields.phase if fields else None) + if value is None: + return None + try: + return _PHASE.validate_python(value) + except ValidationError: + return UnknownPhase(value) + + +def reasoning_input_item( + item_id: str | None, summary: Sequence[object] | None, encrypted_content: str | None +) -> Mapping[str, object]: + return { + "type": "reasoning", + **({"id": item_id} if item_id else {}), + "summary": list(summary or ()), + **({"encrypted_content": encrypted_content} if encrypted_content else {}), + } + + +def retained_replay_fields(provider_specific_fields: object) -> Mapping[str, object] | None: + try: + retained: Final = _RetainedFields.model_validate(provider_specific_fields) + except ValidationError: + return None + return retained.model_dump(exclude_none=True) or None + + +def output_message_text(output_items: Sequence[object], *, first_message_only: bool) -> str: + parsed: Final = map(_parsed_output_item, output_items) + messages: Final = tuple(item for item in parsed if isinstance(item, _OutputMessage)) + return "".join(_texts(messages[:1] if first_message_only else messages)) + + +def _tool_search_entries(message: _ChatMessage) -> tuple[Mapping[str, object], ...]: + fields: Final = message.provider_specific_fields + items: Final = (fields.tool_search_items if fields else None) or () + return tuple(item for item in items if item.get("type") in ("tool_search_call", "tool_search_output")) + + +def _checksum(message: _ChatMessage, entries: Sequence[_MessageEntry | _IndexedEntry]) -> str: + fields: Final = message.provider_specific_fields + bound: Final = { + "content": message.content or "", + "tool_calls": [[call.id, call.function.name, call.function.arguments] for call in message.tool_calls or ()], + "reasoning": [ + [item.id, item.encrypted_content, [part.text for part in item.summary or ()]] + for item in message.reasoning_items or () + ], + "tool_search_items": list((fields.tool_search_items if fields else None) or ()), + "phase": message.phase or (fields.phase if fields else None), + "items": [entry.model_dump(mode="json", exclude_none=True) for entry in entries], + } + encoded: Final = json.dumps(bound, sort_keys=True, separators=(",", ":"), ensure_ascii=False) + return hashlib.sha256(encoded.encode("utf-8", "surrogatepass")).hexdigest() + + +def _kind(item: _OutputItem) -> str: + match item: + case _OutputToolCall(): + return "tool_call" + case _OutputToolSearch(): + return "tool_search" + case _OutputMessage() | _OutputReasoning(): + return item.type + + +def _entry(items: Sequence[_OutputItem], position: int) -> _MessageEntry | _IndexedEntry: + item: Final = items[position] + if isinstance(item, _OutputMessage): + return _MessageEntry(type="message", parts=tuple(len(part.text) for part in item.content), phase=item.phase) + ordinal: Final = sum(1 for earlier in items[:position] if _kind(earlier) == _kind(item)) + return _IndexedEntry(type=item.type, index=ordinal) + + +def _texts(items: Sequence[_OutputItem]) -> Iterator[str]: + for item in items: + if isinstance(item, _OutputMessage): + yield from (part.text for part in item.content) + + +def _matches(items: Sequence[_OutputItem], message: _ChatMessage) -> bool: + reasoning_ids: Final = tuple(item.id for item in items if isinstance(item, _OutputReasoning)) + calls: Final = tuple(item for item in items if isinstance(item, _OutputToolCall)) + tool_calls: Final = message.tool_calls or () + searches: Final = sum(1 for item in items if isinstance(item, _OutputToolSearch)) + return ( + "".join(_texts(items)) == (message.content or "") + and reasoning_ids == tuple(item.id for item in message.reasoning_items or ()) + and len(calls) == len(tool_calls) + and all(chat.id in (call.call_id, call.id) for call, chat in zip(calls, tool_calls)) + and searches == len(_tool_search_entries(message)) + ) + + +def _content_phase( + output_items: Sequence[object], parsed: Sequence[_OutputItem | None], *, first_message_only: bool +) -> Phase | None: + messages: Final = tuple(item for raw, item in zip(output_items, parsed) if _is_message(raw)) + if not messages: + return None + content_message: Final = messages[0] if first_message_only else messages[-1] + return content_message.phase if isinstance(content_message, _OutputMessage) else None + + +def _with_phase(message: _ChatMessage, phase: Phase | None) -> _ChatMessage: + if phase is None: + return message + fields: Final = (message.provider_specific_fields or _ProviderFields()).model_copy(update={PHASE_FIELD: phase}) + return message.model_copy(update={"provider_specific_fields": fields}) + + +def replay_fields( + output_items: Sequence[object], message: object, *, completed: bool, first_message_only: bool +) -> Mapping[str, object]: + parsed: Final = tuple(map(_parsed_output_item, output_items)) + phase: Final = _content_phase(output_items, parsed, first_message_only=first_message_only) + phase_fields: Final[Mapping[str, object]] = MappingProxyType({PHASE_FIELD: phase} if phase else {}) + items: Final = tuple(item for item in parsed if item is not None) + parsed_message: Final = _chat_message(message) + chat: Final = _with_phase(parsed_message, phase) if parsed_message is not None else None + if not completed or not items or len(items) != len(parsed) or chat is None or not _matches(items, chat): + return phase_fields + entries: Final = tuple(_entry(items, position) for position in range(len(items))) + replay: Final = _Replay(version=1, items=entries, checksum=_checksum(chat, entries)) + return MappingProxyType({**phase_fields, REPLAY_FIELD: replay.model_dump(mode="json", exclude_none=True)}) + + +def _stored_replay(message: _ChatMessage) -> _Replay | None: + fields: Final = message.provider_specific_fields + if fields is None or fields.openai_responses_replay is None: + return None + try: + return _Replay.model_validate(fields.openai_responses_replay) + except ValidationError: + return None + + +def _message_texts(entries: Sequence[_MessageEntry], content: str) -> tuple[tuple[str, ...], ...]: + lengths: Final = tuple(chain.from_iterable(entry.parts for entry in entries)) + bounds: Final = tuple(accumulate(lengths, initial=0)) + parts: Final = tuple(content[start:end] for start, end in pairwise(bounds)) + groups: Final = tuple(accumulate((len(entry.parts) for entry in entries), initial=0)) + return tuple(parts[start:end] for start, end in pairwise(groups)) + + +def _message_item(texts: Sequence[str], phase: Phase | None) -> Mapping[str, object]: + return { + "type": "message", + "role": "assistant", + "content": [{"type": "output_text", "text": text} for text in texts], + **({PHASE_FIELD: phase} if phase else {}), + } + + +def _function_call_item(call: _ToolCall) -> Mapping[str, object]: + namespaced: Final = call.provider_specific_fields or call.function.provider_specific_fields + namespace: Final = namespaced.namespace if namespaced else None + return { + "type": "function_call", + "call_id": call.id, + "name": call.function.name, + "arguments": call.function.arguments, + **({"namespace": namespace} if namespace else {}), + } + + +def _custom_tool_call_item(call: _ToolCall) -> Mapping[str, object]: + return { + "type": "custom_tool_call", + "call_id": call.id, + "name": call.function.name, + "input": call.function.arguments, + } + + +def _reasoning_item(item: _Reasoning) -> Mapping[str, object]: + summary: Final = tuple(part.model_dump() for part in item.summary or ()) + return reasoning_input_item(item.id, summary, item.encrypted_content) + + +@dataclass(frozen=True, slots=True) +class _Resolved: + message: _ChatMessage + texts: Mapping[int, tuple[str, ...]] + tool_searches: tuple[Mapping[str, object], ...] + + +def _input_item(resolved: _Resolved, position: int, entry: _MessageEntry | _IndexedEntry) -> Mapping[str, object]: + if isinstance(entry, _MessageEntry): + return _message_item(resolved.texts[position], entry.phase) + tool_calls: Final = resolved.message.tool_calls or () + match entry.type: + case "reasoning": + return _reasoning_item((resolved.message.reasoning_items or ())[entry.index]) + case "function_call": + return _function_call_item(tool_calls[entry.index]) + case "custom_tool_call": + return _custom_tool_call_item(tool_calls[entry.index]) + case "tool_search_call" | "tool_search_output": + return dict(resolved.tool_searches[entry.index]) + + +def _fits(message: _ChatMessage, entries: Sequence[_MessageEntry | _IndexedEntry]) -> bool: + tool_calls: Final = len(message.tool_calls or ()) + tool_searches: Final = len(_tool_search_entries(message)) + sizes: Final = MappingProxyType( + { + "reasoning": len(message.reasoning_items or ()), + "function_call": tool_calls, + "custom_tool_call": tool_calls, + "tool_search_call": tool_searches, + "tool_search_output": tool_searches, + } + ) + parts: Final = chain.from_iterable(entry.parts for entry in entries if isinstance(entry, _MessageEntry)) + indexed: Final = (entry for entry in entries if isinstance(entry, _IndexedEntry)) + return sum(parts) == len(message.content or "") and all(entry.index < sizes[entry.type] for entry in indexed) + + +def _resolve( + message: _ChatMessage, entries: Sequence[_MessageEntry | _IndexedEntry], replay_tool_search: bool +) -> ReplayedTurn | None: + indexed: Final = tuple(entry for entry in entries if isinstance(entry, _IndexedEntry)) + if not replay_tool_search and any(entry.type in ("tool_search_call", "tool_search_output") for entry in indexed): + return None + messages: Final = tuple(entry for entry in entries if isinstance(entry, _MessageEntry)) + calls: Final = tuple(entry for entry in indexed if entry.type in ("function_call", "custom_tool_call")) + texts: Final = _message_texts(messages, message.content or "") + positions: Final = tuple(position for position, entry in enumerate(entries) if isinstance(entry, _MessageEntry)) + resolved: Final = _Resolved( + message=message, + texts=MappingProxyType(dict(zip(positions, texts, strict=True))), + tool_searches=_tool_search_entries(message), + ) + tool_calls: Final = message.tool_calls or () + return ReplayedTurn( + items=tuple(_input_item(resolved, position, entry) for position, entry in enumerate(entries)), + custom_call_ids=frozenset(tool_calls[entry.index].id for entry in calls if entry.type == "custom_tool_call"), + ) + + +def replay_items(message: object, *, replay_tool_search: bool) -> ReplayedTurn | None: + chat: Final = _chat_message(message) + stored: Final = _stored_replay(chat) if chat is not None and chat.role == "assistant" else None + if chat is None or stored is None or stored.checksum != _checksum(chat, stored.items): + return None + if not _fits(chat, stored.items): + return None + return _resolve(chat, stored.items, replay_tool_search) diff --git a/litellm/completion_extras/litellm_responses_transformation/transformation.py b/litellm/completion_extras/litellm_responses_transformation/transformation.py index 98322aecf6a..580e55273f6 100644 --- a/litellm/completion_extras/litellm_responses_transformation/transformation.py +++ b/litellm/completion_extras/litellm_responses_transformation/transformation.py @@ -3,7 +3,6 @@ Handler for transforming /chat/completions api requests to litellm.responses req """ import json -import os from collections.abc import AsyncIterator, Callable, Iterable, Iterator, Mapping, Sequence from itertools import accumulate, chain from types import MappingProxyType @@ -25,9 +24,19 @@ from pydantic import BaseModel, ConfigDict, TypeAdapter, ValidationError import litellm from litellm import ModelResponse from litellm._logging import verbose_logger +from litellm.completion_extras.litellm_responses_transformation.history import ( + PHASE_FIELD, + UnknownPhase, + output_message_text, + reasoning_input_item, + replay_fields, + replay_items, + requested_phase, +) from litellm.integrations.anthropic_cache_control_hook import supports_openai_prompt_cache_breakpoint from litellm.litellm_core_utils.hidden_params import get_hidden_params, get_or_create_hidden_params from litellm.litellm_core_utils.prompt_templates.common_utils import ( + prompt_cache_breakpoint_for_wire, responses_reasoning_items_from_thinking_blocks, with_prompt_cache_breakpoint, ) @@ -35,6 +44,7 @@ from litellm.llms.base_llm.base_model_iterator import BaseModelResponseIterator from litellm.llms.base_llm.bridges.completion_transformation import ( CompletionTransformationBridge, ) +from litellm.llms.custom_httpx.sse_lines import split_sse_lines from litellm.responses.litellm_completion_transformation.tool_search import is_anthropic_tool_search_chat_tool from litellm.responses.sse_output_recovery import ( parse_sse_json_chunk, @@ -43,8 +53,8 @@ from litellm.responses.sse_output_recovery import ( ) from litellm.responses.utils import ( ResponsesAPIRequestUtils, - auto_reasoning_summary, normalize_responses_api_stream_options, + opt_in_auto_reasoning_summary, ) from litellm.types.llms.openai import ( ChatCompletionAnnotation, @@ -52,7 +62,6 @@ from litellm.types.llms.openai import ( ChatCompletionToolCallChunk, ChatCompletionToolCallFunctionChunk, ChatCompletionToolParamFunctionChunk, - PromptCacheBreakpoint, Reasoning, ResponsesAPIOptionalRequestParams, ResponsesAPIResponse, @@ -490,7 +499,7 @@ def _fold_choices_into_one( choices: Sequence["Choices"], tool_calls: Sequence[Mapping[str, object]], trailing_reasoning_content: str | None, - trailing_reasoning_item: _BuiltReasoningItem | None, + trailing_reasoning_items: Sequence[_BuiltReasoningItem], tool_search_items: Sequence[Mapping[str, object]], structured_output: bool = False, ) -> "Choices": @@ -509,7 +518,7 @@ def _fold_choices_into_one( reasoning_contents: Final = (*(_message_reasoning_content(m) for m in messages), trailing_reasoning_content) reasoning_items: Final = ( *chain.from_iterable(_message_reasoning_items(m) for m in messages), - *(() if trailing_reasoning_item is None else (trailing_reasoning_item,)), + *trailing_reasoning_items, ) return Choices( message=Message( @@ -526,6 +535,61 @@ def _fold_choices_into_one( ) +def _with_replay_fields( + choice: "Choices", output_items: Sequence[object], *, completed: bool, structured_output: bool +) -> "Choices": + fields: Final = { + **(choice.message.provider_specific_fields or {}), + **replay_fields(output_items, choice.message, completed=completed, first_message_only=structured_output), + } + message: Final = choice.message.model_copy(update={"provider_specific_fields": fields or None}) + return choice.model_copy(update={"message": message}) + + +_STREAMED_OUTPUT_ITEMS: Final[TypeAdapter[tuple[Mapping[str, object], ...]]] = TypeAdapter( + tuple[Mapping[str, object], ...] +) + + +def completed_stream_history( + output_payload: object, + tool_search_fields: Mapping[str, object] | None, + *, + completed: bool, + structured_output: bool, +) -> dict[str, object] | None: # mutable-ok: Delta.provider_specific_fields is typed as a dict + items: Final = _STREAMED_OUTPUT_ITEMS.validate_python(output_payload) + calls: Final = tuple(item for item in items if item.get("type") in ("function_call", "custom_tool_call")) + streamed_message: Final = { + "role": "assistant", + "content": output_message_text(items, first_message_only=structured_output), + "tool_calls": [tool_call_dict_from_output_item(call, index) for index, call in enumerate(calls)], + "reasoning_items": list(_reasoning_items_from_output_items(items)), + "provider_specific_fields": tool_search_fields, + } + fields: Final = { + **(tool_search_fields or {}), + **replay_fields(items, streamed_message, completed=completed, first_message_only=structured_output), + } + return fields or None + + +def _assistant_phase_field(msg: object, replay_openai_history: bool, drop_params: bool) -> Mapping[str, object]: + match requested_phase(msg) if replay_openai_history else None: + case None: + return {} + case UnknownPhase(value=value) if drop_params: + verbose_logger.debug("Chat provider: dropping assistant phase=%r under drop_params", value) + return {} + case UnknownPhase(value=value): + raise litellm.UnsupportedParamsError( + message=f"phase must be 'commentary' or 'final_answer', got {value!r}. " + "To drop it, set `litellm.drop_params=True` or pass `drop_params=True`." + ) + case phase: + return {PHASE_FIELD: phase} + + def _responses_event_type(chunk: Mapping[str, object]) -> object: event_type: Final = chunk.get("type") return event_type.value if isinstance(event_type, ResponsesAPIStreamEvents) else event_type @@ -567,19 +631,6 @@ def _map_incomplete_reason_to_finish_reason(incomplete_reason: str | None) -> Li return "length" -_PROMPT_CACHE_BREAKPOINT: Final = TypeAdapter(PromptCacheBreakpoint) - - -def _prompt_cache_breakpoint_for_wire(marker: object, drop_params: bool) -> object: - if marker is None or not drop_params: - return marker - try: - return _PROMPT_CACHE_BREAKPOINT.validate_python(marker) - except ValidationError: - verbose_logger.debug("Chat provider: dropping malformed prompt_cache_breakpoint %r under drop_params", marker) - return None - - def _input_file_from_file_value(file_value: object) -> dict[str, object]: if not isinstance(file_value, dict): return {"type": "input_file"} @@ -667,15 +718,7 @@ def _reasoning_item_to_response_input( An item without an id is sent without one: the Responses API accepts that and verifies the encrypted content on its own, while it rejects any id it did not mint. """ - item_id: Final = r_item.get("id") - encrypted_content: Final = r_item.get("encrypted_content") - return { - "type": "reasoning", - **({"id": item_id} if item_id else {}), - # summary is always required by the Responses API, even when empty - "summary": r_item.get("summary") or [], - **({"encrypted_content": encrypted_content} if encrypted_content else {}), - } + return dict(reasoning_input_item(r_item.get("id"), r_item.get("summary"), r_item.get("encrypted_content"))) def _requested_defer_loading(tool: Mapping[str, object], function_tool: Mapping[str, object]) -> object: @@ -804,12 +847,14 @@ class LiteLLMResponsesTransformationHandler(CompletionTransformationBridge): keep_prompt_cache_breakpoints: bool = False, replay_tool_search: bool = False, include_namespace: bool = False, + replay_openai_history: bool = False, ) -> tuple[list[object], str | None]: converted_input_items, instructions = self._convert_chat_completion_messages_to_responses_input( messages, drop_params=drop_params, replay_tool_search=replay_tool_search, include_namespace=include_namespace, + replay_openai_history=replay_openai_history, ) return ( converted_input_items @@ -825,10 +870,18 @@ class LiteLLMResponsesTransformationHandler(CompletionTransformationBridge): drop_params: bool = False, replay_tool_search: bool = False, include_namespace: bool = False, + replay_openai_history: bool = False, ) -> tuple[list[object], str | None]: input_items: Final[list[object]] = [] instructions: str | None = None - custom_tool_call_ids: Final = frozenset( + replayed_turns: Final = tuple( + replay_items(msg, replay_tool_search=replay_tool_search) if replay_openai_history else None + for msg in messages + ) + replayed_custom_call_ids: Final = frozenset( + chain.from_iterable(turn.custom_call_ids for turn in replayed_turns if turn is not None) + ) + custom_tool_call_ids: Final = replayed_custom_call_ids | frozenset( tool_call["id"] for msg in messages if msg.get("role") == "assistant" and isinstance(msg.get("tool_calls"), list) @@ -849,7 +902,9 @@ class LiteLLMResponsesTransformationHandler(CompletionTransformationBridge): tool_calls = msg.get("tool_calls") tool_call_id = msg.get("tool_call_id") - if role == "system": + if (replayed_turn := replayed_turns[index]) is not None: + input_items.extend(replayed_turn.items) + elif role == "system": # Extract system message as instructions if isinstance(content, str) and index < leading_system_count: if instructions: @@ -915,6 +970,7 @@ class LiteLLMResponsesTransformationHandler(CompletionTransformationBridge): "content": self._convert_content_to_responses_format( content, "assistant", drop_params=drop_params ), + **_assistant_phase_field(msg, replay_openai_history, drop_params), } ) for tool_call in tool_calls: @@ -955,6 +1011,7 @@ class LiteLLMResponsesTransformationHandler(CompletionTransformationBridge): "content": self._convert_content_to_responses_format( content, cast(str, role), drop_params=drop_params ), + **_assistant_phase_field(msg, replay_openai_history and role == "assistant", drop_params), } ) elif role == "assistant": @@ -1081,6 +1138,7 @@ class LiteLLMResponsesTransformationHandler(CompletionTransformationBridge): keep_prompt_cache_breakpoints=supports_prompt_cache_breakpoint, replay_tool_search=_requests_tool_search(cast(object, optional_params)), # cast-ok: upcast include_namespace=True, + replay_openai_history=provider == "openai", ) # OpenAI's Responses API rejects an empty input. For a system-only # request, carry the system message as a system-role input item instead @@ -1165,6 +1223,8 @@ class LiteLLMResponsesTransformationHandler(CompletionTransformationBridge): output_items: Sequence[object], handle_raw_dict_callback: Callable[..., tuple["Choices | None", int]] | None = None, structured_output: bool = False, + replay_openai_history: bool = False, + completed: bool = False, ) -> list["Choices"]: """ Convert Responses API output items to chat completion choices. @@ -1174,6 +1234,8 @@ class LiteLLMResponsesTransformationHandler(CompletionTransformationBridge): handle_raw_dict_callback: Optional callback for handling raw dict items structured_output: The chat request carried a json response_format, so only the first message item becomes content + replay_openai_history: Record the output's item sequence for the next turn + completed: The response finished, so its item sequence is whole Returns: List of Choices objects @@ -1196,7 +1258,7 @@ class LiteLLMResponsesTransformationHandler(CompletionTransformationBridge): choices: Final[list[Choices]] = [] index = 0 reasoning_content: str | None = None - pending_reasoning_item: _BuiltReasoningItem | None = None + pending_reasoning_items: tuple[_BuiltReasoningItem, ...] = () # Collect all tool calls to put them in a single choice # (Chat Completions API expects all tool calls in one message) @@ -1205,12 +1267,19 @@ class LiteLLMResponsesTransformationHandler(CompletionTransformationBridge): for item in output_items: if isinstance(item, ResponseReasoningItem): - pending_reasoning_item = _build_reasoning_item( - item_id=item.id, - encrypted_content=getattr(item, "encrypted_content", None), - summary_raw=item.summary, + pending_reasoning_items = ( + *(pending_reasoning_items if replay_openai_history else ()), + _build_reasoning_item( + item_id=item.id, + encrypted_content=getattr(item, "encrypted_content", None), + summary_raw=item.summary, + ), + ) + reasoning_content = " ".join( + s["text"] + for s in chain.from_iterable(built["summary"] for built in pending_reasoning_items) + if s.get("text") ) - reasoning_content = " ".join(s["text"] for s in pending_reasoning_item["summary"] if s.get("text")) elif isinstance(item, ResponseOutputMessage): for content in item.content: @@ -1227,7 +1296,7 @@ class LiteLLMResponsesTransformationHandler(CompletionTransformationBridge): annotations=annotations, reasoning_items=cast( list[ChatCompletionReasoningItem] | None, - ([pending_reasoning_item] if pending_reasoning_item is not None else None), + (list(pending_reasoning_items) or None), ), ) @@ -1240,7 +1309,7 @@ class LiteLLMResponsesTransformationHandler(CompletionTransformationBridge): ) reasoning_content = None # flush - pending_reasoning_item = None # flush + pending_reasoning_items = () # flush index += 1 elif isinstance(item, ResponseFunctionToolCall): @@ -1300,16 +1369,17 @@ class LiteLLMResponsesTransformationHandler(CompletionTransformationBridge): output_items, "stop", tool_search_items=tool_search_items ) ] - return [ - _fold_choices_into_one( - choices=choices, - tool_calls=accumulated_tool_calls, - trailing_reasoning_content=reasoning_content, - trailing_reasoning_item=pending_reasoning_item, - tool_search_items=tool_search_items, - structured_output=structured_output, - ) - ] + folded: Final = _fold_choices_into_one( + choices=choices, + tool_calls=accumulated_tool_calls, + trailing_reasoning_content=reasoning_content, + trailing_reasoning_items=pending_reasoning_items, + tool_search_items=tool_search_items, + structured_output=structured_output, + ) + if not replay_openai_history: + return [folded] + return [_with_replay_fields(folded, output_items, completed=completed, structured_output=structured_output)] @staticmethod def _build_empty_choice( @@ -1352,7 +1422,7 @@ class LiteLLMResponsesTransformationHandler(CompletionTransformationBridge): recovered_output_items: Final[dict[int, dict[str, object]]] = {} recovered_text_only_items: Final[dict[int, dict[str, object]]] = {} - for chunk in raw_sse.splitlines(): + for chunk in split_sse_lines(raw_sse): parsed_chunk = parse_sse_json_chunk(chunk) if parsed_chunk is None: continue @@ -1443,6 +1513,11 @@ class LiteLLMResponsesTransformationHandler(CompletionTransformationBridge): structured_output=is_structured_output_request( cast("Mapping[str, object]", optional_params) # cast-ok: optional_params is an untyped dict ), + replay_openai_history=_served_provider( + cast("Mapping[str, object]", litellm_params) # cast-ok: litellm_params is an untyped dict + ) + == "openai", + completed=raw_response.status == "completed", ) response_is_incomplete: Final = raw_response.status == "incomplete" or ( @@ -1506,9 +1581,14 @@ class LiteLLMResponsesTransformationHandler(CompletionTransformationBridge): sync_stream: bool, json_mode: bool | None = False, structured_output: bool = False, + replays_openai_history: bool = False, ) -> BaseModelResponseIterator: return OpenAiResponsesToChatCompletionStreamIterator( - streaming_response, sync_stream, json_mode, structured_output=structured_output + streaming_response, + sync_stream, + json_mode, + structured_output=structured_output, + replays_openai_history=replays_openai_history, ) def _convert_content_str_to_input_text(self, content: str, role: str) -> dict[str, object]: @@ -1586,7 +1666,7 @@ class LiteLLMResponsesTransformationHandler(CompletionTransformationBridge): if original_type == "text": converted = with_prompt_cache_breakpoint( self._convert_content_str_to_input_text(item.get("text", ""), role), - _prompt_cache_breakpoint_for_wire(item.get("prompt_cache_breakpoint"), drop_params), + prompt_cache_breakpoint_for_wire(item.get("prompt_cache_breakpoint"), drop_params), ) result.append(converted) verbose_logger.debug("Chat provider: text -> %s", converted) @@ -1599,14 +1679,14 @@ class LiteLLMResponsesTransformationHandler(CompletionTransformationBridge): cast(ChatCompletionImageObject, item), role ), ), - _prompt_cache_breakpoint_for_wire(item.get("prompt_cache_breakpoint"), drop_params), + prompt_cache_breakpoint_for_wire(item.get("prompt_cache_breakpoint"), drop_params), ) result.append(converted) verbose_logger.debug("Chat provider: image_url -> %s", converted) elif original_type == "input_audio": converted = with_prompt_cache_breakpoint( {"type": "input_audio", "input_audio": item.get("input_audio")}, - _prompt_cache_breakpoint_for_wire(item.get("prompt_cache_breakpoint"), drop_params), + prompt_cache_breakpoint_for_wire(item.get("prompt_cache_breakpoint"), drop_params), ) result.append(converted) verbose_logger.debug("Chat provider: input_audio -> %s", converted) @@ -1622,7 +1702,7 @@ class LiteLLMResponsesTransformationHandler(CompletionTransformationBridge): _input_file_from_file_value( cast("ChatCompletionFileObject", item).get("file"), # cast-ok: type tag checked ), - _prompt_cache_breakpoint_for_wire(item.get("prompt_cache_breakpoint"), drop_params), + prompt_cache_breakpoint_for_wire(item.get("prompt_cache_breakpoint"), drop_params), ) result.append(converted) verbose_logger.debug("Chat provider: file -> %s", converted) @@ -1646,7 +1726,7 @@ class LiteLLMResponsesTransformationHandler(CompletionTransformationBridge): # Default to input_text for unknown types converted = with_prompt_cache_breakpoint( self._convert_content_str_to_input_text(str(item.get("text", item)), role), - _prompt_cache_breakpoint_for_wire(item.get("prompt_cache_breakpoint"), drop_params), + prompt_cache_breakpoint_for_wire(item.get("prompt_cache_breakpoint"), drop_params), ) result.append(converted) verbose_logger.debug("Chat provider: unknown(%s) -> %s", original_type, converted) @@ -1745,19 +1825,11 @@ class LiteLLMResponsesTransformationHandler(CompletionTransformationBridge): **cast(Reasoning, reasoning_effort) # cast-ok: dict is forwarded verbatim to the provider ) - # Check if auto-summary is enabled via flag or environment variable - # Priority: litellm.reasoning_auto_summary flag > LITELLM_REASONING_AUTO_SUMMARY env var - auto_summary_enabled: Final = ( - litellm.reasoning_auto_summary or os.getenv("LITELLM_REASONING_AUTO_SUMMARY", "false").lower() == "true" - ) - + summary: Final = opt_in_auto_reasoning_summary(model, custom_llm_provider) return ( - Reasoning( - effort=reasoning_effort, - summary="detailed" if model is None else auto_reasoning_summary(model, custom_llm_provider), - ) - if auto_summary_enabled - else Reasoning(effort=reasoning_effort) + Reasoning(effort=reasoning_effort) + if summary is None + else Reasoning(effort=reasoning_effort, summary=summary) ) _map_reasoning_effort = map_reasoning_effort @@ -1898,8 +1970,10 @@ class OpenAiResponsesToChatCompletionStreamIterator(BaseModelResponseIterator): sync_stream: bool, json_mode: bool | None = False, structured_output: bool = False, + replays_openai_history: bool = False, ): super().__init__(streaming_response, sync_stream, json_mode) + self._replays_openai_history: Final = replays_openai_history self._chat_completion_id: str | None = None self._served_service_tier: str | None = None self._tool_call_index_map: dict[int, int] = {} # mutable-ok: per-stream accumulator state @@ -1945,6 +2019,8 @@ class OpenAiResponsesToChatCompletionStreamIterator(BaseModelResponseIterator): def translate_responses_chunk_to_openai_stream( parsed_chunk: dict | BaseModel, tool_call_index_map: dict[int, int] | None = None, # mutable-ok: per-stream state, remapped in place + replays_openai_history: bool = False, + structured_output: bool = False, ) -> "ModelResponseStream": """ Translate a Responses API streaming chunk to OpenAI chat completion streaming format. @@ -1952,6 +2028,8 @@ class OpenAiResponsesToChatCompletionStreamIterator(BaseModelResponseIterator): Args: parsed_chunk: Dict containing the Responses API event chunk tool_call_index_map: Per-stream output_index -> sequential tool_call index map + replays_openai_history: Record the completed output's item sequence for the next turn + structured_output: Only the first message item became content Returns: ModelResponseStream: OpenAI-formatted streaming chunk @@ -2162,6 +2240,10 @@ class OpenAiResponsesToChatCompletionStreamIterator(BaseModelResponseIterator): terminal_reasoning_items_typed: Final = _as_chat_reasoning_items( _reasoning_items_from_output_items(output_items) ) + output_payload: Final = cast(object, output_items) # cast-ok: untyped + tool_search_fields: Final = _tool_search_provider_fields( + _tool_search_items_from_output_items(output_payload) + ) usage = None if response_data.get("usage"): @@ -2175,10 +2257,17 @@ class OpenAiResponsesToChatCompletionStreamIterator(BaseModelResponseIterator): StreamingChoices( index=0, delta=Delta( - content="", + content=None if replays_openai_history else "", reasoning_items=terminal_reasoning_items_typed, - provider_specific_fields=_tool_search_provider_fields( - _tool_search_items_from_output_items(cast(object, output_items)) # cast-ok: untyped + provider_specific_fields=( + completed_stream_history( + output_payload, + tool_search_fields, + completed=event_type == "response.completed", + structured_output=structured_output, + ) + if replays_openai_history + else tool_search_fields ), ), finish_reason=finish_reason, @@ -2224,7 +2313,10 @@ class OpenAiResponsesToChatCompletionStreamIterator(BaseModelResponseIterator): self._empty_content_chunk() if self._is_text_delta_after_structured_answer(chunk) else OpenAiResponsesToChatCompletionStreamIterator.translate_responses_chunk_to_openai_stream( - chunk, tool_call_index_map=self._tool_call_index_map + chunk, + tool_call_index_map=self._tool_call_index_map, + replays_openai_history=self._replays_openai_history, + structured_output=self._structured_output, ) ) if self._structured_output and _is_message_item_done(chunk): diff --git a/litellm/constants.py b/litellm/constants.py index 8cc51d0ab5e..42ad624026c 100644 --- a/litellm/constants.py +++ b/litellm/constants.py @@ -129,6 +129,7 @@ MAX_S3_OBJECT_DOWNLOAD_FILENAME_BYTES: Final = 1024 S3_LOG_PROMPTS_ONLY_ENV_VAR: Final = "S3_LOG_PROMPTS_ONLY" S3_PARTITION_GRANULARITY_ENV_VAR: Final = "S3_PARTITION_GRANULARITY" MAX_FILE_LIST_LIMIT: Final = 10000 +ANTHROPIC_DEFAULT_FILE_LIST_LIMIT: Final = 20 DEFAULT_SQS_FLUSH_INTERVAL_SECONDS: Final = get_env_int("DEFAULT_SQS_FLUSH_INTERVAL_SECONDS", 10) DEFAULT_NUM_WORKERS_LITELLM_PROXY: Final = get_env_int("DEFAULT_NUM_WORKERS_LITELLM_PROXY", 1) GRACEFUL_SHUTDOWN_TEARDOWN_HEADROOM_SECONDS: Final = 10 @@ -763,7 +764,6 @@ ANTHROPIC_WEB_SEARCH_TOOL_MAX_USES: Final = { # Used for web search interception across providers LITELLM_WEB_SEARCH_TOOL_NAME: Final = "litellm_web_search" -DEFAULT_IMAGE_ENDPOINT_MODEL: Final = "dall-e-2" DEFAULT_VIDEO_ENDPOINT_MODEL: Final = "sora-2" DEFAULT_GOOGLE_VIDEO_DURATION_SECONDS: Final = get_env_int("DEFAULT_GOOGLE_VIDEO_DURATION_SECONDS", 8) @@ -1035,6 +1035,7 @@ openai_compatible_endpoints: Final[list[str]] = [ "https://api-inference.modelscope.cn/v1", "https://api.moonshot.ai/v1", "https://api.publicai.co/v1", + "https://api.aiand.com/v1", "https://api.synthetic.new/openai/v1", "https://serverless.tensormesh.ai/v1", "https://api.stima.tech/v1", @@ -1063,6 +1064,7 @@ openai_compatible_endpoints: Final[list[str]] = [ "https://api.reka.ai/v1", "https://gigachat.devices.sberbank.ru/api/v1", "https://api.openinfer.ai/v1", + "https://vanchin.streamlake.ai/api/gateway/v1/endpoints", ] @@ -1095,11 +1097,13 @@ openai_compatible_providers: Final[list[str]] = [ "llamafile", "lm_studio", "galadriel", + "zerogpu", "github_copilot", # GitHub Copilot Chat API "chatgpt", # ChatGPT subscription API "novita", "meta_llama", "publicai", # PublicAI - JSON-configured provider + "aiand", # ai& - JSON-configured provider "synthetic", # Synthetic - JSON-configured provider "tensormesh", # Tensormesh - JSON-configured provider "apertis", # Apertis - JSON-configured provider @@ -1142,6 +1146,7 @@ openai_compatible_providers: Final[list[str]] = [ "prism", "sail", "reka", + "streamlake", ] OPENAI_AUDIO_TRANSCRIPTION_PROVIDERS: Final = frozenset({"openai"} | frozenset(openai_compatible_providers)) @@ -1667,6 +1672,7 @@ MANAGED_BACKGROUND_RESPONSE_METADATA_KEY: Final = "_managed_background_response" SESSION_ID_GENERATED_METADATA_KEY: Final = "litellm_session_id_generated" SESSION_ID_OMITTED_METADATA_KEY: Final = "litellm_session_id_omitted" CALLER_SESSION_ID_METADATA_KEY: Final = "litellm_caller_session_id" +COMPLEXITY_ROUTER_CHILD_SESSION_ID_METADATA_KEY: Final = "_complexity_router_child_session_id" LITELLM_TRUNCATED_PAYLOAD_FIELD: Final = "litellm_truncated" LITELLM_TRUNCATION_DB_SAFEGUARD_NOTE: Final = ( "Truncation is a DB storage safeguard. " @@ -1734,6 +1740,7 @@ PASS_THROUGH_HEADER_PREFIX: Final = "x-pass-" TYPESAFE_DANGER_ZONE_HEADER_PREFIX: Final = "typesafe-danger-zone-" INTERNAL_KWARG_PREFIX: Final = "_litellm_" CONTROL_OPTIONS_KEY: Final = f"{INTERNAL_KWARG_PREFIX}control" +SESSION_ID_FROM_TRACE_ID_PARAM_KEY: Final = f"{INTERNAL_KWARG_PREFIX}session_id_from_trace_id" AZURE_SPEECH_CUSTOM_LLM_PROVIDER: Final = "azure_speech" AZURE_SPEECH_PASS_THROUGH_ROUTE_PREFIX: Final = "/azure_speech" diff --git a/litellm/cost_calculator.py b/litellm/cost_calculator.py index 86b22069a39..b5dc0ce13de 100644 --- a/litellm/cost_calculator.py +++ b/litellm/cost_calculator.py @@ -688,7 +688,7 @@ def cost_per_token( elif call_type == "atranscription" or call_type == "transcription": if _transcription_usage_has_token_details(usage_block): return generic_cost_per_token( - model=model_without_prefix, + model=model, usage=usage_block, custom_llm_provider=custom_llm_provider, service_tier=service_tier, @@ -1592,14 +1592,6 @@ def completion_cost( for part in ws_tier_parts ) - if ( - (call_type == "aimage_generation" or call_type == "image_generation") - and model is not None - and isinstance(model, str) - and len(model) == 0 - and custom_llm_provider == "azure" - ): - model = "dall-e-2" # for dall-e-2, azure expects an empty model name # Handle Inputs to completion_cost prompt_tokens = 0 prompt_characters: int | None = None @@ -1674,7 +1666,8 @@ def completion_cost( raw_candidates if custom_pricing is True else _priced_candidates_before_unpriced_rules(raw_candidates) ) - for idx, (model, candidate_pricing_provider) in enumerate(potential_model_names): + for idx, (candidate_model, candidate_pricing_provider) in enumerate(potential_model_names): + model = candidate_model try: if verbose_logger.isEnabledFor(logging.DEBUG): verbose_logger.debug("selected model name for cost calculation: %s", model) diff --git a/litellm/exceptions.py b/litellm/exceptions.py index b8e933bf046..cd5139f5f79 100644 --- a/litellm/exceptions.py +++ b/litellm/exceptions.py @@ -232,7 +232,7 @@ class BadRequestError(openai.BadRequestError): litellm_debug_info: str | None = None, max_retries: int | None = None, num_retries: int | None = None, - body: dict | None = None, + body: Mapping[str, object] | None = None, ): self.status_code = 400 self.message = f"litellm.BadRequestError: {message}" @@ -276,7 +276,7 @@ class ImageFetchError(BadRequestError): litellm_debug_info: str | None = None, max_retries: int | None = None, num_retries: int | None = None, - body: dict | None = None, + body: Mapping[str, object] | None = None, ): super().__init__( message=message, @@ -317,6 +317,10 @@ class MalformedRequestFieldError(BadRequestError): pass +class UnsupportedEndpointError(BadRequestError): + pass + + class UnprocessableEntityError(openai.UnprocessableEntityError): def __init__( self, @@ -556,6 +560,7 @@ class ContextWindowExceededError(BadRequestError): llm_provider, response: httpx.Response | None = None, litellm_debug_info: str | None = None, + body: Mapping[str, object] | None = None, ): self.status_code = 400 self.model = model @@ -567,6 +572,7 @@ class ContextWindowExceededError(BadRequestError): llm_provider=self.llm_provider, response=response, litellm_debug_info=self.litellm_debug_info, + body=body, ) # Call the base class constructor with the parameters it needs # set after, to make it clear the raised error is a context window exceeded error @@ -685,7 +691,7 @@ class ContentPolicyViolationError(BadRequestError): response: httpx.Response | None = None, litellm_debug_info: str | None = None, provider_specific_fields: dict | None = None, - body: dict | None = None, + body: Mapping[str, object] | None = None, ): self.status_code = 400 self.message = f"litellm.ContentPolicyViolationError: {message}" @@ -1054,6 +1060,7 @@ LITELLM_EXCEPTION_TYPES: Final = [ BadRequestError, UnprocessableEntityError, UnsupportedParamsError, + UnsupportedEndpointError, Timeout, PermissionDeniedError, RateLimitError, diff --git a/litellm/google_genai/adapters/transformation.py b/litellm/google_genai/adapters/transformation.py index e1085dd7857..c1895376675 100644 --- a/litellm/google_genai/adapters/transformation.py +++ b/litellm/google_genai/adapters/transformation.py @@ -198,6 +198,11 @@ def _genai_message_part(part: object) -> _GenAIMessagePart | None: return ChatCompletionTextObject(type="text", text=text) if isinstance(text, str) else _genai_media_part(fields) +def _genai_content_parts(value: object) -> Sequence[object]: + single_part: Final = _validated(_CONFIG_FIELDS, value) + return (single_part,) if single_part is not None else _validated(_GENAI_CONTENT_PARTS, value) or () + + def _genai_message_parts(parts: object) -> tuple[_GenAIMessagePart, ...]: items: Final = _validated(_GENAI_CONTENT_PARTS, parts) or () return tuple(converted for part in items if (converted := _genai_message_part(part)) is not None) @@ -248,7 +253,7 @@ def _genai_content_messages(content: object) -> tuple[AllMessageValues, ...]: fields: Final = _validated(_CONFIG_FIELDS, content) if fields is None: return () - parts: Final = _validated(_GENAI_CONTENT_PARTS, fields.get("parts", ())) or () + parts: Final = _genai_content_parts(fields.get("parts", ())) converted: Final = _genai_message_parts(parts) role: Final = fields.get("role", "user") if role == "user": diff --git a/litellm/google_genai/streaming_iterator.py b/litellm/google_genai/streaming_iterator.py index a22c47cb1e7..08ac7d4f9dc 100644 --- a/litellm/google_genai/streaming_iterator.py +++ b/litellm/google_genai/streaming_iterator.py @@ -4,6 +4,7 @@ from typing import TYPE_CHECKING, Any, Final import litellm from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj +from litellm.llms.custom_httpx.sse_lines import aiter_sse_lines, iter_sse_lines from litellm.proxy.pass_through_endpoints.success_handler import ( PassThroughEndpointLogging, ) @@ -131,9 +132,9 @@ class GoogleGenAIGenerateContentStreamingIterator(BaseGoogleGenAIGenerateContent self.model = model self.generate_content_provider_config = generate_content_provider_config self.litellm_metadata = litellm_metadata - # Gemini streamGenerateContent uses SSE line framing; iter_lines keeps + # Gemini streamGenerateContent uses SSE line framing; iter_sse_lines keeps # large inlineData payloads (e.g. image/jpeg) intact within one event. - self.stream_iterator = response.iter_lines() + self.stream_iterator = iter_sse_lines(response.iter_text()) def __iter__(self): return self @@ -182,9 +183,9 @@ class AsyncGoogleGenAIGenerateContentStreamingIterator(BaseGoogleGenAIGenerateCo self.model = model self.generate_content_provider_config = generate_content_provider_config self.litellm_metadata = litellm_metadata - # Gemini streamGenerateContent uses SSE line framing; aiter_lines keeps + # Gemini streamGenerateContent uses SSE line framing; aiter_sse_lines keeps # large inlineData payloads (e.g. image/jpeg) intact within one event. - self.stream_iterator = response.aiter_lines() + self.stream_iterator = aiter_sse_lines(response.aiter_text()) def __aiter__(self): return self diff --git a/litellm/images/main.py b/litellm/images/main.py index 9c88e737a40..6e77cbb7046 100644 --- a/litellm/images/main.py +++ b/litellm/images/main.py @@ -1,9 +1,9 @@ import asyncio import contextvars import importlib -from collections.abc import Coroutine, Mapping +from collections.abc import Collection, Coroutine, Mapping from functools import partial -from typing import TYPE_CHECKING, Final, Literal, cast, overload +from typing import TYPE_CHECKING, Final, Literal, cast, get_type_hints, overload from pydantic import TypeAdapter, ValidationError @@ -16,7 +16,6 @@ import litellm # client is imported from litellm as it's a decorator from litellm import client -from litellm.constants import DEFAULT_IMAGE_ENDPOINT_MODEL from litellm.constants import request_timeout as DEFAULT_REQUEST_TIMEOUT from litellm.exceptions import LiteLLMUnknownProvider from litellm.litellm_core_utils.get_llm_provider_logic import ( @@ -61,6 +60,7 @@ from litellm.types.utils import ( ProviderRoutingHints, ) from litellm.utils import ( + EXTRA_BODY_ROUTING_KEYS, ImageResponse, ProviderConfigManager, get_llm_provider, @@ -284,6 +284,12 @@ def image_generation( extra_headers: Final = kwargs.get("extra_headers", None) headers: Final[dict] = kwargs.get("headers", None) or {} base_model: Final = kwargs.get("base_model", None) + call_kwargs: Final = cast(Mapping[str, object], kwargs) # cast-ok: image_generation's **kwargs is untyped + max_retries: Final = call_kwargs.get("max_retries") + is_router_call: Final = any( + isinstance(call_metadata := call_kwargs.get(k), Mapping) and "model_group" in call_metadata + for k in ("metadata", "litellm_metadata") + ) if extra_headers is not None: headers.update(extra_headers) model_response: ImageResponse = litellm.utils.ImageResponse() @@ -292,17 +298,14 @@ def image_generation( if custom_llm_provider == "chatgpt" or (model is not None and model.startswith("chatgpt/")) else None ) - dynamic_api_key: str | None = None - if model is not None or custom_llm_provider is not None: - model, custom_llm_provider, dynamic_api_key, api_base = get_llm_provider( - model=model, - custom_llm_provider=custom_llm_provider, - api_base=api_base, - litellm_params=chatgpt_params, - ) - else: - model = "dall-e-2" - custom_llm_provider = "openai" # default to dall-e-2 on openai + if model is None and custom_llm_provider is None: + raise litellm.BadRequestError(message="model is required", model="", llm_provider="") + model, custom_llm_provider, dynamic_api_key, api_base = get_llm_provider( + model=model, + custom_llm_provider=custom_llm_provider, + api_base=api_base, + litellm_params=chatgpt_params, + ) model_response.hidden_params["model"] = model openai_params: Final = [ "user", @@ -460,7 +463,7 @@ def image_generation( litellm.LlmProviders.QWENCLOUD, litellm.LlmProviders.QWEN_AI_PLATFORM, litellm.LlmProviders.EDENAI, - ): + ) or (custom_llm_provider == litellm.LlmProviders.TENCENT and image_generation_config is not None): if image_generation_config is None: raise ValueError(f"image generation config is not supported for {custom_llm_provider}") @@ -550,6 +553,7 @@ def image_generation( optional_params["extra_headers"] = extra_headers # Forward OpenAI organization if present (set by proxy pre-call utils) organization: Final[str | None] = kwargs.get("organization", None) + sdk_max_retries: Final = 0 if is_router_call else max_retries model_response = openai_chat_completions.image_generation( model=model, prompt=prompt, @@ -557,7 +561,9 @@ def image_generation( api_key=api_key or dynamic_api_key, api_base=api_base, logging_obj=litellm_logging_obj, - optional_params=optional_params, + optional_params=( + optional_params if sdk_max_retries is None else {**optional_params, "max_retries": sdk_max_retries} + ), model_response=model_response, organization=organization, aimg_generation=aimg_generation, @@ -702,7 +708,7 @@ async def aimage_variation(*args, **kwargs) -> ImageResponse: @client def image_variation( image: FileTypes, - model: str = "dall-e-2", # set to dall-e-2 by default - like OpenAI. + model: str | None = None, n: int = 1, response_format: Literal["url", "b64_json"] = "url", size: str | None = None, @@ -718,7 +724,7 @@ def image_variation( litellm_params: Final = get_litellm_params(**kwargs) # get the custom llm provider model, custom_llm_provider, dynamic_api_key, api_base = get_llm_provider( - model=model, + model=model or "", custom_llm_provider=litellm_params.get("custom_llm_provider", None), api_base=litellm_params.get("api_base", None), api_key=litellm_params.get("api_key", None), @@ -737,7 +743,7 @@ def image_variation( response: ImageResponse | None = None provider_config: Final = ProviderConfigManager.get_provider_model_info( - model=model or "", # openai defaults to dall-e-2 + model=model, provider=llm_provider, ) @@ -762,7 +768,7 @@ def image_variation( model_response=model_response, api_key=api_key, api_base=api_base, - model=model, + model=model or None, image=image, timeout=litellm_params.get("timeout", None), custom_llm_provider=custom_llm_provider, @@ -780,7 +786,7 @@ def image_variation( model_response=model_response, api_key=api_key, api_base=api_base, - model=model, + model=model or None, image=image, timeout=litellm_params.get("timeout", None) or DEFAULT_REQUEST_TIMEOUT, custom_llm_provider=custom_llm_provider, @@ -798,6 +804,32 @@ def image_variation( return response +_IMAGE_EDIT_OPENAI_PARAMS: Final = frozenset(get_type_hints(ImageEditOptionalRequestParams)) +_DROP_PARAM_KWARGS: Final = frozenset({"drop_params", "additional_drop_params"}) +_ADDITIONAL_DROP_PARAMS: Final = TypeAdapter[tuple[str, ...]](tuple[str, ...]) + + +def _listed_drop_params(additional_drop_params: object) -> tuple[str, ...]: + try: + return _ADDITIONAL_DROP_PARAMS.validate_python(additional_drop_params) + except ValidationError: + return () + + +def _tokenhub_passthrough_edit_params( + non_default_params: Mapping[str, object], + extra_body: Mapping[str, object] | None, + mapped_params: Collection[str], + additional_drop_params: Collection[str] | None, +) -> Mapping[str, object]: + dropped: Final = frozenset(additional_drop_params or ()) + unmapped_excluded: Final = _DROP_PARAM_KWARGS | _IMAGE_EDIT_OPENAI_PARAMS | frozenset(mapped_params) | dropped + return { + **{key: value for key, value in non_default_params.items() if key not in unmapped_excluded}, + **{key: value for key, value in (extra_body or {}).items() if key not in dropped | EXTRA_BODY_ROUTING_KEYS}, + } + + @client def image_edit( image: FileTypes | list[FileTypes] | None = None, @@ -865,7 +897,7 @@ def image_edit( # get llm provider logic litellm_params: Final = GenericLiteLLMParams(**kwargs) model, custom_llm_provider, _, _ = get_llm_provider( - model=model or DEFAULT_IMAGE_ENDPOINT_MODEL, + model=model or "", custom_llm_provider=custom_llm_provider, ) @@ -926,22 +958,24 @@ def image_edit( raise ValueError(f"image edit is not supported for {custom_llm_provider}") local_vars.update(kwargs) + provider_supported_params: Final[frozenset[str]] = frozenset( + image_edit_provider_config.get_supported_openai_params(model) + ) # Get ImageEditOptionalRequestParams with only valid parameters image_edit_optional_params: Final[ImageEditOptionalRequestParams] = ( _get_ImageEditRequestUtils().get_requested_image_edit_optional_param( local_vars, - provider_supported_params=frozenset( - image_edit_provider_config.get_supported_openai_params(model) - ).intersection(non_default_params), + provider_supported_params=provider_supported_params.intersection(non_default_params), ) ) # Get optional parameters for the responses API + additional_drop_params: Final = _listed_drop_params(kwargs.get("additional_drop_params")) image_edit_request_params: Final[dict] = _get_ImageEditRequestUtils().get_optional_params_image_edit( model=model, image_edit_provider_config=image_edit_provider_config, image_edit_optional_params=image_edit_optional_params, drop_params=kwargs.get("drop_params"), - additional_drop_params=kwargs.get("additional_drop_params"), + additional_drop_params=additional_drop_params, ) if image_edit_provider_config.use_multipart_form_data() and ( @@ -1030,7 +1064,19 @@ def image_edit( image=images, prompt=prompt, image_edit_provider_config=image_edit_provider_config, - image_edit_optional_request_params=image_edit_request_params, + image_edit_optional_request_params={ + **image_edit_request_params, + **( + _tokenhub_passthrough_edit_params( + non_default_params, + extra_body if isinstance(extra_body, dict) else None, + provider_supported_params, + additional_drop_params, + ) + if custom_llm_provider == litellm.LlmProviders.TENCENT.value + else {} + ), + }, custom_llm_provider=custom_llm_provider, litellm_params=litellm_params, logging_obj=litellm_logging_obj, @@ -1053,7 +1099,7 @@ def image_edit( @client async def aimage_edit( - image: FileTypes | list[FileTypes], + image: FileTypes | list[FileTypes] | None, model: str, prompt: str, mask: str | None = None, @@ -1093,7 +1139,7 @@ async def aimage_edit( model=model, api_base=local_vars.get("base_url", None) ) - images: Final = image if isinstance(image, list) else [image] + images: Final = image if isinstance(image, list) else ([image] if image is not None else []) func: Final = partial( image_edit, diff --git a/litellm/images/utils.py b/litellm/images/utils.py index 24454954714..4e0cde24a68 100644 --- a/litellm/images/utils.py +++ b/litellm/images/utils.py @@ -1,6 +1,9 @@ +import base64 +import os from collections.abc import Collection, Mapping from io import BufferedReader, BytesIO -from typing import Any, Final, cast, get_type_hints +from pathlib import Path +from typing import Any, Final, Protocol, cast, get_type_hints, runtime_checkable import litellm from litellm.litellm_core_utils.token_counter import get_image_type @@ -16,7 +19,7 @@ class ImageEditRequestUtils: image_edit_provider_config: BaseImageEditConfig, image_edit_optional_params: ImageEditOptionalRequestParams, drop_params: bool | None = None, - additional_drop_params: list[str] | None = None, + additional_drop_params: Collection[str] | None = None, ) -> dict: """ Get optional parameters for the image edit API. @@ -145,3 +148,36 @@ class ImageEditRequestUtils: except Exception: # If anything goes wrong, default to PNG return FILE_MIME_TYPES[FileType.PNG] + + +@runtime_checkable +class _SeekableBinaryReader(Protocol): + def tell(self) -> int: ... + + def seek(self, offset: int) -> int: ... + + def read(self) -> bytes: ... + + +def _read_image_bytes(image: object) -> bytes: + if isinstance(image, bytes): + return image + if isinstance(image, tuple): + return _read_image_bytes(image[1]) + if isinstance(image, os.PathLike): + return Path(image).read_bytes() + if isinstance(image, _SeekableBinaryReader): + position: Final = image.tell() + image.seek(0) + data: Final = image.read() + image.seek(position) + return data + raise ValueError(f"Unsupported image type for image edit: {type(image).__name__}") + + +def image_to_data_url(image: object) -> str: + if isinstance(image, str): + return image + image_bytes: Final = _read_image_bytes(image) + mime_type: Final = ImageEditRequestUtils.get_image_content_type(image_bytes) + return f"data:{mime_type};base64,{base64.b64encode(image_bytes).decode('utf-8')}" diff --git a/litellm/integrations/anthropic_cache_control_hook.py b/litellm/integrations/anthropic_cache_control_hook.py index b0deec24c1a..fc1f1830129 100644 --- a/litellm/integrations/anthropic_cache_control_hook.py +++ b/litellm/integrations/anthropic_cache_control_hook.py @@ -72,6 +72,8 @@ MAX_CACHE_CONTROL_BLOCKS: Final = 4 CACHE_BREAKPOINT_KEYS: Final = ("cache_control", "prompt_cache_breakpoint") OPENAI_PROMPT_CACHE_BREAKPOINT_MIN_GPT_VERSION: Final = (5, 6) _GPT_VERSION_PATTERN: Final = re.compile(r"^gpt-(\d+)(?:\.(\d+))?") +_FINE_TUNED_BASE_PATTERN: Final = re.compile(r"^ft:([^:]+)") +_O_SERIES_PATTERN: Final = re.compile(r"^o\d+(?:-|$)") OPENAI_PROMPT_CACHE_BREAKPOINT_BLOCK_TYPES: Final = frozenset( {"text", "image", "image_url", "file", "input_audio", "input_text", "input_image", "input_file"} ) @@ -125,6 +127,10 @@ def _served_provider_for_model(model: str) -> str | None: def supports_openai_prompt_cache_breakpoint(model: str, custom_llm_provider: str | None = None) -> bool: + return openai_prompt_cache_breakpoint_support(model, custom_llm_provider) is True + + +def openai_prompt_cache_breakpoint_support(model: str, custom_llm_provider: str | None = None) -> bool | None: hosted_flag: Final = ( None if custom_llm_provider is None @@ -135,9 +141,19 @@ def supports_openai_prompt_cache_breakpoint(model: str, custom_llm_provider: str model_map_flag: Final = _model_map_prompt_cache_breakpoint_flag(model) if model_map_flag is not None: return model_map_flag - version_match: Final = _GPT_VERSION_PATTERN.match(model.rsplit("/", 1)[-1].lower()) - if version_match is None: + fine_tuned_base: Final = _FINE_TUNED_BASE_PATTERN.match(model.rsplit("/", 1)[-1]) + if fine_tuned_base is not None: + return False if _named_model_breakpoint_support(fine_tuned_base.group(1)) is False else None + return _named_model_breakpoint_support(model) + + +def _named_model_breakpoint_support(model: str) -> bool | None: + bare_model: Final = model.rsplit("/", 1)[-1].lower() + if _O_SERIES_PATTERN.match(bare_model) is not None: return False + version_match: Final = _GPT_VERSION_PATTERN.match(bare_model) + if version_match is None: + return None version: Final = (int(version_match.group(1)), int(version_match.group(2) or 0)) return version >= OPENAI_PROMPT_CACHE_BREAKPOINT_MIN_GPT_VERSION diff --git a/litellm/integrations/opentelemetry_utils/gen_ai_semconv.py b/litellm/integrations/opentelemetry_utils/gen_ai_semconv.py index 035e5c5db10..84c4b2e58ab 100644 --- a/litellm/integrations/opentelemetry_utils/gen_ai_semconv.py +++ b/litellm/integrations/opentelemetry_utils/gen_ai_semconv.py @@ -35,6 +35,7 @@ from enum import Enum from typing import TYPE_CHECKING, Final, Protocol from litellm.integrations.otel.mappers.utils import drop_none +from litellm.integrations.otel.model.semconv import PASSTHROUGH_OPERATION_KEY, GenAIOperation from litellm.litellm_core_utils.safe_json_dumps import safe_dumps if TYPE_CHECKING: @@ -148,8 +149,11 @@ class OTELGenAISemconvMixin: """Map a LiteLLM ``call_type`` to spec ``gen_ai.operation.name``. Substring match (e.g. ``aembedding`` -> ``embeddings``); defaults to - ``chat``. + ``chat``. A pass-through call's operation, stored under ``PASSTHROUGH_OPERATION_KEY``, wins. """ + passthrough_operation: Final = kwargs.get(PASSTHROUGH_OPERATION_KEY) # pyright: ignore[reportUnknownMemberType, reportUnknownVariableType] # kwargs is an untyped dict + if isinstance(passthrough_operation, GenAIOperation): + return passthrough_operation.value call_type: Final = kwargs.get("call_type", "") or "" match call_type: case s if "embedding" in s: diff --git a/litellm/integrations/otel/logger.py b/litellm/integrations/otel/logger.py index e09226ac9cd..4c5e65ff07d 100644 --- a/litellm/integrations/otel/logger.py +++ b/litellm/integrations/otel/logger.py @@ -600,6 +600,7 @@ class OpenTelemetryV2(CustomLogger): trace=call.trace, session_id=call.session_id, metadata_keys=tuple(self.config.baggage_metadata_keys), + operation=call.operation, ) end_time_ns: Final = to_ns(end_time) if carrier is not None and carrier.span is not None: diff --git a/litellm/integrations/otel/model/metadata.py b/litellm/integrations/otel/model/metadata.py index b96ed55872d..a9a57de04ac 100644 --- a/litellm/integrations/otel/model/metadata.py +++ b/litellm/integrations/otel/model/metadata.py @@ -49,7 +49,7 @@ from litellm.constants import ( LITELLM_LOGGING_NO_UPSTREAM_LLM_CALL, SESSION_ID_GENERATED_METADATA_KEY, ) -from litellm.integrations.otel.model.semconv import resolve_operation +from litellm.integrations.otel.model.semconv import PASSTHROUGH_OPERATION_KEY, GenAIOperation, resolve_operation from litellm.integrations.otel.model.trace_controls import TraceControls, caller_trace_controls from litellm.integrations.otel.model.utils import as_str, as_str_mapping, to_seconds from litellm.types.utils import InternalCallOrigin @@ -262,6 +262,7 @@ class LLMCallEvent: # never hands off to a provider, so ``upstream_started`` stays False even # though the call completed and is worth a span. cache_hit: bool + operation: GenAIOperation # A best-effort ``"{operation} {model}"`` name known at ``pre_call`` time. The # span is renamed from the typed payload at close (``finish_span``); this only # needs to be reasonable for a span that never gets closed (a leak). @@ -275,7 +276,7 @@ class LLMCallEvent: def from_dict(cls, kwargs: Mapping[str, object]) -> LLMCallEvent: raw_payload: Final = kwargs.get("standard_logging_object") payload: Final = cast("StandardLoggingPayload", raw_payload) if raw_payload else None - operation: Final = resolve_operation(as_str(kwargs.get("call_type"))) + operation: Final = resolve_operation(as_str(kwargs.get("call_type")), kwargs.get(PASSTHROUGH_OPERATION_KEY)) model: Final = as_str(kwargs.get("model")) or "" trace: Final = caller_trace_controls(kwargs) return cls( @@ -288,6 +289,7 @@ class LLMCallEvent: upstream_start_seconds=_epoch_seconds(kwargs.get("api_call_start_time")), purpose=internal_call_origin(payload, kwargs), cache_hit=bool(payload.get("cache_hit")) if payload else False, # pyright: ignore[reportUnknownMemberType] # TypedDict .get on a str key is partially unknown + operation=operation, provisional_span_name=f"{operation.value} {model}".strip(), time_to_first_chunk_seconds=time_to_first_chunk_seconds(kwargs), completion_start_seconds=_epoch_seconds(kwargs.get("completion_start_time")), diff --git a/litellm/integrations/otel/model/payloads.py b/litellm/integrations/otel/model/payloads.py index 21b2f44f077..7a62ed6aed9 100644 --- a/litellm/integrations/otel/model/payloads.py +++ b/litellm/integrations/otel/model/payloads.py @@ -464,6 +464,7 @@ class LLMCallSpanData: session_id: str | None = None, *, metadata_keys: tuple[str, ...] = (), + operation: GenAIOperation | None = None, ) -> LLMCallSpanData: params: Final = cast(Mapping[str, object], payload.get("model_parameters") or {}) cache_hit: Final = as_bool(payload.get("cache_hit")) is True # pyright: ignore[reportUnknownMemberType] # TypedDict .get on a str key is partially unknown @@ -486,13 +487,13 @@ class LLMCallSpanData: # no prompt/response text. finish_reasons: Final = _finish_reasons(choices_out) call_type: Final = as_str(payload.get("call_type")) - operation: Final = resolve_operation(call_type) + resolved_operation: Final = operation or resolve_operation(call_type) embedding_output: Final = ( - EmbeddingOutput.from_response(response) if operation is GenAIOperation.EMBEDDINGS else None + EmbeddingOutput.from_response(response) if resolved_operation is GenAIOperation.EMBEDDINGS else None ) cost_lookup_failed: Final = payload.get("response_cost_failure_debug_info") is not None and not cache_hit return cls( - operation=operation, + operation=resolved_operation, provider=resolve_provider(as_str(payload.get("custom_llm_provider"))), request_model=context.request_model, response_model=context.response_model, diff --git a/litellm/integrations/otel/model/semconv.py b/litellm/integrations/otel/model/semconv.py index b7f955a75ed..8d186a2715a 100644 --- a/litellm/integrations/otel/model/semconv.py +++ b/litellm/integrations/otel/model/semconv.py @@ -34,6 +34,7 @@ class GenAIOperation(str, Enum): LITELLM_VECTOR_STORE_FILE_MANAGEMENT = "litellm.vector_store_file_management" LITELLM_RESPONSES_MANAGEMENT = "litellm.responses_management" LITELLM_MODERATION = "litellm.moderation" + LITELLM_PASSTHROUGH = "litellm.passthrough" class GenAIOutputType(str, Enum): @@ -482,14 +483,21 @@ def resolve_provider(custom_llm_provider: str | None) -> str: return mapped.value if mapped is not None else custom_llm_provider -def resolve_operation(call_type: str | None) -> GenAIOperation: +PASSTHROUGH_OPERATION_KEY: Final = "passthrough_gen_ai_operation" + + +def resolve_operation(call_type: str | None, passthrough_operation: object = None) -> GenAIOperation: """Map a litellm ``call_type`` to a ``gen_ai.operation.name`` value. An unmapped call type still falls back to ``chat`` so every series keeps an operation label, but it logs at debug rather than falling through silently: a new call type mislabelled as ``chat`` mixes its latency and cost into everyone's chat charts, which is invisible until someone reads the numbers. + + A pass-through call's operation, stored under ``PASSTHROUGH_OPERATION_KEY``, wins over its call type. """ + if isinstance(passthrough_operation, GenAIOperation): + return passthrough_operation if not call_type: return GenAIOperation.CHAT mapped: Final = _OPERATION_BY_CALL_TYPE.get(call_type.lower()) diff --git a/litellm/integrations/otel/model/spans.py b/litellm/integrations/otel/model/spans.py index d8be607150c..4907bd4368d 100644 --- a/litellm/integrations/otel/model/spans.py +++ b/litellm/integrations/otel/model/spans.py @@ -338,6 +338,8 @@ _PRISMA_MODELS: Final[frozenset[str]] = frozenset( "LiteLLM_ToolTable", "LiteLLM_TelemetryReport", "LiteLLM_AccessGroupTable", + "LiteLLM_AccountingDelivery", + "LiteLLM_AccountingEvent", "LiteLLM_ClaudeCodePluginTable", "LiteLLM_MemoryTable", "LiteLLM_AdaptiveRouterState", @@ -434,6 +436,7 @@ _POSTGRES_OPERATION_BY_CALL_TYPE: Final[Mapping[str, PostgresOperation]] = Mappi "reset_budget_windows": PostgresOperation("select", None), "write_budget_windows": PostgresOperation("update", None), "roll_window_spend_row": PostgresOperation("update", None), + "open_window_spend_row": PostgresOperation("upsert", None), "seed_window_spend": PostgresOperation("select", None), "select_window_spend_rows": PostgresOperation("select", None), "commit_window_spend_updates": PostgresOperation("upsert", None), diff --git a/litellm/integrations/otel/mount.py b/litellm/integrations/otel/mount.py index c0d42eeb5c5..9d6c5fca75c 100644 --- a/litellm/integrations/otel/mount.py +++ b/litellm/integrations/otel/mount.py @@ -22,6 +22,7 @@ from litellm.integrations.otel.model.config import is_otel_v2_enabled if TYPE_CHECKING: from fastapi import FastAPI from opentelemetry.trace import Span, TracerProvider + from starlette.types import ASGIApp, Receive, Scope, Send # Routes excluded from server-span tracing by default: high-frequency pollers and # static UI/docs assets, none of which are LLM traffic. Entries are substring-matched @@ -44,6 +45,33 @@ _DEFAULT_EXCLUDED_ROUTES: Final = ( ) _DEFAULT_EXCLUDED_URLS: Final = ",".join(_DEFAULT_EXCLUDED_ROUTES) + +class _RequestTraceExclusionMiddleware: + def __init__(self, app: "ASGIApp", excluded_urls: str) -> None: + from opentelemetry.util.http import parse_excluded_urls + + self.app = app + self.excluded_urls = parse_excluded_urls(excluded_urls) + + async def __call__(self, scope: "Scope", receive: "Receive", send: "Send") -> None: + if scope["type"] not in ("http", "websocket"): + await self.app(scope, receive, send) + return + from opentelemetry.instrumentation.asgi import ( # pyright: ignore[reportMissingTypeStubs] # upstream ships no py.typed marker + get_host_port_url_tuple, # pyright: ignore[reportUnknownVariableType] # upstream URL helper has no annotations + ) + + from litellm.integrations.otel.plumbing.context import ( + request_trace_scope, + request_traces_excluded, + ) + + url: Final = str(get_host_port_url_tuple(scope)[2]) # pyright: ignore[reportUnknownArgumentType] # upstream constructs a str URL but leaves its return type unannotated + excluded: Final = request_traces_excluded() or self.excluded_urls.url_disabled(url) + with request_trace_scope(excluded): + await self.app(scope, receive, send) + + # Passthrough routes are catch-alls (e.g. "/openai/{endpoint:path}"), so the # default OTel server-span name "{method} {route}" collapses every upstream # endpoint into "POST /openai/{endpoint:path}". The hook below renames those spans @@ -129,6 +157,8 @@ def instrument_fastapi_app(app: "FastAPI", tracer_provider: "TracerProvider | No if app.middleware_stack is not None: verbose_logger.debug("Skipping OTel V2 FastAPI instrumentation: the app has already started") return + if getattr(app, "_is_instrumented_by_opentelemetry", False): + return # Lazy: only the V2-enabled path needs the optional # ``opentelemetry-instrumentation-fastapi`` package, which is not part of the @@ -151,11 +181,7 @@ def instrument_fastapi_app(app: "FastAPI", tracer_provider: "TracerProvider | No claim_server_span(span) _passthrough_span_name_hook(span, scope) - excluded_urls: Final = ( - os.environ.get("OTEL_PYTHON_FASTAPI_EXCLUDED_URLS") - if "OTEL_PYTHON_FASTAPI_EXCLUDED_URLS" in os.environ - else _DEFAULT_EXCLUDED_URLS - ) + excluded_urls: Final = os.environ.get("OTEL_PYTHON_FASTAPI_EXCLUDED_URLS", _DEFAULT_EXCLUDED_URLS) FastAPIInstrumentor.instrument_app( app, tracer_provider=tracer_provider, @@ -166,6 +192,12 @@ def instrument_fastapi_app(app: "FastAPI", tracer_provider: "TracerProvider | No # template in their name, which can't be rewritten from a hook. exclude_spans=["receive", "send"], ) + instrumented_stack: Final = app.build_middleware_stack + + def build_middleware_stack() -> "ASGIApp": + return _RequestTraceExclusionMiddleware(instrumented_stack(), excluded_urls) + + app.build_middleware_stack = build_middleware_stack # rebind-ok: wrap the complete ASGI stack if get_global_response_propagator() is None: set_global_response_propagator(UpstreamFirstTraceResponsePropagator()) except Exception as e: diff --git a/litellm/integrations/otel/plumbing/context.py b/litellm/integrations/otel/plumbing/context.py index d0c419abe87..b328b281dde 100644 --- a/litellm/integrations/otel/plumbing/context.py +++ b/litellm/integrations/otel/plumbing/context.py @@ -30,6 +30,21 @@ if TYPE_CHECKING: _PROPAGATOR: Final = TraceContextTextMapPropagator() _W3C_TRACE_HEADERS: Final = frozenset(("traceparent", "tracestate")) +_request_traces_excluded: Final[ContextVar[bool]] = ContextVar("litellm_otel_request_traces_excluded", default=False) + + +def request_traces_excluded() -> bool: + return _request_traces_excluded.get() + + +@contextmanager +def request_trace_scope(excluded: bool) -> Generator[None]: + token: Final = _request_traces_excluded.set(excluded) + try: + yield + finally: + _request_traces_excluded.reset(token) + # The request's root span — the FastAPI-owned SERVER span — captured ONCE when the # proxy first resolves it, so request-level spans (the LLM call, guardrails) can diff --git a/litellm/integrations/otel/plumbing/metrics.py b/litellm/integrations/otel/plumbing/metrics.py index 72d51471ba2..1197ae055d0 100644 --- a/litellm/integrations/otel/plumbing/metrics.py +++ b/litellm/integrations/otel/plumbing/metrics.py @@ -26,6 +26,7 @@ from litellm.integrations.opentelemetry import ( ) from litellm.integrations.otel.model.metadata import time_to_first_chunk_seconds from litellm.integrations.otel.model.semconv import ( + PASSTHROUGH_OPERATION_KEY, Error, GenAI, Metric, @@ -280,7 +281,9 @@ class GenAIMetricRecorder: def _common_attributes(self, kwargs: Mapping[str, Any]) -> dict: params: Final = kwargs.get("litellm_params") or {} common_attrs: Final[dict] = { - GenAI.OPERATION_NAME: resolve_operation(kwargs.get("call_type")).value, + GenAI.OPERATION_NAME: resolve_operation( + kwargs.get("call_type"), kwargs.get(PASSTHROUGH_OPERATION_KEY) + ).value, **_provider_attributes(params.get("custom_llm_provider")), GenAI.REQUEST_MODEL: kwargs.get("model"), "gen_ai.framework": "litellm", diff --git a/litellm/integrations/otel/plumbing/providers.py b/litellm/integrations/otel/plumbing/providers.py index 9736192a816..a369e352609 100644 --- a/litellm/integrations/otel/plumbing/providers.py +++ b/litellm/integrations/otel/plumbing/providers.py @@ -35,7 +35,8 @@ from opentelemetry.sdk.trace.export import ( from opentelemetry.sdk.trace.export.in_memory_span_exporter import ( InMemorySpanExporter, ) -from opentelemetry.trace import Span, SpanContext, SpanKind, Status, StatusCode, Tracer +from opentelemetry.sdk.trace.sampling import Decision, Sampler, SamplingResult +from opentelemetry.trace import Link, Span, SpanContext, SpanKind, Status, StatusCode, Tracer, TraceState from opentelemetry.util.re import parse_env_headers from opentelemetry.util.types import Attributes, AttributeValue @@ -68,6 +69,7 @@ from litellm.integrations.otel.model.semconv import ( from litellm.integrations.otel.model.spans import LiteLLMSpanKind from litellm.integrations.otel.plumbing.context import ( request_destinations, + request_traces_excluded, suppressed_backends, ) from litellm.integrations.otel.plumbing.otlp_tls import resolve_otlp_http_tls @@ -1499,6 +1501,28 @@ def _spec_processor( return _MessageContentFilter(scoped) if strip_message_content else scoped +class _RequestExclusionSampler(Sampler): + def __init__(self, delegate: Sampler) -> None: + self.delegate = delegate + + def should_sample( + self, + parent_context: Context | None, + trace_id: int, + name: str, + kind: SpanKind | None = None, + attributes: Attributes = None, + links: Sequence[Link] | None = None, + trace_state: TraceState | None = None, + ) -> SamplingResult: + if request_traces_excluded(): + return SamplingResult(Decision.DROP) + return self.delegate.should_sample(parent_context, trace_id, name, kind, attributes, links, trace_state) + + def get_description(self) -> str: + return f"RequestExclusion({self.delegate.get_description()})" + + def build_tracer_provider( config: OpenTelemetryV2Config, exporter: SpanExporter | None = None, @@ -1531,6 +1555,7 @@ def build_tracer_provider( destination asked for. """ provider: Final = TracerProvider(resource=build_resource(config)) + provider.sampler = _RequestExclusionSampler(provider.sampler) if baggage_processor is None: baggage_processor = LiteLLMBaggageSpanProcessor(allowed_keys=config.baggage_promoted_keys) provider.add_span_processor(baggage_processor) diff --git a/litellm/integrations/prometheus.py b/litellm/integrations/prometheus.py index bc8344fa686..d15956c0e95 100644 --- a/litellm/integrations/prometheus.py +++ b/litellm/integrations/prometheus.py @@ -1173,8 +1173,8 @@ class PrometheusLogger(CustomLogger): # Build label filters from valid configurations label_filters: Final = self._build_label_filters(parsed_configs) - # Pretty print the processed configuration - self._pretty_print_prometheus_config(label_filters) + if litellm.suppress_startup_output is not True: + self._pretty_print_prometheus_config(label_filters) return label_filters def _parse_exclude_config(self) -> tuple[frozenset[str], frozenset[str]]: diff --git a/litellm/integrations/websearch_interception/handler.py b/litellm/integrations/websearch_interception/handler.py index a38b8bed595..6e1ba3eea08 100644 --- a/litellm/integrations/websearch_interception/handler.py +++ b/litellm/integrations/websearch_interception/handler.py @@ -97,6 +97,8 @@ WEBSEARCH_NATIVE_BLOCKS_METADATA_KEY: Final = "websearch_native_blocks" _RESPONSE_CONTENT_FIELD: Final = "content" +_CLAUDE_CODE_WEB_SEARCH_PROMPT_PREFIX: Final = "Perform a web search for the query:" + _ResponseT: Final = TypeVar("_ResponseT") @@ -363,7 +365,8 @@ class WebSearchInterceptionLogger(CustomLogger): get_last_user_message, ) - query: Final = get_last_user_message(cast(list[AllMessageValues], messages)) + last_user_message: Final = get_last_user_message(cast(list[AllMessageValues], messages)) or "" + query: Final = last_user_message.removeprefix(_CLAUDE_CODE_WEB_SEARCH_PROMPT_PREFIX).strip() if not query: return None diff --git a/litellm/interactions/__init__.py b/litellm/interactions/__init__.py index 6129cd87153..d5dd9b2cd00 100644 --- a/litellm/interactions/__init__.py +++ b/litellm/interactions/__init__.py @@ -32,11 +32,11 @@ Usage: # Create a managed agent on the provider side result = litellm.interactions.agents.create( - name="waverunner", + id="waverunner", custom_llm_provider="gemini", api_key="...", - base_agent="gemini-2.5-flash", - instructions="You are a helpful assistant.", + base_agent="antigravity-preview-09-2026", + system_instruction="You are a helpful assistant.", ) Methods: diff --git a/litellm/interactions/agents/__init__.py b/litellm/interactions/agents/__init__.py index 21fd2dc0742..a81b35c2fc7 100644 --- a/litellm/interactions/agents/__init__.py +++ b/litellm/interactions/agents/__init__.py @@ -3,11 +3,11 @@ litellm.interactions.agents Full CRUD SDK for provider-side managed agents (e.g. Gemini v1beta/agents). - litellm.interactions.agents.create(name=..., ...) + litellm.interactions.agents.create(id=..., ...) litellm.interactions.agents.list(api_key=...) - litellm.interactions.agents.get(name=..., ...) - litellm.interactions.agents.delete(name=..., ...) - litellm.interactions.agents.list_versions(name=..., ...) + litellm.interactions.agents.get(id=..., ...) + litellm.interactions.agents.delete(id=..., ...) + litellm.interactions.agents.list_versions(id=..., ...) Async counterparts: acreate, alist, aget, adelete, alist_versions """ diff --git a/litellm/interactions/agents/http_handler.py b/litellm/interactions/agents/http_handler.py index 2afedc34d36..fa1e52e6842 100644 --- a/litellm/interactions/agents/http_handler.py +++ b/litellm/interactions/agents/http_handler.py @@ -17,6 +17,7 @@ from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLogging from litellm.llms.base_llm.agents.transformation import BaseAgentsAPIConfig from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler, HTTPHandler from litellm.types.agents import ( + AgentCreateRequest, AgentCreateResponse, AgentDeleteResult, AgentListResponse, @@ -35,7 +36,7 @@ class AgentsHTTPHandler(InteractionsHTTPHandler): def create_agent( self, agents_api_config: BaseAgentsAPIConfig, - name: str, + create_request: AgentCreateRequest, litellm_params: GenericLiteLLMParams, logging_obj: LiteLLMLoggingObj, extra_headers: dict[str, str] | None = None, @@ -47,7 +48,7 @@ class AgentsHTTPHandler(InteractionsHTTPHandler): if _is_async: return self.async_create_agent( agents_api_config=agents_api_config, - name=name, + create_request=create_request, litellm_params=litellm_params, logging_obj=logging_obj, extra_headers=extra_headers, @@ -63,12 +64,13 @@ class AgentsHTTPHandler(InteractionsHTTPHandler): api_base=litellm_params.get("api_base"), litellm_params=dict(litellm_params), ) - data: Final = agents_api_config.transform_create_request(name=name, litellm_params=dict(litellm_params)) - if extra_body: - data.update(extra_body) + data: Final = { + **agents_api_config.transform_create_request(create_request), + **(extra_body or {}), + } logging_obj.pre_call( - input=name, + input=create_request.id, api_key="", additional_args={ "complete_input_dict": data, @@ -85,12 +87,12 @@ class AgentsHTTPHandler(InteractionsHTTPHandler): original_response=response.text, additional_args={"complete_input_dict": data}, ) - return agents_api_config.transform_create_response(raw_response=response, name=name) + return agents_api_config.transform_create_response(raw_response=response, name=create_request.id) async def async_create_agent( self, agents_api_config: BaseAgentsAPIConfig, - name: str, + create_request: AgentCreateRequest, litellm_params: GenericLiteLLMParams, logging_obj: LiteLLMLoggingObj, extra_headers: dict[str, str] | None = None, @@ -106,12 +108,13 @@ class AgentsHTTPHandler(InteractionsHTTPHandler): api_base=litellm_params.get("api_base"), litellm_params=dict(litellm_params), ) - data: Final = agents_api_config.transform_create_request(name=name, litellm_params=dict(litellm_params)) - if extra_body: - data.update(extra_body) + data: Final = { + **agents_api_config.transform_create_request(create_request), + **(extra_body or {}), + } logging_obj.pre_call( - input=name, + input=create_request.id, api_key="", additional_args={ "complete_input_dict": data, @@ -130,7 +133,7 @@ class AgentsHTTPHandler(InteractionsHTTPHandler): original_response=response.text, additional_args={"complete_input_dict": data}, ) - return agents_api_config.transform_create_response(raw_response=response, name=name) + return agents_api_config.transform_create_response(raw_response=response, name=create_request.id) # ------------------------------------------------------------------ # # LIST # diff --git a/litellm/interactions/agents/main.py b/litellm/interactions/agents/main.py index 02b0ef4807f..5e2bfa9cea2 100644 --- a/litellm/interactions/agents/main.py +++ b/litellm/interactions/agents/main.py @@ -6,41 +6,47 @@ Usage: # Create response = litellm.interactions.agents.create( - name="waverunner", + id="waverunner", custom_llm_provider="gemini", api_key="...", - base_agent="gemini-2.5-flash", - instructions="You are a helpful assistant.", + base_agent="antigravity-preview-09-2026", + system_instruction="You are a helpful assistant.", + agent_config={"type": "antigravity", "model": "gemini-3.8-flash"}, ) # List response = litellm.interactions.agents.list(api_key="...", custom_llm_provider="gemini") # Get - response = litellm.interactions.agents.get(name="waverunner", api_key="...") + response = litellm.interactions.agents.get(id="waverunner", api_key="...") # Delete - result = litellm.interactions.agents.delete(name="waverunner", api_key="...") + result = litellm.interactions.agents.delete(id="waverunner", api_key="...") # List versions - result = litellm.interactions.agents.list_versions(name="waverunner", api_key="...") + result = litellm.interactions.agents.list_versions(id="waverunner", api_key="...") # Async versions: acreate, alist, aget, adelete, alist_versions """ import asyncio import contextvars -from collections.abc import Coroutine, Mapping +from collections.abc import Coroutine, Mapping, Sequence +from dataclasses import dataclass from functools import partial +from types import MappingProxyType from typing import Any, Final import httpx +from pydantic import ValidationError import litellm from litellm.interactions.agents.http_handler import agents_http_handler from litellm.interactions.agents.utils import get_provider_agents_api_config +from litellm.litellm_core_utils.core_helpers import drops_unsupported_params from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj from litellm.types.agents import ( + AgentCreateRequest, AgentCreateResponse, AgentDeleteResult, AgentListResponse, @@ -89,14 +95,120 @@ def _make_logging_obj( return litellm_logging_obj +@dataclass(frozen=True, slots=True) +class _InvalidAgentRequest: + message: str + + +def _alias_conflict(field: str, value: str | None, alias: str, alias_value: str | None) -> str | None: + if value is None or alias_value is None or value == alias_value: + return None + return f"'{alias}' is an alias of '{field}', but the request gives them different values. Pass only '{field}'." + + +def _agent_id_or_error(id: str | None, name: str | None) -> str | _InvalidAgentRequest: + conflict: Final = _alias_conflict("id", id, "name", name) + if conflict is not None: + return _InvalidAgentRequest(conflict) + agent_id: Final = id if id is not None else name + if agent_id is None: + return _InvalidAgentRequest("Missing required parameter: 'id' (or its alias 'name').") + return agent_id + + +def _required_agent_id(id: str | None, name: str | None, llm_provider: str) -> str: + agent_id: Final = _agent_id_or_error(id, name) + if isinstance(agent_id, _InvalidAgentRequest): + raise litellm.BadRequestError(message=agent_id.message, model=id or name or "", llm_provider=llm_provider) + return agent_id + + # ================================================================== # # CREATE # # ================================================================== # +_CREATE_FIELD_SHAPES: Final = MappingProxyType( + { + "id": "a string", + "base_agent": "a string", + "agent_config": "an object", + "system_instruction": "a string", + "base_environment": "an environment id string or an object", + "description": "a string", + "tools": "a list of objects", + } +) + + +def _invalid_create_fields_message(invalid_fields: frozenset[str], caller_names: Mapping[str, str]) -> str: + problems: Final = "; ".join( + f"'{caller_names.get(field, field)}' must be {_CREATE_FIELD_SHAPES[field]}" for field in sorted(invalid_fields) + ) + drop_hint: Final = "" if "id" in invalid_fields else " Set drop_params to drop invalid optional fields." + return f"Invalid agent create request: {problems}.{drop_hint}" + + +def _validated_create_request( + fields: Mapping[str, object], drop_invalid_fields: bool, caller_names: Mapping[str, str] +) -> AgentCreateRequest | _InvalidAgentRequest: + try: + return AgentCreateRequest.model_validate(fields) + except ValidationError as e: + invalid_fields: Final = frozenset(str(error["loc"][0]) for error in e.errors()) + if drop_invalid_fields and "id" not in invalid_fields: + return AgentCreateRequest.model_validate( + {field: value for field, value in fields.items() if field not in invalid_fields} + ) + return _InvalidAgentRequest(_invalid_create_fields_message(invalid_fields, caller_names)) + + +def _create_request_or_error( + id: str | None, + name: str | None, + base_agent: str | None, + agent_config: Mapping[str, object] | None, + system_instruction: str | None, + instructions: str | None, + base_environment: InteractionEnvironment | None, + description: str | None, + tools: Sequence[Mapping[str, object]] | None, + drop_invalid_fields: bool, +) -> AgentCreateRequest | _InvalidAgentRequest: + agent_id: Final = _agent_id_or_error(id, name) + if isinstance(agent_id, _InvalidAgentRequest): + return agent_id + instruction_conflict: Final = _alias_conflict( + "system_instruction", system_instruction, "instructions", instructions + ) + if instruction_conflict is not None and not drop_invalid_fields: + return _InvalidAgentRequest(instruction_conflict) + sent_only_instructions: Final = system_instruction is None and instructions is not None + return _validated_create_request( + MappingProxyType( + { + "id": agent_id, + "base_agent": base_agent, + "agent_config": agent_config, + "system_instruction": instructions if sent_only_instructions else system_instruction, + "base_environment": base_environment, + "description": description, + "tools": tools, + } + ), + drop_invalid_fields, + MappingProxyType( + { + "id": "name" if id is None else "id", + "system_instruction": "instructions" if sent_only_instructions else "system_instruction", + } + ), + ) + + @client async def acreate( - name: str, + id: str | None = None, base_agent: str | None = None, instructions: str | None = None, base_environment: InteractionEnvironment | None = None, @@ -104,6 +216,12 @@ async def acreate( extra_headers: dict[str, str] | None = None, extra_body: Mapping[str, object] | None = None, timeout: float | httpx.Timeout | None = None, + *, + name: str | None = None, + agent_config: Mapping[str, object] | None = None, + system_instruction: str | None = None, + description: str | None = None, + tools: Sequence[Mapping[str, object]] | None = None, **kwargs, ) -> AgentCreateResponse: """Async: Create a managed agent on the provider side.""" @@ -113,7 +231,7 @@ async def acreate( kwargs["acreate_agent"] = True func: Final = partial( create, - name=name, + id=id, base_agent=base_agent, instructions=instructions, base_environment=base_environment, @@ -121,6 +239,11 @@ async def acreate( extra_headers=extra_headers, extra_body=extra_body, timeout=timeout, + name=name, + agent_config=agent_config, + system_instruction=system_instruction, + description=description, + tools=tools, **kwargs, ) ctx: Final = contextvars.copy_context() @@ -130,7 +253,7 @@ async def acreate( return init_response except Exception as e: raise litellm.exception_type( - model=name, + model=id or name or "", custom_llm_provider=custom_llm_provider or "gemini", original_exception=e, completion_kwargs=local_vars, @@ -140,7 +263,7 @@ async def acreate( @client def create( - name: str, + id: str | None = None, base_agent: str | None = None, instructions: str | None = None, base_environment: InteractionEnvironment | None = None, @@ -148,40 +271,61 @@ def create( extra_headers: dict[str, str] | None = None, extra_body: Mapping[str, object] | None = None, timeout: float | httpx.Timeout | None = None, + *, + name: str | None = None, + agent_config: Mapping[str, object] | None = None, + system_instruction: str | None = None, + description: str | None = None, + tools: Sequence[Mapping[str, object]] | None = None, **kwargs, ) -> AgentCreateResponse | Coroutine[object, object, AgentCreateResponse]: """ Sync: Create a managed agent on the provider side. Args: - name: Name for the agent (required). - base_agent: Base agent to derive from (e.g. "waverunner"). - instructions: System instructions for the agent. + id: Identifier for the agent. Exactly one of ``id`` or its alias ``name`` is required. + base_agent: Base agent to derive from (e.g. "antigravity-preview-09-2026"). + instructions: Alias of ``system_instruction``. base_environment: Environment to fork from — an env_id string or a dict like ``{"type": "remote", "sources": [...]}``. custom_llm_provider: Provider to use, e.g. "gemini". extra_headers: Additional HTTP headers. extra_body: Additional request body fields. timeout: Request timeout. + name: Alias of ``id``. + agent_config: Agent runtime config, e.g. ``{"type": "antigravity", "model": "gemini-3.8-flash"}``. + system_instruction: System instruction for the agent. + description: Description of the agent for developers. + tools: Tools available to the agent, e.g. ``[{"type": "code_execution"}]``. **kwargs: Forwarded to GenericLiteLLMParams (api_key, api_base, etc.). """ local_vars: Final = locals() - custom_llm_provider = custom_llm_provider or kwargs.get("custom_llm_provider") or "gemini" + custom_llm_provider = custom_llm_provider or "gemini" try: _is_async: Final = kwargs.pop("acreate_agent", False) is True - if base_agent is not None: - kwargs["base_agent"] = base_agent - if instructions is not None: - kwargs["instructions"] = instructions - if base_environment is not None: - kwargs["base_environment"] = base_environment + create_request: Final = _create_request_or_error( + id=id, + name=name, + base_agent=base_agent, + agent_config=agent_config, + system_instruction=system_instruction, + instructions=instructions, + base_environment=base_environment, + description=description, + tools=tools, + drop_invalid_fields=drops_unsupported_params(kwargs.get("drop_params")), + ) + if isinstance(create_request, _InvalidAgentRequest): + raise litellm.BadRequestError( + message=create_request.message, model=id or name or "", llm_provider=custom_llm_provider + ) kwargs.setdefault("custom_llm_provider", custom_llm_provider) litellm_params: Final = GenericLiteLLMParams(**kwargs) - logging_obj: Final = _make_logging_obj(kwargs, name, custom_llm_provider, "create_agent", {}) + logging_obj: Final = _make_logging_obj(kwargs, create_request.id, custom_llm_provider, "create_agent", {}) config: Final = _get_agents_api_config(custom_llm_provider) return agents_http_handler.create_agent( agents_api_config=config, - name=name, + create_request=create_request, litellm_params=litellm_params, logging_obj=logging_obj, extra_headers=extra_headers, @@ -191,7 +335,7 @@ def create( ) except Exception as e: raise litellm.exception_type( - model=name, + model=id or name or "", custom_llm_provider=custom_llm_provider, original_exception=e, completion_kwargs=local_vars, @@ -247,7 +391,7 @@ def list( ) -> AgentListResponse | Coroutine[object, object, AgentListResponse]: """Sync: List all agents on the provider side.""" local_vars: Final = locals() - custom_llm_provider = custom_llm_provider or kwargs.get("custom_llm_provider") or "gemini" + custom_llm_provider = custom_llm_provider or "gemini" try: _is_async: Final = kwargs.pop("alist_agents", False) is True kwargs.setdefault("custom_llm_provider", custom_llm_provider) @@ -279,19 +423,22 @@ def list( @client async def aget( - name: str, + id: str | None = None, custom_llm_provider: str | None = None, extra_headers: dict[str, str] | None = None, timeout: float | httpx.Timeout | None = None, + *, + name: str | None = None, **kwargs, ) -> AgentCreateResponse: - """Async: Get a specific agent by name.""" + """Async: Get a specific agent by id (``name`` is an alias of ``id``).""" local_vars: Final = locals() try: loop: Final = asyncio.get_event_loop() kwargs["aget_agent"] = True func: Final = partial( get, + id=id, name=name, custom_llm_provider=custom_llm_provider or "gemini", extra_headers=extra_headers, @@ -305,7 +452,7 @@ async def aget( return init_response except Exception as e: raise litellm.exception_type( - model=name, + model=id or name or "", custom_llm_provider=custom_llm_provider or "gemini", original_exception=e, completion_kwargs=local_vars, @@ -315,24 +462,27 @@ async def aget( @client def get( - name: str, + id: str | None = None, custom_llm_provider: str | None = None, extra_headers: dict[str, str] | None = None, timeout: float | httpx.Timeout | None = None, + *, + name: str | None = None, **kwargs, ) -> AgentCreateResponse | Coroutine[object, object, AgentCreateResponse]: - """Sync: Get a specific agent by name.""" + """Sync: Get a specific agent by id (``name`` is an alias of ``id``).""" local_vars: Final = locals() - custom_llm_provider = custom_llm_provider or kwargs.get("custom_llm_provider") or "gemini" + custom_llm_provider = custom_llm_provider or "gemini" try: _is_async: Final = kwargs.pop("aget_agent", False) is True + agent_id: Final = _required_agent_id(id, name, custom_llm_provider) kwargs.setdefault("custom_llm_provider", custom_llm_provider) litellm_params: Final = GenericLiteLLMParams(**kwargs) - logging_obj: Final = _make_logging_obj(kwargs, name, custom_llm_provider, "get_agent", {"name": name}) + logging_obj: Final = _make_logging_obj(kwargs, agent_id, custom_llm_provider, "get_agent", {"name": agent_id}) config: Final = _get_agents_api_config(custom_llm_provider) return agents_http_handler.get_agent( agents_api_config=config, - name=name, + name=agent_id, litellm_params=litellm_params, logging_obj=logging_obj, extra_headers=extra_headers, @@ -341,7 +491,7 @@ def get( ) except Exception as e: raise litellm.exception_type( - model=name, + model=id or name or "", custom_llm_provider=custom_llm_provider, original_exception=e, completion_kwargs=local_vars, @@ -356,19 +506,22 @@ def get( @client async def adelete( - name: str, + id: str | None = None, custom_llm_provider: str | None = None, extra_headers: dict[str, str] | None = None, timeout: float | httpx.Timeout | None = None, + *, + name: str | None = None, **kwargs, ) -> AgentDeleteResult: - """Async: Delete a specific agent by name.""" + """Async: Delete a specific agent by id (``name`` is an alias of ``id``).""" local_vars: Final = locals() try: loop: Final = asyncio.get_event_loop() kwargs["adelete_agent"] = True func: Final = partial( delete, + id=id, name=name, custom_llm_provider=custom_llm_provider or "gemini", extra_headers=extra_headers, @@ -382,7 +535,7 @@ async def adelete( return init_response except Exception as e: raise litellm.exception_type( - model=name, + model=id or name or "", custom_llm_provider=custom_llm_provider or "gemini", original_exception=e, completion_kwargs=local_vars, @@ -392,24 +545,29 @@ async def adelete( @client def delete( - name: str, + id: str | None = None, custom_llm_provider: str | None = None, extra_headers: dict[str, str] | None = None, timeout: float | httpx.Timeout | None = None, + *, + name: str | None = None, **kwargs, ) -> AgentDeleteResult | Coroutine[object, object, AgentDeleteResult]: - """Sync: Delete a specific agent by name.""" + """Sync: Delete a specific agent by id (``name`` is an alias of ``id``).""" local_vars: Final = locals() - custom_llm_provider = custom_llm_provider or kwargs.get("custom_llm_provider") or "gemini" + custom_llm_provider = custom_llm_provider or "gemini" try: _is_async: Final = kwargs.pop("adelete_agent", False) is True + agent_id: Final = _required_agent_id(id, name, custom_llm_provider) kwargs.setdefault("custom_llm_provider", custom_llm_provider) litellm_params: Final = GenericLiteLLMParams(**kwargs) - logging_obj: Final = _make_logging_obj(kwargs, name, custom_llm_provider, "delete_agent", {"name": name}) + logging_obj: Final = _make_logging_obj( + kwargs, agent_id, custom_llm_provider, "delete_agent", {"name": agent_id} + ) config: Final = _get_agents_api_config(custom_llm_provider) return agents_http_handler.delete_agent( agents_api_config=config, - name=name, + name=agent_id, litellm_params=litellm_params, logging_obj=logging_obj, extra_headers=extra_headers, @@ -418,7 +576,7 @@ def delete( ) except Exception as e: raise litellm.exception_type( - model=name, + model=id or name or "", custom_llm_provider=custom_llm_provider, original_exception=e, completion_kwargs=local_vars, @@ -433,19 +591,22 @@ def delete( @client async def alist_versions( - name: str, + id: str | None = None, custom_llm_provider: str | None = None, extra_headers: dict[str, str] | None = None, timeout: float | httpx.Timeout | None = None, + *, + name: str | None = None, **kwargs, ) -> AgentVersionsResponse: - """Async: List versions of a specific agent.""" + """Async: List versions of a specific agent by id (``name`` is an alias of ``id``).""" local_vars: Final = locals() try: loop: Final = asyncio.get_event_loop() kwargs["alist_agent_versions"] = True func: Final = partial( list_versions, + id=id, name=name, custom_llm_provider=custom_llm_provider or "gemini", extra_headers=extra_headers, @@ -459,7 +620,7 @@ async def alist_versions( return init_response except Exception as e: raise litellm.exception_type( - model=name, + model=id or name or "", custom_llm_provider=custom_llm_provider or "gemini", original_exception=e, completion_kwargs=local_vars, @@ -469,24 +630,29 @@ async def alist_versions( @client def list_versions( - name: str, + id: str | None = None, custom_llm_provider: str | None = None, extra_headers: dict[str, str] | None = None, timeout: float | httpx.Timeout | None = None, + *, + name: str | None = None, **kwargs, ) -> AgentVersionsResponse | Coroutine[object, object, AgentVersionsResponse]: - """Sync: List versions of a specific agent.""" + """Sync: List versions of a specific agent by id (``name`` is an alias of ``id``).""" local_vars: Final = locals() - custom_llm_provider = custom_llm_provider or kwargs.get("custom_llm_provider") or "gemini" + custom_llm_provider = custom_llm_provider or "gemini" try: _is_async: Final = kwargs.pop("alist_agent_versions", False) is True + agent_id: Final = _required_agent_id(id, name, custom_llm_provider) kwargs.setdefault("custom_llm_provider", custom_llm_provider) litellm_params: Final = GenericLiteLLMParams(**kwargs) - logging_obj: Final = _make_logging_obj(kwargs, name, custom_llm_provider, "list_agent_versions", {"name": name}) + logging_obj: Final = _make_logging_obj( + kwargs, agent_id, custom_llm_provider, "list_agent_versions", {"name": agent_id} + ) config: Final = _get_agents_api_config(custom_llm_provider) return agents_http_handler.list_agent_versions( agents_api_config=config, - name=name, + name=agent_id, litellm_params=litellm_params, logging_obj=logging_obj, extra_headers=extra_headers, @@ -495,7 +661,7 @@ def list_versions( ) except Exception as e: raise litellm.exception_type( - model=name, + model=id or name or "", custom_llm_provider=custom_llm_provider, original_exception=e, completion_kwargs=local_vars, diff --git a/litellm/interactions/main.py b/litellm/interactions/main.py index 498e6e20aec..acd43c9b830 100644 --- a/litellm/interactions/main.py +++ b/litellm/interactions/main.py @@ -49,6 +49,7 @@ from litellm.interactions.utils import ( InteractionsAPIRequestUtils, get_provider_interactions_api_config, ) +from litellm.litellm_core_utils.core_helpers import drops_unsupported_params from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj from litellm.types.interactions import ( CancelInteractionResult, @@ -100,6 +101,8 @@ async def acreate( timeout: float | httpx.Timeout | None = None, # LiteLLM params custom_llm_provider: str | None = None, + *, + agent_config: Mapping[str, object] | None = None, **kwargs, ) -> InteractionsAPIResponse | AsyncIterator[InteractionsAPIStreamingResponse]: """ @@ -121,6 +124,7 @@ async def acreate( string, or a config object such as ``{"type": "remote", "sources": [...]}`` / ``{"type": "remote", "network": {...}}`` + agent_config: Agent runtime config, e.g. ``{"type": "antigravity", "model": "gemini-3.8-flash"}`` response_modalities: Requested response modalities (TEXT, IMAGE, AUDIO) response_format: JSON schema for response format response_mime_type: MIME type of the response @@ -155,6 +159,7 @@ async def acreate( store=store, background=background, environment=environment, + agent_config=agent_config, response_modalities=response_modalities, response_format=response_format, response_mime_type=response_mime_type, @@ -225,6 +230,8 @@ def create( timeout: float | httpx.Timeout | None = None, # LiteLLM params custom_llm_provider: str | None = None, + *, + agent_config: Mapping[str, object] | None = None, **kwargs, ) -> ( InteractionsAPIResponse @@ -250,6 +257,7 @@ def create( string, or a config object such as ``{"type": "remote", "sources": [...]}`` / ``{"type": "remote", "network": {...}}`` + agent_config: Agent runtime config, e.g. ``{"type": "antigravity", "model": "gemini-3.8-flash"}`` response_modalities: Requested response modalities (TEXT, IMAGE, AUDIO) response_format: JSON schema for response format response_mime_type: MIME type of the response @@ -300,6 +308,15 @@ def create( # Check if this is a bridge provider (litellm_responses) - similar to responses API # Either provider is explicitly "litellm_responses" or no config found (bridge to responses) if custom_llm_provider == "litellm_responses" or interactions_api_config is None: + if optional_params.get("agent_config") is not None and not drops_unsupported_params( + kwargs.get("drop_params") + ): + raise litellm.UnsupportedParamsError( + message=f"'agent_config' is not supported for {custom_llm_provider} interactions. " + "Set drop_params to drop it.", + llm_provider=custom_llm_provider, + model=model, + ) # Bridge to litellm.responses() for non-native providers from litellm.interactions.litellm_responses_transformation.handler import ( LiteLLMResponsesInteractionsHandler, diff --git a/litellm/interactions/streaming_iterator.py b/litellm/interactions/streaming_iterator.py index f4ad57bf7b4..c7faa3fc510 100644 --- a/litellm/interactions/streaming_iterator.py +++ b/litellm/interactions/streaming_iterator.py @@ -21,6 +21,7 @@ from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLogging from litellm.litellm_core_utils.llm_response_utils.get_api_base import get_api_base from litellm.litellm_core_utils.thread_pool_executor import executor from litellm.llms.base_llm.interactions.transformation import BaseInteractionsAPIConfig +from litellm.llms.custom_httpx.sse_lines import aiter_sse_lines, iter_sse_lines from litellm.types.interactions import ( InteractionsAPIStreamingResponse, ) @@ -145,7 +146,7 @@ class InteractionsAPIStreamingIterator(BaseInteractionsAPIStreamingIterator): litellm_metadata=litellm_metadata, custom_llm_provider=custom_llm_provider, ) - self.stream_iterator = response.aiter_lines() + self.stream_iterator = aiter_sse_lines(response.aiter_text()) def __aiter__(self): return self @@ -212,7 +213,7 @@ class SyncInteractionsAPIStreamingIterator(BaseInteractionsAPIStreamingIterator) litellm_metadata=litellm_metadata, custom_llm_provider=custom_llm_provider, ) - self.stream_iterator = response.iter_lines() + self.stream_iterator = iter_sse_lines(response.iter_text()) def __iter__(self): return self diff --git a/litellm/litellm_core_utils/README.md b/litellm/litellm_core_utils/README.md index a5f5e8326b9..331f4adccbb 100644 --- a/litellm/litellm_core_utils/README.md +++ b/litellm/litellm_core_utils/README.md @@ -11,4 +11,4 @@ Core files: - `duration_parser.py`: code for parsing durations - e.g. "1d", "1mo", "10s" - `api_route_to_call_types.py`: mapping of API routes to their corresponding CallTypes (e.g., `/chat/completions` -> [acompletion, completion]) -Tokenizer factories return Python tokenizer objects by default. Set `LITELLM_RUST=1` or call `litellm.rust(True)` before constructing tokenizers to select the Rust backend through `Route.TOKENIZER` in the Rust catalog. Missing native bindings or unsupported native features fall back to Python. Existing tokenizer objects keep their selected backend. Rust-backed tokenizer objects carry the read-only `tiktoken.Encoding` / `tokenizers.Tokenizer` surface and are immutable: `enable_padding`, `enable_truncation` and `add_tokens` stay on the Python tokenizer. +Tokenizer factories return Python tokenizer objects by default. Set `LITELLM_RUST=1` or call `litellm.rust(True)` before constructing tokenizers to select the Rust backend through `Route.TOKENIZER` in the Rust catalog. Unsupported native features fall back to Python. Existing tokenizer objects keep their selected backend. Rust-backed tokenizer objects carry the read-only `tiktoken.Encoding` / `tokenizers.Tokenizer` surface and are immutable: `enable_padding`, `enable_truncation` and `add_tokens` stay on the Python tokenizer. diff --git a/litellm/litellm_core_utils/audio_utils/utils.py b/litellm/litellm_core_utils/audio_utils/utils.py index dab3e48f91a..640559ac7e2 100644 --- a/litellm/litellm_core_utils/audio_utils/utils.py +++ b/litellm/litellm_core_utils/audio_utils/utils.py @@ -2,8 +2,12 @@ Utils used for litellm.transcription() and litellm.atranscription() """ +import base64 +import binascii import hashlib +import math import os +from collections.abc import Sequence from dataclasses import dataclass from typing import Final @@ -331,6 +335,45 @@ def calculate_request_duration(file: FileTypes) -> float | None: return None +DEFAULT_AUDIO_TOKEN_ESTIMATE: Final = 300 +AUDIO_TOKENS_PER_SECOND: Final = 10 +AUDIO_BYTES_PER_TOKEN: Final = 1600 +_MAX_AUDIO_ESTIMATE_BYTES: Final = 16 * 1024 * 1024 + + +def _audio_token_rate(model: str) -> int | None: + if model.startswith( + ("gemini-", "gemini/gemini-", "vertex_ai/gemini-", "vertex_ai_beta/gemini-", "openrouter/google/gemini-") + ): + family: Final = model.rsplit("/", 1)[-1] + return 25 if family.startswith(("gemini-3-", "gemini-3.")) else 32 + if model.startswith(("gpt-", "openai/gpt-", "azure/gpt-", "openrouter/openai/gpt-")): + return AUDIO_TOKENS_PER_SECOND + return None + + +def estimate_audio_tokens(data: str | None, models: Sequence[str] = (), fallback_model: str | None = None) -> int: + """Estimate audio tokens from container duration within a bounded decoding budget.""" + if not data: + return DEFAULT_AUDIO_TOKEN_ESTIMATE + fallback_estimate: Final = max(len(data) * 3 // 4 // AUDIO_BYTES_PER_TOKEN, DEFAULT_AUDIO_TOKEN_ESTIMATE) + padding: Final = 2 if data.endswith("==") else 1 if data.endswith("=") else 0 + if len(data) * 3 // 4 - padding > _MAX_AUDIO_ESTIMATE_BYTES: + return fallback_estimate + try: + duration: Final = calculate_request_duration(base64.b64decode(data, validate=True)) + except (ValueError, binascii.Error): + return fallback_estimate + if duration is None or not math.isfinite(duration) or duration <= 0: + return fallback_estimate + fallback_rate: Final = _audio_token_rate(fallback_model) if fallback_model is not None else None + rate: Final = max( + (_audio_token_rate(model) or fallback_rate or AUDIO_TOKENS_PER_SECOND for model in models), + default=fallback_rate or AUDIO_TOKENS_PER_SECOND, + ) + return max(1, math.ceil(duration * rate)) + + DEFAULT_SPEECH_MEDIA_TYPE: Final = "audio/mpeg" diff --git a/litellm/router_utils/batch_utils.py b/litellm/litellm_core_utils/batch_utils.py similarity index 100% rename from litellm/router_utils/batch_utils.py rename to litellm/litellm_core_utils/batch_utils.py diff --git a/litellm/litellm_core_utils/cli_token_utils.py b/litellm/litellm_core_utils/cli_token_utils.py index ffe2c4433a0..37ed4efa0ca 100644 --- a/litellm/litellm_core_utils/cli_token_utils.py +++ b/litellm/litellm_core_utils/cli_token_utils.py @@ -353,9 +353,9 @@ def is_cli_token_fresh( buffer_hours: float = CLI_TOKEN_FRESHNESS_BUFFER_SECONDS / 3600, ) -> bool: """Check whether a cached CLI token is still within its expiration window. - Used by `lite auth print-token` to fail fast, without a network round trip, - once the cached token is past `LITELLM_CLI_JWT_EXPIRATION_HOURS`. A `--pkce` - credential carries its own `expires_at`, which is authoritative when present.""" + Used by `lite auth print-token` to skip asking the proxy while the cached token + is younger than `LITELLM_CLI_JWT_EXPIRATION_HOURS`. A `--pkce` credential + carries its own `expires_at`, which is authoritative when present.""" from litellm.constants import CLI_JWT_EXPIRATION_HOURS expires_at: Final = ( diff --git a/litellm/litellm_core_utils/core_helpers.py b/litellm/litellm_core_utils/core_helpers.py index 00c6ce97e78..55025508e40 100644 --- a/litellm/litellm_core_utils/core_helpers.py +++ b/litellm/litellm_core_utils/core_helpers.py @@ -266,6 +266,7 @@ _FINISH_REASON_MAP: Final[dict[str, OpenAIChatCompletionFinishReason]] = { "tool_use": "tool_calls", "refusal": "content_filter", "compaction": "length", + "model_context_window_exceeded": "length", # Cohere "COMPLETE": "stop", "ERROR_TOXIC": "content_filter", diff --git a/litellm/litellm_core_utils/exception_mapping_utils.py b/litellm/litellm_core_utils/exception_mapping_utils.py index 1c816b22ef1..703550dd2b5 100644 --- a/litellm/litellm_core_utils/exception_mapping_utils.py +++ b/litellm/litellm_core_utils/exception_mapping_utils.py @@ -18,6 +18,7 @@ from litellm.litellm_core_utils.bug_report import ( ) from litellm.litellm_core_utils.core_helpers import as_str_mapping, attribute_or_none from litellm.litellm_core_utils.secret_redaction import redact_string as redact_secret_string +from litellm.llms.bigmodel.common_utils import raise_bigmodel_business_error from litellm.types.utils import LlmProviders from ..exceptions import ( @@ -2036,14 +2037,6 @@ def _map_azure_exception( litellm_debug_info=extra_information, response=getattr(original_exception, "response", None), ) - elif "This model's maximum context length is" in error_str: - raise ContextWindowExceededError( - message=f"AzureException ContextWindowExceededError - {message}", - llm_provider="azure", - model=model, - litellm_debug_info=extra_information, - response=getattr(original_exception, "response", None), - ) elif "DeploymentNotFound" in error_str: raise NotFoundError( message=f"AzureException NotFoundError - {message}", @@ -2085,6 +2078,18 @@ def _map_azure_exception( response=getattr(original_exception, "response", None), body=getattr(original_exception, "body", None), ) + elif getattr(original_exception, "status_code", None) in (None, 400) and ( + azure_error_code == "context_length_exceeded" + or ExceptionCheckers.is_error_str_context_window_exceeded(error_str) + ): + raise ContextWindowExceededError( + message=f"AzureException ContextWindowExceededError - {message}", + llm_provider="azure", + model=model, + litellm_debug_info=extra_information, + response=getattr(original_exception, "response", None), + body=getattr(original_exception, "body", None), + ) elif "invalid_request_error" in error_str and getattr(original_exception, "status_code", None) in (None, 400): raise BadRequestError( message=f"AzureException BadRequestError - {message}", @@ -2758,6 +2763,8 @@ def exception_type( exception_provider=exception_provider, extra_information=extra_information, ) + if custom_llm_provider == "bigmodel": + raise_bigmodel_business_error(model, f"{exception_provider} - {error_str}", original_exception) # pyright: ignore[reportUnknownArgumentType] # exception_type takes untyped parameters if custom_llm_provider == "openrouter": _map_openrouter_exception( model=model, diff --git a/litellm/litellm_core_utils/fallback_generalizations.py b/litellm/litellm_core_utils/fallback_generalizations.py index be432d1fdd4..eb4cf421a19 100644 --- a/litellm/litellm_core_utils/fallback_generalizations.py +++ b/litellm/litellm_core_utils/fallback_generalizations.py @@ -19,17 +19,11 @@ ones on key conflicts, and the caller backfills ``litellm_provider`` with the provider it requested. If no capability rule matches, model-info resolution misses as if no rules existed. -LEGACY-SCHEMA SHIM (temporary, until the new-schema JSON reaches main): released -proxies fetch this JSON remotely from main, whose block still ships the old schema -where a rule mixes ``litellm_provider`` with capability keys and may inherit a -parent's ``model_info`` via ``extends``. Such a legacy rule is tolerated rather -than skipped: ``extends`` is resolved once at install time (single level, against -raw parents), and the resolved rule acts as BOTH kinds, a routing rule (its -``litellm_provider`` participates in first-hit inference) and a capability rule -(its full ``model_info``, provider included, participates in the union). New-schema -rules never mix the two and never use ``extends``. A rule whose -``litellm_provider`` is not a string is invalid and is warned about and skipped -(a warning rather than a crash, for the same remote-fetch reason). +A rule whose ``model_info`` carries ``litellm_provider`` alongside any other key, +or carries it as a non-string, is neither kind: it is warned about and skipped +rather than raising, since released proxies fetch this JSON remotely. A rule +carrying ``extends`` is skipped the same way. Mixed rules and ``extends`` are the +old rule format, so their warning points the operator at a current cost map. Rules are only consulted after exact and case-insensitive lookups miss, so an exact cost-map entry always takes precedence over any rule. @@ -62,37 +56,8 @@ NAME_FIELD: Final = "name" PATTERN_FIELD: Final = "pattern" MODEL_INFO_FIELD: Final = "model_info" PROVIDER_KEY: Final = "litellm_provider" -LEGACY_EXTENDS_FIELD: Final = "extends" FILL_MISSING_FOR_PROVIDERS_FIELD: Final = "fill_missing_for_providers" - - -def _resolve_legacy_extends(rules: list) -> list: - """Expand legacy ``extends`` inheritance so each rule's ``model_info`` is self-contained. - - Compatibility shim for the old remote schema: single level, resolved against each - parent's raw ``model_info``, with the child's own keys winning on conflict. Non-dict - rules and dangling parents pass through unchanged; new-schema rules carry no - ``extends`` and are untouched. - """ - base_by_name: Final = { - rule[NAME_FIELD]: rule[MODEL_INFO_FIELD] - for rule in rules - if isinstance(rule, dict) - and isinstance(rule.get(NAME_FIELD), str) - and isinstance(rule.get(MODEL_INFO_FIELD), dict) - } - - def resolved(rule: object) -> object: - if not isinstance(rule, dict): - return rule - parent_name: Final = rule.get(LEGACY_EXTENDS_FIELD) - own_info: Final = rule.get(MODEL_INFO_FIELD) - parent_info: Final = base_by_name.get(parent_name) if isinstance(parent_name, str) else None - if parent_info is None or not isinstance(own_info, dict): - return rule - return {**rule, MODEL_INFO_FIELD: {**parent_info, **own_info}} - - return [resolved(rule) for rule in rules] +EXTENDS_FIELD: Final = "extends" @dataclass(frozen=True, slots=True) @@ -127,19 +92,33 @@ def _parse_fill_missing_for_providers(rule: Mapping[str, object], pattern_label: return frozenset(raw_fill_missing_for_providers) -def _compile_rule(rule: object) -> tuple[_CompiledRule, ...]: +def _warn_old_format_rule(rule_label: str, reason: str) -> None: + verbose_logger.warning( + "LiteLLM: skipping fallback generalization rule %s, written in the old cost map rule format (%s). " + "Point LITELLM_MODEL_COST_MAP_URL at a current cost map, or with LITELLM_LOCAL_MODEL_COST_MAP set, " + "replace the bundled backup with a current one.", + rule_label, + reason, + ) + + +def _compile_rule(rule: object) -> _CompiledRule | None: if not isinstance(rule, dict): - return () + return None pattern: Final = rule.get(PATTERN_FIELD) model_info: Final = rule.get(MODEL_INFO_FIELD) + rule_label: Final = f"{rule.get(NAME_FIELD, pattern)}" if not isinstance(pattern, str) or not isinstance(model_info, dict): verbose_logger.warning( "LiteLLM: skipping malformed fallback generalization rule %s (needs string '%s' and dict '%s').", - rule.get(NAME_FIELD, pattern), + rule_label, PATTERN_FIELD, MODEL_INFO_FIELD, ) - return () + return None + if EXTENDS_FIELD in rule: + _warn_old_format_rule(rule_label, f"'{EXTENDS_FIELD}' is no longer supported") + return None try: compiled: Final = re.compile(pattern, re.IGNORECASE) except re.error as e: @@ -148,37 +127,28 @@ def _compile_rule(rule: object) -> tuple[_CompiledRule, ...]: pattern, e, ) - return () + return None fill_missing_for_providers: Final = _parse_fill_missing_for_providers(rule, pattern) if fill_missing_for_providers is None: - return () + return None if PROVIDER_KEY not in model_info: - return ( - _CapabilityRule( - pattern=compiled, - model_info=model_info, - fill_missing_for_providers=fill_missing_for_providers, - ), + return _CapabilityRule( + pattern=compiled, + model_info=model_info, + fill_missing_for_providers=fill_missing_for_providers, ) provider: Final = model_info[PROVIDER_KEY] if not isinstance(provider, str): verbose_logger.warning( - "LiteLLM: skipping invalid fallback generalization rule %s: '%s' in '%s' must be a string.", - rule.get(NAME_FIELD, pattern), + "LiteLLM: skipping malformed fallback generalization rule %s ('%s' must be a string).", + rule_label, PROVIDER_KEY, - MODEL_INFO_FIELD, ) - return () - if len(model_info) == 1: - return (_RoutingRule(pattern=compiled, provider=provider),) - return ( - _RoutingRule(pattern=compiled, provider=provider), - _CapabilityRule( - pattern=compiled, - model_info=model_info, - fill_missing_for_providers=fill_missing_for_providers, - ), - ) + return None + if len(model_info) != 1: + _warn_old_format_rule(rule_label, f"'{PROVIDER_KEY}' must be the only key in '{MODEL_INFO_FIELD}'") + return None + return _RoutingRule(pattern=compiled, provider=provider) class _FallbackGeneralizations: @@ -192,7 +162,7 @@ class _FallbackGeneralizations: def set_rules(self, rules: list | None) -> None: installed: Final = rules if isinstance(rules, list) else [] - compiled: Final = tuple(kind for rule in _resolve_legacy_extends(installed) for kind in _compile_rule(rule)) + compiled: Final = tuple(kind for kind in map(_compile_rule, installed) if kind is not None) self.rules = installed self.routing_rules = tuple(rule for rule in compiled if isinstance(rule, _RoutingRule)) self.capability_rules = tuple(rule for rule in compiled if isinstance(rule, _CapabilityRule)) @@ -224,10 +194,7 @@ class _FallbackGeneralizations: ) if not matched: return None - fill_missing: Final[Mapping[str, object]] = { - key: value for model_info in matched for key, value in model_info.items() if key != PROVIDER_KEY - } - return fill_missing or None + return {key: value for model_info in matched for key, value in model_info.items()} or None _registry: Final = _FallbackGeneralizations() @@ -236,10 +203,8 @@ _registry: Final = _FallbackGeneralizations() def set_fallback_generalizations(rules: list | None) -> None: """Install the active rule list, compiling and classifying each rule. - Legacy ``extends`` inheritance is resolved here, once, before classification; - a legacy rule mixing ``litellm_provider`` with capability keys installs as both - kinds. Malformed and invalid-regex rules are warned about and skipped. Called - once when the model cost map is loaded (and again on any reload). + Malformed, mixed-kind, and invalid-regex rules are warned about and skipped. + Called once when the model cost map is loaded (and again on any reload). """ _registry.set_rules(rules) diff --git a/litellm/litellm_core_utils/get_litellm_params.py b/litellm/litellm_core_utils/get_litellm_params.py index ca8e2af18e6..8792fd0f58a 100644 --- a/litellm/litellm_core_utils/get_litellm_params.py +++ b/litellm/litellm_core_utils/get_litellm_params.py @@ -6,7 +6,7 @@ from typing import Final, cast from pydantic import TypeAdapter, ValidationError -from litellm.constants import CONTROL_OPTIONS_KEY +from litellm.constants import CONTROL_OPTIONS_KEY, SESSION_ID_FROM_TRACE_ID_PARAM_KEY from litellm.litellm_core_utils.core_helpers import normalize_drop_params from litellm.llms.openai.data_residency import infer_openai_data_residency from litellm.types.litellm_params import MAX_CONTROL_INT_DIGITS, ControlOptions @@ -75,6 +75,9 @@ OPTIONAL_KWARGS_KEYS: Final = ( "rpm", "itpm", "otpm", + "tpd", + "rpd", + "daily_reset_time", "use_xai_oauth", "chatgpt_auth_file", "github_copilot_auth_type", @@ -212,6 +215,9 @@ def get_litellm_params( # Derive litellm_session_id / litellm_trace_id from metadata when not provided (call chaining) _meta: Final = resolved_metadata or {} + session_id_from_trace_id: Final = ( + litellm_session_id is None and not _meta.get("session_id") and bool(_meta.get("trace_id")) + ) if litellm_session_id is None: litellm_session_id = _meta.get("session_id") or _meta.get("trace_id") if litellm_trace_id is None: @@ -254,6 +260,7 @@ def get_litellm_params( or (get_base_model_from_litellm_call_metadata(metadata=metadata) if metadata else None), "litellm_trace_id": litellm_trace_id, "litellm_session_id": litellm_session_id, + **({SESSION_ID_FROM_TRACE_ID_PARAM_KEY: True} if session_id_from_trace_id else {}), "hf_model_name": hf_model_name, "custom_prompt_dict": custom_prompt_dict, "litellm_metadata": litellm_metadata, diff --git a/litellm/litellm_core_utils/get_llm_provider_logic.py b/litellm/litellm_core_utils/get_llm_provider_logic.py index 19c1d5c414c..f8c8ff71f8e 100644 --- a/litellm/litellm_core_utils/get_llm_provider_logic.py +++ b/litellm/litellm_core_utils/get_llm_provider_logic.py @@ -437,7 +437,6 @@ def get_llm_provider( model in litellm.open_ai_chat_completion_models or "ft:gpt-3.5-turbo" in model or "ft:gpt-4" in model # catches ft:gpt-4-0613, ft:gpt-4o - or model in litellm.openai_image_generation_models or model.startswith("gpt-image") or model in litellm.openai_video_generation_models ): @@ -795,6 +794,13 @@ def _get_openai_compatible_provider_info( api_base, dynamic_api_key, ) = litellm.XAIChatConfig().get_openai_compatible_provider_info(api_base, api_key) + elif custom_llm_provider == "bigmodel": + from litellm.llms.bigmodel.common_utils import get_bigmodel_api_key, get_bigmodel_url + + ( + api_base, # rebind-ok: existing provider-resolution pipeline resolves the API base in place + dynamic_api_key, # rebind-ok: existing provider-resolution pipeline resolves the API key in place + ) = get_bigmodel_url(api_base, "chat"), get_bigmodel_api_key(api_key) elif custom_llm_provider == "zai": ( api_base, diff --git a/litellm/litellm_core_utils/internal_call_metadata.py b/litellm/litellm_core_utils/internal_call_metadata.py index 1200d799018..f3dbd612bee 100644 --- a/litellm/litellm_core_utils/internal_call_metadata.py +++ b/litellm/litellm_core_utils/internal_call_metadata.py @@ -120,7 +120,7 @@ def is_unbilled_non_inference_call( origin: Final = metadata.get(INTERNAL_CALL_ORIGIN_METADATA_KEY) if metadata is not None else None if origin == BACKGROUND_RESPONSE_COST_POLL_CALL_ORIGIN: return False - if not is_background_response(response): + if not is_background_response(_finished_response(response)): return True return origin == BACKGROUND_RESPONSE_STATUS_POLL_CALL_ORIGIN or _is_managed_background_call(metadata) diff --git a/litellm/litellm_core_utils/litellm_logging.py b/litellm/litellm_core_utils/litellm_logging.py index 48e8a44b9a4..7f4b069ded6 100644 --- a/litellm/litellm_core_utils/litellm_logging.py +++ b/litellm/litellm_core_utils/litellm_logging.py @@ -842,6 +842,7 @@ class Logging(LiteLLMLoggingBaseClass): self._async_success_enqueued: bool = False self._sync_success_scheduled: bool = False self.on_detached_stream_failure: Callable[[Exception], Awaitable[None]] | None = None + self._stream_failure_claimed: bool = False self.shadow_eval_request_snapshot: GuardrailRequestSnapshot | None = None def copy_for_new_call(self, litellm_call_id: str, start_time: datetime.datetime) -> "Logging": @@ -1129,9 +1130,6 @@ class Logging(LiteLLMLoggingBaseClass): } self.litellm_request_debug = litellm_params.get("litellm_request_debug", False) self.logger_fn = litellm_params.get("logger_fn", None) - if is_debugging_on() or self.litellm_request_debug: - verbose_logger.debug("self.optional_params: %s", self.optional_params) - self.model_call_details.update( { "model": self.model, @@ -2561,6 +2559,12 @@ class Logging(LiteLLMLoggingBaseClass): }, ) + def claim_stream_failure_report(self) -> bool: + if self._stream_failure_claimed: + return False + self._stream_failure_claimed = True + return True + def record_assembled_response_for_failure(self, assembled: ModelResponse) -> None: """Bill a fully streamed response on the failure log when a post-call hook rejects it.""" usage: Final = getattr(assembled, "usage", None) @@ -2751,7 +2755,7 @@ class Logging(LiteLLMLoggingBaseClass): if entry is None or not is_str_keyed_dict(litellm_params): return metadata: Final[object] = litellm_params.get("metadata") - bucket: Final = metadata if is_str_keyed_dict(metadata) else {} + bucket: Final = {**metadata} if is_str_keyed_dict(metadata) else {} litellm_params["metadata"] = bucket with_guardrail_entry(bucket, entry) @@ -3474,7 +3478,7 @@ class Logging(LiteLLMLoggingBaseClass): start_time=start_time, end_time=end_time, print_verbose=print_verbose, - level=LogfireLevel.INFO.value, + level=LogfireLevel.INFO, ) if callback == "lunary" and lunaryLogger is not None: @@ -4435,7 +4439,7 @@ class Logging(LiteLLMLoggingBaseClass): response_obj=result, start_time=start_time, end_time=end_time, - level=LogfireLevel.ERROR.value, + level=LogfireLevel.ERROR, print_verbose=print_verbose, ) @@ -5048,6 +5052,23 @@ class Logging(LiteLLMLoggingBaseClass): return result_copy +_SENSITIVE_KEYWORDS: Final = ( + "authorization", + "token", + "key", + "secret", + "vertex_credentials", + "credentials", + "password", + "passwd", +) + + +def has_sensitive_keyword(key: str) -> bool: + lowered: Final = key.lower() + return any(keyword in lowered for keyword in _SENSITIVE_KEYWORDS) + + def get_masked_values( sensitive_object: Mapping[str, object], ignore_sensitive_values: bool = False, @@ -5066,16 +5087,6 @@ def get_masked_values( masked_length: Optional length for the masked portion (number of *). If set, will use exactly this many * regardless of original string length. The total length will be unmasked_length + masked_length. """ - sensitive_keywords: Final = ( - "authorization", - "token", - "key", - "secret", - "vertex_credentials", - "credentials", - "password", - "passwd", - ) def _mask_value(v: object) -> object: if isinstance(v, dict): @@ -5102,12 +5113,7 @@ def get_masked_values( return v[: unmasked_length // 2] + "*" * (len(v) - unmasked_length) + v[-unmasked_length // 2 :] return { - k: ( - v - if ignore_sensitive_values - or not any(sensitive_keyword in k.lower() for sensitive_keyword in sensitive_keywords) - else _mask_value(v) - ) + k: (v if ignore_sensitive_values or not has_sensitive_keyword(k) else _mask_value(v)) for k, v in sensitive_object.items() } diff --git a/litellm/litellm_core_utils/llm_cost_calc/usage_object_transformation.py b/litellm/litellm_core_utils/llm_cost_calc/usage_object_transformation.py index a02c40b7611..78a8cb51bac 100644 --- a/litellm/litellm_core_utils/llm_cost_calc/usage_object_transformation.py +++ b/litellm/litellm_core_utils/llm_cost_calc/usage_object_transformation.py @@ -27,13 +27,18 @@ class TranscriptionUsageObjectTransformation: if isinstance(usage_object, TranscriptionUsageDurationObject): return None elif isinstance(usage_object, TranscriptionUsageTokensObject): + input_token_details: Final = usage_object.input_token_details return Usage( prompt_tokens=usage_object.input_tokens, completion_tokens=usage_object.output_tokens, total_tokens=usage_object.total_tokens, - prompt_tokens_details=PromptTokensDetailsWrapper( - text_tokens=usage_object.input_token_details.text_tokens, - audio_tokens=usage_object.input_token_details.audio_tokens, + prompt_tokens_details=( + None + if input_token_details is None + else PromptTokensDetailsWrapper( + text_tokens=input_token_details.text_tokens, + audio_tokens=input_token_details.audio_tokens, + ) ), ) return None diff --git a/litellm/litellm_core_utils/llm_cost_calc/utils.py b/litellm/litellm_core_utils/llm_cost_calc/utils.py index 3b49f239afe..4b0b875af6d 100644 --- a/litellm/litellm_core_utils/llm_cost_calc/utils.py +++ b/litellm/litellm_core_utils/llm_cost_calc/utils.py @@ -6,7 +6,7 @@ from collections.abc import Mapping, Sequence from dataclasses import dataclass, field, replace from datetime import datetime, timezone, tzinfo from types import MappingProxyType -from typing import Final, Literal, TypedDict, cast +from typing import Final, Literal, Protocol, TypedDict, cast from zoneinfo import ZoneInfo, ZoneInfoNotFoundError from typing_extensions import ReadOnly @@ -2085,6 +2085,41 @@ def calculate_image_response_web_search_cost( ) +class _ModelPricedImageCostCalculator(Protocol): + def __call__(self, model: str, image_response: ImageResponse, model_info: ModelInfo | None = None) -> float: ... + + +def _model_priced_image_cost_calculator( + custom_llm_provider: str | None, model: str +) -> _ModelPricedImageCostCalculator | None: + match custom_llm_provider: + case litellm.LlmProviders.RECRAFT.value: + from litellm.llms.recraft.cost_calculator import cost_calculator as recraft_image_cost_calculator + + return recraft_image_cost_calculator + case litellm.LlmProviders.AIML.value: + from litellm.llms.aiml.image_generation.cost_calculator import cost_calculator as aiml_image_cost_calculator + + return aiml_image_cost_calculator + case litellm.LlmProviders.COMETAPI.value: + from litellm.llms.cometapi.image_generation.cost_calculator import ( + cost_calculator as cometapi_image_cost_calculator, + ) + + return cometapi_image_cost_calculator + case litellm.LlmProviders.RUNWAYML.value: + from litellm.llms.runwayml.cost_calculator import cost_calculator as runwayml_image_cost_calculator + + return runwayml_image_cost_calculator + case litellm.LlmProviders.TENCENT.value: + from litellm.llms.tencent.cost_calculator import image_cost_calculator as tencent_image_cost_calculator + from litellm.llms.tencent.image_generation.transformation import is_tokenhub_image_model + + return tencent_image_cost_calculator if is_tokenhub_image_model(model) else None + case _: + return None + + class CostCalculatorUtils: @staticmethod def call_type_has_image_response(call_type: str) -> bool: @@ -2131,9 +2166,6 @@ class CostCalculatorUtils: from litellm.llms.gemini.image_generation.cost_calculator import ( cost_calculator as gemini_image_cost_calculator, ) - from litellm.llms.recraft.cost_calculator import ( - cost_calculator as recraft_image_cost_calculator, - ) from litellm.llms.vertex_ai.image_generation.cost_calculator import ( cost_calculator as vertex_ai_image_cost_calculator, ) @@ -2146,7 +2178,10 @@ class CostCalculatorUtils: ) resolved_n: Final = n if n is not None else (len(completion_response.data) if completion_response.data else 0) pricing: Final = deployment_pricing(model_info) + model_priced_calculator: Final = _model_priced_image_cost_calculator(custom_llm_provider, model) + if model_priced_calculator is not None: + return model_priced_calculator(model=model, image_response=completion_response, model_info=pricing) if custom_llm_provider == litellm.LlmProviders.VERTEX_AI.value: if isinstance(completion_response, ImageResponse): return vertex_ai_image_cost_calculator( @@ -2164,36 +2199,6 @@ class CostCalculatorUtils: optional_params=optional_params, ) raise TypeError("completion_response must be of type ImageResponse for bedrock image cost calculation") - elif custom_llm_provider == litellm.LlmProviders.RECRAFT.value: - from litellm.llms.recraft.cost_calculator import ( - cost_calculator as recraft_image_cost_calculator, - ) - - return recraft_image_cost_calculator( - model=model, - image_response=completion_response, - model_info=pricing, - ) - elif custom_llm_provider == litellm.LlmProviders.AIML.value: - from litellm.llms.aiml.image_generation.cost_calculator import ( - cost_calculator as aiml_image_cost_calculator, - ) - - return aiml_image_cost_calculator( - model=model, - image_response=completion_response, - model_info=pricing, - ) - elif custom_llm_provider == litellm.LlmProviders.COMETAPI.value: - from litellm.llms.cometapi.image_generation.cost_calculator import ( - cost_calculator as cometapi_image_cost_calculator, - ) - - return cometapi_image_cost_calculator( - model=model, - image_response=completion_response, - model_info=pricing, - ) elif custom_llm_provider == litellm.LlmProviders.GEMINI.value: if call_type in ( CallTypes.image_edit.value, @@ -2237,16 +2242,6 @@ class CostCalculatorUtils: optional_params=optional_params, model_info=pricing, ) - elif custom_llm_provider == litellm.LlmProviders.RUNWAYML.value: - from litellm.llms.runwayml.cost_calculator import ( - cost_calculator as runwayml_image_cost_calculator, - ) - - return runwayml_image_cost_calculator( - model=model, - image_response=completion_response, - model_info=pricing, - ) elif ( custom_llm_provider == litellm.LlmProviders.OPENAI.value or custom_llm_provider == litellm.LlmProviders.AZURE.value diff --git a/litellm/litellm_core_utils/llm_request_utils.py b/litellm/litellm_core_utils/llm_request_utils.py index 0bf59a6d1f2..db881aa16c6 100644 --- a/litellm/litellm_core_utils/llm_request_utils.py +++ b/litellm/litellm_core_utils/llm_request_utils.py @@ -1,8 +1,9 @@ -from collections.abc import Mapping +from collections.abc import Iterable, Iterator, Mapping from typing import Final, cast import litellm from litellm.constants import DEFAULT_MAX_RECURSE_DEPTH +from litellm.litellm_core_utils.get_llm_provider_logic import inferred_provider def _form_field_value(value: object) -> str: @@ -153,24 +154,33 @@ def pick_cheapest_chat_models_from_llm_provider(custom_llm_provider: str, n=1): if custom_llm_provider not in litellm.models_by_provider: return [] - known_models: Final = litellm.models_by_provider.get(custom_llm_provider, []) - model_costs: Final = [] + known_models: Final[Iterable[str]] = litellm.models_by_provider.get(custom_llm_provider, ()) + ranked_rows: Final = ( + (route_rank, cost, model) + for model, cost in _chat_row_costs(known_models, custom_llm_provider) + if (route_rank := _route_rank(model, custom_llm_provider)) is not None + ) + return [model for _, _, model in sorted(ranked_rows, key=lambda row: row[:2])[:n]] - for model in known_models: + +def _chat_row_costs(models: Iterable[str], custom_llm_provider: str) -> Iterator[tuple[str, float]]: + for model in models: try: model_info = litellm.get_model_info(model=model, custom_llm_provider=custom_llm_provider) except Exception: continue if model_info.get("mode") != "chat": continue - _cost = (model_info.get("input_cost_per_token") or 0.0) + (model_info.get("output_cost_per_token") or 0.0) - model_costs.append((model, _cost)) + yield model, (model_info.get("input_cost_per_token") or 0.0) + (model_info.get("output_cost_per_token") or 0.0) - # Sort by cost (ascending) - model_costs.sort(key=lambda x: x[1]) - # Return the top n cheapest models - return [model for model, _ in model_costs[:n]] +def _route_rank(model: str, custom_llm_provider: str) -> int | None: + routed_provider: Final = inferred_provider(model) + if routed_provider is None: + return 1 + if routed_provider == inferred_provider(f"{custom_llm_provider}/{model}"): + return 0 + return None def get_proxy_server_request_headers(litellm_params: dict | None) -> dict: diff --git a/litellm/litellm_core_utils/prompt_templates/common_utils.py b/litellm/litellm_core_utils/prompt_templates/common_utils.py index 3c06c522dd6..9bc53791b36 100644 --- a/litellm/litellm_core_utils/prompt_templates/common_utils.py +++ b/litellm/litellm_core_utils/prompt_templates/common_utils.py @@ -9,6 +9,7 @@ import json import mimetypes import re from collections.abc import Callable, Iterable, Iterator, Mapping, Sequence +from dataclasses import dataclass from graphlib import CycleError, TopologicalSorter from itertools import chain, groupby, islice from os import PathLike @@ -16,12 +17,12 @@ from pathlib import Path from types import MappingProxyType from typing import TYPE_CHECKING, Any, Final, Literal, TypeAlias, TypeVar, cast -from pydantic import TypeAdapter +from pydantic import TypeAdapter, ValidationError import litellm from litellm import verbose_logger +from litellm.litellm_core_utils.batch_utils import InMemoryFile from litellm.litellm_core_utils.core_helpers import as_str_mapping -from litellm.router_utils.batch_utils import InMemoryFile from litellm.types.llms.openai import ( AllMessageValues, ChatCompletionAssistantMessage, @@ -236,6 +237,160 @@ _IMAGE_CONTENT_PART_TYPES: Final = frozenset({"image_url", "input_image", "image _IMAGE_SCAN_MAX_DEPTH: Final = 4 +@dataclass(frozen=True, slots=True) +class _TPMMediaProjection: + content: object + media: tuple[Mapping[str, object], ...] = () + + +def _tpm_image_part(url: str, detail: object = "auto") -> Mapping[str, object]: + return {"type": "image_url", "image_url": {"url": url, "detail": detail}} + + +def _tpm_blank_fields(fields: Mapping[str, object], names: tuple[str, ...]) -> Mapping[str, object]: + return {key: "" if key in names and isinstance(value, str) else value for key, value in fields.items()} + + +def _tpm_file_media(part: Mapping[str, object]) -> _TPMMediaProjection: + from litellm.litellm_core_utils.prompt_templates.factory import parse_mime_type + + nested: Final = part.get("type") == "file" + fields: Final = as_str_mapping(part.get("file")) if nested else part + if fields is None: + return _TPMMediaProjection(part) + raw_data: Final = fields.get("file_data") + data: Final = raw_data if isinstance(raw_data, str) else "" + declared: Final = next( + ( + value + for key in ("format", "mime_type", "content_type") + if isinstance(value := fields.get(key), str) and value + ), + "", + ) + mime: Final = (declared or parse_mime_type(data[:256]) or "").split(";", 1)[0].strip().lower() + if not mime.startswith(("image/", "audio/")): + return _TPMMediaProjection(part) + raw_url: Final = fields.get("file_url") or fields.get("file_id") + url: Final = data or (raw_url if isinstance(raw_url, str) else "") + header_end: Final = data.find(",", 0, 256) + encoded: Final = ( + data[header_end + 1 :] + if header_end >= 0 and data[:header_end].endswith(";base64") + else "" + if data.startswith(("data:", "https://", "http://", "gs://")) + else data + ) + media: Final = ( + _tpm_image_part( + url + if not data or url.startswith(("data:", "https://", "http://", "gs://")) + else f"data:{mime};base64,{url}", + fields.get("detail", "auto"), + ) + if mime.startswith("image/") + else {"type": "input_audio", "input_audio": {"data": encoded, "format": mime.removeprefix("audio/")}} + ) + projected: Final = _tpm_blank_fields(fields, ("file_data", "file_url")) + return _TPMMediaProjection({**part, "file": projected} if nested else projected, (media,)) + + +def _tpm_media_leaf(value: object) -> _TPMMediaProjection: + part: Final = as_str_mapping(value) + if part is None: + return _TPMMediaProjection(value) + kind: Final = part.get("type") + if kind in ("file", "input_file"): + return _tpm_file_media(part) + if kind == "input_audio": + audio: Final = as_str_mapping(part.get("input_audio")) + return _TPMMediaProjection( + {**part, "input_audio": _tpm_blank_fields(audio, ("data",))} if audio is not None else value, + ({"type": "input_audio", "input_audio": part.get("input_audio")},), + ) + if kind in ("image_url", "input_image", "image", "computer_screenshot"): + image: Final = as_str_mapping(part.get("image_url")) + source: Final = as_str_mapping(part.get("source")) + canonical: Final = _tpm_image_part( + _image_part_url({**part, "type": "input_image"} if kind == "computer_screenshot" else part) or "", + (image or part).get("detail", part.get("detail", "auto")), + ) + projected: Final = ( + {**part, "image_url": _tpm_blank_fields(image, ("url",))} + if image is not None and kind in ("image_url", "input_image", "computer_screenshot") + else {**part, "source": _tpm_blank_fields(source, ("data", "url"))} + if source is not None and kind == "image" and source.get("type") in ("base64", "url") + else _tpm_blank_fields(part, ("image_url", "url")) + ) + return _TPMMediaProjection(projected, (canonical,)) + return _TPMMediaProjection(value) + + +def _tpm_media_list(value: object, split: Callable[[object], _TPMMediaProjection]) -> _TPMMediaProjection: + if not isinstance(value, (list, tuple)): + return _TPMMediaProjection(value) + parts: Final = cast(Sequence[object], value) # cast-ok: finite JSON content arrays + projected: Final = tuple(map(split, parts)) + media: Final = tuple(chain.from_iterable(part.media for part in projected)) + content: Final = tuple(part.content for part in projected) + return _TPMMediaProjection(parts if not media else content if isinstance(value, tuple) else list(content), media) + + +def _tpm_replace_field(part: Mapping[str, object], key: str, projection: _TPMMediaProjection) -> _TPMMediaProjection: + return _TPMMediaProjection({**part, key: projection.content} if projection.media else part, projection.media) + + +def _tpm_document_media(value: object) -> _TPMMediaProjection: + part: Final = as_str_mapping(value) + source: Final = as_str_mapping(part.get("source")) if part is not None else None + if part is None or part.get("type") != "document" or source is None or source.get("type") != "content": + return _tpm_media_leaf(value) + content: Final = _tpm_media_list(source.get("content"), _tpm_media_leaf) + return _tpm_replace_field(part, "source", _tpm_replace_field(source, "content", content)) + + +def _tpm_tool_result_media(value: object) -> _TPMMediaProjection: + part: Final = as_str_mapping(value) + if part is None or part.get("type") != "tool_result": + return _tpm_document_media(value) + return _tpm_replace_field(part, "content", _tpm_media_list(part.get("content"), _tpm_document_media)) + + +def _tpm_code_output_media(value: object) -> _TPMMediaProjection: + part: Final = as_str_mapping(value) + url: Final = part.get("url") if part is not None else None + if part is None or part.get("type") != "image" or not isinstance(url, str) or not url: + return _TPMMediaProjection(value) + return _TPMMediaProjection(_tpm_blank_fields(part, ("url",)), (_tpm_image_part(url),)) + + +def _tpm_input_media(value: object) -> _TPMMediaProjection: + part: Final = as_str_mapping(value) + if part is None: + return _TPMMediaProjection(value) + kind: Final = part.get("type") + if kind in ("function_call_output", "custom_tool_call_output"): + return _tpm_replace_field(part, "output", _tpm_media_list(part.get("output"), _tpm_tool_result_media)) + if kind == "computer_call_output": + return _tpm_replace_field(part, "output", _tpm_media_leaf(part.get("output"))) + if kind == "code_interpreter_call": + return _tpm_replace_field(part, "outputs", _tpm_media_list(part.get("outputs"), _tpm_code_output_media)) + result: Final = part.get("result") + if kind == "image_generation_call" and isinstance(result, str) and result: + return _TPMMediaProjection( + _tpm_blank_fields(part, ("result",)), + (_tpm_image_part("data:application/octet-stream;base64," + result),), + ) + if kind == "message" or (kind is None and isinstance(part.get("role"), str)): + return _tpm_replace_field(part, "content", _tpm_media_list(part.get("content"), _tpm_tool_result_media)) + return _tpm_tool_result_media(value) + + +def split_media_for_tpm(value: object) -> tuple[object, tuple[Mapping[str, object], ...]]: + projection: Final = _tpm_media_list(value, _tpm_input_media) + return projection.content, projection.media + + def _content_parts_contain_image(parts: Sequence[object]) -> bool: """Depth-bounded frontier walk over nested content lists, iterative because the repo bans recursion; an Anthropic tool_result nests its image parts exactly one level down.""" @@ -1918,6 +2073,19 @@ def with_prompt_cache_breakpoint(target: _MarkedT, marker: object) -> _MarkedT: return cast(_MarkedT, marked) # cast-ok: same block shape as the input plus the marker key +_PROMPT_CACHE_BREAKPOINT: Final = TypeAdapter(PromptCacheBreakpoint) + + +def prompt_cache_breakpoint_for_wire(marker: object, drop_params: bool) -> object: + if marker is None or not drop_params: + return marker + try: + return _PROMPT_CACHE_BREAKPOINT.validate_python(marker) + except ValidationError: + verbose_logger.debug("Dropping malformed prompt_cache_breakpoint %r under drop_params", marker) + return None + + def cache_control_as_prompt_cache_breakpoint(block: _MarkedT) -> _MarkedT: """Anthropic's ``cache_control`` mark rewritten as OpenAI's ``prompt_cache_breakpoint`` on the same block.""" if block.get("cache_control") is None: diff --git a/litellm/litellm_core_utils/provider_affinity.py b/litellm/litellm_core_utils/provider_affinity.py index e022839c5c7..c831e92c09d 100644 --- a/litellm/litellm_core_utils/provider_affinity.py +++ b/litellm/litellm_core_utils/provider_affinity.py @@ -2,7 +2,7 @@ import re from collections.abc import Mapping from typing import Final -from litellm.constants import SESSION_ID_GENERATED_METADATA_KEY +from litellm.constants import SESSION_ID_FROM_TRACE_ID_PARAM_KEY, SESSION_ID_GENERATED_METADATA_KEY _HTTP_HEADER_NAME_PATTERN: Final = re.compile(r"^[!#$%&'*+\-.^_`|~0-9A-Za-z]+$") _FORBIDDEN_AFFINITY_HEADERS: Final = frozenset( @@ -53,36 +53,51 @@ def _get_provider_affinity_header_name(litellm_params: object | None, default_he return validate_provider_affinity_header_name(header) -def get_stable_session_id(litellm_params: object | None) -> str | None: - if litellm_params is None: - return None - - direct_session_id: Final = _get_value(litellm_params, "session_id") - if direct_session_id: - return str(direct_session_id) - - metadata_values: Final[tuple[object, ...]] = tuple( +def _metadata_values(litellm_params: object) -> tuple[object, ...]: + return tuple( value for key in ("metadata", "litellm_metadata") if (value := _get_value(litellm_params, key)) is not None ) + + +def _non_generated_litellm_session_id(litellm_params: object) -> str | None: has_generated_session_id: Final = any( - isinstance(metadata, Mapping) and metadata.get(SESSION_ID_GENERATED_METADATA_KEY) - for metadata in metadata_values + _get_value(metadata, SESSION_ID_GENERATED_METADATA_KEY) for metadata in _metadata_values(litellm_params) ) - litellm_session_id: Final = _get_value(litellm_params, "litellm_session_id") - if litellm_session_id and not has_generated_session_id: - return str(litellm_session_id) + return str(litellm_session_id) if litellm_session_id and not has_generated_session_id else None - for metadata in metadata_values: - if ( - isinstance(metadata, Mapping) - and not metadata.get(SESSION_ID_GENERATED_METADATA_KEY) - and (value := metadata.get("session_id")) + +def _metadata_session_id(litellm_params: object) -> str | None: + for metadata in _metadata_values(litellm_params): + if not _get_value(metadata, SESSION_ID_GENERATED_METADATA_KEY) and ( + value := _get_value(metadata, "session_id") ): return str(value) return None +def get_caller_litellm_session_id(litellm_params: object | None) -> str | None: + if litellm_params is None or _get_value(litellm_params, SESSION_ID_FROM_TRACE_ID_PARAM_KEY): + return None + return _non_generated_litellm_session_id(litellm_params) + + +def get_requested_session_id(litellm_params: object | None) -> str | None: + if litellm_params is None: + return None + direct_session_id: Final = _get_value(litellm_params, "session_id") + return str(direct_session_id) if direct_session_id else _metadata_session_id(litellm_params) + + +def get_stable_session_id(litellm_params: object | None) -> str | None: + if litellm_params is None: + return None + direct_session_id: Final = _get_value(litellm_params, "session_id") + if direct_session_id: + return str(direct_session_id) + return _non_generated_litellm_session_id(litellm_params) or _metadata_session_id(litellm_params) + + def add_provider_affinity_header( headers: Mapping[str, object], litellm_params: object | None, default_header: str | None = None ) -> dict[str, object]: # mutable-ok: downstream handlers add auth and signing headers diff --git a/litellm/litellm_core_utils/safe_json_dumps.py b/litellm/litellm_core_utils/safe_json_dumps.py index 63242a580e7..24c401281ef 100644 --- a/litellm/litellm_core_utils/safe_json_dumps.py +++ b/litellm/litellm_core_utils/safe_json_dumps.py @@ -34,7 +34,7 @@ def safe_json_structure( def _transform(key: str | None, value: str) -> str: return value if value_transform is None else value_transform(key, value) - def _serialize(obj: object, seen: set[int], depth: int, key: str | None = None) -> Any: + def _serialize(obj: object, seen: set[int], depth: int, key: str | None = None) -> object: # Check for maximum depth. if depth > max_depth: return "MaxDepthExceeded" @@ -48,32 +48,32 @@ def safe_json_structure( if id(obj) in seen: return "CircularReference Detected" seen.add(id(obj)) - result: dict | list | tuple | set | str if isinstance(obj, dict): - result = {} - for k, v in obj.items(): - if isinstance(k, (str)): - clean_k = k.replace("\x00", "") if "\x00" in k else k - result[clean_k] = _serialize(v, seen, depth + 1, clean_k) + mapping_result: Final = { + (clean_k := k.replace("\x00", "") if "\x00" in k else k): _serialize(v, seen, depth + 1, clean_k) + for k, v in obj.items() + if isinstance(k, str) + } seen.remove(id(obj)) - return result + return mapping_result elif isinstance(obj, list): - result = [_serialize(item, seen, depth + 1, key) for item in obj] + list_result: Final = [_serialize(item, seen, depth + 1, key) for item in obj] seen.remove(id(obj)) - return result + return list_result elif isinstance(obj, tuple): - result = tuple(_serialize(item, seen, depth + 1, key) for item in obj) + tuple_result: Final = tuple(_serialize(item, seen, depth + 1, key) for item in obj) seen.remove(id(obj)) - return result + return tuple_result elif isinstance(obj, set): - result = sorted([_serialize(item, seen, depth + 1, key) for item in obj]) + sortable_values: Final[list[Any]] = [_serialize(item, seen, depth + 1, key) for item in obj] + set_result: Final = sorted(sortable_values) seen.remove(id(obj)) - return result + return set_result elif isinstance(obj, BaseModel): dumped: Final = obj.model_dump() - result = _serialize(dumped, seen, depth + 1, key) + model_result: Final = _serialize(dumped, seen, depth + 1, key) seen.remove(id(obj)) - return result + return model_result else: # Fall back to string conversion for non-serializable objects. try: diff --git a/litellm/litellm_core_utils/single_flight.py b/litellm/litellm_core_utils/single_flight.py new file mode 100644 index 00000000000..44a84d05925 --- /dev/null +++ b/litellm/litellm_core_utils/single_flight.py @@ -0,0 +1,92 @@ +import threading +from collections.abc import Callable +from concurrent.futures import Future +from dataclasses import dataclass, field +from functools import lru_cache +from typing import Final, Generic, ParamSpec, TypeVar + +_P: Final = ParamSpec("_P") +_R: Final = TypeVar("_R") + + +@dataclass(slots=True) +class SingleFlight(Generic[_R]): + lock: threading.Lock = field(default_factory=threading.Lock) + in_flight: Future[_R] | None = None + flights_started: int = 0 + last_flight_failed: bool = False + + def run(self, fetch: Callable[[], _R], while_busy: _R | None = None) -> _R: + leader: Final[Future[_R]] = Future() + with self.lock: + in_flight: Final = self.in_flight + joined_flight: Final = self.flights_started + retry_if_it_fails: Final = not self.last_flight_failed + if in_flight is None: + self._take_off(leader) + if in_flight is None: + return self._lead(leader, fetch) + if while_busy is not None: + return while_busy + try: + return in_flight.result() + except Exception: + retry: Final = self._claim_retry(joined_flight) if retry_if_it_fails else None + if retry is None: + raise + retry_flight, leads_retry = retry + return self._lead(retry_flight, fetch) if leads_retry else retry_flight.result() + + def _take_off(self, leader: Future[_R]) -> None: + self.in_flight = leader + self.flights_started += 1 + + def _claim_retry(self, failed_flight: int) -> tuple[Future[_R], bool] | None: + leader: Final[Future[_R]] = Future() + with self.lock: + in_flight: Final = self.in_flight + if in_flight is not None: + return in_flight, False + if self.flights_started > failed_flight and self.last_flight_failed: + return None + self._take_off(leader) + return leader, True + + def _lead(self, flight: Future[_R], fetch: Callable[[], _R]) -> _R: + try: + result: Final = fetch() + except BaseException as error: + self._land(failed=True) + flight.set_exception(error) + raise + self._land(failed=False) + flight.set_result(result) + return result + + def _land(self, failed: bool) -> None: + with self.lock: + self.in_flight = None + self.last_flight_failed = failed + + +@dataclass(frozen=True, slots=True) +class SingleFlightCache(Generic[_P, _R]): + cached: Callable[..., _R] + clear: Callable[[], None] + lock: threading.Lock = field(default_factory=threading.Lock) + + def __call__( + self, + *args: _P.args, + **kwargs: _P.kwargs, # kwargs-ok: forwarded verbatim to the cached builder, typed by its own signature + ) -> _R: + with self.lock: + return self.cached(*args, **kwargs) + + def cache_clear(self) -> None: + self.clear() + + +def single_flight_lru_cache(build: Callable[_P, _R]) -> SingleFlightCache[_P, _R]: + cached: Final = lru_cache(maxsize=128)(build) + return SingleFlightCache(cached, cached.cache_clear) diff --git a/litellm/litellm_core_utils/streaming_chunk_builder_utils.py b/litellm/litellm_core_utils/streaming_chunk_builder_utils.py index 8d243e572fa..719f75546b9 100644 --- a/litellm/litellm_core_utils/streaming_chunk_builder_utils.py +++ b/litellm/litellm_core_utils/streaming_chunk_builder_utils.py @@ -18,6 +18,7 @@ from litellm.litellm_core_utils.llm_cost_calc.guardrail_cost import BEDROCK_TRAC from litellm.litellm_core_utils.prompt_templates.common_utils import ( get_content_from_model_response, # pyright: ignore[reportUnknownVariableType] # response param accepts an untyped dict ) +from litellm.litellm_core_utils.token_counter import usage_tokenizer_model from litellm.types.llms.openai import ( AllMessageValues, ChatCompletionAssistantContentValue, @@ -51,7 +52,7 @@ from litellm.types.utils import ( UnreportedUsage, Usage, ) -from litellm.utils import print_verbose, token_counter +from litellm.utils import get_base_model_from_metadata, print_verbose, token_counter if TYPE_CHECKING: from openai.types.completion_usage import CompletionUsage @@ -1552,6 +1553,9 @@ def stream_chunk_builder( return stream_chunk_builder_text_completion(chunks=chunks, messages=messages) model: Final = chunks[0]["model"] + usage_model: Final = usage_tokenizer_model( + model, get_base_model_from_metadata(logging_obj.model_call_details) if logging_obj is not None else None + ) # Initialize the response dictionary response: Final = processor.build_base_response(chunks) @@ -1575,7 +1579,7 @@ def stream_chunk_builder( completion_output = get_content_from_model_response(response) usage = processor.calculate_usage( chunks=chunks, - model=model, + model=usage_model, completion_output=completion_output, messages=messages, reasoning_tokens=0, @@ -1766,7 +1770,7 @@ def stream_chunk_builder( usage = processor.calculate_usage( chunks=chunks, - model=model, + model=usage_model, completion_output=completion_output, messages=messages, reasoning_tokens=reasoning_tokens, diff --git a/litellm/litellm_core_utils/streaming_handler.py b/litellm/litellm_core_utils/streaming_handler.py index b64e146ca08..5542249d2c7 100644 --- a/litellm/litellm_core_utils/streaming_handler.py +++ b/litellm/litellm_core_utils/streaming_handler.py @@ -92,6 +92,18 @@ def _next_sync_or_exhausted(it: Iterator[object]) -> object: return _SYNC_ITER_EXHAUSTED +def _stamp_usage_cost( + usage_chunk: ModelResponse | TextCompletionResponse | ModelResponseStream, + complete_response: ModelResponse | TextCompletionResponse | ModelResponseStream, +) -> None: + bill: Final = (get_hidden_params(complete_response) or {}).get("response_cost") + usage: Final[object] = getattr(usage_chunk, "usage", None) + if usage is None or isinstance(bill, bool) or not isinstance(bill, (int, float)): + return + if bill > 0 or isinstance(getattr(usage, "cost", None), (int, float)): + setattr(usage, "cost", float(bill)) # noqa: B010 # cost is an optional extra on the usage model + + def _stamp_served_service_tier(response: ModelResponseStream, complete_streaming_response: ModelResponse) -> None: served_tier: Final = complete_streaming_response.model_dump().get("service_tier") if isinstance(served_tier, str) and served_tier: @@ -1263,7 +1275,7 @@ class CustomStreamWrapper: ) if _is_delta_empty: - model_response.choices[0].delta = Delta(content=None) # ensure empty delta chunk returned + model_response.choices[0].delta = Delta(content=self._close_open_think_block()) # get any function call arguments model_response.choices[0].finish_reason = map_finish_reason( finish_reason=self.received_finish_reason @@ -1292,21 +1304,26 @@ class CustomStreamWrapper: if self.merge_reasoning_content_in_choices is not True: return delta: Final = model_response.choices[0].delta - reasoning_content: Final = getattr(delta, "reasoning_content", None) + reasoning_content: Final = getattr(delta, "reasoning_content", None) or "" content: Final = delta.content or "" - if reasoning_content: - self._emitted_disqualifying_content = True - closes_thinking: Final = bool(content) and not self.sent_last_thinking_block - opening: Final = "" if self.sent_first_thinking_block else "" - delta.content = opening + reasoning_content + ("" + content if closes_thinking else "") - self.sent_first_thinking_block = True - self.sent_last_thinking_block = self.sent_last_thinking_block or closes_thinking - elif self.sent_first_thinking_block and not self.sent_last_thinking_block and content: - delta.content = "" + content - self.sent_last_thinking_block = True - + ends_thinking: Final = bool(content or delta.tool_calls or delta.function_call) + inside_think_block: Final = self.sent_first_thinking_block and not self.sent_last_thinking_block + opening: Final = "" if reasoning_content and not inside_think_block else "" + closing: Final = "" if ends_thinking and (reasoning_content or inside_think_block) else "" if hasattr(delta, "reasoning_content"): del delta.reasoning_content + if not reasoning_content and not closing: + return + delta.content = opening + reasoning_content + closing + content + self.sent_first_thinking_block = True + self.sent_last_thinking_block = bool(closing) + self._emitted_disqualifying_content = self._emitted_disqualifying_content or bool(reasoning_content) + + def _close_open_think_block(self) -> str | None: + if not self.sent_first_thinking_block or self.sent_last_thinking_block: + return None + self.sent_last_thinking_block = True + return "" def _dispatch_provider_chunk( self, @@ -1557,6 +1574,12 @@ class CustomStreamWrapper: else: # openai / azure chat model if isinstance(chunk, ChatCompletionChunk): self._openai_handler_receives_chat_chunks = True + if any(str(choice.finish_reason) == "abort" for choice in chunk.choices or ()): + raise litellm.InternalServerError( + message="Upstream generation aborted (finish_reason=abort)", + model=chunk.model, + llm_provider=self.custom_llm_provider, + ) if self.custom_llm_provider in [ LlmProviders.AZURE.value, LlmProviders.AZURE_AI.value, @@ -1915,6 +1938,16 @@ class CustomStreamWrapper: model_response: Final = self.model_response_creator( hidden_params=None if self.received_model_id is None else {"received_model_id": self.received_model_id} ) + served_tier: Final = next( + ( + tier + for chunk in reversed(self.chunks) + if isinstance(tier := getattr(chunk, "service_tier", None), str) and tier + ), + None, + ) + if served_tier is not None: + setattr(model_response, "service_tier", served_tier) # noqa: B010 # pydantic extra, not a declared field _finish_reason: Final = self.received_finish_reason or self.intermittent_finish_reason if _finish_reason is not None: model_response.choices[0].finish_reason = _finish_reason @@ -1926,8 +1959,20 @@ class CustomStreamWrapper: model_response.choices[0].finish_reason == "stop" and self.tool_call ): # don't overwrite for other - potential error finish reasons model_response.choices[0].finish_reason = "tool_calls" + close_tag: Final = self._close_open_think_block() + if close_tag is not None: + model_response.choices[0].delta.content = close_tag return model_response + def _final_chunk_for_logging(self, processed_chunk: "ModelResponseStream") -> "ModelResponseStream | None": + if self.received_finish_reason is not None or self.intermittent_finish_reason is not None: + return processed_chunk + if processed_chunk.choices[0].delta.content is None: + return None + return processed_chunk.model_copy( + update={"choices": [processed_chunk.choices[0].model_copy(update={"finish_reason": None})]} + ) + def _record_usage_only_chunk(self, model_response: "ModelResponseStream") -> None: """ Keep provider usage-only chunks (e.g. OpenRouter's post-finish chunk, which carries a @@ -2118,6 +2163,7 @@ class CustomStreamWrapper: getattr(complete_streaming_response, "usage"), ) _stamp_served_service_tier(response, complete_streaming_response) + _stamp_usage_cost(response, complete_streaming_response) try: _cache_copy = complete_streaming_response.model_copy(deep=True) _log_copy = complete_streaming_response.model_copy(deep=True) @@ -2167,10 +2213,9 @@ class CustomStreamWrapper: else: self.sent_last_chunk = True processed_chunk: Final = self.finish_reason_handler() - # The logged response is built from self.chunks; keep a finish_reason the provider sent on its - # last content chunk (stripped there), but never add the synthetic "stop" used when it sent none. - if self.received_finish_reason is not None or self.intermittent_finish_reason is not None: - self.chunks.append(processed_chunk) + final_chunk_for_logging: Final = self._final_chunk_for_logging(processed_chunk) + if final_chunk_for_logging is not None: + self.chunks.append(final_chunk_for_logging) if self.stream_options is None: self._set_final_chunk_usage(processed_chunk) ## LOGGING @@ -2339,6 +2384,7 @@ class CustomStreamWrapper: getattr(complete_streaming_response, "usage"), ) _stamp_served_service_tier(response, complete_streaming_response) + _stamp_usage_cost(response, complete_streaming_response) try: _copy = complete_streaming_response.model_copy(deep=True) except RuntimeError: @@ -2400,10 +2446,9 @@ class CustomStreamWrapper: else: self.sent_last_chunk = True processed_chunk: Final = self.finish_reason_handler() - # The logged response is built from self.chunks; keep a finish_reason the provider sent on its - # last content chunk (stripped there), but never add the synthetic "stop" used when it sent none. - if self.received_finish_reason is not None or self.intermittent_finish_reason is not None: - self.chunks.append(processed_chunk) + final_chunk_for_logging: Final = self._final_chunk_for_logging(processed_chunk) + if final_chunk_for_logging is not None: + self.chunks.append(final_chunk_for_logging) if self.stream_options is None: self._set_final_chunk_usage(processed_chunk) # see sync __next__'s sibling branch: deliberately do NOT restore diff --git a/litellm/litellm_core_utils/token_counter.py b/litellm/litellm_core_utils/token_counter.py index 6d50e4b065e..591d77bdb16 100644 --- a/litellm/litellm_core_utils/token_counter.py +++ b/litellm/litellm_core_utils/token_counter.py @@ -3,15 +3,19 @@ import base64 import io import math +import re import struct +from bisect import bisect_right from collections.abc import Awaitable, Callable, Iterable, Mapping, Sequence from itertools import accumulate +from types import MappingProxyType from typing import TYPE_CHECKING, Final, Literal, cast import anyio import anyio.lowlevel import httpx import tiktoken +from tiktoken.model import MODEL_TO_ENCODING from typing_extensions import ParamSpec, TypeVar import litellm @@ -35,6 +39,7 @@ from litellm.constants import ( TOKEN_COUNTER_MAX_EXACT_CHARS, ) from litellm.litellm_core_utils.asyncify import asyncify +from litellm.litellm_core_utils.core_helpers import as_str_mapping from litellm.litellm_core_utils.prompt_templates.chat_template_tools import ( ChatTemplateToolSection, chat_template_tool_section, @@ -45,6 +50,7 @@ if TYPE_CHECKING: from litellm.litellm_core_utils.tokenizer import Encoding, HuggingFace from litellm.litellm_core_utils.url_utils import safe_get from litellm.llms.custom_httpx.http_handler import get_httpx_client, header_value +from litellm.router_utils.deployment_pricing import deployment_pricing_models from litellm.rust_bridge.tokenizer import get_encoding from litellm.types.llms.anthropic import ( AnthropicContentParamSource, @@ -188,22 +194,23 @@ def resize_image_high_res( # Test the function with the given example def calculate_tiles_needed( - resized_width, - resized_height, - tile_width=MAX_TILE_WIDTH, - tile_height=MAX_TILE_HEIGHT, -): + resized_width: int, + resized_height: int, + tile_width: int = MAX_TILE_WIDTH, + tile_height: int = MAX_TILE_HEIGHT, +) -> int: tiles_across: Final = (resized_width + tile_width - 1) // tile_width tiles_down: Final = (resized_height + tile_height - 1) // tile_height total_tiles: Final = tiles_across * tiles_down return total_tiles -def high_detail_image_token_upper_bound(base_tokens: int = 85) -> int: +def high_detail_image_token_upper_bound(base_tokens: int = 85, tile_tokens: int | None = None) -> int: largest_tile_count: Final = calculate_tiles_needed( MAX_LONG_SIDE_FOR_IMAGE_HIGH_RES, MAX_SHORT_SIDE_FOR_IMAGE_HIGH_RES ) - return base_tokens + (base_tokens * 2) * largest_tile_count + per_tile: Final = base_tokens * 2 if tile_tokens is None else tile_tokens + return base_tokens + per_tile * largest_tile_count def _unpack_ints(fmt: str, buffer: bytes) -> tuple[int, ...]: @@ -381,6 +388,219 @@ def calculate_img_tokens( return total_tokens +_IMAGE_HEADER_BASE64_CHARS: Final = 65_536 +_MAX_IMAGE_PATCHES: Final = 30_000 +_ANTHROPIC_IMAGE_LIMITS: Final = MappingProxyType( + {"claude-standard": (ANTHROPIC_IMAGE_MAX_LONG_EDGE_PX, 1568), "claude-high": (2576, 4784)} +) +_TILE_IMAGE_TOKEN_COSTS: Final = MappingProxyType( + { + "gpt-4o": (85, 170), + "gpt-4.1": (85, 170), + "gpt-4o-mini": (2833, 5667), + "gpt-5": (70, 140), + "gpt-5.1": (70, 140), + "o1": (75, 150), + "o1-pro": (75, 150), + "o3": (75, 150), + } +) +_PATCH_IMAGE_MULTIPLIERS: Final = MappingProxyType( + { + "gpt-6-astra": 1.2, + "gpt-5.6-sol": 1.2, + "gpt-5.6-terra": 1.2, + "gpt-5.6-luna": 1.2, + "gpt-5.5": 1.2, + "gpt-5.4": 1.2, + "gpt-5.4-mini": 1.2, + "gpt-5.4-nano": 1.2, + "gpt-5.2": 1.2, + "gpt-4.1-mini": 1.62, + } +) + + +def _inline_image_dimensions(data: str) -> tuple[int, int] | None: + separator: Final = data.find(",", 0, 256) + if not data.startswith("data:") or separator < 0 or not data[:separator].endswith(";base64"): + return None + encoded_header: Final = data[separator + 1 : separator + 1 + _IMAGE_HEADER_BASE64_CHARS] + try: + header: Final = base64.b64decode(encoded_header, validate=True) + image_type: Final = get_image_type(header) + if image_type not in ("png", "gif", "jpeg", "webp"): + return None + if image_type == "webp" and header[12:16] not in (b"VP8X", b"VP8 ", b"VP8L"): + return None + dimensions: Final = _image_dimensions_from_bytes(header) + except (ValueError, TypeError, struct.error): + return None + width, height = dimensions + return (width, height) if width > 0 and height > 0 else None + + +def _patch_image_limits(model: str, detail: str) -> tuple[int, int | None] | None: + if model in ("gpt-5.2", "gpt-4.1-mini"): + return None if detail == "original" else (2048, 6144) + original_default: Final = model in ("gpt-6-astra", "gpt-5.6-sol", "gpt-5.6-terra", "gpt-5.6-luna", "gpt-5.5") + effective_detail: Final = ("original" if original_default else "high") if detail == "auto" else detail + if effective_detail == "low": + return (2048, 6144) if model in ("gpt-5.4", "gpt-5.4-mini", "gpt-5.4-nano") else (512, None) + if effective_detail == "high": + return (65_535 if model == "gpt-6-astra" else 2048, 2500) + return ( + (65_535, None) if model in ("gpt-6-astra", "gpt-5.6-sol", "gpt-5.6-terra", "gpt-5.6-luna") else (6000, 10_000) + ) + + +def _image_patch_count(width: int, height: int, max_dimension: int, budget: int | None) -> int: + dimension_scale: Final = min(1.0, max_dimension / max(width, height)) + fitted_width: Final = max(1, round(width * dimension_scale)) + fitted_height: Final = max(1, round(height * dimension_scale)) + patches: Final = math.ceil(fitted_width / 32) * math.ceil(fitted_height / 32) + if budget is None or patches <= budget: + return patches + shrink: Final = math.sqrt(32**2 * budget / (fitted_width * fitted_height)) + width_patches: Final = fitted_width * shrink / 32 + height_patches: Final = fitted_height * shrink / 32 + aligned_shrink: Final = shrink * min( + math.floor(width_patches) / width_patches, math.floor(height_patches) / height_patches + ) + resized_width: Final = max(1, math.floor(fitted_width * aligned_shrink)) + resized_height: Final = max(1, math.floor(fitted_height * aligned_shrink)) + return math.ceil(resized_width / 32) * math.ceil(resized_height / 32) + + +def _image_policy_model_name(model: str) -> str | None: + provider, separator, provider_model = model.partition("/") + if not separator: + return model + if provider == "openai": + return provider_model + if provider == "openrouter": + return provider_model.removeprefix("openai/") if provider_model.startswith("openai/") else None + if provider not in ("azure", "azure_ai"): + return None + catalog_entry: Final = as_str_mapping( + cast( # cast-ok: read-only view of the legacy string-keyed registry; as_str_mapping checks the entry + Mapping[str, object], litellm.model_cost + ).get(model) + ) + if catalog_entry is not None and catalog_entry.get("litellm_provider") in ("azure", "azure_ai"): + return provider_model.rsplit("/", 1)[-1] + return provider_model.removeprefix("responses/").removeprefix("o_series/").removeprefix("openai/") + + +def _anthropic_image_family(model: str) -> str | None: + from litellm.utils import get_potential_model_names + + provider, separator, _ = model.partition("/") + if separator and provider not in ( + "anthropic", + "bedrock", + "bedrock_converse", + "bedrock_mantle", + "vertex_ai", + "vertex_ai_beta", + "azure_ai", + "openrouter", + ): + return None + candidates: Final = get_potential_model_names(model, provider if separator else "anthropic") + catalog: Final = cast(Mapping[str, object], litellm.model_cost) # cast-ok: read-only view of the legacy registry + for candidate in dict.fromkeys(candidates.values()): + if not isinstance(candidate, str): + continue + if (entry := as_str_mapping(catalog.get(candidate))) is None or entry.get("supports_vision") is not True: + continue + if ( + version := re.search( + r"(?:^|[./])claude-(?:(?:haiku|sonnet|opus)-)?(\d+)(?:[-.](\d{1,2})(?!\d))?", candidate + ) + ) is None: + continue + major, minor = int(version[1]), int(version[2] or 0) + return "claude-high" if (major, minor) >= (4, 7) else "claude-standard" + return None + + +def _anthropic_image_tokens(dimensions: tuple[int, int] | None, limits: tuple[int, int]) -> int: + max_edge, token_budget = limits + if dimensions is None: + return token_budget + long_edge, short_edge = max(dimensions), min(dimensions) + aspect_ratio: Final = long_edge / short_edge + + def tokens_at_edge(edge: int) -> int: + return math.ceil(edge / 28) * math.ceil(max(round(edge / aspect_ratio), 1) / 28) + + fitted_edge: Final = bisect_right(range(1, min(long_edge, max_edge) + 1), token_budget, key=tokens_at_edge) + return tokens_at_edge(max(fitted_edge, 1)) + + +def _image_model_family(model: str) -> str | None: + provider_model: Final = _image_policy_model_name(model) + if provider_model is None: + return _anthropic_image_family(model) + family: Final = re.sub(r"-\d{4}-\d{2}-\d{2}$", "", provider_model) + canonical: Final = litellm.azure_llms.get(f"azure/{family}", family) if model.startswith("azure/") else family + return ( + canonical + if canonical in _TILE_IMAGE_TOKEN_COSTS or canonical in _PATCH_IMAGE_MULTIPLIERS + else _anthropic_image_family(model) + ) + + +def _image_policy_tokens(family: str | None, dimensions: tuple[int, int] | None, detail: str) -> int: + if family is None: + return DEFAULT_IMAGE_TOKEN_COUNT + anthropic_limits: Final = _ANTHROPIC_IMAGE_LIMITS.get(family) + if anthropic_limits is not None: + return _anthropic_image_tokens(dimensions, anthropic_limits) + tile_costs: Final = _TILE_IMAGE_TOKEN_COSTS.get(family) + multiplier: Final = _PATCH_IMAGE_MULTIPLIERS.get(family) + if tile_costs is not None: + base_tokens, tile_tokens = tile_costs + if detail == "original": + return DEFAULT_IMAGE_TOKEN_COUNT + if detail == "low": + return base_tokens + if dimensions is None: + return high_detail_image_token_upper_bound(base_tokens, tile_tokens) + width, height = dimensions + scale: Final = min(1.0, 2048 / max(width, height), 768 / min(width, height)) + tiles: Final = calculate_tiles_needed(max(1, math.floor(width * scale)), max(1, math.floor(height * scale))) + return base_tokens + tiles * tile_tokens + limits: Final = _patch_image_limits(family, detail) + if limits is None or multiplier is None: + return DEFAULT_IMAGE_TOKEN_COUNT + max_dimension, patch_budget = limits + patches: Final = ( + min(math.ceil(max_dimension / 32) ** 2, patch_budget if patch_budget is not None else _MAX_IMAGE_PATCHES) + if dimensions is None + else _image_patch_count(*dimensions, max_dimension, patch_budget) + ) + return math.ceil(patches * multiplier) + + +def estimate_image_tokens( + model: str | Sequence[str], data: str, detail: str = "auto", *, fallback_model: str | None = None +) -> int: + """Estimate image policies from at most 48 KiB of inline headers, without fetching media.""" + if detail not in ("low", "high", "auto", "original"): + return DEFAULT_IMAGE_TOKEN_COUNT + models: Final = (model,) if isinstance(model, str) else model + fallback_family: Final = _image_model_family(fallback_model) if fallback_model is not None else None + families: Final = tuple( + dict.fromkeys(_image_model_family(candidate) or fallback_family for candidate in models or ("",)) + ) + if all(family is None for family in families): + return DEFAULT_IMAGE_TOKEN_COUNT + dimensions: Final = _inline_image_dimensions(data) + return max(_image_policy_tokens(family, dimensions, detail) for family in families) + + TokenCounterFunction = Callable[[str], int] """ Type for a function that counts tokens in a string. @@ -391,7 +611,7 @@ T_ParamSpec: Final = ParamSpec("T_ParamSpec") T_Retval = TypeVar("T_Retval") _COUNT_OFFLOAD_LIMITER: Final = anyio.lowlevel.RunVar[anyio.CapacityLimiter]("litellm_count_offload_limiter") _ANTHROPIC_TOOL_KEYS_MAPPED_BY_BRIDGE: Final = frozenset( - ("name", "input_schema", "description", "cache_control", "strict", "type", "eager_input_streaming") + ("name", "input_schema", "description", "cache_control", "strict", "type", "eager_input_streaming", "custom") ) @@ -787,17 +1007,144 @@ def openai_tokenizer_encoding(model: str) -> "Encoding": def openai_tokenizer_encoding_name(model: str) -> str: - """The tiktoken encoding name for `model`, without loading the encoding.""" - from litellm.utils import print_verbose + """The tiktoken encoding name for `model`, without loading the encoding. - model_to_use: Final = _fix_model_name(model) + A listed OpenAI or Azure model that tiktoken does not know is either a suffixed variant of a model it does + know (`text-embedding-ada-002-v2`) or a newer release than its table, which gets o200k_base, the encoding every + OpenAI model since gpt-4o uses. Provider and region prefixes (`azure/eu/`, `azure_ai/`) are dropped, a name + listed only under Azure (`gpt-41`, `openai/o1-mini`) counts as listed through its `azure/` cost-map key, and an + unlisted name tiktoken counts with o200k_base (`openai/gpt-5.9`) or named like a gpt-5 or o-series release + (`openai/gpt-6.2`) gets it.""" + model_to_use: Final = _openai_model_name(model) or _fix_model_name(model) if "gpt-4o" in model_to_use: return "o200k_base" try: return tiktoken.encoding_name_for_model(model_to_use) except KeyError: - print_verbose("Warning: model not found. Using cl100k_base encoding.") - return "cl100k_base" + return _suffixed_variant_encoding_name(model_to_use) or "o200k_base" + + +def unresolved_tokenizer_model(model: str) -> str: + """`model`, or `gpt-3.5-turbo` when resolving the OpenAI model `model` names moves it off cl100k_base, the encoding + tiktoken gives the name as written, so a count with the result never drops below that one.""" + as_written: Final = _fix_model_name(model) + as_written_encoding: Final = ( + "o200k_base" if "gpt-4o" in as_written else (_tiktoken_encoding_name(as_written) or "cl100k_base") + ) + moved_off_cl100k: Final = ( + as_written_encoding == "cl100k_base" and openai_tokenizer_encoding_name(model) != "cl100k_base" + ) + return "gpt-3.5-turbo" if moved_off_cl100k else model + + +def usage_tokenizer_model(model: str, base_model: str | None) -> str: + """The model to estimate missing usage with: a deployment's `base_model` when it names an OpenAI model, since a + custom deployment name says nothing about its tokenizer, else `model`.""" + return base_model if base_model is not None and is_openai_model(base_model) else model + + +def is_openai_model(model: str) -> bool: + """Whether `model` names an OpenAI or Azure OpenAI model, listed in the cost map or counted with o200k_base by + tiktoken, with or without its prefixes.""" + return _openai_model_name(model) is not None + + +def deployment_openai_model(deployment: object) -> str | None: + """The OpenAI model a router deployment serves, read from its base model first, since a custom deployment name + (`azure/my-gpt-5`) says nothing about its tokenizer, or None when it serves no OpenAI model.""" + return _as_openai_model(_served_model(deployment)) + + +def served_openai_models(deployments: Iterable[object]) -> tuple[str | None, ...]: + """The distinct OpenAI models `deployments` serve, with None standing for any deployment serving another model.""" + served: Final = dict.fromkeys(_served_model(deployment) for deployment in deployments) + return tuple(dict.fromkeys(_as_openai_model(model) for model in served)) + + +def _served_model(deployment: object) -> str | None: + return next(iter(deployment_pricing_models(deployment)), None) + + +def _as_openai_model(model: str | None) -> str | None: + return model if model is not None and is_openai_model(model) else None + + +def single_encoding_openai_model(served: Sequence[str | None]) -> str | None: + """An OpenAI model to count a request with, when every `served_openai_models` entry is an OpenAI model on the same + encoding, else None.""" + if not served or None in served: + return None + encodings: Final = frozenset(openai_tokenizer_encoding_name(model) for model in served if model is not None) + return served[0] if len(encodings) == 1 else None + + +def _openai_model_name(model: str) -> str | None: + return _listed_openai_model_name(model) or _tiktoken_o200k_model_name(model) or _versioned_openai_model_name(model) + + +_VERSIONED_OPENAI_MODEL: Final = re.compile(r"(?:gpt-(?:[5-9]|[1-9]\d+)|o[1-9]\d*)(?:[.-]|$)") + + +def _versioned_openai_model_name(model: str) -> str | None: + name: Final = model.rsplit("/", 1)[-1] + return name if _VERSIONED_OPENAI_MODEL.match(name) else None + + +def _tiktoken_o200k_model_name(model: str) -> str | None: + name: Final = model.rsplit("/", 1)[-1] + return name if _tiktoken_encoding_name(name) == "o200k_base" else None + + +def _listed_openai_model_name(model: str) -> str | None: + segments: Final = model.split("/") + suffixes: Final = ("/".join(segments[start:]) for start in range(len(segments))) + listed: Final = any( + _is_openai_cost_map_model(suffix) or _is_openai_cost_map_model(f"azure/{suffix}") for suffix in suffixes + ) + return segments[-1] if listed else None + + +def _is_openai_cost_map_model(model: str) -> bool: + return ( + model in litellm.azure_llms + or model in litellm.open_ai_chat_completion_models + or _is_azure_openai_text_model(model) + ) + + +_TEXT_MODEL_MODES: Final = frozenset({"chat", "completion", "responses", "realtime"}) + + +def _is_azure_openai_text_model(model: str) -> bool: + cost_info: Final[Mapping[str, object]] = litellm.model_cost.get(model) or {} + return ( + cost_info.get("litellm_provider") == "azure" + and cost_info.get("mode") in _TEXT_MODEL_MODES + and _is_openai_model_name(model.rsplit("/", 1)[-1]) + ) + + +def _is_openai_model_name(name: str) -> bool: + return ( + name in litellm.open_ai_chat_completion_models + or _tiktoken_encoding_name(name) is not None + or any( + name.startswith(f"{listed}-") or listed.startswith(f"{name}-") + for listed in tuple(litellm.open_ai_chat_completion_models) + ) + ) + + +def _tiktoken_encoding_name(model: str) -> str | None: + try: + return tiktoken.encoding_name_for_model(model) + except KeyError: + return None + + +def _suffixed_variant_encoding_name(model: str) -> str | None: + known: Final = tuple(name for name in MODEL_TO_ENCODING if model.startswith(f"{name}-")) + return MODEL_TO_ENCODING[max(known, key=len)] if known else None def uses_legacy_message_accounting(model: str) -> bool: diff --git a/litellm/llms/aiohttp_openai/chat/transformation.py b/litellm/llms/aiohttp_openai/chat/transformation.py index 74f782b56e7..9253ca389ee 100644 --- a/litellm/llms/aiohttp_openai/chat/transformation.py +++ b/litellm/llms/aiohttp_openai/chat/transformation.py @@ -82,4 +82,6 @@ class AiohttpOpenAIChatConfig(OpenAILikeChatConfig): model_response.model = _json_response.get("model") model_response.object = _json_response.get("object") model_response.system_fingerprint = _json_response.get("system_fingerprint") + if "service_tier" in _json_response: + return model_response.model_copy(update={"service_tier": _json_response.get("service_tier")}) return model_response diff --git a/litellm/llms/anthropic/chat/handler.py b/litellm/llms/anthropic/chat/handler.py index 122f2542bc0..e1436473426 100644 --- a/litellm/llms/anthropic/chat/handler.py +++ b/litellm/llms/anthropic/chat/handler.py @@ -39,6 +39,7 @@ from litellm.llms.custom_httpx.http_handler import ( get_async_httpx_client, get_httpx_client, ) +from litellm.llms.custom_httpx.sse_lines import aiter_sse_lines, iter_sse_lines from litellm.types.llms.anthropic import ( ContentBlockDelta, ContentBlockStart, @@ -234,7 +235,7 @@ async def make_call( raise AnthropicError(status_code=500, message=str(e)) completion_stream: Final = ModelResponseIterator( - streaming_response=response.aiter_lines(), + streaming_response=aiter_sse_lines(response.aiter_text()), sync_stream=False, json_mode=json_mode, speed=speed, @@ -305,7 +306,7 @@ def make_sync_call( ) completion_stream: Final = ModelResponseIterator( - streaming_response=response.iter_lines(), + streaming_response=iter_sse_lines(response.iter_text()), sync_stream=True, json_mode=json_mode, speed=speed, diff --git a/litellm/llms/anthropic/common_utils.py b/litellm/llms/anthropic/common_utils.py index 5c0165d2b95..3b7fcdea0e4 100644 --- a/litellm/llms/anthropic/common_utils.py +++ b/litellm/llms/anthropic/common_utils.py @@ -122,6 +122,54 @@ _DECODED_JSON: Final = TypeAdapter(object) _CLAUDE_CODE_USER_AGENT_PREFIXES: Final = ("claude-cli/", "claude-code/") +def is_claude_tool_target(custom_llm_provider: str | None, model: str) -> bool: + if custom_llm_provider == "anthropic": + return True + model_lower: Final = model.lower() + if custom_llm_provider == "bedrock": + return "claude" in model_lower or ("arn:" in model_lower and ":bedrock:" in model_lower) + if custom_llm_provider == "azure_ai" or custom_llm_provider == "vertex_ai": + return "claude" in model_lower + return False + + +def is_claude_model_target(custom_llm_provider: str | None, model: str) -> bool: + return "claude" in model.lower() and is_claude_tool_target(custom_llm_provider, model) + + +def _hoistable_defer_loading(tool_dict: Mapping[object, object], custom: object) -> bool | None: + if not isinstance(custom, dict) or "defer_loading" in tool_dict: + return None + defer_loading: Final = OBJECT_MAPPING_ADAPTER.validate_python(custom).get("defer_loading") + return defer_loading if isinstance(defer_loading, bool) else None + + +def _tool_without_custom_field(tool: object, hoist_defer_loading: bool, drop_custom: bool) -> object: + if not isinstance(tool, dict): + return tool + + if "custom" not in tool: + return tool + + tool_dict: Final = OBJECT_MAPPING_ADAPTER.validate_python(tool) + + custom: Final = tool_dict["custom"] + without_custom: Final = {key: value for key, value in tool_dict.items() if key != "custom"} + defer_loading: Final = _hoistable_defer_loading(tool_dict, custom) if hoist_defer_loading else None + if defer_loading is None: + return without_custom if drop_custom else tool_dict + + unhoisted: Final = { + key: value for key, value in OBJECT_MAPPING_ADAPTER.validate_python(custom).items() if key != "defer_loading" + } + kept_custom: Final = {"custom": unhoisted} if unhoisted and not drop_custom else {} + return {**without_custom, "defer_loading": defer_loading, **kept_custom} + + +def tools_without_custom_field(tools: Sequence[object], hoist_defer_loading: bool, drop_custom: bool) -> list[object]: + return [_tool_without_custom_field(tool, hoist_defer_loading, drop_custom) for tool in tools] + + def is_anthropic_messages_url(url: str) -> bool: """Check whether a URL addresses Anthropic's Messages API.""" parsed_url: Final = urlparse(url) diff --git a/litellm/llms/anthropic/count_tokens/handler.py b/litellm/llms/anthropic/count_tokens/handler.py index a230294ad3f..f8bf7232d9c 100644 --- a/litellm/llms/anthropic/count_tokens/handler.py +++ b/litellm/llms/anthropic/count_tokens/handler.py @@ -39,6 +39,7 @@ class AnthropicCountTokensHandler(AnthropicCountTokensConfig): tools: list[dict[str, JsonValue]] | None = None, system: JsonValue = None, optional_params: Mapping[str, JsonValue] | None = None, + drop_params: bool = False, ) -> dict[str, JsonValue]: """ Handle a CountTokens request using httpx. @@ -69,6 +70,7 @@ class AnthropicCountTokensHandler(AnthropicCountTokensConfig): tools=tools, system=system, optional_params=optional_params, + drop_params=drop_params, ) verbose_logger.debug("Transformed request: %s", request_body) diff --git a/litellm/llms/anthropic/count_tokens/token_counter.py b/litellm/llms/anthropic/count_tokens/token_counter.py index 0764fb41941..91fc77773d1 100644 --- a/litellm/llms/anthropic/count_tokens/token_counter.py +++ b/litellm/llms/anthropic/count_tokens/token_counter.py @@ -11,6 +11,7 @@ from pydantic import JsonValue import litellm from litellm._logging import verbose_logger from litellm.exceptions import AuthenticationError +from litellm.litellm_core_utils.core_helpers import drops_unsupported_params from litellm.llms.anthropic.count_tokens.handler import AnthropicCountTokensHandler from litellm.llms.anthropic.count_tokens.transformation import ( AnthropicCountFields, @@ -27,6 +28,9 @@ anthropic_count_tokens_handler: Final = AnthropicCountTokensHandler() class AnthropicTokenCounter(BaseTokenCounter): """Token counter implementation for Anthropic provider using the CountTokens API.""" + def __init__(self, client_oauth_token: str | None = None) -> None: + self.client_oauth_token: Final = client_oauth_token + def should_use_token_counting_api( self, custom_llm_provider: str | None = None, @@ -95,12 +99,17 @@ class AnthropicTokenCounter(BaseTokenCounter): api_base: Final = litellm_params.get("api_base") try: - auth_header: Final = await AnthropicModelInfo.aget_auth_header( + configured_auth_header: Final = await AnthropicModelInfo.aget_auth_header( api_key=litellm_params.get("api_key") or litellm.anthropic_key or litellm.api_key, api_base=api_base, litellm_params=litellm_params, allow_workload_identity=True, ) + auth_header: Final = ( + configured_auth_header + if configured_auth_header is not None or self.client_oauth_token is None + else AnthropicModelInfo.get_auth_header(api_key=self.client_oauth_token, api_base=api_base) + ) if auth_header is None: return TokenCountResponse( total_tokens=0, @@ -123,6 +132,7 @@ class AnthropicTokenCounter(BaseTokenCounter): tools=tools, system=system, optional_params=count_options, + drop_params=drops_unsupported_params(litellm_params.get("drop_params")), ) if result is not None: diff --git a/litellm/llms/anthropic/count_tokens/transformation.py b/litellm/llms/anthropic/count_tokens/transformation.py index eb8e595c849..e60ffe67c8d 100644 --- a/litellm/llms/anthropic/count_tokens/transformation.py +++ b/litellm/llms/anthropic/count_tokens/transformation.py @@ -26,7 +26,11 @@ from litellm.litellm_core_utils.prompt_templates.mid_conversation_system import split_leading_system_run, ) from litellm.litellm_core_utils.url_utils import join_api_base -from litellm.llms.anthropic.common_utils import merge_anthropic_beta_headers +from litellm.llms.anthropic.common_utils import ( + is_claude_model_target, + merge_anthropic_beta_headers, + tools_without_custom_field, +) from litellm.llms.anthropic.wif import resolve_anthropic_base from litellm.types.llms.openai import AllMessageValues, ChatCompletionImageObject, ValidUserMessageContentTypes from litellm.types.utils import TokenCountMessagesFormat, TokenCountResponse @@ -161,11 +165,58 @@ def _has_non_chat_user_block(message: Mapping[str, object]) -> bool: return any(isinstance(block, dict) and block.get("type") not in ValidUserMessageContentTypes for block in blocks) +_OPENAI_RESPONSES_BUILT_IN_TOOL_TYPES: Final = frozenset( + ( + "apply_patch", + "code_interpreter", + "computer", + "computer_use_preview", + "file_search", + "image_generation", + "local_shell", + "mcp", + "shell", + "web_search", + "web_search_2025_08_26", + "web_search_preview", + "web_search_preview_2025_03_11", + ) +) + + +_CHAT_INFERENCE_TRANSLATED_TOOL_TYPES: Final = frozenset(("namespace", "tool_search")) + + +def _is_responses_built_in_tool(tool: Mapping[str, object]) -> bool: + tool_type: Final = tool.get("type") + return isinstance(tool_type, str) and tool_type in _OPENAI_RESPONSES_BUILT_IN_TOOL_TYPES + + +def _is_chat_inference_translated_tool(tool: Mapping[str, object]) -> bool: + tool_type: Final = tool.get("type") + return isinstance(tool_type, str) and tool_type in _CHAT_INFERENCE_TRANSLATED_TOOL_TYPES + + +def _needs_tool_translation(tool: Mapping[str, object]) -> bool: + return _is_chat_tool(tool) or _is_chat_inference_translated_tool(tool) or _is_responses_built_in_tool(tool) + + def _gets_placeholder_name(tool: Mapping[str, object]) -> bool: from litellm.llms.anthropic.messages.adapters.transformation import is_provider_native_tool_dict name: Final = tool.get("name") - return not (_is_chat_tool(tool) or is_provider_native_tool_dict(tool) or (isinstance(name, str) and name.strip())) + return not ( + _is_chat_tool(tool) + or _is_chat_inference_translated_tool(tool) + or is_provider_native_tool_dict(tool) + or (isinstance(name, str) and name.strip()) + ) + + +def _chat_tools_for(tool: Mapping[str, object]) -> tuple[Mapping[str, object], ...]: + from litellm.litellm_core_utils.prompt_templates.factory import chat_completion_tools_for + + return (tool,) if _is_chat_inference_translated_tool(tool) else chat_completion_tools_for(tool) def _untranslatable_input( @@ -182,8 +233,8 @@ def _untranslatable_input( unnamed_tool: Final = next(filter(_gets_placeholder_name, tools), None) if unnamed_tool is not None: return ChatCountTranslationError( - message=f"Invalid request for token counting: tool type {unnamed_tool.get('type')!r} " - "has no Chat Completions equivalent" + message=f"Invalid request for token counting: LiteLLM cannot count a tool of type " + f"{unnamed_tool.get('type')!r} for this model" ) return None @@ -223,9 +274,7 @@ def _translated_chat_request( chat_params: Mapping[str, object], translator: _ChatRequestTranslator, ) -> _ChatParams: - from litellm.litellm_core_utils.prompt_templates.factory import chat_completion_tools_for - - chat_tools: Final = [dict(chat_tool) for chat_tool in chain.from_iterable(map(chat_completion_tools_for, tools))] + chat_tools: Final = [dict(chat_tool) for chat_tool in chain.from_iterable(map(_chat_tools_for, tools))] openai_params: Final = {name: value for name, value in chat_params.items() if name != "drop_params"} mapped_params: Final = {**openai_params, **({"tools": chat_tools} if chat_tools else {})} chat_messages: Final = cast( # cast-ok: chat-shaped request messages, read the way chat inference reads them @@ -255,7 +304,7 @@ def anthropic_fields_for_chat_tool_use( counted_tools: Final = tools or () if ( not chat_params - and not any(map(_is_chat_tool, counted_tools)) + and not any(map(_needs_tool_translation, counted_tools)) and not any(map(_needs_chat_translation, messages)) ): return None @@ -327,6 +376,7 @@ class AnthropicCountTokensConfig: tools: list[dict[str, JsonValue]] | None = None, system: JsonValue = None, optional_params: Mapping[str, JsonValue] | None = None, + drop_params: bool = False, ) -> dict[str, JsonValue]: # mutable-ok: provider transport requires JSON dictionaries """ Transform request to Anthropic CountTokens format. @@ -346,7 +396,19 @@ class AnthropicCountTokensConfig: **MappingProxyType( { key: value - for key, value in (("system", counted_system), ("tools", tools)) + for key, value in ( + ("system", counted_system), + ( + "tools", + None + if tools is None + else tools_without_custom_field( + tools, + hoist_defer_loading=is_claude_model_target("anthropic", model), + drop_custom=drop_params, + ), + ), + ) if value is not None } ), diff --git a/litellm/llms/anthropic/messages/adapters/transformation.py b/litellm/llms/anthropic/messages/adapters/transformation.py index 1ed552d46e3..5fc7a56600c 100644 --- a/litellm/llms/anthropic/messages/adapters/transformation.py +++ b/litellm/llms/anthropic/messages/adapters/transformation.py @@ -817,6 +817,7 @@ class LiteLLMAnthropicMessagesAdapter: "name", "input_schema", "description", + "custom", "cache_control", "strict", "type", diff --git a/litellm/llms/anthropic/messages/caller_model_checks.py b/litellm/llms/anthropic/messages/caller_model_checks.py index 7eb6a8f9266..3822f075ccf 100644 --- a/litellm/llms/anthropic/messages/caller_model_checks.py +++ b/litellm/llms/anthropic/messages/caller_model_checks.py @@ -268,6 +268,7 @@ async def caller_within_model_budget( user_id=user_id, user_model_max_budget=user_model_max_budget, model=model, + team_id=user_api_key_auth.team_id, ) except litellm.BudgetExceededError: return "denied" @@ -309,6 +310,7 @@ async def caller_within_model_budget( end_user_id=end_user_id, end_user_model_max_budget=end_user_model_max_budget, model=model, + team_id=user_api_key_auth.team_id, ) except litellm.BudgetExceededError: return "denied" diff --git a/litellm/llms/anthropic/messages/context_management/editors/clear_tool_uses.py b/litellm/llms/anthropic/messages/context_management/editors/clear_tool_uses.py index d4430ca5ab9..c4f7966f429 100644 --- a/litellm/llms/anthropic/messages/context_management/editors/clear_tool_uses.py +++ b/litellm/llms/anthropic/messages/context_management/editors/clear_tool_uses.py @@ -31,6 +31,7 @@ from ..constants import ( ) from ..errors import AnthropicContextManagementError from ..placeholders import build_cleared_tool_result_content +from .compact import count_system_tokens, history_after_client_compaction if TYPE_CHECKING: from litellm.types.llms.openai import ChatCompletionToolParam @@ -203,9 +204,10 @@ def _trigger_met( model: str, messages: list[dict[str, object]], tools: list[dict[str, object]] | None, + system: str | Sequence[Mapping[str, object]] | None, counted_tool_uses: int, ) -> tuple[bool, int | None]: - """Return (trigger_met, input_tokens if counted for reuse).""" + """Return (trigger_met, message and tool tokens for reuse); like the API, input_tokens adds the system prompt.""" trigger_type: Final = trigger.get("type", "input_tokens") threshold = trigger.get("value") @@ -216,14 +218,17 @@ def _trigger_met( if not isinstance(threshold, int): threshold = DEFAULT_INPUT_TOKENS_TRIGGER - current_tokens: Final = litellm.token_counter( + message_tokens: Final = litellm.token_counter( model=model, messages=messages, tools=cast("list[ChatCompletionToolParam] | None", tools), ) + if message_tokens > threshold: + return True, message_tokens + current_tokens: Final = message_tokens + count_system_tokens(model, system) verbose_logger.debug("context_management polyfill: current_tokens: %s", current_tokens) verbose_logger.debug("context_management polyfill: threshold: %s", threshold) - return current_tokens > threshold, current_tokens + return current_tokens > threshold, message_tokens def _resolve_keep_count(keep: dict[str, object]) -> int: @@ -237,7 +242,7 @@ def _resolve_keep_count(keep: dict[str, object]) -> int: def _last_completed_tool_use_id( - messages: list[dict[str, object]], + messages: Sequence[Mapping[str, object]], ) -> str | None: """Latest completed tool_result id; never cleared.""" last_id: str | None = None @@ -253,7 +258,7 @@ def _last_completed_tool_use_id( def _clear_tool_results( - messages: list[dict[str, object]], ids_to_clear: set[str] + messages: list[dict[str, object]], ids_to_clear: Set[str] ) -> tuple[list[dict[str, object]], int]: """Clear matching tool_result content; return (messages, cleared_count).""" cleared = 0 @@ -311,7 +316,11 @@ def apply_clear_tool_uses_20250919( system: str | list[dict[str, object]] | None, edit_spec: ClearToolUsesEditSpec, ) -> tuple[list[dict[str, object]], AppliedEdit | None]: - """Apply clear_tool_uses to an edit ``check_clear_tool_uses_spec`` returned; return (messages, AppliedEdit or None).""" + """Apply clear_tool_uses to an edit ``check_clear_tool_uses_spec`` returned; return (messages, AppliedEdit or None). + + Like the API, it reads only the history after a client compaction block and counts the block's summary as system. + """ + kept, counted_system = history_after_client_compaction(messages, system) fields: Final = _ClearToolUsesFields.model_validate(edit_spec) clear_at_least: Final = 0 if fields.clear_at_least is None else fields.clear_at_least.value exclude_tools: Final = frozenset(fields.exclude_tools or ()) @@ -326,7 +335,7 @@ def apply_clear_tool_uses_20250919( "value": DEFAULT_KEEP_TOOL_USES, } - blocks: Final = _all_blocks(messages) + blocks: Final = _all_blocks(kept) results: Final = _blocks_by_id(blocks, "tool_result", "tool_use_id") uses: Final = _blocks_by_id(blocks, "tool_use", "id") tiny: Final = _tiny_result_ids(results) @@ -335,15 +344,15 @@ def apply_clear_tool_uses_20250919( for tool_use_id, name in _tool_uses_in_order(blocks) if name not in exclude_tools and (tool_use_id not in tiny or _clears_input(name, input_tools)) ) - met, counted_tokens = _trigger_met(trigger, model, messages, tools, len(clearable)) - if not met: - return messages, None - keep_count: Final = _resolve_keep_count(keep) if len(clearable) <= keep_count: return messages, None - last_completed_id: Final = _last_completed_tool_use_id(messages) + met, counted_tokens = _trigger_met(trigger, model, kept, tools, counted_system, len(clearable)) + if not met: + return messages, None + + last_completed_id: Final = _last_completed_tool_use_id(kept) candidates: Final = tuple( (tool_use_id, name) for tool_use_id, name in clearable[: len(clearable) - keep_count] @@ -358,7 +367,7 @@ def apply_clear_tool_uses_20250919( _select_in_batches(candidate_ids, tokens, clear_at_least) if clear_at_least > 0 else candidate_ids ) - edited, cleared_count = _clear_tool_results(messages, set(ids_to_clear)) + edited, cleared_count = _clear_tool_results(messages, ids_to_clear) verbose_logger.debug("context_management polyfill: edited: %s", edited) if cleared_count == 0: return messages, None @@ -370,11 +379,12 @@ def apply_clear_tool_uses_20250919( counted_tokens if counted_tokens is not None else litellm.token_counter( - model=model, messages=messages, tools=cast("list[ChatCompletionToolParam] | None", tools) + model=model, messages=kept, tools=cast("list[ChatCompletionToolParam] | None", tools) ) ) + kept_after, _ = history_after_client_compaction(final_messages, system) tokens_after: Final = litellm.token_counter( - model=model, messages=final_messages, tools=cast("list[ChatCompletionToolParam] | None", tools) + model=model, messages=kept_after, tools=cast("list[ChatCompletionToolParam] | None", tools) ) cleared_input_tokens: Final = max(tokens_before - tokens_after, 0) diff --git a/litellm/llms/anthropic/messages/context_management/editors/compact.py b/litellm/llms/anthropic/messages/context_management/editors/compact.py index 254d1c4c058..0bf8cac7344 100644 --- a/litellm/llms/anthropic/messages/context_management/editors/compact.py +++ b/litellm/llms/anthropic/messages/context_management/editors/compact.py @@ -189,6 +189,21 @@ def _strip_compaction_blocks( return cleaned +def history_after_client_compaction( + messages: Sequence[dict[str, object]], + system: str | Sequence[Mapping[str, object]] | None, +) -> tuple[list[dict[str, object]], str | Sequence[Mapping[str, object]] | None]: + """Return the history the API keeps after the latest compaction block, without it, and the system with its summary.""" + sliced, block = _slice_around_compaction_block(messages) + if block is None: + return list(messages), system + tail: Final = _strip_compaction_blocks(sliced) + summary: Final = block.get("content") + if not isinstance(summary, str) or not summary: + return tail, system + return tail, _augment_system_with_summary(_system_to_text(system) or None, summary) + + def _augment_system_with_summary( system: str | list[dict[str, object]] | None, summary_text: str, @@ -320,14 +335,16 @@ def _count_effective_tokens( content: Final = compaction_block.get("content") or "" if content: total += litellm.token_counter(model=model, text=content) + return total + count_system_tokens(model, system) + + +def count_system_tokens(model: str, system: str | Sequence[Mapping[str, object]] | None) -> int: system_text: Final = _system_to_text(system) - if system_text: - total += litellm.token_counter(model=model, text=system_text) - return total + return litellm.token_counter(model=model, text=system_text) if system_text else 0 def _system_to_text( - system: str | list[dict[str, object]] | None, + system: str | Sequence[Mapping[str, object]] | None, ) -> str: """Flatten an Anthropic-style ``system`` value into a single string for token counting. Returns ``""`` when ``system`` carries no text.""" @@ -338,7 +355,7 @@ def _system_to_text( return "\n".join( text for block in system - if isinstance(block, dict) + if isinstance(block, Mapping) and block.get("type") == "text" and isinstance(text := block.get("text"), str) and text diff --git a/litellm/llms/anthropic/messages/native/transformation.py b/litellm/llms/anthropic/messages/native/transformation.py index 3a8cb8b5b4c..f1b97f3ebeb 100644 --- a/litellm/llms/anthropic/messages/native/transformation.py +++ b/litellm/llms/anthropic/messages/native/transformation.py @@ -39,13 +39,16 @@ from litellm.types.llms.anthropic_tool_search import get_tool_search_beta_header from litellm.types.router import GenericLiteLLMParams from ...common_utils import ( + OBJECT_LIST_ADAPTER, AnthropicError, AnthropicModelInfo, + is_claude_model_target, merge_anthropic_beta_headers, optionally_handle_anthropic_oauth, requires_native_compaction_beta, strip_advisor_blocks_from_messages, strip_encrypted_reasoning_blocks_from_anthropic_messages, + tools_without_custom_field, ) from .mid_conversation_system import ( as_system_content_blocks, @@ -196,6 +199,16 @@ class AnthropicMessagesConfig(BaseAnthropicMessagesConfig): """ return False + def hoists_wrapped_defer_loading(self, model: str) -> bool: + return is_claude_model_target(self._resolved_provider, model) + + def tools_for_upstream(self, tools: Sequence[object], model: str, drop_params: object) -> Sequence[object]: + return tools_without_custom_field( + tools, + hoist_defer_loading=self.hoists_wrapped_defer_loading(model), + drop_custom=drops_unsupported_params(drop_params), + ) + @staticmethod def _filter_billing_headers_from_system(system_param): """ @@ -740,7 +753,8 @@ class AnthropicMessagesConfig(BaseAnthropicMessagesConfig): # Auto-strip advisor blocks from history if advisor tool is absent. # Prevents Anthropic 400: advisor_tool_result in history requires advisor tool. - _tools: Final = anthropic_messages_optional_request_params.get("tools") or [] + tools: Final = anthropic_messages_optional_request_params.get("tools") + _tools: Final = tools or [] _has_advisor: Final = any(isinstance(t, dict) and t.get("type") == ANTHROPIC_ADVISOR_TOOL_TYPE for t in _tools) if not _has_advisor: messages = strip_advisor_blocks_from_messages(messages) @@ -767,9 +781,19 @@ class AnthropicMessagesConfig(BaseAnthropicMessagesConfig): model=model, **anthropic_messages_optional_request_params, ) - if gated.thinking_stripped: - return {**dict(anthropic_messages_request), "thinking": gated.thinking} - return dict(anthropic_messages_request) # pyright: ignore[reportUnknownVariableType] # built from the base signature's bare dict + request: Final = ( + {**dict(anthropic_messages_request), "thinking": gated.thinking} + if gated.thinking_stripped + else dict(anthropic_messages_request) # pyright: ignore[reportUnknownVariableType] # built from the base signature's bare dict + ) + if not isinstance(tools, list): + return request + return { + **request, + "tools": self.tools_for_upstream( + OBJECT_LIST_ADAPTER.validate_python(tools), model, litellm_params.drop_params + ), + } def transform_anthropic_messages_response( self, diff --git a/litellm/llms/anthropic/messages/responses_adapters/handler.py b/litellm/llms/anthropic/messages/responses_adapters/handler.py index 99a07a1e9bf..9b22170c9db 100644 --- a/litellm/llms/anthropic/messages/responses_adapters/handler.py +++ b/litellm/llms/anthropic/messages/responses_adapters/handler.py @@ -15,7 +15,11 @@ from litellm.integrations.anthropic_cache_control_hook import ( supports_openai_prompt_cache_breakpoint, ) from litellm.litellm_core_utils.core_helpers import drops_unsupported_params -from litellm.litellm_core_utils.prompt_templates.common_utils import cache_control_as_prompt_cache_breakpoint +from litellm.litellm_core_utils.prompt_templates.common_utils import ( + cache_control_as_prompt_cache_breakpoint, + prompt_cache_breakpoint_for_wire, + with_prompt_cache_breakpoint, +) from litellm.responses.utils import auto_reasoning_summary from litellm.types.integrations.custom_logger import CONVERTED_STREAM_KEYS from litellm.types.llms.anthropic import ( @@ -90,14 +94,28 @@ def _without_prompt_cache_breakpoint(block: Mapping[str, object]) -> Mapping[str return {key: value for key, value in block.items() if key != "prompt_cache_breakpoint"} +def _cache_control_as_wire_safe_prompt_cache_breakpoint(block: Mapping[str, object]) -> Mapping[str, object]: + if "prompt_cache_breakpoint" not in block: + return cache_control_as_prompt_cache_breakpoint(block) + wire_marker: Final = prompt_cache_breakpoint_for_wire(block["prompt_cache_breakpoint"], drop_params=True) + return cache_control_as_prompt_cache_breakpoint( + with_prompt_cache_breakpoint(_without_prompt_cache_breakpoint(block), wire_marker) + ) + + def _prompt_cache_block_rewrite(model: str, forwarded_kwargs: Mapping[str, object]) -> BlockRewrite | None: """Client cache marks become breakpoints for a deployment that reads them, and a model that takes no breakpoints drops raw ones under drop_params.""" + drops_params: Final = drops_unsupported_params(forwarded_kwargs.get("drop_params")) if _reads_prompt_cache_breakpoint(model, forwarded_kwargs): - return cache_control_as_prompt_cache_breakpoint + return ( + _cache_control_as_wire_safe_prompt_cache_breakpoint + if drops_params + else cache_control_as_prompt_cache_breakpoint + ) if _model_takes_prompt_cache_breakpoint(model, forwarded_kwargs): return None - if drops_unsupported_params(forwarded_kwargs.get("drop_params")): + if drops_params: return _without_prompt_cache_breakpoint return None diff --git a/litellm/llms/anthropic/messages/responses_adapters/streaming_iterator.py b/litellm/llms/anthropic/messages/responses_adapters/streaming_iterator.py index 614a7c96848..44f233f2254 100644 --- a/litellm/llms/anthropic/messages/responses_adapters/streaming_iterator.py +++ b/litellm/llms/anthropic/messages/responses_adapters/streaming_iterator.py @@ -2,15 +2,16 @@ ## Translates OpenAI call to Anthropic `/v1/messages` format import asyncio from collections import deque -from collections.abc import AsyncGenerator, Iterator, Mapping +from collections.abc import AsyncGenerator, Awaitable, Callable, Iterator, Mapping from typing import TYPE_CHECKING, Any, Final +import anyio from pydantic import ConfigDict, field_validator from litellm import verbose_logger from litellm._logging import redact_internal_details_from_client_message from litellm._uuid import uuid -from litellm.exceptions import MidStreamFallbackError +from litellm.exceptions import APIError, MidStreamFallbackError from litellm.litellm_core_utils.prompt_templates.common_utils import ( encrypted_reasoning_signature, ) @@ -22,6 +23,7 @@ from litellm.llms.anthropic.messages.native.utils import ( from litellm.llms.anthropic.messages.safeguards import StreamedSafeguardResults from litellm.llms.anthropic.messages.utils import anthropic_sse_frame from litellm.responses.streaming_iterator import ( + map_stream_error_to_exception, partial_responses_incomplete_event_on_disconnect, stream_error_status_and_message, ) @@ -130,10 +132,12 @@ class AnthropicResponsesStreamWrapper: ) -> None: self.responses_stream = responses_stream self.model = model + self.litellm_logging_obj = litellm_logging_obj self.safeguards_evaluator: Final = safeguards_evaluator self._message_id: str = f"msg_{uuid.uuid4()}" if litellm_logging_obj is not None: litellm_logging_obj.record_streamed_anthropic_message_id(self._message_id) + self._unreported_failure: Exception | None = None self._current_block_index: int = -1 # Map item_id -> content_block_index so we can stop the right block later self._item_id_to_block_index: dict[str, int] = {} @@ -377,16 +381,24 @@ class AnthropicResponsesStreamWrapper: if event_type == "response.failed": failed: Final = _FailedResponseEvent.model_validate(event) - status_code, message = stream_error_status_and_message( - failed.response.error if failed.response is not None else None - ) + upstream_error: Final = failed.response.error if failed.response is not None else None + status_code, message = stream_error_status_and_message(upstream_error) verbose_logger.error( "AnthropicResponsesStreamWrapper: upstream Responses stream for %s failed (%s): %s", self.model, status_code, message, ) - self._fail_stream(status_code, message) + self._fail_stream( + status_code, + message, + failure=map_stream_error_to_exception( + upstream_error, + self.model, + getattr(self.responses_stream, "custom_llm_provider", None) or "", + logging_obj=self.litellm_logging_obj, + ), + ) return # ---- response completed -> message_delta + message_stop ---- @@ -439,10 +451,36 @@ class AnthropicResponsesStreamWrapper: self._sent_message_stop = True return - def _fail_stream(self, status_code: int, message: str) -> None: + def _fail_stream(self, status_code: int, message: str, failure: Exception | None = None) -> None: self._stream_failed = True + self._unreported_failure = failure or APIError( + status_code=status_code, + message=message, + llm_provider=getattr(self.responses_stream, "custom_llm_provider", None), + model=self.model, + ) self._chunk_queue.append(_anthropic_error_chunk(status_code, message)) + async def _report_unreported_failure(self) -> None: + failure: Final = self._unreported_failure + if failure is None: + return + self._unreported_failure = None + on_failure: Final[Callable[[Exception], Awaitable[None]] | None] = getattr( + self.litellm_logging_obj, "_on_detached_stream_failure", None + ) + if on_failure is None: + return + try: + with anyio.CancelScope(shield=True): + await on_failure(failure) + except Exception as hook_failure: # noqa: BLE001 # a failing proxy hook must not hide the error event from the client + verbose_logger.warning( + "AnthropicResponsesStreamWrapper: stream failure hook raised: %s(%s)", + type(hook_failure).__name__, + hook_failure, + ) + def __aiter__(self) -> "AnthropicResponsesStreamWrapper": return self @@ -450,6 +488,7 @@ class AnthropicResponsesStreamWrapper: if self._chunk_queue: return self._chunk_queue.popleft() if self._stream_failed: + await self._report_unreported_failure() raise StopAsyncIteration if not self._sent_message_start: @@ -478,7 +517,7 @@ class AnthropicResponsesStreamWrapper: verbose_logger.exception( "AnthropicResponsesStreamWrapper: upstream Responses stream for %s failed", self.model ) - self._fail_stream(*_failure_status_and_message(e)) + self._fail_stream(*_failure_status_and_message(e), failure=_original_failure(e)) if not self._chunk_queue and not self._sent_message_stop and not self._stream_failed: verbose_logger.error( @@ -498,8 +537,14 @@ class AnthropicResponsesStreamWrapper: async def _sse_frames(self) -> AsyncGenerator[bytes, None]: safeguard_results: Final = StreamedSafeguardResults(self.safeguards_evaluator) - async for chunk in self: - yield anthropic_sse_frame(await safeguard_results.observe(chunk)) + try: + async for chunk in self: + yield anthropic_sse_frame(await safeguard_results.observe(chunk)) + finally: + from litellm.llms.anthropic.messages.native.streaming_iterator import closing_superseded_attempt + + if not closing_superseded_attempt(): + await self._report_unreported_failure() def partial_response_on_disconnect(self) -> "ResponseIncompleteEvent | None": return partial_responses_incomplete_event_on_disconnect(self.responses_stream) diff --git a/litellm/llms/anthropic/messages/stream_assembly.py b/litellm/llms/anthropic/messages/stream_assembly.py index 90bdad8f4bc..c103eb0f975 100644 --- a/litellm/llms/anthropic/messages/stream_assembly.py +++ b/litellm/llms/anthropic/messages/stream_assembly.py @@ -13,6 +13,7 @@ from litellm.llms.anthropic.chat.handler import ( ) from litellm.llms.anthropic.chat.transformation import AnthropicConfig from litellm.llms.anthropic.messages.native.utils import MESSAGE_DELTA_OPTIONAL_KEYS +from litellm.llms.custom_httpx.sse_lines import split_sse_lines from litellm.types.utils import ( Choices, Message, @@ -269,7 +270,7 @@ def build_complete_streaming_response_legacy( def extract_sse_data(event_str: str) -> dict | None: """Parse the JSON object from the ``data:`` line of an Anthropic SSE event.""" - for line in event_str.splitlines(): + for line in split_sse_lines(event_str): stripped = line.strip() if stripped.startswith("data:"): payload = stripped[len("data:") :].strip() diff --git a/litellm/llms/anthropic/prompt_cache_prediction.py b/litellm/llms/anthropic/prompt_cache_prediction.py index d3a4279f3bc..27e003ce8b6 100644 --- a/litellm/llms/anthropic/prompt_cache_prediction.py +++ b/litellm/llms/anthropic/prompt_cache_prediction.py @@ -29,7 +29,7 @@ from litellm.llms.anthropic.messages.native.transformation import ( AnthropicMessagesConfig, ) from litellm.llms.anthropic.messages.native.utils import AnthropicMessagesRequestUtils, prepare_native_messages -from litellm.router_utils.baseline_request import ( +from litellm.router_strategy.auto_router.baseline_request import ( BASELINE_PARAMETERS, capture_baseline_parameters, ) diff --git a/litellm/llms/azure/azure.py b/litellm/llms/azure/azure.py index 02f1ba3472a..a1ba8de6d7f 100644 --- a/litellm/llms/azure/azure.py +++ b/litellm/llms/azure/azure.py @@ -13,13 +13,12 @@ from openai import ( BadRequestError, OpenAI, ) -from pydantic import BaseModel, TypeAdapter +from pydantic import BaseModel import litellm -from litellm.constants import AZURE_OPERATION_POLLING_TIMEOUT, DEFAULT_MAX_RETRIES +from litellm.constants import DEFAULT_MAX_RETRIES from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj from litellm.litellm_core_utils.logging_utils import speech_request_body, track_llm_api_timing -from litellm.litellm_core_utils.url_utils import SSRFError, assert_same_origin from litellm.llms.custom_httpx.http_handler import ( AsyncHTTPHandler, HTTPHandler, @@ -34,7 +33,7 @@ from litellm.types.utils import ( from litellm.utils import ( CustomStreamWrapper, convert_to_model_response_object, - modify_url, + get_base_model_from_metadata, ) from ...types.llms.openai import HttpxBinaryResponseContent @@ -59,8 +58,6 @@ from .image_generation import ( ) from .image_generation.http_utils import azure_deployment_image_generation_json_body -_DECODED_JSON: Final = TypeAdapter(object) - class AzureOpenAIAssistantsAPIConfig: """ @@ -149,6 +146,7 @@ class AzureChatCompletion(BaseAzureLLM, BaseLLM): azure_client: AzureOpenAI | OpenAI, data: dict, timeout: float | httpx.Timeout, + logging_obj: LiteLLMLoggingObj, ): """ Helper to: @@ -164,7 +162,12 @@ class AzureChatCompletion(BaseAzureLLM, BaseLLM): except BadRequestError as e: if not is_output_token_limit_error(e): raise - return build_output_token_limit_response(e=e, data=data, is_async=False) + return build_output_token_limit_response( + e=e, + data=data, + is_async=False, + base_model=get_base_model_from_metadata(logging_obj.model_call_details), + ) except Exception as e: raise e @@ -196,7 +199,12 @@ class AzureChatCompletion(BaseAzureLLM, BaseLLM): except BadRequestError as e: if not is_output_token_limit_error(e): raise - return build_output_token_limit_response(e=e, data=data, is_async=True) + return build_output_token_limit_response( + e=e, + data=data, + is_async=True, + base_model=get_base_model_from_metadata(logging_obj.model_call_details), + ) except Exception as e: raise e @@ -354,7 +362,7 @@ class AzureChatCompletion(BaseAzureLLM, BaseLLM): ) headers, response = self.make_sync_azure_openai_chat_completion_request( - azure_client=azure_client, data=data, timeout=timeout + azure_client=azure_client, data=data, timeout=timeout, logging_obj=logging_obj ) if not isinstance(response, BaseModel): raise AzureOpenAIError( @@ -568,7 +576,7 @@ class AzureChatCompletion(BaseAzureLLM, BaseLLM): }, ) headers, response = self.make_sync_azure_openai_chat_completion_request( - azure_client=azure_client, data=data, timeout=timeout + azure_client=azure_client, data=data, timeout=timeout, logging_obj=logging_obj ) logging_obj.model_call_details["response_headers"] = headers streamwrapper: Final = CustomStreamWrapper( @@ -860,11 +868,6 @@ class AzureChatCompletion(BaseAzureLLM, BaseLLM): headers: dict, deployment_name: str | None = None, ) -> httpx.Response: - """ - Implemented for azure dall-e-2 image gen calls - - Alternative to needing a custom transport implementation - """ if client is None: _params: Final = {} if timeout is not None: @@ -881,95 +884,6 @@ class AzureChatCompletion(BaseAzureLLM, BaseLLM): else: async_handler = client - if ( - "images/generations" in api_base - and api_version - in [ # dall-e-3 starts from `2023-12-01-preview` so we should be able to avoid conflict - "2023-06-01-preview", - "2023-07-01-preview", - "2023-08-01-preview", - "2023-09-01-preview", - "2023-10-01-preview", - ] - ): # CREATE + POLL for azure dall-e-2 calls - api_base = modify_url(original_url=api_base, new_path="/openai/images/generations:submit") - - data.pop( - "model", None - ) # REMOVE 'model' from dall-e-2 arg https://learn.microsoft.com/en-us/azure/ai-services/openai/reference#request-a-generated-image-dall-e-2-preview - response = await async_handler.post( - url=api_base, - data=json.dumps(data), - headers=headers, - ) - if "operation-location" in response.headers: - operation_location_url: Final = response.headers["operation-location"] - else: - raise AzureOpenAIError(status_code=500, message=response.text) - # Reject polling URLs that don't share an origin with ``api_base``. - # Without this an upstream-controlled or attacker-controlled - # value would receive the operator's Azure API key in the - # request headers below. VERIA-51. - try: - assert_same_origin(operation_location_url, api_base) - except SSRFError as ssrf_err: - raise AzureOpenAIError( - status_code=502, - message=f"Rejected polling URL: {ssrf_err}", - ) - response = await async_handler.get( - url=operation_location_url, - headers=headers, - ) - - await response.aread() - - timeout_secs: Final[int] = AZURE_OPERATION_POLLING_TIMEOUT - start_time: Final = time.time() - if "status" not in response.json(): - # Don't reflect the raw response body — when the polling - # URL points at an internal JSON API (cloud metadata - # service etc.) reflecting it here turns Blind SSRF into - # Full-Read SSRF. VERIA-51. - raise AzureOpenAIError( - status_code=502, - message="Polling response missing 'status' field", - ) - while response.json()["status"] not in ["succeeded", "failed"]: - if time.time() - start_time > timeout_secs: - raise AzureOpenAIError(status_code=408, message="Operation polling timed out.") - - await asyncio.sleep(int(response.headers.get("retry-after") or 10)) - response = await async_handler.get( - url=operation_location_url, - headers=headers, - ) - await response.aread() - - if response.json()["status"] == "failed": - error_data: Final = response.json() - # Preserve Azure error details (e.g. content_policy_violation, - # inner_error, content_filter_results) as structured body so - # exception_type() can route them correctly. - _error_body: Final = error_data.get("error", error_data) - _error_msg: Final = ( - _error_body.get("message", "Image generation failed") - if isinstance(_error_body, dict) - else json.dumps(error_data) - ) - raise AzureOpenAIError( - status_code=400, - message=_error_msg, - body=error_data, - ) - - result: Final = _DECODED_JSON.validate_python(response.json()["result"]) - return httpx.Response( - status_code=200, - headers=response.headers, - content=json.dumps(result).encode("utf-8"), - request=httpx.Request(method="POST", url="https://api.openai.com/v1"), - ) request_json: Final = azure_deployment_image_generation_json_body(api_base, data, deployment_name) return await async_handler.post( url=api_base, @@ -988,11 +902,6 @@ class AzureChatCompletion(BaseAzureLLM, BaseLLM): headers: dict, deployment_name: str | None = None, ) -> httpx.Response: - """ - Implemented for azure dall-e-2 image gen calls - - Alternative to needing a custom transport implementation - """ if client is None: _params: Final = {} if timeout is not None: @@ -1006,87 +915,6 @@ class AzureChatCompletion(BaseAzureLLM, BaseLLM): else: sync_handler = client - if ( - "images/generations" in api_base - and api_version - in [ # dall-e-3 starts from `2023-12-01-preview` so we should be able to avoid conflict - "2023-06-01-preview", - "2023-07-01-preview", - "2023-08-01-preview", - "2023-09-01-preview", - "2023-10-01-preview", - ] - ): # CREATE + POLL for azure dall-e-2 calls - api_base = modify_url(original_url=api_base, new_path="/openai/images/generations:submit") - - data.pop( - "model", None - ) # REMOVE 'model' from dall-e-2 arg https://learn.microsoft.com/en-us/azure/ai-services/openai/reference#request-a-generated-image-dall-e-2-preview - response = sync_handler.post( - url=api_base, - data=json.dumps(data), - headers=headers, - ) - if "operation-location" in response.headers: - operation_location_url: Final = response.headers["operation-location"] - else: - raise AzureOpenAIError(status_code=500, message=response.text) - try: - assert_same_origin(operation_location_url, api_base) - except SSRFError as ssrf_err: - raise AzureOpenAIError( - status_code=502, - message=f"Rejected polling URL: {ssrf_err}", - ) - response = sync_handler.get( - url=operation_location_url, - headers=headers, - ) - - response.read() - - timeout_secs: Final[int] = AZURE_OPERATION_POLLING_TIMEOUT - start_time: Final = time.time() - if "status" not in response.json(): - raise AzureOpenAIError( - status_code=502, - message="Polling response missing 'status' field", - ) - while response.json()["status"] not in ["succeeded", "failed"]: - if time.time() - start_time > timeout_secs: - raise AzureOpenAIError(status_code=408, message="Operation polling timed out.") - - time.sleep(int(response.headers.get("retry-after") or 10)) - response = sync_handler.get( - url=operation_location_url, - headers=headers, - ) - response.read() - - if response.json()["status"] == "failed": - error_data: Final = response.json() - # Preserve Azure error details (e.g. content_policy_violation, - # inner_error, content_filter_results) as structured body so - # exception_type() can route them correctly. - _error_body: Final = error_data.get("error", error_data) - _error_msg: Final = ( - _error_body.get("message", "Image generation failed") - if isinstance(_error_body, dict) - else json.dumps(error_data) - ) - raise AzureOpenAIError( - status_code=400, - message=_error_msg, - body=error_data, - ) - - result: Final = _DECODED_JSON.validate_python(response.json()["result"]) - return httpx.Response( - status_code=200, - headers=response.headers, - content=json.dumps(result).encode("utf-8"), - request=httpx.Request(method="POST", url="https://api.openai.com/v1"), - ) request_json: Final = azure_deployment_image_generation_json_body(api_base, data, deployment_name) return sync_handler.post( url=api_base, @@ -1193,10 +1021,10 @@ class AzureChatCompletion(BaseAzureLLM, BaseLLM): deployment_name=model, ) - provider_config: Final = get_azure_image_generation_config(data.get("model", "dall-e-2")) + provider_config: Final = get_azure_image_generation_config(data.get("model", "")) if provider_config is not None: return provider_config.transform_image_generation_response( - model=data.get("model", "dall-e-2"), + model=data.get("model", ""), raw_response=httpx_response, model_response=model_response or ImageResponse(), logging_obj=logging_obj, @@ -1329,10 +1157,10 @@ class AzureChatCompletion(BaseAzureLLM, BaseLLM): headers=request_headers, deployment_name=model, ) - provider_config: Final = get_azure_image_generation_config(data.get("model", "dall-e-2")) + provider_config: Final = get_azure_image_generation_config(data.get("model", "")) if isinstance(provider_config, AzureFoundryMAIImageGenerationConfig): return provider_config.transform_image_generation_response( - model=data.get("model", "dall-e-2"), + model=data.get("model", ""), raw_response=httpx_response, model_response=model_response or ImageResponse(), logging_obj=logging_obj, diff --git a/litellm/llms/azure/common_utils.py b/litellm/llms/azure/common_utils.py index 23c5aa35f4b..6bb6d584385 100644 --- a/litellm/llms/azure/common_utils.py +++ b/litellm/llms/azure/common_utils.py @@ -5,7 +5,6 @@ import os import re from collections.abc import Awaitable, Callable, Mapping from contextlib import closing -from functools import lru_cache from types import MappingProxyType from typing import Final, Literal, NamedTuple, cast @@ -18,15 +17,18 @@ import litellm from litellm._logging import verbose_logger from litellm.caching.caching import DualCache from litellm.constants import DEFAULT_MAX_RETRIES +from litellm.litellm_core_utils.single_flight import SingleFlight, single_flight_lru_cache from litellm.litellm_core_utils.url_utils import ensure_api_route from litellm.llms.base_llm.chat.transformation import BaseLLMException from litellm.llms.custom_httpx.http_handler import HTTPHandler from litellm.llms.openai.common_utils import BaseOpenAILLM, OpenAIAsyncHTTPClient, OpenAIHTTPClient from litellm.secret_managers.get_azure_ad_token_provider import ( get_azure_ad_token_provider, + single_flight_bearer_token_provider, ) from litellm.secret_managers.main import get_secret_str from litellm.types.router import GenericLiteLLMParams +from litellm.types.secret_managers.get_azure_ad_token_provider import AzureCredentialType from litellm.utils import add_path_to_api_base azure_ad_cache: Final = DualCache() @@ -94,7 +96,7 @@ def process_azure_headers(headers: httpx.Headers | dict) -> dict: return {**llm_response_headers, **openai_headers} -@lru_cache(maxsize=128) +@single_flight_lru_cache def _cached_entra_id_token_provider( tenant_id: str, client_id: str, @@ -107,33 +109,38 @@ def _cached_entra_id_token_provider( to expiry, so reusing the provider keeps one AAD round trip per token lifetime instead of one per request. """ - from azure.identity import ClientSecretCredential, get_bearer_token_provider + from azure.identity import ClientSecretCredential - return get_bearer_token_provider(ClientSecretCredential(tenant_id, client_id, client_secret), scope) + return single_flight_bearer_token_provider(ClientSecretCredential(tenant_id, client_id, client_secret), scope) -@lru_cache(maxsize=128) +@single_flight_lru_cache def _cached_username_password_token_provider( client_id: str, azure_username: str, azure_password: str, scope: str, ) -> Callable[[], str]: - from azure.identity import UsernamePasswordCredential, get_bearer_token_provider + from azure.identity import UsernamePasswordCredential credential: Final = UsernamePasswordCredential( client_id=client_id, username=azure_username, password=azure_password, ) - return get_bearer_token_provider(credential, scope) + return single_flight_bearer_token_provider(credential, scope) -@lru_cache(maxsize=128) +@single_flight_lru_cache def _cached_azure_ad_token_refresh_provider(scope: str) -> Callable[[], str]: return get_azure_ad_token_provider(azure_scope=scope) +@single_flight_lru_cache +def _cached_default_azure_credential_provider(scope: str) -> Callable[[], str]: + return get_azure_ad_token_provider(azure_scope=scope, azure_credential=AzureCredentialType.DefaultAzureCredential) + + def cached_azure_ad_token_refresh_provider(scope: str) -> Callable[[], str]: return _cached_azure_ad_token_refresh_provider(scope) @@ -240,6 +247,58 @@ def get_azure_ad_token_from_username_password( return token_provider +@single_flight_lru_cache +def _oidc_token_exchange(cache_key: str) -> SingleFlight[str]: + return SingleFlight() + + +def _cached_oidc_token(cache_key: str) -> str | None: + cached: Final = azure_ad_cache.get_cache(cache_key) + return cached if isinstance(cached, str) else None + + +def _exchange_oidc_token(cache_key: str, token_url: str, client_id: str, scope: str, oidc_token: str) -> str: + cached_access_token: Final = _cached_oidc_token(cache_key) + if cached_access_token is not None: + return cached_access_token + + with closing(HTTPHandler(timeout=litellm.request_timeout)) as client: + req_token: Final = client.post( + token_url, + data={ + "client_id": client_id, + "grant_type": "client_credentials", + "scope": scope, + "client_assertion_type": "urn:ietf:params:oauth:client-assertion-type:jwt-bearer", + "client_assertion": oidc_token, + }, + ) + + if req_token.status_code != 200: + raise AzureOpenAIError( + status_code=req_token.status_code, + message=req_token.text, + ) + + azure_ad_token_json: Final[_AzureAdTokenJson] = req_token.json() + azure_ad_token_access_token: Final = azure_ad_token_json.get("access_token", None) + azure_ad_token_expires_in: Final = azure_ad_token_json.get("expires_in", None) + + if azure_ad_token_access_token is None: + raise AzureOpenAIError(status_code=422, message="Azure AD Token access_token not returned") + + if azure_ad_token_expires_in is None: + raise AzureOpenAIError(status_code=422, message="Azure AD Token expires_in not returned") + + azure_ad_cache.set_cache( + key=cache_key, + value=azure_ad_token_access_token, + ttl=azure_ad_token_expires_in, + ) + + return azure_ad_token_access_token + + def get_azure_ad_token_from_oidc( azure_ad_token: str, azure_client_id: str | None = None, @@ -282,50 +341,25 @@ def get_azure_ad_token_from_oidc( "azure_client_id": azure_client_id, "azure_tenant_id": azure_tenant_id, "azure_authority_host": azure_authority_host, + "scope": scope, "oidc_token": oidc_token, } ) - azure_ad_token_access_token = azure_ad_cache.get_cache(azure_ad_token_cache_key) - if azure_ad_token_access_token is not None: - return azure_ad_token_access_token + cached_access_token: Final = _cached_oidc_token(azure_ad_token_cache_key) + if cached_access_token is not None: + return cached_access_token - with closing(HTTPHandler(timeout=litellm.request_timeout)) as client: - req_token: Final = client.post( - f"{azure_authority_host}/{azure_tenant_id}/oauth2/v2.0/token", - data={ - "client_id": azure_client_id, - "grant_type": "client_credentials", - "scope": scope, - "client_assertion_type": "urn:ietf:params:oauth:client-assertion-type:jwt-bearer", - "client_assertion": oidc_token, - }, + return _oidc_token_exchange(azure_ad_token_cache_key).run( + lambda: _exchange_oidc_token( + azure_ad_token_cache_key, + token_url=f"{azure_authority_host}/{azure_tenant_id}/oauth2/v2.0/token", + client_id=azure_client_id, + scope=scope, + oidc_token=oidc_token, ) - - if req_token.status_code != 200: - raise AzureOpenAIError( - status_code=req_token.status_code, - message=req_token.text, - ) - - azure_ad_token_json: Final[_AzureAdTokenJson] = req_token.json() - azure_ad_token_access_token = azure_ad_token_json.get("access_token", None) - azure_ad_token_expires_in: Final = azure_ad_token_json.get("expires_in", None) - - if azure_ad_token_access_token is None: - raise AzureOpenAIError(status_code=422, message="Azure AD Token access_token not returned") - - if azure_ad_token_expires_in is None: - raise AzureOpenAIError(status_code=422, message="Azure AD Token expires_in not returned") - - azure_ad_cache.set_cache( - key=azure_ad_token_cache_key, - value=azure_ad_token_access_token, - ttl=azure_ad_token_expires_in, ) - return azure_ad_token_access_token - def select_azure_base_url_or_endpoint(azure_client_params: dict): azure_endpoint: Final = azure_client_params.get("azure_endpoint", None) @@ -503,17 +537,10 @@ class BaseAzureLLM(BaseOpenAILLM): Returns: Token provider callable if DefaultAzureCredential is enabled and available, None otherwise """ - from litellm.types.secret_managers.get_azure_ad_token_provider import ( - AzureCredentialType, - ) - verbose_logger.debug("Attempting to use DefaultAzureCredential for Azure Auth") try: - azure_ad_token_provider: Final = get_azure_ad_token_provider( - azure_scope=scope, - azure_credential=AzureCredentialType.DefaultAzureCredential, - ) + azure_ad_token_provider: Final = _cached_default_azure_credential_provider(scope) verbose_logger.debug("Successfully obtained Azure AD token provider using DefaultAzureCredential") return azure_ad_token_provider except Exception as e: @@ -594,7 +621,7 @@ class BaseAzureLLM(BaseOpenAILLM): # For Azure v1 API, use standard OpenAI client instead of AzureOpenAI # See: https://learn.microsoft.com/en-us/azure/ai-services/openai/reference#api-specs - if self._is_azure_v1_api_version(api_version): + if self.is_azure_v1_api_version(api_version): # Extract only params that OpenAI client accepts # Always use /openai/v1/ regardless of whether user passed "v1", "latest", or "preview" # The OpenAI client accepts a callable for `api_key` and re-invokes it @@ -895,7 +922,7 @@ class BaseAzureLLM(BaseOpenAILLM): else: new_url = api_base - if BaseAzureLLM._is_azure_v1_api_version(api_version): + if BaseAzureLLM.is_azure_v1_api_version(api_version): # ensure the request go to /openai/v1 and not just /openai if "/openai/v1" not in new_url: parsed_url: Final = httpx.URL(new_url) @@ -925,7 +952,7 @@ class BaseAzureLLM(BaseOpenAILLM): Returns None when ``api_version`` is a dated one, which still uses the deployment route. """ - if not BaseAzureLLM._is_azure_v1_api_version(api_version): + if not BaseAzureLLM.is_azure_v1_api_version(api_version): return None base_url: Final = httpx.URL(api_base) @@ -943,7 +970,7 @@ class BaseAzureLLM(BaseOpenAILLM): ) @staticmethod - def _is_azure_v1_api_version(api_version: str | None) -> bool: + def is_azure_v1_api_version(api_version: str | None) -> bool: if api_version is None: return False return api_version in {"preview", "latest", "v1"} diff --git a/litellm/llms/azure/image_generation/__init__.py b/litellm/llms/azure/image_generation/__init__.py index a2a905f2287..7e9b5f5d99c 100644 --- a/litellm/llms/azure/image_generation/__init__.py +++ b/litellm/llms/azure/image_generation/__init__.py @@ -4,14 +4,10 @@ from litellm.llms.base_llm.image_generation.transformation import ( BaseImageGenerationConfig, ) -from .dall_e_2_transformation import AzureDallE2ImageGenerationConfig -from .dall_e_3_transformation import AzureDallE3ImageGenerationConfig from .gpt_transformation import AzureGPTImageGenerationConfig from .http_utils import azure_deployment_image_generation_json_body __all__ = [ - "AzureDallE2ImageGenerationConfig", - "AzureDallE3ImageGenerationConfig", "AzureGPTImageGenerationConfig", "azure_deployment_image_generation_json_body", ] @@ -21,11 +17,7 @@ def get_azure_image_generation_config(model: str) -> BaseImageGenerationConfig: model = model.lower() model = model.replace("-", "") model = model.replace("_", "") - if model == "" or "dalle2" in model: # empty model is dall-e-2 - return AzureDallE2ImageGenerationConfig() - elif "dalle3" in model: - return AzureDallE3ImageGenerationConfig() - elif AzureFoundryMAIImageGenerationConfig.is_mai_model(model): + if AzureFoundryMAIImageGenerationConfig.is_mai_model(model): return AzureFoundryMAIImageGenerationConfig() else: verbose_logger.debug( diff --git a/litellm/llms/azure/image_generation/dall_e_2_transformation.py b/litellm/llms/azure/image_generation/dall_e_2_transformation.py deleted file mode 100644 index 788753e4ea9..00000000000 --- a/litellm/llms/azure/image_generation/dall_e_2_transformation.py +++ /dev/null @@ -1,7 +0,0 @@ -from litellm.llms.openai.image_generation import DallE2ImageGenerationConfig - - -class AzureDallE2ImageGenerationConfig(DallE2ImageGenerationConfig): - """ - Azure dall-e-2 image generation config - """ diff --git a/litellm/llms/azure/image_generation/dall_e_3_transformation.py b/litellm/llms/azure/image_generation/dall_e_3_transformation.py deleted file mode 100644 index e6974f9317e..00000000000 --- a/litellm/llms/azure/image_generation/dall_e_3_transformation.py +++ /dev/null @@ -1,7 +0,0 @@ -from litellm.llms.openai.image_generation import DallE3ImageGenerationConfig - - -class AzureDallE3ImageGenerationConfig(DallE3ImageGenerationConfig): - """ - Azure dall-e-3 image generation config - """ diff --git a/litellm/llms/azure/responses/transformation.py b/litellm/llms/azure/responses/transformation.py index 647ad97e02c..09777da8669 100644 --- a/litellm/llms/azure/responses/transformation.py +++ b/litellm/llms/azure/responses/transformation.py @@ -54,6 +54,16 @@ def _resolve_responses_api_version(api_base: str | None, litellm_params: Mapping return api_version +def _v1_responses_url(api_base: str) -> httpx.URL: + parsed_url: Final = httpx.URL(api_base) + path: Final = parsed_url.path.rstrip("/") + root: Final = next( + (path.removesuffix(route) for route in ("/openai/v1/responses", "/openai/responses") if path.endswith(route)), + path, + ) + return parsed_url.copy_with(path=f"{root}/openai/v1/responses", query=None) + + def _with_responses_api_version(api_base: str | None, litellm_params: Mapping[str, object]) -> Mapping[str, object]: return MappingProxyType({**litellm_params, "api_version": _resolve_responses_api_version(api_base, litellm_params)}) @@ -132,7 +142,9 @@ class AzureOpenAIResponsesAPIConfig(OpenAIResponsesAPIConfig): return filtered_item return item - def _validate_input_param(self, input: str | ResponseInputParam) -> str | ResponseInputParam: + def _validate_input_param( + self, input: str | ResponseInputParam, *, drops_set_created_by: bool = False + ) -> str | ResponseInputParam: """ Override parent method to also filter out 'status' field from message items. Azure OpenAI API does not accept 'status' field in input messages. @@ -140,7 +152,7 @@ class AzureOpenAIResponsesAPIConfig(OpenAIResponsesAPIConfig): from typing import cast # First call parent's validation - validated_input: Final = super()._validate_input_param(input) + validated_input: Final = super()._validate_input_param(input, drops_set_created_by=drops_set_created_by) # Then filter out status from message items if isinstance(validated_input, list): @@ -247,20 +259,20 @@ class AzureOpenAIResponsesAPIConfig(OpenAIResponsesAPIConfig): if api_base is None: raise ValueError("api_base is required for Azure WebSocket") - parsed_url: Final = httpx.URL(api_base) - path = parsed_url.path.rstrip("/") - # Strip existing /openai/responses path if the api_base already contains it - for suffix in ("/openai/v1/responses", "/openai/responses"): - if path.endswith(suffix): - path = path[: -len(suffix)] - break - scheme: Final = "wss" if parsed_url.scheme == "https" else "ws" - return str(parsed_url.copy_with(scheme=scheme, path=f"{path}/openai/v1/responses", query=None)) + v1_url: Final = _v1_responses_url(api_base) + return str(v1_url.copy_with(scheme="wss" if v1_url.scheme == "https" else "ws")) def model_in_websocket_url(self) -> bool: # Azure sends the model in the response.create body, not the URL return False + def compact_url(self, api_base: str) -> str: + params: Final = httpx.URL(api_base).params + v1_params: Final = ( + params if BaseAzureLLM.is_azure_v1_api_version(params.get("api-version")) else params.remove("api-version") + ) + return super().compact_url(str(_v1_responses_url(api_base).copy_with(params=v1_params))) + ######################################################### ########## DELETE RESPONSE API TRANSFORMATION ############## ######################################################### @@ -323,7 +335,7 @@ class AzureOpenAIResponsesAPIConfig(OpenAIResponsesAPIConfig): api_base: str, litellm_params: GenericLiteLLMParams, headers: dict, - ) -> tuple[str, dict]: + ) -> tuple[str, dict[str, str]]: """ Transform the get response API request into a URL and data @@ -331,7 +343,7 @@ class AzureOpenAIResponsesAPIConfig(OpenAIResponsesAPIConfig): - GET /v1/responses/{response_id} """ get_url: Final = self._construct_url_for_response_id_in_path(api_base=api_base, response_id=response_id) - data: Final[dict] = {} + data: Final[dict[str, str]] = {} verbose_logger.debug("get response url=%s", get_url) return get_url, data diff --git a/litellm/llms/azure_ai/agents/handler.py b/litellm/llms/azure_ai/agents/handler.py index 94f1399f01b..423a09c5c92 100644 --- a/litellm/llms/azure_ai/agents/handler.py +++ b/litellm/llms/azure_ai/agents/handler.py @@ -35,6 +35,7 @@ from litellm.llms.azure_ai.agents.transformation import ( AzureAIAgentsConfig, AzureAIAgentsError, ) +from litellm.llms.custom_httpx.sse_lines import aiter_sse_lines from litellm.types.llms.openai import ( ChatCompletionAnnotation, ChatCompletionAnnotationURLCitation, @@ -632,7 +633,7 @@ class AzureAIAgentsHandler: current_event = None - async for line in response.aiter_lines(): + async for line in aiter_sse_lines(response.aiter_text()): line = line.strip() if line.startswith("event:"): diff --git a/litellm/llms/azure_ai/anthropic/count_tokens/handler.py b/litellm/llms/azure_ai/anthropic/count_tokens/handler.py index 0f8afaae681..4b3f263201a 100644 --- a/litellm/llms/azure_ai/anthropic/count_tokens/handler.py +++ b/litellm/llms/azure_ai/anthropic/count_tokens/handler.py @@ -13,6 +13,7 @@ from pydantic import JsonValue import litellm from litellm._logging import verbose_logger from litellm.litellm_core_utils.asyncify import asyncify +from litellm.litellm_core_utils.core_helpers import drops_unsupported_params from litellm.llms.anthropic.common_utils import AnthropicError from litellm.llms.azure_ai.anthropic.count_tokens.transformation import ( AzureAIAnthropicCountTokensConfig, @@ -69,6 +70,7 @@ class AzureAIAnthropicCountTokensHandler(AzureAIAnthropicCountTokensConfig): tools=tools, system=system, optional_params=optional_params, + drop_params=drops_unsupported_params((litellm_params or {}).get("drop_params")), ) verbose_logger.debug("Transformed request: %s", request_body) diff --git a/litellm/llms/azure_ai/common_utils.py b/litellm/llms/azure_ai/common_utils.py index 65d73363b30..147bf69e91e 100644 --- a/litellm/llms/azure_ai/common_utils.py +++ b/litellm/llms/azure_ai/common_utils.py @@ -140,6 +140,15 @@ def get_azure_ai_auth_headers( AZURE_MODEL_ROUTER_SELECTED_MODEL_KEY: Final = "azure_model_router_selected_model" +FOUNDRY_CLASSIC_AGENT_ID_PREFIX: Final = "asst_" + + +def is_foundry_project_agent(model: str | None) -> bool: + if model is None or AzureFoundryModelInfo.get_azure_ai_route(model) != "agents": + return False + return not model.split("agents/", 1)[1].startswith(FOUNDRY_CLASSIC_AGENT_ID_PREFIX) + + def azure_ai_supports_native_responses(model: str | None, api_base: str | None) -> bool: resolved_base: Final = AzureFoundryModelInfo.get_api_base(api_base) if resolved_base is not None and not is_azure_openai_v1_host(resolved_base): diff --git a/litellm/llms/azure_ai/image_generation/__init__.py b/litellm/llms/azure_ai/image_generation/__init__.py index 742922ad295..bd3c11d36f9 100644 --- a/litellm/llms/azure_ai/image_generation/__init__.py +++ b/litellm/llms/azure_ai/image_generation/__init__.py @@ -3,15 +3,11 @@ from litellm.llms.base_llm.image_generation.transformation import ( BaseImageGenerationConfig, ) -from .dall_e_2_transformation import AzureFoundryDallE2ImageGenerationConfig -from .dall_e_3_transformation import AzureFoundryDallE3ImageGenerationConfig from .flux_transformation import AzureFoundryFluxImageGenerationConfig from .gpt_transformation import AzureFoundryGPTImageGenerationConfig from .mai_transformation import AzureFoundryMAIImageGenerationConfig __all__ = [ - "AzureFoundryDallE2ImageGenerationConfig", - "AzureFoundryDallE3ImageGenerationConfig", "AzureFoundryFluxImageGenerationConfig", "AzureFoundryGPTImageGenerationConfig", "AzureFoundryMAIImageGenerationConfig", @@ -22,11 +18,7 @@ def get_azure_ai_image_generation_config(model: str) -> BaseImageGenerationConfi model = model.lower() model = model.replace("-", "") model = model.replace("_", "") - if model == "" or "dalle2" in model: # empty model is dall-e-2 - return AzureFoundryDallE2ImageGenerationConfig() - elif "dalle3" in model: - return AzureFoundryDallE3ImageGenerationConfig() - elif AzureFoundryMAIImageGenerationConfig.is_mai_model(model): + if AzureFoundryMAIImageGenerationConfig.is_mai_model(model): return AzureFoundryMAIImageGenerationConfig() elif "flux" in model: return AzureFoundryFluxImageGenerationConfig() diff --git a/litellm/llms/azure_ai/image_generation/dall_e_2_transformation.py b/litellm/llms/azure_ai/image_generation/dall_e_2_transformation.py deleted file mode 100644 index 2c8a5426628..00000000000 --- a/litellm/llms/azure_ai/image_generation/dall_e_2_transformation.py +++ /dev/null @@ -1,7 +0,0 @@ -from litellm.llms.openai.image_generation import DallE2ImageGenerationConfig - - -class AzureFoundryDallE2ImageGenerationConfig(DallE2ImageGenerationConfig): - """ - Azure dall-e-2 image generation config - """ diff --git a/litellm/llms/azure_ai/image_generation/dall_e_3_transformation.py b/litellm/llms/azure_ai/image_generation/dall_e_3_transformation.py deleted file mode 100644 index 3ceb9b405da..00000000000 --- a/litellm/llms/azure_ai/image_generation/dall_e_3_transformation.py +++ /dev/null @@ -1,7 +0,0 @@ -from litellm.llms.openai.image_generation import DallE3ImageGenerationConfig - - -class AzureFoundryDallE3ImageGenerationConfig(DallE3ImageGenerationConfig): - """ - Azure dall-e-3 image generation config - """ diff --git a/litellm/llms/azure_ai/responses/transformation.py b/litellm/llms/azure_ai/responses/transformation.py index d23de05e148..da734cf8189 100644 --- a/litellm/llms/azure_ai/responses/transformation.py +++ b/litellm/llms/azure_ai/responses/transformation.py @@ -1,26 +1,64 @@ -from typing import Final +import os +from collections.abc import Collection, Mapping, Sequence +from typing import TYPE_CHECKING, Final, NoReturn import httpx +from pydantic import BaseModel, ConfigDict, TypeAdapter, ValidationError +import litellm +from litellm.exceptions import UnsupportedParamsError from litellm.llms.azure.responses.transformation import AzureOpenAIResponsesAPIConfig from litellm.llms.azure_ai.chat.transformation import AzureAIGPT5Config from litellm.llms.azure_ai.common_utils import ( + AZURE_AI_AGENTS_SCOPE, AzureFoundryModelInfo, api_key_header_for_base, get_azure_ai_auth_headers, ) +from litellm.types.llms.azure_ai import FoundryAgentReference +from litellm.types.llms.openai import ( + ResponseInputParam, + ResponsesAPIOptionalRequestParams, + ResponsesAPIResponse, + ResponsesAPIStreamingResponse, +) from litellm.types.router import GenericLiteLLMParams from litellm.types.utils import LlmProviders +if TYPE_CHECKING: + from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj + _PROJECT_PATH_PREFIX: Final = ("api", "projects") _RESPONSES_PATH: Final = ("openai", "v1", "responses") +_AGENT_OWNED_PARAMS: Final = frozenset({"temperature", "top_p", "tools", "text", "reasoning"}) +_CALLER_AGENT_KEYS: Final = ("agent", "agent_reference") +_RESPONSE_FIELDS: Final = TypeAdapter(dict[str, object]) + + +def _project_root(base_url: httpx.URL) -> tuple[str, ...]: + segments: Final = tuple(segment for segment in base_url.path.split("/") if segment) + return segments[:3] if segments[:2] == _PROJECT_PATH_PREFIX else () def _responses_url(api_base: str) -> str: base_url: Final = httpx.URL(api_base) - segments: Final = tuple(segment for segment in base_url.path.split("/") if segment) - project_root: Final = segments[:3] if segments[:2] == _PROJECT_PATH_PREFIX else () - return str(base_url.copy_with(path="/" + "/".join((*project_root, *_RESPONSES_PATH)), query=None)) + return str(base_url.copy_with(path="/" + "/".join((*_project_root(base_url), *_RESPONSES_PATH)), query=None)) + + +def _without_agent_instructions(response: ResponsesAPIResponse) -> ResponsesAPIResponse: + if (response.model_extra or {}).get("agent_reference") is None: + return response + return response.model_copy(update={"instructions": None}) + + +def _event_without_agent_instructions(event: Mapping[str, object]) -> Mapping[str, object]: + response: Final = event.get("response") + if not isinstance(response, Mapping): + return event + fields: Final = _RESPONSE_FIELDS.validate_python(response) + if fields.get("agent_reference") is None: + return event + return {**event, "response": {**fields, "instructions": None}} class AzureAIResponsesAPIConfig(AzureOpenAIResponsesAPIConfig): @@ -42,10 +80,19 @@ class AzureAIResponsesAPIConfig(AzureOpenAIResponsesAPIConfig): def validate_environment(self, headers: dict, model: str, litellm_params: GenericLiteLLMParams | None) -> dict: params: Final = litellm_params or GenericLiteLLMParams() + api_base: Final = AzureFoundryModelInfo.get_api_base(params.api_base) + on_project: Final = api_base is not None and bool(_project_root(httpx.URL(api_base))) + auth_params: Final = ( + params.model_copy( + update={"azure_scope": params.azure_scope or os.getenv("AZURE_SCOPE") or AZURE_AI_AGENTS_SCOPE} + ) + if on_project + else params + ) auth_headers: Final = get_azure_ai_auth_headers( api_key=AzureFoundryModelInfo.get_api_key(params.api_key), - litellm_params=params.model_dump(), - api_key_header=api_key_header_for_base(AzureFoundryModelInfo.get_api_base(params.api_base)), + litellm_params=auth_params.model_dump(), + api_key_header="Authorization" if on_project else api_key_header_for_base(api_base), ) return { **headers, @@ -64,3 +111,207 @@ class AzureAIResponsesAPIConfig(AzureOpenAIResponsesAPIConfig): "Set the api_base parameter or the AZURE_AI_API_BASE environment variable." ) return _responses_url(resolved_base) + + def transform_response_api_response( + self, model: str, raw_response: httpx.Response, logging_obj: "LiteLLMLoggingObj" + ) -> ResponsesAPIResponse: + return _without_agent_instructions(super().transform_response_api_response(model, raw_response, logging_obj)) + + def transform_streaming_response( + self, + model: str, + parsed_chunk: Mapping[str, object], + logging_obj: "LiteLLMLoggingObj", + ) -> ResponsesAPIStreamingResponse: + return super().transform_streaming_response( # pyright: ignore[reportUnknownMemberType] # parent types parsed_chunk as a bare dict + model=model, parsed_chunk=dict(_event_without_agent_instructions(parsed_chunk)), logging_obj=logging_obj + ) + + def transform_get_response_api_response( + self, raw_response: httpx.Response, logging_obj: "LiteLLMLoggingObj" + ) -> ResponsesAPIResponse: + return _without_agent_instructions(super().transform_get_response_api_response(raw_response, logging_obj)) + + def transform_cancel_response_api_response( + self, raw_response: httpx.Response, logging_obj: "LiteLLMLoggingObj" + ) -> ResponsesAPIResponse: + return _without_agent_instructions(super().transform_cancel_response_api_response(raw_response, logging_obj)) + + +def _agent_reference(model: str) -> FoundryAgentReference: + name, _, version = model.split("agents/", 1)[1].partition(":") + if version: + return FoundryAgentReference(type="agent_reference", name=name, version=version) + return FoundryAgentReference(type="agent_reference", name=name) + + +class _CallerAgentReference(BaseModel): + model_config = ConfigDict(frozen=True, coerce_numbers_to_str=True) + + name: str + version: str | None = None + + +def _caller_agent_reference(value: object) -> _CallerAgentReference | None: + try: + return _CallerAgentReference.model_validate(value) + except ValidationError: + return None + + +def _requested_agent( + deployment_agent: FoundryAgentReference, caller_agents: Sequence[_CallerAgentReference | None] +) -> FoundryAgentReference: + requested_versions: Final = frozenset( + agent.version + for agent in caller_agents + if agent is not None and agent.name == deployment_agent["name"] and agent.version is not None + ) + if "version" in deployment_agent or len(requested_versions) != 1: + return deployment_agent + return FoundryAgentReference( + type="agent_reference", name=deployment_agent["name"], version=next(iter(requested_versions)) + ) + + +def _caller_agent_fields(fields: Mapping[str, object]) -> tuple[tuple[str, object], ...]: + return tuple((key, fields[key]) for key in _CALLER_AGENT_KEYS if key in fields) + + +def _deployment_agent( + model: str, caller_fields: Sequence[tuple[str, object]], litellm_params: GenericLiteLLMParams +) -> FoundryAgentReference: + caller_keys: Final = tuple(key for key, _ in caller_fields) + caller_agents: Final = tuple(_caller_agent_reference(value) for _, value in caller_fields) + agent: Final = _requested_agent(_agent_reference(model), caller_agents) + other_agents: Final = tuple( + key + for key, caller_agent in zip(caller_keys, caller_agents) + if caller_agent is None + or caller_agent.name != agent["name"] + or caller_agent.version not in (None, agent.get("version")) + ) + if other_agents and not (litellm.drop_params is True or litellm_params.drop_params is True): + raise UnsupportedParamsError( + message=( + f"This model entry always calls Foundry agent {agent['name']!r}, so `{other_agents[0]}` " + "in the request cannot pick another agent or version. Remove it, call the model entry for that " + "agent, or set `drop_params: true` to drop it" + ), + llm_provider=LlmProviders.AZURE_AI.value, + model=model, + ) + return agent + + +_INPUT_ITEMS: Final = TypeAdapter(list[object]) + + +def _with_system_prompt(instructions: str, request_input: object) -> Sequence[object]: + conversation: Final = ( + [{"type": "message", "role": "user", "content": request_input}] + if isinstance(request_input, str) + else _INPUT_ITEMS.validate_python(request_input) + ) + return [{"type": "message", "role": "system", "content": instructions}, *conversation] + + +class AzureAIAgentResponsesAPIConfig(AzureAIResponsesAPIConfig): + def should_fake_stream( + self, model: str | None, stream: bool | None, custom_llm_provider: str | None = None + ) -> bool: + return False + + def get_supported_openai_params(self, model: str) -> list[str]: # mutable-ok: override contract + inherited: Final[list[str]] = super().get_supported_openai_params(model) # pyright: ignore[reportUnknownMemberType, reportUnknownVariableType] # parent returns a bare list # mutable-ok: same + return [param for param in inherited if param not in _AGENT_OWNED_PARAMS] + + def map_openai_params_for_deployment( + self, + response_api_optional_params: ResponsesAPIOptionalRequestParams, + model: str, + drop_params: bool, + *, + declared_reasoning_efforts: Collection[str], + ) -> Mapping[str, object]: + mapped: Final = super().map_openai_params_for_deployment( + response_api_optional_params, model, drop_params, declared_reasoning_efforts=declared_reasoning_efforts + ) + resends_instructions: Final = bool(mapped.get("instructions")) and bool(mapped.get("previous_response_id")) + if resends_instructions and not drop_params: + raise UnsupportedParamsError( + message=( + "azure_ai Foundry agents store a turn's system message with the conversation, so `instructions` " + "with `previous_response_id` would add another copy each turn. Send `instructions` on the first " + "turn only, or set `drop_params: true` to drop it" + ), + llm_provider=LlmProviders.AZURE_AI.value, + model=model, + ) + dropped: Final = _AGENT_OWNED_PARAMS | ( + frozenset({"instructions"}) if resends_instructions else frozenset[str]() + ) + return {key: value for key, value in mapped.items() if key not in dropped} + + def transform_responses_api_request( + self, + model: str, + input: str | ResponseInputParam, + response_api_optional_request_params: dict[str, object], # mutable-ok: signature fixed by the override contract + litellm_params: GenericLiteLLMParams, + headers: dict[str, str], # mutable-ok: same + ) -> dict[str, object]: # mutable-ok: same + request: Final[dict[str, object]] = super().transform_responses_api_request( # pyright: ignore[reportUnknownMemberType, reportUnknownVariableType] # parent returns a bare dict # mutable-ok: same + model=model, + input=input, + response_api_optional_request_params=response_api_optional_request_params, + litellm_params=litellm_params, + headers=headers, + ) + instructions: Final = request.get("instructions") + return { + **{key: value for key, value in request.items() if key not in ("model", "instructions")}, + **( + {"input": _with_system_prompt(instructions, request.get("input"))} + if isinstance(instructions, str) and instructions + else {} + ), + "agent_reference": _deployment_agent( + model, _caller_agent_fields(litellm_params.model_extra or {}), litellm_params + ), + } + + def transform_extra_body( + self, + extra_body: Mapping[str, object], + request: Mapping[str, object], + model: str, + litellm_params: GenericLiteLLMParams, + ) -> Mapping[str, object]: + passthrough: Final = {key: value for key, value in extra_body.items() if key not in _CALLER_AGENT_KEYS} + if len(passthrough) == len(extra_body): + return passthrough + return { + **passthrough, + "agent_reference": _deployment_agent( + model, (*_caller_agent_fields(request), *_caller_agent_fields(extra_body)), litellm_params + ), + } + + def transform_compact_response_api_request( + self, + model: str, + input: str | ResponseInputParam, + response_api_optional_request_params: dict[str, object], # mutable-ok: signature fixed by the override contract + api_base: str, + litellm_params: GenericLiteLLMParams, + headers: dict[str, str], # mutable-ok: same + ) -> NoReturn: + raise UnsupportedParamsError( + message=( + "azure_ai Foundry agents cannot be compacted, because the project's /responses/compact endpoint " + "takes a model deployment, not an agent. Call compact on a model entry for that deployment instead" + ), + llm_provider=LlmProviders.AZURE_AI.value, + model=model, + ) diff --git a/litellm/llms/base_llm/agents/transformation.py b/litellm/llms/base_llm/agents/transformation.py index 9d139b289c4..5ea6ea950d9 100644 --- a/litellm/llms/base_llm/agents/transformation.py +++ b/litellm/llms/base_llm/agents/transformation.py @@ -15,6 +15,7 @@ from collections.abc import Mapping import httpx from litellm.types.agents import ( + AgentCreateRequest, AgentCreateResponse, AgentDeleteResult, AgentListResponse, @@ -50,10 +51,9 @@ class BaseAgentsAPIConfig(ABC): @abstractmethod def transform_create_request( self, - name: str, - litellm_params: Mapping[str, object], - ) -> dict[str, object]: - """Map name + litellm_params to the provider's create-agent body.""" + create_request: AgentCreateRequest, + ) -> Mapping[str, object]: + """Map the create request to the provider's create-agent body.""" @abstractmethod def transform_create_response( diff --git a/litellm/llms/base_llm/base_model_iterator.py b/litellm/llms/base_llm/base_model_iterator.py index 611051bb2dd..3afc685b3dd 100644 --- a/litellm/llms/base_llm/base_model_iterator.py +++ b/litellm/llms/base_llm/base_model_iterator.py @@ -3,6 +3,7 @@ from abc import abstractmethod from typing import TYPE_CHECKING, Final, cast import litellm +from litellm.constants import STREAM_SSE_DONE_STRING if TYPE_CHECKING: import httpx @@ -95,7 +96,7 @@ class BaseModelResponseIterator: released (and a backend like vLLM aborts generation) when the stream is abandoned before its natural end. - ``streaming_response`` is usually a bare ``aiter_lines()`` generator + ``streaming_response`` is usually a bare ``aiter_sse_lines()`` generator that holds no reference to the response, so the handler that owns the response attaches it here after construction.""" if self.http_response is not None: @@ -142,7 +143,8 @@ class BaseModelResponseIterator: def _handle_string_chunk(self, str_line: str) -> GenericStreamingChunk | ModelResponseStream: # chunk is a str at this point stripped_json_chunk: Final = BaseModelResponseIterator._string_to_dict_parser(str_line=str_line) - if "[DONE]" in str_line: + stripped_sse_chunk: Final = litellm.CustomStreamWrapper.strip_sse_data_from_chunk(str_line) + if stripped_sse_chunk is not None and stripped_sse_chunk.strip() == STREAM_SSE_DONE_STRING: return GenericStreamingChunk( text="", is_finished=True, diff --git a/litellm/llms/base_llm/files/transformation.py b/litellm/llms/base_llm/files/transformation.py index 4346e214dc8..491fb1919b6 100644 --- a/litellm/llms/base_llm/files/transformation.py +++ b/litellm/llms/base_llm/files/transformation.py @@ -1,6 +1,7 @@ from abc import ABC, abstractmethod -from collections.abc import AsyncGenerator, Iterator, Mapping -from typing import TYPE_CHECKING, Any, Union +from collections.abc import AsyncGenerator, Callable, Iterable, Iterator, Mapping +from dataclasses import dataclass +from typing import TYPE_CHECKING, Any, Final, Union import httpx from openai.types.file_deleted import FileDeleted @@ -38,6 +39,22 @@ else: UserAPIKeyAuth = Any +def _routes_nowhere(_model_name: str) -> bool: + return False + + +@dataclass(frozen=True, slots=True) +class FileListModelScope: + model_mapping_keys: frozenset[str] + routes_stored_model_name: Callable[[str], bool] = _routes_nowhere + + def holds(self, model_mapping_keys: Iterable[str], stored: bool) -> bool: + mapped_keys: Final = frozenset(model_mapping_keys) + return not self.model_mapping_keys.isdisjoint(mapped_keys) or ( + stored and any(map(self.routes_stored_model_name, mapped_keys)) + ) + + class BaseFileUploadStream(ABC): """Re-iterable request body that yields an upload's bytes lazily. @@ -274,6 +291,8 @@ class BaseFileEndpoints(ABC): user_api_key_dict: UserAPIKeyAuth, limit: int | None = None, after: str | None = None, + model_scope: FileListModelScope | None = None, + before: str | None = None, **data: dict, ) -> FileListPage: pass diff --git a/litellm/llms/base_llm/guardrail_translation/utils.py b/litellm/llms/base_llm/guardrail_translation/utils.py index 725146fe894..fb886e42780 100644 --- a/litellm/llms/base_llm/guardrail_translation/utils.py +++ b/litellm/llms/base_llm/guardrail_translation/utils.py @@ -6,6 +6,7 @@ from typing import Final, TypeVar, cast # noqa: TID251 # a rebuilt chat row ha from pydantic import BaseModel, ConfigDict, TypeAdapter, ValidationError +from litellm.llms.custom_httpx.sse_lines import split_sse_lines from litellm.types.llms.anthropic_messages.anthropic_response import AnthropicUsage from litellm.types.llms.openai import AllMessageValues, ResponseAPIUsage @@ -24,7 +25,7 @@ def _anthropic_stream_chunk_events(item: object) -> list[dict]: events: Final[list[dict]] = [] for block in chunk.split("\n\n"): - for line in block.splitlines(): + for line in split_sse_lines(block): stripped = line.strip() if not stripped.startswith("data:"): continue diff --git a/litellm/llms/base_llm/responses/transformation.py b/litellm/llms/base_llm/responses/transformation.py index 01baeed9bef..792b14090b8 100644 --- a/litellm/llms/base_llm/responses/transformation.py +++ b/litellm/llms/base_llm/responses/transformation.py @@ -69,6 +69,9 @@ class BaseResponsesAPIConfig(ABC): def supports_encrypted_agent_messages(self) -> bool: return False + def supports_streamed_retrieval(self) -> bool: + return self.custom_llm_provider in (LlmProviders.OPENAI, LlmProviders.AZURE, LlmProviders.AZURE_AI) + def sign_request( self, headers: dict, @@ -209,7 +212,7 @@ class BaseResponsesAPIConfig(ABC): api_base: str, litellm_params: GenericLiteLLMParams, headers: dict, - ) -> tuple[str, dict]: + ) -> tuple[str, dict[str, str]]: pass @abstractmethod @@ -268,6 +271,9 @@ class BaseResponsesAPIConfig(ABC): """Returns True if litellm should fake a stream for the given model and stream value""" return False + def may_answer_stream_with_json(self) -> bool: + return False + def supports_native_websocket(self) -> bool: """ Returns True if the provider has a native WebSocket endpoint for Responses API. diff --git a/litellm/llms/base_llm/sandbox/transformation.py b/litellm/llms/base_llm/sandbox/transformation.py index fe0e3abb87e..9b9b4e0a947 100644 --- a/litellm/llms/base_llm/sandbox/transformation.py +++ b/litellm/llms/base_llm/sandbox/transformation.py @@ -12,6 +12,7 @@ from typing import Final import httpx from pydantic import Field, PrivateAttr +from litellm.llms.custom_httpx.sse_lines import aiter_sse_lines from litellm.types.llms.base import LiteLLMPydanticObjectBase SANDBOX_MAX_OUTPUT_BYTES: Final = 10 * 1024 * 1024 @@ -99,7 +100,7 @@ class BaseSandboxConfig: async def _read_capped_lines(self, response: httpx.Response) -> list[str]: lines: Final[list[str]] = [] total = 0 - async for line in response.aiter_lines(): + async for line in aiter_sse_lines(response.aiter_text()): total += len(line.encode("utf-8")) if total > SANDBOX_MAX_OUTPUT_BYTES: raise ValueError( diff --git a/litellm/llms/bedrock/audio_transcription/__init__.py b/litellm/llms/bedrock/audio_transcription/__init__.py index 7f7a138398b..bc74e9c38ab 100644 --- a/litellm/llms/bedrock/audio_transcription/__init__.py +++ b/litellm/llms/bedrock/audio_transcription/__init__.py @@ -1,7 +1,11 @@ import base64 +import math +from collections.abc import Mapping +from dataclasses import dataclass from typing import Final import httpx +from pydantic import BaseModel, ConfigDict from litellm.litellm_core_utils.audio_utils.utils import process_audio_file from litellm.rust_bridge import runtime @@ -14,7 +18,72 @@ from litellm.rust_bridge.transcription.native import ( RustAtranscription, RustTranscription, ) -from litellm.types.utils import FileTypes, TranscriptionResponse +from litellm.secret_managers.main import get_secret_str +from litellm.types.utils import FileTypes, TranscriptionResponse, TranscriptionUsageTokensObject + +SUPPORTED_OPENAI_TRANSCRIPTION_PARAMS: Final = ("language", "prompt", "temperature", "response_format") +TEXT_RESPONSE_FORMATS: Final = frozenset({"json", "text"}) + + +def _as_float(value: object) -> float | None: + if isinstance(value, bool) or not isinstance(value, (int, float, str)): + return None + try: + number: Final = float(value) + except ValueError: + return None + return number if math.isfinite(number) else None + + +def _rejection(key: str, value: object) -> str | None: + if key not in SUPPORTED_OPENAI_TRANSCRIPTION_PARAMS: + return f"bedrock transcription does not support {key}." + if key == "response_format" and value not in TEXT_RESPONSE_FORMATS: + return f"bedrock transcription returns only the transcript text, so response_format={value!r} is not supported." + if key == "temperature" and _as_float(value) is None: + return f"bedrock transcription needs a number for temperature, got {value!r}." + return None + + +@dataclass(frozen=True, slots=True) +class UnsupportedTranscriptionParams: + message: str + + +def map_openai_transcription_params( + non_default_params: Mapping[str, object], drop_params: bool +) -> Mapping[str, object] | UnsupportedTranscriptionParams: + rejections: Final = { + key: reason for key, value in non_default_params.items() if (reason := _rejection(key, value)) is not None + } + if rejections and not drop_params: + return UnsupportedTranscriptionParams( + message=f"{' '.join(rejections.values())} To drop it from the call, set `litellm.drop_params = True`." + ) + return { + key: _as_float(value) if key == "temperature" else value + for key, value in non_default_params.items() + if key not in rejections + } + + +class _RustTranscriptionResult(BaseModel): + model_config = ConfigDict(frozen=True) + + text: str + usage: TranscriptionUsageTokensObject | None = None + + +def _transcription_response( + result: Mapping[str, object], optional_params: Mapping[str, object] +) -> TranscriptionResponse: + parsed: Final = _RustTranscriptionResult.model_validate(result) + response: Final = TranscriptionResponse(text=parsed.text).model_copy(update={"usage": parsed.usage}) + region_name: Final = ( + optional_params.get("aws_region_name") or get_secret_str("AWS_REGION_NAME") or get_secret_str("AWS_REGION") + ) + response.hidden_params = {**response.hidden_params, "region_name": region_name} + return response class BedrockAudioTranscriptionRustDispatch: @@ -64,7 +133,7 @@ class BedrockAudioTranscriptionRustDispatch: "timeout_seconds": timeout_to_seconds(timeout), } call: Final = NativeCall(args=(), kwargs=fields, base={}) - return TranscriptionResponse(**rust(call)) + return _transcription_response(rust(call), optional_params) return runtime.run( RouteContext(Route.TRANSCRIPTION, provider=custom_llm_provider, model=model), @@ -97,7 +166,7 @@ class BedrockAudioTranscriptionRustDispatch: "timeout_seconds": timeout_to_seconds(timeout), } call: Final = NativeCall(args=(), kwargs=fields, base={}) - return TranscriptionResponse(**await rust(call)) + return _transcription_response(await rust(call), optional_params) return await runtime.arun( RouteContext(Route.TRANSCRIPTION, provider=custom_llm_provider, model=model), diff --git a/litellm/llms/bedrock/chat/invoke_transformations/amazon_twelvelabs_pegasus_transformation.py b/litellm/llms/bedrock/chat/invoke_transformations/amazon_twelvelabs_pegasus_transformation.py index f7566ac4923..dc14ef005b5 100644 --- a/litellm/llms/bedrock/chat/invoke_transformations/amazon_twelvelabs_pegasus_transformation.py +++ b/litellm/llms/bedrock/chat/invoke_transformations/amazon_twelvelabs_pegasus_transformation.py @@ -10,6 +10,8 @@ import time from typing import TYPE_CHECKING, Any, Final import httpx +from pydantic import ConfigDict, TypeAdapter, with_config +from typing_extensions import NotRequired, ReadOnly, TypedDict import litellm from litellm._logging import verbose_logger @@ -34,6 +36,15 @@ else: LiteLLMLoggingObj = Any +@with_config(ConfigDict(extra="allow", strict=True)) +class _PegasusResponse(TypedDict): + message: ReadOnly[NotRequired[str | None]] + finishReason: ReadOnly[NotRequired[str | None]] + + +_PEGASUS_RESPONSE: Final = TypeAdapter(_PegasusResponse) + + class AmazonTwelveLabsPegasusConfig(AmazonInvokeConfig, BaseConfig): """ Handles transforming OpenAI-style requests into Bedrock InvokeModel requests for @@ -207,7 +218,7 @@ class AmazonTwelveLabsPegasusConfig(AmazonInvokeConfig, BaseConfig): ModelResponse with choices[0].message.content and finish_reason """ try: - completion_response: Final = raw_response.json() + completion_response: Final = _PEGASUS_RESPONSE.validate_python(raw_response.json()) except Exception as e: raise BedrockError( message=f"Error parsing response: {raw_response.text}, error: {e}", @@ -224,7 +235,7 @@ class AmazonTwelveLabsPegasusConfig(AmazonInvokeConfig, BaseConfig): message_content: Final = completion_response.get("message", "") # Extract finish reason and map to LiteLLM format - finish_reason_raw: Final = completion_response.get("finishReason", "stop") + finish_reason_raw: Final = completion_response.get("finishReason") or "stop" finish_reason: Final = map_finish_reason(finish_reason_raw) # Set the response content diff --git a/litellm/llms/bedrock/chat/invoke_transformations/base_invoke_transformation.py b/litellm/llms/bedrock/chat/invoke_transformations/base_invoke_transformation.py index 51b5a99272e..852179e8caa 100644 --- a/litellm/llms/bedrock/chat/invoke_transformations/base_invoke_transformation.py +++ b/litellm/llms/bedrock/chat/invoke_transformations/base_invoke_transformation.py @@ -1,11 +1,12 @@ import copy import json import time -from collections.abc import Mapping +from collections.abc import Mapping, Sequence from typing import TYPE_CHECKING, Any, Final, cast, get_args import httpx -from pydantic import TypeAdapter, ValidationError +from pydantic import ConfigDict, TypeAdapter, ValidationError, with_config +from typing_extensions import NotRequired, ReadOnly, TypedDict import litellm from litellm._logging import verbose_logger @@ -48,6 +49,27 @@ from litellm.llms.bedrock.base_aws_llm import BaseAWSLLM _GUARDRAIL_CONFIG_VALIDATOR: Final["TypeAdapter[GuardrailConfigBlock]"] = TypeAdapter(GuardrailConfigBlock) + +@with_config(ConfigDict(extra="allow", strict=True)) +class _CohereGeneration(TypedDict): + text: ReadOnly[str | None] + finish_reason: ReadOnly[str | None] + + +@with_config(ConfigDict(extra="allow", strict=True)) +class _CohereInvokeResponse(TypedDict): + text: NotRequired[ReadOnly[str | None]] + generations: NotRequired[ReadOnly[Sequence[_CohereGeneration]]] + + +@with_config(ConfigDict(extra="allow", strict=True)) +class _LlamaInvokeResponse(TypedDict): + generation: ReadOnly[str | None] + + +_COHERE_INVOKE_RESPONSE: Final = TypeAdapter(_CohereInvokeResponse) +_LLAMA_INVOKE_RESPONSE: Final = TypeAdapter(_LlamaInvokeResponse) + _GUARDRAIL_CONFIG_EXPECTED_FORMAT: Final = ( "{'guardrailIdentifier': str, 'guardrailVersion': str, 'trace': 'enabled'|'disabled'|'enabled_full'}" ) @@ -310,12 +332,13 @@ class AmazonInvokeConfig(BaseConfig, BaseAWSLLM): outputText: str | None = None try: if provider == "cohere": - if "text" in completion_response: - outputText = completion_response["text"] - elif "generations" in completion_response: - outputText = completion_response["generations"][0]["text"] + cohere_response: Final = _COHERE_INVOKE_RESPONSE.validate_python(completion_response) + if "text" in cohere_response: + outputText = cohere_response["text"] + elif "generations" in cohere_response: + outputText = cohere_response["generations"][0]["text"] model_response.choices[0].finish_reason = map_finish_reason( - completion_response["generations"][0]["finish_reason"] + cohere_response["generations"][0]["finish_reason"] or "stop" ) elif provider == "anthropic": return litellm.AmazonAnthropicClaudeConfig().transform_response( @@ -361,7 +384,7 @@ class AmazonInvokeConfig(BaseConfig, BaseAWSLLM): elif provider == "ai21": outputText = completion_response.get("completions")[0].get("data").get("text") elif provider == "meta" or provider == "llama" or provider == "deepseek_r1": - outputText = completion_response["generation"] + outputText = _LLAMA_INVOKE_RESPONSE.validate_python(completion_response)["generation"] elif provider == "mistral": outputText = litellm.AmazonMistralConfig.get_outputText(completion_response, model_response) else: # amazon titan diff --git a/litellm/llms/bedrock/chat/native_output_fallback.py b/litellm/llms/bedrock/chat/native_output_fallback.py index 1b8ce5fcda4..6892cd37beb 100644 --- a/litellm/llms/bedrock/chat/native_output_fallback.py +++ b/litellm/llms/bedrock/chat/native_output_fallback.py @@ -1,11 +1,14 @@ from collections.abc import Callable, Coroutine +from functools import partial from typing import Final, TypeAlias from litellm.llms.base_llm.chat.transformation import BaseLLMException from litellm.llms.bedrock.common_utils import ( NativeOutputFallback, is_bedrock_native_output_rejection, + is_bedrock_strict_tools_rejection, warn_bedrock_native_output_rejected, + warn_bedrock_strict_tools_dropped, ) from litellm.types.utils import ModelResponse from litellm.utils import CustomStreamWrapper @@ -14,12 +17,13 @@ NativeOutputResponse: TypeAlias = ModelResponse | CustomStreamWrapper NativeOutputAttemptResult: TypeAlias = NativeOutputResponse | Coroutine[object, object, NativeOutputResponse] NativeOutputAttempt: TypeAlias = Callable[[NativeOutputFallback | None], NativeOutputAttemptResult] NativeOutputFallbackFactory: TypeAlias = Callable[[], NativeOutputFallback | None] +_RetryFor: TypeAlias = Callable[[BaseLLMException], NativeOutputFallback | None] -def _fallback_for( - error: BaseLLMException, fallback: NativeOutputFallbackFactory, model: str +def _native_output_retry( + error: BaseLLMException, fallback: NativeOutputFallbackFactory | None, model: str ) -> NativeOutputFallback | None: - if not is_bedrock_native_output_rejection(error.status_code, error.message): + if fallback is None or not is_bedrock_native_output_rejection(error.status_code, error.message): return None retry: Final = fallback() if retry is not None: @@ -27,16 +31,38 @@ def _fallback_for( return retry +def _strict_tools_retry( + error: BaseLLMException, fallback: NativeOutputFallbackFactory | None, model: str +) -> NativeOutputFallback | None: + if fallback is None or not is_bedrock_strict_tools_rejection(error.status_code, error.message): + return None + retry: Final = fallback() + if retry is not None: + warn_bedrock_strict_tools_dropped(model) + return retry + + +def _fallback_for( + error: BaseLLMException, + fallback: NativeOutputFallbackFactory | None, + strict_tools_fallback: NativeOutputFallbackFactory | None, + model: str, +) -> NativeOutputFallback | None: + native_output_retry: Final = _native_output_retry(error, fallback, model) + if native_output_retry is not None: + return native_output_retry + return _strict_tools_retry(error, strict_tools_fallback, model) + + async def _await_with_native_output_fallback( first_attempt: Coroutine[object, object, NativeOutputResponse], attempt: NativeOutputAttempt, - fallback: NativeOutputFallbackFactory, - model: str, + retry_for: _RetryFor, ) -> NativeOutputResponse: try: return await first_attempt except BaseLLMException as error: - retry: Final = _fallback_for(error, fallback, model) + retry: Final = retry_for(error) if retry is None: raise second_attempt: Final = attempt(retry) @@ -47,16 +73,20 @@ def call_with_native_output_fallback( attempt: NativeOutputAttempt, fallback: NativeOutputFallbackFactory | None, model: str, + strict_tools_fallback: NativeOutputFallbackFactory | None = None, ) -> NativeOutputAttemptResult: - if fallback is None: + if fallback is None and strict_tools_fallback is None: return attempt(None) + retry_for: Final = partial( + _fallback_for, fallback=fallback, strict_tools_fallback=strict_tools_fallback, model=model + ) try: first_attempt: Final = attempt(None) except BaseLLMException as error: - retry: Final = _fallback_for(error, fallback, model) + retry: Final = retry_for(error) if retry is None: raise return attempt(retry) if isinstance(first_attempt, Coroutine): - return _await_with_native_output_fallback(first_attempt, attempt, fallback, model) + return _await_with_native_output_fallback(first_attempt, attempt, retry_for) return first_attempt diff --git a/litellm/llms/bedrock/common_utils.py b/litellm/llms/bedrock/common_utils.py index 28888f1a23a..dd721e059a9 100644 --- a/litellm/llms/bedrock/common_utils.py +++ b/litellm/llms/bedrock/common_utils.py @@ -15,7 +15,11 @@ from dataclasses import dataclass from types import MappingProxyType from typing import TYPE_CHECKING, Any, Final, Literal, TypeAlias -from typing_extensions import ReadOnly, TypedDict +from typing_extensions import ( + ReadOnly, + TypedDict, + TypeIs, # noqa: TID251 # narrows the caller's tools without copying them +) if TYPE_CHECKING: from botocore.eventstream import EventStreamMessage @@ -362,6 +366,60 @@ class NativeOutputFallback: litellm_params: Mapping[str, object] +_BEDROCK_STRICT_TOOLS_REJECTION: Final = re.compile( + r"Too many strict tools \(\d+\)" + r"|Schemas contains too many (?:optional parameters|parameters with union types)" + r"|[Cc]ompiled grammar (?:is too large|size)" + r"|tools\.\d+\.custom(?:\.strict)?: " + r"|Grammar compilation timed out" +) +_TOOLS_ADAPTER: Final = TypeAdapter(tuple[Mapping[str, object], ...]) +_TOOL_SPEC_ADAPTER: Final = TypeAdapter(Mapping[str, object]) + + +def is_bedrock_strict_tools_rejection(status_code: int, error_text: str) -> bool: + return status_code == 400 and _BEDROCK_STRICT_TOOLS_REJECTION.search(error_text) is not None + + +def warn_bedrock_strict_tools_dropped(model: str) -> None: + verbose_logger.warning( + "Bedrock rejected the strict tool schemas for model=%s, so litellm sent the request again without `strict` " + "because drop_params is set.", + model, + ) + + +def _without_strict(tool: Mapping[str, object]) -> Mapping[str, object]: + spec_key: Final = next((key for key in ("function", "toolSpec") if key in tool), None) + if spec_key is None: + return tool + spec: Final = _TOOL_SPEC_ADAPTER.validate_python(tool[spec_key]) + return {**tool, spec_key: {key: value for key, value in spec.items() if key != "strict"}} + + +def _sends_strict(tool: Mapping[str, object], supports_strict_tools: bool) -> bool: + if "toolSpec" in tool: + return "strict" in _TOOL_SPEC_ADAPTER.validate_python(tool["toolSpec"]) + if "function" not in tool: + return False + return supports_strict_tools and bool(_TOOL_SPEC_ADAPTER.validate_python(tool["function"]).get("strict")) + + +def bedrock_strict_tools_fallback( + model: str, optional_params: Mapping[str, object], litellm_params: Mapping[str, object] +) -> NativeOutputFallback | None: + tools: Final = _TOOLS_ADAPTER.validate_python(optional_params.get("tools", ())) + supports_strict_tools: Final = bedrock_converse_supports_strict_tools( + bedrock_capability_model(model, litellm_params.get("base_model")) + ) + if not any(_sends_strict(tool, supports_strict_tools) for tool in tools): + return None + return NativeOutputFallback( + optional_params={**optional_params, "tools": [_without_strict(tool) for tool in tools]}, + litellm_params=litellm_params, + ) + + def requests_output_config_format(optional_params: Mapping[str, object]) -> bool: match optional_params: case {"output_config": {"format": object()}}: @@ -519,6 +577,26 @@ def strip_unsupported_bedrock_invoke_output_config_keys( request_body["output_config"] = {"format": preserved_format} # rebind-ok: out-param +_TOOL_ITEMS_ADAPTER: Final = TypeAdapter(tuple[object, ...]) + + +def _is_str_keyed_dict( + value: object, +) -> TypeIs[dict[str, object]]: # guard-ok: JSON tool objects # mutable-ok: fallbacks reuse tools edited in place + return isinstance(value, dict) + + +def _normalize_custom_field_on_tool(tool: object) -> None: + if not _is_str_keyed_dict(tool): + return + custom: Final = tool.pop("custom", None) + if not _is_str_keyed_dict(custom) or "defer_loading" in tool: + return + deferred: Final = custom.get("defer_loading") + if isinstance(deferred, bool): + tool["defer_loading"] = deferred # rebind-ok: a fallback reuses the caller's tool, as on main + + def normalize_custom_field_on_tools(request_body: dict) -> None: """ Drop the ``custom`` field from each tool, first hoisting a boolean @@ -536,15 +614,8 @@ def normalize_custom_field_on_tools(request_body: dict) -> None: tools: Final = request_body.get("tools") if not tools or not isinstance(tools, list): return - for tool in tools: - if not isinstance(tool, dict): - continue - custom: dict[str, object] | None = tool.pop("custom", None) - if not isinstance(custom, dict) or "defer_loading" in tool: - continue - deferred: object = custom.get("defer_loading") - if isinstance(deferred, bool): - tool["defer_loading"] = deferred + for tool in _TOOL_ITEMS_ADAPTER.validate_python(tools): + _normalize_custom_field_on_tool(tool) _TOOL_DICTS_ADAPTER: Final = TypeAdapter(tuple[Mapping[str, object], ...]) diff --git a/litellm/llms/bedrock/count_tokens/bedrock_token_counter.py b/litellm/llms/bedrock/count_tokens/bedrock_token_counter.py index 21fbdb04896..26bc5904e06 100644 --- a/litellm/llms/bedrock/count_tokens/bedrock_token_counter.py +++ b/litellm/llms/bedrock/count_tokens/bedrock_token_counter.py @@ -10,6 +10,7 @@ from typing import Any, Final from pydantic import JsonValue from typing_extensions import assert_never +import litellm from litellm._logging import verbose_logger from litellm.llms.anthropic.chat.transformation import AnthropicConfig from litellm.llms.anthropic.count_tokens.transformation import ChatCountTranslationError, anthropic_count_fields @@ -53,6 +54,18 @@ class CountTokensFailure: CountTokensOutcome = CountedTokens | CountTokensFailure +def _claude_count_translator(litellm_params: Mapping[str, object]) -> AnthropicConfig: + deployment_model: Final = litellm_params.get("model") + if not isinstance(deployment_model, str): + return AnthropicConfig() + provider_hint: Final = litellm_params.get("custom_llm_provider") + model, provider, _, _ = litellm.get_llm_provider( + model=deployment_model, custom_llm_provider=provider_hint if isinstance(provider_hint, str) else None + ) + chat_config: Final = litellm.ProviderConfigManager.get_provider_chat_config(model, LlmProviders(provider)) + return chat_config if isinstance(chat_config, AnthropicConfig) else AnthropicConfig() + + def _runtime_rejected_claude_model(outcome: CountTokensOutcome, resolved_model: str) -> bool: return ( isinstance(outcome, CountTokensFailure) @@ -138,16 +151,22 @@ class BedrockTokenCounter(BaseTokenCounter): counted_model: Final = model_to_use.removeprefix("bedrock_mantle/") resolved_model: Final = get_bedrock_base_model(counted_model) primary_tokenizer: Final = MANTLE_TOKENIZER_TYPE if use_mantle else RUNTIME_TOKENIZER_TYPE + litellm_params: Final = (deployment or {}).get("litellm_params", {}) translated: Final = ( await anthropic_count_fields( - counted_model, messages, system, tools, messages_format, AnthropicConfig(), chat_params + counted_model, + messages, + system, + tools, + messages_format, + _claude_count_translator(litellm_params), + chat_params, ) if is_mantle_claude_model(resolved_model) else None ) if isinstance(translated, ChatCountTranslationError): return translated.response(request_model, model_to_use, primary_tokenizer) - litellm_params: Final = (deployment or {}).get("litellm_params", {}) runtime_request: Final = ( _request_data(model_to_use, messages, tools, system) if translated is None diff --git a/litellm/llms/bedrock/count_tokens/mantle_handler.py b/litellm/llms/bedrock/count_tokens/mantle_handler.py index 34e622b5e8d..5cd26235ba2 100644 --- a/litellm/llms/bedrock/count_tokens/mantle_handler.py +++ b/litellm/llms/bedrock/count_tokens/mantle_handler.py @@ -8,6 +8,7 @@ from typing_extensions import NotRequired, ReadOnly, TypedDict import litellm from litellm._logging import verbose_logger from litellm.litellm_core_utils.url_utils import join_api_base +from litellm.llms.anthropic.common_utils import tools_without_custom_field from litellm.llms.anthropic.count_tokens.transformation import COUNT_TOKEN_OPTION_NAMES, AnthropicCountTokensConfig from litellm.llms.bedrock.base_aws_llm import BaseAWSLLM, run_aws_signing from litellm.llms.bedrock.common_utils import BedrockError, build_mantle_messages_url @@ -26,6 +27,7 @@ class MantleCountTokensRequest(TypedDict): _COUNT_REQUEST: Final = TypeAdapter(MantleCountTokensRequest) _COUNT_RESPONSE: Final = TypeAdapter(dict[str, JsonValue]) _COUNT_OPTIONS: Final[TypeAdapter[Mapping[str, JsonValue]]] = TypeAdapter(Mapping[str, JsonValue]) +_TOOLS: Final = TypeAdapter(list[dict[str, JsonValue]]) class BedrockMantleCountTokensHandler(BaseAWSLLM): @@ -59,10 +61,15 @@ class BedrockMantleCountTokensHandler(BaseAWSLLM): self.get_aws_region_name, optional_params=litellm_params, model=resolved_model, model_id=None ) endpoint_url: Final = await run_aws_signing(self.get_mantle_count_tokens_endpoint, aws_region_name) + tools: Final = request.get("tools") body: Final = self._anthropic_config.transform_request_to_count_tokens( model=resolved_model, messages=request["messages"], - tools=request.get("tools"), + tools=None + if tools is None + else _TOOLS.validate_python( + tools_without_custom_field(tools, hoist_defer_loading=True, drop_custom=True) + ), system=request.get("system"), optional_params=_COUNT_OPTIONS.validate_python( {name: value for name, value in request_data.items() if name in COUNT_TOKEN_OPTION_NAMES} diff --git a/litellm/llms/bedrock/count_tokens/transformation.py b/litellm/llms/bedrock/count_tokens/transformation.py index a9f95c1f9b9..df5a3827c1f 100644 --- a/litellm/llms/bedrock/count_tokens/transformation.py +++ b/litellm/llms/bedrock/count_tokens/transformation.py @@ -12,6 +12,7 @@ from typing import Final, Literal from pydantic import JsonValue from litellm.litellm_core_utils.url_utils import join_api_base +from litellm.llms.anthropic.common_utils import tools_without_custom_field from litellm.llms.bedrock.base_aws_llm import BaseAWSLLM from litellm.llms.bedrock.common_utils import get_bedrock_base_model @@ -194,7 +195,15 @@ class BedrockCountTokensConfig(BaseAWSLLM): # For InvokeModel, we need to provide the raw body that would be sent to the model # Remove the 'model' field from the body as it's not part of the model input - body_data: Final = {k: v for k, v in request_data.items() if k != "model"} + tools: Final = request_data.get("tools") + body_data: Final = { + **{k: v for k, v in request_data.items() if k != "model"}, + **( + {"tools": tools_without_custom_field(tools, hoist_defer_loading=True, drop_custom=True)} + if isinstance(tools, list) + else {} + ), + } if "messages" in body_data: # Bedrock validates the body against the model's InvokeModel schema; @@ -206,6 +215,10 @@ class BedrockCountTokensConfig(BaseAWSLLM): encoded_body: Final = base64.b64encode(json.dumps(body_data).encode()).decode() return {"input": {"invokeModel": {"body": encoded_body}}} + @staticmethod + def count_tokens_model_id(model: str) -> str: + return get_bedrock_base_model(model).removeprefix("bedrock/") + def get_bedrock_count_tokens_endpoint( self, model: str, @@ -225,12 +238,7 @@ class BedrockCountTokensConfig(BaseAWSLLM): Returns: Complete endpoint URL for CountTokens API """ - # Use existing LiteLLM function to get the base model ID (removes region prefix) - model_id = get_bedrock_base_model(model) - - # Remove bedrock/ prefix if present - model_id = model_id.removeprefix("bedrock/") # Remove "bedrock/" prefix - encoded_model_id: Final = self.encode_model_id(model_id=model_id) + encoded_model_id: Final = self.encode_model_id(model_id=self.count_tokens_model_id(model)) base_url, _ = self.get_runtime_endpoint( api_base=api_base, diff --git a/litellm/llms/bedrock/files/transformation.py b/litellm/llms/bedrock/files/transformation.py index 8c4702bcf99..0624c2c65db 100644 --- a/litellm/llms/bedrock/files/transformation.py +++ b/litellm/llms/bedrock/files/transformation.py @@ -49,6 +49,7 @@ from litellm.llms.base_llm.files.transformation import ( BaseFilesConfig, LiteLLMLoggingObj, ) +from litellm.llms.custom_httpx.sse_lines import split_sse_lines from litellm.types.llms.base import LiteLLMBaseModel from litellm.types.llms.bedrock import AwsAuthParams, BedrockBatchRecordKind from litellm.types.llms.openai import ( @@ -400,7 +401,7 @@ def _batch_input_line(line_number: int, line: str) -> _BatchInputLine: def _non_blank_lines(file_content: str) -> Iterator[tuple[int, str]]: - numbered_lines: Final = enumerate(file_content.splitlines(), start=1) + numbered_lines: Final = enumerate(split_sse_lines(file_content), start=1) return ((line_number, line) for line_number, line in numbered_lines if line.strip()) diff --git a/litellm/llms/bedrock/messages/invoke_transformations/anthropic_claude_transformation.py b/litellm/llms/bedrock/messages/invoke_transformations/anthropic_claude_transformation.py index e66d087bbd0..e5d6a168d57 100644 --- a/litellm/llms/bedrock/messages/invoke_transformations/anthropic_claude_transformation.py +++ b/litellm/llms/bedrock/messages/invoke_transformations/anthropic_claude_transformation.py @@ -103,6 +103,9 @@ class AmazonAnthropicClaudeMessagesConfig( def should_strip_billing_metadata(self) -> bool: return True + def tools_for_upstream(self, tools: Sequence[object], model: str, drop_params: object) -> Sequence[object]: + return tools + def drops_dangerous_tool_use_beta_without_safeguards(self) -> bool: return True diff --git a/litellm/llms/bedrock/passthrough/guardrail_translation/handler.py b/litellm/llms/bedrock/passthrough/guardrail_translation/handler.py index 1b01b0ec6d0..3a65a8928bf 100644 --- a/litellm/llms/bedrock/passthrough/guardrail_translation/handler.py +++ b/litellm/llms/bedrock/passthrough/guardrail_translation/handler.py @@ -45,6 +45,7 @@ from litellm.llms.bedrock.passthrough.guardrail_translation.structured_edits imp structured_edits, tool_edits, ) +from litellm.llms.custom_httpx.sse_lines import split_sse_lines from litellm.proxy.guardrails.auto_router_compression import is_compression_guardrail from litellm.types.utils import GenericGuardrailAPIInputs @@ -947,7 +948,7 @@ def _invoke_frames(items: Sequence[object]) -> tuple[InvokeStreamFrame, ...]: def _sse_events(sse: bytes) -> tuple[Mapping[str, object], ...]: return tuple( _JSON_OBJECT.validate_python(json.loads(line[len("data:") :])) - for line in sse.decode().splitlines() + for line in split_sse_lines(sse.decode()) if line.startswith("data:") ) diff --git a/litellm/llms/bedrock/realtime/transformation.py b/litellm/llms/bedrock/realtime/transformation.py index 9cb38822881..952d8858f78 100644 --- a/litellm/llms/bedrock/realtime/transformation.py +++ b/litellm/llms/bedrock/realtime/transformation.py @@ -53,6 +53,7 @@ from litellm.types.realtime import ( RealtimeResponseTypedDict, ) +_JSON_OBJECT_MESSAGE: Final = TypeAdapter(dict[str, JsonValue], config=ConfigDict(strict=True)) _JSON_VALUE: Final = TypeAdapter(object) _JSON_OBJECT: Final = TypeAdapter(Mapping[str, object]) @@ -856,7 +857,7 @@ class BedrockRealtimeConfig(BaseRealtimeConfig): List of Bedrock format messages (JSON strings) """ try: - json_message: Final[dict[str, JsonValue]] = json.loads(message) + json_message: Final = _JSON_OBJECT_MESSAGE.validate_python(json.loads(message)) except json.JSONDecodeError: verbose_logger.warning("Invalid JSON message: %s", message[:200]) return [] diff --git a/litellm/llms/bedrock/search/transformation.py b/litellm/llms/bedrock/search/transformation.py index 565fc12aa1e..6f72cadad67 100644 --- a/litellm/llms/bedrock/search/transformation.py +++ b/litellm/llms/bedrock/search/transformation.py @@ -47,6 +47,7 @@ from litellm.llms.base_llm.search.transformation import ( ) from litellm.llms.bedrock.base_aws_llm import BaseAWSLLM from litellm.llms.bedrock.common_utils import BedrockError +from litellm.llms.custom_httpx.sse_lines import split_sse_lines from litellm.secret_managers.main import get_secret_str # AgentCore web-search rejects queries longer than 200 characters @@ -146,7 +147,9 @@ def _iter_sse_events(text: str) -> Iterator[Mapping[str, object]]: progress notifications before the JSON-RPC response. """ for chunk in _SSE_EVENT_SEPARATOR.split(text): - payload = "\n".join(line[len("data:") :].lstrip() for line in chunk.splitlines() if line.startswith("data:")) + payload = "\n".join( + line[len("data:") :].lstrip() for line in split_sse_lines(chunk) if line.startswith("data:") + ) if not payload: continue try: diff --git a/litellm/llms/bigmodel/__init__.py b/litellm/llms/bigmodel/__init__.py new file mode 100644 index 00000000000..e69de29bb2d diff --git a/litellm/llms/bigmodel/chat/__init__.py b/litellm/llms/bigmodel/chat/__init__.py new file mode 100644 index 00000000000..e69de29bb2d diff --git a/litellm/llms/bigmodel/chat/transformation.py b/litellm/llms/bigmodel/chat/transformation.py new file mode 100644 index 00000000000..12d5e912c15 --- /dev/null +++ b/litellm/llms/bigmodel/chat/transformation.py @@ -0,0 +1,59 @@ +from collections.abc import Mapping +from typing import Final + +from litellm.llms.zai.chat.transformation import ZAIChatConfig + +from ..common_utils import get_bigmodel_api_key, get_bigmodel_url, is_unsupported_disabled_thinking + +_SUPPORTED_PARAMS: Final = ( + "max_tokens", + "max_completion_tokens", + "stream", + "stream_options", + "temperature", + "top_p", + "stop", + "tools", + "tool_choice", + "response_format", + "thinking", + "reasoning_effort", +) + + +class BigModelChatConfig(ZAIChatConfig): + @property + def custom_llm_provider(self) -> str: + return "bigmodel" + + def get_openai_compatible_provider_info(self, api_base: str | None, api_key: str | None) -> tuple[str, str | None]: + return get_bigmodel_url(api_base, "chat"), get_bigmodel_api_key(api_key) + + def get_supported_openai_params(self, model: str) -> list[str]: # mutable-ok: inherited interface requires a list + return list(_SUPPORTED_PARAMS) + + def map_openai_params( + self, + non_default_params: Mapping[str, object], + optional_params: Mapping[str, object], + model: str, + drop_params: bool, + ) -> dict[str, object]: # mutable-ok: request pipeline adds parameters to the returned body + mapped: Final = { + **optional_params, + **{ + ("max_tokens" if key == "max_completion_tokens" else key): value + for key, value in non_default_params.items() + if key in _SUPPORTED_PARAMS and key != "thinking" + }, + } + if "thinking" not in non_default_params: + return mapped + thinking: Final = non_default_params["thinking"] + if is_unsupported_disabled_thinking(model, thinking): + return { + **mapped, + "reasoning_effort": mapped.get("reasoning_effort", "low"), + "extra_body": {"thinking": {"type": "enabled"}}, + } + return {**mapped, "extra_body": {"thinking": thinking}} diff --git a/litellm/llms/bigmodel/common_utils.py b/litellm/llms/bigmodel/common_utils.py new file mode 100644 index 00000000000..0c9b6da5c8f --- /dev/null +++ b/litellm/llms/bigmodel/common_utils.py @@ -0,0 +1,92 @@ +import re +from collections.abc import Mapping +from types import MappingProxyType +from typing import Final, Literal +from urllib.parse import urlsplit, urlunsplit + +import httpx +from pydantic import JsonValue, TypeAdapter, ValidationError + +import litellm +from litellm.exceptions import ContentPolicyViolationError, ContextWindowExceededError +from litellm.llms.base_llm.chat.transformation import BaseLLMException +from litellm.secret_managers.main import get_secret_str + +BIGMODEL_API_BASE: Final = "https://open.bigmodel.cn" +_JSON_OBJECT: Final = TypeAdapter(dict[str, JsonValue]) +_BUSINESS_CODE_IN_ERROR: Final = re.compile(r"""['"]code['"]\s*:\s*['"]?(\d{4})\b""") +_CODING_CHAT_PATH: Final = "/api/coding/paas/v4" +_API_PATHS: Final = ( + "/api/coding/paas/v4/chat/completions", + _CODING_CHAT_PATH, + "/api/paas/v4/chat/completions", + "/api/anthropic/v1/messages", + "/api/anthropic/v1", + "/api/v1/responses", + "/api/paas/v4", + "/api/anthropic", + "/api/v1", + "/api", +) +_ENDPOINT_PATHS: Final = MappingProxyType( + { + "chat": "/api/paas/v4", + "responses": "/api/v1/responses", + "messages": "/api/anthropic/v1/messages", + } +) + + +def get_bigmodel_api_key(api_key: str | None) -> str | None: + return api_key or get_secret_str("BIGMODEL_API_KEY") + + +def get_bigmodel_url(api_base: str | None, endpoint: Literal["chat", "responses", "messages"]) -> str: + resolved_base: Final = api_base or get_secret_str("BIGMODEL_API_BASE") or BIGMODEL_API_BASE + parsed: Final = urlsplit(resolved_base) + path: Final = parsed.path.rstrip("/") + suffix: Final = next((candidate for candidate in _API_PATHS if path.endswith(candidate)), "") + endpoint_path: Final = ( + _CODING_CHAT_PATH if endpoint == "chat" and suffix.startswith(_CODING_CHAT_PATH) else _ENDPOINT_PATHS[endpoint] + ) + return urlunsplit( + (parsed.scheme, parsed.netloc, f"{path.removesuffix(suffix)}{endpoint_path}", parsed.query, parsed.fragment) + ) + + +def bigmodel_json_body(response: httpx.Response) -> Mapping[str, JsonValue]: + try: + return _JSON_OBJECT.validate_json(response.content) + except ValidationError: + raise BaseLLMException(message=response.text, status_code=response.status_code, headers=response.headers) + + +def is_unsupported_disabled_thinking(model: str, thinking: object) -> bool: + return thinking == {"type": "disabled"} and litellm.utils.supports_factory( + model=model, custom_llm_provider="bigmodel", key="thinking_always_on" + ) + + +def bigmodel_business_error( + code: JsonValue, message: str, model: str, response: httpx.Response | None +) -> ContextWindowExceededError | ContentPolicyViolationError | None: + match code: + case 1261 | "1261": + return ContextWindowExceededError(message=message, model=model, llm_provider="bigmodel", response=response) + case 1301 | "1301": + return ContentPolicyViolationError(message=message, model=model, llm_provider="bigmodel", response=response) + case _: + return None + + +def raise_bigmodel_business_error(model: object, error_str: str, original_exception: object) -> None: + found: Final = _BUSINESS_CODE_IN_ERROR.search(error_str) + response: Final = getattr(original_exception, "response", None) + error: Final = bigmodel_business_error( + found.group(1) if found else None, + error_str, + str(model), + response if isinstance(response, httpx.Response) else None, + ) + if error is not None: + raise error diff --git a/litellm/llms/bigmodel/messages/__init__.py b/litellm/llms/bigmodel/messages/__init__.py new file mode 100644 index 00000000000..e69de29bb2d diff --git a/litellm/llms/bigmodel/messages/transformation.py b/litellm/llms/bigmodel/messages/transformation.py new file mode 100644 index 00000000000..82ce59631f1 --- /dev/null +++ b/litellm/llms/bigmodel/messages/transformation.py @@ -0,0 +1,206 @@ +import json +from collections.abc import AsyncIterator, Mapping, Sequence +from typing import Final + +import httpx +from openai._streaming import ServerSentEvent, SSEDecoder +from pydantic import JsonValue, TypeAdapter, ValidationError + +from litellm.exceptions import AuthenticationError +from litellm.litellm_core_utils.litellm_logging import Logging +from litellm.llms.openai_like.messages.transformation import ( + DEFAULT_ANTHROPIC_API_VERSION, + OpenAILikeAnthropicMessagesConfig, +) +from litellm.types.llms.anthropic_messages.anthropic_response import AnthropicMessagesResponse +from litellm.types.router import GenericLiteLLMParams + +from ..common_utils import ( + bigmodel_json_body, + get_bigmodel_api_key, + get_bigmodel_url, + is_unsupported_disabled_thinking, +) + +_JSON_OBJECT: Final = TypeAdapter(dict[str, JsonValue]) +_OUTPUT_CONFIG: Final = TypeAdapter(dict[str, object]) + + +def _with_lowest_effort_thinking( + params: Mapping[str, object], +) -> dict[str, object]: # mutable-ok: the parent transform takes a request dict + requested_output_config: Final = params.get("output_config") + output_config: Final = { + **({} if "reasoning_effort" in params else {"effort": "low"}), + **( + _OUTPUT_CONFIG.validate_python(requested_output_config) if isinstance(requested_output_config, dict) else {} + ), + } + return {**params, "thinking": {"type": "adaptive"}, **({"output_config": output_config} if output_config else {})} + + +def _normalize_message(body: Mapping[str, JsonValue]) -> dict[str, JsonValue]: # mutable-ok: native JSON response + usage: Final = body.get("usage") + if not isinstance(usage, dict): + return dict(body) + server_tools: Final = usage.get("server_tool_use") + if not isinstance(server_tools, dict) or "web_fetch_requests" in server_tools: + return dict(body) + normalized: Final[JsonValue] = { + **body, + "usage": {**usage, "server_tool_use": {"web_fetch_requests": 0, **server_tools}}, + } + return normalized + + +class _BigModelMessagesStream(httpx.AsyncByteStream): + def __init__(self, response: httpx.Response) -> None: + self._response = response + + async def __aiter__(self) -> AsyncIterator[bytes]: + async for event in SSEDecoder().aiter_bytes(self._response.aiter_bytes()): + yield _normalize_event(event) + + async def aclose(self) -> None: + await self._response.aclose() + + +def _json_object(data: str) -> Mapping[str, JsonValue] | None: + try: + return _JSON_OBJECT.validate_json(data) + except ValidationError: + return None + + +def _normalized_data(data: str) -> str: + body: Final = _json_object(data) + if body is None: + return data + message: Final = body.get("message") + normalized: Final[JsonValue] = ( + {**body, "message": _normalize_message(message)} + if body.get("type") == "message_start" and isinstance(message, dict) + else _normalize_message(body) + ) + return data if normalized == body else json.dumps(normalized, ensure_ascii=False) + + +def _normalize_event(event: ServerSentEvent) -> bytes: + metadata: Final = "".join( + f"{name}: {value}\n" + for name, value in (("event", event.event), ("id", event.id), ("retry", event.retry)) + if value is not None + ) + data_lines: Final = "".join(f"data: {line}\n" for line in _normalized_data(event.data).split("\n")) + return f"{metadata}{data_lines}\n".encode() + + +class BigModelMessagesConfig(OpenAILikeAnthropicMessagesConfig): + @property + def custom_llm_provider(self) -> str: + return "bigmodel" + + def is_native_messages_route(self) -> bool: + return True + + def should_strip_billing_metadata(self) -> bool: + return True + + def transform_anthropic_messages_request( + self, + model: str, + messages: list[dict[str, object]], # mutable-ok: matches dict-typed base signature + anthropic_messages_optional_request_params: dict[str, object], # mutable-ok: matches dict-typed base signature + litellm_params: GenericLiteLLMParams, + headers: dict[str, str], # mutable-ok: matches dict-typed base signature + ) -> dict[str, object]: # mutable-ok: matches dict-typed base signature + request_params: Final = ( + _with_lowest_effort_thinking(anthropic_messages_optional_request_params) + if is_unsupported_disabled_thinking(model, anthropic_messages_optional_request_params.get("thinking")) + else anthropic_messages_optional_request_params + ) + return super().transform_anthropic_messages_request( # pyright: ignore[reportUnknownMemberType, reportUnknownVariableType] # the parent transform returns a bare dict + model, messages, request_params, litellm_params, headers + ) + + def transform_anthropic_messages_response( + self, model: str, raw_response: httpx.Response, logging_obj: Logging + ) -> AnthropicMessagesResponse: + normalized: Final = httpx.Response( + raw_response.status_code, + json=_normalize_message(bigmodel_json_body(raw_response)), + request=raw_response.request, + ) + return super().transform_anthropic_messages_response(model, normalized, logging_obj) + + def get_async_streaming_response_iterator( + self, + model: str, + httpx_response: httpx.Response, + request_body: dict[str, object], # mutable-ok: inherited native stream API takes a request dict + litellm_logging_obj: Logging, + ) -> AsyncIterator[bytes]: + normalized: Final = httpx.Response( + httpx_response.status_code, + headers={ + key: value + for key, value in httpx_response.headers.items() + if key.lower() not in ("content-encoding", "content-length") + }, + stream=_BigModelMessagesStream(httpx_response), + request=httpx_response.request, + ) + return super().get_async_streaming_response_iterator( # pyright: ignore[reportUnknownMemberType, reportUnknownVariableType] # native parent yields bytes but its iterator annotation omits the element type + model, normalized, request_body, litellm_logging_obj + ) + + @staticmethod + def _translate_reasoning_effort_to_anthropic( + model: str, optional_params: Mapping[str, object], max_tokens: int | None, custom_llm_provider: str + ) -> None: + return None + + @staticmethod + def _translate_adaptive_effort_for_non_adaptive_model( + model: str, optional_params: Mapping[str, object], max_tokens: int | None, custom_llm_provider: str + ) -> None: + return None + + @staticmethod + def _drop_incompatible_temperature_for_thinking( + model: str, optional_params: Mapping[str, object], custom_llm_provider: str + ) -> None: + return None + + def validate_anthropic_messages_environment( + self, + headers: Mapping[str, str], + model: str, + messages: Sequence[object], + optional_params: Mapping[str, object], + litellm_params: Mapping[str, object], + api_key: str | None = None, + api_base: str | None = None, + ) -> tuple[dict[str, str], str | None]: # mutable-ok: HTTP handler merges forwarded headers + resolved_key: Final = get_bigmodel_api_key(api_key) + if resolved_key is None: + raise AuthenticationError( + message="Set BIGMODEL_API_KEY or pass api_key", llm_provider="bigmodel", model=model + ) + return { + **{key: value for key, value in headers.items() if key.lower() not in ("x-api-key", "authorization")}, + "x-api-key": resolved_key, + "anthropic-version": DEFAULT_ANTHROPIC_API_VERSION, + "content-type": "application/json", + }, api_base + + def get_complete_url( + self, + api_base: str | None, + api_key: str | None, + model: str, + optional_params: Mapping[str, object], + litellm_params: Mapping[str, object], + stream: bool | None = None, + ) -> str: + return get_bigmodel_url(api_base, "messages") diff --git a/litellm/llms/bigmodel/responses/__init__.py b/litellm/llms/bigmodel/responses/__init__.py new file mode 100644 index 00000000000..e69de29bb2d diff --git a/litellm/llms/bigmodel/responses/transformation.py b/litellm/llms/bigmodel/responses/transformation.py new file mode 100644 index 00000000000..80c53682d16 --- /dev/null +++ b/litellm/llms/bigmodel/responses/transformation.py @@ -0,0 +1,263 @@ +from collections.abc import Mapping +from types import MappingProxyType +from typing import Final + +import httpx +from pydantic import BaseModel, ConfigDict, JsonValue, TypeAdapter, ValidationError +from typing_extensions import Never + +from litellm.exceptions import AuthenticationError, UnsupportedParamsError +from litellm.litellm_core_utils.litellm_logging import Logging +from litellm.llms.base_llm.chat.transformation import BaseLLMException +from litellm.llms.openai.responses.transformation import OpenAIResponsesAPIConfig +from litellm.types.llms.openai import ( + ResponseInputParam, + ResponsesAPIOptionalRequestParams, + ResponsesAPIResponse, + ResponsesAPIStreamingResponse, +) +from litellm.types.router import GenericLiteLLMParams +from litellm.types.utils import LlmProviders + +from ..common_utils import bigmodel_business_error, bigmodel_json_body, get_bigmodel_api_key, get_bigmodel_url + +_JSON_OBJECT: Final = TypeAdapter(dict[str, JsonValue]) +_SUPPORTED_PARAMS: Final = ( + "input", + "model", + "instructions", + "stream", + "temperature", + "top_p", + "max_output_tokens", + "tools", + "tool_choice", + "parallel_tool_calls", + "include", + "reasoning", + "text", + "prompt_cache_key", + "previous_response_id", + "store", + "extra_headers", + "extra_query", + "extra_body", + "timeout", +) + + +_STATUS_BY_BUSINESS_CODE: Final = MappingProxyType( + { + **dict.fromkeys((1000, 1001, 1003, 1005), 401), + **dict.fromkeys((1210, 1211, 1212, 1213, 1214, 1215, 1221, 1222, 1261, 1301), 400), + 1220: 403, + **dict.fromkeys( + (1113, 1302, 1305, 1308, 1309, 1310, 1311, 1313, 1314, 1315, 1316, 1317, 1318, 1319, 1320, 1321), + 429, + ), + } +) + + +class _RequestedTools(BaseModel): + model_config = ConfigDict(frozen=True, extra="ignore") + + tools: JsonValue = None + tool_choice: JsonValue = None + parallel_tool_calls: JsonValue = None + + +def _requested_tools(logging_obj: Logging) -> _RequestedTools: + try: + return _RequestedTools.model_validate(logging_obj.model_call_details.get("optional_params") or {}) + except ValidationError: + return _RequestedTools() + + +def _envelope_status_code(code: JsonValue) -> int: + if not isinstance(code, int) or isinstance(code, bool): + return 500 + if 400 <= code <= 599: + return code + return _STATUS_BY_BUSINESS_CODE.get(code, 500) + + +def _normalize_output_item(item: JsonValue) -> JsonValue: + if not isinstance(item, dict) or item.get("type") not in ("message", "reasoning"): + return item + content: Final = item.get("content") + normalized: Final[JsonValue] = {"summary": [], **item} if item["type"] == "reasoning" else item + if not isinstance(content, dict): + return normalized + return {**normalized, "content": [content]} + + +def _normalize_response( + body: Mapping[str, JsonValue], + requested: _RequestedTools, +) -> dict[str, JsonValue]: # mutable-ok: JSON serialization boundary + usage: Final = body.get("usage") + output: Final = body.get("output") + tools: Final = body.get("tools") + tool_choice: Final = body.get("tool_choice") + parallel_tool_calls: Final = body.get("parallel_tool_calls") + input_tokens: Final = usage.get("input_tokens") if isinstance(usage, dict) else None + output_tokens: Final = usage.get("output_tokens") if isinstance(usage, dict) else None + normalized_usage: Final = ( + { + "total_tokens": input_tokens + output_tokens, + **usage, + } + if isinstance(usage, dict) and isinstance(input_tokens, int) and isinstance(output_tokens, int) + else usage + ) + normalized: Final[JsonValue] = { + **body, + "parallel_tool_calls": ( + requested.parallel_tool_calls is not False if parallel_tool_calls is None else parallel_tool_calls + ), + "tools": (requested.tools or []) if tools is None else tools, + "tool_choice": (requested.tool_choice or "auto") if tool_choice is None else tool_choice, + **({"usage": normalized_usage} if "usage" in body else {}), + **({"output": [_normalize_output_item(item) for item in output]} if isinstance(output, list) else {}), + } + return normalized + + +def _normalize_stream_part(part: JsonValue) -> JsonValue: + if not isinstance(part, dict): + return part + if part.get("type") == "output_text": + return { + "annotations": [], + "logprobs": None, + **part, + } + if part.get("type") == "reasoning_text": + return {"reasoning": part.get("text", ""), **part} + return part + + +class BigModelResponsesAPIConfig(OpenAIResponsesAPIConfig): + @property + def custom_llm_provider(self) -> LlmProviders: + return LlmProviders.BIGMODEL + + def supports_native_file_search(self) -> bool: + return False + + def supports_native_websocket(self) -> bool: + return False + + def should_fake_stream( + self, model: str | None, stream: bool | None, custom_llm_provider: str | None = None + ) -> bool: + return False + + def may_answer_stream_with_json(self) -> bool: + return True + + def get_supported_openai_params(self, model: str) -> list[str]: # mutable-ok: inherited API requires a list + return list(_SUPPORTED_PARAMS) + + def map_openai_params( + self, + response_api_optional_params: ResponsesAPIOptionalRequestParams, + model: str, + drop_params: bool, + ) -> dict[str, object]: # mutable-ok: request pipeline adds parameters to the returned body + return {key: value for key, value in response_api_optional_params.items() if key in _SUPPORTED_PARAMS} + + def validate_environment( + self, headers: Mapping[str, str], model: str, litellm_params: GenericLiteLLMParams | None + ) -> dict[str, str]: # mutable-ok: HTTP handler merges forwarded headers + resolved_key: Final = get_bigmodel_api_key(litellm_params.api_key if litellm_params else None) + if resolved_key is None: + raise AuthenticationError( + message="Set BIGMODEL_API_KEY or pass api_key", llm_provider="bigmodel", model=model + ) + return { + **headers, + "Authorization": f"Bearer {resolved_key}", + "Content-Type": "application/json", + } + + def get_complete_url(self, api_base: str | None, litellm_params: Mapping[str, object]) -> str: + return get_bigmodel_url(api_base, "responses") + + def transform_response_api_response( + self, model: str, raw_response: httpx.Response, logging_obj: Logging + ) -> ResponsesAPIResponse: + body: Final = bigmodel_json_body(raw_response) + if body.get("success") is False: + message: Final = str(body.get("msg") or raw_response.text) + raise bigmodel_business_error(body.get("code"), message, model, None) or BaseLLMException( + message=message, + status_code=_envelope_status_code(body.get("code")), + headers=raw_response.headers, + ) + normalized: Final = _normalize_response(body, _requested_tools(logging_obj)) + normalized_response: Final = httpx.Response( + status_code=raw_response.status_code, + headers={ + key: value + for key, value in raw_response.headers.items() + if key.lower() not in ("content-encoding", "content-length") + }, + json=normalized, + request=raw_response.request, + ) + return super().transform_response_api_response(model, normalized_response, logging_obj) + + def transform_get_response_api_response( + self, raw_response: httpx.Response, logging_obj: Logging + ) -> ResponsesAPIResponse: + return self.transform_response_api_response("", raw_response, logging_obj) + + def transform_streaming_response( + self, model: str, parsed_chunk: Mapping[str, object], logging_obj: Logging + ) -> ResponsesAPIStreamingResponse: + chunk: Final = _JSON_OBJECT.validate_python(parsed_chunk) + response: Final = chunk.get("response") + item: Final = chunk.get("item") + normalized: Final[JsonValue] = { + **chunk, + **( + {"response": _normalize_response(response, _requested_tools(logging_obj))} + if isinstance(response, dict) + else {} + ), + **({"item": _normalize_output_item(item)} if "item" in chunk else {}), + } + event_model: Final = self.get_event_model_class(str(normalized.get("type"))) + match chunk.get("type"): + case "response.output_text.done": + return event_model.model_validate({"logprobs": [], **normalized}) + case "response.content_part.done": + return event_model.model_validate({**normalized, "part": _normalize_stream_part(chunk.get("part"))}) + case "error": + error: Final = chunk.get("error") + error_fields: Final = error if isinstance(error, dict) else chunk + normalized_error: Final[JsonValue] = { + **normalized, + "error": {"type": "api_error", **error_fields, "code": error_fields.get("code") or "unknown_error"}, + } + return event_model.model_validate(normalized_error) + case _: + return event_model.model_validate(normalized) + + def transform_cancel_response_api_request( + self, response_id: str, api_base: str, litellm_params: GenericLiteLLMParams, headers: Mapping[str, str] + ) -> Never: + raise UnsupportedParamsError(message="BigModel does not support cancelling responses", status_code=400) + + def transform_compact_response_api_request( + self, + model: str, + input: str | ResponseInputParam, + response_api_optional_request_params: Mapping[str, object], + api_base: str, + litellm_params: GenericLiteLLMParams, + headers: Mapping[str, str], + ) -> Never: + raise UnsupportedParamsError(message="BigModel does not support compacting responses", status_code=400) diff --git a/litellm/llms/chatgpt/common_utils.py b/litellm/llms/chatgpt/common_utils.py index ec7fbfa92da..cd2ea6b9ccc 100644 --- a/litellm/llms/chatgpt/common_utils.py +++ b/litellm/llms/chatgpt/common_utils.py @@ -3,6 +3,7 @@ Constants and helpers for ChatGPT subscription OAuth. """ import base64 +import hashlib import json import os import platform @@ -17,6 +18,7 @@ import httpx from pydantic import JsonValue, TypeAdapter from litellm.litellm_core_utils.get_provider_specific_headers import ProviderSpecificHeaderUtils +from litellm.litellm_core_utils.provider_affinity import get_caller_litellm_session_id, get_requested_session_id from litellm.llms.base_llm.chat.transformation import BaseLLMException from litellm.types.utils import ProviderSpecificHeader @@ -395,22 +397,31 @@ def _normalize_litellm_params(litellm_params: object) -> Mapping[str, object]: return MappingProxyType({}) +def _prompt_cache_session_id(prompt_cache_key: object) -> str | None: + if not isinstance(prompt_cache_key, str) or not prompt_cache_key: + return None + return ( + prompt_cache_key + if _safe_header_value(prompt_cache_key.strip()) == prompt_cache_key + else hashlib.sha256(prompt_cache_key.encode("utf-8", "surrogatepass")).hexdigest() + ) + + def get_chatgpt_session_id(litellm_params: object) -> str | None: params: Final = _normalize_litellm_params(litellm_params) - for key in ("litellm_session_id", "session_id"): - value = params.get(key) - if value: - return str(value) - metadata: Final = _normalize_litellm_params(params.get("metadata")) - if metadata: - value = metadata.get("session_id") - if value: - return str(value) - for key in ("litellm_trace_id", "litellm_call_id"): - value = params.get(key) - if value: - return str(value) - return None + return ( + get_caller_litellm_session_id(params) + or get_requested_session_id(params) + or _prompt_cache_session_id(params.get("prompt_cache_key")) + or next( + ( + str(value) + for key in ("litellm_session_id", "litellm_trace_id", "litellm_call_id") + if (value := params.get(key)) + ), + None, + ) + ) def ensure_chatgpt_session_id(litellm_params: object) -> str: diff --git a/litellm/llms/chatgpt/responses/transformation.py b/litellm/llms/chatgpt/responses/transformation.py index 040b7b8c1d8..72b5cde21d1 100644 --- a/litellm/llms/chatgpt/responses/transformation.py +++ b/litellm/llms/chatgpt/responses/transformation.py @@ -11,6 +11,7 @@ from litellm.litellm_core_utils.llm_response_utils.convert_dict_to_response impo safe_convert_created_field, ) from litellm.litellm_core_utils.url_utils import join_api_base +from litellm.llms.custom_httpx.sse_lines import split_sse_lines from litellm.llms.openai.common_utils import OpenAIError from litellm.llms.openai.responses.transformation import OpenAIResponsesAPIConfig from litellm.responses.sse_output_recovery import ( @@ -199,7 +200,7 @@ class ChatGPTResponsesAPIConfig(OpenAIResponsesAPIConfig): error_message = None streamed_output_items: Final[dict[int, dict[str, object]]] = {} text_only_output_items: Final[dict[int, dict[str, object]]] = {} - for chunk in body_text.splitlines(): + for chunk in split_sse_lines(body_text): parsed_chunk = parse_sse_json_chunk(chunk) if parsed_chunk is None: continue diff --git a/litellm/llms/codestral/completion/handler.py b/litellm/llms/codestral/completion/handler.py index 6bebfe2d444..6b172e77295 100644 --- a/litellm/llms/codestral/completion/handler.py +++ b/litellm/llms/codestral/completion/handler.py @@ -20,6 +20,7 @@ from litellm.llms.custom_httpx.http_handler import ( AsyncHTTPHandler, get_async_httpx_client, ) +from litellm.llms.custom_httpx.sse_lines import aiter_sse_lines, iter_sse_lines from litellm.types.utils import TextChoices from litellm.utils import CustomStreamWrapper, TextCompletionResponse @@ -109,7 +110,7 @@ async def make_call( if response.status_code != 200: raise TextCompletionCodestralError(status_code=response.status_code, message=response.text) - completion_stream: Final = response.aiter_lines() + completion_stream: Final = aiter_sse_lines(response.aiter_text()) # LOGGING logging_obj.post_call( input=messages, @@ -339,13 +340,13 @@ class CodestralTextCompletion: response = litellm.module_level_client.post( completion_url, headers=headers, - data=json.dumps(data), + data=json.dumps({**data, "stream": True}), stream=stream, ) _response: Final = CustomStreamWrapper( - response.iter_lines(), + iter_sse_lines(response.iter_text()), model, - custom_llm_provider="codestral", + custom_llm_provider="text-completion-codestral", logging_obj=logging_obj, ) return _response diff --git a/litellm/llms/custom_httpx/aiohttp_handler.py b/litellm/llms/custom_httpx/aiohttp_handler.py index 447d7b685f7..e6544968d24 100644 --- a/litellm/llms/custom_httpx/aiohttp_handler.py +++ b/litellm/llms/custom_httpx/aiohttp_handler.py @@ -21,6 +21,7 @@ from litellm.llms.custom_httpx.http_handler import ( get_httpx_client, get_ssl_configuration, ) +from litellm.llms.custom_httpx.sse_lines import iter_sse_lines from litellm.types.llms.openai import FileTypes from litellm.types.utils import HttpHandlerRequestFields, ImageResponse, LlmProviders from litellm.utils import CustomStreamWrapper, ModelResponse, ProviderConfigManager @@ -466,7 +467,7 @@ class BaseLLMAIOHTTPHandler: ) else: completion_stream = provider_config.get_model_response_iterator( - streaming_response=response.iter_lines(), sync_stream=True + streaming_response=iter_sse_lines(response.iter_text()), sync_stream=True ) # LOGGING @@ -560,11 +561,8 @@ class BaseLLMAIOHTTPHandler: organization: str | None = None, headers: dict | None = None, ) -> ImageResponse: - if model is None: - raise ValueError("model is required for non-openai image variations") - provider_config: Final = ProviderConfigManager.get_provider_image_variation_config( - model=model, # openai defaults to dall-e-2 + model=model or "", provider=LlmProviders(custom_llm_provider), ) diff --git a/litellm/llms/custom_httpx/aiohttp_transport.py b/litellm/llms/custom_httpx/aiohttp_transport.py index 0e4d97fd770..9297e76624d 100644 --- a/litellm/llms/custom_httpx/aiohttp_transport.py +++ b/litellm/llms/custom_httpx/aiohttp_transport.py @@ -6,6 +6,7 @@ import ssl import sys import typing import urllib.request +import weakref from collections.abc import Callable, Generator from typing import ClassVar, Final @@ -109,6 +110,24 @@ def map_aiohttp_exceptions() -> Generator[None, None, None]: raise mapped_exc(message) from exc +def _release_transport_anchor(_transport: object) -> None: + """Release a transport anchored to a response stream. See ``_anchor_transport_to``.""" + + +def _anchor_transport_to(stream: "AiohttpResponseStream", transport: object) -> None: + """Keep the transport alive for as long as the stream can still read. + + The transport finalizer closes the session it owns, and nothing on the path from a + live response back to that session references the transport, so a client dropped + mid-stream would close the session under the body. ``weakref.finalize`` holds the + transport in its own registry rather than on the stream, which keeps the transport + out of the response's reference cycle (an exception carrying the response, for one) + so it is finalized by refcount once the anchor drops and can still schedule an async + close, instead of being collected in the same cyclic pass as the session it closes. + """ + weakref.finalize(stream, _release_transport_anchor, transport) + + class AiohttpResponseStream(httpx.AsyncByteStream): CHUNK_SIZE = 1024 * 16 @@ -463,10 +482,12 @@ class LiteLLMAiohttpTransport(AiohttpTransport): # Re-raise if it's a different RuntimeError raise + stream: Final = AiohttpResponseStream(response) + _anchor_transport_to(stream, self) return httpx.Response( status_code=response.status, headers=response.headers, - stream=AiohttpResponseStream(response), + stream=stream, request=request, ) diff --git a/litellm/llms/custom_httpx/http_handler.py b/litellm/llms/custom_httpx/http_handler.py index 0b64885df45..54adfb5c692 100644 --- a/litellm/llms/custom_httpx/http_handler.py +++ b/litellm/llms/custom_httpx/http_handler.py @@ -764,18 +764,23 @@ class AsyncHTTPHandler: follow_redirects: bool | None = None, timeout: float | httpx.Timeout | None = None, max_response_bytes: int | None = None, + stream: bool = False, ): # Set follow_redirects to UseClientDefault if None _follow_redirects: Final = follow_redirects if follow_redirects is not None else USE_CLIENT_DEFAULT + query: Final = httpx.QueryParams(params).merge(HTTPHandler.extract_query_params(url)) + request_headers: Final = httpx.Headers(headers) - params = params or {} - params.update(HTTPHandler.extract_query_params(url)) + if stream: + return await self._send_streaming_get( + url, params=query, headers=request_headers, follow_redirects=follow_redirects, timeout=timeout + ) if max_response_bytes is not None: return await self._get_with_response_limit( url, - params=httpx.QueryParams(params), - headers=httpx.Headers(headers), + params=query, + headers=request_headers, max_bytes=max_response_bytes, follow_redirects=self.client.follow_redirects if follow_redirects is None else follow_redirects, timeout=self.client.timeout if timeout is None else httpx.Timeout(timeout), @@ -783,13 +788,41 @@ class AsyncHTTPHandler: response: Final = await self.client.get( url, - params=params, - headers=headers, + params=query, + headers=request_headers, follow_redirects=_follow_redirects, timeout=timeout if timeout is not None else USE_CLIENT_DEFAULT, ) return response + async def _send_streaming_get( + self, + url: str, + *, + params: httpx.QueryParams, + headers: httpx.Headers, + follow_redirects: bool | None, + timeout: float | httpx.Timeout | None, + ) -> httpx.Response: + start_time: Final = time.time() + request: Final = self.client.build_request( + "GET", url, params=params, headers=headers, timeout=USE_CLIENT_DEFAULT if timeout is None else timeout + ) + try: + response: Final = await self.client.send( + request, + stream=True, + follow_redirects=USE_CLIENT_DEFAULT if follow_redirects is None else follow_redirects, + ) + _anchor_handler_to(response, self) + response.raise_for_status() + except httpx.TimeoutException as e: + _raise_timeout(e, start_time) + except httpx.HTTPStatusError as e: + await _raise_masked_async_error(e, True) + else: + return response + async def _get_with_response_limit( self, url: str, @@ -1468,15 +1501,20 @@ class HTTPHandler: headers: Mapping[str, Any] | None = None, follow_redirects: bool | None = None, timeout: float | httpx.Timeout | None = None, + stream: bool = False, ): # Set follow_redirects to UseClientDefault if None _follow_redirects: Final = follow_redirects if follow_redirects is not None else USE_CLIENT_DEFAULT - params = params or {} - params.update(self.extract_query_params(url)) + query: Final = httpx.QueryParams(params).merge(self.extract_query_params(url)) + + if stream: + return self._send_streaming_get( + url, params=query, headers=headers, follow_redirects=follow_redirects, timeout=timeout + ) response: Final = self.client.get( url, - params=params, + params=query, headers=headers, follow_redirects=_follow_redirects, timeout=timeout if timeout is not None else USE_CLIENT_DEFAULT, @@ -1484,6 +1522,34 @@ class HTTPHandler: return response + def _send_streaming_get( + self, + url: str, + *, + params: httpx.QueryParams, + headers: Mapping[str, str] | None, + follow_redirects: bool | None, + timeout: float | httpx.Timeout | None, + ) -> httpx.Response: + start_time: Final = time.time() + request: Final = self.client.build_request( + "GET", url, params=params, headers=headers, timeout=USE_CLIENT_DEFAULT if timeout is None else timeout + ) + try: + response: Final = self.client.send( + request, + stream=True, + follow_redirects=USE_CLIENT_DEFAULT if follow_redirects is None else follow_redirects, + ) + _anchor_handler_to(response, self) + response.raise_for_status() + except httpx.TimeoutException as e: + _raise_timeout(e, start_time) + except httpx.HTTPStatusError as e: + _raise_masked_sync_error(e, True) + else: + return response + @staticmethod def extract_query_params(url: str) -> dict[str, str]: """ diff --git a/litellm/llms/custom_httpx/llm_http_handler.py b/litellm/llms/custom_httpx/llm_http_handler.py index ef009e70137..9700465ebc3 100644 --- a/litellm/llms/custom_httpx/llm_http_handler.py +++ b/litellm/llms/custom_httpx/llm_http_handler.py @@ -6,6 +6,7 @@ import ssl from collections.abc import AsyncGenerator, AsyncIterator, Awaitable, Callable, Coroutine, Iterator, Mapping, Sequence from contextlib import asynccontextmanager from functools import lru_cache, partial, reduce +from itertools import chain from types import MappingProxyType from typing import ( TYPE_CHECKING, @@ -62,7 +63,7 @@ from litellm.litellm_core_utils.realtime_errors import ( ) from litellm.litellm_core_utils.realtime_streaming import RealTimeStreaming from litellm.litellm_core_utils.url_utils import encode_url_path_segment, join_api_base -from litellm.llms.anthropic.common_utils import AnthropicModelInfo +from litellm.llms.anthropic.common_utils import AnthropicModelInfo, merge_anthropic_beta_headers from litellm.llms.base_llm.anthropic_messages.transformation import ( BaseAnthropicMessagesConfig, ) @@ -117,6 +118,7 @@ from litellm.llms.custom_httpx.http_handler import ( get_httpx_client, header_value, ) +from litellm.llms.custom_httpx.sse_lines import aiter_sse_lines, iter_sse_lines from litellm.responses.streaming_iterator import ( BaseResponsesAPIStreamingIterator, MockResponsesAPIStreamingIterator, @@ -365,12 +367,37 @@ class _SignedBodyKwargs(TypedDict, total=False): json: ReadOnly[dict[str, object]] +def _is_sized_json_body(response: httpx.Response) -> bool: + headers: Final = httpx.Headers(response.headers) + media_types: Final = (value.split(";")[0].strip().lower() for value in headers.get_list("content-type")) + return "content-length" in headers and "application/json" in media_types + + +def _is_json_document(content: bytes) -> bool: + try: + return isinstance(json.loads(content), dict) + except ValueError: + return False + + def _signed_body_kwargs(*, signed_body: bytes | None, data: dict[str, object]) -> _SignedBodyKwargs: if signed_body is not None: return {"data": signed_body} return {"json": data} +def _answered_json(response: httpx.Response) -> bool: + return "application/json" in response.headers.get("content-type", "").lower() + + +def _stream_query_params(stream: bool, starting_after: int | None) -> Mapping[str, object]: + if not stream: + return {} + if starting_after is None: + return {"stream": "true"} + return {"stream": "true", "starting_after": starting_after} + + def _google_genai_streaming_hidden_params( *, api_base: str, @@ -572,6 +599,22 @@ def _unwrap_provider_error(error: Exception) -> Exception: return error +def _merge_messages_header_sources(*sources: Mapping[str, object] | None) -> Mapping[str, object]: + """Later sources win per header, except ``anthropic-beta``, which unions every source so client betas + never drop a deployment's configured ones.""" + entries: Final = tuple(chain.from_iterable((source or {}).items() for source in sources)) + beta_values: Final = tuple( + cast("str | Sequence[str]", value) # cast-ok: the merge helper skips non-str list entries + for name, value in entries + if name.lower() == "anthropic-beta" and isinstance(value, str | Sequence) + ) + merged_beta: Final = reduce(merge_anthropic_beta_headers, beta_values, "") + return MappingProxyType( + {name: value for name, value in entries if name.lower() != "anthropic-beta"} + | ({"anthropic-beta": merged_beta} if merged_beta else {}) + ) + + class BaseLLMHTTPHandler: async def _make_common_async_call( self, @@ -1069,7 +1112,7 @@ class BaseLLMHTTPHandler: completion_stream: object = MockResponseIterator(model_response=model_response, json_mode=json_mode) else: completion_stream = provider_config.get_model_response_iterator_for_request( - streaming_response=response.iter_lines(), + streaming_response=iter_sse_lines(response.iter_text()), sync_stream=True, json_mode=json_mode, optional_params=_OPTIONAL_PARAMS.validate_python(optional_params), @@ -1212,7 +1255,7 @@ class BaseLLMHTTPHandler: completion_stream: object = MockResponseIterator(model_response=model_response, json_mode=json_mode) else: completion_stream = provider_config.get_model_response_iterator_for_request( - streaming_response=response.aiter_lines(), + streaming_response=aiter_sse_lines(response.aiter_text()), sync_stream=False, json_mode=json_mode, optional_params=_OPTIONAL_PARAMS.validate_python(optional_params), @@ -2481,13 +2524,8 @@ class BaseLLMHTTPHandler: forwarded_headers: Final = kwargs.get("headers", None) # Also check for extra_headers in kwargs (from config or direct calls) extra_headers_from_kwargs: Final = kwargs.get("extra_headers", None) - # Merge all header sources: forwarded < extra_headers < provider_specific - merged_headers: Final[Mapping[str, object]] = MappingProxyType( - { - **(forwarded_headers or {}), - **(extra_headers_from_kwargs or {}), - **(provider_specific_headers or {}), - } + merged_headers: Final = _merge_messages_header_sources( + forwarded_headers, extra_headers_from_kwargs, provider_specific_headers ) request_params: Final = reduce( delete_nested_value, @@ -3012,6 +3050,17 @@ class BaseLLMHTTPHandler: }, ) + replay_as_stream: Final = partial( + MockResponsesAPIStreamingIterator, + model=model, + logging_obj=logging_obj, + responses_api_provider_config=responses_api_provider_config, + litellm_metadata=litellm_metadata, + custom_llm_provider=custom_llm_provider, + request_data=request_context, + call_type=CallTypes.responses.value, + ) + try: if is_stream_request: response = sync_httpx_client.post( @@ -3023,7 +3072,13 @@ class BaseLLMHTTPHandler: ) if caller_requested_stream: if fake_stream is True: - return MockResponsesAPIStreamingIterator( + return replay_as_stream(response=response) + if not ( + responses_api_provider_config.may_answer_stream_with_json() + and _is_sized_json_body(response) + and _is_json_document(response.read()) + ): + return SyncResponsesAPIStreamingIterator( response=response, model=model, logging_obj=logging_obj, @@ -3033,17 +3088,6 @@ class BaseLLMHTTPHandler: request_data=request_context, call_type=CallTypes.responses.value, ) - - return SyncResponsesAPIStreamingIterator( - response=response, - model=model, - logging_obj=logging_obj, - responses_api_provider_config=responses_api_provider_config, - litellm_metadata=litellm_metadata, - custom_llm_provider=custom_llm_provider, - request_data=request_context, - call_type=CallTypes.responses.value, - ) response.read() else: response = sync_httpx_client.post( @@ -3058,6 +3102,9 @@ class BaseLLMHTTPHandler: provider_config=responses_api_provider_config, ) + if is_stream_request and caller_requested_stream: + return replay_as_stream(response=response) + initial_response: Final = responses_api_provider_config.transform_response_api_response( model=model, raw_response=response, @@ -3213,6 +3260,17 @@ class BaseLLMHTTPHandler: }, ) + replay_as_stream: Final = partial( + MockResponsesAPIStreamingIterator, + model=model, + logging_obj=logging_obj, + responses_api_provider_config=responses_api_provider_config, + litellm_metadata=litellm_metadata, + custom_llm_provider=custom_llm_provider, + request_data=request_context, + call_type=CallTypes.responses.value, + ) + try: if is_stream_request: response = await async_httpx_client.post( @@ -3226,7 +3284,13 @@ class BaseLLMHTTPHandler: if caller_requested_stream: if fake_stream is True: - return MockResponsesAPIStreamingIterator( + return replay_as_stream(response=response) + if not ( + responses_api_provider_config.may_answer_stream_with_json() + and _is_sized_json_body(response) + and _is_json_document(await response.aread()) + ): + return ResponsesAPIStreamingIterator( response=response, model=model, logging_obj=logging_obj, @@ -3236,17 +3300,6 @@ class BaseLLMHTTPHandler: request_data=request_context, call_type=CallTypes.responses.value, ) - - return ResponsesAPIStreamingIterator( - response=response, - model=model, - logging_obj=logging_obj, - responses_api_provider_config=responses_api_provider_config, - litellm_metadata=litellm_metadata, - custom_llm_provider=custom_llm_provider, - request_data=request_context, - call_type=CallTypes.responses.value, - ) await response.aread() else: response = await async_httpx_client.post( @@ -3263,6 +3316,9 @@ class BaseLLMHTTPHandler: provider_config=responses_api_provider_config, ) + if is_stream_request and caller_requested_stream: + return replay_as_stream(response=response) + initial_response: Final = responses_api_provider_config.transform_response_api_response( model=model, raw_response=response, @@ -3480,12 +3536,20 @@ class BaseLLMHTTPHandler: logging_obj: LiteLLMLoggingObj, custom_llm_provider: str | None = None, extra_headers: dict[str, object] | None = None, + extra_query: Mapping[str, object] | None = None, extra_body: dict[str, object] | None = None, + stream: bool = False, + starting_after: int | None = None, + litellm_metadata: Mapping[str, object] = MappingProxyType({}), timeout: float | httpx.Timeout | None = None, client: HTTPHandler | AsyncHTTPHandler | None = None, _is_async: bool = False, shared_session: Optional["ClientSession"] = None, - ) -> ResponsesAPIResponse | Coroutine[object, object, ResponsesAPIResponse]: + ) -> ( + ResponsesAPIResponse + | SyncResponsesAPIStreamingIterator + | Coroutine[object, object, ResponsesAPIResponse | ResponsesAPIStreamingIterator] + ): """ Get a response by ID Uses GET /v1/responses/{response_id} endpoint in the responses API @@ -3498,7 +3562,11 @@ class BaseLLMHTTPHandler: logging_obj=logging_obj, custom_llm_provider=custom_llm_provider, extra_headers=extra_headers, + extra_query=extra_query, extra_body=extra_body, + stream=stream, + starting_after=starting_after, + litellm_metadata=litellm_metadata, timeout=timeout, client=client, shared_session=shared_session, @@ -3527,20 +3595,23 @@ class BaseLLMHTTPHandler: litellm_params=litellm_params, headers=headers, ) + query: Final = {**data, **(extra_query or {}), **_stream_query_params(stream, starting_after)} ## LOGGING logging_obj.pre_call( input="", api_key="", additional_args={ - "complete_input_dict": data, + "complete_input_dict": query, "api_base": api_base, "headers": headers, }, ) try: - response: Final = sync_httpx_client.get(url=url, headers=headers, params=data) + response: Final = sync_httpx_client.get( + url=url, headers=headers, params=query, stream=stream, timeout=timeout if stream else None + ) response.raise_for_status() except Exception as e: raise self._handle_error( @@ -3548,6 +3619,20 @@ class BaseLLMHTTPHandler: provider_config=responses_api_provider_config, ) + if stream and not _answered_json(response): + return SyncResponsesAPIStreamingIterator( + response=response, + model="", + logging_obj=logging_obj, + responses_api_provider_config=responses_api_provider_config, + litellm_metadata=dict(litellm_metadata), + custom_llm_provider=custom_llm_provider, + request_data={"litellm_params": dict(litellm_params)}, + replays_stored_stream=True, + ) + + if stream: + response.read() return responses_api_provider_config.transform_get_response_api_response( raw_response=response, logging_obj=logging_obj, @@ -3561,11 +3646,15 @@ class BaseLLMHTTPHandler: logging_obj: LiteLLMLoggingObj, custom_llm_provider: str | None = None, extra_headers: dict[str, object] | None = None, + extra_query: Mapping[str, object] | None = None, extra_body: dict[str, object] | None = None, + stream: bool = False, + starting_after: int | None = None, + litellm_metadata: Mapping[str, object] = MappingProxyType({}), timeout: float | httpx.Timeout | None = None, client: HTTPHandler | AsyncHTTPHandler | None = None, shared_session: Optional["ClientSession"] = None, - ) -> ResponsesAPIResponse: + ) -> ResponsesAPIResponse | ResponsesAPIStreamingIterator: """ Async version of get_responses """ @@ -3603,20 +3692,23 @@ class BaseLLMHTTPHandler: litellm_params=litellm_params, headers=headers, ) + query: Final = {**data, **(extra_query or {}), **_stream_query_params(stream, starting_after)} ## LOGGING logging_obj.pre_call( input="", api_key="", additional_args={ - "complete_input_dict": data, + "complete_input_dict": query, "api_base": api_base, "headers": headers, }, ) try: - response: Final = await async_httpx_client.get(url=url, headers=headers, params=data) + response: Final = await async_httpx_client.get( + url=url, headers=headers, params=query, stream=stream, timeout=timeout if stream else None + ) response.raise_for_status() except Exception as e: verbose_logger.debug("Error retrieving response: %s", e) @@ -3625,6 +3717,20 @@ class BaseLLMHTTPHandler: provider_config=responses_api_provider_config, ) + if stream and not _answered_json(response): + return ResponsesAPIStreamingIterator( + response=response, + model="", + logging_obj=logging_obj, + responses_api_provider_config=responses_api_provider_config, + litellm_metadata=dict(litellm_metadata), + custom_llm_provider=custom_llm_provider, + request_data={"litellm_params": dict(litellm_params)}, + replays_stored_stream=True, + ) + + if stream: + await response.aread() return responses_api_provider_config.transform_get_response_api_response( raw_response=response, logging_obj=logging_obj, diff --git a/litellm/llms/custom_httpx/sse_lines.py b/litellm/llms/custom_httpx/sse_lines.py new file mode 100644 index 00000000000..71ea7d621eb --- /dev/null +++ b/litellm/llms/custom_httpx/sse_lines.py @@ -0,0 +1,74 @@ +""" +Split a decoded Server-Sent Events body into lines the way the SSE spec does. + +httpx's `iter_lines()` / `aiter_lines()` follow `str.splitlines()`, which also breaks on U+0085, U+2028, +U+2029, \\x0b, \\x0c and \\x1c-\\x1e. JSON leaves U+0085, U+2028 and U+2029 unescaped inside strings, so a +`data:` line carrying one of them gets cut in half. SSE lines end only at CRLF, LF or CR +(https://html.spec.whatwg.org/multipage/server-sent-events.html#parsing-an-event-stream) +""" + +import io +import re +from collections.abc import AsyncIterable, AsyncIterator, Iterable, Iterator, Sequence +from typing import Final + +_SSE_LINE_BREAK: Final = re.compile(r"\r\n|\r|\n") +_SSE_LINE_WITH_BREAK: Final = re.compile(r"[^\r\n]*(?:\r\n|\r|\n)|[^\r\n]+") + + +def _split_lines(text: str) -> Sequence[str]: + if "\r" not in text: + return text.split("\n") + crlf_folded: Final = text.replace("\r\n", "\n") + if "\r" not in crlf_folded: + return crlf_folded.split("\n") + return _SSE_LINE_BREAK.split(text) + + +class _SSELineSplitter: + def __init__(self) -> None: + self._partial_line: io.StringIO = io.StringIO() + self._after_cr: bool = False + + def feed(self, text: str) -> tuple[str, ...]: + if not text: + return () + fresh: Final = text[1:] if self._after_cr and text.startswith("\n") else text + self._after_cr = fresh.endswith("\r") + *ended, tail = _split_lines(fresh) + if not ended: + _ = self._partial_line.write(tail) + return () + first: Final = self._partial_line.getvalue() + ended[0] + self._partial_line = io.StringIO() + _ = self._partial_line.write(tail) + return (first, *ended[1:]) + + def flush(self) -> tuple[str, ...]: + rest: Final = self._partial_line.getvalue() + self._partial_line = io.StringIO() + return (rest,) if rest else () + + +def iter_sse_lines(text_chunks: Iterable[str]) -> Iterator[str]: + splitter: Final = _SSELineSplitter() + for text in text_chunks: + yield from splitter.feed(text) + yield from splitter.flush() + + +def split_sse_lines(text: str) -> tuple[str, ...]: + return tuple(iter_sse_lines((text,))) + + +def split_sse_lines_keepends(text: str) -> tuple[str, ...]: + return tuple(_SSE_LINE_WITH_BREAK.findall(text)) + + +async def aiter_sse_lines(text_chunks: AsyncIterable[str]) -> AsyncIterator[str]: + splitter: Final = _SSELineSplitter() + async for text in text_chunks: + for line in splitter.feed(text): + yield line + for line in splitter.flush(): + yield line diff --git a/litellm/llms/dashscope/embed/transformation.py b/litellm/llms/dashscope/embed/transformation.py index d0c2b4dff0c..35132346261 100644 --- a/litellm/llms/dashscope/embed/transformation.py +++ b/litellm/llms/dashscope/embed/transformation.py @@ -14,6 +14,8 @@ Docs - https://help.aliyun.com/zh/model-studio/text-embedding-synchronous-api from typing import Final import httpx +from pydantic import ConfigDict, TypeAdapter, with_config +from typing_extensions import NotRequired, ReadOnly, TypedDict from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj from litellm.litellm_core_utils.url_utils import ensure_api_route @@ -28,6 +30,23 @@ from ..common_utils import DashScopeError DEFAULT_API_BASE: Final = "https://dashscope.aliyuncs.com/compatible-mode/v1" +@with_config(ConfigDict(extra="allow", strict=True)) +class _DashScopeUsage(TypedDict, total=False): + prompt_tokens: NotRequired[ReadOnly[int]] + total_tokens: NotRequired[ReadOnly[int]] + + +@with_config(ConfigDict(extra="allow", strict=True)) +class _DashScopeEmbeddingResponse(TypedDict, total=False): + data: NotRequired[ReadOnly[list[object]]] + model: NotRequired[ReadOnly[str | None]] + usage: NotRequired[ReadOnly[_DashScopeUsage | None]] + id: NotRequired[ReadOnly[object]] + + +_DASHSCOPE_EMBEDDING_RESPONSE: Final = TypeAdapter(_DashScopeEmbeddingResponse) + + class DashScopeEmbeddingConfig(BaseEmbeddingConfig): """ Reference: https://help.aliyun.com/zh/model-studio/text-embedding-synchronous-api @@ -152,11 +171,12 @@ class DashScopeEmbeddingConfig(BaseEmbeddingConfig): message=message, ) + parsed_response: Final = _DASHSCOPE_EMBEDDING_RESPONSE.validate_python(response_json) model_response.object = "list" - model_response.data = response_json.get("data", []) - model_response.model = response_json.get("model", model) + model_response.data = parsed_response.get("data", []) + model_response.model = parsed_response.get("model", model) - usage: Final = response_json.get("usage") or {} + usage: Final = parsed_response.get("usage") or {} prompt_tokens: Final = usage.get("prompt_tokens", 0) total_tokens: Final = usage.get("total_tokens", prompt_tokens) setattr( @@ -169,8 +189,8 @@ class DashScopeEmbeddingConfig(BaseEmbeddingConfig): ), ) - if "id" in response_json: - setattr(model_response, "id", response_json["id"]) + if "id" in parsed_response: + setattr(model_response, "id", parsed_response["id"]) return model_response diff --git a/litellm/llms/databricks/streaming_utils.py b/litellm/llms/databricks/streaming_utils.py index eca87f9dd5f..cc85012b803 100644 --- a/litellm/llms/databricks/streaming_utils.py +++ b/litellm/llms/databricks/streaming_utils.py @@ -1,6 +1,8 @@ import json from typing import Final +from pydantic import ConfigDict, TypeAdapter + import litellm from litellm import verbose_logger from litellm.types.llms.openai import ( @@ -23,6 +25,9 @@ def _usage_block(usage: Usage) -> ChatCompletionUsageBlock: ) +_JSON_CHUNK: Final = TypeAdapter(dict[str, object], config=ConfigDict(strict=True)) + + class ModelResponseIterator: def __init__(self, streaming_response, sync_stream: bool): self.streaming_response = streaming_response @@ -99,7 +104,7 @@ class ModelResponseIterator: self.response_iterator = self.streaming_response chunk: Final = self._next_sse_data() try: - json_chunk: Final = json.loads(chunk) + json_chunk: Final = _JSON_CHUNK.validate_python(json.loads(chunk)) return self.chunk_parser(chunk=json_chunk) except ValueError as e: verbose_logger.debug( @@ -126,7 +131,7 @@ class ModelResponseIterator: if chunk == "[DONE]": raise StopAsyncIteration try: - json_chunk: Final = json.loads(chunk) + json_chunk: Final = _JSON_CHUNK.validate_python(json.loads(chunk)) return self.chunk_parser(chunk=json_chunk) except ValueError as e: verbose_logger.debug( diff --git a/litellm/llms/fal_ai/image_edit/flux_lora_depth_transformation.py b/litellm/llms/fal_ai/image_edit/flux_lora_depth_transformation.py index 344d9d3c75b..6d0891295bd 100644 --- a/litellm/llms/fal_ai/image_edit/flux_lora_depth_transformation.py +++ b/litellm/llms/fal_ai/image_edit/flux_lora_depth_transformation.py @@ -4,13 +4,14 @@ from typing import Final from httpx._types import RequestFiles +from litellm.images.utils import image_to_data_url from litellm.litellm_core_utils.url_utils import join_api_base from litellm.secret_managers.main import get_secret_str from litellm.types.images.main import ImageEditOptionalRequestParams from litellm.types.router import GenericLiteLLMParams from litellm.types.utils import FileTypes -from .transformation import DEFAULT_BASE_URL, FalAIImageEditConfig, to_data_url +from .transformation import DEFAULT_BASE_URL, FalAIImageEditConfig FLUX_LORA_DEPTH_ENDPOINT: Final[str] = "fal-ai/flux-lora-depth" SUPPORTED_OPENAI_PARAMS: Final[tuple[str, ...]] = ("n", "size") @@ -68,7 +69,7 @@ class FalAIFluxLoraDepthEditConfig(FalAIImageEditConfig): ) request_body: Final[dict[str, object]] = { # mutable-ok: base class contract returns a dict "prompt": prompt, - "image_url": to_data_url(next(iter(images))), + "image_url": image_to_data_url(next(iter(images))), **provider_params, } return request_body, () diff --git a/litellm/llms/fal_ai/image_edit/transformation.py b/litellm/llms/fal_ai/image_edit/transformation.py index ea4e8cac5bf..5cbf635fd47 100644 --- a/litellm/llms/fal_ai/image_edit/transformation.py +++ b/litellm/llms/fal_ai/image_edit/transformation.py @@ -1,15 +1,12 @@ -import base64 -import os from collections.abc import Mapping -from pathlib import Path from types import MappingProxyType -from typing import TYPE_CHECKING, Final, Protocol, runtime_checkable +from typing import TYPE_CHECKING, Final import httpx from httpx._types import RequestFiles from pydantic import ConfigDict, TypeAdapter -from litellm.images.utils import ImageEditRequestUtils +from litellm.images.utils import image_to_data_url from litellm.llms.base_llm.image_edit.transformation import BaseImageEditConfig from litellm.llms.fal_ai.image_generation.gpt_image_2_transformation import ( map_gpt_image_quality, @@ -39,39 +36,6 @@ PARAM_TRANSLATION: Final[Mapping[str, str]] = MappingProxyType( ) -@runtime_checkable -class _SeekableBinaryReader(Protocol): - def tell(self) -> int: ... - - def seek(self, offset: int) -> int: ... - - def read(self) -> bytes: ... - - -def _read_image_bytes(image: object) -> bytes: - if isinstance(image, bytes): - return image - if isinstance(image, tuple): - return _read_image_bytes(image[1]) - if isinstance(image, os.PathLike): - return Path(image).read_bytes() - if isinstance(image, _SeekableBinaryReader): - position: Final = image.tell() - image.seek(0) - data: Final = image.read() - image.seek(position) - return data - raise ValueError(f"Unsupported image type for Fal AI image edit: {type(image).__name__}") - - -def to_data_url(image: object) -> str: - if isinstance(image, str): - return image - image_bytes: Final = _read_image_bytes(image) - mime_type: Final = ImageEditRequestUtils.get_image_content_type(image_bytes) - return f"data:{mime_type};base64,{base64.b64encode(image_bytes).decode('utf-8')}" - - def _first(value: object) -> object: return value[0] if isinstance(value, list) and value else value @@ -146,14 +110,14 @@ class FalAIImageEditConfig(BaseImageEditConfig): raise ValueError("Fal AI image edit requires at least one input image") mask: Final = _first(image_edit_optional_request_params.get("mask")) mask_field: Final[Mapping[str, str]] = ( - MappingProxyType({"mask_url": to_data_url(mask)}) if mask is not None else MappingProxyType({}) + MappingProxyType({"mask_url": image_to_data_url(mask)}) if mask is not None else MappingProxyType({}) ) provider_params: Final[Mapping[str, object]] = MappingProxyType( {key: value for key, value in image_edit_optional_request_params.items() if key != "mask"} ) request_body: Final[dict[str, object]] = { # mutable-ok: base class contract returns a dict "prompt": prompt, - "image_urls": tuple(to_data_url(img) for img in images), + "image_urls": tuple(image_to_data_url(img) for img in images), **mask_field, **provider_params, } diff --git a/litellm/llms/gemini/agents/transformation.py b/litellm/llms/gemini/agents/transformation.py index f7352da5fb6..45a6552a3fa 100644 --- a/litellm/llms/gemini/agents/transformation.py +++ b/litellm/llms/gemini/agents/transformation.py @@ -20,16 +20,13 @@ from litellm.litellm_core_utils.url_utils import join_api_base from litellm.llms.base_llm.agents.transformation import BaseAgentsAPIConfig from litellm.llms.gemini.common_utils import GeminiError, GeminiModelInfo from litellm.types.agents import ( + AgentCreateRequest, AgentCreateResponse, AgentDeleteResult, AgentListResponse, AgentVersionsResponse, ) -# Keys inside litellm_params that should be forwarded to the Gemini -# create-agent body verbatim. -_GEMINI_AGENT_BODY_KEYS: Final = ("base_agent", "instructions", "base_environment") - class _JsonResponse(Protocol): def json(self) -> object: ... @@ -39,30 +36,6 @@ def _json_body(response: _JsonResponse) -> object: return response.json() -# LiteLLM-internal keys that must never be forwarded to Gemini. -_LITELLM_INTERNAL_KEYS: Final = frozenset( - { - "custom_llm_provider", - "api_key", - "api_base", - "make_public", - "cost_per_query", - "input_cost_per_token", - "output_cost_per_token", - "require_trace_id_on_calls_to_agent", - "require_trace_id_on_calls_by_agent", - "max_iterations", - "max_budget_per_session", - "guardrails", - "is_public", - "agent_name", - "agent_id", - "agent_card_params", - "provider_agent_response", - } -) - - class GeminiAgentsConfig(BaseAgentsAPIConfig): """ Configuration for the Google AI Studio (Gemini) native Agents API. @@ -143,14 +116,9 @@ class GeminiAgentsConfig(BaseAgentsAPIConfig): def transform_create_request( self, - name: str, - litellm_params: Mapping[str, object], - ) -> dict[str, object]: - body: Final[dict[str, object]] = {"name": name} - for key in _GEMINI_AGENT_BODY_KEYS: - value = litellm_params.get(key) - if value is not None: - body[key] = value + create_request: AgentCreateRequest, + ) -> Mapping[str, object]: + body: Final[Mapping[str, object]] = create_request.model_dump(mode="json", exclude_none=True) verbose_logger.debug("GeminiAgentsConfig create body: %s", body) return body diff --git a/litellm/llms/gemini/common_utils.py b/litellm/llms/gemini/common_utils.py index 9634c580858..88c6494e3f7 100644 --- a/litellm/llms/gemini/common_utils.py +++ b/litellm/llms/gemini/common_utils.py @@ -18,6 +18,25 @@ from litellm.secret_managers.main import get_secret_str from litellm.types.llms.openai import AllMessageValues from litellm.types.utils import CountContextManagement, TokenCountMessagesFormat, TokenCountResponse +# 2.5 Flash has no configurable imageSize and supports ten aspect ratios, excluding these four +# https://docs.cloud.google.com/gemini-enterprise-agent-platform/models/gemini/2-5-flash-image +_GEMINI_2_5_FLASH_MODEL_FAMILY: Final = "2.5-flash" +_GEMINI_2_5_FLASH_UNSUPPORTED_ASPECT_RATIOS: Final = frozenset(("1:4", "4:1", "1:8", "8:1")) + +# 3.1 Flash supports the 512 tier, while other Gemini image models start at 1K +# https://docs.cloud.google.com/gemini-enterprise-agent-platform/models/gemini/3-1-flash-image +_GEMINI_512_IMAGE_SIZE_MODEL: Final = "gemini-3.1-flash-image" + +# Flash Lite supports only 1K, even when the requested dimensions are larger +# https://docs.cloud.google.com/gemini-enterprise-agent-platform/models/gemini/3-1-flash-lite-image +_GEMINI_1K_ONLY_IMAGE_SIZE_MODEL: Final = "gemini-3.1-flash-lite-image" + +# LiteLLM chooses the nearest resolution tier using the side length of a square with the same total number of pixels +# as the requested image +_GEMINI_IMAGE_SIZE_1K_THRESHOLD: Final = (512 + 1024) // 2 +_GEMINI_IMAGE_SIZE_2K_THRESHOLD: Final = (1024 + 2048) // 2 +_GEMINI_IMAGE_SIZE_4K_THRESHOLD: Final = (2048 + 4096) // 2 + GEMINI_IMAGE_ASPECT_RATIOS: Final[dict[str, float]] = { "1:1": 1 / 1, "1:4": 1 / 4, @@ -105,8 +124,8 @@ def map_openai_size_to_gemini_image_config(size: str, model: str) -> dict[str, s return None width, height = dimensions - image_config: Final = {"aspectRatio": _map_dimensions_to_gemini_aspect_ratio(width, height)} - image_size: Final = _map_dimensions_to_gemini_image_size(width, height) + image_config: Final = {"aspectRatio": _map_dimensions_to_gemini_aspect_ratio(width, height, model)} + image_size: Final = _map_dimensions_to_gemini_image_size(width, height, model) if is_gemini_image_model(model): if supports_gemini_image_size(model): image_config["imageSize"] = image_size @@ -123,7 +142,7 @@ def supports_gemini_image_size(model: str) -> bool: return bool(value) except Exception: pass - return "2.5-flash" not in model + return _GEMINI_2_5_FLASH_MODEL_FAMILY not in model def is_gemini_image_model(model: str) -> bool: @@ -333,24 +352,36 @@ def _parse_openai_image_size(size: str) -> tuple[int, int] | None: return width, height -def _map_dimensions_to_gemini_aspect_ratio(width: int, height: int) -> str: - if (width, height) in GEMINI_IMAGE_SIZE_TO_ASPECT_RATIO: - return GEMINI_IMAGE_SIZE_TO_ASPECT_RATIO[(width, height)] +def _map_dimensions_to_gemini_aspect_ratio(width: int, height: int, model: str) -> str: + aspect_ratios: Final = tuple( + ratio + for ratio in GEMINI_IMAGE_ASPECT_RATIOS + if _GEMINI_2_5_FLASH_MODEL_FAMILY not in model or ratio not in _GEMINI_2_5_FLASH_UNSUPPORTED_ASPECT_RATIOS + ) + known_ratio: Final = GEMINI_IMAGE_SIZE_TO_ASPECT_RATIO.get((width, height)) + if known_ratio is not None and known_ratio in aspect_ratios: + return known_ratio requested_ratio: Final = width / height return min( - GEMINI_IMAGE_ASPECT_RATIOS, + aspect_ratios, key=lambda aspect_ratio: abs(math.log(GEMINI_IMAGE_ASPECT_RATIOS[aspect_ratio] / requested_ratio)), ) -def _map_dimensions_to_gemini_image_size(width: int, height: int) -> str: - effective_square_side: Final = math.sqrt(width * height) - if effective_square_side < 768: - return "512" - if effective_square_side < 1536: +def _map_dimensions_to_gemini_image_size(width: int, height: int, model: str) -> str: + if _GEMINI_1K_ONLY_IMAGE_SIZE_MODEL in model: return "1K" - if effective_square_side < 3072: + + effective_square_side: Final = math.sqrt(width * height) + if effective_square_side < _GEMINI_IMAGE_SIZE_1K_THRESHOLD: + if is_gemini_image_model(model) and _GEMINI_512_IMAGE_SIZE_MODEL not in model: + return "1K" + else: + return "512" + if effective_square_side < _GEMINI_IMAGE_SIZE_2K_THRESHOLD: + return "1K" + if effective_square_side < _GEMINI_IMAGE_SIZE_4K_THRESHOLD: return "2K" return "4K" diff --git a/litellm/llms/gemini/google_genai/guardrail_translation/handler.py b/litellm/llms/gemini/google_genai/guardrail_translation/handler.py index 34007bc8fd4..b6b2aa6c28f 100644 --- a/litellm/llms/gemini/google_genai/guardrail_translation/handler.py +++ b/litellm/llms/gemini/google_genai/guardrail_translation/handler.py @@ -23,6 +23,7 @@ from litellm.llms.base_llm.guardrail_translation.base_translation import ( BaseTranslation, StreamTransformSink, ) +from litellm.llms.custom_httpx.sse_lines import split_sse_lines from litellm.types.utils import GenericGuardrailAPIInputs if TYPE_CHECKING: @@ -121,7 +122,7 @@ def _parse_json_dict_or_none(payload: str) -> Mapping[str, object] | None: def _sse_payload_texts(sse_text: str) -> tuple[str, ...]: return tuple( text - for line in sse_text.splitlines() + for line in split_sse_lines(sse_text) if line.startswith("data:") for payload in (line[len("data:") :].strip(),) if payload and payload != "[DONE]" diff --git a/litellm/llms/gemini/interactions/transformation.py b/litellm/llms/gemini/interactions/transformation.py index 6f3e9a56b92..1895a97af7d 100644 --- a/litellm/llms/gemini/interactions/transformation.py +++ b/litellm/llms/gemini/interactions/transformation.py @@ -15,7 +15,7 @@ import httpx from typing_extensions import ReadOnly, TypedDict from litellm._logging import verbose_logger -from litellm.litellm_core_utils.core_helpers import process_response_headers +from litellm.litellm_core_utils.core_helpers import drops_unsupported_params, process_response_headers from litellm.litellm_core_utils.url_utils import encode_url_path_segment, join_api_base from litellm.llms.base_llm.interactions.transformation import BaseInteractionsAPIConfig from litellm.llms.gemini.common_utils import GeminiError, GeminiModelInfo @@ -41,6 +41,14 @@ else: _JsonObject: TypeAlias = dict[str, object] +def _has_agent_config_type(agent_config: object) -> bool: + match agent_config: + case {"type": str()}: + return True + case _: + return False + + class _InteractionPayload(TypedDict, total=False): """JSON body of an Interactions API interaction, keyed as ``InteractionsAPIResponse`` fields.""" @@ -105,6 +113,7 @@ class GoogleAIStudioInteractionsConfig(BaseInteractionsAPIConfig): return [ "model", "agent", + "agent_config", "input", "tools", "system_instruction", @@ -188,6 +197,7 @@ class GoogleAIStudioInteractionsConfig(BaseInteractionsAPIConfig): request_body["input"] = input optional_keys: Final = [ + "agent_config", "tools", "system_instruction", "stream", @@ -197,8 +207,14 @@ class GoogleAIStudioInteractionsConfig(BaseInteractionsAPIConfig): "response_modalities", "previous_interaction_id", ] + dropped_keys: Final = ( + frozenset({"agent_config"}) + if drops_unsupported_params(litellm_params.get("drop_params")) + and (model or not _has_agent_config_type(optional_params.get("agent_config"))) + else frozenset() + ) for key in optional_keys: - if optional_params.get(key) is not None: + if key not in dropped_keys and optional_params.get(key) is not None: request_body[key] = optional_params[key] # response_mime_type is removed — fold it into response_format. diff --git a/litellm/llms/gigachat/authenticator.py b/litellm/llms/gigachat/authenticator.py index d43e203d7a1..f37c6e88896 100644 --- a/litellm/llms/gigachat/authenticator.py +++ b/litellm/llms/gigachat/authenticator.py @@ -12,6 +12,8 @@ from types import MappingProxyType from typing import Final import httpx +from pydantic import ConfigDict, TypeAdapter, with_config +from typing_extensions import NotRequired, ReadOnly, TypedDict from litellm._logging import verbose_logger from litellm.caching.caching import InMemoryCache @@ -37,6 +39,17 @@ _token_cache: Final = InMemoryCache() _NO_LITELLM_PARAMS: Final[Mapping[str, object]] = MappingProxyType({}) +@with_config(ConfigDict(extra="allow", strict=True)) +class _GigaChatTokenResponse(TypedDict): + tok: NotRequired[ReadOnly[str | None]] + access_token: NotRequired[ReadOnly[str | None]] + exp: NotRequired[ReadOnly[int | float | str | None]] + expires_at: NotRequired[ReadOnly[int | float | str | None]] + + +_TOKEN_RESPONSE: Final = TypeAdapter(_GigaChatTokenResponse) + + class GigaChatAuthError(BaseLLMException): """GigaChat authentication error.""" @@ -230,7 +243,7 @@ async def _request_token_async( def _parse_token_response(response: httpx.Response) -> tuple[str, int]: """Parse OAuth token response.""" - data: Final = response.json() + data: Final = _TOKEN_RESPONSE.validate_python(response.json()) # GigaChat returns either 'tok'/'exp' or 'access_token'/'expires_at' access_token: Final = data.get("tok") or data.get("access_token") diff --git a/litellm/llms/github_copilot/authenticator.py b/litellm/llms/github_copilot/authenticator.py index 59e1804f453..ee0e7af7e9b 100644 --- a/litellm/llms/github_copilot/authenticator.py +++ b/litellm/llms/github_copilot/authenticator.py @@ -1,11 +1,12 @@ import json import os import time +from dataclasses import dataclass from datetime import datetime -from typing import Any, Final +from typing import Any, Final, TypeVar import httpx -from pydantic import ConfigDict, TypeAdapter, with_config +from pydantic import BaseModel, ConfigDict, TypeAdapter, with_config from typing_extensions import NotRequired, ReadOnly, TypedDict from litellm._logging import verbose_logger @@ -13,7 +14,6 @@ from litellm.litellm_core_utils.asyncify import can_block_current_thread from litellm.llms.custom_httpx.http_handler import get_httpx_client from .common_utils import ( - APIKeyExpiredError, GetAccessTokenError, GetAPIKeyError, GetDeviceCodeError, @@ -27,6 +27,44 @@ DEFAULT_GITHUB_ACCESS_TOKEN_URL: Final = "https://github.com/login/oauth/access_ DEFAULT_GITHUB_API_KEY_URL: Final = "https://api.github.com/copilot_internal/v2/token" +class CopilotEndpoints(BaseModel): + model_config = ConfigDict(frozen=True, strict=True, extra="ignore", hide_input_in_errors=True) + + api: str | None = None + + +class CopilotCachedKey(BaseModel): + model_config = ConfigDict(frozen=True, strict=True, extra="ignore", hide_input_in_errors=True) + + token: str + expires_at: float + endpoints: CopilotEndpoints | None = None + + +class CopilotCachedEndpoints(BaseModel): + model_config = ConfigDict(frozen=True, strict=True, extra="ignore", hide_input_in_errors=True) + + endpoints: CopilotEndpoints | None = None + + +ApiKeyFileView = TypeVar("ApiKeyFileView", CopilotCachedKey, CopilotCachedEndpoints) + + +@dataclass(frozen=True, slots=True) +class _UnsavedApiKey: + access_token: str + key: CopilotCachedKey + + +_UNSAVED_API_KEYS: Final[dict[str, _UnsavedApiKey]] = {} # mutable-ok: refreshed keys api-key.json could not hold + + +def _read_token_file(path: str) -> str: + with open(path, "rb") as f: + raw: Final = f.read() + return raw.decode(json.detect_encoding(raw)) + + @with_config(ConfigDict(extra="allow", strict=True)) class _DeviceCode(TypedDict): device_code: ReadOnly[str] @@ -87,12 +125,13 @@ class Authenticator: GetAccessTokenError: If unable to obtain an access token after retries. """ try: - with open(self.access_token_file, "r") as f: - access_token = f.read().strip() - if access_token: - return access_token + saved_token: Final = _read_token_file(self.access_token_file).strip() + if saved_token: + return saved_token except OSError: verbose_logger.warning("No existing access token found or error reading file") + except ValueError as e: + verbose_logger.warning("Ignoring %s, not a text access token: %s", self.access_token_file, e) if not can_block_current_thread(): raise GetAccessTokenError( @@ -135,64 +174,83 @@ class Authenticator: Raises: GetAPIKeyError: If unable to obtain an API key. """ - try: - with open(self.api_key_file, "r") as f: - api_key_info = json.load(f) - if api_key_info.get("expires_at", 0) > datetime.now().timestamp(): - return api_key_info.get("token") - else: - verbose_logger.warning("API key expired, refreshing") - raise APIKeyExpiredError( - message="API key expired", - status_code=401, - ) - except OSError: - verbose_logger.warning("No API key file found or error opening file") - except (json.JSONDecodeError, KeyError) as e: - verbose_logger.warning("Error reading API key from file: %s", e) - except APIKeyExpiredError: - pass # Already logged in the try block + unsaved: Final = self._unsaved_api_key() + if unsaved is not None: + return unsaved.token + cached: Final = self._read_api_key_file(CopilotCachedKey) + if cached is not None and cached.expires_at > datetime.now().timestamp(): + return cached.token + if cached is not None: + verbose_logger.warning("API key expired, refreshing") try: - api_key_info = self._refresh_api_key() - with open(self.api_key_file, "w") as f: - json.dump(api_key_info, f) - token: Final = api_key_info.get("token") - if token: - return token - else: - raise GetAPIKeyError( - message="API key response missing token", - status_code=401, - ) - except OSError as e: - verbose_logger.error("Error saving API key to file: %s", e) - raise GetAPIKeyError( - message=f"Failed to save API key: {e}", - status_code=500, - ) + api_key_info: Final = self._refresh_api_key() except RefreshAPIKeyError as e: raise GetAPIKeyError( message=f"Failed to refresh API key: {e}", status_code=401, + ) from e + serialized: Final = json.dumps(api_key_info) + try: + with open(self.api_key_file, "w") as f: + f.write(serialized) + except OSError as e: + verbose_logger.warning( + "Keeping the refreshed API key in memory, it could not be saved to %s: %s", self.api_key_file, e ) + self._keep_unsaved_api_key(serialized) + token: Final = api_key_info.get("token") + if not token: + raise GetAPIKeyError( + message="API key response missing token", + status_code=401, + ) + return token def get_api_base(self) -> str | None: """ - Get the API endpoint from the api-key.json file. + Get the API endpoint of the current API key. Returns: Optional[str]: The GitHub Copilot API endpoint, or None if not found. """ - try: - with open(self.api_key_file, "r") as f: - api_key_info: Final = json.load(f) - endpoints: Final = api_key_info.get("endpoints", {}) - api_endpoint: Final = endpoints.get("api") - return api_endpoint - except (OSError, json.JSONDecodeError, KeyError) as e: - verbose_logger.warning("Error reading API endpoint from file: %s", e) + cached: Final = self._unsaved_api_key() or self._read_api_key_file(CopilotCachedEndpoints) + if cached is None or cached.endpoints is None: return None + return cached.endpoints.api + + def _read_api_key_file(self, view: type[ApiKeyFileView]) -> ApiKeyFileView | None: + try: + return view.model_validate_json(_read_token_file(self.api_key_file)) + except OSError: + verbose_logger.warning("No API key file found or error opening file") + return None + except ValueError as e: + verbose_logger.warning("Ignoring %s, not a Copilot API key file: %s", self.api_key_file, e) + return None + + def _stored_access_token(self) -> str | None: + try: + access_token: Final = _read_token_file(self.access_token_file).strip() + except (OSError, ValueError): + return None + return access_token or None + + def _unsaved_api_key(self) -> CopilotCachedKey | None: + unsaved: Final = _UNSAVED_API_KEYS.get(self.api_key_file) + if unsaved is None or unsaved.key.expires_at <= time.time(): + return None + return unsaved.key if unsaved.access_token == self._stored_access_token() else None + + def _keep_unsaved_api_key(self, serialized: str) -> None: + access_token: Final = self._stored_access_token() + if access_token is None: + return + try: + key: Final = CopilotCachedKey.model_validate_json(serialized) + except ValueError: + return + _UNSAVED_API_KEYS[self.api_key_file] = _UnsavedApiKey(access_token=access_token, key=key) def _refresh_api_key(self) -> dict[str, Any]: """ diff --git a/litellm/llms/huggingface/embedding/transformation.py b/litellm/llms/huggingface/embedding/transformation.py index 1b7d6483739..6e6a117227e 100644 --- a/litellm/llms/huggingface/embedding/transformation.py +++ b/litellm/llms/huggingface/embedding/transformation.py @@ -17,6 +17,7 @@ from litellm.litellm_core_utils.prompt_templates.factory import ( ) from litellm.litellm_core_utils.streaming_handler import CustomStreamWrapper from litellm.llms.base_llm.chat.transformation import BaseConfig, BaseLLMException +from litellm.llms.custom_httpx.sse_lines import iter_sse_lines from litellm.secret_managers.main import get_secret_str from litellm.types.llms.openai import AllMessageValues from litellm.types.utils import Choices, Message, ModelResponse, Usage @@ -357,7 +358,7 @@ class HuggingFaceEmbeddingConfig(BaseConfig): api_key: str | None = None, ) -> list[dict[str, str]]: streamed_response: Final = CustomStreamWrapper( - completion_stream=response.iter_lines(), + completion_stream=iter_sse_lines(response.iter_text()), model=model, custom_llm_provider="huggingface", logging_obj=logging_obj, diff --git a/litellm/llms/huggingface/rerank/transformation.py b/litellm/llms/huggingface/rerank/transformation.py index 1f130f84283..476e22fc088 100644 --- a/litellm/llms/huggingface/rerank/transformation.py +++ b/litellm/llms/huggingface/rerank/transformation.py @@ -78,6 +78,8 @@ class HuggingFaceRerankConfig(BaseRerankConfig): "documents", "top_n", "return_documents", + "truncate", + "truncation_direction", ] def map_cohere_rerank_params( @@ -104,6 +106,10 @@ class HuggingFaceRerankConfig(BaseRerankConfig): optional_rerank_params["return_text"] = v elif k == "top_n" and v is not None: optional_rerank_params["top_n"] = v + elif k == "truncate" and isinstance(v, bool): + optional_rerank_params["truncate"] = v + elif k == "truncation_direction" and v is not None: + optional_rerank_params["truncation_direction"] = v elif k == "documents" and v is not None: optional_rerank_params["texts"] = v elif k == "query" and v is not None: @@ -151,7 +157,6 @@ class HuggingFaceRerankConfig(BaseRerankConfig): # HuggingFace API expects return_text parameter, corresponding to our return_documents parameter request_body: Final = { "raw_scores": False, - "truncate": False, "truncation_direction": "Right", } diff --git a/litellm/llms/langgraph/chat/sse_iterator.py b/litellm/llms/langgraph/chat/sse_iterator.py index 575820bceee..6fe355ad98c 100644 --- a/litellm/llms/langgraph/chat/sse_iterator.py +++ b/litellm/llms/langgraph/chat/sse_iterator.py @@ -12,6 +12,7 @@ import httpx from pydantic import TypeAdapter from litellm._logging import verbose_logger +from litellm.llms.custom_httpx.sse_lines import aiter_sse_lines, iter_sse_lines from litellm.types.utils import Delta, ModelResponseStream, StreamingChoices _DECODED_JSON: Final = TypeAdapter(object) @@ -36,12 +37,12 @@ class LangGraphSSEStreamIterator: def __iter__(self): """Initialize sync iteration.""" - self.line_iterator = self.response.iter_lines() + self.line_iterator = iter_sse_lines(self.response.iter_text()) return self def __aiter__(self): """Initialize async iteration.""" - self.async_line_iterator = self.response.aiter_lines() + self.async_line_iterator = aiter_sse_lines(self.response.aiter_text()) return self def _parse_sse_line(self, line: str) -> ModelResponseStream | None: diff --git a/litellm/llms/manus/responses/transformation.py b/litellm/llms/manus/responses/transformation.py index ed06391a260..91832899141 100644 --- a/litellm/llms/manus/responses/transformation.py +++ b/litellm/llms/manus/responses/transformation.py @@ -241,7 +241,7 @@ class ManusResponsesAPIConfig(OpenAIResponsesAPIConfig): api_base: str, litellm_params: GenericLiteLLMParams, headers: dict, - ) -> tuple[str, dict]: + ) -> tuple[str, dict[str, str]]: """ Transform the get response API request into a URL and data. @@ -252,7 +252,7 @@ class ManusResponsesAPIConfig(OpenAIResponsesAPIConfig): """ encoded_response_id: Final = encode_url_path_segment(response_id, field_name="response_id") url: Final = f"{api_base}/{encoded_response_id}" - data: Final[dict] = {} + data: Final[dict[str, str]] = {} return url, data def transform_get_response_api_response( diff --git a/litellm/llms/mistral/chat/transformation.py b/litellm/llms/mistral/chat/transformation.py index 2c0acacff23..2fb9402ed03 100644 --- a/litellm/llms/mistral/chat/transformation.py +++ b/litellm/llms/mistral/chat/transformation.py @@ -6,16 +6,17 @@ Why separate file? Make it easy to see how transformation works Docs - https://docs.mistral.ai/api/ """ -from collections.abc import AsyncIterator, Coroutine, Iterator, Mapping +from collections.abc import AsyncIterator, Coroutine, Iterator, Mapping, Sequence from itertools import accumulate, count from typing import TYPE_CHECKING, Final, Literal, cast, get_type_hints, overload import httpx +from typing_extensions import TypeIs # noqa: TID251 # TypeIs reaches typing only on 3.13 from litellm._logging import verbose_logger from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj from litellm.litellm_core_utils.prompt_templates.common_utils import ( - handle_messages_with_content_list_to_str_conversion, + convert_content_list_to_str, strip_litellm_internal_message_fields, strip_none_values_from_message, ) @@ -29,8 +30,8 @@ from litellm.router_utils.reasoning_effort_capability import ( nearest_declared_reasoning_effort, ) from litellm.secret_managers.main import get_secret_str -from litellm.types.llms.mistral import MistralThinkingBlock, MistralToolCallMessage -from litellm.types.llms.openai import AllMessageValues +from litellm.types.llms.mistral import MistralTextBlock, MistralThinkingBlock, MistralToolCallMessage +from litellm.types.llms.openai import AllMessageValues, ChatCompletionAssistantMessage, ChatCompletionTextObject from litellm.types.utils import ModelResponse, ModelResponseStream from litellm.utils import convert_to_model_response_object, supports_reasoning @@ -58,6 +59,10 @@ def _accepted_reasoning_effort(model: str, requested: str, custom_llm_provider: _NO_TOOL_CALL_TURN: Final[tuple[int, frozenset[str]]] = (-1, frozenset()) +def _is_json_array(value: object) -> TypeIs[Sequence[object]]: # guard-ok: a decoded JSON array is a list + return isinstance(value, list) + + class MistralConfig(OpenAIGPTConfig): """ Reference: https://docs.mistral.ai/api/ @@ -118,11 +123,14 @@ class MistralConfig(OpenAIGPTConfig): def custom_llm_provider(self) -> str: return "mistral" - def get_supported_openai_params(self, model: str) -> list[str]: - is_magistral: Final = "magistral" in model.lower() - accepts_reasoning_effort: Final = is_magistral or supports_reasoning( + def _accepts_reasoning(self, model: str) -> bool: + return "magistral" in model.lower() or supports_reasoning( model=model, custom_llm_provider=self.custom_llm_provider ) + + def get_supported_openai_params(self, model: str) -> list[str]: + is_magistral: Final = "magistral" in model.lower() + accepts_reasoning_effort: Final = self._accepts_reasoning(model) return [ "stream", "temperature", @@ -260,25 +268,32 @@ class MistralConfig(OpenAIGPTConfig): The above statement is not valid now. Need to plan to remove all the #1,2,3 Mistral API supports content as a list. """ - messages = [self._strip_output_only_fields(m) for m in messages] + keeps_reasoning: Final = self._accepts_reasoning(model) + final_position: Final = len(messages) - 1 + replayed_messages: Final = [ + MistralConfig._with_replayed_reasoning(m, keeps_reasoning, position == final_position) + for position, m in enumerate(messages) + ] ## 1. If 'image_url' or 'file' in content, then transform with base class and mistral-specific handling - for m in messages: + for m in replayed_messages: _content_block = m.get("content") if _content_block and isinstance(_content_block, list): if any(c.get("type") in ["image_url", "file"] for c in _content_block): if is_async: - return self._transform_messages_async(messages, model) + return self._transform_messages_async(replayed_messages, model) else: - messages = self._transform_messages_sync(messages, model) - return messages + return self._transform_messages_sync(replayed_messages, model) ## 2. If content is list, then convert to string - messages = handle_messages_with_content_list_to_str_conversion(messages) + flattened_messages: Final = tuple( + MistralConfig._with_flattened_content(m, keeps_reasoning) for m in replayed_messages + ) ## 3. Handle name in message prepared_messages: Final = tuple( - MistralConfig._handle_tool_call_message(MistralConfig._handle_name_in_message(m)) for m in messages + MistralConfig._handle_tool_call_message(MistralConfig._handle_name_in_message(m)) + for m in flattened_messages ) empty_flags: Final = tuple(map(MistralConfig._is_empty_assistant_message, prepared_messages)) tool_call_turns: Final = accumulate( @@ -442,17 +457,163 @@ class MistralConfig(OpenAIGPTConfig): return cleaned_tools - @classmethod - def _strip_output_only_fields(cls, message: AllMessageValues) -> AllMessageValues: - """ - LiteLLM attaches output-only fields (``reasoning_content``, ``thinking_blocks``, - ``provider_specific_fields``) to assistant responses. Mistral's input schema forbids - unknown fields, so replaying them verbatim in a follow-up turn triggers a - 422 ``extra_forbidden``. Drop them before the request is sent. - """ + @staticmethod + def _is_mistral_think_chunk(part: object) -> bool: + match part: + case {"type": "thinking", "thinking": list()}: + return True + case _: + return False + + @staticmethod + def _text_item_text(item: object) -> str | None: + match item: + case {"type": "text", "text": str(text)}: + return text + case _: + return None + + @staticmethod + def _sendable_think_chunk( + chunk: object, items: Sequence[object], may_stay_open: bool + ) -> MistralThinkingBlock | None: + text_items: Final = [ + MistralTextBlock(type="text", text=text) + for text in map(MistralConfig._text_item_text, items) + if text is not None + ] + if not text_items: + return None + match chunk: + case {"closed": False} if not may_stay_open: + return MistralThinkingBlock(type="thinking", thinking=text_items) + case {"closed": bool(closed)}: + return MistralThinkingBlock(type="thinking", thinking=text_items, closed=closed) + case _: + return MistralThinkingBlock(type="thinking", thinking=text_items) + + @staticmethod + def _sendable_part(part: object, may_stay_open: bool) -> object | None: + match part: + case {"type": "thinking", "thinking": object() as items} if _is_json_array(items): + return MistralConfig._sendable_think_chunk(part, items, may_stay_open) + case _: + return part + + @staticmethod + def _with_sendable_think_chunks( + message: AllMessageValues, content_parts: tuple[object, ...], may_end_open: bool + ) -> AllMessageValues: + last_position: Final = len(content_parts) - 1 + sendable_parts: Final = [ + sendable + for position, part in enumerate(content_parts) + if (sendable := MistralConfig._sendable_part(part, may_end_open and position == last_position)) is not None + ] + return cast( # cast-ok: Mistral's ThinkChunk is outside the OpenAI assistant content union + AllMessageValues, {**message, "content": sendable_parts or None} + ) + + @staticmethod + def _thinking_block_text(block: object) -> str: + match block: + case {"type": "thinking", "thinking": str(thinking)}: + return thinking + case _: + return "" + + @staticmethod + def _replayed_reasoning_text(message: ChatCompletionAssistantMessage) -> str | None: + reasoning_content: Final = message.get("reasoning_content") + if isinstance(reasoning_content, str) and reasoning_content.strip(): + return reasoning_content + thinking_blocks: Final = message.get("thinking_blocks") + thinking_text: Final = ( + "".join(map(MistralConfig._thinking_block_text, thinking_blocks)) + if isinstance(thinking_blocks, list) + else "" + ) + return thinking_text if thinking_text.strip() else None + + @staticmethod + def _assistant_content_parts(message: ChatCompletionAssistantMessage) -> tuple[object, ...] | None: + match message.get("content"): + case None | "": + return () + case str(text): + return (ChatCompletionTextObject(type="text", text=text),) + case list(parts) | tuple(parts): + return tuple(parts) + case _: + return None + + @staticmethod + def _is_prefix_turn(message: object) -> bool: + match message: + case {"prefix": True}: + return True + case _: + return False + + @staticmethod + def _with_replayed_reasoning( + message: AllMessageValues, keeps_reasoning: bool, is_final_turn: bool + ) -> AllMessageValues: if message["role"] != "assistant": return message - return strip_litellm_internal_message_fields(message) + stripped_message: Final = strip_litellm_internal_message_fields(message) + content_parts: Final = MistralConfig._assistant_content_parts(message) + if not keeps_reasoning: + return MistralConfig._without_think_chunks(stripped_message, content_parts) + if content_parts is not None and any(map(MistralConfig._is_mistral_think_chunk, content_parts)): + return MistralConfig._with_sendable_think_chunks( + stripped_message, content_parts, is_final_turn and MistralConfig._is_prefix_turn(message) + ) + reasoning_text: Final = MistralConfig._replayed_reasoning_text(message) + has_turn_output: Final = bool(content_parts) or bool(message.get("tool_calls")) + if reasoning_text is None or content_parts is None or not has_turn_output: + return stripped_message + think_chunk: Final = MistralThinkingBlock( + type="thinking", thinking=[MistralTextBlock(type="text", text=reasoning_text)], closed=True + ) + return cast( # cast-ok: Mistral's ThinkChunk is outside the OpenAI assistant content union + AllMessageValues, {**stripped_message, "content": [think_chunk, *content_parts]} + ) + + @staticmethod + def _without_think_chunks(message: AllMessageValues, content_parts: tuple[object, ...] | None) -> AllMessageValues: + if content_parts is None or not any(map(MistralConfig._is_mistral_think_chunk, content_parts)): + return message + kept_parts: Final = [part for part in content_parts if not MistralConfig._is_mistral_think_chunk(part)] + return cast( # cast-ok: an assistant turn takes a content list or no content + AllMessageValues, {**message, "content": kept_parts or None} + ) + + @staticmethod + def _with_flattened_content(message: AllMessageValues, keeps_reasoning: bool) -> AllMessageValues: + flattened_text: Final = convert_content_list_to_str(message) + match message: + case {"role": "assistant", "content": list(content)} if keeps_reasoning and any( + map(MistralConfig._is_mistral_think_chunk, content) + ): + text_parts: Final = ( + (ChatCompletionTextObject(type="text", text=flattened_text),) if flattened_text else () + ) + think_chunks: Final = tuple(filter(MistralConfig._is_mistral_think_chunk, content)) + sent_chunks: Final = tuple( + sendable + for chunk in think_chunks + if (sendable := MistralConfig._sendable_part(chunk, not text_parts)) is not None + ) + return cast( # cast-ok: Mistral's ThinkChunk is outside the OpenAI assistant content union + AllMessageValues, {**message, "content": [*sent_chunks, *text_parts]} + ) + case _ if flattened_text: + return cast( # cast-ok: every message role takes str content + AllMessageValues, {**message, "content": flattened_text} + ) + case _: + return message @classmethod def _handle_name_in_message(cls, message: AllMessageValues) -> AllMessageValues: diff --git a/litellm/llms/ollama/completion/handler.py b/litellm/llms/ollama/completion/handler.py index 0c13b1cd1d3..1e70141f939 100644 --- a/litellm/llms/ollama/completion/handler.py +++ b/litellm/llms/ollama/completion/handler.py @@ -5,12 +5,15 @@ Ollama /chat/completion calls handled in llm_http_handler.py """ from collections.abc import Mapping, Sequence +from types import MappingProxyType from typing import Any, Final, Protocol, TypedDict +import httpx from typing_extensions import NotRequired, ReadOnly import litellm from litellm.litellm_core_utils.url_utils import ensure_api_route +from litellm.types.mcp import has_header from litellm.types.utils import EmbeddingResponse @@ -82,6 +85,15 @@ def _process_ollama_embedding_response( return model_response +def _ollama_embedding_headers(api_key: str | None, headers: Mapping[str, str] | None) -> Mapping[str, str]: + return MappingProxyType( + { + **({"Authorization": f"Bearer {api_key}"} if api_key and not has_header(headers, "Authorization") else {}), + **(headers or {}), + } + ) + + async def ollama_aembeddings( api_base: str, model: str, @@ -90,10 +102,19 @@ async def ollama_aembeddings( optional_params: Mapping[str, object], logging_obj: object, encoding: TokenEncoder | None, -): + *, + api_key: str | None = None, + headers: Mapping[str, str] | None = None, + timeout: float | httpx.Timeout | None = None, +) -> EmbeddingResponse: data: Final = _prepare_ollama_embedding_payload(model, prompts, optional_params) - response: Final = await litellm.module_level_aclient.post(url=ensure_api_route(api_base, "api/embed"), json=data) + response: Final = await litellm.module_level_aclient.post( + url=ensure_api_route(api_base, "api/embed"), + json=data, + headers=dict(_ollama_embedding_headers(api_key, headers)), + timeout=timeout, + ) response_json: Final[OllamaEmbeddingResponse] = response.json() return _process_ollama_embedding_response( @@ -114,10 +135,19 @@ def ollama_embeddings( model_response: EmbeddingResponse, logging_obj: object, encoding: TokenEncoder | None = None, -): + *, + api_key: str | None = None, + headers: Mapping[str, str] | None = None, + timeout: float | httpx.Timeout | None = None, +) -> EmbeddingResponse: data: Final = _prepare_ollama_embedding_payload(model, prompts, optional_params) - response: Final = litellm.module_level_client.post(url=ensure_api_route(api_base, "api/embed"), json=data) + response: Final = litellm.module_level_client.post( + url=ensure_api_route(api_base, "api/embed"), + json=data, + headers=dict(_ollama_embedding_headers(api_key, headers)), + timeout=timeout, + ) response_json: Final[OllamaEmbeddingResponse] = response.json() return _process_ollama_embedding_response( diff --git a/litellm/llms/ollama/decisions/transformation.py b/litellm/llms/ollama/decisions/transformation.py new file mode 100644 index 00000000000..3e69f5cfede --- /dev/null +++ b/litellm/llms/ollama/decisions/transformation.py @@ -0,0 +1,17 @@ +from typing import Final + +from litellm.constants import PLACEHOLDER_API_KEY +from litellm.llms.base_llm.decisions.transformation import BaseDecisionsConfig + + +class OllamaDecisionsConfig(BaseDecisionsConfig): + api_key_env = ("OLLAMA_API_KEY",) + api_base_env = ("OLLAMA_API_BASE",) + api_key_required = False + + def get_default_api_base(self) -> str | None: + return "http://localhost:11434" + + def resolve_api_key(self, api_key: str | None) -> str | None: + resolved: Final = super().resolve_api_key(api_key) + return None if resolved == PLACEHOLDER_API_KEY else resolved diff --git a/litellm/llms/oobabooga/chat/oobabooga.py b/litellm/llms/oobabooga/chat/oobabooga.py index 8879c20c5eb..b4dc57ff5ed 100644 --- a/litellm/llms/oobabooga/chat/oobabooga.py +++ b/litellm/llms/oobabooga/chat/oobabooga.py @@ -5,6 +5,7 @@ from typing import TYPE_CHECKING, Final import litellm from litellm.litellm_core_utils.url_utils import join_api_base from litellm.llms.custom_httpx.http_handler import get_httpx_client +from litellm.llms.custom_httpx.sse_lines import iter_sse_lines from litellm.utils import EmbeddingResponse, ModelResponse, Usage from ..common_utils import OobaboogaError @@ -74,7 +75,7 @@ def completion( stream=optional_params["stream"] if "stream" in optional_params else False, ) if "stream" in optional_params and optional_params["stream"] is True: - return response.iter_lines() + return iter_sse_lines(response.iter_text()) else: return oobabooga_config.transform_response( model=model, diff --git a/litellm/llms/openai/chat/gpt_transformation.py b/litellm/llms/openai/chat/gpt_transformation.py index 97e988ef2b1..b7396e8fb03 100644 --- a/litellm/llms/openai/chat/gpt_transformation.py +++ b/litellm/llms/openai/chat/gpt_transformation.py @@ -76,6 +76,7 @@ else: _NO_TOOLS_UPDATE: Final[Mapping[str, object]] = MappingProxyType({}) _OBJECT_MAPPING: Final[TypeAdapter[Mapping[str, object]]] = TypeAdapter(Mapping[str, object]) +_CHOICE_MAPPINGS: Final = TypeAdapter(tuple[Mapping[str, object], ...]) _DECODED_JSON: Final = TypeAdapter(object) @@ -958,8 +959,13 @@ class OpenAIChatCompletionStreamingHandler(BaseModelResponseIterator): status_code=error_status_code, message=error_message, ) - choices = chunk.get("choices", []) - choices = self._map_reasoning_to_reasoning_content(choices) + raw_choices: Final = chunk.get("choices") or [] + if any(choice.get("finish_reason") == "abort" for choice in _CHOICE_MAPPINGS.validate_python(raw_choices)): + raise OpenAIError( + status_code=500, + message="Upstream generation aborted (finish_reason=abort)", + ) + choices: Final = self._map_reasoning_to_reasoning_content(raw_choices) fingerprint: Final = _OBJECT_MAPPING.validate_python(chunk).get("system_fingerprint") kwargs: Final[dict[str, Any]] = { diff --git a/litellm/llms/openai/common_utils.py b/litellm/llms/openai/common_utils.py index 12ead582975..216725b9449 100644 --- a/litellm/llms/openai/common_utils.py +++ b/litellm/llms/openai/common_utils.py @@ -31,7 +31,7 @@ if TYPE_CHECKING: import litellm from litellm.litellm_core_utils.completion_timeout import CompletionTimeout from litellm.litellm_core_utils.core_helpers import as_str_mapping, decoded_json_object -from litellm.litellm_core_utils.token_counter import token_counter +from litellm.litellm_core_utils.token_counter import token_counter, usage_tokenizer_model from litellm.llms.base_llm.chat.transformation import BaseLLMException from litellm.llms.custom_httpx.http_handler import ( _DEFAULT_TTL_FOR_HTTPX_CLIENTS, @@ -242,7 +242,7 @@ async def _aiter_once(chunk: ChatCompletionChunk) -> AsyncIterator[ChatCompletio def build_output_token_limit_response( - e: openai.BadRequestError, data: Mapping[str, object], is_async: bool + e: openai.BadRequestError, data: Mapping[str, object], is_async: bool, base_model: str | None ) -> tuple[httpx.Headers, ChatCompletion | Iterator[ChatCompletionChunk] | AsyncIterator[ChatCompletionChunk]]: """Synthesize the length-truncated response the provider itself returns for slightly larger output budgets. @@ -251,7 +251,11 @@ def build_output_token_limit_response( """ model: Final[str] = str(data.get("model", "")) messages: Final = data.get("messages") - prompt_tokens: Final = token_counter(model=model, messages=messages) if isinstance(messages, list) else 0 + prompt_tokens: Final = ( + token_counter(model=usage_tokenizer_model(model, base_model), messages=messages) + if isinstance(messages, list) + else 0 + ) if not data.get("stream"): return e.response.headers, _output_token_limit_completion(model, prompt_tokens) chunk: Final = _output_token_limit_chunk(model) diff --git a/litellm/llms/openai/image_edit/__init__.py b/litellm/llms/openai/image_edit/__init__.py index 63a41b65e8a..261010071c9 100644 --- a/litellm/llms/openai/image_edit/__init__.py +++ b/litellm/llms/openai/image_edit/__init__.py @@ -1,31 +1,5 @@ -from typing import Final - -from litellm.llms.base_llm.image_edit.transformation import BaseImageEditConfig - -from .dalle2_transformation import DallE2ImageEditConfig from .transformation import OpenAIImageEditConfig __all__ = [ - "DallE2ImageEditConfig", "OpenAIImageEditConfig", - "get_openai_image_edit_config", ] - - -def get_openai_image_edit_config(model: str) -> BaseImageEditConfig: - """ - Get the appropriate OpenAI image edit config based on the model. - - Args: - model: The model name (e.g., "dall-e-2", "gpt-image-1") - - Returns: - The appropriate config instance for the model - """ - model_normalized: Final = model.lower().replace("-", "").replace("_", "") - - if model_normalized == "dalle2": - return DallE2ImageEditConfig() - else: - # Default to standard OpenAI config for gpt-image-1 and other models - return OpenAIImageEditConfig() diff --git a/litellm/llms/openai/image_edit/dalle2_transformation.py b/litellm/llms/openai/image_edit/dalle2_transformation.py deleted file mode 100644 index f349959b14f..00000000000 --- a/litellm/llms/openai/image_edit/dalle2_transformation.py +++ /dev/null @@ -1,98 +0,0 @@ -from io import BufferedReader -from typing import TYPE_CHECKING, Any, Final, cast - -from httpx._types import RequestFiles - -import litellm -from litellm.images.utils import ImageEditRequestUtils -from litellm.types.images.main import ImageEditRequestParams -from litellm.types.llms.openai import FileTypes -from litellm.types.router import GenericLiteLLMParams - -from .transformation import OpenAIImageEditConfig - -if TYPE_CHECKING: - from litellm.litellm_core_utils.litellm_logging import Logging as _LiteLLMLoggingObj - - LiteLLMLoggingObj = _LiteLLMLoggingObj -else: - LiteLLMLoggingObj = Any - - -class DallE2ImageEditConfig(OpenAIImageEditConfig): - """ - DALL-E-2 specific configuration for image edit API. - - DALL-E-2 only supports editing a single image (not an array). - Uses "image" field name instead of "image[]". - """ - - def transform_image_edit_request( - self, - model: str, - prompt: str | None, - image: FileTypes | None, - image_edit_optional_request_params: dict, - litellm_params: GenericLiteLLMParams, - headers: dict, - ) -> tuple[dict, RequestFiles]: - """ - Transform image edit request for DALL-E-2. - - DALL-E-2 only accepts a single image with field name "image" (not "image[]"). - """ - request_params: Final = { - "model": model, - **image_edit_optional_request_params, - } - if image is not None: - request_params["image"] = image - if prompt is not None: - request_params["prompt"] = prompt - - request: Final = ImageEditRequestParams(**request_params) - request_dict: Final = cast(dict, request) - - ######################################################### - # Separate images and masks as `files` and send other parameters as `data` - ######################################################### - _image_list: Final = request_dict.get("image") - _mask = request_dict.get("mask") - data_without_files: Final = {k: v for k, v in request_dict.items() if k not in ["image", "mask"]} - files_list: Final[list[tuple[str, Any]]] = [] - - # Handle image parameter - DALL-E-2 only supports single image - if _image_list is not None: - image_list: Final = [_image_list] if not isinstance(_image_list, list) else _image_list - - # Validate only one image is provided - if len(image_list) > 1: - raise litellm.BadRequestError( - message="DALL-E-2 only supports editing a single image. Please provide one image.", - model=model, - llm_provider="openai", - ) - - # Use "image" field name (singular) for DALL-E-2 - for _image in image_list: - if _image is not None: - self._add_image_to_files( - files_list=files_list, - image=_image, - field_name="image", - ) - - # Handle mask parameter if provided - if _mask is not None: - # Handle case where mask can be a list (extract first mask) - if isinstance(_mask, list): - _mask = _mask[0] if _mask else None - - if _mask is not None: - mask_content_type: Final[str] = ImageEditRequestUtils.get_image_content_type(_mask) - if isinstance(_mask, BufferedReader): - files_list.append(("mask", (_mask.name, _mask, mask_content_type))) - else: - files_list.append(("mask", ("mask.png", _mask, mask_content_type))) - - return data_without_files, files_list diff --git a/litellm/llms/openai/image_edit/transformation.py b/litellm/llms/openai/image_edit/transformation.py index 9def833052b..0bba58096ef 100644 --- a/litellm/llms/openai/image_edit/transformation.py +++ b/litellm/llms/openai/image_edit/transformation.py @@ -96,7 +96,7 @@ class OpenAIImageEditConfig(BaseImageEditConfig): """ # Build request params, only including non-None values request_params: Final = { - "model": model, + **({"model": model} if model else {}), **image_edit_optional_request_params, } if image is not None: diff --git a/litellm/llms/openai/image_generation/__init__.py b/litellm/llms/openai/image_generation/__init__.py index e20c80f20bb..4cffbe81a0e 100644 --- a/litellm/llms/openai/image_generation/__init__.py +++ b/litellm/llms/openai/image_generation/__init__.py @@ -1,9 +1,3 @@ -from litellm.llms.base_llm.image_generation.transformation import ( - BaseImageGenerationConfig, -) - -from .dall_e_2_transformation import DallE2ImageGenerationConfig -from .dall_e_3_transformation import DallE3ImageGenerationConfig from .gpt_transformation import GPTImageGenerationConfig from .guardrail_translation import ( OpenAIImageGenerationHandler, @@ -11,18 +5,7 @@ from .guardrail_translation import ( ) __all__ = [ - "DallE2ImageGenerationConfig", - "DallE3ImageGenerationConfig", "GPTImageGenerationConfig", "OpenAIImageGenerationHandler", "guardrail_translation_mappings", ] - - -def get_openai_image_generation_config(model: str) -> BaseImageGenerationConfig: - if model.startswith("dall-e-2") or model == "": # empty model is dall-e-2 - return DallE2ImageGenerationConfig() - elif model.startswith("dall-e-3"): - return DallE3ImageGenerationConfig() - else: - return GPTImageGenerationConfig() diff --git a/litellm/llms/openai/image_generation/dall_e_2_transformation.py b/litellm/llms/openai/image_generation/dall_e_2_transformation.py deleted file mode 100644 index ffc6f1d5fe9..00000000000 --- a/litellm/llms/openai/image_generation/dall_e_2_transformation.py +++ /dev/null @@ -1,81 +0,0 @@ -from typing import TYPE_CHECKING, Final - -import httpx - -from litellm.llms.base_llm.image_generation.transformation import ( - BaseImageGenerationConfig, -) -from litellm.types.llms.openai import OpenAIImageGenerationOptionalParams -from litellm.types.utils import ImageResponse -from litellm.utils import convert_to_model_response_object - -if TYPE_CHECKING: - from litellm.litellm_core_utils.logging import Logging as LiteLLMLoggingObj - - from litellm.litellm_core_utils.tokenizer import Encoding as Tokenizer - - -class DallE2ImageGenerationConfig(BaseImageGenerationConfig): - """ - OpenAI dall-e-2 image generation config - """ - - def get_supported_openai_params(self, model: str) -> list[OpenAIImageGenerationOptionalParams]: - return ["n", "response_format", "quality", "size", "user"] - - def map_openai_params( - self, - non_default_params: dict, - optional_params: dict, - model: str, - drop_params: bool, - ) -> dict: - supported_params: Final = self.get_supported_openai_params(model) - for k in non_default_params: - if k not in optional_params: - if k in supported_params: - optional_params[k] = non_default_params[k] - elif drop_params: - pass - else: - raise ValueError( - f"Parameter {k} is not supported for model {model}. Supported parameters are {supported_params}. Set drop_params=True to drop unsupported parameters." - ) - - return optional_params - - def transform_image_generation_response( - self, - model: str, - raw_response: httpx.Response, - model_response: ImageResponse, - logging_obj: "LiteLLMLoggingObj", - request_data: dict, - optional_params: dict, - litellm_params: dict, - encoding: "Tokenizer | None", - api_key: str | None = None, - json_mode: bool | None = None, - ) -> ImageResponse: - response: Final = raw_response.json() - - stringified_response: Final = response - ## LOGGING - logging_obj.post_call( - input=request_data.get("prompt", ""), - api_key=api_key, - additional_args={"complete_input_dict": request_data}, - original_response=stringified_response, - ) - image_response: Final[ImageResponse] = convert_to_model_response_object( - response_object=stringified_response, - model_response_object=model_response, - response_type="image_generation", - ) - - # set optional params - image_response.size = optional_params.get("size", "1024x1024") # default is always 1024x1024 - image_response.quality = optional_params.get("quality", "standard") # always standard for dall-e-2 - image_response.output_format = optional_params.get("output_format", "png") # always png for dall-e-2 - - return image_response diff --git a/litellm/llms/openai/image_generation/dall_e_3_transformation.py b/litellm/llms/openai/image_generation/dall_e_3_transformation.py deleted file mode 100644 index 90b7eaedf2f..00000000000 --- a/litellm/llms/openai/image_generation/dall_e_3_transformation.py +++ /dev/null @@ -1,81 +0,0 @@ -from typing import TYPE_CHECKING, Final - -import httpx - -from litellm.llms.base_llm.image_generation.transformation import ( - BaseImageGenerationConfig, -) -from litellm.types.llms.openai import OpenAIImageGenerationOptionalParams -from litellm.types.utils import ImageResponse -from litellm.utils import convert_to_model_response_object - -if TYPE_CHECKING: - from litellm.litellm_core_utils.logging import Logging as LiteLLMLoggingObj - - from litellm.litellm_core_utils.tokenizer import Encoding as Tokenizer - - -class DallE3ImageGenerationConfig(BaseImageGenerationConfig): - """ - OpenAI dall-e-3 image generation config - """ - - def get_supported_openai_params(self, model: str) -> list[OpenAIImageGenerationOptionalParams]: - return ["n", "response_format", "quality", "size", "user", "style"] - - def map_openai_params( - self, - non_default_params: dict, - optional_params: dict, - model: str, - drop_params: bool, - ) -> dict: - supported_params: Final = self.get_supported_openai_params(model) - for k in non_default_params: - if k not in optional_params: - if k in supported_params: - optional_params[k] = non_default_params[k] - elif drop_params: - pass - else: - raise ValueError( - f"Parameter {k} is not supported for model {model}. Supported parameters are {supported_params}. Set drop_params=True to drop unsupported parameters." - ) - - return optional_params - - def transform_image_generation_response( - self, - model: str, - raw_response: httpx.Response, - model_response: ImageResponse, - logging_obj: "LiteLLMLoggingObj", - request_data: dict, - optional_params: dict, - litellm_params: dict, - encoding: "Tokenizer | None", - api_key: str | None = None, - json_mode: bool | None = None, - ) -> ImageResponse: - response: Final = raw_response.json() - - stringified_response: Final = response - ## LOGGING - logging_obj.post_call( - input=request_data.get("prompt", ""), - api_key=api_key, - additional_args={"complete_input_dict": request_data}, - original_response=stringified_response, - ) - image_response: Final[ImageResponse] = convert_to_model_response_object( - response_object=stringified_response, - model_response_object=model_response, - response_type="image_generation", - ) - - # set optional params - image_response.size = optional_params.get("size", "1024x1024") # default is always 1024x1024 - image_response.quality = optional_params.get("quality", "hd") # always hd for dall-e-3 - image_response.output_format = optional_params.get("output_format", "png") # always png for dall-e-3 - - return image_response diff --git a/litellm/llms/openai/image_variations/handler.py b/litellm/llms/openai/image_variations/handler.py index 89dcdc40e02..01f01d3de1d 100644 --- a/litellm/llms/openai/image_variations/handler.py +++ b/litellm/llms/openai/image_variations/handler.py @@ -151,7 +151,7 @@ class OpenAIImageVariationsHandler: ) -> ImageResponse: try: provider_config: Final = ProviderConfigManager.get_provider_image_variation_config( - model=model or "", # openai defaults to dall-e-2 + model=model or "", provider=LlmProviders.OPENAI, ) diff --git a/litellm/llms/openai/openai.py b/litellm/llms/openai/openai.py index 9d4df354a30..5a3ab8aebea 100644 --- a/litellm/llms/openai/openai.py +++ b/litellm/llms/openai/openai.py @@ -44,6 +44,7 @@ from litellm.utils import ( CustomStreamWrapper, ProviderConfigManager, convert_to_model_response_object, + get_base_model_from_metadata, ) from ...types.llms.openai import * @@ -557,7 +558,12 @@ class OpenAIChatCompletion(BaseLLM, BaseOpenAILLM): except openai.BadRequestError as e: if not is_output_token_limit_error(e): raise - return build_output_token_limit_response(e=e, data=data, is_async=True) + return build_output_token_limit_response( + e=e, + data=data, + is_async=True, + base_model=get_base_model_from_metadata(logging_obj.model_call_details), + ) except Exception as e: raise e @@ -604,7 +610,12 @@ class OpenAIChatCompletion(BaseLLM, BaseOpenAILLM): except openai.BadRequestError as e: if not is_output_token_limit_error(e): raise - return build_output_token_limit_response(e=e, data=data, is_async=False) + return build_output_token_limit_response( + e=e, + data=data, + is_async=False, + base_model=get_base_model_from_metadata(logging_obj.model_call_details), + ) except Exception as e: if raw_response is not None: raise Exception( diff --git a/litellm/llms/openai/realtime/handler.py b/litellm/llms/openai/realtime/handler.py index 080fc3d24c9..5be488f0f6e 100644 --- a/litellm/llms/openai/realtime/handler.py +++ b/litellm/llms/openai/realtime/handler.py @@ -4,11 +4,17 @@ This file contains the calling OpenAI's `/v1/realtime` endpoint. This requires websockets, and is currently only supported on LiteLLM Proxy. """ +import asyncio import ssl -from typing import Any, Final, cast +from collections.abc import Mapping +from typing import TYPE_CHECKING, Final, Literal, cast + +from pydantic import TypeAdapter from litellm._logging import redact_string, verbose_logger from litellm.constants import REALTIME_WEBSOCKET_MAX_MESSAGE_SIZE_BYTES +from litellm.exceptions import AuthenticationError +from litellm.responses.streaming_iterator import map_stream_error_to_exception from litellm.types.realtime import RealtimeQueryParams from ....litellm_core_utils.litellm_logging import Logging as LiteLLMLogging @@ -23,6 +29,57 @@ from ....llms.custom_httpx.http_handler import get_shared_realtime_ssl_context from ..common_utils import is_openai_backed_api_base from ..openai import OpenAIChatCompletion +if TYPE_CHECKING: + from fastapi import WebSocket + from openai.types.realtime import RealtimeError + from websockets.asyncio.client import ClientConnection + +_SERVER_EVENT_FIELDS: Final = TypeAdapter(Mapping[str, object]) +_CREDENTIALS_ACCEPTED_FOR_A_NON_REALTIME_MODEL: Final = "invalid_model" +_CREDENTIALS_REJECTED: Final = "invalid_api_key" + + +def first_event_error(first_event: str | bytes) -> "RealtimeError | None": + event: Final = _SERVER_EVENT_FIELDS.validate_json(first_event) + if event.get("type") != "error": + return None + from openai.types.realtime import RealtimeErrorEvent + + return RealtimeErrorEvent.model_validate(event).error + + +def _confirm_first_event( + first_event: str | bytes, model: str, sent_credentials: bool, model_listed_outside_realtime: bool +) -> Literal[True]: + error: Final = first_event_error(first_event) + if error is None or ( + error.code == _CREDENTIALS_ACCEPTED_FOR_A_NON_REALTIME_MODEL and not model_listed_outside_realtime + ): + return True + if error.code == _CREDENTIALS_REJECTED or not sent_credentials: + raise AuthenticationError(message=error.message, llm_provider="openai", model=model) + raise map_stream_error_to_exception(error, model=model, custom_llm_provider="openai") + + +async def confirm_session_started( + connection: "ClientConnection", model: str, sent_credentials: bool, model_listed_outside_realtime: bool +) -> Literal[True]: + return _confirm_first_event(await connection.recv(), model, sent_credentials, model_listed_outside_realtime) + + +async def confirm_gateway_session_started( + connection: "ClientConnection", + model: str, + sent_credentials: bool, + model_listed_outside_realtime: bool, + first_event_wait_seconds: float, +) -> Literal[True]: + try: + first_event: Final = await asyncio.wait_for(connection.recv(), first_event_wait_seconds) + except asyncio.TimeoutError: + return True + return _confirm_first_event(first_event, model, sent_credentials, model_listed_outside_realtime) + class OpenAIRealtime(OpenAIChatCompletion): """ @@ -131,7 +188,7 @@ class OpenAIRealtime(OpenAIChatCompletion): async def async_realtime( self, model: str, - websocket: Any, + websocket: "WebSocket", logging_obj: LiteLLMLogging, api_base: str | None = None, api_key: str | None = None, diff --git a/litellm/llms/openai/responses/count_tokens/transformation.py b/litellm/llms/openai/responses/count_tokens/transformation.py index b4e152ff406..a45a0448326 100644 --- a/litellm/llms/openai/responses/count_tokens/transformation.py +++ b/litellm/llms/openai/responses/count_tokens/transformation.py @@ -22,7 +22,7 @@ from litellm.llms.anthropic.messages.responses_adapters.transformation import ( ) from litellm.responses.utils import ResponsesAPIRequestUtils from litellm.types.llms.anthropic import AnthropicMessagesRequest, AnthropicOutputSchema -from litellm.types.llms.openai import ResponsesAPIRequestParams +from litellm.types.llms.openai import ResponsesAPIRequestParams, replayable_responses_input from litellm.types.utils import all_litellm_params @@ -387,10 +387,13 @@ def _forwards(field: str, policy: DropPolicy) -> bool: return field in _COUNT_REQUEST_FIELDS or (not policy.drop_params and field in _INFERENCE_REQUEST_FIELDS) -def _restored(field: str, value: object) -> object: +def _restored(field: str, value: object, policy: DropPolicy) -> object: match field, value: case "input", _: - return ResponsesAPIRequestUtils.restore_encrypted_content_item_ids_in_input(copy.deepcopy(value)) + return replayable_responses_input( + ResponsesAPIRequestUtils.restore_encrypted_content_item_ids_in_input(copy.deepcopy(value)), + drops_set_created_by=policy.drop_params, + ) case "previous_response_id", str(): return ResponsesAPIRequestUtils.decode_previous_response_id_to_original_previous_response_id(value) case _: @@ -398,5 +401,7 @@ def _restored(field: str, value: object) -> object: def native_count_request(request: Mapping[str, object], model: str, policy: DropPolicy) -> Mapping[str, object]: - forwarded: Final = {field: _restored(field, value) for field, value in request.items() if _forwards(field, policy)} + forwarded: Final = { + field: _restored(field, value, policy) for field, value in request.items() if _forwards(field, policy) + } return {**forwarded, "model": model} diff --git a/litellm/llms/openai/responses/guardrail_translation/handler.py b/litellm/llms/openai/responses/guardrail_translation/handler.py index d37a12a91d6..559daf767c2 100644 --- a/litellm/llms/openai/responses/guardrail_translation/handler.py +++ b/litellm/llms/openai/responses/guardrail_translation/handler.py @@ -32,11 +32,11 @@ import copy import json import time import uuid -from collections.abc import Mapping, MutableSequence, Sequence +from collections.abc import Iterable, Mapping, MutableSequence, Sequence from dataclasses import dataclass -from itertools import accumulate, chain, repeat +from itertools import accumulate, chain, groupby, repeat from types import MappingProxyType -from typing import TYPE_CHECKING, Any, Final, NamedTuple, Protocol, Union, cast +from typing import TYPE_CHECKING, Any, Final, NamedTuple, Protocol, TypeVar, Union, cast from pydantic import BaseModel, ConfigDict, TypeAdapter, ValidationError from typing_extensions import ReadOnly, TypedDict @@ -55,7 +55,9 @@ from litellm.llms.base_llm.guardrail_translation.base_translation import ( ) from litellm.llms.base_llm.guardrail_translation.utils import ( blocked_responses_stream_usage, + effective_scan_only_tool_results_for_guardrail, effective_skip_system_message_for_guardrail, + effective_skip_tool_message_for_guardrail, list_field, merge_guardrailed_scoped_messages, role_out_of_guardrail_scope, @@ -65,7 +67,10 @@ from litellm.llms.base_llm.guardrail_translation.utils import ( stream_item_items, unappliable_request_rewrite, ) -from litellm.llms.openai.responses.guardrail_translation.tool_merge import merge_guardrailed_tools +from litellm.llms.openai.responses.guardrail_translation.tool_merge import ( + append_returned_tools, + merge_guardrailed_tools, +) from litellm.responses.litellm_completion_transformation.compaction_items import ( compaction_summary, decode_compaction_item, @@ -74,7 +79,9 @@ from litellm.responses.litellm_completion_transformation.compaction_items import from litellm.responses.litellm_completion_transformation.custom_tools import without_malformed_tool_flags from litellm.responses.litellm_completion_transformation.tool_search import is_server_tool_search_tool from litellm.responses.litellm_completion_transformation.transformation import ( + TOOL_CALL_OUTPUT_ITEM_TYPES, LiteLLMCompletionResponsesConfig, + tool_output_to_chat_content, ) from litellm.types.llms.base import LiteLLMBaseModel from litellm.types.llms.openai import ( @@ -270,6 +277,7 @@ _TOOL_CALL_PAYLOAD_EVENT_TYPES: Final = _TOOL_CALL_PAYLOAD_DELTA_EVENT_TYPES | f ) _OUTPUT_ITEM_EVENT_TYPES: Final = frozenset({"response.output_item.added", "response.output_item.done"}) _OUTPUT_TEXT_EVENT_TYPES: Final = frozenset({"response.output_text.delta", "response.output_text.done"}) +_TOOL_OUTPUT_TEXT_PART_TYPES: Final = frozenset({"input_text", "output_text", "text"}) _PATCHABLE_ITEM_FIELDS: Final[Mapping[str, str]] = MappingProxyType( {"function_call_output": "output", "custom_tool_call_output": "output", "message": "content"} ) @@ -519,10 +527,109 @@ def scannable_instructions(data: Mapping[str, object], *, skip_system: bool = Fa def _input_item_role(item: object) -> str: + if stream_item_field(item, "type") in TOOL_CALL_OUTPUT_ITEM_TYPES: + return "tool" role: Final = item.get("role") if isinstance(item, Mapping) else None return role.lower() if isinstance(role, str) else "" +def _scanned_text_field(item: Mapping[str, object]) -> str: + return "output" if item.get("type") in TOOL_CALL_OUTPUT_ITEM_TYPES else "content" + + +def _tool_output_part_text(part: object) -> str | None: + if not isinstance(part, dict): + return None + fields: Final = _item_fields_adapter.validate_python(part) + text: Final = fields.get("text") + return text if fields.get("type") in _TOOL_OUTPUT_TEXT_PART_TYPES and isinstance(text, str) else None + + +def tool_output_texts(item: object) -> tuple[tuple[int | None, str], ...]: + if not stream_item_field(item, "call_id") or stream_item_field(item, "type") == "computer_call_output": + return () + parts: Final = stream_item_items(item, "output") + part_texts: Final = tuple( + (index, text) for index, part in enumerate(parts) if (text := _tool_output_part_text(part)) + ) + if part_texts: + return part_texts + tool_content: Final = tool_output_to_chat_content(stream_item_field(item, "output")) + return ((None, tool_content),) if isinstance(tool_content, str) and tool_content else () + + +_Grouped: Final = TypeVar("_Grouped") + + +def _pair_call_id(pair: tuple[str, object]) -> str: + return pair[0] + + +def _grouped_by_call_id(pairs: Iterable[tuple[str, _Grouped]]) -> Mapping[str, tuple[_Grouped, ...]]: + ordered: Final = sorted(pairs, key=_pair_call_id) + return MappingProxyType( + {call_id: tuple(value for _, value in group) for call_id, group in groupby(ordered, key=_pair_call_id)} + ) + + +def _texts_by_tool_row( + messages: Sequence[Mapping[str, object]], input_data: "str | ResponseInputParam" +) -> Mapping[int, tuple[str, ...]]: + if isinstance(input_data, str): + return MappingProxyType({}) + output_texts_by_call_id: Final = _grouped_by_call_id( + (str(stream_item_field(item, "call_id")), tuple(text for _, text in tool_output_texts(item))) + for item in input_data + if stream_item_field(item, "type") in TOOL_CALL_OUTPUT_ITEM_TYPES + ) + row_indices_by_call_id: Final = _grouped_by_call_id( + (str(message.get("tool_call_id")), index) + for index, message in enumerate(messages) + if message.get("role") == "tool" + ) + return MappingProxyType( + dict( + chain.from_iterable( + zip(indices, output_texts_by_call_id[call_id], strict=True) + for call_id, indices in row_indices_by_call_id.items() + if len(indices) == len(output_texts_by_call_id.get(call_id, ())) + ) + ) + ) + + +def _is_string_tool_row(message: Mapping[str, object]) -> bool: + return message.get("role") == "tool" and isinstance(message.get("content"), str) + + +def _split_into_text_parts(message: AllMessageValues, texts: tuple[str, ...]) -> AllMessageValues: + if not _is_string_tool_row(message) or len(texts) < 2: + return message + return cast( # cast-ok: a tool row whose content is its text parts as chat text blocks + "AllMessageValues", {**message, "content": [{"type": "text", "text": text} for text in texts]} + ) + + +def _with_split_rows_restored( + rows: Sequence[AllMessageValues], split_rows: Sequence[tuple[AllMessageValues, AllMessageValues]] +) -> Sequence[AllMessageValues]: + if not isinstance(rows, list): + return rows + return [next((original for split, original in split_rows if row == split), row) for row in rows] + + +def _is_textless_tool_row(message: Mapping[str, object], texts: tuple[str, ...] | None) -> bool: + return _is_string_tool_row(message) and (not message.get("content") or texts == ()) + + +def _rewritten_whole_text(item: object, field: str, guardrail_response: str) -> object | None: + if isinstance(stream_item_field(item, field), str): + return guardrail_response + if tool_output_texts(item) == ((None, guardrail_response),): + return None + return guardrail_response + + def _patched_request_fields( raw_input: object, instructions: object, @@ -636,17 +743,28 @@ class OpenAIResponsesHandler(BaseTranslation): Handles both string input and list of message objects. """ - input_data: Final[str | ResponseInputParam | None] = data.get("input") - if not isinstance(input_data, (str, list)): + raw_input: Final[str | ResponseInputParam | None] = data.get("input") + if not isinstance(raw_input, (str, list)): return data + input_data: Final = cast("str | ResponseInputParam", raw_input) # cast-ok: fields read via stream_item_field skip_system: Final = effective_skip_system_message_for_guardrail(guardrail_to_apply) + skip_tool: Final = effective_skip_tool_message_for_guardrail(guardrail_to_apply) + scan_only: Final = effective_scan_only_tool_results_for_guardrail(guardrail_to_apply) structured_messages: Final = self.get_structured_messages(data) - scoped_indices: Final = scoped_structured_message_indices( - structured_messages or [], scan_only_tool_results=False, skip_system=skip_system, skip_tool=False + all_messages: Final = structured_messages or [] + texts_by_tool_row: Final = _texts_by_tool_row(all_messages, input_data) + scoped_indices: Final = tuple( + index + for index in scoped_structured_message_indices( + all_messages, scan_only_tool_results=scan_only, skip_system=skip_system, skip_tool=skip_tool + ) + if not _is_textless_tool_row(all_messages[index], texts_by_tool_row.get(index)) ) - scoped_structured_messages: Final = ( - [structured_messages[index] for index in scoped_indices] if structured_messages else None + split_rows: Final = tuple( + (_split_into_text_parts(all_messages[index], texts_by_tool_row.get(index, ())), all_messages[index]) + for index in scoped_indices ) + scoped_structured_messages: Final = [split for split, _ in split_rows] if structured_messages else None raw_tools: Final = data.get("tools") original_tools: Final[tuple[Mapping[str, object], ...]] = ( tuple(raw_tools) if isinstance(raw_tools, list) else () @@ -661,7 +779,12 @@ class OpenAIResponsesHandler(BaseTranslation): ) ) extracted: Final = self._extract_guardrail_inputs( - data, input_data, flattened_tool_groups, skip_system=skip_system + data, + input_data, + () if scan_only else flattened_tool_groups, + skip_system=skip_system, + skip_tool=skip_tool, + scan_only=scan_only, ) if not extracted.inputs.get("texts"): return data @@ -674,13 +797,14 @@ class OpenAIResponsesHandler(BaseTranslation): logging_obj=litellm_logging_obj, ) self._apply_guardrailed_tools_to_data( - data, original_tools, flattened_tool_groups, guardrailed_inputs.get("tools") + data, original_tools, flattened_tool_groups, guardrailed_inputs.get("tools"), scan_only=scan_only ) written_back: Final = self._written_back_request_fields( data, structured_messages or (), scoped_indices, scoped_structured_messages, + tuple((split, original) for split, original in split_rows if split is not original), guardrail_to_apply, guardrailed_inputs, ) @@ -730,8 +854,10 @@ class OpenAIResponsesHandler(BaseTranslation): flattened_tool_groups: Sequence[Sequence[Mapping[str, object]]], *, skip_system: bool = False, + skip_tool: bool = False, + scan_only: bool = False, ) -> _ExtractedInputs: - instructions: Final = scannable_instructions(data, skip_system=skip_system) + instructions: Final = scannable_instructions(data, skip_system=skip_system or scan_only) texts_to_check: Final[list[str]] = [] if instructions is None else [instructions] images_to_check: Final[list[str]] = [] task_mappings: Final[list[tuple[int, int | None]]] = [] @@ -745,11 +871,15 @@ class OpenAIResponsesHandler(BaseTranslation): ) ) if isinstance(input_data, str): - texts_to_check.append(input_data) + if not scan_only: + texts_to_check.append(input_data) else: for msg_idx, message in enumerate(input_data): if role_out_of_guardrail_scope( - _input_item_role(message), skip_system_message=skip_system, skip_tool_message=False + _input_item_role(message), + skip_system_message=skip_system, + skip_tool_message=skip_tool, + scan_only_tool_results=scan_only, ): continue self._extract_input_text_and_images( @@ -775,12 +905,14 @@ class OpenAIResponsesHandler(BaseTranslation): structured_messages: Sequence[AllMessageValues], scoped_indices: Sequence[int], scoped_structured_messages: Sequence[AllMessageValues] | None, + split_rows: Sequence[tuple[AllMessageValues, AllMessageValues]], guardrail_to_apply: "CustomGuardrail", guardrailed_inputs: GenericGuardrailAPIInputs, ) -> _RequestFields | None: - guardrailed: Final = guardrailed_inputs.get("structured_messages") - if guardrailed is None or guardrailed is scoped_structured_messages: + returned: Final = guardrailed_inputs.get("structured_messages") + if returned is None or returned is scoped_structured_messages: return None + guardrailed: Final = _with_split_rows_restored(returned, split_rows) covers_full_request: Final = len(scoped_indices) == len(structured_messages) or ( guardrail_to_apply.structured_messages_cover_full_request() and len(guardrailed) == len(structured_messages) ) @@ -814,11 +946,14 @@ class OpenAIResponsesHandler(BaseTranslation): original_tools: Sequence[Mapping[str, object]], flattened_tool_groups: Sequence[Sequence[Mapping[str, object]]], guardrailed_tools: Sequence[ChatCompletionToolParam] | None, + *, + scan_only: bool, ) -> None: if guardrailed_tools is None: return + merge: Final = append_returned_tools if scan_only else merge_guardrailed_tools data["tools"] = list( # rebind-ok: in-place request rewrite - merge_guardrailed_tools(original_tools, flattened_tool_groups, guardrailed_tools) + merge(original_tools, flattened_tool_groups, guardrailed_tools) ) def _extract_input_text_and_images( @@ -839,6 +974,11 @@ class OpenAIResponsesHandler(BaseTranslation): texts_to_check.append(summary) task_mappings.append((msg_idx, None)) return + if message.get("type") in TOOL_CALL_OUTPUT_ITEM_TYPES: + for content_idx, text in tool_output_texts(message): + texts_to_check.append(text) + task_mappings.append((msg_idx, content_idx)) + return content: Final = message.get("content", None) if content is None: return @@ -890,18 +1030,20 @@ class OpenAIResponsesHandler(BaseTranslation): ) continue - content = messages[msg_idx].get("content", None) + field = _scanned_text_field(messages[msg_idx]) + content = messages[msg_idx].get(field, None) if content is None: continue - if isinstance(content, str) and content_idx_optional is None: - # Replace string content with guardrail response - messages[msg_idx]["content"] = guardrail_response + if content_idx_optional is None: + rewritten = _rewritten_whole_text(messages[msg_idx], field, guardrail_response) + if rewritten is not None: + messages[msg_idx][field] = rewritten - elif isinstance(content, list) and content_idx_optional is not None: + elif isinstance(content, list): # Replace specific text item in list content - if isinstance(messages[msg_idx]["content"][content_idx_optional], dict): - messages[msg_idx]["content"][content_idx_optional]["text"] = guardrail_response + if isinstance(messages[msg_idx][field][content_idx_optional], dict): + messages[msg_idx][field][content_idx_optional]["text"] = guardrail_response async def process_output_response( self, diff --git a/litellm/llms/openai/responses/guardrail_translation/tool_merge.py b/litellm/llms/openai/responses/guardrail_translation/tool_merge.py index f295a864b71..e529cba4edf 100644 --- a/litellm/llms/openai/responses/guardrail_translation/tool_merge.py +++ b/litellm/llms/openai/responses/guardrail_translation/tool_merge.py @@ -6,6 +6,7 @@ from typing import Final, TypeAlias from pydantic import BaseModel, TypeAdapter, ValidationError from litellm._logging import verbose_logger +from litellm.llms.base_llm.guardrail_translation.utils import merge_returned_tools_into_request_tools, openai_tool_name from litellm.responses.litellm_completion_transformation.custom_tools import custom_tool_grammar_suffix from litellm.responses.litellm_completion_transformation.transformation import ( NAMESPACE_DESCRIPTION_SEPARATOR, @@ -183,3 +184,18 @@ def merge_guardrailed_tools( tuple(tool for key, tool in zip(guardrailed_keys, guardrailed) if key not in owned_keys) ) return tuple(chain(merged_originals, appended)) + + +def append_returned_tools( + original_tools: Sequence[Tool], + flattened_groups: Sequence[Sequence[Tool]], + returned_tools: Iterable[object], +) -> tuple[Tool, ...]: + request_chat_tools: Final = tuple(chain.from_iterable(flattened_groups)) + additions: Final = merge_returned_tools_into_request_tools( + request_tools=request_chat_tools, returned_tools=_validated_tools(returned_tools), tool_name=openai_tool_name + )[len(request_chat_tools) :] + return ( + *original_tools, + *LiteLLMCompletionResponsesConfig.transform_chat_completion_tool_params_to_responses_api_tools(additions), + ) diff --git a/litellm/llms/openai/responses/transformation.py b/litellm/llms/openai/responses/transformation.py index 07822bb17b3..903e6177e7b 100644 --- a/litellm/llms/openai/responses/transformation.py +++ b/litellm/llms/openai/responses/transformation.py @@ -1,4 +1,4 @@ -from collections.abc import Callable, Collection, Mapping, Sequence +from collections.abc import Callable, Collection, Iterable, Mapping, Sequence from functools import lru_cache from types import MappingProxyType from typing import TYPE_CHECKING, Any, Final, Protocol, cast, get_type_hints @@ -10,7 +10,11 @@ from typing_extensions import ReadOnly, TypedDict import litellm from litellm._logging import verbose_logger -from litellm.integrations.anthropic_cache_control_hook import AnthropicCacheControlHook, targets_openai_api +from litellm.integrations.anthropic_cache_control_hook import ( + AnthropicCacheControlHook, + openai_prompt_cache_breakpoint_support, + targets_openai_api, +) from litellm.litellm_core_utils.core_helpers import normalize_drop_params, process_response_headers from litellm.litellm_core_utils.get_model_cost_map import GetModelCostMap from litellm.litellm_core_utils.llm_response_utils.convert_dict_to_response import ( @@ -20,6 +24,7 @@ from litellm.litellm_core_utils.prompt_templates.common_utils import ( cache_control_as_prompt_cache_breakpoint, drop_non_python_regex_patterns, flatten_combinators_and_drop_non_python_regex_patterns, + prompt_cache_breakpoint_for_wire, with_prompt_cache_breakpoint, ) from litellm.litellm_core_utils.safe_json_loads import safe_json_loads @@ -66,10 +71,41 @@ _PROVIDERS_VALIDATING_TOOL_CALL_ITEM_IDS: Final = frozenset({LlmProviders.AZURE, _PROVIDERS_REPLAYING_ONLY_THEIR_OWN_REASONING: Final = _PROVIDERS_VALIDATING_TOOL_CALL_ITEM_IDS _ROLES_READING_PROMPT_CACHE_BREAKPOINTS: Final = frozenset({"system", "developer", "user"}) _PART_TYPES_READING_PROMPT_CACHE_BREAKPOINTS: Final = frozenset({"input_text", "input_image", "input_file"}) +_INPUT_PART_LIST_KEYS: Final = frozenset({"content", "output"}) +_COMPACT_TRACKING_PARAMS: Final = frozenset({"metadata", "user"}) +_COMPACT_REJECTED_PARAMS: Final = frozenset( + { + "background", + "context_management", + "max_output_tokens", + "max_tool_calls", + "moderation", + "partial_images", + "prompt", + "safety_identifier", + "store", + "stream_options", + "temperature", + "tool_choice", + "top_logprobs", + "top_p", + "truncation", + } +) +_PROVIDERS_WITH_STRICT_COMPACT_PARAMS: Final = frozenset( + {LlmProviders.OPENAI, LlmProviders.AZURE, LlmProviders.AZURE_AI} +) _INPUT_ITEM: Final[TypeAdapter[Mapping[str, object]]] = TypeAdapter(Mapping[str, object]) _CONTENT_PARTS: Final[TypeAdapter[Sequence[Mapping[str, object]]]] = TypeAdapter(Sequence[Mapping[str, object]]) +class _DeclaredModel(BaseModel): + model_config = ConfigDict(frozen=True, extra="ignore", from_attributes=True) + + base_model: object = None + model_info: object = None + + class _DeploymentHost(BaseModel): """`responses()` builds the params from raw kwargs, where callers may spell the host `base_url`.""" @@ -85,7 +121,7 @@ class _DropParamsSetting(BaseModel): drop_params: object = None -def _drops_params(litellm_params: GenericLiteLLMParams) -> bool: +def drops_params(litellm_params: GenericLiteLLMParams) -> bool: setting: Final = _DropParamsSetting.model_validate(litellm_params) return litellm.drop_params is True or normalize_drop_params(setting.drop_params) is True @@ -193,6 +229,63 @@ def _with_breakpoint_on_last_reading_part( return (*parts[:last], marked_last, *parts[last + 1 :]) +def _json_object_or_none(value: object) -> Mapping[str, object] | None: + return value if isinstance(value, Mapping) else None + + +def _json_array_or_empty(value: object) -> Sequence[object]: + return value if isinstance(value, (list, tuple)) else () + + +def _item_with_wire_safe_prompt_cache_breakpoints(item: object, keeps_markers: bool) -> object: + fields: Final = _json_object_or_none(item) + if fields is None or not _carries_prompt_cache_breakpoint(fields): + return item + wire_safe_fields: Final = { + key: _parts_with_wire_safe_prompt_cache_breakpoints(key, value, keeps_markers) + for key, value in fields.items() + if key != "prompt_cache_breakpoint" + } + unchanged: Final = "prompt_cache_breakpoint" not in fields and _same_objects( + wire_safe_fields.values(), fields.values() + ) + return item if unchanged else wire_safe_fields + + +def _same_objects(rebuilt: Iterable[object], originals: Iterable[object]) -> bool: + return all(new is old for new, old in zip(rebuilt, originals, strict=True)) + + +def _carries_prompt_cache_breakpoint(fields: Mapping[str, object]) -> bool: + return "prompt_cache_breakpoint" in fields or any( + _parts_carry_prompt_cache_breakpoint(fields.get(key)) for key in _INPUT_PART_LIST_KEYS + ) + + +def _parts_carry_prompt_cache_breakpoint(parts: object) -> bool: + return any(isinstance(part, Mapping) and "prompt_cache_breakpoint" in part for part in _json_array_or_empty(parts)) + + +def _parts_with_wire_safe_prompt_cache_breakpoints(key: str, value: object, keeps_markers: bool) -> object: + if key not in _INPUT_PART_LIST_KEYS or not _parts_carry_prompt_cache_breakpoint(value): + return value + parts: Final = _json_array_or_empty(value) + wire_safe_parts: Final = tuple(_part_with_wire_safe_prompt_cache_breakpoint(part, keeps_markers) for part in parts) + return value if _same_objects(wire_safe_parts, parts) else list(wire_safe_parts) + + +def _part_with_wire_safe_prompt_cache_breakpoint(part: object, keeps_markers: bool) -> object: + fields: Final = _json_object_or_none(part) + if fields is None or "prompt_cache_breakpoint" not in fields: + return part + marker: Final = fields["prompt_cache_breakpoint"] + wire_marker: Final = prompt_cache_breakpoint_for_wire(marker, drop_params=True) if keeps_markers else None + if keeps_markers and wire_marker == marker: + return part + unmarked: Final = {key: value for key, value in fields.items() if key != "prompt_cache_breakpoint"} + return with_prompt_cache_breakpoint(unmarked, wire_marker) + + class _ReasoningSupportEntry(LiteLLMBaseModel): litellm_provider: str | None = None supports_reasoning: bool | None = None @@ -499,8 +592,13 @@ class OpenAIResponsesAPIConfig(BaseResponsesAPIConfig): ) if sanitized_tools is not None: response_api_optional_request_params["tools"] = sanitized_tools - final_request_params: Final = dict( - ResponsesAPIRequestParams(model=model, input=replay_safe_input, **response_api_optional_request_params) + final_request_params: Final = cast( # cast-ok: typed dict spread is inferred as Unknown by basedpyright + dict[str, object], + { + "model": model, + "input": replay_safe_input, + **response_api_optional_request_params, + }, ) return final_request_params @@ -513,13 +611,14 @@ class OpenAIResponsesAPIConfig(BaseResponsesAPIConfig): litellm_params: GenericLiteLLMParams, prompt_cache_options: object = None, ) -> tuple[str | ResponseInputParam, Sequence[ALL_RESPONSES_API_TOOL_PARAMS] | None]: - validated_input: Final = self._validate_input_param(self._drop_bridge_minted_reasoning_items(input)) - marked_input: Final = ( - self._input_with_prompt_cache_breakpoints(validated_input) - if self._reads_prompt_cache_breakpoints( - model=model, litellm_params=litellm_params, prompt_cache_options=prompt_cache_options - ) - else validated_input + validated_input: Final = self._validate_input_param( + self._drop_bridge_minted_reasoning_items(input), drops_set_created_by=drops_params(litellm_params) + ) + reads_breakpoints: Final = self._reads_prompt_cache_breakpoints( + model=model, litellm_params=litellm_params, prompt_cache_options=prompt_cache_options + ) + marker_safe_input: Final = self._input_with_wire_safe_prompt_cache_breakpoints( + model=model, input=validated_input, litellm_params=litellm_params, reads_breakpoints=reads_breakpoints ) maps_anthropic_tool_search: Final = self._targets_openai_api(litellm_params) and any( is_anthropic_tool_search_chat_tool(tool) for tool in tools or () @@ -529,20 +628,71 @@ class OpenAIResponsesAPIConfig(BaseResponsesAPIConfig): if maps_anthropic_tool_search else tools ) - replayable_input: Final = ( - input_without_unanswered_anthropic_tool_search_calls(marked_input) - if maps_anthropic_tool_search - else marked_input - ) stripped_input, stripped_tools = self.remove_cache_control_flag_from_input_and_tools( - model=model, input=replayable_input, tools=mapped_tools + model=model, + input=self._replayable_input(marker_safe_input, reads_breakpoints, maps_anthropic_tool_search), + tools=mapped_tools, ) + if marker_safe_input is not validated_input: + self._strip_caller_input_as_if_unmarked( + model=model, + caller_input=validated_input, + reads_breakpoints=reads_breakpoints, + maps_anthropic_tool_search=maps_anthropic_tool_search, + ) object_schema_tools: Final = self._tools_with_object_parameters(model=model, tools=stripped_tools) sanitized_tools: Final = self._sanitized_tool_schemas_for_openai( model=model, tools=object_schema_tools, litellm_params=litellm_params ) return self._drop_foreign_tool_call_item_ids(stripped_input), sanitized_tools + def _replayable_input( + self, input: str | ResponseInputParam, reads_breakpoints: bool, maps_anthropic_tool_search: bool + ) -> str | ResponseInputParam: + marked_input: Final = self._input_with_prompt_cache_breakpoints(input) if reads_breakpoints else input + if not maps_anthropic_tool_search: + return marked_input + return input_without_unanswered_anthropic_tool_search_calls(marked_input) + + def _strip_caller_input_as_if_unmarked( + self, + model: str, + caller_input: str | ResponseInputParam, + reads_breakpoints: bool, + maps_anthropic_tool_search: bool, + ) -> None: + self.remove_cache_control_flag_from_input_and_tools( + model=model, input=self._replayable_input(caller_input, reads_breakpoints, maps_anthropic_tool_search) + ) + + def _input_with_wire_safe_prompt_cache_breakpoints( + self, + model: str, + input: str | ResponseInputParam, + litellm_params: GenericLiteLLMParams, + reads_breakpoints: bool, + ) -> str | ResponseInputParam: + if not isinstance(input, list) or not drops_params(litellm_params): + return input + keeps_markers: Final = reads_breakpoints or self._keeps_prompt_cache_breakpoints( + model=model, litellm_params=litellm_params + ) + wire_safe_items: Final = tuple( + _item_with_wire_safe_prompt_cache_breakpoints(item, keeps_markers) for item in input + ) + if _same_objects(wire_safe_items, input): + return input + wire_safe_input: Final = list(wire_safe_items) + return cast("ResponseInputParam", wire_safe_input) # cast-ok: items keep their shape, minus a rejected marker + + def _keeps_prompt_cache_breakpoints(self, model: str, litellm_params: GenericLiteLLMParams) -> bool: + provider: Final = _provider_name(self.custom_llm_provider) + base_model: Final = self._declared_base_model(model=model, litellm_params=litellm_params) + known_support: Final = ( + openai_prompt_cache_breakpoint_support(name, provider) for name in dict.fromkeys((base_model, model)) + ) + return next((support for support in known_support if support is not None), None) is not False + def _targets_openai_api(self, litellm_params: GenericLiteLLMParams) -> bool: host: Final = _DeploymentHost.model_validate(litellm_params) return self.custom_llm_provider == LlmProviders.OPENAI and targets_openai_api(host.api_base or host.base_url) @@ -554,7 +704,7 @@ class OpenAIResponsesAPIConfig(BaseResponsesAPIConfig): if tools is None or not any(is_anthropic_tool_search_chat_tool(tool) for tool in tools): return tools callers_own_search: Final = any(is_openai_tool_search_tool(tool) for tool in tools) - if callers_own_search or not _drops_params(litellm_params) or _runs_tool_search(model, tools): + if callers_own_search or not drops_params(litellm_params) or _runs_tool_search(model, tools): return tools_with_anthropic_tool_search_mapped(tools) verbose_logger.warning( "Dropping tool search under drop_params: OpenAI model '%s' cannot run it or no tool is deferred, so every " @@ -658,14 +808,15 @@ class OpenAIResponsesAPIConfig(BaseResponsesAPIConfig): @staticmethod def _without_foreign_tool_call_item_id(item: object) -> object: - if not isinstance(item, dict): + fields: Final = _json_object_or_none(item) + if fields is None: return item - item_type: Final = item.get("type") - item_id: Final = item.get("id") + item_type: Final = fields.get("type") + item_id: Final = fields.get("id") genuine_prefix: Final = TOOL_CALL_ITEM_ID_PREFIX_BY_TYPE.get(item_type) if isinstance(item_type, str) else None if genuine_prefix is None or not isinstance(item_id, str) or item_id.startswith(genuine_prefix): return item - return {key: value for key, value in item.items() if key != "id"} + return {key: value for key, value in fields.items() if key != "id"} def _sanitized_tool_schemas_for_openai( self, @@ -709,6 +860,13 @@ class OpenAIResponsesAPIConfig(BaseResponsesAPIConfig): base_model: Final[object] = model_info.get("base_model") if isinstance(model_info, dict) else None return base_model if isinstance(base_model, str) and base_model else model + @staticmethod + def _declared_base_model(model: str, litellm_params: GenericLiteLLMParams) -> str: + declared: Final = _DeclaredModel.model_validate(litellm_params) + model_info: Final = _json_object_or_none(declared.model_info) + candidates: Final = (declared.base_model, None if model_info is None else model_info.get("base_model")) + return next((name for name in candidates if isinstance(name, str) and name), model) + @staticmethod def _sanitized_tool_entry( entry: Mapping[str, object], @@ -747,7 +905,9 @@ class OpenAIResponsesAPIConfig(BaseResponsesAPIConfig): ] return tools if all(new is old for new, old in zip(sanitized, tools, strict=True)) else sanitized - def _validate_input_param(self, input: str | ResponseInputParam) -> str | ResponseInputParam: + def _validate_input_param( + self, input: str | ResponseInputParam, *, drops_set_created_by: bool = False + ) -> str | ResponseInputParam: """ Ensure all input fields if pydantic are converted to dict @@ -759,18 +919,20 @@ class OpenAIResponsesAPIConfig(BaseResponsesAPIConfig): for item in input: # if it's pydantic, convert to dict if isinstance(item, BaseModel): - validated_input.append(item.model_dump(exclude_none=True)) + validated_input.append( + replayable_responses_item( + item.model_dump(exclude_none=True), drops_set_created_by=drops_set_created_by + ) + ) elif isinstance(item, dict): - # Handle reasoning items specifically to filter out status=None - if item.get("type") == "reasoning": - verbose_logger.debug("Handling reasoning item: %s", item) - # Type assertion since we know it's a dict at this point - dict_item = cast(dict[str, object], item) - filtered_item = self._handle_reasoning_item(dict_item) - else: - # For other dict items, just pass through - filtered_item = cast(dict[str, object], item) - validated_input.append(filtered_item) + validated_input.append( + replayable_responses_item( + self._handle_reasoning_item(cast(dict[str, object], item)) + if item.get("type") == "reasoning" + else item, + drops_set_created_by=drops_set_created_by, + ) + ) else: validated_input.append(item) return validated_input @@ -1060,7 +1222,7 @@ class OpenAIResponsesAPIConfig(BaseResponsesAPIConfig): api_base: str, litellm_params: GenericLiteLLMParams, headers: dict, - ) -> tuple[str, dict]: + ) -> tuple[str, dict[str, str]]: """ Transform the get response API request into a URL and data @@ -1069,7 +1231,7 @@ class OpenAIResponsesAPIConfig(BaseResponsesAPIConfig): """ encoded_response_id: Final = encode_url_path_segment(response_id, field_name="response_id") url: Final = f"{api_base}/{encoded_response_id}" - data: Final[dict] = {} + data: Final[dict[str, str]] = {} return url, data def transform_get_response_api_response( @@ -1177,6 +1339,17 @@ class OpenAIResponsesAPIConfig(BaseResponsesAPIConfig): ######################################################### ########## COMPACT RESPONSE API TRANSFORMATION ########## ######################################################### + def compact_url(self, api_base: str) -> str: + parsed_url: Final = httpx.URL(api_base) + return str(parsed_url.copy_with(path=parsed_url.path.rstrip("/") + "/compact")) + + def compact_dropped_params(self, litellm_params: GenericLiteLLMParams) -> frozenset[str]: + if self.custom_llm_provider not in _PROVIDERS_WITH_STRICT_COMPACT_PARAMS: + return frozenset() + if drops_params(litellm_params): + return _COMPACT_TRACKING_PARAMS | _COMPACT_REJECTED_PARAMS + return _COMPACT_TRACKING_PARAMS + def transform_compact_response_api_request( self, model: str, @@ -1192,10 +1365,8 @@ class OpenAIResponsesAPIConfig(BaseResponsesAPIConfig): OpenAI API expects the following request - POST /v1/responses/compact """ - # Preserve query params (e.g., api-version) while appending /compact. - parsed_url: Final = httpx.URL(api_base) - compact_path: Final = parsed_url.path.rstrip("/") + "/compact" - url: Final = str(parsed_url.copy_with(path=compact_path)) + url: Final = self.compact_url(api_base) + dropped_params: Final = self.compact_dropped_params(litellm_params) request_params: Final = cast( # cast-ok: the base signature leaves the params bag untyped "Mapping[str, object]", response_api_optional_request_params @@ -1209,9 +1380,11 @@ class OpenAIResponsesAPIConfig(BaseResponsesAPIConfig): ) if sanitized_tools is not None: response_api_optional_request_params["tools"] = sanitized_tools - data: Final = dict( - ResponsesAPIRequestParams(model=model, input=replay_safe_input, **response_api_optional_request_params) - ) + data: Final = { + "model": model, + "input": replay_safe_input, + **{key: value for key, value in request_params.items() if key not in dropped_params}, + } return url, data diff --git a/litellm/llms/openai_like/chat/handler.py b/litellm/llms/openai_like/chat/handler.py index 2c74ef19e7d..a450947afdf 100644 --- a/litellm/llms/openai_like/chat/handler.py +++ b/litellm/llms/openai_like/chat/handler.py @@ -16,6 +16,7 @@ from litellm import LlmProviders from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj from litellm.llms.base_llm.base_model_iterator import MockResponseIterator from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler, HTTPHandler +from litellm.llms.custom_httpx.sse_lines import aiter_sse_lines, iter_sse_lines from litellm.llms.databricks.streaming_utils import ModelResponseIterator from litellm.llms.openai.chat.gpt_transformation import OpenAIGPTConfig from litellm.llms.openai.openai import OpenAIConfig @@ -65,7 +66,9 @@ async def make_call( model_response: Final = _fake_streamed_model_response(response.json()) completion_stream = MockResponseIterator(model_response=model_response) else: - completion_stream = ModelResponseIterator(streaming_response=response.aiter_lines(), sync_stream=False) + completion_stream = ModelResponseIterator( + streaming_response=aiter_sse_lines(response.aiter_text()), sync_stream=False + ) # LOGGING logging_obj.post_call( input=messages, @@ -103,7 +106,9 @@ def make_sync_call( model_response: Final = _fake_streamed_model_response(response.json()) completion_stream = MockResponseIterator(model_response=model_response) else: - completion_stream = ModelResponseIterator(streaming_response=response.iter_lines(), sync_stream=True) + completion_stream = ModelResponseIterator( + streaming_response=iter_sse_lines(response.iter_text()), sync_stream=True + ) # LOGGING logging_obj.post_call( diff --git a/litellm/llms/openai_like/dynamic_config.py b/litellm/llms/openai_like/dynamic_config.py index 685561f55a5..d7aafe9f06e 100644 --- a/litellm/llms/openai_like/dynamic_config.py +++ b/litellm/llms/openai_like/dynamic_config.py @@ -55,6 +55,15 @@ def create_config_class(provider: SimpleProviderConfig): else: return super()._transform_messages(messages=messages, model=model, is_async=False) + def _should_preserve_cache_control_for_endpoint( + self, + custom_llm_provider: str | None, + api_base: str | None, + ) -> bool: + return provider.special_handling.get( + "preserve_cache_control", False + ) or super()._should_preserve_cache_control_for_endpoint(custom_llm_provider, api_base) + def _get_openai_compatible_provider_info( self, api_base: str | None, api_key: str | None ) -> tuple[str | None, str | None]: @@ -177,7 +186,7 @@ def create_config_class(provider: SimpleProviderConfig): return JSONProviderConfig -_responses_config_cache: Final[dict] = {} +_responses_config_cache: Final[dict[str, "type[OpenAILikeResponsesConfig]"]] = {} def create_responses_config_class(provider: SimpleProviderConfig) -> "type[OpenAILikeResponsesConfig]": diff --git a/litellm/llms/openai_like/json_loader.py b/litellm/llms/openai_like/json_loader.py index 23b63177137..6e99b9e7fec 100644 --- a/litellm/llms/openai_like/json_loader.py +++ b/litellm/llms/openai_like/json_loader.py @@ -3,6 +3,7 @@ JSON-based provider configuration loader for OpenAI-compatible providers. """ import json +from collections.abc import Mapping from pathlib import Path from typing import Final @@ -12,6 +13,7 @@ from litellm._logging import verbose_logger from litellm.types.utils import ProviderSpecificModelInfo _PROVIDER_INFO_ADAPTER: Final = TypeAdapter(ProviderSpecificModelInfo) +_SPECIAL_HANDLING_ADAPTER: Final = TypeAdapter(Mapping[str, bool]) class SimpleProviderConfig: @@ -20,12 +22,14 @@ class SimpleProviderConfig: def __init__(self, slug: str, data: dict): self.slug = slug self.base_url = data["base_url"] - self.api_key_env = data["api_key_env"] - self.api_base_env = data.get("api_base_env") + self.api_key_env: str = data["api_key_env"] + self.api_base_env: str | None = data.get("api_base_env") self.base_class = data.get("base_class", "openai_gpt") self.param_mappings = data.get("param_mappings", {}) self.constraints = data.get("constraints", {}) - self.special_handling = data.get("special_handling", {}) + self.special_handling: Mapping[str, bool] = _SPECIAL_HANDLING_ADAPTER.validate_python( + data.get("special_handling", {}) + ) self.supported_endpoints = data.get("supported_endpoints", []) self.provider_info: ProviderSpecificModelInfo = ( _PROVIDER_INFO_ADAPTER.validate_python(data["provider_info"]) if "provider_info" in data else {} diff --git a/litellm/llms/openai_like/messages/transformation.py b/litellm/llms/openai_like/messages/transformation.py index 8daae2a8e6a..a5d825a39d7 100644 --- a/litellm/llms/openai_like/messages/transformation.py +++ b/litellm/llms/openai_like/messages/transformation.py @@ -37,6 +37,9 @@ class OpenAILikeAnthropicMessagesConfig(AnthropicMessagesConfig): def is_native_messages_route(self) -> bool: return False + def hoists_wrapped_defer_loading(self, model: str) -> bool: + return False + def validate_anthropic_messages_environment( self, headers: dict[str, str], diff --git a/litellm/llms/openai_like/providers.json b/litellm/llms/openai_like/providers.json index 115d914d3ac..fe88ac03e04 100644 --- a/litellm/llms/openai_like/providers.json +++ b/litellm/llms/openai_like/providers.json @@ -58,6 +58,12 @@ "max_completion_tokens": "max_tokens" } }, + "zerogpu": { + "base_url": "https://api.zerogpu.ai/v1", + "api_key_env": "ZEROGPU_API_KEY", + "api_base_env": "ZEROGPU_API_BASE", + "supported_endpoints": ["/v1/chat/completions", "/v1/responses"] + }, "chutes": { "base_url": "https://llm.chutes.ai/v1/", "api_key_env": "CHUTES_API_KEY", @@ -107,6 +113,12 @@ "api_key_env": "AIHUBMIX_API_KEY", "api_base_env": "AIHUBMIX_API_BASE" }, + "aiand": { + "base_url": "https://api.aiand.com/v1", + "api_key_env": "AIAND_API_KEY", + "api_base_env": "AIAND_API_BASE", + "supported_endpoints": ["/v1/chat/completions", "/v1/responses", "/v1/messages"] + }, "crusoe": { "base_url": "https://api.inference.crusoecloud.com/v1", "api_key_env": "CRUSOE_API_KEY", @@ -257,5 +269,21 @@ "/v1/chat/completions", "/v1/responses" ] + }, + "streamlake": { + "base_url": "https://vanchin.streamlake.ai/api/gateway/v1/endpoints", + "api_key_env": "STREAMLAKE_API_KEY", + "api_base_env": "STREAMLAKE_API_BASE", + "param_mappings": { + "max_tokens": "max_completion_tokens" + }, + "provider_info": { + "supports_function_calling": true, + "supports_reasoning": true + }, + "special_handling": { + "preserve_cache_control": true + }, + "supported_endpoints": ["/v1/chat/completions"] } } diff --git a/litellm/llms/perplexity/embedding/transformation.py b/litellm/llms/perplexity/embedding/transformation.py index 7b4da933976..147d344795d 100644 --- a/litellm/llms/perplexity/embedding/transformation.py +++ b/litellm/llms/perplexity/embedding/transformation.py @@ -12,12 +12,14 @@ This module decodes them into float arrays for OpenAI-compatible responses. """ import base64 +import builtins import struct -from collections.abc import Mapping -from typing import Final +from collections.abc import Mapping, Sequence +from typing import Final, Literal import httpx -from pydantic import ConfigDict, TypeAdapter +from pydantic import ConfigDict, TypeAdapter, with_config +from typing_extensions import ReadOnly, TypedDict from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj from litellm.litellm_core_utils.url_utils import join_api_base @@ -31,6 +33,17 @@ _JSON_OBJECT: Final = TypeAdapter(Mapping[str, object], config=ConfigDict(hide_i _INT: Final = TypeAdapter(int) +@with_config(ConfigDict(extra="allow", strict=True)) +class _PerplexityEmbeddingResponse(TypedDict, total=False): + model: ReadOnly[str | None] + object: ReadOnly[Literal["list"]] + data: ReadOnly[Sequence[builtins.object] | Mapping[str, builtins.object] | Literal[""]] + usage: ReadOnly[builtins.object] + + +_EMBEDDING_RESPONSE_ADAPTER: Final = TypeAdapter(_PerplexityEmbeddingResponse) + + class PerplexityEmbeddingError(BaseLLMException): def __init__( self, @@ -153,14 +166,18 @@ class PerplexityEmbeddingConfig(BaseEmbeddingConfig): litellm_params: dict = {}, ) -> EmbeddingResponse: try: - raw_response_json: Final = raw_response.json() + raw_response_json: Final[object] = raw_response.json() except Exception: raise PerplexityEmbeddingError(message=raw_response.text, status_code=raw_response.status_code) - model_response.model = raw_response_json.get("model", model) - model_response.object = raw_response_json.get("object", "list") + response_data: Final[_PerplexityEmbeddingResponse] = _EMBEDDING_RESPONSE_ADAPTER.validate_python( + raw_response_json + ) - raw_data: Final = raw_response_json.get("data", []) + model_response.model = response_data.get("model", model) + model_response.object = response_data.get("object", "list") + + raw_data: Final = response_data.get("data", []) decoded_data: Final[list[dict[str, object]]] = [] for item in raw_data: decoded_item = dict(_JSON_OBJECT.validate_python(item)) @@ -168,7 +185,7 @@ class PerplexityEmbeddingConfig(BaseEmbeddingConfig): decoded_data.append(decoded_item) model_response.data = decoded_data - usage_data: Final = _JSON_OBJECT.validate_python(raw_response_json.get("usage", {})) + usage_data: Final = _JSON_OBJECT.validate_python(response_data.get("usage", {})) usage: Final = Usage( prompt_tokens=_INT.validate_python( usage_data.get("prompt_tokens", 0) or usage_data.get("total_tokens", 0) or 0 diff --git a/litellm/llms/perplexity/responses/transformation.py b/litellm/llms/perplexity/responses/transformation.py index 77817a5e5bb..58f71028451 100644 --- a/litellm/llms/perplexity/responses/transformation.py +++ b/litellm/llms/perplexity/responses/transformation.py @@ -17,7 +17,7 @@ from pydantic import TypeAdapter from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj from litellm.litellm_core_utils.url_utils import join_api_base from litellm.llms.base_llm.chat.transformation import BaseLLMException -from litellm.llms.openai.responses.transformation import OpenAIResponsesAPIConfig +from litellm.llms.openai.responses.transformation import OpenAIResponsesAPIConfig, drops_params from litellm.secret_managers.main import get_secret_str from litellm.types.llms.openai import ResponseInputParam, ResponsesAPIResponse from litellm.types.router import GenericLiteLLMParams @@ -84,7 +84,7 @@ class PerplexityResponsesConfig(OpenAIResponsesAPIConfig): """Handle preset/ model prefix: send as {"preset": name} instead of {"model": name}.""" input = self._ensure_message_type(input) if model.startswith("preset/"): - input = self._validate_input_param(input) + input = self._validate_input_param(input, drops_set_created_by=drops_params(litellm_params)) data: Final[dict] = { "preset": model[len("preset/") :], "input": input, diff --git a/litellm/llms/predibase/chat/handler.py b/litellm/llms/predibase/chat/handler.py index d0a61ea6e00..2ba4a63e08b 100644 --- a/litellm/llms/predibase/chat/handler.py +++ b/litellm/llms/predibase/chat/handler.py @@ -14,6 +14,7 @@ from litellm.llms.custom_httpx.http_handler import ( AsyncHTTPHandler, get_async_httpx_client, ) +from litellm.llms.custom_httpx.sse_lines import aiter_sse_lines, iter_sse_lines from litellm.utils import CustomStreamWrapper, ModelResponse from ..common_utils import PredibaseError @@ -34,7 +35,7 @@ async def make_call( if response.status_code != 200: raise PredibaseError(status_code=response.status_code, message=response.text) - completion_stream: Final = response.aiter_lines() + completion_stream: Final = aiter_sse_lines(response.aiter_text()) # LOGGING logging_obj.post_call( input=messages, @@ -163,7 +164,7 @@ class PredibaseChatCompletion: timeout=timeout, ) _response: Final = CustomStreamWrapper( - response.iter_lines(), + iter_sse_lines(response.iter_text()), model, custom_llm_provider="predibase", logging_obj=logging_obj, diff --git a/litellm/llms/tencent/cost_calculator.py b/litellm/llms/tencent/cost_calculator.py index d9aebdc3284..5d2abe3acf4 100644 --- a/litellm/llms/tencent/cost_calculator.py +++ b/litellm/llms/tencent/cost_calculator.py @@ -1,6 +1,49 @@ -from litellm.litellm_core_utils.llm_cost_calc.utils import generic_cost_per_token -from litellm.types.utils import Usage +from typing import Final + +from litellm.litellm_core_utils.llm_cost_calc.utils import ( + calculate_image_response_cost_from_usage, + flat_image_cost, + generic_cost_per_token, + resolve_image_model_info, +) +from litellm.types.utils import ImageResponse, ModelInfo, Usage def cost_per_token(model: str, usage: Usage) -> tuple[float, float]: return generic_cost_per_token(model=model, usage=usage, custom_llm_provider="tencent") + + +def _deployment_image_token_pricing(model_info: ModelInfo | None) -> ModelInfo | None: + if model_info is None or model_info.get("output_cost_per_image_token") is not None: + return model_info + output_cost_per_token: Final = model_info.get("output_cost_per_token") + if output_cost_per_token is None: + return model_info + priced: Final[ModelInfo] = {**model_info, "output_cost_per_image_token": output_cost_per_token} + return priced + + +def _deployment_prices_per_image_only(model_info: ModelInfo | None) -> bool: + return ( + model_info is not None + and model_info.get("output_cost_per_image") is not None + and model_info.get("output_cost_per_image_token") is None + and model_info.get("output_cost_per_token") is None + ) + + +def image_cost_calculator(model: str, image_response: ImageResponse, model_info: ModelInfo | None = None) -> float: + resolved_model_info: Final = resolve_image_model_info( + model=model, custom_llm_provider="tencent", model_info=_deployment_image_token_pricing(model_info) + ) + if _deployment_prices_per_image_only(model_info): + return flat_image_cost(resolved_model_info, image_response) + token_based_cost: Final = calculate_image_response_cost_from_usage( + model=model, + image_response=image_response, + custom_llm_provider="tencent", + model_info=resolved_model_info, + ) + if token_based_cost is not None: + return token_based_cost + return flat_image_cost(resolved_model_info, image_response) diff --git a/litellm/llms/tencent/image_edit/__init__.py b/litellm/llms/tencent/image_edit/__init__.py new file mode 100644 index 00000000000..e69de29bb2d diff --git a/litellm/llms/tencent/image_edit/transformation.py b/litellm/llms/tencent/image_edit/transformation.py new file mode 100644 index 00000000000..3033d161ce7 --- /dev/null +++ b/litellm/llms/tencent/image_edit/transformation.py @@ -0,0 +1,147 @@ +from collections.abc import Mapping +from types import MappingProxyType +from typing import TYPE_CHECKING, Final, TypeAlias + +import httpx +from httpx._types import RequestFiles +from pydantic import TypeAdapter +from typing_extensions import override + +from litellm.images.utils import image_to_data_url +from litellm.llms.base_llm.chat.transformation import BaseLLMException +from litellm.llms.base_llm.image_edit.transformation import BaseImageEditConfig +from litellm.llms.tencent.image_generation.transformation import ( + TOKENHUB_IMAGE_PARAMS, + tokenhub_image_headers, + tokenhub_image_params, + tokenhub_image_response, + tokenhub_image_url, +) +from litellm.types.images.main import ImageEditOptionalRequestParams +from litellm.types.router import GenericLiteLLMParams +from litellm.types.utils import ImageResponse + +if TYPE_CHECKING: + from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj + +_IMAGES: Final = TypeAdapter(tuple[object, ...]) +_FORM_BOOLEANS: Final = MappingProxyType({"true": True, "false": False}) +_OPENAI_PARAMS: Final = frozenset(TOKENHUB_IMAGE_PARAMS) + +_FormEntries: TypeAlias = tuple[tuple[tuple[str, ...], object], ...] + + +def _form_scalar(value: object) -> object: + match value: + case str() if value.lower() in _FORM_BOOLEANS: + return _FORM_BOOLEANS[value.lower()] + case str() if value.removeprefix("-").isdigit(): + return int(value) + case _: + return value + + +def _form_path(key: str) -> tuple[str, ...]: + root, bracket, rest = key.partition("[") + if not bracket or not rest.endswith("]"): + return (key,) + return (root, *rest.removesuffix("]").split("][")) + + +def _nested_form_value(entries: _FormEntries) -> object: + match entries: + case (((), value),): + return _form_scalar(value) + case _: + return _nested_form_fields(tuple(entry for entry in entries if entry[0])) + + +def _nested_form_fields(entries: _FormEntries) -> Mapping[str, object]: + roots: Final = tuple(dict.fromkeys(path[0] for path, _ in entries)) + return { + root: _nested_form_value(tuple((path[1:], value) for path, value in entries if path[0] == root)) + for root in roots + } + + +def _tokenhub_form_params(params: Mapping[str, object]) -> Mapping[str, object]: + tokenhub_entries: Final = tuple( + (_form_path(key), value) for key, value in params.items() if key not in _OPENAI_PARAMS + ) + return { + **{key: value for key, value in params.items() if key in _OPENAI_PARAMS}, + **_nested_form_fields(tokenhub_entries), + } + + +class TencentImageEditConfig(BaseImageEditConfig): + @override + def get_supported_openai_params(self, model: str) -> list[str]: # mutable-ok: mirrors override contract + return list(TOKENHUB_IMAGE_PARAMS) + + @override + def map_openai_params( + self, + image_edit_optional_params: ImageEditOptionalRequestParams, + model: str, + drop_params: bool, + ) -> dict[str, object]: # mutable-ok: mirrors override contract + return dict(tokenhub_image_params(image_edit_optional_params, model, drop_params)) + + @override + def validate_environment( + self, + headers: Mapping[str, str], + model: str, + api_key: str | None = None, + litellm_params: Mapping[str, object] | None = None, + api_base: str | None = None, + ) -> dict[str, str]: # mutable-ok: mirrors override contract + return dict(tokenhub_image_headers(headers, api_key, model)) + + @override + def get_complete_url( + self, + model: str, + api_base: str | None, + litellm_params: Mapping[str, object], + ) -> str: + return tokenhub_image_url(api_base) + + @override + def use_multipart_form_data(self) -> bool: + return False + + @override + def transform_image_edit_request( + self, + model: str, + prompt: str | None, + image: object, + image_edit_optional_request_params: Mapping[str, object], + litellm_params: GenericLiteLLMParams, + headers: Mapping[str, str], + ) -> tuple[dict[str, object], RequestFiles]: # mutable-ok: mirrors override contract + images: Final = _IMAGES.validate_python(image) if isinstance(image, list) else (image,) + return { + "model": model, + "prompt": prompt, + "images": tuple(image_to_data_url(img) for img in images if img is not None), + **_tokenhub_form_params(image_edit_optional_request_params), + }, () + + @override + def transform_image_edit_response( + self, + model: str, + raw_response: httpx.Response, + logging_obj: "LiteLLMLoggingObj", + ) -> ImageResponse: + image_response: Final = tokenhub_image_response(raw_response) + if image_response is None: + raise BaseLLMException( + status_code=raw_response.status_code, + message=raw_response.text, + headers=raw_response.headers, + ) + return image_response diff --git a/litellm/llms/tencent/image_generation/__init__.py b/litellm/llms/tencent/image_generation/__init__.py new file mode 100644 index 00000000000..e69de29bb2d diff --git a/litellm/llms/tencent/image_generation/transformation.py b/litellm/llms/tencent/image_generation/transformation.py new file mode 100644 index 00000000000..fb4b102e8be --- /dev/null +++ b/litellm/llms/tencent/image_generation/transformation.py @@ -0,0 +1,200 @@ +from collections.abc import Mapping, Sequence +from typing import TYPE_CHECKING, Final + +import httpx +from pydantic import BaseModel, ConfigDict, TypeAdapter, ValidationError +from typing_extensions import override + +from litellm.exceptions import AuthenticationError, UnsupportedParamsError +from litellm.litellm_core_utils.url_utils import ensure_api_route, join_api_base +from litellm.llms.base_llm.chat.transformation import BaseLLMException +from litellm.llms.base_llm.image_generation.transformation import ( + BaseImageGenerationConfig, +) +from litellm.secret_managers.main import get_secret_str +from litellm.types.llms.openai import ( + AllMessageValues, + OpenAIImageGenerationOptionalParams, +) +from litellm.types.utils import ( + ImageObject, + ImageResponse, + ImageUsage, + ImageUsageInputTokensDetails, + LlmProviders, +) + +if TYPE_CHECKING: + from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj + +TOKENHUB_API_BASE: Final = "https://tokenhub-intl.tencentcloudmaas.com/v1" +TOKENHUB_IMAGE_PATH: Final = "/wand/si-image/generation" +TOKENHUB_IMAGE_MODEL_PREFIX: Final = "seedream-" +TOKENHUB_IMAGE_PARAMS: Final[tuple[OpenAIImageGenerationOptionalParams, ...]] = ( + "n", + "size", + "response_format", + "output_format", + "background", + "user", +) + +_JSON_OBJECT: Final = TypeAdapter(Mapping[str, object], config=ConfigDict(hide_input_in_errors=True)) + + +class _TokenHubImage(BaseModel): + model_config = ConfigDict(frozen=True) + + url: str | None = None + b64_json: str | None = None + size: str | None = None + output_format: str | None = None + + +class _TokenHubUsage(BaseModel): + model_config = ConfigDict(frozen=True) + + total_tokens: int + + +class _TokenHubImageResponse(BaseModel): + model_config = ConfigDict(frozen=True, hide_input_in_errors=True) + + created: int + data: tuple[_TokenHubImage, ...] + tokenhub_usage: _TokenHubUsage | None = None + + +def is_tokenhub_image_model(model: str) -> bool: + return model.removeprefix(f"{LlmProviders.TENCENT.value}/").startswith(TOKENHUB_IMAGE_MODEL_PREFIX) + + +def tokenhub_image_url(api_base: str | None) -> str: + base: Final = api_base or get_secret_str("TENCENT_API_BASE") or TOKENHUB_API_BASE + return join_api_base(ensure_api_route(base, "v1"), TOKENHUB_IMAGE_PATH) + + +def tokenhub_image_headers(headers: Mapping[str, str], api_key: str | None, model: str) -> Mapping[str, str]: + resolved_api_key: Final = api_key or get_secret_str("TENCENT_API_KEY") + if not resolved_api_key: + raise AuthenticationError( + message="TENCENT_API_KEY is not set. Set it in the environment or pass api_key.", + llm_provider="tencent", + model=model, + ) + return {**headers, "Authorization": f"Bearer {resolved_api_key}", "Content-Type": "application/json"} + + +def tokenhub_image_params(params: Mapping[str, object], model: str, drop_params: bool) -> Mapping[str, object]: + n: Final = params.get("n") + if n is not None and n != 1 and not drop_params: + raise UnsupportedParamsError( + status_code=400, + message=f"Tencent TokenHub returns one image per request, so n={n} is not supported for {model}. " + + "To send n=1 instead, set `litellm.drop_params = True`.", + ) + return { + key: value + for key, value in params.items() + if key != "n" and value is not None and not (key == "background" and value == "auto") + } + + +def tokenhub_image_response(raw_response: httpx.Response) -> ImageResponse | None: + try: + parsed: Final = _TokenHubImageResponse.model_validate_json(raw_response.content) + except ValidationError: + return None + total_tokens: Final = parsed.tokenhub_usage.total_tokens if parsed.tokenhub_usage is not None else 0 + first_image: Final = parsed.data[0] if parsed.data else _TokenHubImage() + return ImageResponse( + created=parsed.created, + data=[ImageObject(url=image.url, b64_json=image.b64_json) for image in parsed.data], + size=first_image.size, + output_format=first_image.output_format, + usage=ImageUsage( + input_tokens=0, + input_tokens_details=ImageUsageInputTokensDetails(image_tokens=0, text_tokens=0), + output_tokens=total_tokens, + total_tokens=total_tokens, + ), + ) + + +class TencentImageGenerationConfig(BaseImageGenerationConfig): + @override + def get_supported_openai_params( + self, model: str + ) -> list[OpenAIImageGenerationOptionalParams]: # mutable-ok: mirrors override contract + return list(TOKENHUB_IMAGE_PARAMS) + + @override + def map_openai_params( + self, + non_default_params: Mapping[str, object], + optional_params: Mapping[str, object], + model: str, + drop_params: bool, + ) -> dict[str, object]: # mutable-ok: mirrors override contract + return {**optional_params, **tokenhub_image_params(non_default_params, model, drop_params)} + + @override + def get_complete_url( + self, + api_base: str | None, + api_key: str | None, + model: str, + optional_params: Mapping[str, object], + litellm_params: Mapping[str, object], + stream: bool | None = None, + ) -> str: + return tokenhub_image_url(api_base) + + @override + def validate_environment( + self, + headers: Mapping[str, str], + model: str, + messages: Sequence[AllMessageValues], + optional_params: Mapping[str, object], + litellm_params: Mapping[str, object], + api_key: str | None = None, + api_base: str | None = None, + ) -> dict[str, str]: # mutable-ok: mirrors override contract + return dict(tokenhub_image_headers(headers, api_key, model)) + + @override + def transform_image_generation_request( + self, + model: str, + prompt: str, + optional_params: Mapping[str, object], + litellm_params: Mapping[str, object], + headers: Mapping[str, str], + ) -> dict[str, object]: # mutable-ok: mirrors override contract + extra_body: Final = _JSON_OBJECT.validate_python(optional_params.get("extra_body") or {}) + params: Final = {key: value for key, value in optional_params.items() if key != "extra_body"} + return {"model": model, "prompt": prompt, **params, **extra_body} + + @override + def transform_image_generation_response( + self, + model: str, + raw_response: httpx.Response, + model_response: ImageResponse, + logging_obj: "LiteLLMLoggingObj", + request_data: Mapping[str, object], + optional_params: Mapping[str, object], + litellm_params: Mapping[str, object], + encoding: object, + api_key: str | None = None, + json_mode: bool | None = None, + ) -> ImageResponse: + image_response: Final = tokenhub_image_response(raw_response) + if image_response is None: + raise BaseLLMException( + status_code=raw_response.status_code, + message=raw_response.text, + headers=raw_response.headers, + ) + return image_response diff --git a/litellm/llms/vertex_ai/agent_engine/transformation.py b/litellm/llms/vertex_ai/agent_engine/transformation.py index 9f592398f74..0339533e1f5 100644 --- a/litellm/llms/vertex_ai/agent_engine/transformation.py +++ b/litellm/llms/vertex_ai/agent_engine/transformation.py @@ -22,6 +22,7 @@ from litellm.litellm_core_utils.prompt_templates.common_utils import ( convert_content_list_to_str, ) from litellm.llms.base_llm.chat.transformation import BaseConfig, BaseLLMException +from litellm.llms.custom_httpx.sse_lines import aiter_sse_lines, iter_sse_lines from litellm.llms.vertex_ai.agent_engine.sse_iterator import ( VertexAgentEngineResponseIterator, ) @@ -357,7 +358,7 @@ class VertexAgentEngineConfig(BaseConfig, VertexBase): ) -> VertexAgentEngineResponseIterator: """Return a streaming iterator for SSE responses.""" return VertexAgentEngineResponseIterator( - streaming_response=raw_response.iter_lines(), + streaming_response=iter_sse_lines(raw_response.iter_text()), sync_stream=True, ) @@ -465,7 +466,7 @@ class VertexAgentEngineConfig(BaseConfig, VertexBase): # Create iterator for SSE stream (async) completion_stream: Final = VertexAgentEngineResponseIterator( - streaming_response=response.aiter_lines(), + streaming_response=aiter_sse_lines(response.aiter_text()), sync_stream=False, ) diff --git a/litellm/llms/vertex_ai/common_utils.py b/litellm/llms/vertex_ai/common_utils.py index 27f2aedb300..0fa80cb2cad 100644 --- a/litellm/llms/vertex_ai/common_utils.py +++ b/litellm/llms/vertex_ai/common_utils.py @@ -1,3 +1,4 @@ +import math import re from collections.abc import Callable, Iterable, Mapping, Sequence from copy import deepcopy @@ -18,6 +19,11 @@ from litellm.constants import DEFAULT_MAX_RECURSE_DEPTH from litellm.litellm_core_utils.prompt_templates.common_utils import unpack_defs from litellm.llms.base_llm.base_utils import BaseLLMModelInfo, BaseTokenCounter from litellm.llms.base_llm.chat.transformation import BaseLLMException +from litellm.llms.gemini.common_utils import ( + GEMINI_IMAGE_ASPECT_RATIOS, + GEMINI_IMAGE_SIZE_TO_ASPECT_RATIO, + map_openai_size_to_gemini_image_config, +) from litellm.types.llms.openai import AllMessageValues from litellm.types.llms.vertex_ai import ( VERTEX_AI_PROVIDER_METADATA_FIELDS, @@ -35,6 +41,31 @@ GEMINI_VIDEO_METADATA_KEYS: Final = MappingProxyType( GEMINI_FILES_API_URI_PREFIX: Final = "https://generativelanguage.googleapis.com/v1beta/files/" +# https://cloud.google.com/vertex-ai/generative-ai/docs/image/configure-aspect-ratio +_IMAGEN_ASPECT_RATIOS: Final = MappingProxyType( + {"1:1": 1.0, "3:4": 3 / 4, "4:3": 4 / 3, "9:16": 9 / 16, "16:9": 16 / 9} +) + + +def map_vertex_image_size(size: object, model: str, *, imagen: bool = False) -> Mapping[str, str] | None: + if not isinstance(size, str) or (image_config := map_openai_size_to_gemini_image_config(size, model)) is None: + return None + + width, height = map(int, size.lower().split("x")) + requested_ratio: Final = width / height + aspect_ratio: Final = ( + min(_IMAGEN_ASPECT_RATIOS, key=lambda ratio: abs(math.log(_IMAGEN_ASPECT_RATIOS[ratio] / requested_ratio))) + if imagen + else image_config["aspectRatio"] + ) + if ( + not math.isclose(GEMINI_IMAGE_ASPECT_RATIOS[aspect_ratio], requested_ratio) + and GEMINI_IMAGE_SIZE_TO_ASPECT_RATIO.get((width, height)) != aspect_ratio + ): + verbose_logger.warning("Vertex AI size %s is approximated with aspectRatio %s", size, aspect_ratio) + return MappingProxyType({"aspectRatio": aspect_ratio} if imagen else image_config) + + def gemini_video_metadata_from_openai(video_metadata: Mapping[str, object]) -> dict[str, object]: return { gemini_key: video_metadata[openai_key] diff --git a/litellm/llms/vertex_ai/context_caching/vertex_ai_context_caching.py b/litellm/llms/vertex_ai/context_caching/vertex_ai_context_caching.py index 5bff43828d6..884c82fe331 100644 --- a/litellm/llms/vertex_ai/context_caching/vertex_ai_context_caching.py +++ b/litellm/llms/vertex_ai/context_caching/vertex_ai_context_caching.py @@ -1,4 +1,5 @@ from collections.abc import Sequence +from dataclasses import dataclass from typing import Final, Literal import httpx @@ -8,7 +9,6 @@ from typing_extensions import NotRequired, ReadOnly, TypedDict import litellm from litellm._logging import verbose_logger from litellm.caching.caching import Cache, LiteLLMCacheType -from litellm.constants import MINIMUM_PROMPT_CACHE_TOKEN_COUNT from litellm.litellm_core_utils.litellm_logging import Logging from litellm.llms.custom_httpx.http_handler import ( AsyncHTTPHandler, @@ -16,10 +16,11 @@ from litellm.llms.custom_httpx.http_handler import ( get_async_httpx_client, ) from litellm.llms.openai.openai import AllMessageValues -from litellm.utils import is_prompt_caching_valid_prompt +from litellm.types.llms.openai import ChatCompletionToolParam +from litellm.utils import get_prompt_cache_min_tokens, is_prompt_caching_valid_prompt from ..common_utils import VertexAIError, get_vertex_base_url -from ..vertex_llm_base import VertexBase +from ..vertex_llm_base import VertexBase, publisher_model_location from .known_cached_contents import KnownCachedContents, known_cached_contents from .transformation import ( cached_messages_end_on_supported_turn, @@ -65,6 +66,19 @@ class _CreatedCachedContentRoot(RootModel[_CreatedCachedContent]): model_config = ConfigDict(frozen=True, hide_input_in_errors=True) +_TOOL_PARAMS: Final = ("tools", "tool_choice") + + +def _sync_cache_client(timeout: float | httpx.Timeout | None) -> HTTPHandler: + if timeout is None: + return HTTPHandler() + return HTTPHandler(timeout=httpx.Timeout(timeout) if isinstance(timeout, (float, int)) else timeout) + + +class _CachedContentsNotServedError(VertexAIError): + pass + + def _record_cache_creation_tokens(logging_obj: Logging, created: _CreatedCachedContent) -> None: tokens: Final = (created.get("usageMetadata") or {}).get("totalTokenCount") or 0 logging_obj.vertex_ai_cache_creation_input_tokens = max(tokens, 0) # rebind-ok: set provider count @@ -78,6 +92,61 @@ def _wait_seconds(timeout: float | httpx.Timeout | None) -> float | None: return timeout +@dataclass(frozen=True, slots=True) +class _CacheTarget: + model: str + project: str | None + location: str | None + + +def _cache_target( + custom_llm_provider: Literal["vertex_ai", "vertex_ai_beta", "gemini"], + api_base: str | None, + model: str, + vertex_project: str | None, + vertex_location: str | None, +) -> _CacheTarget: + model_location: Final = ( + None if custom_llm_provider == "gemini" or api_base is None else publisher_model_location(api_base) + ) + if model_location is None: + return _CacheTarget(model=model, project=vertex_project, location=vertex_location) + return _CacheTarget(model=model_location.model, project=model_location.project, location=model_location.location) + + +def _prompt_cache_min_tokens(models: Sequence[str], custom_llm_provider: str) -> int: + return max( + get_prompt_cache_min_tokens( + model if model.startswith(custom_llm_provider) else f"{custom_llm_provider}/{model}" + ) + for model in models + ) + + +def _context_caching_skip_reason( + cached_messages: Sequence[AllMessageValues], + tools: Sequence[ChatCompletionToolParam] | None, + deployment_model: str, + cache_model: str, + custom_llm_provider: Literal["vertex_ai", "vertex_ai_beta", "gemini"], +) -> str | None: + if not cached_messages_end_on_supported_turn(cached_messages): + return ( + "Vertex AI context caching: cached message block ends on a model turn once " + "system messages are extracted, which the cachedContents API rejects." + ) + min_tokens: Final = _prompt_cache_min_tokens((deployment_model, cache_model), custom_llm_provider) + if not is_prompt_caching_valid_prompt( + model=cache_model, + messages=list(cached_messages), + tools=None if tools is None else list(tools), + custom_llm_provider=custom_llm_provider, + min_token_count=min_tokens, + ): + return f"Vertex AI context caching: cached content is below minimum token count ({min_tokens})." + return None + + class ContextCachingEndpoints(VertexBase): """ Covers context caching endpoints for Vertex AI + Google AI Studio @@ -135,6 +204,7 @@ class ContextCachingEndpoints(VertexBase): vertex_project=vertex_project, vertex_location=vertex_location, vertex_api_version=("v1beta1" if custom_llm_provider == "vertex_ai_beta" else "v1"), + collection_endpoint=True, ) def check_cache( @@ -206,6 +276,8 @@ class ContextCachingEndpoints(VertexBase): except httpx.HTTPStatusError as e: if e.response.status_code == 403: return None + if e.response.status_code == 404 and custom_llm_provider == "gemini": + raise _CachedContentsNotServedError(status_code=404, message=e.response.text) raise VertexAIError(status_code=e.response.status_code, message=e.response.text) except Exception as e: raise VertexAIError(status_code=500, message=str(e)) @@ -305,6 +377,8 @@ class ContextCachingEndpoints(VertexBase): except httpx.HTTPStatusError as e: if e.response.status_code == 403: return None + if e.response.status_code == 404 and custom_llm_provider == "gemini": + raise _CachedContentsNotServedError(status_code=404, message=e.response.text) raise VertexAIError(status_code=e.response.status_code, message=e.response.text) except Exception as e: raise VertexAIError(status_code=500, message=str(e)) @@ -370,41 +444,25 @@ class ContextCachingEndpoints(VertexBase): if len(cached_messages) == 0: return messages, optional_params, None - if not cached_messages_end_on_supported_turn(cached_messages): - verbose_logger.debug( - "Vertex AI context caching: cached message block ends on a model turn once " - "system messages are extracted, which the cachedContents API rejects. " - "Skipping context caching." - ) + target: Final = _cache_target(custom_llm_provider, api_base, model, vertex_project, vertex_location) + tools: Final = optional_params.get("tools") + tool_choice: Final = optional_params.get("tool_choice") + skip_reason: Final = _context_caching_skip_reason( + cached_messages, tools, model, target.model, custom_llm_provider + ) + if skip_reason is not None: + verbose_logger.debug("%s Skipping context caching.", skip_reason) return messages, optional_params, None - # Gemini requires a minimum of 1024 tokens for context caching. - # Skip caching if the cached content is too small to avoid API errors. - if not is_prompt_caching_valid_prompt( - model=model, - messages=cached_messages, - tools=optional_params.get("tools"), - custom_llm_provider=custom_llm_provider, - ): - verbose_logger.debug( - "Vertex AI context caching: cached content is below minimum token " - "count (%d). Skipping context caching.", - MINIMUM_PROMPT_CACHE_TOKEN_COUNT, - ) - return messages, optional_params, None - - tools: Final = optional_params.pop("tools", None) - tool_choice: Final = optional_params.pop("tool_choice", None) - ## AUTHORIZATION ## token, url = self._get_token_and_url_context_caching( gemini_api_key=api_key, custom_llm_provider=custom_llm_provider, api_base=api_base, - vertex_project=vertex_project, - vertex_location=vertex_location, + vertex_project=target.project, + vertex_location=target.location, vertex_auth_header=vertex_auth_header, - model=model, + model=target.model, ) headers: Final = { @@ -417,44 +475,42 @@ class ContextCachingEndpoints(VertexBase): if extra_headers is not None: headers.update(extra_headers) - if client is None or not isinstance(client, HTTPHandler): - _params: Final = {} - if timeout is not None: - if isinstance(timeout, float) or isinstance(timeout, int): - timeout = httpx.Timeout(timeout) - _params["timeout"] = timeout - client = HTTPHandler(**_params) - else: - client = client + http_client: Final = client if isinstance(client, HTTPHandler) else _sync_cache_client(timeout) ## CHECK IF CACHED ALREADY generated_cache_key: Final = local_cache_obj.get_cache_key( - messages=cached_messages, tools=tools, tool_choice=tool_choice, model=model - ) - google_cache_name: Final = self.check_cache( - cache_key=generated_cache_key, - client=client, - headers=headers, - api_key=api_key, - api_base=api_base, - logging_obj=logging_obj, - custom_llm_provider=custom_llm_provider, - vertex_project=vertex_project, - vertex_location=vertex_location, - vertex_auth_header=vertex_auth_header, - model=model, + messages=cached_messages, tools=tools, tool_choice=tool_choice, model=target.model ) + try: + google_cache_name: Final = self.check_cache( + cache_key=generated_cache_key, + client=http_client, + headers=headers, + api_key=api_key, + api_base=api_base, + logging_obj=logging_obj, + custom_llm_provider=custom_llm_provider, + vertex_project=target.project, + vertex_location=target.location, + vertex_auth_header=vertex_auth_header, + model=target.model, + ) + except _CachedContentsNotServedError: + verbose_logger.debug("Gemini context caching: %s answers 404. Skipping context caching.", url) + return messages, optional_params, None + for tool_param in _TOOL_PARAMS: + optional_params.pop(tool_param, None) if google_cache_name: return non_cached_messages, optional_params, google_cache_name ## TRANSFORM REQUEST cached_content_request_body: Final = transform_openai_messages_to_gemini_context_caching( - model=model, + model=target.model, messages=cached_messages, cache_key=generated_cache_key, custom_llm_provider=custom_llm_provider, - vertex_project=vertex_project, - vertex_location=vertex_location, + vertex_project=target.project, + vertex_location=target.location, ) cached_content_request_body["tools"] = tools @@ -473,7 +529,7 @@ class ContextCachingEndpoints(VertexBase): ) try: - response: Final = client.post( + response: Final = http_client.post( url=url, headers=headers, json=cached_content_request_body, @@ -489,7 +545,7 @@ class ContextCachingEndpoints(VertexBase): _record_cache_creation_tokens(logging_obj, raw_response_cached) self._known_caches.remember( KnownCachedContents.scope( - url, custom_llm_provider, headers, vertex_project=vertex_project, vertex_location=vertex_location + url, custom_llm_provider, headers, vertex_project=target.project, vertex_location=target.location ), generated_cache_key, raw_response_cached.get("name"), @@ -536,41 +592,25 @@ class ContextCachingEndpoints(VertexBase): if len(cached_messages) == 0: return messages, optional_params, None - if not cached_messages_end_on_supported_turn(cached_messages): - verbose_logger.debug( - "Vertex AI context caching: cached message block ends on a model turn once " - "system messages are extracted, which the cachedContents API rejects. " - "Skipping context caching." - ) + target: Final = _cache_target(custom_llm_provider, api_base, model, vertex_project, vertex_location) + tools: Final = optional_params.get("tools") + tool_choice: Final = optional_params.get("tool_choice") + skip_reason: Final = _context_caching_skip_reason( + cached_messages, tools, model, target.model, custom_llm_provider + ) + if skip_reason is not None: + verbose_logger.debug("%s Skipping context caching.", skip_reason) return messages, optional_params, None - # Gemini requires a minimum of 1024 tokens for context caching. - # Skip caching if the cached content is too small to avoid API errors. - if not is_prompt_caching_valid_prompt( - model=model, - messages=cached_messages, - tools=optional_params.get("tools"), - custom_llm_provider=custom_llm_provider, - ): - verbose_logger.debug( - "Vertex AI context caching: cached content is below minimum token " - "count (%d). Skipping context caching.", - MINIMUM_PROMPT_CACHE_TOKEN_COUNT, - ) - return messages, optional_params, None - - tools: Final = optional_params.pop("tools", None) - tool_choice: Final = optional_params.pop("tool_choice", None) - ## AUTHORIZATION ## token, url = self._get_token_and_url_context_caching( gemini_api_key=api_key, custom_llm_provider=custom_llm_provider, api_base=api_base, - vertex_project=vertex_project, - vertex_location=vertex_location, + vertex_project=target.project, + vertex_location=target.location, vertex_auth_header=vertex_auth_header, - model=model, + model=target.model, ) headers: Final = { @@ -590,10 +630,10 @@ class ContextCachingEndpoints(VertexBase): ## CHECK IF CACHED ALREADY generated_cache_key: Final = local_cache_obj.get_cache_key( - messages=cached_messages, tools=tools, tool_choice=tool_choice, model=model + messages=cached_messages, tools=tools, tool_choice=tool_choice, model=target.model ) scope: Final = KnownCachedContents.scope( - url, custom_llm_provider, headers, vertex_project=vertex_project, vertex_location=vertex_location + url, custom_llm_provider, headers, vertex_project=target.project, vertex_location=target.location ) async def lookup_or_create() -> str | None: @@ -605,10 +645,10 @@ class ContextCachingEndpoints(VertexBase): api_base=api_base, logging_obj=logging_obj, custom_llm_provider=custom_llm_provider, - vertex_project=vertex_project, - vertex_location=vertex_location, + vertex_project=target.project, + vertex_location=target.location, vertex_auth_header=vertex_auth_header, - model=model, + model=target.model, ) if google_cache_name: @@ -616,12 +656,12 @@ class ContextCachingEndpoints(VertexBase): ## TRANSFORM REQUEST cached_content_request_body: Final = transform_openai_messages_to_gemini_context_caching( - model=model, + model=target.model, messages=cached_messages, cache_key=generated_cache_key, custom_llm_provider=custom_llm_provider, - vertex_project=vertex_project, - vertex_location=vertex_location, + vertex_project=target.project, + vertex_location=target.location, ) cached_content_request_body["tools"] = tools @@ -659,9 +699,15 @@ class ContextCachingEndpoints(VertexBase): ) return raw_response_cached.get("name") - cache_name: Final = await self._known_caches.single_flight( - scope, generated_cache_key, lookup_or_create, _wait_seconds(timeout) - ) + try: + cache_name: Final = await self._known_caches.single_flight( + scope, generated_cache_key, lookup_or_create, _wait_seconds(timeout) + ) + except _CachedContentsNotServedError: + verbose_logger.debug("Gemini context caching: %s answers 404. Skipping context caching.", url) + return messages, optional_params, None + for tool_param in _TOOL_PARAMS: + optional_params.pop(tool_param, None) return non_cached_messages, optional_params, cache_name def get_cache(self): diff --git a/litellm/llms/vertex_ai/gemini/vertex_and_google_ai_studio_gemini.py b/litellm/llms/vertex_ai/gemini/vertex_and_google_ai_studio_gemini.py index 9acbc9c459c..c506192f253 100644 --- a/litellm/llms/vertex_ai/gemini/vertex_and_google_ai_studio_gemini.py +++ b/litellm/llms/vertex_ai/gemini/vertex_and_google_ai_studio_gemini.py @@ -41,6 +41,7 @@ from litellm.llms.custom_httpx.http_handler import ( get_async_httpx_client, get_httpx_client, ) +from litellm.llms.custom_httpx.sse_lines import aiter_sse_lines, iter_sse_lines from litellm.types.llms.anthropic import AnthropicThinkingParam from litellm.types.llms.base import CachedTokensDetails from litellm.types.llms.gemini import BidiGenerateContentServerMessage @@ -2743,10 +2744,10 @@ class VertexGeminiConfig(VertexAIBaseConfig, BaseConfig): chunk_indices = support.get("groundingChunkIndices", []) if start_index is not None and end_index is not None and chunk_indices: - # Use the first chunk's URL for the annotation - first_chunk_idx = chunk_indices[0] - if first_chunk_idx in chunk_to_uri_map: - uri_info = chunk_to_uri_map[first_chunk_idx] + for chunk_index in chunk_indices: + if chunk_index not in chunk_to_uri_map: + continue + uri_info = chunk_to_uri_map[chunk_index] url_citation: ChatCompletionAnnotationURLCitation = { "start_index": start_index, @@ -3241,7 +3242,7 @@ async def make_call( raise completion_stream: Final = ModelResponseIterator( - streaming_response=response.aiter_lines(), + streaming_response=aiter_sse_lines(response.aiter_text()), sync_stream=False, logging_obj=logging_obj, response_headers=response.headers, @@ -3312,7 +3313,7 @@ def make_sync_call( raise completion_stream: Final = ModelResponseIterator( - streaming_response=response.iter_lines(), + streaming_response=iter_sse_lines(response.iter_text()), sync_stream=True, logging_obj=logging_obj, response_headers=response.headers, @@ -4190,7 +4191,7 @@ class ModelResponseIterator: log_failed_hop(e) return self._truncated_stream_end(token) self._start_hop(hop_response, token) - self.streaming_response = hop_response.aiter_lines() + self.streaming_response = aiter_sse_lines(hop_response.aiter_text()) self.async_response_iterator = self.streaming_response return None @@ -4204,7 +4205,7 @@ class ModelResponseIterator: log_failed_hop(e) return self._truncated_stream_end(token) self._start_hop(hop_response, token) - self.streaming_response = hop_response.iter_lines() + self.streaming_response = iter_sse_lines(hop_response.iter_text()) self.response_iterator = self.streaming_response return None diff --git a/litellm/llms/vertex_ai/image_edit/vertex_gemini_transformation.py b/litellm/llms/vertex_ai/image_edit/vertex_gemini_transformation.py index 6d071363823..0b90f74ea6d 100644 --- a/litellm/llms/vertex_ai/image_edit/vertex_gemini_transformation.py +++ b/litellm/llms/vertex_ai/image_edit/vertex_gemini_transformation.py @@ -10,7 +10,7 @@ from httpx._types import RequestFiles import litellm from litellm.images.utils import ImageEditRequestUtils from litellm.llms.base_llm.image_edit.transformation import BaseImageEditConfig -from litellm.llms.vertex_ai.common_utils import get_vertex_base_url +from litellm.llms.vertex_ai.common_utils import get_vertex_base_url, map_vertex_image_size from litellm.llms.vertex_ai.gemini.vertex_and_google_ai_studio_gemini import VertexLLM from litellm.secret_managers.main import get_secret_str from litellm.types.images.main import ImageEditOptionalRequestParams @@ -67,7 +67,7 @@ class VertexAIGeminiImageEditConfig(BaseImageEditConfig, VertexLLM): return {} size: Final = image_edit_optional_params.get("size") - return {"aspectRatio": self._map_size_to_aspect_ratio(size or "")} + return dict(map_vertex_image_size(size, model) or {"aspectRatio": "1:1"}) def _resolve_vertex_project(self) -> str | None: return ( @@ -176,11 +176,11 @@ class VertexAIGeminiImageEditConfig(BaseImageEditConfig, VertexLLM): contents: Final[dict[str, object]] = {"role": "USER", "parts": parts} # Add image-specific configuration - image_config: Final = ( - {"aspect_ratio": image_edit_optional_request_params["aspectRatio"]} - if "aspectRatio" in image_edit_optional_request_params - else None - ) + image_config: Final = { + field: image_edit_optional_request_params[param] + for param, field in (("aspectRatio", "aspect_ratio"), ("imageSize", "image_size")) + if param in image_edit_optional_request_params + } generation_config: Final[dict[str, object]] = { key: value for key, value in (("response_modalities", ["IMAGE"]), ("image_config", image_config)) if value @@ -222,17 +222,6 @@ class VertexAIGeminiImageEditConfig(BaseImageEditConfig, VertexLLM): model_response.data = cast(list[OpenAIImage], data_list) return model_response - def _map_size_to_aspect_ratio(self, size: str) -> str: - """Map OpenAI size format to Gemini aspect ratio format""" - aspect_ratio_map: Final = { - "1024x1024": "1:1", - "1792x1024": "16:9", - "1024x1792": "9:16", - "1280x896": "4:3", - "896x1280": "3:4", - } - return aspect_ratio_map.get(size, "1:1") - def _prepare_inline_image_parts(self, image: FileTypes | list[FileTypes]) -> list[HttpxPartType]: images: Final[list[FileTypes]] = image if isinstance(image, list) else [image] return [ diff --git a/litellm/llms/vertex_ai/image_edit/vertex_imagen_transformation.py b/litellm/llms/vertex_ai/image_edit/vertex_imagen_transformation.py index deaa32f7308..87b0dfdbcbc 100644 --- a/litellm/llms/vertex_ai/image_edit/vertex_imagen_transformation.py +++ b/litellm/llms/vertex_ai/image_edit/vertex_imagen_transformation.py @@ -15,7 +15,7 @@ import litellm from litellm.constants import DEFAULT_MAX_RECURSE_DEPTH from litellm.litellm_core_utils.url_utils import join_api_base from litellm.llms.base_llm.image_edit.transformation import BaseImageEditConfig -from litellm.llms.vertex_ai.common_utils import get_vertex_base_url +from litellm.llms.vertex_ai.common_utils import get_vertex_base_url, map_vertex_image_size from litellm.llms.vertex_ai.gemini.vertex_and_google_ai_studio_gemini import VertexLLM from litellm.secret_managers.main import get_secret_str from litellm.types.images.main import ImageEditOptionalRequestParams @@ -70,13 +70,11 @@ class VertexAIImagenImageEditConfig(BaseImageEditConfig, VertexLLM): if "n" in filtered_params: mapped_params["sampleCount"] = filtered_params["n"] - if "size" in filtered_params: - mapped_params["aspectRatio"] = self._map_size_to_aspect_ratio(filtered_params["size"]) - if "mask" in filtered_params: mapped_params["mask"] = filtered_params["mask"] - return mapped_params + size_params: Final = map_vertex_image_size(filtered_params.get("size"), model, imagen=True) or {} + return {**mapped_params, **size_params} def _resolve_vertex_project(self) -> str | None: return ( @@ -189,6 +187,11 @@ class VertexAIImagenImageEditConfig(BaseImageEditConfig, VertexLLM): "sampleCount": sample_count, "editMode": edit_mode, "editConfig": {"baseSteps": base_steps}, + **( + {"aspectRatio": image_edit_optional_request_params["aspectRatio"]} + if "aspectRatio" in image_edit_optional_request_params + else {} + ), } # Set default values for Vertex AI-specific parameters (not configurable by users via OpenAI API) @@ -239,17 +242,6 @@ class VertexAIImagenImageEditConfig(BaseImageEditConfig, VertexLLM): model_response.data = cast(list[OpenAIImage], data_list) return model_response - def _map_size_to_aspect_ratio(self, size: str) -> str: - """Map OpenAI size format to Imagen aspect ratio format""" - aspect_ratio_map: Final = { - "1024x1024": "1:1", - "1792x1024": "16:9", - "1024x1792": "9:16", - "1280x896": "4:3", - "896x1280": "3:4", - } - return aspect_ratio_map.get(size, "1:1") - def _prepare_reference_images( self, image: FileTypes | list[FileTypes], diff --git a/litellm/llms/vertex_ai/image_generation/vertex_gemini_transformation.py b/litellm/llms/vertex_ai/image_generation/vertex_gemini_transformation.py index f6df772dd56..e1049ef8ece 100644 --- a/litellm/llms/vertex_ai/image_generation/vertex_gemini_transformation.py +++ b/litellm/llms/vertex_ai/image_generation/vertex_gemini_transformation.py @@ -14,7 +14,7 @@ from litellm.llms.gemini.common_utils import ( get_gemini_image_web_search_requests, map_gemini_image_tools_params, ) -from litellm.llms.vertex_ai.common_utils import get_vertex_base_url +from litellm.llms.vertex_ai.common_utils import get_vertex_base_url, map_vertex_image_size from litellm.llms.vertex_ai.gemini.vertex_and_google_ai_studio_gemini import VertexLLM from litellm.secret_managers.main import get_secret_str from litellm.types.llms.openai import AllMessageValues @@ -89,8 +89,7 @@ class VertexAIGeminiImageGenerationConfig(BaseImageGenerationConfig, VertexLLM): if k == "n": mapped_params["candidate_count"] = v elif k == "size": - # Map OpenAI size format to Gemini aspectRatio - mapped_params["aspectRatio"] = self._map_size_to_aspect_ratio(v) + continue elif k in ("aspectRatio", "aspect_ratio"): mapped_params["aspectRatio"] = v elif k in ("imageSize", "image_size"): @@ -103,22 +102,23 @@ class VertexAIGeminiImageGenerationConfig(BaseImageGenerationConfig, VertexLLM): elif k not in ("tools", "web_search_options", "imageConfig"): mapped_params[k] = v + if "size" in non_default_params and "size" not in optional_params: + image_params: Final = _JSON_OBJECT.validate_python(mapped_params) + image_config: Final = _JSON_OBJECT.validate_python(image_params.get("imageConfig", {})) + size_params: Final = { + key: value + for key, value in ( + map_vertex_image_size(non_default_params["size"], model) or {"aspectRatio": "1:1"} + ).items() + if key not in image_config + } + return map_gemini_image_tools_params( + _JSON_OBJECT.validate_python(non_default_params), {**size_params, **image_params} + ) + mapped_params = map_gemini_image_tools_params(non_default_params, mapped_params) return mapped_params - def _map_size_to_aspect_ratio(self, size: str) -> str: - """ - Map OpenAI size format to Gemini aspect ratio format - """ - aspect_ratio_map: Final = { - "1024x1024": "1:1", - "1792x1024": "16:9", - "1024x1792": "9:16", - "1280x896": "4:3", - "896x1280": "3:4", - } - return aspect_ratio_map.get(size, "1:1") - def _resolve_vertex_project(self) -> str | None: return ( getattr(self, "_vertex_project", None) diff --git a/litellm/llms/vertex_ai/image_generation/vertex_imagen_transformation.py b/litellm/llms/vertex_ai/image_generation/vertex_imagen_transformation.py index 927c7b74e67..daf87b1ec58 100644 --- a/litellm/llms/vertex_ai/image_generation/vertex_imagen_transformation.py +++ b/litellm/llms/vertex_ai/image_generation/vertex_imagen_transformation.py @@ -11,6 +11,7 @@ from litellm.llms.base_llm.image_generation.transformation import ( ) from litellm.llms.vertex_ai.common_utils import ( get_vertex_base_url, + map_vertex_image_size, pop_vertex_request_labels, ) from litellm.llms.vertex_ai.gemini.vertex_and_google_ai_studio_gemini import VertexLLM @@ -72,25 +73,14 @@ class VertexAIImagenImageGenerationConfig(BaseImageGenerationConfig, VertexLLM): mapped_params["sampleCount"] = v elif k == "size": # Map OpenAI size format to Imagen aspectRatio - mapped_params["aspectRatio"] = self._map_size_to_aspect_ratio(v) + mapped_params["aspectRatio"] = ( + map_vertex_image_size(v, model, imagen=True) or {"aspectRatio": "1:1"} + )["aspectRatio"] else: mapped_params[k] = v return mapped_params - def _map_size_to_aspect_ratio(self, size: str) -> str: - """ - Map OpenAI size format to Imagen aspect ratio format - """ - aspect_ratio_map: Final = { - "1024x1024": "1:1", - "1792x1024": "16:9", - "1024x1792": "9:16", - "1280x896": "4:3", - "896x1280": "3:4", - } - return aspect_ratio_map.get(size, "1:1") - def _resolve_vertex_project(self) -> str | None: return ( getattr(self, "_vertex_project", None) diff --git a/litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/messages/transformation.py b/litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/messages/transformation.py index b28d37a0563..bfa94396ea7 100644 --- a/litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/messages/transformation.py +++ b/litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/messages/transformation.py @@ -1,6 +1,8 @@ from collections.abc import Mapping, Sequence from typing import Final +from litellm.exceptions import UnsupportedParamsError +from litellm.litellm_core_utils.core_helpers import drops_unsupported_params from litellm.llms.anthropic.common_utils import AnthropicModelInfo from litellm.llms.anthropic.messages.native.transformation import ( AnthropicMessagesConfig, @@ -17,6 +19,41 @@ from litellm.types.router import GenericLiteLLMParams from ....vertex_llm_base import VertexBase from ..output_params_utils import sanitize_vertex_anthropic_output_params +_VERSION_HEADER_VERTEX_READS_FROM_BODY: Final = "anthropic-version" +_VERTEX_DEFAULT_VERSION: Final = "vertex-2023-10-16" +_VERSIONS_SERVED_AS_VERTEX_DEFAULT: Final = frozenset({"", "2023-01-01", "2023-06-01"}) +_VERSIONS_VERTEX_ACCEPTS_IN_BODY: Final = frozenset({_VERTEX_DEFAULT_VERSION, "2026-10-21"}) + + +def _requested_version(headers: Mapping[str, object]) -> str: + requested: Final = next( + (value for name, value in headers.items() if name.lower() == _VERSION_HEADER_VERTEX_READS_FROM_BODY), + "", + ) + return requested.strip() if isinstance(requested, str) else "" + + +def _vertex_version(headers: Mapping[str, object], model: str, drop_params: bool) -> str | UnsupportedParamsError: + requested: Final = _requested_version(headers) + if requested in _VERSIONS_SERVED_AS_VERTEX_DEFAULT: + return _VERTEX_DEFAULT_VERSION + if requested in _VERSIONS_VERTEX_ACCEPTS_IN_BODY: + return requested + if drop_params: + return _VERTEX_DEFAULT_VERSION + return UnsupportedParamsError( + message=( + f"{model} does not support {_VERSION_HEADER_VERTEX_READS_FROM_BODY}={requested}. " + "To drop unsupported params, set `litellm.drop_params = True`." + ), + llm_provider="vertex_ai", + model=model, + ) + + +def _without_version_header(headers: Mapping[str, str]) -> dict[str, str]: # mutable-ok: the caller sends these headers + return {name: value for name, value in headers.items() if name.lower() != _VERSION_HEADER_VERTEX_READS_FROM_BODY} + class VertexAIPartnerModelsAnthropicMessagesConfig(AnthropicMessagesConfig, VertexBase): @property @@ -204,7 +241,7 @@ class VertexAIPartnerModelsAnthropicMessagesConfig(AnthropicMessagesConfig, Vert messages: list[dict], anthropic_messages_optional_request_params: dict, litellm_params: GenericLiteLLMParams, - headers: dict, + headers: dict[str, object], # mutable-ok: mirrors the provider transform contract ) -> dict: anthropic_messages_request: Final = super().transform_anthropic_messages_request( model=model, @@ -220,10 +257,28 @@ class VertexAIPartnerModelsAnthropicMessagesConfig(AnthropicMessagesConfig, Vert self._remove_scope_from_cache_control(anthropic_messages_request) - anthropic_messages_request["anthropic_version"] = "vertex-2023-10-16" + version: Final = _vertex_version( + headers, model=model, drop_params=drops_unsupported_params(litellm_params.drop_params) + ) + if isinstance(version, UnsupportedParamsError): + raise version + anthropic_messages_request["anthropic_version"] = version anthropic_messages_request.pop("model", None) # do not pass model in request body to vertex ai sanitize_vertex_anthropic_output_params(anthropic_messages_request, model) return anthropic_messages_request + + def sign_request( + self, + headers: Mapping[str, str], + optional_params: Mapping[str, object], + request_data: Mapping[str, object], + api_base: str, + api_key: str | None = None, + model: str | None = None, + stream: bool | None = None, + fake_stream: bool | None = None, + ) -> tuple[dict[str, str], bytes | None]: # mutable-ok: the caller sends these headers + return _without_version_header(headers), None diff --git a/litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/transformation.py b/litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/transformation.py index 3674c8434e7..79fd9f9e8b1 100644 --- a/litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/transformation.py +++ b/litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/transformation.py @@ -1,5 +1,7 @@ # What is this? ## Handler file for calling claude-3 on vertex ai +import base64 +import json from collections.abc import Mapping from typing import TYPE_CHECKING, Final @@ -19,6 +21,19 @@ if TYPE_CHECKING: from litellm.litellm_core_utils.tokenizer import Encoding as Tokenizer _NON_DEFAULT_PARAMS: Final = TypeAdapter(Mapping[str, object]) +_VERTEX_LABELS_HEADER: Final = "X-Vertex-AI-Labels" +_LABELS: Final = TypeAdapter(Mapping[object, object]) + + +def _vertex_labels_header(labels: object, header_names: Mapping[str, object]) -> str | None: + if not isinstance(labels, dict) or any(name.lower() == _VERTEX_LABELS_HEADER.lower() for name in header_names): + return None + string_labels: Final = { + key: value + for key, value in _LABELS.validate_python(labels).items() + if isinstance(key, str) and isinstance(value, str) + } + return base64.b64encode(json.dumps(string_labels).encode()).decode() if string_labels else None class VertexAIError(Exception): @@ -102,6 +117,12 @@ class VertexAIAnthropicConfig(AnthropicConfig): litellm_params: dict, headers: dict, ) -> dict: + params: Final = _NON_DEFAULT_PARAMS.validate_python(optional_params) + labels_header: Final = _vertex_labels_header(params.get("labels"), _NON_DEFAULT_PARAMS.validate_python(headers)) + if "labels" in params: + del optional_params["labels"] # rebind-ok: labels travel in the X-Vertex-AI-Labels header, not the body + if labels_header is not None: + headers[_VERTEX_LABELS_HEADER] = labels_header # rebind-ok: outbound headers are returned by mutation data: Final = super().transform_request( model=model, messages=messages, diff --git a/litellm/llms/vertex_ai/vertex_ai_partner_models/count_tokens/handler.py b/litellm/llms/vertex_ai/vertex_ai_partner_models/count_tokens/handler.py index 4be41e26326..180761f15d9 100644 --- a/litellm/llms/vertex_ai/vertex_ai_partner_models/count_tokens/handler.py +++ b/litellm/llms/vertex_ai/vertex_ai_partner_models/count_tokens/handler.py @@ -6,9 +6,12 @@ Unlike Gemini models which use Google's token counting API, partner models use their respective publisher-specific count-tokens endpoints. """ +from collections.abc import Mapping from typing import Any, Final +from litellm.litellm_core_utils.core_helpers import drops_unsupported_params from litellm.litellm_core_utils.url_utils import join_api_base +from litellm.llms.anthropic.common_utils import OBJECT_LIST_ADAPTER, is_claude_model_target, tools_without_custom_field from litellm.llms.custom_httpx.http_handler import get_async_httpx_client from litellm.llms.vertex_ai.common_utils import get_vertex_base_url from litellm.llms.vertex_ai.vertex_llm_base import VertexBase @@ -20,6 +23,22 @@ _COUNT_TOKENS_PUBLISHERS: Final = ( ) +def count_tokens_request_body( + request_data: Mapping[str, object], model: str, drop_params: object +) -> Mapping[str, object]: + tools: Final = request_data.get("tools") + if not isinstance(tools, list): + return request_data + return { + **request_data, + "tools": tools_without_custom_field( + OBJECT_LIST_ADAPTER.validate_python(tools), + hoist_defer_loading=is_claude_model_target("vertex_ai", model), + drop_custom=drops_unsupported_params(drop_params), + ), + } + + def count_tokens_publisher(model: str) -> str | None: return next((publisher for marker, publisher in _COUNT_TOKENS_PUBLISHERS if marker in model), None) @@ -169,7 +188,7 @@ class VertexAIPartnerModelsTokenCounter(VertexBase): response: Final = await async_client.post( endpoint_url, headers=headers, - json=request_data, + json=dict(count_tokens_request_body(request_data, model, litellm_params.get("drop_params"))), timeout=30.0, ) diff --git a/litellm/llms/vertex_ai/vertex_gemma_models/transformation.py b/litellm/llms/vertex_ai/vertex_gemma_models/transformation.py index 9fa86ec30f5..ec2fd16f93e 100644 --- a/litellm/llms/vertex_ai/vertex_gemma_models/transformation.py +++ b/litellm/llms/vertex_ai/vertex_gemma_models/transformation.py @@ -9,10 +9,11 @@ The actual message transformation reuses OpenAIGPTConfig since Gemma uses OpenAI """ from collections.abc import Callable -from typing import TYPE_CHECKING, Any, Final, cast +from typing import TYPE_CHECKING, Final, cast import httpx -from pydantic import ValidationError +from pydantic import ConfigDict, TypeAdapter, ValidationError +from typing_extensions import NotRequired, ReadOnly, TypeAliasType, TypedDict from litellm.llms.base_llm.chat.transformation import BaseLLMException from litellm.llms.custom_httpx.http_handler import ( @@ -32,6 +33,17 @@ if TYPE_CHECKING: from litellm.litellm_core_utils.tokenizer import Encoding as Tokenizer +class _PredictionsEnvelope(TypedDict): + predictions: NotRequired[ReadOnly[dict[str, object]]] + + +_PredictionsEnvelopeType = TypeAliasType("_PredictionsEnvelopeType", _PredictionsEnvelope) +_PREDICTIONS_ENVELOPE: Final[TypeAdapter[_PredictionsEnvelope]] = TypeAdapter( + _PredictionsEnvelopeType, + config=ConfigDict(strict=True, extra="allow"), +) + + def parse_vertex_gemma_container_error(predictions: object) -> VertexGemmaContainerError | None: try: return VertexGemmaContainerError.model_validate(predictions) @@ -142,7 +154,7 @@ class VertexGemmaConfig(OpenAIGPTConfig): def _unwrap_predictions_response( self, - response_json: dict[str, Any], + response_json: _PredictionsEnvelope, ) -> dict[str, object]: """ Unwrap the Vertex Gemma predictions format to OpenAI format. @@ -354,7 +366,7 @@ class VertexGemmaConfig(OpenAIGPTConfig): message=f"Request failed: {response.text}", ) - response_json: Final = response.json() + response_json: Final = _PREDICTIONS_ENVELOPE.validate_python(response.json()) # Unwrap predictions to get OpenAI-compatible response openai_response: Final = self._unwrap_predictions_response(response_json) @@ -449,7 +461,7 @@ class VertexGemmaConfig(OpenAIGPTConfig): message=f"Request failed: {response.text}", ) - response_json: Final = response.json() + response_json: Final = _PREDICTIONS_ENVELOPE.validate_python(response.json()) # Unwrap predictions to get OpenAI-compatible response openai_response: Final = self._unwrap_predictions_response(response_json) diff --git a/litellm/llms/vertex_ai/vertex_llm_base.py b/litellm/llms/vertex_ai/vertex_llm_base.py index 0cdd92bb071..7dd98212f76 100644 --- a/litellm/llms/vertex_ai/vertex_llm_base.py +++ b/litellm/llms/vertex_ai/vertex_llm_base.py @@ -6,9 +6,11 @@ Handles Authentication and generating request urls for Vertex AI and Google AI S import asyncio import json +import re import threading from collections import OrderedDict from collections.abc import Mapping +from dataclasses import dataclass from typing import TYPE_CHECKING, Any, Final, Literal, Protocol from urllib.parse import urlparse @@ -46,6 +48,31 @@ def graft_default_vertex_path(api_base: str, default_url: str) -> str: _graft_default_vertex_path = graft_default_vertex_path + +_PUBLISHER_MODEL_LOCATION: Final = re.compile(r".*/projects/[^/]+/locations/[^/]+(?=/publishers/[^/]+/models/[^/]+/?$)") + + +@dataclass(frozen=True, slots=True) +class PublisherModelLocation: + parent_url: str + project: str + location: str + model: str + + +def publisher_model_location(api_base: str) -> PublisherModelLocation | None: + match: Final = _PUBLISHER_MODEL_LOCATION.match(api_base) + if match is None: + return None + _, _, project, _, location = match.group().rsplit("/", 4) + return PublisherModelLocation( + parent_url=match.group(), + project=project, + location=location, + model=api_base.rstrip("/").rsplit("/", 1)[-1], + ) + + GOOGLE_IMPORT_ERROR_MESSAGE: Final = ( "Google Cloud SDK not found. Install it with: pip install 'litellm[google]' or pip install google-cloud-aiplatform" ) @@ -637,15 +664,18 @@ class VertexBase: vertex_location: str | None = None, vertex_api_version: Literal["v1", "v1beta1"] | None = None, use_psc_endpoint_format: bool = False, + collection_endpoint: bool = False, ) -> tuple[str | None, str]: """ for cloudflare ai gateway - https://github.com/BerriAI/litellm/issues/4317 Handles custom api_base for: - 1. Gemini (Google AI Studio) - constructs /models/{model}:{endpoint} + 1. Gemini (Google AI Studio) - constructs /models/{model}:{endpoint}, or {api_base}/{endpoint} + for a collection endpoint 2. Vertex AI with standard proxies - grafts the default vertex URL path onto the api_base when its path is empty or only an API version (/v1, /v1beta1); - otherwise constructs {api_base}:{endpoint} + otherwise constructs {api_base}:{endpoint}, or, for a collection endpoint under an api_base + naming a publisher model, the collection under that model's projects/{project}/locations/{location} 3. Vertex AI with PSC endpoints - constructs full path structure {api_base}/v1/projects/{project}/locations/{location}/endpoints/{model}:{endpoint} (only when use_psc_endpoint_format=True) @@ -653,22 +683,22 @@ class VertexBase: Args: use_psc_endpoint_format: If True, constructs PSC endpoint URL format. If False (default), uses api_base as-is and appends :{endpoint} + collection_endpoint: True when `endpoint` names a collection resource such as + cachedContents rather than a model action such as generateContent ## Returns - (auth_header, url) - Tuple[Optional[str], str] """ if api_base: if custom_llm_provider == "gemini": - # For Gemini (Google AI Studio), construct the full path like other providers - if model is None: + if model is None and not collection_endpoint: raise ValueError("Model parameter is required for Gemini custom API base URLs") - url = join_api_base(api_base, f"models/{model}:{endpoint}") + url = join_api_base(api_base, endpoint if collection_endpoint else f"models/{model}:{endpoint}") if gemini_api_key is None: raise ValueError( "Missing Gemini API key. Set the GEMINI_API_KEY or GOOGLE_API_KEY environment variable." ) - if gemini_api_key is not None: - auth_header = {"x-goog-api-key": gemini_api_key} + auth_header = {"x-goog-api-key": gemini_api_key} else: # For Vertex AI if use_psc_endpoint_format: @@ -692,7 +722,12 @@ class VertexBase: elif urlparse(api_base).path.rstrip("/") in ("/v1", "/v1beta1") and "/projects/" in urlparse(url).path: url = graft_default_vertex_path(api_base=api_base, default_url=url) else: - url = f"{api_base.rstrip('/')}:{endpoint}" + model_location: Final = publisher_model_location(api_base) if collection_endpoint else None + url = ( + f"{api_base.rstrip('/')}:{endpoint}" + if model_location is None + else join_api_base(model_location.parent_url, endpoint) + ) if stream is True: parsed_stream_url: Final = urlparse(url) stream_query: Final = f"{parsed_stream_url.query}&alt=sse" if parsed_stream_url.query else "alt=sse" diff --git a/litellm/llms/volcengine/responses/transformation.py b/litellm/llms/volcengine/responses/transformation.py index 747ea21e4fb..7f2425d0909 100644 --- a/litellm/llms/volcengine/responses/transformation.py +++ b/litellm/llms/volcengine/responses/transformation.py @@ -3,6 +3,7 @@ from types import UnionType from typing import TYPE_CHECKING, Any, Final, Literal, Protocol, Union, get_args, get_origin import httpx +from pydantic import ConfigDict, TypeAdapter from pydantic import fields as pyd_fields import litellm @@ -37,6 +38,8 @@ if TYPE_CHECKING: else: LiteLLMLoggingObj = Any +_RESPONSE_BODY: Final = TypeAdapter(dict[str, object], config=ConfigDict(strict=True)) + class _EventModelClass(Protocol): @property @@ -310,10 +313,10 @@ class VolcEngineResponsesAPIConfig(OpenAIResponsesAPIConfig): api_base: str, litellm_params: GenericLiteLLMParams, headers: dict, - ) -> tuple[str, dict]: + ) -> tuple[str, dict[str, str]]: encoded_response_id: Final = encode_url_path_segment(response_id, field_name="response_id") url: Final = f"{api_base}/{encoded_response_id}" - data: Final[dict] = {} + data: Final[dict[str, str]] = {} return url, data def transform_get_response_api_response( @@ -420,7 +423,7 @@ class VolcEngineResponsesAPIConfig(OpenAIResponsesAPIConfig): @staticmethod def _parsed_response_body(raw_response: httpx.Response) -> dict[str, object]: - return raw_response.json() + return _RESPONSE_BODY.validate_python(raw_response.json()) @staticmethod def _annotation_origin(annotation: object) -> object: diff --git a/litellm/main.py b/litellm/main.py index 9f412e1f24b..996e93589fe 100644 --- a/litellm/main.py +++ b/litellm/main.py @@ -123,6 +123,7 @@ from litellm.llms.bedrock.common_utils import ( BedrockModelInfo, NativeOutputFallback, bedrock_route_for_request, + bedrock_strict_tools_fallback, deployment_model_info, without_bedrock_native_output_opt_in, without_bedrock_route_prefix, @@ -206,7 +207,12 @@ from litellm.utils import ( from ._logging import verbose_logger from .caching.caching import disable_cache, enable_cache, update_cache -from .litellm_core_utils.core_helpers import as_str_mapping, normalize_drop_params, safe_deep_copy +from .litellm_core_utils.core_helpers import ( + as_str_mapping, + drops_unsupported_params, + normalize_drop_params, + safe_deep_copy, +) from .litellm_core_utils.fallback_utils import ( async_completion_with_fallbacks, completion_with_fallbacks, @@ -228,6 +234,7 @@ from .litellm_core_utils.streaming_chunk_builder_utils import ( ChunkProcessor as ChunkProcessor, # noqa: PLC0414 # public re-export ) from .llms.anthropic.chat import AnthropicChatCompletion +from .llms.anthropic.common_utils import is_claude_tool_target from .llms.azure.audio_transcriptions import AzureAudioTranscription from .llms.azure.azure import AzureChatCompletion, check_dynamic_azure_params from .llms.azure.chat.o_series_handler import AzureOpenAIO1ChatCompletion @@ -1129,17 +1136,6 @@ from litellm.responses.bridge_check import ( # noqa: E402 # re-export at the o _ANTHROPIC_ONLY_TOOL_KEYS: Final = frozenset({"input_examples", "eager_input_streaming"}) -def _is_claude_tool_target(custom_llm_provider: str | None, model: str) -> bool: - if custom_llm_provider == "anthropic": - return True - model_lower: Final = model.lower() - if custom_llm_provider == "bedrock": - return "claude" in model_lower or ("arn:" in model_lower and ":bedrock:" in model_lower) - if custom_llm_provider == "azure_ai" or custom_llm_provider == "vertex_ai": - return "claude" in model_lower - return False - - def _history_without_unanswered_tool_search_calls( messages: Sequence[object], custom_llm_provider: str | None, provider_config: BaseConfig ) -> tuple[object, ...] | None: @@ -2666,10 +2662,13 @@ def _complete_custom_openai( # for deepinfra/perplexity/anyscale/groq/friendliai we check in get_llm_provider and pass in the api base from there api_base = _resolve_openai_api_base(api_base) + if custom_llm_provider == "bigmodel" and not api_key: + raise litellm.AuthenticationError( + message="Set BIGMODEL_API_KEY or pass api_key", llm_provider="bigmodel", model=model + ) organization = ( organization - or litellm.organization - or get_secret("OPENAI_ORGANIZATION") + or (None if custom_llm_provider == "bigmodel" else litellm.organization or get_secret("OPENAI_ORGANIZATION")) or None # default - https://github.com/openai/openai-python/blob/284c1799070c723c6a553337134148a7ab088dd8/openai/util.py#L105 ) openai.organization = organization @@ -4223,6 +4222,7 @@ def _complete_sagemaker(ctx: CompletionDispatchContext) -> _CompletionDispatchRe _ADDITIONAL_DROP_PARAMS_ADAPTER: Final = TypeAdapter(list[str]) _OPTIONAL_PARAMS_ADAPTER: Final = TypeAdapter(dict[str, object]) +_OLLAMA_EMBEDDING_HEADERS_ADAPTER: Final = TypeAdapter(dict[str, str]) _REQUEST_KWARGS_ADAPTER: Final = TypeAdapter(Mapping[str, object]) _MODEL_INFO_ADAPTER: Final = TypeAdapter(Mapping[str, object]) _PROVIDER_ROUTING_HINTS: Final = TypeAdapter(ProviderRoutingHints) @@ -4378,6 +4378,11 @@ def _complete_bedrock(ctx: CompletionDispatchContext) -> _CompletionDispatchResu else None ), converse_model, + strict_tools_fallback=( + partial(bedrock_strict_tools_fallback, converse_model, converse_params, dict(litellm_params)) + if drops_unsupported_params(litellm_params.get("drop_params")) + else None + ), ) elif bedrock_route == "converse_like": model = model.replace("converse_like/", "") @@ -5737,7 +5742,7 @@ def completion( } ) - if not _is_claude_tool_target(custom_llm_provider=custom_llm_provider, model=model): + if not is_claude_tool_target(custom_llm_provider=custom_llm_provider, model=model): tools = _drop_anthropic_only_tool_keys(tools=tools) if provider_specific_header is not None: @@ -6112,7 +6117,18 @@ def completion( optional_params, rs_val = strip_reasoning_summary_aliases_from_optional_params(optional_params) - if isinstance(resolved_reasoning_effort, dict) and "summary" in resolved_reasoning_effort: + if custom_llm_provider == "openai" and isinstance(resolved_reasoning_effort, dict): + from litellm.responses.utils import openai_bridge_reasoning + + optional_params["reasoning_effort"] = openai_bridge_reasoning( + requested=resolved_reasoning_effort, + effort_kept="reasoning_effort" in optional_params, + summary_alias=rs_val, + model=model, + drop_params=drop_unsupported_reasoning, + additional_drop_params=routing_kwargs.get("additional_drop_params"), + ) + elif isinstance(resolved_reasoning_effort, dict) and "summary" in resolved_reasoning_effort: optional_params["reasoning_effort"] = resolved_reasoning_effort elif rs_val is not None: eff: Final = optional_params.get("reasoning_effort", resolved_reasoning_effort) @@ -6276,6 +6292,7 @@ def completion( or custom_llm_provider == "nebius" or custom_llm_provider == "wandb" or custom_llm_provider == "clarifai" + or custom_llm_provider == "bigmodel" or custom_llm_provider in litellm.openai_compatible_providers or JSONProviderRegistry.exists(custom_llm_provider) # JSON-configured providers or "ft:gpt-3.5-turbo" in model # finetune gpt-3.5-turbo @@ -7309,6 +7326,9 @@ def embedding( logging_obj=logging, optional_params=optional_params, model_response=EmbeddingResponse(), + api_key=api_key, + headers=_OLLAMA_EMBEDDING_HEADERS_ADAPTER.validate_python(headers), + timeout=timeout, ) elif custom_llm_provider == "sagemaker": response = sagemaker_llm.embedding( @@ -8375,7 +8395,7 @@ def transcription( custom_llm_provider=custom_llm_provider, ) - response: TranscriptionResponse | Coroutine[object, object, TranscriptionResponse] | None = None + response: TranscriptionResponse | Coroutine[object, object, TranscriptionResponse] provider_config: Final = ProviderConfigManager.get_provider_audio_transcription_config( model=model, @@ -8537,10 +8557,16 @@ def transcription( provider_config=provider_config, shared_session=shared_session, ) + else: + raise litellm.UnsupportedEndpointError( + message=f"{custom_llm_provider}/{model} does not support audio transcription.", + model=model, + llm_provider=custom_llm_provider, + ) # Store duration in _hidden_params for cost calculation without # exposing it in the response body (see sync path comment above). - if response is not None and not isinstance(response, Coroutine): + if not isinstance(response, Coroutine): existing_duration: Final = getattr(response, "duration", None) if existing_duration is None: calculated_duration: Final = calculate_request_duration(file) @@ -8550,8 +8576,6 @@ def transcription( ) response_hidden_params["audio_transcription_duration"] = calculated_duration - if response is None: - raise ValueError("Unmapped provider passed in. Unable to get the response.") return response diff --git a/litellm/messages/dispatch.py b/litellm/messages/dispatch.py index 0e2fc2e3dcb..8e6becc60b4 100644 --- a/litellm/messages/dispatch.py +++ b/litellm/messages/dispatch.py @@ -111,6 +111,7 @@ _FEATURES: Final[detectors.Detectors] = MappingProxyType( Feature.CACHE_CONTROL_INJECTION: detectors.cache_control_injection, Feature.STREAM_COST_INJECTION: route_detectors.stream_cost_injection, Feature.THINKING_SIGNATURE_RETRY: route_detectors.thinking_signature_retry, + Feature.TOOL_CUSTOM_FIELD: route_detectors.tool_custom_field, } ) diff --git a/litellm/model_prices_and_context_window_backup.json b/litellm/model_prices_and_context_window_backup.json index 5774e699ad7..50b3560f05b 100644 --- a/litellm/model_prices_and_context_window_backup.json +++ b/litellm/model_prices_and_context_window_backup.json @@ -4039,6 +4039,7 @@ "source": "https://azure.microsoft.com/en-us/pricing/details/cognitive-services/openai-service/" }, "azure_ai/gpt-oss-120b": { + "deprecation_date": "2027-09-15", "input_cost_per_token": 1.5e-07, "output_cost_per_token": 6e-07, "litellm_provider": "azure_ai", @@ -4243,6 +4244,54 @@ "supports_web_search": true, "supports_xhigh_reasoning_effort": true }, + "azure_ai/gpt-6.1-terra": { + "cache_creation_input_token_cost": 1.25e-06, + "cache_creation_input_token_cost_above_272k_tokens": 2.5e-06, + "cache_read_input_token_cost": 5e-08, + "cache_read_input_token_cost_above_272k_tokens": 1e-07, + "input_cost_per_token": 1e-06, + "input_cost_per_token_above_272k_tokens": 2e-06, + "litellm_provider": "azure_ai", + "max_input_tokens": 922000, + "max_output_tokens": 128000, + "mode": "chat", + "output_cost_per_token": 5e-06, + "output_cost_per_token_above_272k_tokens": 7.5e-06, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, + "source": "https://techcommunity.microsoft.com/blog/azure-ai-foundry-blog/gpt-6-1-terra-now-generally-available-in-microsoft-foundry-build-agents-that-see/4567769", + "supported_endpoints": [ + "/v1/chat/completions", + "/v1/responses" + ], + "supported_modalities": [ + "text", + "image" + ], + "supported_output_modalities": [ + "text" + ], + "supports_computer_use": true, + "supports_function_calling": true, + "supports_max_reasoning_effort": true, + "supports_minimal_reasoning_effort": false, + "supports_native_streaming": true, + "supports_none_reasoning_effort": false, + "supports_parallel_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_cache_breakpoint": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_system_messages": true, + "supports_tool_choice": true, + "supports_vision": true, + "supports_web_search": true, + "supports_xhigh_reasoning_effort": true + }, "azure_ai/gpt-5.5": { "deprecation_date": "2027-10-26", "cache_read_input_token_cost": 5e-07, @@ -4904,6 +4953,11 @@ "max_output_tokens": 16384, "mode": "chat", "output_cost_per_token": 6.6e-07, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supports_function_calling": true, "supports_parallel_function_calling": true, @@ -4922,6 +4976,11 @@ "max_output_tokens": 16384, "mode": "chat", "output_cost_per_token": 6.6e-07, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supports_function_calling": true, "supports_parallel_function_calling": true, @@ -5009,6 +5068,11 @@ "output_cost_per_token": 1.1e-05, "output_cost_per_token_batches": 5.5e-06, "output_cost_per_token_priority": 2.2e-05, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ "/v1/chat/completions", @@ -5048,6 +5112,11 @@ "output_cost_per_token": 2.2e-06, "output_cost_per_token_batches": 1.1e-06, "output_cost_per_token_priority": 3.96e-06, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ "/v1/chat/completions", @@ -5113,6 +5182,11 @@ "input_cost_per_token_priority": 2.75e-06, "output_cost_per_token_batches": 5.5e-06, "output_cost_per_token_priority": 2.2e-05, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" }, "azure/eu/gpt-5.1-codex": { @@ -5188,6 +5262,11 @@ "mode": "chat", "output_cost_per_token": 4.4e-07, "output_cost_per_token_batches": 2.2e-07, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ "/v1/chat/completions", @@ -5344,6 +5423,11 @@ "max_output_tokens": 16384, "mode": "chat", "output_cost_per_token": 6e-07, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_response_schema": true, @@ -5428,6 +5512,11 @@ "input_cost_per_token_priority": 2.5e-06, "output_cost_per_token_batches": 5e-06, "output_cost_per_token_priority": 2e-05, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" }, "azure/global/gpt-5.1-codex": { @@ -5680,6 +5769,11 @@ "output_cost_per_token": 8e-06, "output_cost_per_token_batches": 4e-06, "output_cost_per_token_priority": 1.4e-05, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ "/v1/chat/completions", @@ -5717,6 +5811,11 @@ "output_cost_per_token": 8e-06, "output_cost_per_token_batches": 4e-06, "output_cost_per_token_priority": 1.4e-05, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ "/v1/chat/completions", @@ -5754,6 +5853,11 @@ "output_cost_per_token": 1.6e-06, "output_cost_per_token_batches": 8e-07, "output_cost_per_token_priority": 2.8e-06, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ "/v1/chat/completions", @@ -5791,6 +5895,11 @@ "output_cost_per_token": 1.6e-06, "output_cost_per_token_batches": 8e-07, "output_cost_per_token_priority": 2.8e-06, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ "/v1/chat/completions", @@ -5992,6 +6101,7 @@ "text", "audio" ], + "supports_audio_output": true, "supports_function_calling": true, "supports_native_streaming": true, "supports_parallel_function_calling": true, @@ -6024,6 +6134,7 @@ "text", "audio" ], + "supports_audio_output": true, "supports_function_calling": true, "supports_native_streaming": true, "supports_parallel_function_calling": true, @@ -6055,6 +6166,7 @@ "text", "audio" ], + "supports_audio_output": true, "supports_function_calling": true, "supports_native_streaming": true, "supports_parallel_function_calling": true, @@ -6121,6 +6233,7 @@ "text", "audio" ], + "supports_audio_output": true, "supports_function_calling": true, "supports_native_streaming": true, "supports_parallel_function_calling": true, @@ -6184,6 +6297,7 @@ "text", "audio" ], + "supports_audio_output": true, "supports_function_calling": true, "supports_native_streaming": true, "supports_parallel_function_calling": true, @@ -6203,6 +6317,11 @@ "max_output_tokens": 16384, "mode": "chat", "output_cost_per_token": 6e-07, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_prompt_caching": true, @@ -6221,6 +6340,11 @@ "mode": "chat", "output_cost_per_token": 6e-07, "output_cost_per_token_batches": 3e-07, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supports_function_calling": true, "supports_parallel_function_calling": true, @@ -6250,6 +6374,7 @@ "text", "audio" ], + "supports_audio_output": true, "supports_function_calling": true, "supports_native_streaming": true, "supports_parallel_function_calling": true, @@ -6710,6 +6835,11 @@ "default_reasoning_effort": "none", "input_cost_per_token_batches": 6.25e-07, "output_cost_per_token_batches": 5e-06, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supports_minimal_reasoning_effort": true, "cache_read_input_token_cost_batches": 6.25e-08 @@ -6797,6 +6927,11 @@ "output_cost_per_token": 1e-05, "output_cost_per_token_batches": 5e-06, "output_cost_per_token_priority": 2e-05, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ "/v1/chat/completions", @@ -6835,6 +6970,11 @@ "output_cost_per_token": 1e-05, "output_cost_per_token_batches": 5e-06, "output_cost_per_token_priority": 2e-05, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ "/v1/chat/completions", @@ -6906,6 +7046,11 @@ "output_cost_per_token": 2e-06, "output_cost_per_token_batches": 1e-06, "output_cost_per_token_priority": 3.6e-06, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ "/v1/chat/completions", @@ -6944,6 +7089,11 @@ "output_cost_per_token": 2e-06, "output_cost_per_token_batches": 1e-06, "output_cost_per_token_priority": 3.6e-06, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ "/v1/chat/completions", @@ -6981,6 +7131,11 @@ "mode": "chat", "output_cost_per_token": 4e-07, "output_cost_per_token_batches": 2e-07, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ "/v1/chat/completions", @@ -7016,6 +7171,11 @@ "mode": "chat", "output_cost_per_token": 4e-07, "output_cost_per_token_batches": 2e-07, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ "/v1/chat/completions", @@ -7051,6 +7211,11 @@ "mode": "responses", "output_cost_per_token": 0.00012, "output_cost_per_token_batches": 6e-05, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ "/v1/responses" @@ -7112,6 +7277,11 @@ "input_cost_per_token_priority": 2.5e-06, "output_cost_per_token_batches": 5e-06, "output_cost_per_token_priority": 2e-05, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" }, "azure/gpt-5-chat": { @@ -7459,6 +7629,11 @@ "output_cost_per_token": 1.4e-05, "output_cost_per_token_batches": 7e-06, "output_cost_per_token_priority": 2.8e-05, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ "/v1/chat/completions", @@ -7498,6 +7673,11 @@ "output_cost_per_token": 1.4e-05, "output_cost_per_token_batches": 7e-06, "output_cost_per_token_priority": 2.8e-05, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ "/v1/chat/completions", @@ -7567,6 +7747,11 @@ "mode": "responses", "output_cost_per_token": 1.4e-05, "output_cost_per_token_priority": 2.8e-05, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ "/v1/responses" @@ -7599,9 +7784,9 @@ "output_cost_per_token": 0.000168, "output_cost_per_token_batches": 8.4e-05, "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ @@ -7637,9 +7822,9 @@ "output_cost_per_token": 0.000168, "output_cost_per_token_batches": 8.4e-05, "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ @@ -7996,9 +8181,9 @@ "output_cost_per_token_batches": 9e-05, "output_cost_per_token_flex": 9e-05, "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ @@ -8043,9 +8228,9 @@ "output_cost_per_token_batches": 9e-05, "output_cost_per_token_flex": 9e-05, "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ @@ -8095,9 +8280,9 @@ "output_cost_per_token_priority": 4e-05, "output_cost_per_token_above_272k_tokens_priority": 6e-05, "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 }, "supported_endpoints": [ "/v1/chat/completions", @@ -8157,9 +8342,9 @@ "output_cost_per_token_above_272k_tokens_priority": 6e-05, "output_cost_per_token_flex": 1e-05, "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ @@ -8220,9 +8405,9 @@ "output_cost_per_token_above_272k_tokens_priority": 6e-05, "output_cost_per_token_flex": 1e-05, "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ @@ -8283,9 +8468,9 @@ "output_cost_per_token_above_272k_tokens_priority": 3.6e-05, "output_cost_per_token_flex": 6e-06, "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ @@ -8346,9 +8531,9 @@ "output_cost_per_token_above_272k_tokens_priority": 3.6e-05, "output_cost_per_token_flex": 6e-06, "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ @@ -8409,9 +8594,9 @@ "output_cost_per_token_above_272k_tokens_priority": 3.6e-06, "output_cost_per_token_flex": 6e-07, "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ @@ -8472,9 +8657,9 @@ "output_cost_per_token_above_272k_tokens_priority": 3.6e-06, "output_cost_per_token_flex": 6e-07, "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 }, "supported_endpoints": [ "/v1/chat/completions", @@ -8519,9 +8704,9 @@ "output_cost_per_token": 5e-05, "output_cost_per_token_above_272k_tokens": 7.5e-05, "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ @@ -8567,9 +8752,9 @@ "output_cost_per_token": 5e-05, "output_cost_per_token_above_272k_tokens": 7.5e-05, "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ @@ -8615,9 +8800,9 @@ "output_cost_per_token": 5e-07, "output_cost_per_token_above_272k_tokens": 7.5e-07, "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 }, "source": "https://azure.microsoft.com/en-us/blog/gpt-6-astra-sol-and-luna-for-production-agents-in-microsoft-foundry/", "supported_endpoints": [ @@ -8663,9 +8848,9 @@ "output_cost_per_token": 5e-07, "output_cost_per_token_above_272k_tokens": 7.5e-07, "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 }, "source": "https://azure.microsoft.com/en-us/blog/gpt-6-astra-sol-and-luna-for-production-agents-in-microsoft-foundry/", "supported_endpoints": [ @@ -8718,7 +8903,7 @@ "output_cost_per_token_above_272k_tokens": 1.5e-05, "output_cost_per_token_above_272k_tokens_priority": 3e-05, "output_cost_per_token_priority": 2e-05, - "search_context_cost_per_query": {"search_context_size_high":0.01,"search_context_size_low":0.01,"search_context_size_medium":0.01}, + "search_context_cost_per_query": {"search_context_size_high":0.014,"search_context_size_low":0.014,"search_context_size_medium":0.014}, "source": "https://azure.microsoft.com/en-us/blog/gpt-6-astra-sol-and-luna-for-production-agents-in-microsoft-foundry/", "supported_endpoints": [ "/v1/chat/completions", @@ -8770,7 +8955,7 @@ "output_cost_per_token_above_272k_tokens": 1.5e-05, "output_cost_per_token_above_272k_tokens_priority": 3e-05, "output_cost_per_token_priority": 2e-05, - "search_context_cost_per_query": {"search_context_size_high":0.01,"search_context_size_low":0.01,"search_context_size_medium":0.01}, + "search_context_cost_per_query": {"search_context_size_high":0.014,"search_context_size_low":0.014,"search_context_size_medium":0.014}, "source": "https://azure.microsoft.com/en-us/blog/gpt-6-astra-sol-and-luna-for-production-agents-in-microsoft-foundry/", "supported_endpoints": [ "/v1/chat/completions", @@ -8800,6 +8985,53 @@ "supports_web_search": true, "supports_xhigh_reasoning_effort": true }, + "azure/gpt-6.1-terra": { + "cache_creation_input_token_cost": 1.25e-06, + "cache_creation_input_token_cost_above_272k_tokens": 2.5e-06, + "cache_read_input_token_cost": 5e-08, + "cache_read_input_token_cost_above_272k_tokens": 1e-07, + "input_cost_per_token": 1e-06, + "input_cost_per_token_above_272k_tokens": 2e-06, + "litellm_provider": "azure", + "max_input_tokens": 922000, + "max_output_tokens": 128000, + "mode": "chat", + "output_cost_per_token": 5e-06, + "output_cost_per_token_above_272k_tokens": 7.5e-06, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, + "source": "https://techcommunity.microsoft.com/blog/azure-ai-foundry-blog/gpt-6-1-terra-now-generally-available-in-microsoft-foundry-build-agents-that-see/4567769", + "supported_endpoints": [ + "/v1/chat/completions", + "/v1/responses" + ], + "supported_modalities": [ + "text", + "image" + ], + "supported_output_modalities": [ + "text" + ], + "supports_computer_use": true, + "supports_function_calling": true, + "supports_max_reasoning_effort": true, + "supports_minimal_reasoning_effort": false, + "supports_native_streaming": true, + "supports_none_reasoning_effort": false, + "supports_parallel_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_system_messages": true, + "supports_tool_choice": true, + "supports_vision": true, + "supports_web_search": true, + "supports_xhigh_reasoning_effort": true + }, "azure/gpt-6.1-sol": { "cache_creation_input_token_cost": 2.5e-06, "cache_creation_input_token_cost_above_272k_tokens": 5e-06, @@ -8815,9 +9047,9 @@ "output_cost_per_token": 1e-05, "output_cost_per_token_above_272k_tokens": 1.5e-05, "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 }, "source": "https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/models", "supported_endpoints": [ @@ -8863,9 +9095,9 @@ "output_cost_per_token": 1e-05, "output_cost_per_token_above_272k_tokens": 1.5e-05, "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 }, "source": "https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/models", "supported_endpoints": [ @@ -8896,6 +9128,53 @@ "supports_web_search": true, "supports_xhigh_reasoning_effort": true }, + "azure/us/gpt-6.1-terra": { + "cache_creation_input_token_cost": 1.375e-06, + "cache_creation_input_token_cost_above_272k_tokens": 2.75e-06, + "cache_read_input_token_cost": 5.5e-08, + "cache_read_input_token_cost_above_272k_tokens": 1.1e-07, + "input_cost_per_token": 1.1e-06, + "input_cost_per_token_above_272k_tokens": 2.2e-06, + "litellm_provider": "azure", + "max_input_tokens": 922000, + "max_output_tokens": 128000, + "mode": "chat", + "output_cost_per_token": 5.5e-06, + "output_cost_per_token_above_272k_tokens": 8.25e-06, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, + "source": "https://techcommunity.microsoft.com/blog/azure-ai-foundry-blog/gpt-6-1-terra-now-generally-available-in-microsoft-foundry-build-agents-that-see/4567769", + "supported_endpoints": [ + "/v1/chat/completions", + "/v1/responses" + ], + "supported_modalities": [ + "text", + "image" + ], + "supported_output_modalities": [ + "text" + ], + "supports_computer_use": true, + "supports_function_calling": true, + "supports_max_reasoning_effort": true, + "supports_minimal_reasoning_effort": false, + "supports_native_streaming": true, + "supports_none_reasoning_effort": false, + "supports_parallel_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_system_messages": true, + "supports_tool_choice": true, + "supports_vision": true, + "supports_web_search": true, + "supports_xhigh_reasoning_effort": true + }, "azure/us/gpt-6.1-sol": { "cache_creation_input_token_cost": 2.75e-06, "cache_creation_input_token_cost_above_272k_tokens": 5.5e-06, @@ -8911,9 +9190,9 @@ "output_cost_per_token": 1.1e-05, "output_cost_per_token_above_272k_tokens": 1.65e-05, "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 }, "source": "https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/models", "supported_endpoints": [ @@ -8944,6 +9223,53 @@ "supports_web_search": true, "supports_xhigh_reasoning_effort": true }, + "azure/eu/gpt-6.1-terra": { + "cache_creation_input_token_cost": 1.5e-06, + "cache_creation_input_token_cost_above_272k_tokens": 3e-06, + "cache_read_input_token_cost": 6e-08, + "cache_read_input_token_cost_above_272k_tokens": 1.2e-07, + "input_cost_per_token": 1.2e-06, + "input_cost_per_token_above_272k_tokens": 2.4e-06, + "litellm_provider": "azure", + "max_input_tokens": 922000, + "max_output_tokens": 128000, + "mode": "chat", + "output_cost_per_token": 6e-06, + "output_cost_per_token_above_272k_tokens": 9e-06, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, + "source": "https://techcommunity.microsoft.com/blog/azure-ai-foundry-blog/gpt-6-1-terra-now-generally-available-in-microsoft-foundry-build-agents-that-see/4567769", + "supported_endpoints": [ + "/v1/chat/completions", + "/v1/responses" + ], + "supported_modalities": [ + "text", + "image" + ], + "supported_output_modalities": [ + "text" + ], + "supports_computer_use": true, + "supports_function_calling": true, + "supports_max_reasoning_effort": true, + "supports_minimal_reasoning_effort": false, + "supports_native_streaming": true, + "supports_none_reasoning_effort": false, + "supports_parallel_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_system_messages": true, + "supports_tool_choice": true, + "supports_vision": true, + "supports_web_search": true, + "supports_xhigh_reasoning_effort": true + }, "azure/eu/gpt-6.1-sol": { "cache_creation_input_token_cost": 3e-06, "cache_creation_input_token_cost_above_272k_tokens": 6e-06, @@ -8959,9 +9285,9 @@ "output_cost_per_token": 1.2e-05, "output_cost_per_token_above_272k_tokens": 1.8e-05, "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 }, "source": "https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/models", "supported_endpoints": [ @@ -8992,6 +9318,53 @@ "supports_web_search": true, "supports_xhigh_reasoning_effort": true }, + "azure/apac/gpt-6.1-terra": { + "cache_creation_input_token_cost": 1.5e-06, + "cache_creation_input_token_cost_above_272k_tokens": 3e-06, + "cache_read_input_token_cost": 6e-08, + "cache_read_input_token_cost_above_272k_tokens": 1.2e-07, + "input_cost_per_token": 1.2e-06, + "input_cost_per_token_above_272k_tokens": 2.4e-06, + "litellm_provider": "azure", + "max_input_tokens": 922000, + "max_output_tokens": 128000, + "mode": "chat", + "output_cost_per_token": 6e-06, + "output_cost_per_token_above_272k_tokens": 9e-06, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, + "source": "https://techcommunity.microsoft.com/blog/azure-ai-foundry-blog/gpt-6-1-terra-now-generally-available-in-microsoft-foundry-build-agents-that-see/4567769", + "supported_endpoints": [ + "/v1/chat/completions", + "/v1/responses" + ], + "supported_modalities": [ + "text", + "image" + ], + "supported_output_modalities": [ + "text" + ], + "supports_computer_use": true, + "supports_function_calling": true, + "supports_max_reasoning_effort": true, + "supports_minimal_reasoning_effort": false, + "supports_native_streaming": true, + "supports_none_reasoning_effort": false, + "supports_parallel_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_system_messages": true, + "supports_tool_choice": true, + "supports_vision": true, + "supports_web_search": true, + "supports_xhigh_reasoning_effort": true + }, "azure/apac/gpt-6.1-sol": { "cache_creation_input_token_cost": 3e-06, "cache_creation_input_token_cost_above_272k_tokens": 6e-06, @@ -9007,9 +9380,9 @@ "output_cost_per_token": 1.2e-05, "output_cost_per_token_above_272k_tokens": 1.8e-05, "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 }, "source": "https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/models", "supported_endpoints": [ @@ -9134,9 +9507,9 @@ "output_cost_per_token_above_272k_tokens_priority": 6.6e-05, "output_cost_per_token_priority": 4.4e-05, "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 }, "supported_endpoints": [ "/v1/chat/completions", @@ -9188,9 +9561,9 @@ "output_cost_per_token_above_272k_tokens_priority": 6.6e-05, "output_cost_per_token_priority": 4.4e-05, "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ @@ -9243,9 +9616,9 @@ "output_cost_per_token_above_272k_tokens_priority": 3.96e-05, "output_cost_per_token_priority": 2.64e-05, "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ @@ -9298,9 +9671,9 @@ "output_cost_per_token_above_272k_tokens_priority": 3.96e-06, "output_cost_per_token_priority": 2.64e-06, "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ @@ -9345,9 +9718,9 @@ "output_cost_per_token": 5.5e-05, "output_cost_per_token_above_272k_tokens": 8.25e-05, "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ @@ -9393,9 +9766,9 @@ "output_cost_per_token": 5.5e-07, "output_cost_per_token_above_272k_tokens": 8.25e-07, "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 }, "source": "https://azure.microsoft.com/en-us/blog/gpt-6-astra-sol-and-luna-for-production-agents-in-microsoft-foundry/", "supported_endpoints": [ @@ -9448,7 +9821,7 @@ "output_cost_per_token_above_272k_tokens": 1.65e-05, "output_cost_per_token_above_272k_tokens_priority": 3.3e-05, "output_cost_per_token_priority": 2.2e-05, - "search_context_cost_per_query": {"search_context_size_high":0.01,"search_context_size_low":0.01,"search_context_size_medium":0.01}, + "search_context_cost_per_query": {"search_context_size_high":0.014,"search_context_size_low":0.014,"search_context_size_medium":0.014}, "source": "https://azure.microsoft.com/en-us/blog/gpt-6-astra-sol-and-luna-for-production-agents-in-microsoft-foundry/", "supported_endpoints": [ "/v1/chat/completions", @@ -9536,9 +9909,9 @@ "output_cost_per_token_above_272k_tokens_priority": 6.6e-05, "output_cost_per_token_priority": 4.4e-05, "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 }, "supported_endpoints": [ "/v1/chat/completions", @@ -9590,9 +9963,9 @@ "output_cost_per_token_above_272k_tokens_priority": 6.6e-05, "output_cost_per_token_priority": 4.4e-05, "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ @@ -9645,9 +10018,9 @@ "output_cost_per_token_above_272k_tokens_priority": 3.96e-05, "output_cost_per_token_priority": 2.64e-05, "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ @@ -9700,9 +10073,9 @@ "output_cost_per_token_above_272k_tokens_priority": 3.96e-06, "output_cost_per_token_priority": 2.64e-06, "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ @@ -9760,9 +10133,9 @@ "output_cost_per_token_above_272k_tokens_priority": 9e-05, "output_cost_per_token_batches": 1.5e-05, "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ @@ -9814,9 +10187,9 @@ "output_cost_per_token_above_272k_tokens_batches": 2.475e-05, "output_cost_per_token_batches": 1.65e-05, "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ @@ -9868,9 +10241,9 @@ "output_cost_per_token_above_272k_tokens_batches": 2.475e-05, "output_cost_per_token_batches": 1.65e-05, "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ @@ -9921,9 +10294,9 @@ "output_cost_per_token_priority": 7.5e-05, "output_cost_per_token_above_272k_tokens_priority": 9e-05, "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 }, "supported_endpoints": [ "/v1/chat/completions", @@ -9981,9 +10354,9 @@ "output_cost_per_token_priority": 7.5e-05, "output_cost_per_token_above_272k_tokens_priority": 9e-05, "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 }, "supported_endpoints": [ "/v1/chat/completions", @@ -10034,9 +10407,9 @@ "max_output_tokens": 128000, "mode": "chat", "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 }, "supported_endpoints": [ "/v1/chat/completions", @@ -10086,9 +10459,9 @@ "max_output_tokens": 128000, "mode": "chat", "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 }, "supported_endpoints": [ "/v1/chat/completions", @@ -10139,9 +10512,9 @@ "max_output_tokens": 128000, "mode": "chat", "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 }, "supported_endpoints": [ "/v1/chat/completions", @@ -10191,9 +10564,9 @@ "max_output_tokens": 128000, "mode": "chat", "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 }, "supported_endpoints": [ "/v1/chat/completions", @@ -10239,9 +10612,9 @@ "output_cost_per_token": 0.00018, "output_cost_per_token_above_272k_tokens": 0.00027, "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 }, "supported_endpoints": [ "/v1/batch", @@ -10282,9 +10655,9 @@ "output_cost_per_token": 0.00018, "output_cost_per_token_above_272k_tokens": 0.00027, "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 }, "supported_endpoints": [ "/v1/batch", @@ -10322,9 +10695,9 @@ "mode": "chat", "output_cost_per_token": 4.5e-06, "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 }, "supported_endpoints": [ "/v1/chat/completions", @@ -10372,9 +10745,9 @@ "mode": "chat", "output_cost_per_token": 4.5e-06, "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 }, "supported_endpoints": [ "/v1/chat/completions", @@ -10423,9 +10796,9 @@ "mode": "chat", "output_cost_per_token": 1.25e-06, "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 }, "supported_endpoints": [ "/v1/chat/completions", @@ -10470,9 +10843,9 @@ "mode": "chat", "output_cost_per_token": 1.25e-06, "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 }, "supported_endpoints": [ "/v1/chat/completions", @@ -10934,6 +11307,11 @@ "max_output_tokens": 100000, "mode": "chat", "output_cost_per_token": 8e-06, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "supported_endpoints": [ "/v1/chat/completions", "/v1/batch", @@ -10965,6 +11343,11 @@ "mode": "chat", "output_cost_per_token": 8e-06, "output_cost_per_token_batches": 4e-06, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ "/v1/chat/completions", @@ -10996,9 +11379,9 @@ "mode": "responses", "output_cost_per_token": 4e-05, "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ @@ -11065,6 +11448,11 @@ "mode": "responses", "output_cost_per_token": 8e-05, "output_cost_per_token_batches": 4e-05, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ "/v1/batch", @@ -11095,6 +11483,11 @@ "mode": "responses", "output_cost_per_token": 8e-05, "output_cost_per_token_batches": 4e-05, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ "/v1/batch", @@ -11124,6 +11517,11 @@ "max_output_tokens": 100000, "mode": "chat", "output_cost_per_token": 4.4e-06, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "supported_endpoints": [ "/v1/chat/completions", "/v1/batch", @@ -11155,6 +11553,11 @@ "mode": "chat", "output_cost_per_token": 4.4e-06, "output_cost_per_token_batches": 2.2e-06, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supports_function_calling": true, "supports_parallel_function_calling": false, @@ -11268,6 +11671,11 @@ "output_cost_per_token": 8.8e-06, "output_cost_per_token_batches": 4.4e-06, "output_cost_per_token_priority": 1.54e-05, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ "/v1/chat/completions", @@ -11305,6 +11713,11 @@ "output_cost_per_token": 1.76e-06, "output_cost_per_token_batches": 8.8e-07, "output_cost_per_token_priority": 3.08e-06, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ "/v1/chat/completions", @@ -11428,6 +11841,11 @@ "max_output_tokens": 16384, "mode": "chat", "output_cost_per_token": 6.6e-07, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supports_function_calling": true, "supports_parallel_function_calling": true, @@ -11446,6 +11864,11 @@ "max_output_tokens": 16384, "mode": "chat", "output_cost_per_token": 6.6e-07, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supports_function_calling": true, "supports_parallel_function_calling": true, @@ -11533,6 +11956,11 @@ "output_cost_per_token": 1.1e-05, "output_cost_per_token_batches": 5.5e-06, "output_cost_per_token_priority": 2.2e-05, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ "/v1/chat/completions", @@ -11572,6 +12000,11 @@ "output_cost_per_token": 2.2e-06, "output_cost_per_token_batches": 1.1e-06, "output_cost_per_token_priority": 3.96e-06, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ "/v1/chat/completions", @@ -11608,6 +12041,11 @@ "mode": "chat", "output_cost_per_token": 4.4e-07, "output_cost_per_token_batches": 2.2e-07, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ "/v1/chat/completions", @@ -11673,6 +12111,11 @@ "input_cost_per_token_priority": 2.75e-06, "output_cost_per_token_batches": 5.5e-06, "output_cost_per_token_priority": 2.2e-05, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" }, "azure/us/gpt-5.1-codex": { @@ -11800,6 +12243,11 @@ "mode": "chat", "output_cost_per_token": 8.8e-06, "output_cost_per_token_batches": 4.4e-06, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ "/v1/chat/completions", @@ -11832,6 +12280,11 @@ "mode": "chat", "output_cost_per_token": 8.8e-06, "output_cost_per_token_batches": 4.4e-06, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ "/v1/chat/completions", @@ -11898,6 +12351,11 @@ "mode": "chat", "output_cost_per_token": 4.84e-06, "output_cost_per_token_batches": 2.42e-06, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supports_function_calling": true, "supports_parallel_function_calling": false, @@ -11918,6 +12376,11 @@ "mode": "chat", "output_cost_per_token": 4.84e-06, "output_cost_per_token_batches": 2.42e-06, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supports_function_calling": true, "supports_parallel_function_calling": false, @@ -11935,6 +12398,7 @@ "output_cost_per_second": 0.0001 }, "azure_ai/Cohere-embed-v3-english": { + "deprecation_date": "2027-02-15", "input_cost_per_token": 1e-07, "litellm_provider": "azure_ai", "max_input_tokens": 512, @@ -11945,6 +12409,7 @@ "supports_embedding_image_input": true }, "azure_ai/Cohere-embed-v3-multilingual": { + "deprecation_date": "2027-02-15", "input_cost_per_token": 1e-07, "litellm_provider": "azure_ai", "max_input_tokens": 512, @@ -11955,6 +12420,7 @@ "supports_embedding_image_input": true }, "azure_ai/Codestral-2501": { + "deprecation_date": "2027-02-15", "input_cost_per_token": 3e-07, "litellm_provider": "azure_ai", "max_input_tokens": 256000, @@ -11974,6 +12440,7 @@ "supports_native_streaming": true }, "azure_ai/FLUX-1.1-pro": { + "deprecation_date": "2027-01-05", "litellm_provider": "azure_ai", "max_input_tokens": 5000, "mode": "image_generation", @@ -11984,6 +12451,7 @@ ] }, "azure_ai/FLUX.1-Kontext-pro": { + "deprecation_date": "2027-01-05", "litellm_provider": "azure_ai", "max_input_tokens": 5000, "mode": "image_generation", @@ -11994,6 +12462,7 @@ ] }, "azure_ai/flux.2-pro": { + "deprecation_date": "2027-01-20", "litellm_provider": "azure_ai", "max_input_tokens": 32000, "mode": "image_generation", @@ -12004,6 +12473,7 @@ ] }, "azure_ai/FLUX.2-flex": { + "deprecation_date": "2027-01-20", "input_cost_per_pixel": 5e-08, "litellm_provider": "azure_ai", "max_input_tokens": 32000, @@ -12368,6 +12838,7 @@ "supports_tool_choice": true }, "azure_ai/Llama-3.3-70B-Instruct": { + "deprecation_date": "2027-01-31", "input_cost_per_token": 7.1e-07, "litellm_provider": "azure_ai", "max_input_tokens": 128000, @@ -12379,6 +12850,7 @@ "supports_tool_choice": true }, "azure_ai/Llama-4-Maverick-17B-128E-Instruct-FP8": { + "deprecation_date": "2026-11-19", "input_cost_per_token": 2.5e-07, "litellm_provider": "azure_ai", "max_input_tokens": 1000000, @@ -12391,6 +12863,7 @@ "supports_vision": true }, "azure_ai/Llama-4-Scout-17B-16E-Instruct": { + "deprecation_date": "2027-01-31", "input_cost_per_token": 2e-07, "litellm_provider": "azure_ai", "max_input_tokens": 10000000, @@ -12624,6 +13097,7 @@ ] }, "azure_ai/cohere-command-a": { + "deprecation_date": "2027-02-15", "input_cost_per_token": 2.5e-06, "litellm_provider": "azure_ai", "max_input_tokens": 131072, @@ -12696,6 +13170,7 @@ "source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/retired-models" }, "azure_ai/cohere-rerank-v4.0-pro": { + "deprecation_date": "2027-09-13", "input_cost_per_query": 0.0025, "input_cost_per_token": 0.0, "litellm_provider": "azure_ai", @@ -12706,6 +13181,7 @@ "source": "https://techcommunity.microsoft.com/blog/azure-ai-foundry-blog/introducing-cohere-rerank-4-0-in-microsoft-foundry/4477076" }, "azure_ai/cohere-rerank-v4.0-fast": { + "deprecation_date": "2027-09-13", "input_cost_per_query": 0.002, "input_cost_per_token": 0.0, "litellm_provider": "azure_ai", @@ -12716,6 +13192,7 @@ "source": "https://techcommunity.microsoft.com/blog/azure-ai-foundry-blog/introducing-cohere-rerank-4-0-in-microsoft-foundry/4477076" }, "azure_ai/deepseek-v3.2": { + "deprecation_date": "2027-11-01", "input_cost_per_token": 5.8e-07, "litellm_provider": "azure_ai", "max_input_tokens": 128000, @@ -12730,6 +13207,7 @@ "supports_tool_choice": true }, "azure_ai/deepseek-v3.2-speciale": { + "deprecation_date": "2027-11-01", "input_cost_per_token": 5.8e-07, "litellm_provider": "azure_ai", "max_input_tokens": 128000, @@ -12800,6 +13278,7 @@ "supports_tool_choice": true }, "azure_ai/embed-v-4-0": { + "deprecation_date": "2027-06-01", "input_cost_per_token": 1.2e-07, "litellm_provider": "azure_ai", "max_input_tokens": 128000, @@ -12818,6 +13297,7 @@ "input_cost_per_image_token": 4.7e-07 }, "azure_ai/grok-4": { + "deprecation_date": "2027-01-31", "input_cost_per_token": 3e-06, "litellm_provider": "azure_ai", "max_input_tokens": 262000, @@ -12906,6 +13386,7 @@ "supports_web_search": true }, "azure_ai/grok-4-1-fast-non-reasoning": { + "deprecation_date": "2027-05-19", "input_cost_per_token": 2e-07, "output_cost_per_token": 5e-07, "litellm_provider": "azure_ai", @@ -12919,6 +13400,7 @@ "supports_web_search": true }, "azure_ai/grok-4-1-fast-reasoning": { + "deprecation_date": "2027-05-19", "input_cost_per_token": 2e-07, "output_cost_per_token": 5e-07, "litellm_provider": "azure_ai", @@ -12933,6 +13415,7 @@ "supports_web_search": true }, "azure_ai/grok-code-fast-1": { + "deprecation_date": "2027-01-31", "input_cost_per_token": 2e-07, "litellm_provider": "azure_ai", "max_input_tokens": 256000, @@ -13100,7 +13583,7 @@ "supports_tool_choice": true }, "azure_ai/mistral-small-2503": { - "deprecation_date": "2026-12-09", + "deprecation_date": "2027-02-15", "input_cost_per_token": 1e-07, "litellm_provider": "azure_ai", "max_input_tokens": 128000, @@ -14619,11 +15102,12 @@ "cache_creation_input_token_cost": 4.5e-06, "cache_creation_input_token_cost_above_1hr": 7.2e-06, "cache_read_input_token_cost": 3.6e-07, + "deprecation_date": "2027-04-08", "input_cost_per_token": 3.6e-06, "litellm_provider": "bedrock", "supports_tool_search": true, "max_input_tokens": 200000, - "max_output_tokens": 8192, + "max_output_tokens": 64000, "mode": "chat", "output_cost_per_token": 1.8e-05, "supports_assistant_prefill": true, @@ -14638,6 +15122,7 @@ "supports_native_structured_output": true, "supports_parallel_tool_use_config": true, "prompt_cache_min_tokens": 1024, + "source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-anthropic-claude-sonnet-4-5.md", "token_count_model": { "model": "anthropic.claude-sonnet-4-5-20250929-v1:0", "litellm_provider": "bedrock" @@ -14647,11 +15132,12 @@ "cache_creation_input_token_cost": 4.5e-06, "cache_creation_input_token_cost_above_1hr": 7.2e-06, "cache_read_input_token_cost": 3.6e-07, + "deprecation_date": "2027-04-08", "input_cost_per_token": 3.6e-06, "litellm_provider": "bedrock", "supports_tool_search": true, "max_input_tokens": 200000, - "max_output_tokens": 8192, + "max_output_tokens": 64000, "mode": "chat", "output_cost_per_token": 1.8e-05, "supports_assistant_prefill": true, @@ -14665,7 +15151,8 @@ "supports_vision": true, "supports_native_structured_output": true, "supports_parallel_tool_use_config": true, - "prompt_cache_min_tokens": 1024 + "prompt_cache_min_tokens": 1024, + "source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-anthropic-claude-sonnet-4-5.md" }, "bedrock/us-gov-east-1/meta.llama3-70b-instruct-v1:0": { "input_cost_per_token": 2.65e-06, @@ -14787,11 +15274,12 @@ "cache_creation_input_token_cost": 4.5e-06, "cache_creation_input_token_cost_above_1hr": 7.2e-06, "cache_read_input_token_cost": 3.6e-07, + "deprecation_date": "2027-04-08", "input_cost_per_token": 3.6e-06, "litellm_provider": "bedrock", "supports_tool_search": true, "max_input_tokens": 200000, - "max_output_tokens": 8192, + "max_output_tokens": 64000, "mode": "chat", "output_cost_per_token": 1.8e-05, "supports_assistant_prefill": true, @@ -14806,6 +15294,7 @@ "supports_native_structured_output": true, "supports_parallel_tool_use_config": true, "prompt_cache_min_tokens": 1024, + "source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-anthropic-claude-sonnet-4-5.md", "token_count_model": { "model": "anthropic.claude-sonnet-4-5-20250929-v1:0", "litellm_provider": "bedrock" @@ -14815,11 +15304,12 @@ "cache_creation_input_token_cost": 4.5e-06, "cache_creation_input_token_cost_above_1hr": 7.2e-06, "cache_read_input_token_cost": 3.6e-07, + "deprecation_date": "2027-04-08", "input_cost_per_token": 3.6e-06, "litellm_provider": "bedrock", "supports_tool_search": true, "max_input_tokens": 200000, - "max_output_tokens": 8192, + "max_output_tokens": 64000, "mode": "chat", "output_cost_per_token": 1.8e-05, "supports_assistant_prefill": true, @@ -14833,7 +15323,8 @@ "supports_vision": true, "supports_native_structured_output": true, "supports_parallel_tool_use_config": true, - "prompt_cache_min_tokens": 1024 + "prompt_cache_min_tokens": 1024, + "source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-anthropic-claude-sonnet-4-5.md" }, "bedrock/us-gov-west-1/meta.llama3-70b-instruct-v1:0": { "input_cost_per_token": 2.65e-06, @@ -15197,6 +15688,7 @@ "supports_tool_choice": true }, "cerebras/llama-3.3-70b": { + "deprecation_date": "2026-02-16", "input_cost_per_token": 8.5e-07, "litellm_provider": "cerebras", "max_input_tokens": 128000, @@ -15207,6 +15699,7 @@ "supports_tool_choice": true }, "cerebras/llama3.1-70b": { + "deprecation_date": "2025-01-17", "input_cost_per_token": 6e-07, "litellm_provider": "cerebras", "max_input_tokens": 128000, @@ -15217,6 +15710,7 @@ "supports_tool_choice": true }, "cerebras/llama3.1-8b": { + "deprecation_date": "2026-05-27", "input_cost_per_token": 1e-07, "litellm_provider": "cerebras", "max_input_tokens": 128000, @@ -15241,6 +15735,7 @@ "supports_tool_choice": true }, "cerebras/qwen-3-32b": { + "deprecation_date": "2026-02-16", "input_cost_per_token": 4e-07, "litellm_provider": "cerebras", "max_input_tokens": 128000, @@ -15552,6 +16047,7 @@ "output_cost_per_token_above_200k_tokens": 2.25e-05, "cache_creation_input_token_cost_above_200k_tokens": 7.5e-06, "cache_read_input_token_cost_above_200k_tokens": 6e-07, + "deprecation_date": "2027-04-08", "litellm_provider": "bedrock", "supports_tool_search": true, "max_input_tokens": 200000, @@ -15570,7 +16066,8 @@ "supports_parallel_tool_use_config": true, "prompt_cache_min_tokens": 1024, "input_cost_per_token_batches": 1.5e-06, - "output_cost_per_token_batches": 7.5e-06 + "output_cost_per_token_batches": 7.5e-06, + "source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-anthropic-claude-sonnet-4-5.md" }, "claude-opus-4-5-20251101": { "supports_web_search": true, @@ -15764,7 +16261,6 @@ "us": 1.1 }, "supports_output_config": true, - "supports_speed": true, "prompt_cache_min_tokens": 2048, "source": "https://platform.claude.com/docs/en/about-claude/pricing" }, @@ -15807,7 +16303,6 @@ "us": 1.1 }, "supports_output_config": true, - "supports_speed": true, "prompt_cache_min_tokens": 2048 }, "claude-fable-5": { @@ -20520,10 +21015,11 @@ "source": "https://www.databricks.com/product/pricing/foundation-model-serving" }, "databricks/databricks-claude-fable-5": { - "cache_creation_input_token_cost": 1.250004e-05, + "cache_creation_input_token_cost": 1.249997e-05, + "cache_creation_input_token_cost_above_1hr": 1.999998e-05, "cache_read_input_token_cost": 1.00002e-06, - "input_cost_per_token": 1.000006e-05, - "input_dbu_cost_per_token": 0.000142858, + "input_cost_per_token": 9.99999e-06, + "input_dbu_cost_per_token": 0.00014286, "litellm_provider": "databricks", "max_input_tokens": 1000000, "max_output_tokens": 128000, @@ -20532,7 +21028,7 @@ }, "mode": "chat", "output_cost_per_token": 5.000002e-05, - "output_dbu_cost_per_token": 0.000714286, + "output_dbu_cost_per_token": 0.00071429, "prompt_cache_min_tokens": 512, "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", "supports_adaptive_thinking": true, @@ -20548,10 +21044,11 @@ "thinking_always_on": true }, "databricks/databricks-claude-fable-5-1": { - "cache_creation_input_token_cost": 1.250004e-05, - "cache_read_input_token_cost": 2.5004e-07, - "input_cost_per_token": 1.000006e-05, - "input_dbu_cost_per_token": 0.000142858, + "cache_creation_input_token_cost": 1.249997e-05, + "cache_creation_input_token_cost_above_1hr": 1.999998e-05, + "cache_read_input_token_cost": 2.4997e-07, + "input_cost_per_token": 9.99999e-06, + "input_dbu_cost_per_token": 0.00014286, "litellm_provider": "databricks", "max_input_tokens": 1000000, "max_output_tokens": 128000, @@ -20560,7 +21057,7 @@ }, "mode": "chat", "output_cost_per_token": 5.000002e-05, - "output_dbu_cost_per_token": 0.000714286, + "output_dbu_cost_per_token": 0.00071429, "prompt_cache_min_tokens": 512, "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", "supports_adaptive_thinking": true, @@ -20578,6 +21075,7 @@ }, "databricks/databricks-claude-haiku-4-5": { "cache_creation_input_token_cost": 1.24999e-06, + "cache_creation_input_token_cost_above_1hr": 1.99997e-06, "cache_read_input_token_cost": 1.0003e-07, "input_cost_per_token": 1.00002e-06, "input_dbu_cost_per_token": 1.4286e-05, @@ -20601,9 +21099,10 @@ }, "databricks/databricks-claude-opus-4": { "cache_creation_input_token_cost": 1.874999e-05, + "cache_creation_input_token_cost_above_1hr": 2.999997e-05, "cache_read_input_token_cost": 1.50003e-06, - "input_cost_per_token": 1.5000020000000002e-05, - "input_dbu_cost_per_token": 0.000214286, + "input_cost_per_token": 1.500002e-05, + "input_dbu_cost_per_token": 0.00021429, "litellm_provider": "databricks", "max_input_tokens": 200000, "max_output_tokens": 32000, @@ -20611,8 +21110,8 @@ "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." }, "mode": "chat", - "output_cost_per_token": 7.500003000000001e-05, - "output_dbu_cost_per_token": 0.001071429, + "output_cost_per_token": 7.50001e-05, + "output_dbu_cost_per_token": 0.0010714, "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", "supports_assistant_prefill": true, "supports_function_calling": true, @@ -20624,9 +21123,10 @@ }, "databricks/databricks-claude-opus-4-1": { "cache_creation_input_token_cost": 1.874999e-05, + "cache_creation_input_token_cost_above_1hr": 2.999997e-05, "cache_read_input_token_cost": 1.50003e-06, - "input_cost_per_token": 1.5000020000000002e-05, - "input_dbu_cost_per_token": 0.000214286, + "input_cost_per_token": 1.500002e-05, + "input_dbu_cost_per_token": 0.00021429, "litellm_provider": "databricks", "max_input_tokens": 200000, "max_output_tokens": 32000, @@ -20634,8 +21134,8 @@ "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." }, "mode": "chat", - "output_cost_per_token": 7.500003000000001e-05, - "output_dbu_cost_per_token": 0.001071429, + "output_cost_per_token": 7.50001e-05, + "output_dbu_cost_per_token": 0.0010714, "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", "supports_assistant_prefill": true, "supports_function_calling": true, @@ -20647,6 +21147,7 @@ }, "databricks/databricks-claude-opus-4-5": { "cache_creation_input_token_cost": 6.25002e-06, + "cache_creation_input_token_cost_above_1hr": 9.99999e-06, "cache_read_input_token_cost": 5.0001e-07, "input_cost_per_token": 5.00003e-06, "input_dbu_cost_per_token": 7.1429e-05, @@ -20657,8 +21158,8 @@ "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." }, "mode": "chat", - "output_cost_per_token": 2.5000010000000002e-05, - "output_dbu_cost_per_token": 0.000357143, + "output_cost_per_token": 2.500001e-05, + "output_dbu_cost_per_token": 0.00035714, "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", "supports_assistant_prefill": true, "supports_function_calling": true, @@ -20671,6 +21172,7 @@ }, "databricks/databricks-claude-opus-4-6": { "cache_creation_input_token_cost": 6.25002e-06, + "cache_creation_input_token_cost_above_1hr": 9.99999e-06, "cache_read_input_token_cost": 5.0001e-07, "input_cost_per_token": 5.00003e-06, "input_dbu_cost_per_token": 7.1429e-05, @@ -20681,8 +21183,8 @@ "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." }, "mode": "chat", - "output_cost_per_token": 2.5000010000000002e-05, - "output_dbu_cost_per_token": 0.000357143, + "output_cost_per_token": 2.500001e-05, + "output_dbu_cost_per_token": 0.00035714, "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", "supports_assistant_prefill": false, "supports_function_calling": true, @@ -20695,6 +21197,7 @@ }, "databricks/databricks-claude-opus-4-7": { "cache_creation_input_token_cost": 6.25002e-06, + "cache_creation_input_token_cost_above_1hr": 9.99999e-06, "cache_read_input_token_cost": 5.0001e-07, "input_cost_per_token": 5.00003e-06, "input_dbu_cost_per_token": 7.1429e-05, @@ -20706,7 +21209,7 @@ }, "mode": "chat", "output_cost_per_token": 2.500001e-05, - "output_dbu_cost_per_token": 0.000357143, + "output_dbu_cost_per_token": 0.00035714, "prompt_cache_min_tokens": 2048, "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", "supports_adaptive_thinking": true, @@ -20721,6 +21224,7 @@ }, "databricks/databricks-claude-opus-4-8": { "cache_creation_input_token_cost": 6.25002e-06, + "cache_creation_input_token_cost_above_1hr": 9.99999e-06, "cache_read_input_token_cost": 5.0001e-07, "input_cost_per_token": 5.00003e-06, "input_dbu_cost_per_token": 7.1429e-05, @@ -20732,7 +21236,7 @@ }, "mode": "chat", "output_cost_per_token": 2.500001e-05, - "output_dbu_cost_per_token": 0.000357143, + "output_dbu_cost_per_token": 0.00035714, "prompt_cache_min_tokens": 1024, "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", "supports_adaptive_thinking": true, @@ -20748,6 +21252,7 @@ }, "databricks/databricks-claude-opus-5": { "cache_creation_input_token_cost": 6.25002e-06, + "cache_creation_input_token_cost_above_1hr": 9.99999e-06, "cache_read_input_token_cost": 5.0001e-07, "input_cost_per_token": 5.00003e-06, "input_dbu_cost_per_token": 7.1429e-05, @@ -20759,7 +21264,7 @@ }, "mode": "chat", "output_cost_per_token": 2.500001e-05, - "output_dbu_cost_per_token": 0.000357143, + "output_dbu_cost_per_token": 0.00035714, "prompt_cache_min_tokens": 512, "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", "supports_adaptive_thinking": true, @@ -20855,8 +21360,9 @@ }, "databricks/databricks-claude-sonnet-4-5": { "cache_creation_input_token_cost": 3.74997e-06, + "cache_creation_input_token_cost_above_1hr": 5.99998e-06, "cache_read_input_token_cost": 3.0002e-07, - "input_cost_per_token": 2.9999900000000002e-06, + "input_cost_per_token": 2.99999e-06, "input_dbu_cost_per_token": 4.2857e-05, "litellm_provider": "databricks", "max_input_tokens": 200000, @@ -20865,8 +21371,8 @@ "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." }, "mode": "chat", - "output_cost_per_token": 1.5000020000000002e-05, - "output_dbu_cost_per_token": 0.000214286, + "output_cost_per_token": 1.500002e-05, + "output_dbu_cost_per_token": 0.00021429, "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", "supports_assistant_prefill": true, "supports_function_calling": true, @@ -20878,8 +21384,9 @@ }, "databricks/databricks-claude-sonnet-4-6": { "cache_creation_input_token_cost": 3.74997e-06, + "cache_creation_input_token_cost_above_1hr": 5.99998e-06, "cache_read_input_token_cost": 3.0002e-07, - "input_cost_per_token": 2.9999900000000002e-06, + "input_cost_per_token": 2.99999e-06, "input_dbu_cost_per_token": 4.2857e-05, "litellm_provider": "databricks", "max_input_tokens": 1000000, @@ -20888,8 +21395,8 @@ "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." }, "mode": "chat", - "output_cost_per_token": 1.5000020000000002e-05, - "output_dbu_cost_per_token": 0.000214286, + "output_cost_per_token": 1.500002e-05, + "output_dbu_cost_per_token": 0.00021429, "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", "supports_assistant_prefill": false, "supports_function_calling": true, @@ -20901,19 +21408,20 @@ "prompt_cache_min_tokens": 1024 }, "databricks/databricks-claude-sonnet-5": { - "cache_creation_input_token_cost": 3.74997e-06, - "cache_read_input_token_cost": 3.0002e-07, - "input_cost_per_token": 2.99999e-06, - "input_dbu_cost_per_token": 4.2857e-05, + "cache_creation_input_token_cost": 2.49998e-06, + "cache_creation_input_token_cost_above_1hr": 4.00001e-06, + "cache_read_input_token_cost": 1.9999e-07, + "input_cost_per_token": 1.99997e-06, + "input_dbu_cost_per_token": 2.8571e-05, "litellm_provider": "databricks", "max_input_tokens": 1000000, "max_output_tokens": 128000, "metadata": { - "notes": "Costs per token are the published Global DBU rates times $0.070 per DBU. The '*_dbu_cost_per_token' fields are provided for reference; cost calculation reads the dollar '*_cost_per_token' fields. Introductory launch rates of 28.571 input / 142.857 output / 35.714 cache write / 2.857 cache read DBU run through 2026-08-31; the standard rates are listed here because entries carry no expiry date." + "notes": "Costs per token are the published Global DBU rates times $0.070 per DBU. The '*_dbu_cost_per_token' fields are provided for reference; cost calculation reads the dollar '*_cost_per_token' fields." }, "mode": "chat", - "output_cost_per_token": 1.500002e-05, - "output_dbu_cost_per_token": 0.000214286, + "output_cost_per_token": 9.99999e-06, + "output_dbu_cost_per_token": 0.00014286, "prompt_cache_min_tokens": 1024, "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", "supports_adaptive_thinking": true, @@ -21057,7 +21565,10 @@ }, "databricks/databricks-gemini-3-1-flash-lite": { "cache_creation_input_token_cost": 3.1248e-07, + "cache_read_input_audio_token_cost": 6.251e-08, "cache_read_input_token_cost": 3.122e-08, + "input_cost_per_audio_token": 6.2503e-07, + "input_cost_per_image_token": 3.1248e-07, "input_cost_per_token": 3.1248e-07, "input_dbu_cost_per_token": 4.464e-06, "litellm_provider": "databricks", @@ -21084,16 +21595,28 @@ ], "supports_vision": true, "supports_audio_input": true, - "supports_video_input": true + "supports_video_input": true, + "input_cost_per_token_priority": 5.6252e-07, + "output_cost_per_token_priority": 3.37498e-06, + "cache_read_input_token_cost_priority": 5.628e-08, + "cache_creation_input_token_cost_priority": 5.6252e-07, + "input_cost_per_audio_token_priority": 1.12497e-06, + "cache_read_input_audio_token_cost_priority": 1.1249e-07 }, "databricks/databricks-gemini-3-1-flash-image": { + "cache_creation_input_token_cost": 6.2503e-07, + "cache_read_input_token_cost": 6.2503e-07, + "input_cost_per_image_token": 6.2503e-07, + "input_cost_per_token": 6.2503e-07, "litellm_provider": "databricks", "max_input_tokens": 131072, "max_output_tokens": 32768, "metadata": { - "notes": "Databricks DBU rates not yet published for this model; endpoint metadata only." + "notes": "Costs per token are the published Global DBU rates times $0.070 per DBU. The '*_dbu_cost_per_token' fields are provided for reference; cost calculation reads the dollar '*_cost_per_token' fields." }, "mode": "chat", + "output_cost_per_image_token": 7.50001e-05, + "output_cost_per_token": 3.74997e-06, "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", "supported_modalities": [ "text", @@ -21107,13 +21630,19 @@ "supports_vision": true }, "databricks/databricks-gemini-3-pro-image": { + "cache_creation_input_token_cost": 2.49998e-06, + "cache_read_input_token_cost": 2.49998e-06, + "input_cost_per_image_token": 2.49998e-06, + "input_cost_per_token": 2.49998e-06, "litellm_provider": "databricks", "max_input_tokens": 65536, "max_output_tokens": 32768, "metadata": { - "notes": "Databricks DBU rates not yet published for this model; endpoint metadata only." + "notes": "Costs per token are the published Global DBU rates times $0.070 per DBU. The '*_dbu_cost_per_token' fields are provided for reference; cost calculation reads the dollar '*_cost_per_token' fields." }, "mode": "chat", + "output_cost_per_image_token": 0.0001500002, + "output_cost_per_token": 1.500002e-05, "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", "supported_modalities": [ "text", @@ -21129,7 +21658,9 @@ "databricks/databricks-gemini-3-1-pro": { "cache_creation_input_token_cost": 2.49998e-06, "cache_read_input_token_cost": 2.4997e-07, + "cache_read_input_token_cost_above_200k_tokens": 5.0001e-07, "input_cost_per_token": 2.49998e-06, + "input_cost_per_token_above_200k_tokens": 5.00003e-06, "input_dbu_cost_per_token": 3.5714e-05, "litellm_provider": "databricks", "max_input_tokens": 1048576, @@ -21139,12 +21670,9 @@ }, "mode": "chat", "output_cost_per_token": 1.5000020000000002e-05, + "output_cost_per_token_above_200k_tokens": 2.25e-05, "output_dbu_cost_per_token": 0.000214286, "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", - "supports_function_calling": true, - "supports_prompt_caching": true, - "supports_tool_choice": true, - "supports_reasoning": true, "supported_modalities": [ "text", "image", @@ -21154,13 +21682,27 @@ "supported_output_modalities": [ "text" ], - "supports_vision": true, "supports_audio_input": true, - "supports_video_input": true + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_tool_choice": true, + "supports_video_input": true, + "supports_vision": true, + "input_cost_per_token_priority": 4.50002e-06, + "output_cost_per_token_priority": 2.699998e-05, + "cache_read_input_token_cost_priority": 4.5003e-07, + "cache_creation_input_token_cost_priority": 4.50002e-06, + "input_cost_per_token_above_200k_tokens_priority": 8.99997e-06, + "output_cost_per_token_above_200k_tokens_priority": 4.049997e-05, + "cache_read_input_token_cost_above_200k_tokens_priority": 8.9999e-07 }, "databricks/databricks-gemini-3-flash": { "cache_creation_input_token_cost": 6.2503e-07, + "cache_read_input_audio_token_cost": 1.2502e-07, "cache_read_input_token_cost": 6.251e-08, + "input_cost_per_audio_token": 1.24999e-06, + "input_cost_per_image_token": 6.2503e-07, "input_cost_per_token": 6.2503e-07, "input_dbu_cost_per_token": 8.929e-06, "litellm_provider": "databricks", @@ -21187,7 +21729,13 @@ ], "supports_vision": true, "supports_audio_input": true, - "supports_video_input": true + "supports_video_input": true, + "input_cost_per_token_priority": 1.12497e-06, + "output_cost_per_token_priority": 6.75003e-06, + "cache_read_input_token_cost_priority": 1.1249e-07, + "cache_creation_input_token_cost_priority": 1.12497e-06, + "input_cost_per_audio_token_priority": 2.25001e-06, + "cache_read_input_audio_token_cost_priority": 2.2498e-07 }, "databricks/databricks-gemini-3-pro": { "cache_creation_input_token_cost": 2.49998e-06, @@ -21209,58 +21757,9 @@ "supports_tool_choice": true }, "databricks/databricks-gemini-3-8-flash": { - "litellm_provider": "databricks", - "max_input_tokens": 1048576, - "max_output_tokens": 65536, - "metadata": { - "notes": "Databricks DBU rates not yet published for this model; endpoint metadata only." - }, - "mode": "chat", - "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", - "supported_modalities": [ - "text", - "image", - "audio", - "video" - ], - "supported_output_modalities": [ - "text" - ], - "supports_function_calling": true, - "supports_reasoning": true, - "supports_sampling_params": false, - "supports_tool_choice": true, - "supports_vision": true - }, - "databricks/databricks-gemini-3-7-flash": { - "litellm_provider": "databricks", - "max_input_tokens": 1048576, - "max_output_tokens": 65536, - "metadata": { - "notes": "Databricks DBU rates not yet published for this model; endpoint metadata only." - }, - "mode": "chat", - "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", - "supported_modalities": [ - "text", - "image", - "audio", - "video" - ], - "supported_output_modalities": [ - "text" - ], - "supports_function_calling": true, - "supports_reasoning": true, - "supports_sampling_params": false, - "supports_tool_choice": true, - "supports_vision": true - }, - "databricks/databricks-gemini-3-6-flash": { - "cache_creation_input_token_cost": 1.87502e-06, - "cache_read_input_token_cost": 1.8753e-07, - "input_cost_per_token": 1.87502e-06, - "input_dbu_cost_per_token": 2.6786e-05, + "cache_creation_input_token_cost": 7.4998e-07, + "cache_read_input_token_cost": 7.497e-08, + "input_cost_per_token": 7.4998e-07, "litellm_provider": "databricks", "max_input_tokens": 1048576, "max_output_tokens": 65536, @@ -21268,8 +21767,73 @@ "notes": "Costs per token are the published Global DBU rates times $0.070 per DBU. The '*_dbu_cost_per_token' fields are provided for reference; cost calculation reads the dollar '*_cost_per_token' fields." }, "mode": "chat", - "output_cost_per_token": 9.37503e-06, - "output_dbu_cost_per_token": 0.000133929, + "output_cost_per_token": 3.74997e-06, + "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", + "supported_modalities": [ + "text", + "image", + "audio", + "video" + ], + "supported_output_modalities": [ + "text" + ], + "supports_function_calling": true, + "supports_reasoning": true, + "supports_sampling_params": false, + "supports_tool_choice": true, + "supports_vision": true, + "input_cost_per_token_priority": 1.35002e-06, + "output_cost_per_token_priority": 6.75003e-06, + "cache_read_input_token_cost_priority": 1.3503e-07, + "cache_creation_input_token_cost_priority": 1.35002e-06 + }, + "databricks/databricks-gemini-3-7-flash": { + "cache_creation_input_token_cost": 7.4998e-07, + "cache_read_input_token_cost": 7.497e-08, + "input_cost_per_token": 7.4998e-07, + "litellm_provider": "databricks", + "max_input_tokens": 1048576, + "max_output_tokens": 65536, + "metadata": { + "notes": "Costs per token are the published Global DBU rates times $0.070 per DBU. The '*_dbu_cost_per_token' fields are provided for reference; cost calculation reads the dollar '*_cost_per_token' fields." + }, + "mode": "chat", + "output_cost_per_token": 3.74997e-06, + "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", + "supported_modalities": [ + "text", + "image", + "audio", + "video" + ], + "supported_output_modalities": [ + "text" + ], + "supports_function_calling": true, + "supports_reasoning": true, + "supports_sampling_params": false, + "supports_tool_choice": true, + "supports_vision": true, + "input_cost_per_token_priority": 1.35002e-06, + "output_cost_per_token_priority": 6.75003e-06, + "cache_read_input_token_cost_priority": 1.3503e-07, + "cache_creation_input_token_cost_priority": 1.35002e-06 + }, + "databricks/databricks-gemini-3-6-flash": { + "cache_creation_input_token_cost": 7.4998e-07, + "cache_read_input_token_cost": 7.497e-08, + "input_cost_per_token": 7.4998e-07, + "input_dbu_cost_per_token": 1.0714e-05, + "litellm_provider": "databricks", + "max_input_tokens": 1048576, + "max_output_tokens": 65536, + "metadata": { + "notes": "Costs per token are the published Global DBU rates times $0.070 per DBU. The '*_dbu_cost_per_token' fields are provided for reference; cost calculation reads the dollar '*_cost_per_token' fields." + }, + "mode": "chat", + "output_cost_per_token": 3.74997e-06, + "output_dbu_cost_per_token": 5.3571e-05, "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", "supported_modalities": [ "text", @@ -21285,7 +21849,11 @@ "supports_reasoning": true, "supports_sampling_params": false, "supports_tool_choice": true, - "supports_vision": true + "supports_vision": true, + "input_cost_per_token_priority": 1.35002e-06, + "output_cost_per_token_priority": 6.75003e-06, + "cache_read_input_token_cost_priority": 1.3503e-07, + "cache_creation_input_token_cost_priority": 1.35002e-06 }, "databricks/databricks-gemini-3-5-flash": { "cache_creation_input_token_cost": 1.87502e-06, @@ -21315,7 +21883,11 @@ "supports_prompt_caching": true, "supports_reasoning": true, "supports_tool_choice": true, - "supports_vision": true + "supports_vision": true, + "input_cost_per_token_priority": 3.37498e-06, + "output_cost_per_token_priority": 2.025002e-05, + "cache_read_input_token_cost_priority": 3.3747e-07, + "cache_creation_input_token_cost_priority": 3.37498e-06 }, "databricks/databricks-gemini-3-5-flash-lite": { "cache_creation_input_token_cost": 3.7499e-07, @@ -21347,7 +21919,11 @@ "supports_response_schema": true, "supports_sampling_params": false, "supports_tool_choice": true, - "supports_vision": true + "supports_vision": true, + "input_cost_per_token_priority": 6.7501e-07, + "output_cost_per_token_priority": 5.62499e-06, + "cache_read_input_token_cost_priority": 6.748e-08, + "cache_creation_input_token_cost_priority": 6.7501e-07 }, "databricks/databricks-gemma-3-12b": { "cache_creation_input_token_cost": 1.5001e-07, @@ -21390,7 +21966,11 @@ "supports_prompt_caching": true, "supports_reasoning": true, "supports_tool_choice": true, - "supports_vision": false + "supports_vision": false, + "input_cost_per_token_priority": 2.45e-06, + "output_cost_per_token_priority": 7.7e-06, + "cache_read_input_token_cost_priority": 4.55e-07, + "cache_creation_input_token_cost_priority": 2.45e-06 }, "databricks/databricks-glm-5-3": { "cache_creation_input_token_cost": 1.4e-06, @@ -21420,7 +22000,11 @@ "supports_response_schema": true, "supports_tool_choice": true, "supports_vision": false, - "thinking_always_on": true + "thinking_always_on": true, + "input_cost_per_token_priority": 2.45e-06, + "output_cost_per_token_priority": 7.7e-06, + "cache_read_input_token_cost_priority": 4.55e-07, + "cache_creation_input_token_cost_priority": 2.45e-06 }, "databricks/databricks-glm-5-3-flash": { "cache_creation_input_token_cost": 1.5001e-07, @@ -21449,7 +22033,11 @@ "supports_reasoning": true, "supports_tool_choice": true, "supports_vision": true, - "thinking_always_on": true + "thinking_always_on": true, + "input_cost_per_token_priority": 2.625e-07, + "output_cost_per_token_priority": 8.75e-07, + "cache_read_input_token_cost_priority": 5.25e-08, + "cache_creation_input_token_cost_priority": 2.625e-07 }, "databricks/databricks-gpt-5": { "cache_creation_input_token_cost": 1.24999e-06, @@ -21468,7 +22056,11 @@ "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", "supports_function_calling": true, "supports_prompt_caching": true, - "supports_tool_choice": true + "supports_tool_choice": true, + "input_cost_per_token_priority": 2.49998e-06, + "output_cost_per_token_priority": 1.999998e-05, + "cache_read_input_token_cost_priority": 2.4997e-07, + "cache_creation_input_token_cost_priority": 2.49998e-06 }, "databricks/databricks-gpt-5-1": { "cache_creation_input_token_cost": 1.24999e-06, @@ -21487,7 +22079,11 @@ "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", "supports_function_calling": true, "supports_prompt_caching": true, - "supports_tool_choice": true + "supports_tool_choice": true, + "input_cost_per_token_priority": 2.49998e-06, + "output_cost_per_token_priority": 1.999998e-05, + "cache_read_input_token_cost_priority": 2.4997e-07, + "cache_creation_input_token_cost_priority": 2.49998e-06 }, "databricks/databricks-gpt-5-2": { "cache_creation_input_token_cost": 1.75e-06, @@ -21506,7 +22102,11 @@ "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", "supports_function_calling": true, "supports_prompt_caching": true, - "supports_tool_choice": true + "supports_tool_choice": true, + "input_cost_per_token_priority": 3.5e-06, + "output_cost_per_token_priority": 2.8e-05, + "cache_read_input_token_cost_priority": 3.5e-07, + "cache_creation_input_token_cost_priority": 3.5e-06 }, "databricks/databricks-gpt-5-3-codex": { "cache_creation_input_token_cost": 1.75e-06, @@ -21525,12 +22125,18 @@ "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", "supports_function_calling": true, "supports_prompt_caching": true, - "supports_tool_choice": true + "supports_tool_choice": true, + "input_cost_per_token_priority": 3.5e-06, + "output_cost_per_token_priority": 2.8e-05, + "cache_read_input_token_cost_priority": 3.5e-07, + "cache_creation_input_token_cost_priority": 3.5e-06 }, "databricks/databricks-gpt-5-4": { "cache_creation_input_token_cost": 2.49998e-06, "cache_read_input_token_cost": 2.4997e-07, + "cache_read_input_token_cost_above_272k_tokens": 5.0001e-07, "input_cost_per_token": 2.49998e-06, + "input_cost_per_token_above_272k_tokens": 5.00003e-06, "input_dbu_cost_per_token": 3.5714e-05, "litellm_provider": "databricks", "max_input_tokens": 922000, @@ -21540,6 +22146,7 @@ }, "mode": "chat", "output_cost_per_token": 1.5000020000000002e-05, + "output_cost_per_token_above_272k_tokens": 2.25e-05, "output_dbu_cost_per_token": 0.000214286, "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", "supported_modalities": [ @@ -21553,7 +22160,14 @@ "supports_prompt_caching": true, "supports_reasoning": true, "supports_tool_choice": true, - "supports_vision": true + "supports_vision": true, + "input_cost_per_token_priority": 5.00003e-06, + "output_cost_per_token_priority": 2.999997e-05, + "cache_read_input_token_cost_priority": 5.0001e-07, + "cache_creation_input_token_cost_priority": 5.00003e-06, + "input_cost_per_token_above_272k_tokens_priority": 5.00003e-06, + "output_cost_per_token_above_272k_tokens_priority": 2.999997e-05, + "cache_read_input_token_cost_above_272k_tokens_priority": 5.0001e-07 }, "databricks/databricks-gpt-5-4-mini": { "cache_creation_input_token_cost": 7.4998e-07, @@ -21581,7 +22195,11 @@ "supports_prompt_caching": true, "supports_reasoning": true, "supports_tool_choice": true, - "supports_vision": true + "supports_vision": true, + "input_cost_per_token_priority": 1.50003e-06, + "output_cost_per_token_priority": 8.99997e-06, + "cache_read_input_token_cost_priority": 1.5001e-07, + "cache_creation_input_token_cost_priority": 1.50003e-06 }, "databricks/databricks-gpt-5-4-nano": { "cache_creation_input_token_cost": 1.9999e-07, @@ -21613,8 +22231,11 @@ }, "databricks/databricks-gpt-5-6-sol": { "cache_creation_input_token_cost": 5.00003e-06, + "cache_creation_input_token_cost_above_272k_tokens": 9.99999e-06, "cache_read_input_token_cost": 3.9998e-07, + "cache_read_input_token_cost_above_272k_tokens": 8.0003e-07, "input_cost_per_token": 4.00001e-06, + "input_cost_per_token_above_272k_tokens": 8.00002e-06, "input_dbu_cost_per_token": 5.7143e-05, "litellm_provider": "databricks", "max_input_tokens": 922000, @@ -21624,6 +22245,7 @@ }, "mode": "chat", "output_cost_per_token": 1.999998e-05, + "output_cost_per_token_above_272k_tokens": 3e-05, "output_dbu_cost_per_token": 0.000285714, "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", "supported_modalities": [ @@ -21637,13 +22259,24 @@ "supports_prompt_caching": true, "supports_reasoning": true, "supports_tool_choice": true, - "supports_vision": true + "supports_vision": true, + "input_cost_per_token_priority": 8.00002e-06, + "output_cost_per_token_priority": 4.000003e-05, + "cache_read_input_token_cost_priority": 8.0003e-07, + "cache_creation_input_token_cost_priority": 9.99999e-06, + "input_cost_per_token_above_272k_tokens_priority": 1.599997e-05, + "output_cost_per_token_above_272k_tokens_priority": 6.000001e-05, + "cache_read_input_token_cost_above_272k_tokens_priority": 1.59999e-06, + "cache_creation_input_token_cost_above_272k_tokens_priority": 1.999998e-05 }, "databricks/databricks-gpt-5-6-terra": { - "cache_creation_input_token_cost": 3.12501e-06, - "cache_read_input_token_cost": 2.4997e-07, - "input_cost_per_token": 2.49998e-06, - "input_dbu_cost_per_token": 3.5714e-05, + "cache_creation_input_token_cost": 2.49998e-06, + "cache_creation_input_token_cost_above_272k_tokens": 5.00003e-06, + "cache_read_input_token_cost": 1.9999e-07, + "cache_read_input_token_cost_above_272k_tokens": 3.9998e-07, + "input_cost_per_token": 1.99997e-06, + "input_cost_per_token_above_272k_tokens": 4.00001e-06, + "input_dbu_cost_per_token": 2.8571e-05, "litellm_provider": "databricks", "max_input_tokens": 922000, "max_output_tokens": 128000, @@ -21651,8 +22284,9 @@ "notes": "Costs per token are the published Global DBU rates times $0.070 per DBU. The '*_dbu_cost_per_token' fields are provided for reference; cost calculation reads the dollar '*_cost_per_token' fields." }, "mode": "chat", - "output_cost_per_token": 1.500002e-05, - "output_dbu_cost_per_token": 0.000214286, + "output_cost_per_token": 1.200003e-05, + "output_cost_per_token_above_272k_tokens": 1.8e-05, + "output_dbu_cost_per_token": 0.000171429, "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", "supported_modalities": [ "text", @@ -21665,13 +22299,24 @@ "supports_prompt_caching": true, "supports_reasoning": true, "supports_tool_choice": true, - "supports_vision": true + "supports_vision": true, + "input_cost_per_token_priority": 4.00001e-06, + "output_cost_per_token_priority": 2.399999e-05, + "cache_read_input_token_cost_priority": 3.9998e-07, + "cache_creation_input_token_cost_priority": 5.00003e-06, + "input_cost_per_token_above_272k_tokens_priority": 8.00002e-06, + "output_cost_per_token_above_272k_tokens_priority": 3.600002e-05, + "cache_read_input_token_cost_above_272k_tokens_priority": 8.0003e-07, + "cache_creation_input_token_cost_above_272k_tokens_priority": 9.99999e-06 }, "databricks/databricks-gpt-5-6-luna": { - "cache_creation_input_token_cost": 1.24999e-06, - "cache_read_input_token_cost": 1.0003e-07, - "input_cost_per_token": 1.00002e-06, - "input_dbu_cost_per_token": 1.4286e-05, + "cache_creation_input_token_cost": 2.4997e-07, + "cache_creation_input_token_cost_above_272k_tokens": 5.0001e-07, + "cache_read_input_token_cost": 2.002e-08, + "cache_read_input_token_cost_above_272k_tokens": 3.997e-08, + "input_cost_per_token": 1.9999e-07, + "input_cost_per_token_above_272k_tokens": 3.9998e-07, + "input_dbu_cost_per_token": 2.857e-06, "litellm_provider": "databricks", "max_input_tokens": 922000, "max_output_tokens": 128000, @@ -21679,8 +22324,9 @@ "notes": "Costs per token are the published Global DBU rates times $0.070 per DBU. The '*_dbu_cost_per_token' fields are provided for reference; cost calculation reads the dollar '*_cost_per_token' fields." }, "mode": "chat", - "output_cost_per_token": 5.99998e-06, - "output_dbu_cost_per_token": 8.5714e-05, + "output_cost_per_token": 1.20001e-06, + "output_cost_per_token_above_272k_tokens": 1.79998e-06, + "output_dbu_cost_per_token": 1.7143e-05, "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", "supported_modalities": [ "text", @@ -21693,12 +22339,22 @@ "supports_prompt_caching": true, "supports_reasoning": true, "supports_tool_choice": true, - "supports_vision": true + "supports_vision": true, + "input_cost_per_token_priority": 3.9998e-07, + "output_cost_per_token_priority": 2.40002e-06, + "cache_read_input_token_cost_priority": 3.997e-08, + "cache_creation_input_token_cost_priority": 5.0001e-07, + "input_cost_per_token_above_272k_tokens_priority": 8.0003e-07, + "output_cost_per_token_above_272k_tokens_priority": 3.60003e-06, + "cache_read_input_token_cost_above_272k_tokens_priority": 8.001e-08, + "cache_creation_input_token_cost_above_272k_tokens_priority": 1.00002e-06 }, "databricks/databricks-gpt-5-5": { "cache_creation_input_token_cost": 5.00003e-06, "cache_read_input_token_cost": 5.0001e-07, + "cache_read_input_token_cost_above_272k_tokens": 1.00002e-06, "input_cost_per_token": 5.00003e-06, + "input_cost_per_token_above_272k_tokens": 9.99999e-06, "input_dbu_cost_per_token": 7.1429e-05, "litellm_provider": "databricks", "max_input_tokens": 922000, @@ -21708,6 +22364,7 @@ }, "mode": "responses", "output_cost_per_token": 2.999997e-05, + "output_cost_per_token_above_272k_tokens": 4.5e-05, "output_dbu_cost_per_token": 0.000428571, "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", "supported_modalities": [ @@ -21721,13 +22378,21 @@ "supports_prompt_caching": true, "supports_reasoning": true, "supports_tool_choice": true, - "supports_vision": true + "supports_vision": true, + "input_cost_per_token_priority": 1.249997e-05, + "output_cost_per_token_priority": 7.50001e-05, + "cache_read_input_token_cost_priority": 1.24999e-06, + "cache_creation_input_token_cost_priority": 1.249997e-05, + "input_cost_per_token_above_272k_tokens_priority": 1.249997e-05, + "output_cost_per_token_above_272k_tokens_priority": 7.50001e-05, + "cache_read_input_token_cost_above_272k_tokens_priority": 1.24999e-06 }, "databricks/databricks-gpt-5-5-pro": { "cache_creation_input_token_cost": 2.999997e-05, "cache_read_input_token_cost": 2.999997e-05, "input_cost_per_token": 2.999997e-05, - "input_dbu_cost_per_token": 0.000428571, + "input_cost_per_token_above_272k_tokens": 6e-05, + "input_dbu_cost_per_token": 0.00042857, "litellm_provider": "databricks", "max_input_tokens": 922000, "max_output_tokens": 128000, @@ -21735,8 +22400,9 @@ "notes": "Costs per token are the published Global DBU rates times $0.070 per DBU. The '*_dbu_cost_per_token' fields are provided for reference; cost calculation reads the dollar '*_cost_per_token' fields." }, "mode": "responses", - "output_cost_per_token": 0.00018000003, - "output_dbu_cost_per_token": 0.002571429, + "output_cost_per_token": 0.0001800001, + "output_cost_per_token_above_272k_tokens": 0.00027, + "output_dbu_cost_per_token": 0.0025714, "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", "supported_modalities": [ "text", @@ -21768,7 +22434,11 @@ "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", "supports_function_calling": true, "supports_prompt_caching": true, - "supports_tool_choice": true + "supports_tool_choice": true, + "input_cost_per_token_priority": 4.5003e-07, + "output_cost_per_token_priority": 3.60003e-06, + "cache_read_input_token_cost_priority": 4.501e-08, + "cache_creation_input_token_cost_priority": 4.5003e-07 }, "databricks/databricks-gpt-5-nano": { "cache_creation_input_token_cost": 4.998e-08, @@ -21918,7 +22588,11 @@ "supports_prompt_caching": true, "supports_reasoning": true, "supports_tool_choice": true, - "supports_vision": true + "supports_vision": true, + "input_cost_per_token_priority": 5.25e-06, + "output_cost_per_token_priority": 2.625e-05, + "cache_read_input_token_cost_priority": 5.25e-07, + "cache_creation_input_token_cost_priority": 5.25e-06 }, "databricks/system.ai.kimi-k3": { "litellm_provider": "databricks", @@ -22000,7 +22674,11 @@ "supports_reasoning": true, "supports_tool_choice": true, "supports_vision": false, - "thinking_always_on": true + "thinking_always_on": true, + "input_cost_per_token_priority": 3.85e-07, + "output_cost_per_token_priority": 3.85e-06, + "cache_read_input_token_cost_priority": 3.85e-07, + "cache_creation_input_token_cost_priority": 3.85e-07 }, "databricks/databricks-qwen3-next-80b-a3b-instruct": { "cache_creation_input_token_cost": 1.5001e-07, @@ -22055,6 +22733,25 @@ "output_dbu_cost_per_token": 0.0, "source": "https://docs.databricks.com/aws/en/machine-learning/foundation-model-apis/supported-models" }, + "databricks/databricks-typesafeai-jev-1-14-0": { + "cache_creation_input_token_cost": 4.2e-08, + "cache_read_input_token_cost": 4.2e-08, + "input_cost_per_token": 4.2e-08, + "input_dbu_cost_per_token": 6e-07, + "litellm_provider": "databricks", + "metadata": { + "notes": "TypeSafe AI Jev 1.14.0, provider-hosted by TypeSafe AI and served through Unity Gateway, queried through the System One API. The proprietary pricing page lists 'Jev 1.14' at 0.600 DBU per 1M input tokens; input_cost_per_token is that times $0.070 per DBU. Output is free. No cache rates are published, so cache tokens bill at the input rate." + }, + "mode": "evaluation", + "output_cost_per_token": 0.0, + "output_dbu_cost_per_token": 0.0, + "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", + "supported_modalities": [ + "text", + "image" + ], + "supports_vision": true + }, "databricks/ai_decide": { "cache_creation_input_token_cost": 0.0, "cache_read_input_token_cost": 0.0, @@ -27374,7 +28071,7 @@ "supports_reasoning": true, "supports_response_schema": true, "supports_tool_choice": true, - "supports_vision": false + "supports_vision": true }, "fireworks_ai/accounts/fireworks/models/mixtral-8x22b-instruct-hf": { "input_cost_per_token": 1.2e-06, @@ -27648,7 +28345,7 @@ "supports_reasoning": true, "supports_response_schema": true, "supports_tool_choice": true, - "supports_vision": false + "supports_vision": true }, "fireworks_ai/qwen3p7-plus": { "cache_read_input_token_cost": 8e-08, @@ -28162,6 +28859,7 @@ "mode": "image_generation", "output_cost_per_image": 0.039, "output_cost_per_image_token": 3e-05, + "output_cost_per_image_token_batches": 1.5e-05, "output_cost_per_reasoning_token": 2.5e-06, "output_cost_per_token": 2.5e-06, "output_cost_per_token_batches": 1.25e-06, @@ -28219,6 +28917,7 @@ "mode": "image_generation", "output_cost_per_image": 0.134, "output_cost_per_image_token": 0.00012, + "output_cost_per_image_token_batches": 6e-05, "output_cost_per_token": 1.2e-05, "output_cost_per_token_above_200k_tokens": 1.8e-05, "output_cost_per_token_above_200k_tokens_priority": 3.24e-05, @@ -28272,12 +28971,13 @@ "mode": "image_generation", "output_cost_per_image": 0.134, "output_cost_per_image_token": 0.00012, + "output_cost_per_image_token_batches": 6e-05, "output_cost_per_token": 1.2e-05, "output_cost_per_token_priority": 2.16e-05, "output_cost_per_token_above_200k_tokens": 1.8e-05, "output_cost_per_token_above_200k_tokens_priority": 3.24e-05, "output_cost_per_token_batches": 6e-06, - "source": "https://ai.google.dev/gemini-api/docs/pricing", + "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", "supported_endpoints": [ "/v1/chat/completions", "/v1/images/generations", @@ -28323,6 +29023,7 @@ "mode": "image_generation", "output_cost_per_image": 0.0672, "output_cost_per_image_token": 6e-05, + "output_cost_per_image_token_batches": 3e-05, "output_cost_per_token": 3e-06, "output_cost_per_token_batches": 1.5e-06, "output_cost_per_token_flex": 1.5e-06, @@ -28368,9 +29069,10 @@ "mode": "image_generation", "output_cost_per_image": 0.0672, "output_cost_per_image_token": 6e-05, + "output_cost_per_image_token_batches": 3e-05, "output_cost_per_token": 3e-06, "output_cost_per_token_batches": 1.5e-06, - "source": "https://cloud.google.com/vertex-ai/generative-ai/pricing#gemini-models", + "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", "supported_endpoints": [ "/v1/chat/completions", "/v1/images/generations", @@ -28415,6 +29117,7 @@ "mode": "image_generation", "output_cost_per_image": 0.0336, "output_cost_per_image_token": 3e-05, + "output_cost_per_image_token_batches": 1.5e-05, "output_cost_per_token": 1.5e-06, "output_cost_per_token_batches": 7.5e-07, "output_cost_per_token_flex": 7.5e-07, @@ -28981,10 +29684,12 @@ }, "search_free_requests": {"count": 10000, "period": "day", "shared_group": "gemini-2.5-pro"}, "google_maps_grounding_cost_per_query": 0.025, + "input_cost_per_token_above_200k_tokens_batches": 1.25e-06, "input_cost_per_token_above_200k_tokens_priority": 4.5e-06, "input_cost_per_token_batches": 6.25e-07, "input_cost_per_token_flex": 6.25e-07, "input_cost_per_token_priority": 2.25e-06, + "output_cost_per_token_above_200k_tokens_batches": 7.5e-06, "output_cost_per_token_above_200k_tokens_priority": 2.7e-05, "output_cost_per_token_batches": 5e-06, "output_cost_per_token_flex": 5e-06, @@ -28999,6 +29704,7 @@ "google_maps_grounding_cost_per_query": 0.014, "input_cost_per_token": 2e-06, "input_cost_per_token_above_200k_tokens": 4e-06, + "input_cost_per_token_above_200k_tokens_batches": 2e-06, "input_cost_per_token_above_200k_tokens_priority": 7.2e-06, "input_cost_per_token_batches": 1e-06, "input_cost_per_token_flex": 1e-06, @@ -29010,6 +29716,7 @@ "output_cost_per_image": 0.00012, "output_cost_per_token": 1.2e-05, "output_cost_per_token_above_200k_tokens": 1.8e-05, + "output_cost_per_token_above_200k_tokens_batches": 9e-06, "output_cost_per_token_above_200k_tokens_priority": 3.24e-05, "output_cost_per_token_batches": 6e-06, "output_cost_per_token_flex": 6e-06, @@ -29538,6 +30245,7 @@ "google_maps_grounding_cost_per_query": 0.014, "input_cost_per_token": 2e-06, "input_cost_per_token_above_200k_tokens": 4e-06, + "input_cost_per_token_above_200k_tokens_batches": 2e-06, "input_cost_per_token_above_200k_tokens_priority": 7.2e-06, "input_cost_per_token_batches": 1e-06, "input_cost_per_token_flex": 1e-06, @@ -29549,6 +30257,7 @@ "output_cost_per_image": 0.00012, "output_cost_per_token": 1.2e-05, "output_cost_per_token_above_200k_tokens": 1.8e-05, + "output_cost_per_token_above_200k_tokens_batches": 9e-06, "output_cost_per_token_above_200k_tokens_priority": 3.24e-05, "output_cost_per_token_batches": 6e-06, "output_cost_per_token_flex": 6e-06, @@ -34478,6 +35187,7 @@ "source": "https://developers.openai.com/api/docs/pricing" }, "gpt-4o-mini-tts": { + "deprecation_date": "2027-01-06", "input_cost_per_token": 6e-07, "litellm_provider": "openai", "mode": "audio_speech", @@ -35095,6 +35805,7 @@ "cache_read_input_token_cost_batches": 6.25e-08, "cache_read_input_token_cost_flex": 6.25e-08, "cache_read_input_token_cost_priority": 2.5e-07, + "deprecation_date": "2026-12-11", "input_cost_per_token": 1.25e-06, "input_cost_per_token_batches": 6.25e-07, "input_cost_per_token_flex": 6.25e-07, @@ -35107,6 +35818,13 @@ "output_cost_per_token_batches": 5e-06, "output_cost_per_token_flex": 5e-06, "output_cost_per_token_priority": 2e-05, + "reasoning_contexts": [ + "auto", + "current_turn" + ], + "reasoning_modes": [ + "standard" + ], "search_context_cost_per_query": { "search_context_size_high": 0.01, "search_context_size_low": 0.01, @@ -35184,6 +35902,13 @@ "mode": "chat", "output_cost_per_token": 1e-05, "output_cost_per_token_priority": 2e-05, + "reasoning_contexts": [ + "auto", + "current_turn" + ], + "reasoning_modes": [ + "standard" + ], "search_context_cost_per_query": { "search_context_size_high": 0.01, "search_context_size_low": 0.01, @@ -35351,6 +36076,7 @@ "cache_read_input_token_cost_batches": 6.25e-08, "cache_read_input_token_cost_flex": 6.25e-08, "cache_read_input_token_cost_priority": 2.5e-07, + "deprecation_date": "2027-04-01", "input_cost_per_token": 1.25e-06, "input_cost_per_token_priority": 2.5e-06, "litellm_provider": "openai", @@ -35359,6 +36085,13 @@ "mode": "chat", "output_cost_per_token": 1e-05, "output_cost_per_token_priority": 2e-05, + "reasoning_contexts": [ + "auto", + "current_turn" + ], + "reasoning_modes": [ + "standard" + ], "search_context_cost_per_query": { "search_context_size_high": 0.01, "search_context_size_low": 0.01, @@ -35410,6 +36143,13 @@ "mode": "chat", "output_cost_per_token": 1.4e-05, "output_cost_per_token_priority": 2.8e-05, + "reasoning_contexts": [ + "auto", + "current_turn" + ], + "reasoning_modes": [ + "standard" + ], "search_context_cost_per_query": { "search_context_size_high": 0.01, "search_context_size_low": 0.01, @@ -35525,6 +36265,13 @@ "mode": "chat", "output_cost_per_token": 1.4e-05, "output_cost_per_token_priority": 2.8e-05, + "reasoning_contexts": [ + "auto", + "current_turn" + ], + "reasoning_modes": [ + "standard" + ], "search_context_cost_per_query": { "search_context_size_high": 0.01, "search_context_size_low": 0.01, @@ -35574,6 +36321,13 @@ "mode": "responses", "output_cost_per_token": 0.000168, "output_cost_per_token_batches": 8.4e-05, + "reasoning_contexts": [ + "auto", + "current_turn" + ], + "reasoning_modes": [ + "pro" + ], "search_context_cost_per_query": { "search_context_size_high": 0.01, "search_context_size_low": 0.01, @@ -35615,6 +36369,13 @@ "mode": "responses", "output_cost_per_token": 0.000168, "output_cost_per_token_batches": 8.4e-05, + "reasoning_contexts": [ + "auto", + "current_turn" + ], + "reasoning_modes": [ + "pro" + ], "search_context_cost_per_query": { "search_context_size_high": 0.01, "search_context_size_low": 0.01, @@ -35650,15 +36411,15 @@ "gpt-6-astra": { "cache_creation_input_token_cost": 1.25e-05, "cache_creation_input_token_cost_above_12hr": 2.5e-05, + "cache_creation_input_token_cost_above_12hr_ultrafast": 0.00015, + "cache_creation_input_token_cost_above_12hr_batches": 1.25e-05, "cache_creation_input_token_cost_above_12hr_above_272k_tokens": 5e-05, "cache_creation_input_token_cost_above_12hr_above_272k_tokens_batches": 2.5e-05, "cache_creation_input_token_cost_above_12hr_above_272k_tokens_flex": 2.5e-05, "cache_creation_input_token_cost_above_12hr_above_272k_tokens_priority": 0.0001, "cache_creation_input_token_cost_above_12hr_above_272k_tokens_ultrafast": 0.0003, - "cache_creation_input_token_cost_above_12hr_batches": 1.25e-05, "cache_creation_input_token_cost_above_12hr_flex": 1.25e-05, "cache_creation_input_token_cost_above_12hr_priority": 5e-05, - "cache_creation_input_token_cost_above_12hr_ultrafast": 0.00015, "cache_creation_input_token_cost_above_272k_tokens": 2.5e-05, "cache_creation_input_token_cost_above_272k_tokens_flex": 1.25e-05, "cache_creation_input_token_cost_above_272k_tokens_priority": 5e-05, @@ -35702,6 +36463,15 @@ "output_cost_per_token_flex": 2.5e-05, "output_cost_per_token_priority": 0.0001, "output_cost_per_token_ultrafast": 0.0003, + "reasoning_contexts": [ + "auto", + "current_turn", + "all_turns" + ], + "reasoning_modes": [ + "standard", + "pro" + ], "regional_processing_uplift_multiplier_eu": 1.1, "regional_processing_uplift_multiplier_us": 1.1, "search_context_cost_per_query": { @@ -35786,6 +36556,15 @@ "output_cost_per_token_above_272k_tokens_batches": 7.5e-06, "output_cost_per_token_flex": 5e-06, "output_cost_per_token_priority": 2e-05, + "reasoning_contexts": [ + "auto", + "current_turn", + "all_turns" + ], + "reasoning_modes": [ + "standard", + "pro" + ], "regional_processing_uplift_multiplier_eu": 1.1, "regional_processing_uplift_multiplier_us": 1.1, "search_context_cost_per_query": { @@ -35828,11 +36607,11 @@ "gpt-6-luna": { "cache_creation_input_token_cost": 1.25e-07, "cache_creation_input_token_cost_above_12hr": 2.5e-07, + "cache_creation_input_token_cost_above_12hr_batches": 1.25e-07, "cache_creation_input_token_cost_above_12hr_above_272k_tokens": 5e-07, "cache_creation_input_token_cost_above_12hr_above_272k_tokens_batches": 2.5e-07, "cache_creation_input_token_cost_above_12hr_above_272k_tokens_flex": 2.5e-07, "cache_creation_input_token_cost_above_12hr_above_272k_tokens_priority": 1e-06, - "cache_creation_input_token_cost_above_12hr_batches": 1.25e-07, "cache_creation_input_token_cost_above_12hr_flex": 1.25e-07, "cache_creation_input_token_cost_above_12hr_priority": 5e-07, "cache_creation_input_token_cost_decisions": 1.25e-07, @@ -35878,6 +36657,15 @@ "output_cost_per_token_above_272k_tokens_batches": 3.75e-07, "output_cost_per_token_flex": 2.5e-07, "output_cost_per_token_priority": 1e-06, + "reasoning_contexts": [ + "auto", + "current_turn", + "all_turns" + ], + "reasoning_modes": [ + "standard", + "pro" + ], "regional_processing_uplift_multiplier_eu": 1.1, "regional_processing_uplift_multiplier_us": 1.1, "search_context_cost_per_query": { @@ -35961,6 +36749,15 @@ "output_cost_per_token_above_272k_tokens_batches": 1.5e-05, "output_cost_per_token_flex": 1e-05, "output_cost_per_token_priority": 4e-05, + "reasoning_contexts": [ + "auto", + "current_turn", + "all_turns" + ], + "reasoning_modes": [ + "standard", + "pro" + ], "regional_processing_uplift_multiplier_eu": 1.1, "regional_processing_uplift_multiplier_us": 1.1, "search_context_cost_per_query": { @@ -36042,6 +36839,15 @@ "output_cost_per_token_above_272k_tokens_batches": 1.5e-05, "output_cost_per_token_flex": 1e-05, "output_cost_per_token_priority": 4e-05, + "reasoning_contexts": [ + "auto", + "current_turn", + "all_turns" + ], + "reasoning_modes": [ + "standard", + "pro" + ], "regional_processing_uplift_multiplier_eu": 1.1, "regional_processing_uplift_multiplier_us": 1.1, "search_context_cost_per_query": { @@ -36125,6 +36931,15 @@ "output_cost_per_token_above_272k_tokens_batches": 9e-06, "output_cost_per_token_flex": 6e-06, "output_cost_per_token_priority": 2.4e-05, + "reasoning_contexts": [ + "auto", + "current_turn", + "all_turns" + ], + "reasoning_modes": [ + "standard", + "pro" + ], "regional_processing_uplift_multiplier_eu": 1.1, "regional_processing_uplift_multiplier_us": 1.1, "search_context_cost_per_query": { @@ -36207,6 +37022,15 @@ "output_cost_per_token_above_272k_tokens_batches": 9e-07, "output_cost_per_token_flex": 6e-07, "output_cost_per_token_priority": 2.4e-06, + "reasoning_contexts": [ + "auto", + "current_turn", + "all_turns" + ], + "reasoning_modes": [ + "standard", + "pro" + ], "regional_processing_uplift_multiplier_eu": 1.1, "regional_processing_uplift_multiplier_us": 1.1, "search_context_cost_per_query": { @@ -36444,6 +37268,14 @@ "reasoning_effort_levels": [ "medium" ], + "reasoning_contexts": [ + "auto", + "current_turn", + "all_turns" + ], + "reasoning_modes": [ + "standard" + ], "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/chat/completions", @@ -36491,6 +37323,14 @@ "output_cost_per_token_batches": 1.5e-05, "output_cost_per_token_above_272k_tokens_batches": 2.25e-05, "output_cost_per_token_priority": 7.5e-05, + "reasoning_contexts": [ + "auto", + "current_turn", + "all_turns" + ], + "reasoning_modes": [ + "standard" + ], "regional_processing_uplift_multiplier_eu": 1.1, "regional_processing_uplift_multiplier_us": 1.1, "search_context_cost_per_query": { @@ -36553,6 +37393,14 @@ "output_cost_per_token_batches": 1.5e-05, "output_cost_per_token_above_272k_tokens_batches": 2.25e-05, "output_cost_per_token_priority": 7.5e-05, + "reasoning_contexts": [ + "auto", + "current_turn", + "all_turns" + ], + "reasoning_modes": [ + "standard" + ], "regional_processing_uplift_multiplier_eu": 1.1, "regional_processing_uplift_multiplier_us": 1.1, "search_context_cost_per_query": { @@ -36607,6 +37455,14 @@ "output_cost_per_token_flex": 9e-05, "output_cost_per_token_batches": 9e-05, "output_cost_per_token_above_272k_tokens_batches": 0.000135, + "reasoning_contexts": [ + "auto", + "current_turn", + "all_turns" + ], + "reasoning_modes": [ + "pro" + ], "regional_processing_uplift_multiplier_eu": 1.1, "regional_processing_uplift_multiplier_us": 1.1, "search_context_cost_per_query": { @@ -36658,6 +37514,14 @@ "output_cost_per_token_flex": 9e-05, "output_cost_per_token_batches": 9e-05, "output_cost_per_token_above_272k_tokens_batches": 0.000135, + "reasoning_contexts": [ + "auto", + "current_turn", + "all_turns" + ], + "reasoning_modes": [ + "pro" + ], "regional_processing_uplift_multiplier_eu": 1.1, "regional_processing_uplift_multiplier_us": 1.1, "search_context_cost_per_query": { @@ -36717,6 +37581,14 @@ "output_cost_per_token_batches": 7.5e-06, "output_cost_per_token_above_272k_tokens_batches": 1.125e-05, "output_cost_per_token_priority": 3e-05, + "reasoning_contexts": [ + "auto", + "current_turn", + "all_turns" + ], + "reasoning_modes": [ + "standard" + ], "regional_processing_uplift_multiplier_eu": 1.1, "regional_processing_uplift_multiplier_us": 1.1, "supported_endpoints": [ @@ -36774,6 +37646,14 @@ "output_cost_per_token_batches": 7.5e-06, "output_cost_per_token_above_272k_tokens_batches": 1.125e-05, "output_cost_per_token_priority": 3e-05, + "reasoning_contexts": [ + "auto", + "current_turn", + "all_turns" + ], + "reasoning_modes": [ + "standard" + ], "regional_processing_uplift_multiplier_eu": 1.1, "regional_processing_uplift_multiplier_us": 1.1, "supported_endpoints": [ @@ -36823,6 +37703,14 @@ "output_cost_per_token_flex": 9e-05, "output_cost_per_token_batches": 9e-05, "output_cost_per_token_above_272k_tokens_batches": 0.000135, + "reasoning_contexts": [ + "auto", + "current_turn", + "all_turns" + ], + "reasoning_modes": [ + "pro" + ], "regional_processing_uplift_multiplier_eu": 1.1, "regional_processing_uplift_multiplier_us": 1.1, "search_context_cost_per_query": { @@ -36875,6 +37763,14 @@ "output_cost_per_token_flex": 9e-05, "output_cost_per_token_batches": 9e-05, "output_cost_per_token_above_272k_tokens_batches": 0.000135, + "reasoning_contexts": [ + "auto", + "current_turn", + "all_turns" + ], + "reasoning_modes": [ + "pro" + ], "regional_processing_uplift_multiplier_eu": 1.1, "regional_processing_uplift_multiplier_us": 1.1, "search_context_cost_per_query": { @@ -36929,6 +37825,14 @@ "output_cost_per_token_flex": 2.25e-06, "output_cost_per_token_batches": 2.25e-06, "output_cost_per_token_priority": 9e-06, + "reasoning_contexts": [ + "auto", + "current_turn", + "all_turns" + ], + "reasoning_modes": [ + "standard" + ], "regional_processing_uplift_multiplier_eu": 1.1, "regional_processing_uplift_multiplier_us": 1.1, "search_context_cost_per_query": { @@ -36983,6 +37887,14 @@ "output_cost_per_token_flex": 2.25e-06, "output_cost_per_token_batches": 2.25e-06, "output_cost_per_token_priority": 9e-06, + "reasoning_contexts": [ + "auto", + "current_turn", + "all_turns" + ], + "reasoning_modes": [ + "standard" + ], "regional_processing_uplift_multiplier_eu": 1.1, "regional_processing_uplift_multiplier_us": 1.1, "search_context_cost_per_query": { @@ -37034,6 +37946,14 @@ "output_cost_per_token": 1.25e-06, "output_cost_per_token_flex": 6.25e-07, "output_cost_per_token_batches": 6.25e-07, + "reasoning_contexts": [ + "auto", + "current_turn", + "all_turns" + ], + "reasoning_modes": [ + "standard" + ], "regional_processing_uplift_multiplier_eu": 1.1, "regional_processing_uplift_multiplier_us": 1.1, "search_context_cost_per_query": { @@ -37075,6 +37995,7 @@ "cache_read_input_token_cost": 2e-08, "cache_read_input_token_cost_batches": 1e-08, "cache_read_input_token_cost_flex": 1e-08, + "deprecation_date": "2027-04-01", "input_cost_per_token": 2e-07, "input_cost_per_token_flex": 1e-07, "input_cost_per_token_batches": 1e-07, @@ -37085,6 +38006,14 @@ "output_cost_per_token": 1.25e-06, "output_cost_per_token_flex": 6.25e-07, "output_cost_per_token_batches": 6.25e-07, + "reasoning_contexts": [ + "auto", + "current_turn", + "all_turns" + ], + "reasoning_modes": [ + "standard" + ], "regional_processing_uplift_multiplier_eu": 1.1, "regional_processing_uplift_multiplier_us": 1.1, "search_context_cost_per_query": { @@ -37122,6 +38051,7 @@ "supports_minimal_reasoning_effort": false }, "gpt-5-pro": { + "deprecation_date": "2026-12-11", "input_cost_per_token": 1.5e-05, "input_cost_per_token_batches": 7.5e-06, "litellm_provider": "openai", @@ -37130,6 +38060,13 @@ "mode": "responses", "output_cost_per_token": 0.00012, "output_cost_per_token_batches": 6e-05, + "reasoning_contexts": [ + "auto", + "current_turn" + ], + "reasoning_modes": [ + "pro" + ], "search_context_cost_per_query": { "search_context_size_high": 0.01, "search_context_size_low": 0.01, @@ -37172,6 +38109,13 @@ "mode": "responses", "output_cost_per_token": 0.00012, "output_cost_per_token_batches": 6e-05, + "reasoning_contexts": [ + "auto", + "current_turn" + ], + "reasoning_modes": [ + "pro" + ], "search_context_cost_per_query": { "search_context_size_high": 0.01, "search_context_size_low": 0.01, @@ -37222,6 +38166,13 @@ "output_cost_per_token_batches": 5e-06, "output_cost_per_token_flex": 5e-06, "output_cost_per_token_priority": 2e-05, + "reasoning_contexts": [ + "auto", + "current_turn" + ], + "reasoning_modes": [ + "standard" + ], "search_context_cost_per_query": { "search_context_size_high": 0.01, "search_context_size_low": 0.01, @@ -37332,6 +38283,13 @@ "mode": "responses", "output_cost_per_token": 1.4e-05, "output_cost_per_token_priority": 2.8e-05, + "reasoning_contexts": [ + "auto", + "current_turn" + ], + "reasoning_modes": [ + "standard" + ], "search_context_cost_per_query": { "search_context_size_high": 0.01, "search_context_size_low": 0.01, @@ -37401,6 +38359,7 @@ "cache_read_input_token_cost_batches": 1.25e-08, "cache_read_input_token_cost_flex": 1.25e-08, "cache_read_input_token_cost_priority": 4.5e-08, + "deprecation_date": "2026-12-11", "input_cost_per_token": 2.5e-07, "input_cost_per_token_batches": 1.25e-07, "input_cost_per_token_flex": 1.25e-07, @@ -37413,6 +38372,13 @@ "output_cost_per_token_batches": 1e-06, "output_cost_per_token_flex": 1e-06, "output_cost_per_token_priority": 3.6e-06, + "reasoning_contexts": [ + "auto", + "current_turn" + ], + "reasoning_modes": [ + "standard" + ], "search_context_cost_per_query": { "search_context_size_high": 0.01, "search_context_size_low": 0.01, @@ -37464,6 +38430,13 @@ "output_cost_per_token_batches": 1e-06, "output_cost_per_token_flex": 1e-06, "output_cost_per_token_priority": 3.6e-06, + "reasoning_contexts": [ + "auto", + "current_turn" + ], + "reasoning_modes": [ + "standard" + ], "search_context_cost_per_query": { "search_context_size_high": 0.01, "search_context_size_low": 0.01, @@ -37501,10 +38474,10 @@ "cache_read_input_token_cost": 5e-09, "cache_read_input_token_cost_batches": 2.5e-09, "cache_read_input_token_cost_flex": 2.5e-09, + "deprecation_date": "2026-12-11", "input_cost_per_token": 5e-08, "input_cost_per_token_batches": 2.5e-08, "input_cost_per_token_flex": 2.5e-08, - "input_cost_per_token_priority": 2.5e-06, "litellm_provider": "openai", "max_input_tokens": 272000, "max_output_tokens": 128000, @@ -37512,6 +38485,13 @@ "output_cost_per_token": 4e-07, "output_cost_per_token_batches": 2e-07, "output_cost_per_token_flex": 2e-07, + "reasoning_contexts": [ + "auto", + "current_turn" + ], + "reasoning_modes": [ + "standard" + ], "search_context_cost_per_query": { "search_context_size_high": 0.01, "search_context_size_low": 0.01, @@ -37552,7 +38532,6 @@ "deprecation_date": "2026-12-11", "input_cost_per_token": 5e-08, "input_cost_per_token_batches": 2.5e-08, - "input_cost_per_token_priority": 2.5e-06, "input_cost_per_token_flex": 2.5e-08, "litellm_provider": "openai", "max_input_tokens": 272000, @@ -37561,6 +38540,13 @@ "output_cost_per_token": 4e-07, "output_cost_per_token_batches": 2e-07, "output_cost_per_token_flex": 2e-07, + "reasoning_contexts": [ + "auto", + "current_turn" + ], + "reasoning_modes": [ + "standard" + ], "search_context_cost_per_query": { "search_context_size_high": 0.01, "search_context_size_low": 0.01, @@ -38212,6 +39198,7 @@ }, "supports_function_calling": true, "supports_parallel_function_calling": true, + "supports_prompt_caching": true, "supports_reasoning": true, "supports_response_schema": true, "supports_tool_choice": true, @@ -38232,6 +39219,7 @@ }, "supports_function_calling": true, "supports_parallel_function_calling": true, + "supports_prompt_caching": true, "supports_reasoning": true, "supports_response_schema": true, "supports_tool_choice": true, @@ -38251,6 +39239,7 @@ "search_context_size_medium": 0.005 }, "supports_function_calling": true, + "supports_prompt_caching": true, "supports_reasoning": true, "supports_response_schema": true, "supports_tool_choice": true, @@ -40950,6 +41939,120 @@ "supports_system_messages": true, "supports_native_structured_output": true }, + "bedrock/ap-southeast-2/mistral.voxtral-mini-3b-2507": { + "deprecation_date": "2027-03-30", + "input_cost_per_token": 4.12e-08, + "input_cost_per_token_batches": 2.06e-08, + "input_cost_per_token_flex": 2.06e-08, + "input_cost_per_token_priority": 7.21e-08, + "litellm_provider": "bedrock", + "max_input_tokens": 32768, + "max_output_tokens": 8192, + "mode": "chat", + "output_cost_per_token": 4.12e-08, + "output_cost_per_token_batches": 2.06e-08, + "output_cost_per_token_flex": 2.06e-08, + "output_cost_per_token_priority": 7.21e-08, + "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrock/current/ap-southeast-2/index.json", + "supports_audio_input": true, + "supports_system_messages": true, + "supports_native_structured_output": true + }, + "bedrock/ap-southeast-2/mistral.voxtral-small-24b-2507": { + "deprecation_date": "2027-03-30", + "input_cost_per_token": 1.03e-07, + "input_cost_per_token_batches": 5.15e-08, + "input_cost_per_token_flex": 5.15e-08, + "input_cost_per_token_priority": 1.8025e-07, + "litellm_provider": "bedrock", + "max_input_tokens": 32768, + "max_output_tokens": 8192, + "mode": "chat", + "output_cost_per_token": 3.09e-07, + "output_cost_per_token_batches": 1.545e-07, + "output_cost_per_token_flex": 1.545e-07, + "output_cost_per_token_priority": 5.4075e-07, + "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrock/current/ap-southeast-2/index.json", + "supports_audio_input": true, + "supports_system_messages": true, + "supports_native_structured_output": true + }, + "bedrock/ap-northeast-1/mistral.voxtral-mini-3b-2507": { + "deprecation_date": "2027-03-30", + "input_cost_per_token": 5e-08, + "input_cost_per_token_batches": 3e-08, + "input_cost_per_token_flex": 3e-08, + "input_cost_per_token_priority": 9e-08, + "litellm_provider": "bedrock", + "max_input_tokens": 32768, + "max_output_tokens": 8192, + "mode": "chat", + "output_cost_per_token": 5e-08, + "output_cost_per_token_batches": 3e-08, + "output_cost_per_token_flex": 3e-08, + "output_cost_per_token_priority": 9e-08, + "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrock/current/ap-northeast-1/index.json", + "supports_audio_input": true, + "supports_system_messages": true, + "supports_native_structured_output": true + }, + "bedrock/ap-northeast-1/mistral.voxtral-small-24b-2507": { + "deprecation_date": "2027-03-30", + "input_cost_per_token": 1.2e-07, + "input_cost_per_token_batches": 6e-08, + "input_cost_per_token_flex": 6e-08, + "input_cost_per_token_priority": 2.1e-07, + "litellm_provider": "bedrock", + "max_input_tokens": 32768, + "max_output_tokens": 8192, + "mode": "chat", + "output_cost_per_token": 3.6e-07, + "output_cost_per_token_batches": 1.8e-07, + "output_cost_per_token_flex": 1.8e-07, + "output_cost_per_token_priority": 6.3e-07, + "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrock/current/ap-northeast-1/index.json", + "supports_audio_input": true, + "supports_system_messages": true, + "supports_native_structured_output": true + }, + "bedrock/eu-west-2/mistral.voxtral-mini-3b-2507": { + "deprecation_date": "2027-03-30", + "input_cost_per_token": 6e-08, + "input_cost_per_token_batches": 3e-08, + "input_cost_per_token_flex": 3e-08, + "input_cost_per_token_priority": 1.1e-07, + "litellm_provider": "bedrock", + "max_input_tokens": 32768, + "max_output_tokens": 8192, + "mode": "chat", + "output_cost_per_token": 6e-08, + "output_cost_per_token_batches": 3e-08, + "output_cost_per_token_flex": 3e-08, + "output_cost_per_token_priority": 1.1e-07, + "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrock/current/eu-west-2/index.json", + "supports_audio_input": true, + "supports_system_messages": true, + "supports_native_structured_output": true + }, + "bedrock/eu-west-2/mistral.voxtral-small-24b-2507": { + "deprecation_date": "2027-03-30", + "input_cost_per_token": 1.6e-07, + "input_cost_per_token_batches": 8e-08, + "input_cost_per_token_flex": 8e-08, + "input_cost_per_token_priority": 2.8e-07, + "litellm_provider": "bedrock", + "max_input_tokens": 32768, + "max_output_tokens": 8192, + "mode": "chat", + "output_cost_per_token": 4.7e-07, + "output_cost_per_token_batches": 2.3e-07, + "output_cost_per_token_flex": 2.3e-07, + "output_cost_per_token_priority": 8.2e-07, + "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrock/current/eu-west-2/index.json", + "supports_audio_input": true, + "supports_system_messages": true, + "supports_native_structured_output": true + }, "mistral/codestral-2508": { "cache_read_input_token_cost": 3e-08, "input_cost_per_token": 3e-07, @@ -40998,9 +42101,14 @@ "max_output_tokens": 256000, "mode": "chat", "output_cost_per_token": 3e-07, + "reasoning_effort_levels": [ + "none", + "high" + ], "source": "https://docs.mistral.ai/models/devstral-small-2-25-12", "supports_assistant_prefill": true, "supports_function_calling": true, + "supports_reasoning": true, "supports_response_schema": true, "supports_tool_choice": true }, @@ -41012,9 +42120,14 @@ "max_output_tokens": 256000, "mode": "chat", "output_cost_per_token": 2e-06, + "reasoning_effort_levels": [ + "none", + "high" + ], "source": "https://mistral.ai/news/devstral-2-vibe-cli", "supports_assistant_prefill": true, "supports_function_calling": true, + "supports_reasoning": true, "supports_response_schema": true, "supports_tool_choice": true }, @@ -41026,9 +42139,14 @@ "max_output_tokens": 256000, "mode": "chat", "output_cost_per_token": 2e-06, + "reasoning_effort_levels": [ + "none", + "high" + ], "source": "https://mistral.ai/news/devstral-2-vibe-cli", "supports_assistant_prefill": true, "supports_function_calling": true, + "supports_reasoning": true, "supports_response_schema": true, "supports_tool_choice": true }, @@ -41333,6 +42451,22 @@ "supports_response_schema": true, "supports_tool_choice": true }, + "mistral/deepseek-v4-1-flash-1017": { + "cache_read_input_token_cost": 7e-09, + "input_cost_per_token": 3e-07, + "litellm_provider": "mistral", + "max_input_tokens": 1048576, + "max_output_tokens": 131072, + "mode": "chat", + "output_cost_per_token": 1.2e-06, + "source": "https://docs.mistral.ai/models/deepseek-v4-flash-1017", + "supports_assistant_prefill": true, + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_tool_choice": true + }, "mistral/zai-glm-5-3": { "cache_read_input_token_cost": 1.4e-07, "input_cost_per_token": 1.4e-06, @@ -41549,13 +42683,13 @@ "mode": "embedding" }, "mistral/mistral-large-4": { - "cache_read_input_token_cost": 6.8e-08, - "input_cost_per_token": 6.8e-07, + "cache_read_input_token_cost": 1.4e-07, + "input_cost_per_token": 1.36e-06, "litellm_provider": "mistral", "max_input_tokens": 1048576, "max_output_tokens": 1048576, "mode": "chat", - "output_cost_per_token": 2.09e-06, + "output_cost_per_token": 4.18e-06, "reasoning_effort_levels": [ "none", "high" @@ -41570,13 +42704,13 @@ "supports_vision": true }, "mistral/mistral-large-4-0": { - "cache_read_input_token_cost": 6.8e-08, - "input_cost_per_token": 6.8e-07, + "cache_read_input_token_cost": 1.4e-07, + "input_cost_per_token": 1.36e-06, "litellm_provider": "mistral", "max_input_tokens": 1048576, "max_output_tokens": 1048576, "mode": "chat", - "output_cost_per_token": 2.09e-06, + "output_cost_per_token": 4.18e-06, "reasoning_effort_levels": [ "none", "high" @@ -41723,8 +42857,13 @@ "max_output_tokens": 8191, "mode": "chat", "output_cost_per_token": 3e-07, + "reasoning_effort_levels": [ + "none", + "high" + ], "supports_assistant_prefill": true, "supports_function_calling": true, + "supports_reasoning": true, "supports_response_schema": true, "supports_tool_choice": true }, @@ -41923,6 +43062,7 @@ }, "moonshot/kimi-k2.5": { "cache_read_input_token_cost": 1e-07, + "deprecation_date": "2026-08-31", "input_cost_per_token": 6e-07, "litellm_provider": "moonshot", "max_input_tokens": 262144, @@ -41953,7 +43093,31 @@ "supports_video_input": true, "supports_vision": true }, + "moonshot/kimi-k3.1-pro": { + "cache_creation_input_token_cost": 2e-06, + "cache_creation_input_token_cost_above_1hr": 4e-06, + "cache_read_input_token_cost": 2e-07, + "input_cost_per_token": 2e-06, + "litellm_provider": "moonshot", + "max_input_tokens": 1048576, + "max_output_tokens": 1048576, + "mode": "chat", + "output_cost_per_token": 1e-05, + "reasoning_effort_levels": [ + "low", + "high", + "max" + ], + "source": "https://platform.kimi.ai/docs/pricing/chat", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_vision": true + }, "moonshot/kimi-k3": { + "cache_creation_input_token_cost": 3e-06, + "cache_creation_input_token_cost_above_1hr": 6e-06, "cache_read_input_token_cost": 3e-07, "input_cost_per_token": 3e-06, "litellm_provider": "moonshot", @@ -41968,6 +43132,7 @@ ], "source": "https://platform.kimi.ai/docs/pricing/chat-k3", "supports_function_calling": true, + "supports_prompt_caching": true, "supports_reasoning": true, "supports_response_schema": true, "supports_tool_choice": true, @@ -41975,6 +43140,7 @@ "supports_vision": true }, "moonshot/moonshot-v1-128k": { + "deprecation_date": "2026-08-31", "input_cost_per_token": 2e-06, "litellm_provider": "moonshot", "max_input_tokens": 131072, @@ -41987,6 +43153,7 @@ "supports_tool_choice": true }, "moonshot/moonshot-v1-128k-vision-preview": { + "deprecation_date": "2026-08-31", "input_cost_per_token": 2e-06, "litellm_provider": "moonshot", "max_input_tokens": 131072, @@ -42000,6 +43167,7 @@ "supports_vision": true }, "moonshot/moonshot-v1-32k": { + "deprecation_date": "2026-08-31", "input_cost_per_token": 1e-06, "litellm_provider": "moonshot", "max_input_tokens": 32768, @@ -42012,6 +43180,7 @@ "supports_tool_choice": true }, "moonshot/moonshot-v1-32k-vision-preview": { + "deprecation_date": "2026-08-31", "input_cost_per_token": 1e-06, "litellm_provider": "moonshot", "max_input_tokens": 32768, @@ -42025,6 +43194,7 @@ "supports_vision": true }, "moonshot/moonshot-v1-8k": { + "deprecation_date": "2026-08-31", "input_cost_per_token": 2e-07, "litellm_provider": "moonshot", "max_input_tokens": 8192, @@ -42037,6 +43207,7 @@ "supports_tool_choice": true }, "moonshot/moonshot-v1-8k-vision-preview": { + "deprecation_date": "2026-08-31", "input_cost_per_token": 2e-07, "litellm_provider": "moonshot", "max_input_tokens": 8192, @@ -42050,6 +43221,7 @@ "supports_vision": true }, "moonshot/moonshot-v1-auto": { + "deprecation_date": "2026-08-31", "input_cost_per_token": 2e-06, "litellm_provider": "moonshot", "max_input_tokens": 131072, @@ -43242,6 +44414,7 @@ "cache_read_input_token_cost": 5e-07, "cache_read_input_token_cost_flex": 2.5e-07, "cache_read_input_token_cost_priority": 8.75e-07, + "deprecation_date": "2026-12-11", "input_cost_per_token": 2e-06, "input_cost_per_token_batches": 1e-06, "input_cost_per_token_flex": 1e-06, @@ -43254,6 +44427,13 @@ "output_cost_per_token_batches": 4e-06, "output_cost_per_token_flex": 4e-06, "output_cost_per_token_priority": 1.4e-05, + "reasoning_contexts": [ + "auto", + "current_turn" + ], + "reasoning_modes": [ + "standard" + ], "search_context_cost_per_query": { "search_context_size_high": 0.01, "search_context_size_low": 0.01, @@ -43362,6 +44542,13 @@ "output_cost_per_token_batches": 4e-06, "output_cost_per_token_flex": 4e-06, "output_cost_per_token_priority": 1.4e-05, + "reasoning_contexts": [ + "auto", + "current_turn" + ], + "reasoning_modes": [ + "standard" + ], "search_context_cost_per_query": { "search_context_size_high": 0.01, "search_context_size_low": 0.01, @@ -43432,6 +44619,7 @@ "supports_vision": false }, "o3-pro": { + "deprecation_date": "2026-12-11", "input_cost_per_token": 2e-05, "input_cost_per_token_batches": 1e-05, "litellm_provider": "openai", @@ -43440,6 +44628,13 @@ "mode": "responses", "output_cost_per_token": 8e-05, "output_cost_per_token_batches": 4e-05, + "reasoning_contexts": [ + "auto", + "current_turn" + ], + "reasoning_modes": [ + "pro" + ], "search_context_cost_per_query": { "search_context_size_high": 0.01, "search_context_size_low": 0.01, @@ -43477,6 +44672,13 @@ "mode": "responses", "output_cost_per_token": 8e-05, "output_cost_per_token_batches": 4e-05, + "reasoning_contexts": [ + "auto", + "current_turn" + ], + "reasoning_modes": [ + "pro" + ], "search_context_cost_per_query": { "search_context_size_high": 0.01, "search_context_size_low": 0.01, @@ -47292,13 +48494,13 @@ "supports_reasoning": true }, "together_ai/Qwen/Qwen3.7-Max": { - "cache_read_input_token_cost": 3e-07, - "input_cost_per_token": 1.5e-06, + "cache_read_input_token_cost": 5e-07, + "input_cost_per_token": 2.5e-06, "litellm_provider": "together_ai", "max_input_tokens": 1000000, "max_output_tokens": 1000000, "mode": "chat", - "output_cost_per_token": 4.5e-06, + "output_cost_per_token": 7.5e-06, "source": "https://www.together.ai/pricing", "supports_prompt_caching": true }, @@ -47808,6 +49010,7 @@ "cache_creation_input_token_cost_above_200k_tokens": 9e-06, "cache_creation_input_token_cost_above_1hr_above_200k_tokens": 1.44e-05, "cache_read_input_token_cost_above_200k_tokens": 7.2e-07, + "deprecation_date": "2027-04-08", "litellm_provider": "bedrock_converse", "supports_tool_search": true, "max_input_tokens": 200000, @@ -47826,7 +49029,7 @@ "supports_native_structured_output": true, "supports_parallel_tool_use_config": true, "prompt_cache_min_tokens": 1024, - "source": "https://aws.amazon.com/bedrock/pricing/", + "source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-anthropic-claude-sonnet-4-5.md", "token_count_model": { "model": "anthropic.claude-sonnet-4-5-20250929-v1:0", "litellm_provider": "bedrock" @@ -50839,6 +52042,7 @@ "mode": "image_generation", "output_cost_per_image": 0.039, "output_cost_per_image_token": 3e-05, + "output_cost_per_image_token_batches": 1.5e-05, "output_cost_per_reasoning_token": 2.5e-06, "output_cost_per_token": 2.5e-06, "output_cost_per_token_batches": 1.25e-06, @@ -50897,6 +52101,7 @@ "mode": "image_generation", "output_cost_per_image": 0.134, "output_cost_per_image_token": 0.00012, + "output_cost_per_image_token_batches": 6e-05, "output_cost_per_token": 1.2e-05, "output_cost_per_token_above_200k_tokens": 1.8e-05, "output_cost_per_token_above_200k_tokens_priority": 3.24e-05, @@ -50931,13 +52136,14 @@ "mode": "image_generation", "output_cost_per_image": 0.134, "output_cost_per_image_token": 0.00012, + "output_cost_per_image_token_batches": 6e-05, "output_cost_per_token": 1.2e-05, "output_cost_per_token_priority": 2.16e-05, "output_cost_per_token_above_200k_tokens": 1.8e-05, "output_cost_per_token_above_200k_tokens_priority": 3.24e-05, "output_cost_per_token_batches": 6e-06, "supports_reasoning": false, - "source": "https://docs.cloud.google.com/vertex-ai/generative-ai/docs/models/gemini/3-pro-image", + "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", "supported_endpoints": [ "/v1/chat/completions", "/v1/images/generations", @@ -50963,6 +52169,7 @@ "mode": "image_generation", "output_cost_per_image": 0.0672, "output_cost_per_image_token": 6e-05, + "output_cost_per_image_token_batches": 3e-05, "output_cost_per_token": 3e-06, "output_cost_per_token_batches": 1.5e-06, "output_cost_per_token_flex": 1.5e-06, @@ -50990,10 +52197,11 @@ "mode": "image_generation", "output_cost_per_image": 0.0672, "output_cost_per_image_token": 6e-05, + "output_cost_per_image_token_batches": 3e-05, "output_cost_per_token": 3e-06, "output_cost_per_token_batches": 1.5e-06, "supports_reasoning": false, - "source": "https://cloud.google.com/vertex-ai/generative-ai/pricing#gemini-models", + "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", "supported_endpoints": [ "/v1/chat/completions", "/v1/images/generations", @@ -51018,6 +52226,7 @@ "mode": "image_generation", "output_cost_per_image": 0.0336, "output_cost_per_image_token": 3e-05, + "output_cost_per_image_token_batches": 1.5e-05, "output_cost_per_token": 1.5e-06, "output_cost_per_token_batches": 7.5e-07, "output_cost_per_token_flex": 7.5e-07, @@ -52903,15 +54112,21 @@ "xai/grok-4.7": { "cache_read_input_token_cost": 5e-07, "cache_read_input_token_cost_above_200k_tokens": 1e-06, + "cache_read_input_token_cost_above_200k_tokens_batches": 8e-07, + "cache_read_input_token_cost_batches": 4e-07, "input_cost_per_image_token": 2e-06, "input_cost_per_token": 2e-06, "input_cost_per_token_above_200k_tokens": 4e-06, + "input_cost_per_token_above_200k_tokens_batches": 3.2e-06, + "input_cost_per_token_batches": 1.6e-06, "litellm_provider": "xai", "max_input_tokens": 500000, "max_output_tokens": 500000, "mode": "chat", "output_cost_per_token": 6e-06, "output_cost_per_token_above_200k_tokens": 1.2e-05, + "output_cost_per_token_above_200k_tokens_batches": 9.6e-06, + "output_cost_per_token_batches": 4.8e-06, "source": "https://api.x.ai/v1/language-models", "supports_function_calling": true, "supports_prompt_caching": true, @@ -56992,6 +58207,7 @@ ] }, "gpt-4o-mini-transcribe-2025-12-15": { + "deprecation_date": "2027-02-26", "input_cost_per_audio_token": 1.25e-06, "input_cost_per_second": 5e-05, "input_cost_per_token": 1.25e-06, @@ -60173,6 +61389,359 @@ "supports_tool_choice": true, "supports_vision": true }, + "streamlake/deepseek-v4-flash-0731": { + "cache_read_input_token_cost": 1.4e-08, + "input_cost_per_token": 4.4e-07, + "litellm_provider": "streamlake", + "max_input_tokens": 1048576, + "max_output_tokens": 384000, + "mode": "chat", + "output_cost_per_token": 1.32e-06, + "supports_function_calling": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_prompt_caching": true, + "source": "https://www.streamlake.ai/document/DOC/mgrnm4xm362hvp5wyce" + }, + "streamlake/DeepSeek-V4-Pro-0813": { + "cache_read_input_token_cost": 4.4e-08, + "input_cost_per_token": 1.32e-06, + "litellm_provider": "streamlake", + "max_input_tokens": 1048566, + "max_output_tokens": 384000, + "mode": "chat", + "output_cost_per_token": 3.96e-06, + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "source": "https://www.streamlake.ai/document/DOC/mgrnm4xm362hvp5wyce" + }, + "streamlake/DeepSeek-V3": { + "cache_read_input_token_cost": 1.14e-07, + "input_cost_per_token": 2.86e-07, + "litellm_provider": "streamlake", + "max_input_tokens": 56000, + "max_output_tokens": 8000, + "mode": "chat", + "output_cost_per_token": 1.143e-06, + "supports_function_calling": true, + "supports_reasoning": false, + "supports_prompt_caching": true, + "source": "https://www.streamlake.ai/document/DOC/mgrnm4xm362hvp5wyce" + }, + "streamlake/GLM-5.3": { + "cache_read_input_token_cost": 2.6e-07, + "input_cost_per_token": 1.4e-06, + "litellm_provider": "streamlake", + "max_input_tokens": 1048576, + "max_output_tokens": 128000, + "mode": "chat", + "output_cost_per_token": 4.4e-06, + "supports_function_calling": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_assistant_prefill": true, + "supports_prompt_caching": true, + "source": "https://www.streamlake.ai/document/DOC/mgrnm4xm362hvp5wyce" + }, + "streamlake/GLM-5.3-Flash": { + "cache_read_input_token_cost": 3e-08, + "input_cost_per_token": 1.5e-07, + "litellm_provider": "streamlake", + "max_input_tokens": 1048576, + "max_output_tokens": 128000, + "mode": "chat", + "output_cost_per_token": 5e-07, + "supports_function_calling": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_vision": true, + "supports_assistant_prefill": true, + "supports_prompt_caching": true, + "source": "https://www.streamlake.ai/document/DOC/mgrnm4xm362hvp5wyce" + }, + "streamlake/Kimi-K2-Instruct-0905": { + "cache_read_input_token_cost": 1.43e-07, + "input_cost_per_token": 5.71e-07, + "litellm_provider": "streamlake", + "max_input_tokens": 224000, + "max_output_tokens": 32000, + "mode": "chat", + "output_cost_per_token": 2.286e-06, + "supports_function_calling": true, + "supports_reasoning": false, + "supports_prompt_caching": true, + "source": "https://www.streamlake.ai/document/DOC/mgrnm4xm362hvp5wyce" + }, + "streamlake/deepseek-r1": { + "cache_read_input_token_cost": 2.29e-07, + "input_cost_per_token": 5.71e-07, + "litellm_provider": "streamlake", + "max_input_tokens": 98304, + "max_output_tokens": 16000, + "mode": "chat", + "output_cost_per_token": 2.286e-06, + "supports_function_calling": true, + "supports_reasoning": true, + "supports_prompt_caching": true, + "source": "https://www.streamlake.ai/document/DOC/mgrnm4xm362hvp5wyce" + }, + "streamlake/deepseek-v3.1": { + "cache_read_input_token_cost": 2.29e-07, + "input_cost_per_token": 5.71e-07, + "litellm_provider": "streamlake", + "max_input_tokens": 98304, + "max_output_tokens": 32000, + "mode": "chat", + "output_cost_per_token": 1.714e-06, + "supports_function_calling": true, + "supports_reasoning": true, + 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+ "streamlake/qwen3.5-397b-a17b": { + "cache_read_input_token_cost": 1.2e-07, + "input_cost_per_token": 6e-07, + "litellm_provider": "streamlake", + "max_input_tokens": 258048, + "max_output_tokens": 64000, + "mode": "chat", + "output_cost_per_token": 3.6e-06, + "supports_function_calling": true, + "supports_reasoning": true, + "supports_vision": true, + "supports_prompt_caching": true, + "source": "https://www.streamlake.ai/document/DOC/mgrnm4xm362hvp5wyce" + }, + "streamlake/qwen3.6-27b": { + "input_cost_per_token": 6e-07, + "litellm_provider": "streamlake", + "max_input_tokens": 229376, + "max_output_tokens": 64000, + "mode": "chat", + "output_cost_per_token": 3.6e-06, + "supports_function_calling": true, + "supports_vision": true, + "supports_reasoning": false, + "source": "https://www.streamlake.ai/document/DOC/mgrnm4xm362hvp5wyce" + }, + "streamlake/qwen3.6-35b-a3b": { + "input_cost_per_token": 3.75e-07, + "litellm_provider": "streamlake", + "max_input_tokens": 229376, + "max_output_tokens": 64000, + "mode": "chat", + "output_cost_per_token": 2.25e-06, + "supports_function_calling": true, + "supports_vision": true, + "supports_reasoning": false, + "source": "https://www.streamlake.ai/document/DOC/mgrnm4xm362hvp5wyce" + }, + "streamlake/qwen3.8-2.4t-a95b": { + "cache_read_input_token_cost": 2.5e-07, + "input_cost_per_token": 2e-06, + "litellm_provider": "streamlake", + "max_input_tokens": 983616, + "max_output_tokens": 128000, + "mode": "chat", + "output_cost_per_token": 6e-06, + "supports_function_calling": true, + "supports_reasoning": true, + "supports_vision": true, + "cache_creation_input_token_cost": 2.5e-06, + "explicit_cache_read_input_token_cost": 1.7e-07, + "supports_prompt_caching": true, + "source": "https://www.streamlake.ai/document/DOC/mgrnm4xm362hvp5wyce" + }, + "streamlake/qwen3.8-27b": { + "cache_read_input_token_cost": 1e-07, + "input_cost_per_token": 5e-07, + "litellm_provider": "streamlake", + "max_input_tokens": 983616, + "max_output_tokens": 128000, + "mode": "chat", + "output_cost_per_token": 3e-06, + "supports_function_calling": true, + "supports_reasoning": true, + "supports_vision": true, + "cache_creation_input_token_cost": 6.25e-07, + "explicit_cache_read_input_token_cost": 5e-08, + "supports_prompt_caching": true, + "source": "https://www.streamlake.ai/document/DOC/mgrnm4xm362hvp5wyce" + }, "deepseek-v4-flash": { "cache_creation_input_token_cost": 0.0, "cache_read_input_token_cost": 6e-09, @@ -60908,6 +62477,39 @@ "supports_reasoning": true, "supports_vision": false }, + "tencent/seedream-image-v5.0-flash": { + "litellm_provider": "tencent", + "mode": "image_generation", + "output_cost_per_image": 0.018, + "output_cost_per_image_token": 1.6e-06, + "source": "https://cloud.tencent.com/document/product/1823/130055", + "supported_endpoints": [ + "/v1/images/generations", + "/v1/images/edits" + ] + }, + "tencent/seedream-image-v5.0-lite": { + "litellm_provider": "tencent", + "mode": "image_generation", + "output_cost_per_image": 0.035, + "output_cost_per_image_token": 1.6e-06, + "source": "https://www.tencentcloud.com/document/product/1300/78937", + "supported_endpoints": [ + "/v1/images/generations", + "/v1/images/edits" + ] + }, + "tencent/seedream-image-v5.0-pro": { + "litellm_provider": "tencent", + "mode": "image_generation", + "output_cost_per_image": 0.09, + "output_cost_per_image_token": 1.6e-06, + "source": "https://www.tencentcloud.com/document/product/1300/78937", + "supported_endpoints": [ + "/v1/images/generations", + "/v1/images/edits" + ] + }, "cognition/swe-1.6": { "input_cost_per_token": 5e-07, "output_cost_per_token": 2.5e-06, @@ -61455,6 +63057,14 @@ "litellm_provider": "anthropic" } }, + { + "name": "typesafe-jev-ids", + "pattern": "^jev-(?:latest|preview|1\\.13\\.0|1\\.14\\.0)$", + "description": "A bare Jev id that has a typesafe/ price entry (jev-latest, jev-preview, jev-1.13.0, jev-1.14.0), the name the /typesafe pass-through forwards to TypeSafe. Listed by name, matched case-insensitively like every rule here, so foo/jev-latest or a model group named like a Jev id TypeSafe does not serve, such as jev-1.0 or jev-internal-router, never resolves to typesafe. A new Jev version goes here together with its price entry. Provider inference feeds the proxy's provider/* wildcard access checks, so this rule is what lets typesafe/* on a key, team or project allowlist cover a jev-latest request.", + "model_info": { + "litellm_provider": "typesafe" + } + }, { "name": "claude-family-baseline", "pattern": "claude-[a-z]+-\\d+(?:[-.]\\d+)?(?:-\\d{8})?", @@ -64529,6 +66139,7 @@ ] }, "xai/grok-imagine-image-pro": { + "deprecation_date": "2026-05-15", "input_cost_per_image": 0.05, "litellm_provider": "xai", "mode": "image_generation", @@ -64935,9 +66546,14 @@ "max_output_tokens": 256000, "mode": "chat", "output_cost_per_token": 2e-06, + "reasoning_effort_levels": [ + "none", + "high" + ], "source": "https://mistral.ai/news/devstral-2-vibe-cli", "supports_assistant_prefill": true, "supports_function_calling": true, + "supports_reasoning": true, "supports_response_schema": true, "supports_tool_choice": true }, @@ -65281,6 +66897,180 @@ "supports_reasoning": true, "supports_tool_choice": true }, + "zerogpu/deepseek-v4.1-flash": { + "cache_read_input_token_cost": 3e-09, + "input_cost_per_token": 3e-07, + "litellm_provider": "zerogpu", + "max_input_tokens": 1048576, + "max_output_tokens": 65536, + "mode": "chat", + "output_cost_per_token": 1.2e-06, + "source": "https://docs.zerogpu.ai/docs/model-catalog", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_tool_choice": true + }, + "zerogpu/glm-5.3-flash": { + "cache_read_input_token_cost": 1.5e-08, + "input_cost_per_token": 1e-07, + "litellm_provider": "zerogpu", + "max_input_tokens": 1048576, + "max_output_tokens": 32768, + "mode": "chat", + "output_cost_per_token": 3.5e-07, + "source": "https://docs.zerogpu.ai/docs/model-catalog", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_tool_choice": true + }, + "zerogpu/gpt-4.1-mini": { + "cache_read_input_token_cost": 1e-07, + "input_cost_per_token": 4e-07, + "litellm_provider": "zerogpu", + "max_input_tokens": 1047576, + "max_output_tokens": 32768, + "mode": "chat", + "output_cost_per_token": 1.6e-06, + "source": "https://docs.zerogpu.ai/docs/model-catalog", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_response_schema": true, + "supports_tool_choice": true + }, + "zerogpu/gpt-5.4-nano": { + "cache_read_input_token_cost": 2e-08, + "input_cost_per_token": 2e-07, + "litellm_provider": "zerogpu", + "max_input_tokens": 272000, + "max_output_tokens": 128000, + "mode": "chat", + "output_cost_per_token": 1.25e-06, + "source": "https://docs.zerogpu.ai/docs/model-catalog", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_tool_choice": true + }, + "zerogpu/gpt-5.6-luna": { + "cache_read_input_token_cost": 2e-07, + "input_cost_per_token": 2e-07, + "litellm_provider": "zerogpu", + "max_input_tokens": 272000, + "max_output_tokens": 128000, + "mode": "chat", + "output_cost_per_token": 1.2e-06, + "source": "https://docs.zerogpu.ai/docs/model-catalog", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_tool_choice": true + }, + "zerogpu/gpt-6-luna": { + "cache_read_input_token_cost": 1e-08, + "input_cost_per_token": 1e-07, + "litellm_provider": "zerogpu", + "max_input_tokens": 272000, + "max_output_tokens": 128000, + "mode": "chat", + "output_cost_per_token": 5e-07, + "source": "https://docs.zerogpu.ai/docs/model-catalog", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_tool_choice": true, + "supports_vision": true + }, + "zerogpu/gpt-oss-120b": { + "cache_read_input_token_cost": 3e-08, + "input_cost_per_token": 1.5e-07, + "litellm_provider": "zerogpu", + "max_input_tokens": 128000, + "max_output_tokens": 32768, + "mode": "chat", + "output_cost_per_token": 6e-07, + "source": "https://docs.zerogpu.ai/docs/model-catalog", + "supports_function_calling": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_tool_choice": true + }, + "zerogpu/LFM2.5-1.2B-Instruct": { + "input_cost_per_token": 2e-08, + "litellm_provider": "zerogpu", + "max_input_tokens": 32768, + "max_output_tokens": 8192, + "mode": "chat", + "output_cost_per_token": 5e-08, + "source": "https://docs.zerogpu.ai/docs/model-catalog" + }, + "zerogpu/LFM2.5-1.2B-Thinking": { + "input_cost_per_token": 2e-08, + "litellm_provider": "zerogpu", + "max_input_tokens": 32768, + "max_output_tokens": 8192, + "mode": "chat", + "output_cost_per_token": 5e-08, + "source": "https://docs.zerogpu.ai/docs/model-catalog" + }, + "zerogpu/llama-3.1-8b-instruct-fast": { + "cache_read_input_token_cost": 2.5e-08, + "input_cost_per_token": 1.5e-07, + "litellm_provider": "zerogpu", + "max_input_tokens": 131072, + "max_output_tokens": 8192, + "mode": "chat", + "output_cost_per_token": 2.8e-07, + "source": "https://docs.zerogpu.ai/docs/model-catalog", + "supports_function_calling": true, + "supports_response_schema": true, + "supports_tool_choice": true + }, + "zerogpu/llama-3.2-3b-instruct-fast": { + "cache_read_input_token_cost": 2.5e-08, + "input_cost_per_token": 5e-08, + "litellm_provider": "zerogpu", + "max_input_tokens": 131072, + "max_output_tokens": 8192, + "mode": "chat", + "output_cost_per_token": 3e-07, + "source": "https://docs.zerogpu.ai/docs/model-catalog" + }, + "zerogpu/qwen3-30b-a3b-fp8": { + "cache_read_input_token_cost": 5e-08, + "input_cost_per_token": 1e-07, + "litellm_provider": "zerogpu", + "max_input_tokens": 32768, + "max_output_tokens": 16384, + "mode": "chat", + "output_cost_per_token": 4.5e-07, + "source": "https://docs.zerogpu.ai/docs/model-catalog", + "supports_function_calling": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_tool_choice": true + }, + "zerogpu/qwen3.6-35b-a3b": { + "cache_read_input_token_cost": 2e-07, + "input_cost_per_token": 2e-07, + "litellm_provider": "zerogpu", + "max_input_tokens": 262144, + "max_output_tokens": 16384, + "mode": "chat", + "output_cost_per_token": 1.5e-06, + "source": "https://docs.zerogpu.ai/docs/model-catalog", + "supports_function_calling": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_tool_choice": true, + "supports_vision": true + }, "together_ai/Qwen/Qwen3.8-Flash": { "input_cost_per_token": 1.5e-07, "litellm_provider": "together_ai", @@ -65366,6 +67156,7 @@ ] }, "scaleway/glm-5.2": { + "deprecation_date": "2026-11-16", "input_cost_per_token": 1.8e-06, "litellm_provider": "scaleway", "max_input_tokens": 256000, @@ -67924,6 +69715,11 @@ "output_cost_per_token": 8.8e-06, "output_cost_per_token_batches": 4.4e-06, "output_cost_per_token_priority": 1.54e-05, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" }, "azure/eu/gpt-4.1-mini": { @@ -67938,6 +69734,11 @@ "output_cost_per_token": 1.76e-06, "output_cost_per_token_batches": 8.8e-07, "output_cost_per_token_priority": 3.08e-06, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" }, "azure/eu/gpt-4.1-nano": { @@ -67976,6 +69777,11 @@ "output_cost_per_token": 1.1e-05, "output_cost_per_token_batches": 5.5e-06, "output_cost_per_token_priority": 2.2e-05, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" }, "azure/eu/gpt-5-codex": { @@ -68000,6 +69806,11 @@ "output_cost_per_token": 2.2e-06, "output_cost_per_token_batches": 1.1e-06, "output_cost_per_token_priority": 3.96e-06, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" }, "azure/eu/gpt-5-nano": { @@ -68012,6 +69823,11 @@ "mode": "chat", "output_cost_per_token": 4.4e-07, "output_cost_per_token_batches": 2.2e-07, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" }, "azure/eu/gpt-5-pro": { @@ -68022,6 +69838,11 @@ "mode": "responses", "output_cost_per_token": 0.000132, "output_cost_per_token_batches": 6.6e-05, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" }, "azure/eu/gpt-5.1-codex-max": { @@ -68046,6 +69867,11 @@ "output_cost_per_token": 1.54e-05, "output_cost_per_token_batches": 7.7e-06, "output_cost_per_token_priority": 3.08e-05, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" }, "azure/eu/gpt-5.2-codex": { @@ -68064,6 +69890,11 @@ "mode": "responses", "output_cost_per_token": 0.0001848, "output_cost_per_token_batches": 9.24e-05, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" }, "azure/eu/gpt-5.3-codex": { @@ -68076,6 +69907,11 @@ "mode": "responses", "output_cost_per_token": 1.54e-05, "output_cost_per_token_priority": 3.08e-05, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" }, "azure/eu/gpt-5.4-mini": { @@ -68091,6 +69927,11 @@ "output_cost_per_token": 4.95e-06, "output_cost_per_token_batches": 2.475e-06, "output_cost_per_token_priority": 9.9e-06, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" }, "azure/eu/gpt-5.4-nano": { @@ -68103,6 +69944,11 @@ "mode": "chat", "output_cost_per_token": 1.375e-06, "output_cost_per_token_batches": 6.875e-07, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" }, "azure/eu/gpt-5.4-pro": { @@ -68117,6 +69963,11 @@ "output_cost_per_token_above_272k_tokens": 0.000297, "output_cost_per_token_above_272k_tokens_batches": 0.0001485, "output_cost_per_token_batches": 9.9e-05, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" }, "azure/eu/gpt-6-astra": { @@ -68133,6 +69984,11 @@ "mode": "chat", "output_cost_per_token": 6e-05, "output_cost_per_token_above_272k_tokens": 9e-05, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://learn.microsoft.com/en-us/azure/foundry/foundry-models/concepts/models-sold-directly-by-azure", "supported_endpoints": [ "/v1/chat/completions", @@ -68177,9 +70033,9 @@ "output_cost_per_token": 6e-07, "output_cost_per_token_above_272k_tokens": 9e-07, "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 }, "source": "https://azure.microsoft.com/en-us/blog/gpt-6-astra-sol-and-luna-for-production-agents-in-microsoft-foundry/", "supported_endpoints": [ @@ -68225,9 +70081,9 @@ "output_cost_per_token": 1.2e-05, "output_cost_per_token_above_272k_tokens": 1.8e-05, "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 }, "source": "https://azure.microsoft.com/en-us/blog/gpt-6-astra-sol-and-luna-for-production-agents-in-microsoft-foundry/", "supported_endpoints": [ @@ -68279,6 +70135,11 @@ "mode": "chat", "output_cost_per_token": 8.8e-06, "output_cost_per_token_batches": 4.4e-06, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" }, "azure/eu/o3-2025-04-16": { @@ -68292,6 +70153,11 @@ "mode": "chat", "output_cost_per_token": 8.8e-06, "output_cost_per_token_batches": 4.4e-06, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" }, "azure/eu/o3-deep-research": { @@ -68314,6 +70180,11 @@ "mode": "chat", "output_cost_per_token": 4.84e-06, "output_cost_per_token_batches": 2.42e-06, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" }, "azure/eu/o4-mini-2025-04-16": { @@ -68327,6 +70198,11 @@ "mode": "chat", "output_cost_per_token": 4.84e-06, "output_cost_per_token_batches": 2.42e-06, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" }, "azure/eu/text-embedding-3-large": { @@ -68420,6 +70296,11 @@ "output_cost_per_token": 8.8e-06, "output_cost_per_token_batches": 4.4e-06, "output_cost_per_token_priority": 1.54e-05, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" }, "azure/us/gpt-4.1-mini": { @@ -68434,6 +70315,11 @@ "output_cost_per_token": 1.76e-06, "output_cost_per_token_batches": 8.8e-07, "output_cost_per_token_priority": 3.08e-06, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" }, "azure/us/gpt-4.1-nano": { @@ -68472,6 +70358,11 @@ "output_cost_per_token": 1.1e-05, "output_cost_per_token_batches": 5.5e-06, "output_cost_per_token_priority": 2.2e-05, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" }, "azure/us/gpt-5-codex": { @@ -68496,6 +70387,11 @@ "output_cost_per_token": 2.2e-06, "output_cost_per_token_batches": 1.1e-06, "output_cost_per_token_priority": 3.96e-06, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" }, "azure/us/gpt-5-nano": { @@ -68508,6 +70404,11 @@ "mode": "chat", "output_cost_per_token": 4.4e-07, "output_cost_per_token_batches": 2.2e-07, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" }, "azure/us/gpt-5-pro": { @@ -68518,6 +70419,11 @@ "mode": "responses", "output_cost_per_token": 0.000132, "output_cost_per_token_batches": 6.6e-05, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" }, "azure/us/gpt-5.1-codex-max": { @@ -68542,6 +70448,11 @@ "output_cost_per_token": 1.54e-05, "output_cost_per_token_batches": 7.7e-06, "output_cost_per_token_priority": 3.08e-05, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" }, "azure/us/gpt-5.2-codex": { @@ -68560,6 +70471,11 @@ "mode": "responses", "output_cost_per_token": 0.0001848, "output_cost_per_token_batches": 9.24e-05, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" }, "azure/us/gpt-5.3-codex": { @@ -68572,6 +70488,11 @@ "mode": "responses", "output_cost_per_token": 1.54e-05, "output_cost_per_token_priority": 3.08e-05, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" }, "azure/us/gpt-5.4-mini": { @@ -68587,6 +70508,11 @@ "output_cost_per_token": 4.95e-06, "output_cost_per_token_batches": 2.475e-06, "output_cost_per_token_priority": 9.9e-06, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" }, "azure/us/gpt-5.4-nano": { @@ -68599,6 +70525,11 @@ "mode": "chat", "output_cost_per_token": 1.375e-06, "output_cost_per_token_batches": 6.875e-07, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" }, "azure/us/gpt-5.4-pro": { @@ -68613,6 +70544,11 @@ "output_cost_per_token_above_272k_tokens": 0.000297, "output_cost_per_token_above_272k_tokens_batches": 0.0001485, "output_cost_per_token_batches": 9.9e-05, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" }, "azure/us/o1-mini": { @@ -68659,7 +70595,7 @@ "cache_creation_input_audio_token_cost": 4e-07, "cache_read_input_audio_token_cost": 4e-07, "cache_read_input_token_cost": 4e-07, - "deprecation_date": "2026-10-31", + "deprecation_date": "2027-01-20", "input_cost_per_audio_token": 3.2e-05, "input_cost_per_image_token": 5e-06, "input_cost_per_token": 4e-06, @@ -69827,6 +71763,201 @@ "supports_reasoning": true, "supports_vision": true }, + "aiand/deepseek-ai/deepseek-v4-flash": { + "cache_read_input_token_cost": 8e-08, + "input_cost_per_token": 1.5e-07, + "litellm_provider": "aiand", + "max_input_tokens": 1048576, + "max_output_tokens": 384000, + "mode": "chat", + "output_cost_per_token": 2.5e-07, + "source": "https://api.aiand.com/v1/models", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_tool_choice": true, + "supports_vision": false + }, + "aiand/deepseek-ai/deepseek-v4-pro": { + "cache_read_input_token_cost": 2.5e-07, + "input_cost_per_token": 1e-06, + "litellm_provider": "aiand", + "max_input_tokens": 1048576, + "max_output_tokens": 384000, + "mode": "chat", + "output_cost_per_token": 2.5e-06, + "source": "https://api.aiand.com/v1/models", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_tool_choice": true, + "supports_vision": false + }, + "aiand/deepseek-ai/deepseek-v4.1-flash": { + "cache_read_input_token_cost": 2e-08, + "input_cost_per_token": 3e-07, + "litellm_provider": "aiand", + "max_input_tokens": 1048576, + "max_output_tokens": 384000, + "mode": "chat", + "output_cost_per_token": 6e-07, + "source": "https://api.aiand.com/v1/models", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_tool_choice": true, + "supports_vision": true + }, + "aiand/google/gemma-4-31b-it": { + "cache_read_input_token_cost": 5e-08, + "input_cost_per_token": 2e-07, + "litellm_provider": "aiand", + "max_input_tokens": 262144, + "max_output_tokens": 32768, + "mode": "chat", + "output_cost_per_token": 5e-07, + "source": "https://api.aiand.com/v1/models", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_tool_choice": true, + "supports_vision": true + }, + "aiand/moonshotai/kimi-k2.7-code": { + "cache_read_input_token_cost": 2e-07, + "input_cost_per_token": 7.5e-07, + "litellm_provider": "aiand", + "max_input_tokens": 262144, + "max_output_tokens": 262144, + "mode": "chat", + "output_cost_per_token": 3.5e-06, + "source": "https://api.aiand.com/v1/models", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_tool_choice": true, + "supports_vision": true + }, + "aiand/moonshotai/kimi-k3": { + "cache_read_input_token_cost": 5e-07, + "input_cost_per_token": 3e-06, + "litellm_provider": "aiand", + "max_input_tokens": 1048576, + "max_output_tokens": 131072, + "mode": "chat", + "output_cost_per_token": 1.25e-05, + "source": "https://api.aiand.com/v1/models", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_tool_choice": true, + "supports_vision": true + }, + "aiand/motif-technologies/motif-3": { + "cache_read_input_token_cost": 2e-07, + "input_cost_per_token": 5e-07, + "litellm_provider": "aiand", + "max_input_tokens": 262144, + "max_output_tokens": 262144, + "mode": "chat", + "output_cost_per_token": 2e-06, + "source": "https://api.aiand.com/v1/models", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_tool_choice": true, + "supports_vision": false + }, + "aiand/openai/gpt-oss-120b": { + "cache_read_input_token_cost": 8e-08, + "input_cost_per_token": 1.5e-07, + "litellm_provider": "aiand", + "max_input_tokens": 131072, + "max_output_tokens": 32768, + "mode": "chat", + "output_cost_per_token": 6e-07, + "source": "https://api.aiand.com/v1/models", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_tool_choice": true, + "supports_vision": false + }, + "aiand/qwen/qwen3.6-27b": { + "cache_read_input_token_cost": 2e-07, + "input_cost_per_token": 3.2e-07, + "litellm_provider": "aiand", + "max_input_tokens": 262144, + "max_output_tokens": 65536, + "mode": "chat", + "output_cost_per_token": 3.2e-06, + "source": "https://api.aiand.com/v1/models", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_tool_choice": true, + "supports_vision": true + }, + "aiand/qwen/qwen3.8-27b": { + "cache_read_input_token_cost": 2e-07, + "input_cost_per_token": 4e-07, + "litellm_provider": "aiand", + "max_input_tokens": 262144, + "max_output_tokens": 32768, + "mode": "chat", + "output_cost_per_token": 3e-06, + "source": "https://api.aiand.com/v1/models", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_tool_choice": true, + "supports_vision": true + }, + "aiand/zai-org/glm-5.2": { + "cache_read_input_token_cost": 3e-07, + "input_cost_per_token": 1e-06, + "litellm_provider": "aiand", + "max_input_tokens": 1048576, + "max_output_tokens": 131072, + "mode": "chat", + "output_cost_per_token": 4e-06, + "source": "https://api.aiand.com/v1/models", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_tool_choice": true, + "supports_vision": false + }, + "aiand/zai-org/glm-5.3": { + "cache_read_input_token_cost": 3e-07, + "input_cost_per_token": 1e-06, + "litellm_provider": "aiand", + "max_input_tokens": 1048576, + "max_output_tokens": 131072, + "mode": "chat", + "output_cost_per_token": 4e-06, + "source": "https://api.aiand.com/v1/models", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_tool_choice": true, + "supports_vision": false + }, + "aiand/zai-org/glm-5.3-flash": { + "cache_read_input_token_cost": 3e-08, + "input_cost_per_token": 1.5e-07, + "litellm_provider": "aiand", + "max_input_tokens": 1048550, + "max_output_tokens": 131072, + "mode": "chat", + "output_cost_per_token": 5e-07, + "source": "https://api.aiand.com/v1/models", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_tool_choice": true, + "supports_vision": true + }, "bespoke/nimble-latest": { "input_cost_per_token": 0.0, "litellm_provider": "bespoke", @@ -70809,6 +72940,7 @@ "xai/grok-code-fast-1": { "cache_read_input_token_cost": 2e-07, "cache_read_input_token_cost_above_200k_tokens": 4e-07, + "deprecation_date": "2026-05-15", "input_cost_per_image_token": 1e-06, "input_cost_per_token": 1e-06, "input_cost_per_token_above_200k_tokens": 2e-06, @@ -71705,7 +73837,7 @@ "supports_mid_conversation_system": true, "cache_creation_input_token_cost": 2.5e-06, "cache_creation_input_token_cost_above_1hr": 4e-06, - "cache_read_input_token_cost": 2e-07, + "cache_read_input_token_cost": 1e-07, "deprecation_date": "2027-09-29", "input_cost_per_token": 2e-06, "litellm_provider": "azure_ai", @@ -72312,15 +74444,15 @@ "gpt-6.1-sol": { "cache_creation_input_token_cost": 2.5e-06, "cache_creation_input_token_cost_above_12hr": 5e-06, + "cache_creation_input_token_cost_above_12hr_ultrafast": 3e-05, + "cache_creation_input_token_cost_above_12hr_batches": 2.5e-06, "cache_creation_input_token_cost_above_12hr_above_272k_tokens": 1e-05, "cache_creation_input_token_cost_above_12hr_above_272k_tokens_batches": 5e-06, "cache_creation_input_token_cost_above_12hr_above_272k_tokens_flex": 5e-06, "cache_creation_input_token_cost_above_12hr_above_272k_tokens_priority": 2e-05, "cache_creation_input_token_cost_above_12hr_above_272k_tokens_ultrafast": 6e-05, - "cache_creation_input_token_cost_above_12hr_batches": 2.5e-06, "cache_creation_input_token_cost_above_12hr_flex": 2.5e-06, "cache_creation_input_token_cost_above_12hr_priority": 1e-05, - "cache_creation_input_token_cost_above_12hr_ultrafast": 3e-05, "cache_creation_input_token_cost_above_272k_tokens": 5e-06, "cache_creation_input_token_cost_above_272k_tokens_batches": 2.5e-06, "cache_creation_input_token_cost_above_272k_tokens_flex": 2.5e-06, @@ -72364,6 +74496,15 @@ "output_cost_per_token_flex": 5e-06, "output_cost_per_token_priority": 2e-05, "output_cost_per_token_ultrafast": 6e-05, + "reasoning_contexts": [ + "auto", + "current_turn", + "all_turns" + ], + "reasoning_modes": [ + "standard", + "pro" + ], "regional_processing_uplift_multiplier_eu": 1.1, "regional_processing_uplift_multiplier_us": 1.1, "search_context_cost_per_query": { @@ -72758,6 +74899,7 @@ "mode": "image_generation", "output_cost_per_image": 0.0336, "output_cost_per_image_token": 3e-05, + "output_cost_per_image_token_batches": 1.5e-05, "output_cost_per_token": 7.5e-06, "output_cost_per_token_batches": 3.75e-06, "output_cost_per_token_priority": 1.35e-05, @@ -72803,6 +74945,7 @@ "mode": "image_generation", "output_cost_per_image": 0.0336, "output_cost_per_image_token": 3e-05, + "output_cost_per_image_token_batches": 1.5e-05, "output_cost_per_token": 7.5e-06, "output_cost_per_token_batches": 3.75e-06, "output_cost_per_token_priority": 1.35e-05, @@ -74281,14 +76424,14 @@ "supports_vision": true }, "wandb/nvidia/NVIDIA-Nemotron-3.5-Super-VL-120B-A12B": { - "cache_read_input_token_cost": 2e-08, - "input_cost_per_token": 1.5e-07, + "cache_read_input_token_cost": 5e-08, + "input_cost_per_token": 2.5e-07, "litellm_provider": "wandb", "max_input_tokens": 1049000, "max_output_tokens": 943718, "mode": "chat", - "output_cost_per_token": 7.5e-07, - "source": "https://openrouter.ai/api/v1/models/nvidia/nemotron-3.5-super-vl/endpoints", + "output_cost_per_token": 1.5e-06, + "source": "https://www.coreweave.com/products/coreweave-forge/serverless-inference", "supports_function_calling": true, "supports_prompt_caching": true, "supports_reasoning": true, @@ -75863,6 +78006,15 @@ "output_cost_per_token_batches": 2.5e-06, "output_cost_per_token_flex": 2.5e-06, "output_cost_per_token_priority": 1e-05, + "reasoning_contexts": [ + "auto", + "current_turn", + "all_turns" + ], + "reasoning_modes": [ + "standard", + "pro" + ], "regional_processing_uplift_multiplier_eu": 1.1, "regional_processing_uplift_multiplier_us": 1.1, "search_context_cost_per_query": {"search_context_size_high":0.01,"search_context_size_low":0.01,"search_context_size_medium":0.01}, @@ -75995,7 +78147,7 @@ "supports_xhigh_reasoning_effort": true }, "baseten/decision-models/baseten-elephant-9b-latest": { - "input_cost_per_token": 0.0, + "input_cost_per_token": 3.5e-08, "litellm_provider": "baseten", "max_input_tokens": 16384, "mode": "decisions", @@ -76004,7 +78156,7 @@ "supports_vision": true }, "baseten/decision-models/baseten-mammoth-27b-latest": { - "input_cost_per_token": 0.0, + "input_cost_per_token": 1e-07, "litellm_provider": "baseten", "max_input_tokens": 16384, "mode": "decisions", @@ -76036,13 +78188,13 @@ "supports_vision": true }, "refuseless/glm-5.3-abliterated": { - "cache_read_input_token_cost": 2.5e-07, - "input_cost_per_token": 1.25e-06, + "cache_read_input_token_cost": 1.5e-07, + "input_cost_per_token": 1e-06, "litellm_provider": "refuseless", "max_input_tokens": 1048576, "max_output_tokens": 131072, "mode": "chat", - "output_cost_per_token": 2.25e-06, + "output_cost_per_token": 2e-06, "source": "https://refuseless.com/pricing", "supports_function_calling": true, "supports_prompt_caching": true, @@ -76057,13 +78209,13 @@ ] }, "refuseless/glm-5.3-flash-abliterated": { - "cache_read_input_token_cost": 1.5e-07, - "input_cost_per_token": 2.5e-07, + "cache_read_input_token_cost": 4e-08, + "input_cost_per_token": 1.2e-07, "litellm_provider": "refuseless", "max_input_tokens": 1048576, "max_output_tokens": 131072, "mode": "chat", - "output_cost_per_token": 8e-07, + "output_cost_per_token": 5e-07, "source": "https://refuseless.com/pricing", "supports_function_calling": true, "supports_prompt_caching": true, @@ -76078,13 +78230,13 @@ ] }, "refuseless/deepseek-v4.1-flash-abliterated": { - "cache_read_input_token_cost": 4.5e-08, - "input_cost_per_token": 2.2e-07, + "cache_read_input_token_cost": 3.5e-08, + "input_cost_per_token": 1.4e-07, "litellm_provider": "refuseless", "max_input_tokens": 1048576, "max_output_tokens": 130000, "mode": "chat", - "output_cost_per_token": 7.5e-07, + "output_cost_per_token": 5e-07, "source": "https://refuseless.com/pricing", "supports_function_calling": true, "supports_prompt_caching": true, @@ -76140,6 +78292,15 @@ "max" ] }, + "fireworks_ai/accounts/fireworks/models/rune": { + "cache_read_input_token_cost": 8.4e-09, + "input_cost_per_token": 4.2e-08, + "litellm_provider": "fireworks_ai", + "max_input_tokens": 262144, + "mode": "decisions", + "output_cost_per_token": 0.0, + "source": "https://api.fireworks.ai/v1/serverless/models?format=nested" + }, "bedrock_mantle/openai.gpt-6.1-terra": { "cache_creation_input_token_cost": 1.375e-06, "cache_creation_input_token_cost_above_272k_tokens": 2.75e-06, @@ -76177,5 +78338,738 @@ "supports_vision": true, "supports_xhigh_reasoning_effort": true, "use_openai_responses_path": true + }, + "databricks/databricks-claude-haiku-5-5": { + "cache_creation_input_token_cost": 1.2502e-07, + "cache_creation_input_token_cost_above_100k_tokens": 6.2503e-07, + "cache_creation_input_token_cost_above_1hr": 1.9999e-07, + "cache_creation_input_token_cost_above_1hr_above_100k_tokens": 1.00002e-06, + "cache_read_input_token_cost": 1.001e-08, + "cache_read_input_token_cost_above_100k_tokens": 4.998e-08, + "input_cost_per_token": 1.0003e-07, + "input_cost_per_token_above_100k_tokens": 5.0001e-07, + "input_dbu_cost_per_token": 1.429e-06, + "litellm_provider": "databricks", + "max_input_tokens": 1000000, + "max_output_tokens": 128000, + "metadata": { + "notes": "Costs per token are the published Global DBU rates times $0.070 per DBU. The '*_dbu_cost_per_token' fields are provided for reference; cost calculation reads the dollar '*_cost_per_token' fields." + }, + "mode": "chat", + "output_cost_per_token": 5.0001e-07, + "output_cost_per_token_above_100k_tokens": 2.49998e-06, + "output_dbu_cost_per_token": 7.143e-06, + "prompt_cache_min_tokens": 512.0, + "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", + "supports_adaptive_thinking": true, + "supports_anthropic_thinking_payload": true, + "supports_assistant_prefill": false, + "supports_function_calling": true, + "supports_mid_conversation_system": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_sampling_params": false, + "supports_tool_choice": true, + "supports_vision": true, + "thinking_always_on": false + }, + "databricks/databricks-claude-sonnet-5-5": { + "cache_creation_input_token_cost": 2.49998e-06, + "cache_creation_input_token_cost_above_1hr": 4.00001e-06, + "cache_read_input_token_cost": 1.0003e-07, + "input_cost_per_token": 1.99997e-06, + "input_dbu_cost_per_token": 2.8571e-05, + "litellm_provider": "databricks", + "max_input_tokens": 1000000, + "max_output_tokens": 128000, + "metadata": { + "notes": "Costs per token are the published Global DBU rates times $0.070 per DBU. The '*_dbu_cost_per_token' fields are provided for reference; cost calculation reads the dollar '*_cost_per_token' fields." + }, + "mode": "chat", + "output_cost_per_token": 9.99999e-06, + "output_dbu_cost_per_token": 0.00014286, + "prompt_cache_min_tokens": 512.0, + "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", + "supports_adaptive_thinking": true, + "supports_anthropic_thinking_payload": true, + "supports_assistant_prefill": false, + "supports_function_calling": true, + "supports_mid_conversation_system": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_sampling_params": false, + "supports_tool_choice": true, + "supports_vision": false, + "thinking_always_on": true + }, + "databricks/databricks-deepseek-v4-1-flash": { + "cache_creation_input_token_cost": 3.0002e-07, + "cache_read_input_token_cost": 3.003e-08, + "deprecation_date": "2026-11-19", + "input_cost_per_token": 3.0002e-07, + "input_dbu_cost_per_token": 4.286e-06, + "litellm_provider": "databricks", + "max_input_tokens": 1000000, + "max_output_tokens": 384000, + "metadata": { + "notes": "Costs per token are the published Global DBU rates times $0.070 per DBU. The '*_dbu_cost_per_token' fields are provided for reference; cost calculation reads the dollar '*_cost_per_token' fields. The docs list only databricks-deepseek-v4-1-flash (retiring 2026-11-19) and databricks-deepseek-v4-1-flash-1017, so the pricing page's 'DeepSeek V4.1 Flash (0910)' row prices the unsuffixed endpoint." + }, + "mode": "chat", + "output_cost_per_token": 1.20001e-06, + "output_dbu_cost_per_token": 1.7143e-05, + "source": "https://docs.databricks.com/aws/en/machine-learning/foundation-model-apis/supported-models", + "supported_modalities": [ + "text", + "image" + ], + "supported_output_modalities": [ + "text" + ], + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_tool_choice": true, + "supports_vision": true, + "input_cost_per_token_priority": 5.25e-07, + "output_cost_per_token_priority": 2.1e-06, + "cache_read_input_token_cost_priority": 5.25e-08, + "cache_creation_input_token_cost_priority": 5.25e-07 + }, + "databricks/databricks-deepseek-v4-1-flash-1017": { + "cache_creation_input_token_cost": 3.0002e-07, + "cache_read_input_token_cost": 7e-09, + "input_cost_per_token": 3.0002e-07, + "input_dbu_cost_per_token": 4.286e-06, + "litellm_provider": "databricks", + "max_input_tokens": 1000000, + "max_output_tokens": 384000, + "metadata": { + "notes": "Costs per token are the published Global DBU rates times $0.070 per DBU. The '*_dbu_cost_per_token' fields are provided for reference; cost calculation reads the dollar '*_cost_per_token' fields." + }, + "mode": "chat", + "output_cost_per_token": 1.20001e-06, + "output_dbu_cost_per_token": 1.7143e-05, + "source": "https://www.databricks.com/product/pricing/foundation-model-serving", + "supported_modalities": [ + "text", + "image" + ], + "supported_output_modalities": [ + "text" + ], + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_tool_choice": true, + "supports_vision": true + }, + "databricks/databricks-gemini-2-5-flash-lite": { + "cache_creation_input_token_cost": 1.2502e-07, + "cache_read_input_audio_token_cost": 3.752e-08, + "cache_read_input_token_cost": 1.253e-08, + "input_cost_per_audio_token": 3.7499e-07, + "input_cost_per_image_token": 1.2502e-07, + "input_cost_per_token": 1.2502e-07, + "input_dbu_cost_per_token": 1.786e-06, + "litellm_provider": "databricks", + "max_input_tokens": 1048576, + "max_output_tokens": 65536, + "metadata": { + "notes": "Costs per token are the published Global DBU rates times $0.070 per DBU. The '*_dbu_cost_per_token' fields are provided for reference; cost calculation reads the dollar '*_cost_per_token' fields." + }, + "mode": "chat", + "output_cost_per_token": 5.0001e-07, + "output_dbu_cost_per_token": 7.143e-06, + "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", + "supported_modalities": [ + "text", + "image", + "audio", + "video" + ], + "supported_output_modalities": [ + "text" + ], + "supports_audio_input": true, + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_tool_choice": true, + "supports_video_input": true, + "supports_vision": true + }, + "databricks/databricks-gemini-3-1-flash-lite-image": { + "cache_creation_input_token_cost": 3.1248e-07, + "cache_read_input_token_cost": 3.1248e-07, + "input_cost_per_image_token": 3.1248e-07, + "input_cost_per_token": 3.1248e-07, + "input_dbu_cost_per_token": 4.464e-06, + "litellm_provider": "databricks", + "max_input_tokens": 65536, + "max_output_tokens": 4096, + "metadata": { + "notes": "Costs per token are the published Global DBU rates times $0.070 per DBU. The '*_dbu_cost_per_token' fields are provided for reference; cost calculation reads the dollar '*_cost_per_token' fields." + }, + "mode": "chat", + "output_cost_per_image_token": 3.749998e-05, + "output_cost_per_token": 1.87502e-06, + "output_dbu_cost_per_token": 2.6786e-05, + "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", + "supported_modalities": [ + "text", + "image" + ], + "supported_output_modalities": [ + "text", + "image" + ], + "supports_function_calling": false, + "supports_vision": true + }, + "databricks/databricks-gemini-4-argon": { + "cache_creation_input_token_cost": 2.49998e-06, + "cache_read_input_token_cost": 1.2502e-07, + "input_cost_per_token": 2.49998e-06, + "input_dbu_cost_per_token": 3.5714e-05, + "litellm_provider": "databricks", + "max_input_tokens": 1048576, + "max_output_tokens": 1048576, + "metadata": { + "notes": "Costs per token are the published Global DBU rates times $0.070 per DBU. The '*_dbu_cost_per_token' fields are provided for reference; cost calculation reads the dollar '*_cost_per_token' fields." + }, + "mode": "chat", + "output_cost_per_token": 1.249997e-05, + "output_dbu_cost_per_token": 0.00017857, + "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", + "supported_modalities": [ + "text", + "image", + "audio", + "video" + ], + "supported_output_modalities": [ + "text" + ], + "supports_audio_input": true, + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_tool_choice": true, + "supports_video_input": true, + "supports_vision": true, + "input_cost_per_token_priority": 4.50002e-06, + "output_cost_per_token_priority": 2.250003e-05, + "cache_read_input_token_cost_priority": 2.2498e-07, + "cache_creation_input_token_cost_priority": 4.50002e-06 + }, + "databricks/databricks-gpt-5-4-pro": { + "cache_creation_input_token_cost": 2.999997e-05, + "cache_read_input_token_cost": 2.999997e-05, + "input_cost_per_token": 2.999997e-05, + "input_cost_per_token_above_272k_tokens": 6e-05, + "input_dbu_cost_per_token": 0.00042857, + "litellm_provider": "databricks", + "max_input_tokens": 922000, + "max_output_tokens": 128000, + "metadata": { + "notes": "Costs per token are the published Global DBU rates times $0.070 per DBU. The '*_dbu_cost_per_token' fields are provided for reference; cost calculation reads the dollar '*_cost_per_token' fields." + }, + "mode": "responses", + "output_cost_per_token": 0.0001800001, + "output_cost_per_token_above_272k_tokens": 0.00027, + "output_dbu_cost_per_token": 0.0025714, + "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", + "supported_modalities": [ + "text", + "image" + ], + "supported_output_modalities": [ + "text" + ], + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_tool_choice": true, + "supports_vision": true + }, + "databricks/databricks-gpt-6-1-sol": { + "cache_creation_input_token_cost": 2.49998e-06, + "cache_creation_input_token_cost_above_272k_tokens": 5.00003e-06, + "cache_read_input_token_cost": 1.0003e-07, + "cache_read_input_token_cost_above_272k_tokens": 1.9999e-07, + "input_cost_per_token": 1.99997e-06, + "input_cost_per_token_above_272k_tokens": 4.00001e-06, + "input_dbu_cost_per_token": 2.8571e-05, + "litellm_provider": "databricks", + "max_input_tokens": 922000, + "max_output_tokens": 128000, + "metadata": { + "notes": "Costs per token are the published Global DBU rates times $0.070 per DBU. The '*_dbu_cost_per_token' fields are provided for reference; cost calculation reads the dollar '*_cost_per_token' fields." + }, + "mode": "responses", + "output_cost_per_token": 9.99999e-06, + "output_cost_per_token_above_272k_tokens": 1.5e-05, + "output_dbu_cost_per_token": 0.00014286, + "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", + "supported_modalities": [ + "text", + "image" + ], + "supported_output_modalities": [ + "text" + ], + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_tool_choice": true, + "supports_vision": true, + "input_cost_per_token_priority": 4.00001e-06, + "output_cost_per_token_priority": 1.99997e-05, + "cache_read_input_token_cost_priority": 1.9999e-07, + "cache_creation_input_token_cost_priority": 5.00003e-06, + "input_cost_per_token_above_272k_tokens_priority": 8.00002e-06, + "output_cost_per_token_above_272k_tokens_priority": 2.99999e-05, + "cache_read_input_token_cost_above_272k_tokens_priority": 3.9998e-07, + "cache_creation_input_token_cost_above_272k_tokens_priority": 9.99999e-06 + }, + "databricks/databricks-gpt-6-1-terra": { + "cache_creation_input_token_cost": 1.24999e-06, + "cache_creation_input_token_cost_above_272k_tokens": 2.49998e-06, + "cache_read_input_token_cost": 4.998e-08, + "cache_read_input_token_cost_above_272k_tokens": 1.0003e-07, + "input_cost_per_token": 1.00002e-06, + "input_cost_per_token_above_272k_tokens": 1.99997e-06, + "input_dbu_cost_per_token": 1.4286e-05, + "litellm_provider": "databricks", + "max_input_tokens": 922000, + "max_output_tokens": 128000, + "metadata": { + "notes": "Costs per token are the published Global DBU rates times $0.070 per DBU. The '*_dbu_cost_per_token' fields are provided for reference; cost calculation reads the dollar '*_cost_per_token' fields." + }, + "mode": "chat", + "output_cost_per_token": 5.00003e-06, + "output_cost_per_token_above_272k_tokens": 7.50001e-06, + "output_dbu_cost_per_token": 7.1429e-05, + "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", + "supported_modalities": [ + "text", + "image" + ], + "supported_output_modalities": [ + "text" + ], + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_tool_choice": true, + "supports_vision": true, + "input_cost_per_token_priority": 1.99997e-06, + "output_cost_per_token_priority": 9.99999e-06, + "cache_read_input_token_cost_priority": 1.0003e-07, + "cache_creation_input_token_cost_priority": 2.49998e-06, + "input_cost_per_token_above_272k_tokens_priority": 4.00001e-06, + "output_cost_per_token_above_272k_tokens_priority": 1.500002e-05, + "cache_read_input_token_cost_above_272k_tokens_priority": 1.9999e-07, + "cache_creation_input_token_cost_above_272k_tokens_priority": 5.00003e-06 + }, + "databricks/databricks-gpt-6-astra": { + "cache_creation_input_token_cost": 1.249997e-05, + "cache_creation_input_token_cost_above_272k_tokens": 2.5e-05, + "cache_read_input_token_cost": 1.00002e-06, + "cache_read_input_token_cost_above_272k_tokens": 1.99997e-06, + "input_cost_per_token": 9.99999e-06, + "input_cost_per_token_above_272k_tokens": 2e-05, + "input_dbu_cost_per_token": 0.00014286, + "litellm_provider": "databricks", + "max_input_tokens": 922000, + "max_output_tokens": 128000, + "metadata": { + "notes": "Costs per token are the published Global DBU rates times $0.070 per DBU. The '*_dbu_cost_per_token' fields are provided for reference; cost calculation reads the dollar '*_cost_per_token' fields." + }, + "mode": "chat", + "output_cost_per_token": 5.000002e-05, + "output_cost_per_token_above_272k_tokens": 7.50001e-05, + "output_dbu_cost_per_token": 0.00071429, + "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", + "supported_modalities": [ + "text", + "image" + ], + "supported_output_modalities": [ + "text" + ], + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_tool_choice": true, + "supports_vision": true, + "input_cost_per_token_priority": 1.999998e-05, + "output_cost_per_token_priority": 9.99999e-05, + "cache_read_input_token_cost_priority": 1.99997e-06, + "cache_creation_input_token_cost_priority": 2.500001e-05, + "input_cost_per_token_above_272k_tokens_priority": 4.000003e-05, + "output_cost_per_token_above_272k_tokens_priority": 0.0001500002, + "cache_read_input_token_cost_above_272k_tokens_priority": 4.00001e-06, + "cache_creation_input_token_cost_above_272k_tokens_priority": 5.000002e-05 + }, + "databricks/databricks-gpt-6-luna": { + "cache_creation_input_token_cost": 1.2502e-07, + "cache_creation_input_token_cost_above_272k_tokens": 2.4997e-07, + "cache_read_input_token_cost": 1.001e-08, + "cache_read_input_token_cost_above_272k_tokens": 2.002e-08, + "input_cost_per_token": 1.0003e-07, + "input_cost_per_token_above_272k_tokens": 1.9999e-07, + "input_dbu_cost_per_token": 1.429e-06, + "litellm_provider": "databricks", + "max_input_tokens": 922000, + "max_output_tokens": 128000, + "metadata": { + "notes": "Costs per token are the published Global DBU rates times $0.070 per DBU. The '*_dbu_cost_per_token' fields are provided for reference; cost calculation reads the dollar '*_cost_per_token' fields." + }, + "mode": "responses", + "output_cost_per_token": 5.0001e-07, + "output_cost_per_token_above_272k_tokens": 7.497e-07, + "output_dbu_cost_per_token": 7.143e-06, + "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", + "supported_modalities": [ + "text", + "image" + ], + "supported_output_modalities": [ + "text" + ], + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_tool_choice": true, + "supports_vision": true, + "input_cost_per_token_priority": 1.9999e-07, + "output_cost_per_token_priority": 1.0003e-06, + "cache_read_input_token_cost_priority": 2.002e-08, + "cache_creation_input_token_cost_priority": 2.4997e-07, + "input_cost_per_token_above_272k_tokens_priority": 3.9998e-07, + "output_cost_per_token_above_272k_tokens_priority": 1.5001e-06, + "cache_read_input_token_cost_above_272k_tokens_priority": 3.997e-08, + "cache_creation_input_token_cost_above_272k_tokens_priority": 5.0001e-07 + }, + "databricks/databricks-gpt-6-sol": { + "cache_creation_input_token_cost": 2.49998e-06, + "cache_creation_input_token_cost_above_272k_tokens": 5.00003e-06, + "cache_read_input_token_cost": 1.9999e-07, + "cache_read_input_token_cost_above_272k_tokens": 3.9998e-07, + "input_cost_per_token": 1.99997e-06, + "input_cost_per_token_above_272k_tokens": 4.00001e-06, + "input_dbu_cost_per_token": 2.8571e-05, + "litellm_provider": "databricks", + "max_input_tokens": 922000, + "max_output_tokens": 128000, + "metadata": { + "notes": "Costs per token are the published Global DBU rates times $0.070 per DBU. The '*_dbu_cost_per_token' fields are provided for reference; cost calculation reads the dollar '*_cost_per_token' fields." + }, + "mode": "responses", + "output_cost_per_token": 9.99999e-06, + "output_cost_per_token_above_272k_tokens": 1.50003e-05, + "output_dbu_cost_per_token": 0.00014286, + "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", + "supported_modalities": [ + "text", + "image" + ], + "supported_output_modalities": [ + "text" + ], + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_tool_choice": true, + "supports_vision": true, + "input_cost_per_token_priority": 4.00001e-06, + "output_cost_per_token_priority": 1.99997e-05, + "cache_read_input_token_cost_priority": 3.9998e-07, + "cache_creation_input_token_cost_priority": 5.00003e-06, + "input_cost_per_token_above_272k_tokens_priority": 8.00002e-06, + "output_cost_per_token_above_272k_tokens_priority": 2.99999e-05, + "cache_read_input_token_cost_above_272k_tokens_priority": 8.0003e-07, + "cache_creation_input_token_cost_above_272k_tokens_priority": 9.99999e-06 + }, + "databricks/databricks-gpt-image-1": { + "cache_creation_input_token_cost": 5.00003e-06, + "cache_read_input_token_cost": 1.24999e-06, + "input_cost_per_image_token": 9.99999e-06, + "input_cost_per_token": 5.00003e-06, + "input_dbu_cost_per_token": 7.1429e-05, + "litellm_provider": "databricks", + "metadata": { + "notes": "Costs per token are the published Global DBU rates times $0.070 per DBU. The '*_dbu_cost_per_token' fields are provided for reference; cost calculation reads the dollar '*_cost_per_token' fields." + }, + "mode": "image_generation", + "output_cost_per_image_token": 4.000003e-05, + "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving" + }, + "databricks/databricks-gpt-image-1-5": { + "cache_creation_input_token_cost": 5.00003e-06, + "cache_read_input_token_cost": 1.24999e-06, + "input_cost_per_image_token": 8.00002e-06, + "input_cost_per_token": 5.00003e-06, + "input_dbu_cost_per_token": 7.1429e-05, + "litellm_provider": "databricks", + "metadata": { + "notes": "Costs per token are the published Global DBU rates times $0.070 per DBU. The '*_dbu_cost_per_token' fields are provided for reference; cost calculation reads the dollar '*_cost_per_token' fields." + }, + "mode": "image_generation", + "output_cost_per_image_token": 3.200001e-05, + "output_cost_per_token": 9.99999e-06, + "output_dbu_cost_per_token": 0.00014286, + "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", + "supports_pdf_input": true, + "supports_vision": true + }, + "databricks/databricks-gpt-image-1-mini": { + "cache_creation_input_token_cost": 1.99997e-06, + "cache_read_input_token_cost": 1.9999e-07, + "input_cost_per_image_token": 2.49998e-06, + "input_cost_per_token": 1.99997e-06, + "input_dbu_cost_per_token": 2.8571e-05, + "litellm_provider": "databricks", + "metadata": { + "notes": "Costs per token are the published Global DBU rates times $0.070 per DBU. The '*_dbu_cost_per_token' fields are provided for reference; cost calculation reads the dollar '*_cost_per_token' fields." + }, + "mode": "image_generation", + "output_cost_per_image_token": 8.00002e-06, + "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving" + }, + "databricks/databricks-gpt-image-2": { + "cache_creation_input_token_cost": 5.00003e-06, + "cache_read_input_token_cost": 1.24999e-06, + "input_cost_per_image_token": 8.00002e-06, + "input_cost_per_token": 5.00003e-06, + "input_dbu_cost_per_token": 7.1429e-05, + "litellm_provider": "databricks", + "metadata": { + "notes": "Costs per token are the published Global DBU rates times $0.070 per DBU. The '*_dbu_cost_per_token' fields are provided for reference; cost calculation reads the dollar '*_cost_per_token' fields." + }, + "mode": "image_generation", + "output_cost_per_image_token": 2.999997e-05, + "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", + "supports_pdf_input": true, + "supports_vision": true + }, + "databricks/databricks-grok-4-7": { + "cache_creation_input_token_cost": 2.49998e-06, + "cache_read_input_token_cost": 6.2503e-07, + "input_cost_per_token": 2.49998e-06, + "input_dbu_cost_per_token": 3.5714e-05, + "litellm_provider": "databricks", + "max_input_tokens": 500000, + "max_output_tokens": 500000, + "metadata": { + "notes": "Costs per token are the published Global DBU rates times $0.070 per DBU. The '*_dbu_cost_per_token' fields are provided for reference; cost calculation reads the dollar '*_cost_per_token' fields." + }, + "mode": "chat", + "output_cost_per_token": 7.50001e-06, + "output_dbu_cost_per_token": 0.00010714, + "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", + "supported_modalities": [ + "text", + "image" + ], + "supported_output_modalities": [ + "text" + ], + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_tool_choice": true, + "supports_vision": true + }, + "databricks/databricks-kimi-k2-7": { + "cache_creation_input_token_cost": 9.4997e-07, + "cache_read_input_token_cost": 1.8998e-07, + "input_cost_per_token": 9.4997e-07, + "input_dbu_cost_per_token": 1.3571e-05, + "litellm_provider": "databricks", + "max_input_tokens": 262144, + "max_output_tokens": 262144, + "metadata": { + "notes": "Costs per token are the published Global DBU rates times $0.070 per DBU. The '*_dbu_cost_per_token' fields are provided for reference; cost calculation reads the dollar '*_cost_per_token' fields." + }, + "mode": "chat", + "output_cost_per_token": 4.00001e-06, + "output_dbu_cost_per_token": 5.7143e-05, + "source": "https://www.databricks.com/product/pricing/foundation-model-serving", + "supported_modalities": [ + "text", + "image" + ], + "supported_output_modalities": [ + "text" + ], + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_tool_choice": true, + "supports_vision": true + }, + "fireworks_ai/accounts/fireworks/routers/spot-deepseek-v4-flash": { + "cache_read_input_token_cost": 2.1e-08, + "deprecation_date": "2026-08-14", + "input_cost_per_token": 1.05e-07, + "litellm_provider": "fireworks_ai", + "max_input_tokens": 1048576, + "max_output_tokens": 384000, + "mode": "chat", + "output_cost_per_token": 2.1e-07, + "source": "https://api.fireworks.ai/v1/serverless/models", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_tool_choice": true, + "supports_vision": false + }, + "fireworks_ai/accounts/fireworks/routers/kimi-k3-spot": { + "cache_read_input_token_cost": 2.1e-07, + "input_cost_per_token": 2.1e-06, + "litellm_provider": "fireworks_ai", + "max_input_tokens": 1048576, + "max_output_tokens": 131072, + "mode": "chat", + "output_cost_per_token": 1.05e-05, + "reasoning_effort_levels": [ + "low", + "high", + "max" + ], + "source": "https://api.fireworks.ai/v1/serverless/models", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_tool_choice": true, + "supports_vision": true + }, + "fireworks_ai/accounts/fireworks/routers/glm-5p3-spot": { + "cache_read_input_token_cost": 1.82e-07, + "input_cost_per_token": 9.8e-07, + "litellm_provider": "fireworks_ai", + "max_input_tokens": 1048576, + "max_output_tokens": 128000, + "mode": "chat", + "output_cost_per_token": 3.08e-06, + "source": "https://api.fireworks.ai/v1/serverless/models", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_tool_choice": true, + "supports_vision": false + }, + "fireworks_ai/accounts/fireworks/routers/deepseek-v4p1-flash-spot": { + "cache_read_input_token_cost": 4.2e-09, + "input_cost_per_token": 2.1e-07, + "litellm_provider": "fireworks_ai", + "max_input_tokens": 1048576, + "max_output_tokens": 393216, + "mode": "chat", + "output_cost_per_token": 8.4e-07, + "source": "https://api.fireworks.ai/v1/serverless/models", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_tool_choice": true, + "supports_vision": true + }, + "fireworks_ai/accounts/fireworks/routers/deepseek-v4p1-flash-1017-spot": { + "cache_read_input_token_cost": 4.2e-09, + "input_cost_per_token": 2.1e-07, + "litellm_provider": "fireworks_ai", + "max_input_tokens": 1048576, + "max_output_tokens": 393216, + "mode": "chat", + "output_cost_per_token": 8.4e-07, + "source": "https://api.fireworks.ai/v1/serverless/models", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_tool_choice": true, + "supports_vision": true + }, + "bigmodel/glm-5.3": { + "input_cost_per_token": 1.1428571428571428e-06, + "output_cost_per_token": 4e-06, + "cache_read_input_token_cost": 2.857142857142857e-07, + "litellm_provider": "bigmodel", + "max_input_tokens": 1000000, + "max_output_tokens": 128000, + "mode": "chat", + "source": "https://docs.bigmodel.cn/cn/guide/start/pricing", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_tool_choice": true, + "thinking_always_on": true, + "metadata": { + "comment": "Official API list price checked 2026-10-27: input 8, output 28, cached input 2 CNY per million tokens; converted at 7.0 CNY/USD. Cache storage is temporarily free and is not encoded." + }, + "supported_endpoints": [ + "/v1/chat/completions", + "/v1/responses", + "/v1/messages" + ], + "supports_native_streaming": true + }, + "bigmodel/glm-5.3-flash": { + "input_cost_per_token": 1.142857142857143e-07, + "output_cost_per_token": 4e-07, + "cache_read_input_token_cost": 3.2857142857142855e-08, + "litellm_provider": "bigmodel", + "max_input_tokens": 1000000, + "max_output_tokens": 128000, + "mode": "chat", + "source": "https://docs.bigmodel.cn/cn/guide/start/pricing", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_tool_choice": true, + "thinking_always_on": true, + "supports_vision": true, + "supports_video_input": true, + "metadata": { + "comment": "Official API list price checked 2026-10-27: input 0.8, output 2.8, cached input 0.23 CNY per million tokens; converted at 7.0 CNY/USD. Cache storage is temporarily free and is not encoded." + }, + "supported_endpoints": [ + "/v1/chat/completions", + "/v1/responses", + "/v1/messages" + ], + "supports_native_streaming": true + }, + "bigmodel/glm-5.3-flashx": { + "input_cost_per_token": 2.857142857142857e-07, + "output_cost_per_token": 1e-06, + "cache_read_input_token_cost": 8.142857142857142e-08, + "litellm_provider": "bigmodel", + "max_input_tokens": 1000000, + "max_output_tokens": 128000, + "mode": "chat", + "source": "https://docs.bigmodel.cn/cn/guide/start/pricing", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_tool_choice": true, + "thinking_always_on": true, + "supports_vision": true, + "supports_video_input": true, + "metadata": { + "comment": "Official API list price checked 2026-10-27: input 2, output 7, cached input 0.57 CNY per million tokens; converted at 7.0 CNY/USD. Cache storage is temporarily free and is not encoded." + }, + "supported_endpoints": [ + "/v1/chat/completions", + "/v1/responses", + "/v1/messages" + ], + "supports_native_streaming": true } } diff --git a/litellm/provider_endpoints_support_backup.json b/litellm/provider_endpoints_support_backup.json index 9ba6ed342ea..7b0234e28d7 100644 --- a/litellm/provider_endpoints_support_backup.json +++ b/litellm/provider_endpoints_support_backup.json @@ -189,6 +189,32 @@ "generateContent": false } }, + "aiand": { + "display_name": "ai& (`aiand`)", + "url": "https://docs.aiand.com/api/chat-completions/", + "endpoints": { + "chat_completions": true, + "responses": true, + "text_completion": true, + "embeddings": false, + "image_generations": false, + "image_edits": false, + "audio_transcriptions": false, + "audio_speech": false, + "rerank": false, + "ocr": false, + "search": false, + "moderations": false, + "realtime": false, + "video_generations": false, + "batches": false, + "messages": true, + "interactions": true, + "systemone": false, + "a2a": true, + "generateContent": true + } + }, "amazon_nova": { "display_name": "Amazon Nova (`amazon_nova`)", "url": "https://docs.litellm.ai/docs/providers/amazon_nova", @@ -1199,7 +1225,7 @@ "responses": true, "text_completion": true, "embeddings": true, - "image_generations": false, + "image_generations": true, "image_edits": false, "audio_transcriptions": false, "audio_speech": false, @@ -3759,6 +3785,32 @@ "generateContent": true } }, + "streamlake": { + "display_name": "StreamLake (`streamlake`)", + "url": "https://docs.litellm.ai/docs/providers/openai_compatible", + "endpoints": { + "chat_completions": true, + "responses": true, + "text_completion": true, + "embeddings": false, + "image_generations": false, + "image_edits": false, + "audio_transcriptions": false, + "audio_speech": false, + "rerank": false, + "ocr": false, + "search": false, + "moderations": false, + "realtime": false, + "video_generations": false, + "batches": false, + "messages": true, + "interactions": true, + "systemone": false, + "a2a": true, + "generateContent": true + } + }, "tencent": { "display_name": "Tencent TokenHub (`tencent`)", "url": "https://docs.litellm.ai/docs/providers/tencent", @@ -3767,8 +3819,8 @@ "responses": true, "text_completion": true, "embeddings": false, - "image_generations": false, - "image_edits": false, + "image_generations": true, + "image_edits": true, "audio_transcriptions": false, "audio_speech": false, "rerank": false, @@ -4411,6 +4463,32 @@ "generateContent": true } }, + "zerogpu": { + "display_name": "ZeroGPU (`zerogpu`)", + "url": "https://docs.litellm.ai/docs/providers/zerogpu", + "endpoints": { + "chat_completions": true, + "responses": true, + "text_completion": true, + "embeddings": false, + "image_generations": false, + "image_edits": false, + "audio_transcriptions": false, + "audio_speech": false, + "rerank": false, + "ocr": false, + "search": false, + "moderations": false, + "realtime": false, + "video_generations": false, + "batches": false, + "messages": true, + "interactions": true, + "systemone": false, + "a2a": true, + "generateContent": true + } + }, "ragflow": { "display_name": "RAGFlow (`ragflow`)", "url": "https://docs.litellm.ai/docs/providers/ragflow", @@ -5248,6 +5326,32 @@ "a2a": false, "generateContent": false } + }, + "bigmodel": { + "display_name": "BigModel (Zhipu AI) (`bigmodel`)", + "url": "https://docs.bigmodel.cn/cn/guide/develop/responses/introduction", + "endpoints": { + "chat_completions": true, + "responses": true, + "text_completion": true, + "embeddings": false, + "image_generations": false, + "image_edits": false, + "audio_transcriptions": false, + "audio_speech": false, + "rerank": false, + "ocr": false, + "search": false, + "moderations": false, + "realtime": false, + "video_generations": false, + "batches": false, + "messages": true, + "interactions": true, + "systemone": false, + "a2a": true, + "generateContent": true + } } }, "endpoints": { diff --git a/litellm/proxy/_lazy_openapi_snapshot.json b/litellm/proxy/_lazy_openapi_snapshot.json index 2aaa987ba6a..01aa69ba5d2 100644 --- a/litellm/proxy/_lazy_openapi_snapshot.json +++ b/litellm/proxy/_lazy_openapi_snapshot.json @@ -3487,6 +3487,13 @@ "title": "Entities", "type": "object" }, + "guardrails": { + "additionalProperties": { + "$ref": "#/components/schemas/GuardrailMetric" + }, + "title": "Guardrails", + "type": "object" + }, "mcp_servers": { "additionalProperties": { "$ref": "#/components/schemas/MetricWithMetadata" @@ -3802,6 +3809,74 @@ "title": "ExportType", "type": "string" }, + "GuardrailKeyMetric": { + "properties": { + "metadata": { + "$ref": "#/components/schemas/KeyMetadata" + }, + "metrics": { + "$ref": "#/components/schemas/GuardrailSpendMetrics" + } + }, + "required": [ + "metrics", + "metadata" + ], + "title": "GuardrailKeyMetric", + "type": "object" + }, + "GuardrailMetadata": { + "properties": { + "guardrail_name": { + "title": "Guardrail Name", + "type": "string" + } + }, + "required": [ + "guardrail_name" + ], + "title": "GuardrailMetadata", + "type": "object" + }, + "GuardrailMetric": { + "properties": { + "api_key_breakdown": { + "additionalProperties": { + "$ref": "#/components/schemas/GuardrailKeyMetric" + }, + "title": "Api Key Breakdown", + "type": "object" + }, + "metadata": { + "$ref": "#/components/schemas/GuardrailMetadata" + }, + "metrics": { + "$ref": "#/components/schemas/GuardrailSpendMetrics" + } + }, + "required": [ + "metrics", + "metadata" + ], + "title": "GuardrailMetric", + "type": "object" + }, + "GuardrailSpendMetrics": { + "properties": { + "spend": { + "default": 0.0, + "title": "Spend", + "type": "number" + }, + "untracked_units": { + "default": 0, + "title": "Untracked Units", + "type": "integer" + } + }, + "title": "GuardrailSpendMetrics", + "type": "object" + }, "HTTPAuthSecurityScheme": { "description": "Defines a security scheme using HTTP authentication.", "properties": { @@ -15015,7 +15090,7 @@ ] }, "post": { - "description": "Create a named custom agent on the Gemini side.\n\nExample:\n```bash\ncurl -X POST \"http://localhost:4000/v1beta/agents\" \\\n -H \"Authorization: Bearer sk-...\" \\\n -H \"Content-Type: application/json\" \\\n -d '{\n \"name\": \"my-custom-slides-agent\",\n \"base_agent\": \"waverunner\",\n \"instructions\": \"You are a helpful assistant that creates slides.\",\n \"base_environment\": {\n \"type\": \"remote\",\n \"sources\": [\n {\"type\": \"gcs\", \"source\": \"gs://eap-templates/slides-skill\",\n \"target\": \"/.agents/skills/slides-skill\"}\n ]\n }\n }'\n```", + "description": "Create a named custom agent on the Gemini side.\n\nExample:\n```bash\ncurl -X POST \"http://localhost:4000/v1beta/agents\" \\\n -H \"Authorization: Bearer sk-...\" \\\n -H \"Content-Type: application/json\" \\\n -d '{\n \"id\": \"my-custom-slides-agent\",\n \"base_agent\": \"antigravity-preview-09-2026\",\n \"system_instruction\": \"You are a helpful assistant that creates slides.\",\n \"agent_config\": {\"type\": \"antigravity\", \"model\": \"gemini-3.8-flash\"},\n \"base_environment\": {\n \"type\": \"remote\",\n \"sources\": [\n {\"type\": \"gcs\", \"source\": \"gs://eap-templates/slides-skill\",\n \"target\": \"/.agents/skills/slides-skill\"}\n ]\n }\n }'\n```", "operationId": "create_gemini_agent_v1beta_agents_post", "responses": { "200": { @@ -33564,7 +33639,7 @@ ] }, "get": { - "description": "Get a response by ID.\n\nSupports both:\n- Polling IDs (litellm_poll_*): Returns cumulative cached content from background responses\n- Provider response IDs: Passes through to provider API\n\nFollows the OpenAI Responses API spec: https://platform.openai.com/docs/api-reference/responses/get\n\n```bash\n# Get polling response\ncurl -X GET http://localhost:4000/v1/responses/litellm_poll_abc123 -H \"Authorization: Bearer $LITELLM_MASTER_KEY\"\n\n# Get provider response\ncurl -X GET http://localhost:4000/v1/responses/resp_abc123 -H \"Authorization: Bearer $LITELLM_MASTER_KEY\"\n```", + "description": "Get a response by ID.\n\nSupports both:\n- Polling IDs (litellm_poll_*): Returns cumulative cached content from background responses\n- Provider response IDs: Passes through to provider API\n\nFollows the OpenAI Responses API spec: https://platform.openai.com/docs/api-reference/responses/get\n\n```bash\n# Get polling response\ncurl -X GET http://localhost:4000/v1/responses/litellm_poll_abc123 -H \"Authorization: Bearer $LITELLM_MASTER_KEY\"\n\n# Get provider response\ncurl -X GET http://localhost:4000/v1/responses/resp_abc123 -H \"Authorization: Bearer $LITELLM_MASTER_KEY\"\n\n# Resume a background response's event stream after sequence number 7\ncurl -N \"http://localhost:4000/v1/responses/resp_abc123?stream=true&starting_after=7\" -H \"Authorization: Bearer $LITELLM_MASTER_KEY\"\n```", "operationId": "get_response_openai_v1_responses__response_id__get", "parameters": [ { @@ -33575,6 +33650,46 @@ "title": "Response Id", "type": "string" } + }, + { + "description": "Replay the response's events as server-sent events (OpenAI, Azure, and Azure AI Foundry)", + "in": "query", + "name": "stream", + "required": false, + "schema": { + "type": "boolean" + } + }, + { + "description": "With stream=true, replay only the events after this sequence number", + "in": "query", + "name": "starting_after", + "required": false, + "schema": { + "minimum": 0, + "type": "integer" + } + }, + { + "description": "Additional output data to include, forwarded to the provider", + "in": "query", + "name": "include", + "required": false, + "schema": { + "items": { + "type": "string" + }, + "type": "array" + } + }, + { + "description": "With stream=true, whether delta events carry obfuscation padding", + "in": "query", + "name": "include_obfuscation", + "required": false, + "schema": { + "type": "boolean" + } } ], "responses": { @@ -33584,6 +33699,12 @@ "schema": { "$ref": "#/components/schemas/ResponsesAPIResponse" } + }, + "text/event-stream": { + "schema": { + "description": "Server sent events when stream=true", + "type": "string" + } } }, "description": "Successful Response" diff --git a/litellm/proxy/_types.py b/litellm/proxy/_types.py index dd91bb6eef3..df139a9b84d 100644 --- a/litellm/proxy/_types.py +++ b/litellm/proxy/_types.py @@ -3461,12 +3461,12 @@ class LiteLLM_SpendLogs_ResponseObject(LiteLLMPydanticObjectBase): class TokenCountRequest(LiteLLMPydanticObjectBase): model: str prompt: str | None = None - messages: list[dict] | None = None + messages: list[dict[Any, Any]] | None = None """ Anthropic token counting endpoint uses /messages """ - contents: list[dict] | None = None + contents: list[dict[Any, Any]] | None = None """ Google /countTokens endpoint expects contents to be a list of dicts with the following structure: """ @@ -3816,6 +3816,16 @@ class ManagementEndpointLoggingPayload(LiteLLMPydanticObjectBase): end_time: datetime | None = None +def proxy_exception_status_code(message: str, code: str) -> str: + # Litellm router.py returns "No healthy deployment available" when there are no deployments available + # Should map to 429 errors https://github.com/BerriAI/litellm/issues/2487 + if "No healthy deployment available" in message or "No deployments available" in message: + return "429" + if RouterErrors.no_deployments_with_tag_routing.value in message: + return "401" + return code + + class ProxyException(Exception): # NOTE: DO NOT MODIFY THIS # This is used to map exactly to OPENAI Exceptions @@ -3844,13 +3854,7 @@ class ProxyException(Exception): headers[k] = str(v) self.headers = headers or {} self.provider_specific_fields = provider_specific_fields - # rules for proxyExceptions - # Litellm router.py returns "No healthy deployment available" when there are no deployments available - # Should map to 429 errors https://github.com/BerriAI/litellm/issues/2487 - if "No healthy deployment available" in self.message or "No deployments available" in self.message: - self.code = "429" - elif RouterErrors.no_deployments_with_tag_routing.value in self.message: - self.code = "401" + self.code = proxy_exception_status_code(self.message, self.code) def to_dict(self) -> dict: """Converts the ProxyException instance to a dictionary.""" diff --git a/litellm/proxy/agent_endpoints/a2a_endpoints.py b/litellm/proxy/agent_endpoints/a2a_endpoints.py index 4691c7b0bc5..219ce906340 100644 --- a/litellm/proxy/agent_endpoints/a2a_endpoints.py +++ b/litellm/proxy/agent_endpoints/a2a_endpoints.py @@ -26,6 +26,7 @@ from litellm._logging import verbose_proxy_logger from litellm.litellm_core_utils.core_helpers import as_str_mapping from litellm.litellm_core_utils.url_utils import SSRFError, validate_url from litellm.llms.a2a.common_utils import resolve_a2a_hop_auth_header +from litellm.llms.custom_httpx.sse_lines import aiter_sse_lines from litellm.proxy._types import UserAPIKeyAuth from litellm.proxy.a2a.version_convert import ( A2AVersion, @@ -320,7 +321,7 @@ async def _a2a_sse_event_source( "error": {"code": -32603, "message": resp.reason_phrase}, } return - async for line in resp.aiter_lines(): + async for line in aiter_sse_lines(resp.aiter_text()): stripped = line.strip() if not stripped.startswith("data:"): continue diff --git a/litellm/proxy/anthropic_endpoints/endpoints.py b/litellm/proxy/anthropic_endpoints/endpoints.py index 13a1844a6de..1d88e133cf9 100644 --- a/litellm/proxy/anthropic_endpoints/endpoints.py +++ b/litellm/proxy/anthropic_endpoints/endpoints.py @@ -18,7 +18,6 @@ from litellm.anthropic_interface.exceptions import ( AnthropicExceptionMapping, ) from litellm.integrations.custom_guardrail import ModifyResponseException -from litellm.litellm_core_utils.token_counter import UnsupportedContentTypeError from litellm.litellm_core_utils.tool_fields import first_validation_error from litellm.llms.anthropic.messages.context_management import ( AnthropicContextManagementError, @@ -49,8 +48,12 @@ from litellm.proxy.common_utils.openai_error_payload import ( openai_error_type, with_litellm_call_id, ) +from litellm.proxy.common_utils.token_count_log import rejected_token_count from litellm.proxy.common_utils.token_count_settings import count_source_fields -from litellm.proxy.litellm_pre_call_utils import should_auto_drop_params_for_agentic_cli +from litellm.proxy.litellm_pre_call_utils import ( + forwarded_anthropic_oauth_token, + should_auto_drop_params_for_agentic_cli, +) from litellm.router import Router router: Final = APIRouter() @@ -391,12 +394,17 @@ async def count_tokens( # Extract required fields model_name: Final = data.get("model") messages: Final = data.get("messages", []) + request_model: Final = model_name if isinstance(model_name, str) else None if not model_name: - raise HTTPException(status_code=400, detail="model parameter is required") + raise rejected_token_count( + HTTPException(status_code=400, detail="model parameter is required"), litellm_call_id, request_model + ) if not messages: - raise HTTPException(status_code=400, detail="messages parameter is required") + raise rejected_token_count( + HTTPException(status_code=400, detail="messages parameter is required"), litellm_call_id, request_model + ) auto_drop_params: Final = should_auto_drop_params_for_agentic_cli( request.headers.get("user-agent", ""), "drop_params" in data, proxy_config @@ -406,18 +414,18 @@ async def count_tokens( token_fields if isinstance(token_fields, ProxyException) else _token_count_request(token_fields) ) if isinstance(token_request, ProxyException): - return _anthropic_error_json_response(token_request, request) + return rejected_token_count( + _anthropic_error_json_response(token_request, request), litellm_call_id, request_model + ) token_response: Final = await count_request_tokens( request=token_request, call_endpoint=True, messages_format="anthropic", + litellm_call_id=litellm_call_id, + client_oauth_token=forwarded_anthropic_oauth_token(request.headers), **_count_tokens_body_options(data, auto_drop_params), ) - except UnsupportedContentTypeError as e: - return _anthropic_error_json_response( - ProxyException(message=str(e), type="invalid_request_error", param="messages", code=400), request - ) except HTTPException as e: return _anthropic_error_json_response(proxy_exception_from_http_exception(e, {}), request) except ProxyException as e: diff --git a/litellm/proxy/anthropic_endpoints/gateway_endpoints.py b/litellm/proxy/anthropic_endpoints/gateway_endpoints.py index 1911cb574ef..6c58f2edc02 100644 --- a/litellm/proxy/anthropic_endpoints/gateway_endpoints.py +++ b/litellm/proxy/anthropic_endpoints/gateway_endpoints.py @@ -45,7 +45,11 @@ from litellm.proxy.common_utils.http_parsing_utils import ( # noqa: F401 # leg safe_set_request_parsed_body, ) from litellm.proxy.management_endpoints.sso_helper_utils import CLI_SSO_SESSIONS_TARGET -from litellm.proxy.management_endpoints.ui_sso import CliSsoTeamDetail +from litellm.proxy.management_endpoints.ui_sso import ( + CLI_SSO_BROWSER_TEAM_CHOICE, + CLI_SSO_CHOSEN_TEAM_ID, + CliSsoTeamDetail, +) from litellm.proxy.mcp_server.gateway_dcr_flow import ( PROXY_API_AUDIENCE, MintedProxyCredential, @@ -235,6 +239,7 @@ async def device_authorization(request: Request) -> JSONResponse: "sso_complete": False, "user_code_verified": False, "session_data": None, + CLI_SSO_BROWSER_TEAM_CHOICE: True, } _set_cli_sso_flow(login_id=login_id, cache=cli_sso_session_cache, flow=flow) @@ -267,7 +272,15 @@ def _validate_login(flow: Mapping[str, object]) -> _GatewayLogin | _OAuthError: status_code=400, error="invalid_grant", description="The login session is malformed; sign in again" ) - team_id: Final = session_data.teams[0] if session_data.teams else None + chosen: Final = flow.get(CLI_SSO_CHOSEN_TEAM_ID) + chosen_team_id: Final = chosen if isinstance(chosen, str) else None + if chosen_team_id is not None and chosen_team_id not in session_data.teams: + return _OAuthError( + status_code=400, + error="invalid_grant", + description="The team picked at sign-in is no longer one of your teams; sign in again", + ) + team_id: Final = chosen_team_id or next(iter(session_data.teams), None) selected_team: Final = selected_cli_sso_team_detail(team_details=session_data.team_details, team_id=team_id) if selected_team is None: return _OAuthError( diff --git a/litellm/proxy/anthropic_endpoints/streaming_model_restamp.py b/litellm/proxy/anthropic_endpoints/streaming_model_restamp.py index f748a754fe0..32e0f6e8682 100644 --- a/litellm/proxy/anthropic_endpoints/streaming_model_restamp.py +++ b/litellm/proxy/anthropic_endpoints/streaming_model_restamp.py @@ -14,6 +14,8 @@ from typing import Final from pydantic import TypeAdapter, ValidationError +from litellm.llms.custom_httpx.sse_lines import split_sse_lines_keepends + _MESSAGE_START_EVENT: Final = "message_start" _MESSAGE_START_MARKER: Final = b"message_start" _SSE_DATA_FIELD: Final = "data:" @@ -52,7 +54,7 @@ def _restamped_data_line(line: str, requested_model: str) -> str | None: def _restamped_frame(frame: str, requested_model: str) -> str | None: - lines: Final = frame.splitlines(keepends=True) + lines: Final = split_sse_lines_keepends(frame) restamped: Final = tuple(_restamped_data_line(line, requested_model) for line in lines) if all(line is None for line in restamped): return None diff --git a/litellm/proxy/auth/auth_checks.py b/litellm/proxy/auth/auth_checks.py index 448643ef59b..882e98ec097 100644 --- a/litellm/proxy/auth/auth_checks.py +++ b/litellm/proxy/auth/auth_checks.py @@ -46,6 +46,11 @@ from litellm.constants import ( from litellm.litellm_core_utils.dd_tracing import tracer from litellm.litellm_core_utils.get_llm_provider_logic import get_llm_provider from litellm.litellm_core_utils.safe_json_loads import safe_json_loads +from litellm.litellm_core_utils.tool_fields import DropPolicy +from litellm.llms.base_llm.managed_resources.utils import ( + extract_provider_resource_id_from_unified_id, + is_base64_encoded_unified_id, +) from litellm.models.project import LiteLLM_ProjectTable from litellm.proxy._types import ( MODEL_LIST_ROUTES, @@ -165,6 +170,7 @@ from litellm.types.proxy.auth.auth_checks import UserNotFoundError from litellm.types.proxy.model_access_group_budget import ModelAccessGroupBudget from litellm.types.router import DeploymentTypedDict from litellm.utils import get_utc_datetime +from litellm.vector_stores.vector_store_registry import listed_vector_store_ids, vector_store_ids_in_tool from .auth_checks_organization import ( add_team_org_context_to_request_body, @@ -1063,6 +1069,15 @@ def is_mcp_discovery_request(route: str, request_body: Mapping[str, object]) -> return isinstance(method, str) and method in MCP_ZERO_SPEND_JSONRPC_METHODS +class ModelMaxBudgetHolder(Protocol): + @property + def model_max_budget(self) -> Mapping[str, object] | None: ... + + +def model_max_budget_of(holder: ModelMaxBudgetHolder) -> Mapping[str, object] | None: + return holder.model_max_budget + + def route_skips_budget_checks(route: str) -> bool: return route not in BUDGET_ENFORCED_SIDE_EFFECT_ROUTES and ( route in MODEL_DISCOVERY_ROUTES or not RouteChecks.is_llm_api_route(route=route) @@ -1505,6 +1520,7 @@ async def common_checks( valid_token=valid_token, user_object=user_object, deny_by_default=_vector_store_deny_by_default(_typed_request_body(general_settings)), + llm_router=llm_router, ) # 12. [OPTIONAL] Tool allowlist - key/team allowed_tools (no DB in hot path) @@ -7976,6 +7992,57 @@ def _strict_requested_vector_store_ids(request_body: Mapping[str, object]) -> tu ) +@dataclass(frozen=True, slots=True) +class _UnreadableVectorStoreIds: + pass + + +def _top_level_vector_store_ids( + vector_store_ids: object, drop_policies: Callable[[], tuple[DropPolicy, ...]] +) -> tuple[str, ...] | _UnreadableVectorStoreIds: + listed: Final = listed_vector_store_ids(vector_store_ids) + if vector_store_ids is None or vector_store_ids == [*listed]: + return listed + if any(policy.drops("vector_store_ids") for policy in drop_policies()): + return listed + if isinstance(vector_store_ids, str): + return (vector_store_ids,) + return _UnreadableVectorStoreIds() + + +def _legacy_requested_vector_store_ids( + request_body: Mapping[str, object], drop_policies: Callable[[], tuple[DropPolicy, ...]] +) -> tuple[str, ...] | _UnreadableVectorStoreIds: + """ + Reads tools the way VectorStoreRegistry does and leaves a malformed tool to the proxy's tool + validation. A top-level vector_store_ids string names one store, since a query parameter always + arrives as a string. Any other value that is not a list of strings names no readable stores unless a + drop policy the request can resolve to drops it, and then only the string entries of a list name + stores, as in registry retrieval. + """ + top_level: Final = _top_level_vector_store_ids(request_body.get("vector_store_ids"), drop_policies) + if isinstance(top_level, _UnreadableVectorStoreIds): + return top_level + return tuple( + chain( + top_level, + chain.from_iterable(vector_store_ids_in_tool(tool) for tool in _tools(request_body.get("tools"))), + ) + ) + + +def _restricts_vector_stores(grants: Sequence[tuple[GrantLayer, LiteLLM_ObjectPermissionTable | None]]) -> bool: + return any(grant is not None and bool(grant.vector_stores) for _, grant in grants) + + +def _request_drop_policies( + request_body: Mapping[str, object], llm_router: Router | None, valid_token: UserAPIKeyAuth | None +) -> tuple[DropPolicy, ...]: + from litellm.proxy.common_request_processing import counted_drop_policies + + return counted_drop_policies(request_body, llm_router, valid_token.team_id if valid_token is not None else None) + + def _require_vector_store_grant( object_type: GrantLayer, vector_store_ids_to_run: Sequence[str], @@ -8023,6 +8090,7 @@ async def vector_store_access_check( *, user_object: LiteLLM_UserTable | None = None, deny_by_default: bool = False, + llm_router: Router | None = None, ): """ Checks whether the caller may use every vector store the request names. @@ -8031,11 +8099,19 @@ async def vector_store_access_check( `retrieval_config.vector_store_id`. Grants come from each identity's `object_permission.vector_stores`. - With `deny_by_default=False` (legacy), a key or team only restricts access when its list is - nonempty, and stores are only read from the request when a vector store registry is loaded. + Both modes read the same request fields, with or without a vector store registry, and answer 400 + when the top-level `vector_store_ids` is not a list of strings, which legacy mode does only when the + key or team has an allowlist and the value is not a string, which it checks as one store id. A + LiteLLM-managed store id is compared by the provider store id it decodes to, on both sides. Legacy mode skips that value instead when the request, `litellm_settings`, the router defaults or a deployment of the requested + model drops it (`drop_params`, or `additional_drop_params` naming it), the same settings the proxy's + tool validation reads, and reads tools the way the registry does, where strict mode answers 400 on a + malformed one. - With `deny_by_default=True` (`general_settings.vector_store_deny_by_default`), stores are read - even without a registry, and a missing record, `null` or `[]` grants nothing: + With `deny_by_default=False` (legacy), a key or team only restricts access when its list is + nonempty. + + With `deny_by_default=True` (`general_settings.vector_store_deny_by_default`), a missing record, + `null` or `[]` grants nothing: - virtual key: the key must grant every store, and so must its team when it has one, even if the team failed to load @@ -8047,8 +8123,8 @@ async def vector_store_access_check( rescue nor restrict a key or team request. Raises ProxyException (401, `{key,team,user}_vector_store_access_denied`) on the first identity - that does not grant a requested store, and with the flag on, ProxyException (400, - `invalid_request_error`) when a `vector_store_ids` field is not a list of strings. + that does not grant a requested store, and ProxyException (400, `invalid_request_error`) on a + malformed `vector_store_ids` the request does not drop and, in legacy mode, an allowlist applies to. """ from litellm.proxy.proxy_server import prisma_client, user_api_key_cache @@ -8059,23 +8135,24 @@ async def vector_store_access_check( verbose_proxy_logger.debug("Prisma client not found, skipping vector store access check") return True - registry_ids: Final = ( - _strict_requested_vector_store_ids(_typed_request_body(request_body)) + typed_request_body: Final = _typed_request_body(request_body) + requested_ids: Final = ( + _strict_requested_vector_store_ids(typed_request_body) if deny_by_default - else ( - litellm.vector_store_registry.get_vector_store_ids_to_run( - non_default_params=request_body, tools=request_body.get("tools", None) - ) - if litellm.vector_store_registry is not None - else None + else _legacy_requested_vector_store_ids( + typed_request_body, lambda: _request_drop_policies(typed_request_body, llm_router, valid_token) ) - or () ) - rag_vector_store_id: Final = _get_rag_query_vector_store_id(_typed_request_body(request_body)) + if isinstance(requested_ids, _UnreadableVectorStoreIds): + if _restricts_vector_stores( + await _identity_grants(valid_token, team_object, None, prisma_client, user_api_key_cache) + ): + raise _malformed_vector_store_ids() + return True + rag_vector_store_id: Final = _get_rag_query_vector_store_id(typed_request_body) rag_ids: Final = (rag_vector_store_id,) if rag_vector_store_id is not None else () - vector_store_ids_to_run: Final = tuple(dict.fromkeys((*registry_ids, *rag_ids))) + vector_store_ids_to_run: Final = tuple(dict.fromkeys((*requested_ids, *rag_ids))) if not vector_store_ids_to_run: - verbose_proxy_logger.debug("Vector store to run not found, skipping vector store access check") return True ######################################################### @@ -8101,6 +8178,12 @@ async def vector_store_access_check( return True +def _provider_vector_store_id(vector_store_id: str) -> str: + if not is_base64_encoded_unified_id(vector_store_id): + return vector_store_id + return extract_provider_resource_id_from_unified_id(vector_store_id) or vector_store_id + + def _can_object_call_vector_stores( object_type: Literal["key", "team", "org", "user"], vector_store_ids_to_run: Sequence[str], @@ -8119,8 +8202,9 @@ def _can_object_call_vector_stores( if len(object_permissions.vector_stores) == 0: return True + allowed_stores: Final = frozenset(map(_provider_vector_store_id, object_permissions.vector_stores)) for vector_store_id in vector_store_ids_to_run: - if vector_store_id not in object_permissions.vector_stores: + if _provider_vector_store_id(vector_store_id) not in allowed_stores: raise ProxyException( message=f"User not allowed to access vector store. Tried to access {vector_store_id}. Only allowed to access {object_permissions.vector_stores}", type=ProxyErrorTypes.get_vector_store_access_error_type_for_object(object_type), diff --git a/litellm/proxy/auth/model_checks.py b/litellm/proxy/auth/model_checks.py index c4c538083ee..48884d0fedc 100644 --- a/litellm/proxy/auth/model_checks.py +++ b/litellm/proxy/auth/model_checks.py @@ -20,6 +20,8 @@ from litellm.types.router import CredentialLiteLLMParams, LiteLLM_Params from litellm.types.utils import LlmProviders from litellm.utils import ProviderConfigManager, get_valid_models +LLM_PROVIDER_PREFIXES: Final = frozenset(llm_provider.value for llm_provider in LlmProviders) + _CREDENTIAL_LITELLM_PARAM_FIELDS = set(CredentialLiteLLMParams.model_fields) @@ -458,23 +460,21 @@ def get_known_models_from_wildcard( # add model prefix to wildcard models wildcard_models = [f"{model_prefix}{model.removeprefix(provider_id_prefix)}" for model in wildcard_models] - known_providers: Final = {provider.value for provider in LlmProviders} - suffix_appended_wildcard_models: Final = [] - for model in wildcard_models: - if not model.startswith(f"{wildcard_provider_prefix}/"): - # `get_provider_models` returns provider-prefixed ids (e.g. "ollama/gemma3:1b"). - # When the wildcard uses a custom prefix (e.g. "ollama_server1/*" to distinguish - # multiple instances), replace that existing provider prefix instead of stacking - # both, which would otherwise yield an uncallable "ollama_server1/ollama/gemma3:1b". - # Only strip the leading segment when it is a known provider, so ids whose first - # segment is an org rather than a provider (e.g. "meta-llama/Llama-3-8B") keep it. - leading, sep, model_suffix = model.partition("/") - if sep and leading in known_providers: - model = f"{wildcard_provider_prefix}/{model_suffix}" - else: - model = f"{wildcard_provider_prefix}/{model}" - suffix_appended_wildcard_models.append(model) - return list(dict.fromkeys(suffix_appended_wildcard_models)) + return list( + dict.fromkeys(_under_wildcard_prefix(model, wildcard_provider_prefix, provider) for model in wildcard_models) + ) + + +def _under_wildcard_prefix(model: str, wildcard_provider_prefix: str, listed_provider: str) -> str: + if model.startswith(f"{wildcard_provider_prefix}/"): + return model + leading, sep, model_suffix = model.partition("/") + leading_is_listed_providers_own_prefix: Final = ( + sep != "" + and leading in LLM_PROVIDER_PREFIXES + and (leading == listed_provider or listed_provider.startswith(f"{leading}_")) + ) + return f"{wildcard_provider_prefix}/{model_suffix if leading_is_listed_providers_own_prefix else model}" def expand_wildcard_deployments_for_model_info( diff --git a/litellm/proxy/auth/user_api_key_auth.py b/litellm/proxy/auth/user_api_key_auth.py index cb490b55352..292a147d200 100644 --- a/litellm/proxy/auth/user_api_key_auth.py +++ b/litellm/proxy/auth/user_api_key_auth.py @@ -40,6 +40,7 @@ from litellm.integrations.otel.model.config import is_otel_v2_enabled from litellm.integrations.otel.runtime import phase_event, phase_span, seed_request_identity from litellm.litellm_core_utils.dd_tracing import tracer from litellm.litellm_core_utils.dot_notation_indexing import get_nested_value +from litellm.models.end_user import LiteLLM_EndUserTable from litellm.proxy._types import * from litellm.proxy.agent_endpoints.auth.agent_caller import agent_caller_from_headers from litellm.proxy.auth.auth_checks import ( # noqa: F401 # legacy module exports @@ -85,6 +86,7 @@ from litellm.proxy.auth.auth_checks import ( # noqa: F401 # legacy module expo jwt_key_mapping_cache_key, key_access_group_grants_model, key_model_aliases_for_auth_check, + model_max_budget_of, resolve_and_validate_end_user_id, resolve_default_end_user_budget, route_skips_budget_checks, @@ -370,7 +372,7 @@ class _KeyModelBudgetLimiter(Protocol): class _UserModelBudgetLimiter(Protocol): async def is_user_within_model_budget( - self, user_id: str, user_model_max_budget: Mapping[str, object], model: str + self, user_id: str, user_model_max_budget: Mapping[str, object], model: str, team_id: str | None = None ) -> bool: ... @@ -384,15 +386,29 @@ class _TeamModelBudgetLimiter(Protocol): ) -> bool: ... +class _EndUserModelBudgetLimiter(Protocol): + async def is_end_user_within_model_budget( + self, + end_user_id: str, + end_user_model_max_budget: Mapping[str, object], + model: str, + team_id: str | None = None, + ) -> bool: ... + + class _EveryModelBudgetLimiter(Protocol): async def is_key_within_model_budget(self, user_api_key_dict: UserAPIKeyAuth, model: str) -> bool: ... async def is_user_within_model_budget( - self, user_id: str, user_model_max_budget: Mapping[str, object], model: str + self, user_id: str, user_model_max_budget: Mapping[str, object], model: str, team_id: str | None = None ) -> bool: ... async def is_end_user_within_model_budget( - self, end_user_id: str, end_user_model_max_budget: Mapping[str, object], model: str + self, + end_user_id: str, + end_user_model_max_budget: Mapping[str, object], + model: str, + team_id: str | None = None, ) -> bool: ... async def is_team_within_model_budget( @@ -503,6 +519,7 @@ async def _check_user_model_budget( user_id=valid_token.user_id, user_model_max_budget=user_model_max_budget, model=model_name, + team_id=valid_token.team_id, ) @@ -525,6 +542,49 @@ async def _check_team_model_budget( ) +async def _end_user_model_max_budget( + end_user_id: str | None, + end_user_object: LiteLLM_EndUserTable | None, + key_end_user_budget_id: str | None, + prisma_client: PrismaClient | None, + user_api_key_cache: UserApiKeyCache, + parent_otel_span: Span | None, +) -> Mapping[str, object] | None: + budget_table: Final = ( + end_user_object.litellm_budget_table + if end_user_object is not None + else ( + await resolve_default_end_user_budget( + prisma_client=prisma_client, + user_api_key_cache=user_api_key_cache, + key_end_user_budget_id=key_end_user_budget_id, + parent_otel_span=parent_otel_span, + ) + if end_user_id and prisma_client is not None + else None + ) + ) + return model_max_budget_of(budget_table) if budget_table is not None else None + + +async def _check_end_user_model_budget( + end_user_id: str | None, + end_user_model_max_budget: Mapping[str, object] | None, + model_max_budget_limiter: _EndUserModelBudgetLimiter, + models: Sequence[str], + team_id: str | None, +) -> None: + if not end_user_id or not end_user_model_max_budget: + return + for model_name in models: + await model_max_budget_limiter.is_end_user_within_model_budget( + end_user_id=end_user_id, + end_user_model_max_budget=end_user_model_max_budget, + model=model_name, + team_id=team_id, + ) + + async def _is_within_every_model_budget( valid_token: UserAPIKeyAuth, model_max_budget_limiter: _EveryModelBudgetLimiter, @@ -547,6 +607,7 @@ async def _is_within_every_model_budget( user_id=valid_token.user_id, user_model_max_budget=user_model_max_budget, model=model, + team_id=valid_token.team_id, ) if ( valid_token.end_user_id is not None @@ -557,6 +618,7 @@ async def _is_within_every_model_budget( end_user_id=valid_token.end_user_id, end_user_model_max_budget=end_user_model_max_budget, model=model, + team_id=valid_token.team_id, ) if valid_token.team_id is not None and isinstance(team_model_max_budget, Mapping) and team_model_max_budget: await model_max_budget_limiter.is_team_within_model_budget( @@ -2087,6 +2149,10 @@ async def _resolve_object_permission_for_unresolvable_team( ) +def _custom_auth_token_for_this_request(response: object) -> UserAPIKeyAuth: + return UserAPIKeyAuth.model_validate(response).model_copy() + + async def user_api_key_auth_builder( request: Request, api_key: str, @@ -2165,7 +2231,7 @@ async def user_api_key_auth_builder( request=request, api_key=api_key, user_custom_auth=user_custom_auth ) if response is not None and isinstance(response, UserAPIKeyAuth): - validated = UserAPIKeyAuth.model_validate(response) + validated = _custom_auth_token_for_this_request(response) if getattr(litellm, "enable_post_custom_auth_checks", False): validated = await _run_post_custom_auth_checks( valid_token=validated, @@ -2181,7 +2247,7 @@ async def user_api_key_auth_builder( custom_auth_api_key = True elif user_custom_auth is not None: response = await user_custom_auth(request=request, api_key=api_key) - validated = UserAPIKeyAuth.model_validate(response) + validated = _custom_auth_token_for_this_request(response) if getattr(litellm, "enable_post_custom_auth_checks", False): validated = await _run_post_custom_auth_checks( valid_token=validated, @@ -3122,7 +3188,7 @@ async def validate_resolved_virtual_key( # noqa: C901 # Preserve ordering of e ) # Recompute after a potential budget-fallback rewrite so - # the end-user check below validates the final model + # the user check below validates the final model current_model = _get_model_from_request_context( request_data=request_data, route=route, @@ -3140,22 +3206,6 @@ async def validate_resolved_virtual_key( # noqa: C901 # Preserve ordering of e models=current_models, ) - # Check 5b. End-user model max budget - end_user_mmb: Final = valid_token.end_user_model_max_budget - if ( - end_user_mmb is not None - and isinstance(end_user_mmb, dict) - and len(end_user_mmb) > 0 - and current_models - and valid_token.end_user_id is not None - ): - for model_name in current_models: - await model_max_budget_limiter.is_end_user_within_model_budget( - end_user_id=valid_token.end_user_id, - end_user_model_max_budget=end_user_mmb, - model=model_name, - ) - # Check 6: Additional Common Checks across jwt + key auth if valid_token.team_id is not None: try: @@ -3257,8 +3307,9 @@ async def validate_resolved_virtual_key( # noqa: C901 # Preserve ordering of e if valid_token.budget_throttle_pct is not None: valid_token_dict["budget_throttle_pct"] = valid_token.budget_throttle_pct - if _end_user_object is not None: + if _end_user_object is not None or litellm.max_end_user_budget_id is not None: valid_token_dict.update(end_user_params) + if _end_user_object is not None: valid_token_dict["end_user_object_permission"] = _end_user_object.object_permission # check if token is from litellm-ui, litellm ui makes keys to allow users to login with sso. These keys can only be used for LiteLLM UI functions @@ -3724,9 +3775,7 @@ async def run_centralized_common_checks( project_object: Final[LiteLLM_ProjectTableCachedObj | None] = ( None if isinstance(project_result, BaseException) else project_result ) - end_user_object: Final[LiteLLM_EndUserTable | None] = ( - None if isinstance(end_user_result, BaseException) else end_user_result - ) + end_user_object: Final = end_user_result if isinstance(end_user_result, LiteLLM_EndUserTable) else None global_proxy_spend: float | None = None if isinstance(global_spend_result, BaseException) else global_spend_result carry_team_and_user_budget_state( valid_token=user_api_key_auth_obj, @@ -3786,6 +3835,21 @@ async def run_centralized_common_checks( parent_otel_span=parent_otel_span, keep_token_limits=user_custom_auth is not None, ) + end_user_model_max_budget: Final = await _end_user_model_max_budget( + end_user_id=end_user_id, + end_user_object=end_user_object, + key_end_user_budget_id=key_end_user_budget_id, + prisma_client=prisma_client, + user_api_key_cache=user_api_key_cache, + parent_otel_span=parent_otel_span, + ) + if end_user_id and ( + not user_api_key_auth_obj.authenticated_by_custom_auth + or user_api_key_auth_obj.end_user_model_max_budget is None + ): + user_api_key_auth_obj.end_user_model_max_budget = ( # rebind-ok: the spend hook charges from this token + dict(end_user_model_max_budget) if end_user_model_max_budget else None + ) skip_budget_checks: Final = _should_skip_budget_checks( request_data=request_data, @@ -3878,6 +3942,21 @@ async def run_centralized_common_checks( user_api_key_cache=user_api_key_cache, proxy_logging_obj=proxy_logging_obj, ) + await _check_end_user_model_budget( + end_user_id=end_user_id, + end_user_model_max_budget=user_api_key_auth_obj.end_user_model_max_budget, + model_max_budget_limiter=model_max_budget_limiter, + team_id=user_api_key_auth_obj.team_id, + models=_get_model_names_for_budget_checks( + model=_get_model_from_request_context( + request_data=request_data, + route=route, + request=request, + llm_router=llm_router, + team_id=user_api_key_auth_obj.team_id, + ) + ), + ) if sub_call and RouteChecks.is_llm_api_route(route=route): await virtual_key_max_budget_check( valid_token=user_api_key_auth_obj, @@ -4732,6 +4811,7 @@ async def _run_post_custom_auth_checks( end_user_id=valid_token.end_user_id, end_user_model_max_budget=end_user_mmb, model=model_name, + team_id=valid_token.team_id, ) # team / user / end_user / project context objects are fetched by diff --git a/litellm/proxy/client/README.md b/litellm/proxy/client/README.md index 1fff68677cc..ceec636567f 100644 --- a/litellm/proxy/client/README.md +++ b/litellm/proxy/client/README.md @@ -342,7 +342,7 @@ The CLI provides these authentication commands: - **`lite login --pkce`** - Sign in through the system browser with OAuth authorization code + PKCE; the key renews itself with a refresh token - **`lite logout`** - Clear stored authentication token (and revoke a `--pkce` refresh token on the proxy) - **`lite whoami`** - Show current authentication status -- **`lite auth print-token`** - Print the cached token (used as Claude Code's `apiKeyHelper`); renews a `--pkce` key first and fails once a classic token has expired +- **`lite auth print-token`** - Print the cached token (used as Claude Code's `apiKeyHelper`); renews a `--pkce` key first, and fails once a classic token is past 24 hours and the proxy rejects it ### Authentication Flow Steps @@ -382,7 +382,7 @@ Keychain storage needs the `keyring` package, which ships with `pip install 'lit `lite logout` clears both stores. If the keychain is locked at that moment it says so, and re-running it once the keychain is unlocked finishes the job. -The stored credential is a short-lived, per-session agent token, not a managed virtual key. It is scoped to the user and team you logged in as and inherits their models and budgets; spend is tracked against the shared team and user budgets rather than a separate per-session cap, so multiple logins or several concurrent agents all draw down the same allowance. It is short-lived by design (default 24h, configurable via `LITELLM_CLI_JWT_EXPIRATION_HOURS`); re-run `lite login` to refresh it and pick up your latest team and user settings. `lite auth print-token` (usable as Claude Code's `apiKeyHelper`) prints it while fresh and fails once it expires -- there is no silent renewal. It is accepted on a default deployment without `EXPERIMENTAL_UI_LOGIN`, does not appear in the Keys UI, and cannot be rotated or revoked mid-session. A credential from `lite login --pkce` is the exception: it carries a refresh token, so the CLI renews the key shortly before it expires and `lite logout` revokes the refresh token on the proxy (see [Browser sign-in with PKCE](https://docs.litellm.ai/docs/proxy/cli_sso#browser-sign-in-with-pkce)). Only the holder can end a `--pkce` session early, with `lite logout`; an admin has no button for it, but every renewal re-reads the user on the proxy, so deactivating the user or removing them from the team makes the next renewal fail and the key runs out within `LITELLM_CLI_JWT_EXPIRATION_HOURS`. On a proxy with more than one worker or replica, configure Redis (`litellm_settings.cache` with Redis `cache_params`, or `general_settings.coordination_redis`) so a refresh token stays single-use and `lite logout` holds on every worker; without Redis each worker keeps its own record. For a long-lived, rotatable, Keys-UI-visible credential, create a dedicated virtual key in the dashboard and pass it via `--api-key` or `LITELLM_PROXY_API_KEY`. +The stored credential is a short-lived, per-session agent token, not a managed virtual key. It is scoped to the user and team you logged in as and inherits their models and budgets; spend is tracked against the shared team and user budgets rather than a separate per-session cap, so multiple logins or several concurrent agents all draw down the same allowance. It is short-lived by design (default 24h, configurable via `LITELLM_CLI_JWT_EXPIRATION_HOURS`); re-run `lite login` to refresh it and pick up your latest team and user settings. `lite auth print-token` (usable as Claude Code's `apiKeyHelper`) prints it, and once it is past 24 hours (or the client's `LITELLM_CLI_JWT_EXPIRATION_HOURS`) asks the proxy first and fails if the proxy rejects it. There is no silent renewal. It is accepted on a default deployment without `EXPERIMENTAL_UI_LOGIN`, does not appear in the Keys UI, and cannot be rotated or revoked mid-session. A credential from `lite login --pkce` is the exception: it carries a refresh token, so the CLI renews the key shortly before it expires and `lite logout` revokes the refresh token on the proxy (see [Browser sign-in with PKCE](https://docs.litellm.ai/docs/proxy/cli_sso#browser-sign-in-with-pkce)). Only the holder can end a `--pkce` session early, with `lite logout`; an admin has no button for it, but every renewal re-reads the user on the proxy, so deactivating the user or removing them from the team makes the next renewal fail and the key runs out within `LITELLM_CLI_JWT_EXPIRATION_HOURS`. On a proxy with more than one worker or replica, configure Redis (`litellm_settings.cache` with Redis `cache_params`, or `general_settings.coordination_redis`) so a refresh token stays single-use and `lite logout` holds on every worker; without Redis each worker keeps its own record. For a long-lived, rotatable, Keys-UI-visible credential, create a dedicated virtual key in the dashboard and pass it via `--api-key` or `LITELLM_PROXY_API_KEY`. ### Usage diff --git a/litellm/proxy/client/cli/README.md b/litellm/proxy/client/cli/README.md index 4038ff6f582..819908f9e70 100644 --- a/litellm/proxy/client/cli/README.md +++ b/litellm/proxy/client/cli/README.md @@ -506,7 +506,7 @@ To pin the model, pass the agent's own model flag (for example `lite claude --mo The token minted by `lite login` is a short-lived, per-session agent credential, not a managed virtual key. It is scoped to the user and team you authenticated as, inherits that user's and team's models and budgets, and is enforced on the proxy exactly like a virtual key on the same team (guardrails, routing, logging, spend). Spend is tracked against the shared team and user budgets, so running several agents (or logging in more than once) does not hand each session its own separate budget; they all draw down the same team/user allowance. There is no separate per-session cap, so sustained agent use is not capped at a small chat-session limit. -The credential is short-lived by design (default 24h, configurable via `LITELLM_CLI_JWT_EXPIRATION_HOURS`); run `lite login` again to refresh it, which also re-reads your latest team and user settings. It does not appear in the Keys UI and cannot be rotated or revoked mid-session. `lite auth print-token` (usable as Claude Code's `apiKeyHelper`) prints it while it's still fresh and fails once it expires -- there is no silent renewal, so a long-running session needs a fresh `lite login` once a day. `lite claude`, `lite codex`, `lite opencode`, and `lite pi` work with it on a default deployment; `EXPERIMENTAL_UI_LOGIN` is not required. `lite login --pkce` is the exception to the daily re-login: it signs in through your system browser with OAuth authorization code and PKCE and stores a refresh token next to the key, so every `lite` command and `lite auth print-token` renew the key on their own shortly before it expires, `lite whoami` shows when the current key expires, and `lite logout` revokes the refresh token on the proxy (it needs a proxy that serves `/.well-known/litellm-cli-auth`; see [Browser sign-in with PKCE](https://docs.litellm.ai/docs/proxy/cli_sso#browser-sign-in-with-pkce)). When a renewal is refused, for example after a `lite logout` run from another copy of the credential, the command prints why on stderr and, once the key has run out, tells you to run `lite login --pkce` again. Only the holder can end a `--pkce` session early, with `lite logout`; an admin has no button for it, but every renewal re-reads the user on the proxy, so deactivating the user or removing them from the team makes the next renewal fail and the key runs out within `LITELLM_CLI_JWT_EXPIRATION_HOURS`. On a proxy with more than one worker or replica, configure Redis (`litellm_settings.cache` with Redis `cache_params`, or `general_settings.coordination_redis`) so a refresh token stays single-use and `lite logout` holds on every worker; without Redis each worker keeps its own record. If you need a long-lived, rotatable key that shows up in the Keys UI, create a dedicated virtual key in the dashboard and pass it via `--api-key` or `LITELLM_PROXY_API_KEY` instead. +The credential is short-lived by design (default 24h, configurable via `LITELLM_CLI_JWT_EXPIRATION_HOURS`); run `lite login` again to refresh it, which also re-reads your latest team and user settings. It does not appear in the Keys UI and cannot be rotated or revoked mid-session. `lite auth print-token` (usable as Claude Code's `apiKeyHelper`) prints it without asking the proxy for its first 24 hours, or `LITELLM_CLI_JWT_EXPIRATION_HOURS` if you set it on the client. After that, `print-token` and `lite whoami` ask the proxy whether it still accepts the token, and `print-token` fails once the proxy rejects it. There is no silent renewal, so a long-running session needs a fresh `lite login` each time the proxy's token lifetime runs out. If the proxy's tokens last less than 24 hours, set the same `LITELLM_CLI_JWT_EXPIRATION_HOURS` on the client so `print-token` stops printing the token once it runs out. `lite up` still starts a new login once the token is older than that same client window. It copies the token into Claude Code's settings as a static key that it never renews, so a fresh login gives Claude Code the proxy's full token lifetime instead of whatever an old token has left. `lite claude`, `lite codex`, `lite opencode`, and `lite pi` work with it on a default deployment; `EXPERIMENTAL_UI_LOGIN` is not required. `lite login --pkce` is the exception to the re-login: it signs in through your system browser with OAuth authorization code and PKCE and stores a refresh token next to the key, so every `lite` command and `lite auth print-token` renew the key on their own shortly before it expires, `lite whoami` shows when the current key expires, and `lite logout` revokes the refresh token on the proxy (it needs a proxy that serves `/.well-known/litellm-cli-auth`; see [Browser sign-in with PKCE](https://docs.litellm.ai/docs/proxy/cli_sso#browser-sign-in-with-pkce)). When a renewal is refused, for example after a `lite logout` run from another copy of the credential, the command prints why on stderr and, once the key has run out, tells you to run `lite login --pkce` again. Only the holder can end a `--pkce` session early, with `lite logout`; an admin has no button for it, but every renewal re-reads the user on the proxy, so deactivating the user or removing them from the team makes the next renewal fail and the key runs out within `LITELLM_CLI_JWT_EXPIRATION_HOURS`. On a proxy with more than one worker or replica, configure Redis (`litellm_settings.cache` with Redis `cache_params`, or `general_settings.coordination_redis`) so a refresh token stays single-use and `lite logout` holds on every worker; without Redis each worker keeps its own record. If you need a long-lived, rotatable key that shows up in the Keys UI, create a dedicated virtual key in the dashboard and pass it via `--api-key` or `LITELLM_PROXY_API_KEY` instead. ### Route Every Claude Code Session Through the Proxy diff --git a/litellm/proxy/client/cli/commands/agents.py b/litellm/proxy/client/cli/commands/agents.py index 52e36964bc1..f19fb508c7d 100644 --- a/litellm/proxy/client/cli/commands/agents.py +++ b/litellm/proxy/client/cli/commands/agents.py @@ -5,16 +5,18 @@ import shutil import subprocess import sys import tempfile -from collections.abc import Callable, Mapping, Sequence +from collections import Counter +from collections.abc import Callable, Hashable, Iterable, Mapping, Sequence from dataclasses import dataclass from itertools import chain from pathlib import Path from types import MappingProxyType from typing import Final, TypeAlias, TypeVar +from urllib.parse import urlsplit import click import requests -from pydantic import JsonValue, TypeAdapter, ValidationError +from pydantic import ConfigDict, JsonValue, TypeAdapter, ValidationError from litellm.proxy.common_utils.codex_model_catalog import ( CODEX_BASE_INSTRUCTIONS_PATH, @@ -34,7 +36,7 @@ from .claude_settings import ( load_json_or_empty, ) from .cmd_quoting import quote_for_cmd -from .config import claude_subscription_default +from .config import subscription_default from .pi import ( LITELLM_PROXY_API_KEY_ENV, PI_PROVIDER_NAME, @@ -83,9 +85,11 @@ _INSTALL_DOCS: Final[dict[str, str]] = { } _HIDDEN_AGENTS: Final = frozenset({"pi"}) -_SUBSCRIPTION_AGENTS: Final = frozenset({"claude"}) +_SUBSCRIPTION_LOGINS: Final = MappingProxyType({"claude": "claude.ai", "codex": "ChatGPT"}) +_SUBSCRIPTION_AGENTS: Final = frozenset(_SUBSCRIPTION_LOGINS) CODEX_PROXY_PROVIDER: Final = "litellm" +CODEX_SUBSCRIPTION_PROVIDER: Final = "lite_subscription" CODEX_HOME_ENV: Final = "CODEX_HOME" CODEX_MODEL_CATALOG_FILENAME: Final = "litellm-models.json" _CODEX_PREFLIGHT_TIMEOUT_SECONDS: Final = 10.0 @@ -143,6 +147,10 @@ def build_agent_env( travels in the x-litellm-api-key header through ANTHROPIC_CUSTOM_HEADERS, and no ANTHROPIC_AUTH_TOKEN or ANTHROPIC_API_KEY is left in the environment, since either one makes Claude Code stop using the subscription (and its connectors). + With subscription=True the OpenAI profile keeps Codex on its ChatGPT login: the key goes to + LITELLM_PROXY_API_KEY, which Codex sends in the x-litellm-api-key header, and OPENAI_API_KEY and + OPENAI_BASE_URL are left exactly as the caller had them, so the key is never offered to Codex as an + OpenAI credential and a child process never pairs the caller's own OpenAI key with the proxy URL. """ env: Final = dict(base_env) root: Final = base_url.rstrip("/") @@ -161,21 +169,24 @@ def build_agent_env( if ENABLE_GATEWAY_MODEL_DISCOVERY_ENV not in env: env[ENABLE_GATEWAY_MODEL_DISCOVERY_ENV] = ENABLE_GATEWAY_MODEL_DISCOVERY_VALUE if PROFILE_OPENAI in profiles: - env[OPENAI_BASE_URL_ENV] = root + "/v1" - env[OPENAI_API_KEY_ENV] = api_key + if subscription: + env[LITELLM_PROXY_API_KEY_ENV] = api_key + else: + env[OPENAI_BASE_URL_ENV] = root + "/v1" + env[OPENAI_API_KEY_ENV] = api_key if PROFILE_LITELLM in profiles: env[LITELLM_PROXY_API_KEY_ENV] = api_key return env -def codex_proxy_provider(base_url: str) -> Mapping[str, str | bool]: +def codex_proxy_provider(base_url: str, *, subscription: bool = False) -> Mapping[str, str | bool]: return MappingProxyType( { "name": "LiteLLM proxy", "base_url": base_url.rstrip("/") + "/v1", "wire_api": "responses", "supports_websockets": False, - "requires_openai_auth": False, + "requires_openai_auth": subscription, } ) @@ -304,7 +315,7 @@ def subscription_launch_args( return (_SETTINGS_FLAG, str(overlay)), rest -def _codex_proxy_args(base_url: str) -> list[str]: +def _codex_proxy_args(base_url: str, subscription: bool) -> list[str]: """Codex `-c` overrides that point it at the proxy. Codex ignores OPENAI_BASE_URL (it always dials api.openai.com), so the env @@ -312,24 +323,35 @@ def _codex_proxy_args(base_url: str) -> list[str]: inline; supports_websockets=false forces the HTTP/SSE Responses transport because the proxy does not speak the Responses WebSocket protocol. The key is read from OPENAI_API_KEY, which build_agent_env already exports. + With subscription=True the provider is `lite_subscription` with requires_openai_auth, so Codex + signs in with its own ChatGPT login, and the key travels in the x-litellm-api-key header from + LITELLM_PROXY_API_KEY. It sets no env_key, which would win over the login. A `-c` override cannot + remove keys, so the id is one no config.toml defines: `lite configure codex` writes `litellm`, and + the cookbook tells users to write `litellm_subscription`, whose env_key or headers would otherwise apply. """ - provider: Final = f"model_providers.{CODEX_PROXY_PROVIDER}" + provider_id: Final = CODEX_SUBSCRIPTION_PROVIDER if subscription else CODEX_PROXY_PROVIDER + provider: Final = f"model_providers.{provider_id}" + credential: Final = ( + f"{provider}.env_http_headers={{{json.dumps(LITELLM_KEY_HEADER)}={json.dumps(LITELLM_PROXY_API_KEY_ENV)}}}" + if subscription + else f'{provider}.env_key="{OPENAI_API_KEY_ENV}"' + ) return [ "-c", - f'model_provider="{CODEX_PROXY_PROVIDER}"', + f'model_provider="{provider_id}"', *( argument - for key, value in codex_proxy_provider(base_url).items() + for key, value in codex_proxy_provider(base_url, subscription=subscription).items() for argument in ("-c", f"{provider}.{key}={json.dumps(value)}") ), "-c", - f'{provider}.env_key="{OPENAI_API_KEY_ENV}"', + credential, "-c", f"{provider}.http_headers={{}}", ] -_PROXY_ARGS: Final[dict[str, Callable[[str], list[str]]]] = { +_PROXY_ARGS: Final[dict[str, Callable[[str, bool], list[str]]]] = { "codex": _codex_proxy_args, } @@ -410,14 +432,14 @@ _Preparer: TypeAlias = Callable[[str, str, Mapping[str, str]], Sequence[str]] _PREPARERS: Final[Mapping[str, _Preparer]] = MappingProxyType({"pi": prepare_pi, "codex": prepare_codex}) -def agent_launch_args(command: str, base_url: str) -> list[str]: +def agent_launch_args(command: str, base_url: str, *, subscription: bool = False) -> list[str]: """Extra CLI args an agent needs to actually honor the proxy. Claude Code and OpenCode respect the exported env vars, so they get nothing here; Codex needs its provider pointed via config overrides. """ builder: Final = _PROXY_ARGS.get(os.path.basename(command)) - return builder(base_url) if builder else [] + return builder(base_url, subscription) if builder else [] class ListedModel(LiteLLMBaseModel): @@ -477,6 +499,113 @@ def _fetch_model_listing( return listing.data +class _DeploymentParams(LiteLLMBaseModel): + model_config = ConfigDict(frozen=True) + + model: str + custom_llm_provider: str | None = None + api_base: str | None = None + litellm_credential_name: str | None = None + reasoning_effort: JsonValue = None + + +class _DeploymentInfo(LiteLLMBaseModel): + model_config = ConfigDict(frozen=True) + + team_public_model_name: str | None = None + blocked: bool | None = None + + +class _Deployment(LiteLLMBaseModel): + model_config = ConfigDict(frozen=True) + + model_name: str + litellm_params: _DeploymentParams + model_info: _DeploymentInfo | None = None + + +class _DeploymentListing(LiteLLMBaseModel): + model_config = ConfigDict(frozen=True) + + data: tuple[_Deployment, ...] + + +@dataclass(frozen=True, slots=True) +class ModelUpstream: + """The OpenAI model every deployment behind a public name routes to, and the reasoning effort they all pin.""" + + model: str + reasoning_effort: str | None = None + + +_NO_UPSTREAMS: Final[Mapping[str, ModelUpstream]] = MappingProxyType({}) +_Pinned: Final = TypeVar("_Pinned", bound=Hashable) + + +def _public_name(deployment: _Deployment) -> str: + team_name: Final = deployment.model_info.team_public_model_name if deployment.model_info is not None else None + return team_name or deployment.model_name + + +def _is_paused(deployment: _Deployment) -> bool: + return deployment.model_info is not None and deployment.model_info.blocked is True + + +def _is_openai_host(params: _DeploymentParams) -> bool: + if params.api_base is None: + return not params.litellm_credential_name + host: Final = urlsplit(params.api_base).hostname or "" + return host == "api.openai.com" or host.endswith(".api.openai.com") + + +def _openai_model(params: _DeploymentParams) -> str | None: + if params.custom_llm_provider not in (None, "openai") or not _is_openai_host(params): + return None + provider, slash, name = params.model.partition("/") + if not slash: + return params.model + return name if provider == "openai" else None + + +def _pinned_effort(params: _DeploymentParams) -> str | None: + return params.reasoning_effort if isinstance(params.reasoning_effort, str) else None + + +def _shared_by_every_deployment(values: Iterable[tuple[str, _Pinned]]) -> Mapping[str, _Pinned]: + distinct: Final = frozenset(values) + values_per_name: Final = Counter(name for name, _ in distinct) + return MappingProxyType({name: value for name, value in distinct if values_per_name[name] == 1}) + + +def _upstreams_by_public_name(deployments: Sequence[_Deployment]) -> Mapping[str, ModelUpstream]: + live: Final = tuple(d for d in deployments if not _is_paused(d)) + models: Final = _shared_by_every_deployment((_public_name(d), _openai_model(d.litellm_params)) for d in live) + efforts: Final = _shared_by_every_deployment((_public_name(d), _pinned_effort(d.litellm_params)) for d in live) + return MappingProxyType( + {name: ModelUpstream(model, efforts.get(name)) for name, model in models.items() if model is not None} + ) + + +def _fetch_model_upstreams( + base_url: str, + api_key: str, + *, + get: Callable[..., requests.Response], +) -> Mapping[str, ModelUpstream]: + url: Final = base_url.rstrip("/") + "/v1/model/info" + try: + resp: Final = get(url, headers=MappingProxyType({"Authorization": f"Bearer {api_key}"}), timeout=10) + except requests.RequestException: + return _NO_UPSTREAMS + if resp.status_code != 200: + return _NO_UPSTREAMS + try: + listing: Final = _DeploymentListing.model_validate_json(resp.content) + except ValidationError: + return _NO_UPSTREAMS + return _upstreams_by_public_name(listing.data) + + class _OpenCodeLimit(LiteLLMBaseModel): context: int output: int @@ -556,8 +685,21 @@ def opencode_model_sync_env( return MappingProxyType({OPENCODE_CONFIG_CONTENT_ENV: opencode_provider_config(base_url, listing)}) +def _codex_row(model: ListedModel, upstream: ModelUpstream | None) -> CodexCatalogRow: + return CodexCatalogRow( + id=model.id, + mode=model.mode, + max_input_tokens=model.max_input_tokens, + upstream_model=upstream.model if upstream is not None else None, + reasoning_effort=upstream.reasoning_effort if upstream is not None else None, + ) + + def codex_model_catalog( - models: Sequence[ListedModel], stock: Sequence[CodexStockModel], instructions: str + models: Sequence[ListedModel], + stock: Sequence[CodexStockModel], + instructions: str, + upstreams: Mapping[str, ModelUpstream], ) -> str | None: """The `model_catalog_json` body listing the proxy's chat models, or None if there are none. @@ -566,14 +708,23 @@ def codex_model_catalog( installed Codex knows keeps that Codex's own entry and the proxy only decides its place in the picker: the listing orders it, lists it even when Codex hides it or keeps it off the API, and keeps Codex's upgrade nudge only - when the model it points at is served too. A model Codex does not know gets the fallback + when the model it points at is served too. An alias of such a model, per + `upstreams`, takes that entry too, minus the defaults Codex picks for the + model: no service tier or upgrade nudge, the reasoning effort its + deployments pin, and a window no larger than its listed max_input_tokens. + A model Codex does not know gets the fallback entry, with the same base instructions Codex itself uses so the agent never - runs without a system prompt. The catalog is the one `/v1/models?client_version=...` - serves, built from the installed Codex's own entries instead of the proxy's vendored ones. + runs without a system prompt. Apart from aliases, the catalog is the one + `/v1/models?client_version=...` serves, built from the installed Codex's own + entries instead of the proxy's vendored ones. """ - rows: Final = tuple(CodexCatalogRow(id=m.id, mode=m.mode, max_input_tokens=m.max_input_tokens) for m in models) + rows: Final = tuple(_codex_row(m, upstreams.get(m.id)) for m in models) body: Final = codex_models_response_json( - rows, stock=MappingProxyType({m.slug: m for m in stock}), instructions=instructions, byte_limit=None + rows, + stock=MappingProxyType({m.slug: m for m in stock}), + instructions=instructions, + byte_limit=None, + alias_defaults="deployment", ) return body.json if body.listed else None @@ -658,12 +809,14 @@ def codex_model_sync_args( Codex has no env or inline equivalent of OPENCODE_CONFIG_CONTENT: the catalog must be a file, so it is written under $CODEX_HOME (default ~/.codex) and atomically replaced on every launch. The Codex at `binary` first lists its - own models, so the ones the proxy serves keep that Codex's entries, and then + own models, so the ones the proxy serves keep that Codex's entries, an alias + included when every unpaused deployment /v1/model/info lists for it routes + to the same OpenAI model and Codex knows that model, and then reads the file back once before it is handed over. The key never lands in the file. A failed fetch, read, listing, write or read-back is reported rather than raised: Codex still launches with its built-in catalog and takes a proxy model by name via -m, and a rejected file stays on disk to be looked - at. + at. An unavailable /v1/model/info only leaves every alias on the fallback entry. """ listing: Final = _fetch_model_listing(base_url, api_key, get=get) if isinstance(listing, ModelSyncSkipped): @@ -680,7 +833,8 @@ def codex_model_sync_args( stock: Final = _stock_codex_models(binary, base_env, run=run) if isinstance(stock, ModelSyncSkipped): return stock - catalog: Final = codex_model_catalog(listing, stock, instructions) + upstreams: Final = _fetch_model_upstreams(base_url, api_key, get=get) + catalog: Final = codex_model_catalog(listing, stock, instructions, upstreams) if catalog is None: return ModelSyncSkipped(f"{base_url.rstrip('/')}/v1/models lists no chat models") try: @@ -889,11 +1043,13 @@ def run_agent( (verify_subscription if subscription else verify)(base_url, api_key) env_before_sync: Final = base_env if base_env is not None else os.environ - synced: Final = sync_models(binary, env_before_sync, base_url, api_key, skip_verify) + synced: Final = ( + _NO_EXTRA_ENV if subscription else sync_models(binary, env_before_sync, base_url, api_key, skip_verify) + ) if isinstance(synced, ModelSyncSkipped): warn(f"litellm: not syncing {display_name} models from the proxy: {synced.reason}") - prepare: Final = preparers.get(os.path.basename(command[0])) + prepare: Final = None if subscription else preparers.get(os.path.basename(command[0])) prepared_args: Final = tuple(prepare(base_url, api_key, env_before_sync)) if prepare is not None else () env: Final = MappingProxyType( @@ -903,7 +1059,11 @@ def run_agent( } ) synced_args: Final = synced.args if isinstance(synced, ModelSyncArgs) else () - extra_args: Final = (*agent_launch_args(command[0], base_url), *synced_args, *prepared_args) + extra_args: Final = ( + *agent_launch_args(command[0], base_url, subscription=subscription), + *synced_args, + *prepared_args, + ) settings_args, forwarded = ( subscription_launch_args( command, @@ -914,7 +1074,7 @@ def run_agent( ), write_overlay, ) - if subscription and os.path.basename(command[0]) in _SUBSCRIPTION_AGENTS + if subscription and os.path.basename(command[0]) == "claude" else ((), tuple(command[1:])) ) if reattach_terminal is not None: @@ -948,10 +1108,19 @@ def resolve_api_key(ctx: click.Context) -> str: _SKIP_VERIFY_HELP: Final = "Skip the pre-launch key check against the proxy." -_SUBSCRIPTION_HELP: Final = ( - "Keep using your claude.ai login (and its connectors). The LiteLLM key is sent in the " - "x-litellm-api-key header instead of replacing Claude Code's own credential. " - "Make it the default with `lite config set claude_subscription true`." +_SUBSCRIPTION_HELP: Final = MappingProxyType( + { + "claude": ( + "Keep using your claude.ai login (and its connectors). The LiteLLM key is sent in the " + "x-litellm-api-key header instead of replacing Claude Code's own credential. " + "Make it the default with `lite config set claude_subscription true`." + ), + "codex": ( + "Keep using your ChatGPT login. The LiteLLM key is sent in the " + "x-litellm-api-key header instead of replacing Codex's own credential. " + "Make it the default with `lite config set codex_subscription true`." + ), + } ) @@ -964,10 +1133,8 @@ def _launch( api_key: Final = resolve_api_key(ctx) display_name, _profiles = agent_profile(binary) - use_subscription: Final = ( - subscription if subscription is not None else binary in _SUBSCRIPTION_AGENTS and claude_subscription_default() - ) - login_note: Final = " (keeping your claude.ai login)" if use_subscription else "" + use_subscription: Final = subscription if subscription is not None else subscription_default(binary) + login_note: Final = f" (keeping your {_SUBSCRIPTION_LOGINS[binary]} login)" if use_subscription else "" click.echo(f"litellm: routing {display_name} through proxy at {base_url.rstrip('/')}{login_note}") try: @@ -989,7 +1156,7 @@ _Decorated: Final = TypeVar("_Decorated", bound=Callable[..., object] | click.Co def _subscription_option(binary: str) -> Callable[[_Decorated], _Decorated]: if binary not in _SUBSCRIPTION_AGENTS: return lambda func: func - return click.option("--subscription/--no-subscription", default=None, help=_SUBSCRIPTION_HELP) + return click.option("--subscription/--no-subscription", default=None, help=_SUBSCRIPTION_HELP[binary]) def _make_agent_command(binary: str, display_name: str) -> click.Command: diff --git a/litellm/proxy/client/cli/commands/auth.py b/litellm/proxy/client/cli/commands/auth.py index b5302d1f561..e38f54adc4f 100644 --- a/litellm/proxy/client/cli/commands/auth.py +++ b/litellm/proxy/client/cli/commands/auth.py @@ -13,7 +13,6 @@ from rich.console import Console from rich.table import Table from typing_extensions import NotRequired, ReadOnly, TypedDict, assert_never -from litellm.constants import CLI_JWT_EXPIRATION_HOURS from litellm.litellm_core_utils.cli_keyring import ( DISABLE_KEYRING_ENV_VAR, SYSTEM_KEYRING, @@ -143,6 +142,9 @@ _TeamMapping: Final = TypeVar("_TeamMapping", bound=Mapping[str, object]) _JSON_OBJECT: Final = TypeAdapter(Mapping[str, object], config=ConfigDict(hide_input_in_errors=True)) +_PROXY_KEY_CHECK_TIMEOUT_SECONDS: Final = 3 +_PROXY_REJECTED_KEY_STATUSES: Final = frozenset({401, 403}) + KEYRING_INSTALL_HINT: Final = "pip install 'litellm[cli]'" KEYRING_ENABLE_HINT: Final = "keyring --enable (or unset PYTHON_KEYRING_BACKEND)" @@ -1033,10 +1035,12 @@ def print_token(ctx: click.Context): Designed to be used as Claude Code's `apiKeyHelper` (https://docs.claude.com/en/docs/claude-code/settings): stdout must - contain only the token, so all diagnostics go to stderr. The token - expires after `LITELLM_CLI_JWT_EXPIRATION_HOURS` (default 24h); a - `lite login --pkce` token renews itself here first, and once a token - has expired for good, run the same `lite login` command again. + contain only the token, so all diagnostics go to stderr. A token younger + than `LITELLM_CLI_JWT_EXPIRATION_HOURS` (default 24h) is printed without + asking the proxy. An older one is checked against the proxy and refused + only if the proxy rejects it. A `lite login --pkce` + token renews itself here first, and once a token has expired for good, + run the same `lite login` command again. """ vault: Final = context_secret_vault(ctx) token_data: Final = load_token(vault=vault) @@ -1055,7 +1059,7 @@ def print_token(ctx: click.Context): sys.exit(1) renews: Final = "refresh_token" in token_data - if not is_cli_token_fresh(token_data) and not renews: + if not renews and token_expired(token_data): click.echo("Token expired. Run 'lite login' again.", err=True) sys.exit(1) @@ -1111,8 +1115,32 @@ def whoami(ctx: click.Context): expires_at: Final = token_data.get("expires_at") if isinstance(expires_at, (int, float)): click.echo(_key_expiry_line(expires_at, renews="refresh_token" in token_data)) - elif age_hours > CLI_JWT_EXPIRATION_HOURS: - click.echo(f"Warning: Token is more than {CLI_JWT_EXPIRATION_HOURS} hours old and may have expired.") + elif token_expired(token_data): + click.echo("Token expired. Run 'lite login' again.") + + +def token_expired(token_data: Mapping[str, object]) -> bool: + if is_cli_token_fresh(token_data): + return False + if isinstance(token_data.get("expires_at"), (int, float)): + return True + return _proxy_rejects_key(token_data) + + +def _proxy_rejects_key(token_data: Mapping[str, object]) -> bool: + key: Final = token_data.get("key") + base_url: Final = token_data.get("base_url") + if not isinstance(key, str) or not isinstance(base_url, str) or not base_url: + return True + try: + response: Final = requests.get( + f"{base_url}/v1/models", + headers={"Authorization": f"Bearer {key}"}, + timeout=_PROXY_KEY_CHECK_TIMEOUT_SECONDS, + ) + except requests.RequestException: + return False + return response.status_code in _PROXY_REJECTED_KEY_STATUSES def _key_expiry_line(expires_at: float, renews: bool) -> str: diff --git a/litellm/proxy/client/cli/commands/config.py b/litellm/proxy/client/cli/commands/config.py index 539d88dce4a..1689a08c3de 100644 --- a/litellm/proxy/client/cli/commands/config.py +++ b/litellm/proxy/client/cli/commands/config.py @@ -14,6 +14,7 @@ from litellm.litellm_core_utils.private_json import ensure_private_dir, write_pr HIDDEN_COMMANDS_KEY: Final = "hidden_commands" CLAUDE_SUBSCRIPTION_KEY: Final = "claude_subscription" +CODEX_SUBSCRIPTION_KEY: Final = "codex_subscription" PKCE_KEY: Final = "pkce" _config_adapter: Final[TypeAdapter[Mapping[str, str]]] = TypeAdapter(Mapping[str, str]) @@ -114,9 +115,15 @@ def _normalize_boolean(key: str) -> Callable[[str], str]: return normalize -def claude_subscription_default() -> bool: - """Whether `lite claude` keeps the claude.ai login unless told otherwise.""" - return get_config_value(CLAUDE_SUBSCRIPTION_KEY) == "true" +_SUBSCRIPTION_KEYS: Final[Mapping[str, str]] = MappingProxyType( + {"claude": CLAUDE_SUBSCRIPTION_KEY, "codex": CODEX_SUBSCRIPTION_KEY} +) + + +def subscription_default(agent: str) -> bool: + """Whether `lite ` keeps the agent's own subscription login unless told otherwise.""" + key: Final = _SUBSCRIPTION_KEYS.get(agent) + return key is not None and get_config_value(key) == "true" def pkce_default() -> bool: @@ -129,6 +136,7 @@ _NORMALIZERS: Final[Mapping[str, Callable[[str], str]]] = MappingProxyType( "base_url": normalize_base_url, HIDDEN_COMMANDS_KEY: _normalize_hidden_commands, CLAUDE_SUBSCRIPTION_KEY: _normalize_boolean(CLAUDE_SUBSCRIPTION_KEY), + CODEX_SUBSCRIPTION_KEY: _normalize_boolean(CODEX_SUBSCRIPTION_KEY), PKCE_KEY: _normalize_boolean(PKCE_KEY), } ) diff --git a/litellm/proxy/client/models.py b/litellm/proxy/client/models.py index 1361a3e6364..859322f061d 100644 --- a/litellm/proxy/client/models.py +++ b/litellm/proxy/client/models.py @@ -3,9 +3,12 @@ from collections.abc import Mapping from typing import Any, Final import requests +from pydantic import ConfigDict, TypeAdapter from .exceptions import NotFoundError, UnauthorizedError +_JSON_OBJECT: Final = TypeAdapter(dict[str, object], config=ConfigDict(strict=True)) + class ModelsManagementClient: def __init__(self, base_url: str, api_key: str | None = None, timeout: int = 30): @@ -109,7 +112,7 @@ class ModelsManagementClient: try: response: Final = session.send(request.prepare(), timeout=self._timeout) response.raise_for_status() - return response.json() + return _JSON_OBJECT.validate_python(response.json()) except requests.exceptions.HTTPError as e: if e.response.status_code == 401: raise UnauthorizedError(e) @@ -145,7 +148,7 @@ class ModelsManagementClient: try: response: Final = session.send(request.prepare(), timeout=self._timeout) response.raise_for_status() - return response.json() + return _JSON_OBJECT.validate_python(response.json()) except requests.exceptions.HTTPError as e: if e.response.status_code == 401: raise UnauthorizedError(e) @@ -287,7 +290,7 @@ class ModelsManagementClient: try: response: Final = session.send(request.prepare(), timeout=self._timeout) response.raise_for_status() - return response.json() + return _JSON_OBJECT.validate_python(response.json()) except requests.exceptions.HTTPError as e: if e.response.status_code == 401: raise UnauthorizedError(e) diff --git a/litellm/proxy/common_request_processing.py b/litellm/proxy/common_request_processing.py index 24a36a7f2dc..fc29a6e3a08 100644 --- a/litellm/proxy/common_request_processing.py +++ b/litellm/proxy/common_request_processing.py @@ -4,6 +4,7 @@ import json import logging import math from collections.abc import AsyncGenerator, AsyncIterator, Awaitable, Callable, Coroutine, Mapping, Sequence +from dataclasses import dataclass from datetime import datetime from functools import lru_cache from itertools import chain @@ -136,10 +137,10 @@ from litellm.proxy.utils import ( # noqa: F401 # legacy module exports _check_and_merge_model_level_guardrails, # pyright: ignore[reportPrivateUsage,reportUnusedImport] # backwards-compatible package export check_and_merge_model_level_guardrails, ) -from litellm.responses.streaming_iterator import partial_responses_incomplete_event_on_disconnect +from litellm.responses.streaming_iterator import partial_responses_incomplete_event_on_disconnect, spawn_logging_task from litellm.router import Router +from litellm.router_strategy.auto_router.auto_router_model_naming import AUTO_ROUTER_MODEL_PREFIX from litellm.router_utils.add_retry_fallback_headers import get_hidden_params_dict -from litellm.router_utils.auto_router_model_naming import AUTO_ROUTER_MODEL_PREFIX from litellm.router_utils.common_utils import resolve_model_group_alias, resolve_served_model from litellm.types.extraction import ExtractionResponse from litellm.types.guardrails import GuardrailEventHooks @@ -265,6 +266,8 @@ from litellm.proxy.anthropic_endpoints.streaming_model_restamp import ( AnthropicStreamModelRestamper, ) from litellm.proxy.litellm_pre_call_utils import ( + ROUTER_SCHEDULED_ROUTE_TYPES, + SCHEDULER_PRIORITY_HEADER, LiteLLMProxyRequestSetup, add_litellm_data_to_request, get_metadata_variable_name, @@ -721,7 +724,7 @@ def _router_defaults(llm_router: Router | None) -> Mapping[str, object]: return {name: value for name, value in _REQUEST_FIELDS.validate_python(configured).items() if value is not None} -def _counted_drop_policies( +def counted_drop_policies( data: Mapping[str, object], llm_router: Router | None, team_id: str | None ) -> tuple[DropPolicy, ...]: requested: Final = {**_router_defaults(llm_router), **data} @@ -737,7 +740,7 @@ def _counted_drop_policies( def resolve_counted_tool_fields( data: Mapping[str, object], llm_router: Router | None, team_id: str | None ) -> Mapping[str, object] | ProxyException: - resolved: Final = resolve_tool_fields(data, lambda: _counted_drop_policies(data, llm_router, team_id)) + resolved: Final = resolve_tool_fields(data, lambda: counted_drop_policies(data, llm_router, team_id)) if isinstance(resolved, MalformedField): return ProxyException( message=resolved.message, @@ -2006,6 +2009,49 @@ def _content_text(fields: Mapping[str, object]) -> str: return str(fields.get("content", "")) +async def _no_stream_failure_to_release() -> None: + return None + + +@dataclass(slots=True) +class _ClientStreamFailureReport: + logging_obj: LiteLLMLoggingObj + report: Callable[[Exception], Awaitable[None]] + held: Exception | None = None + + @classmethod + def hold_while_streaming(cls, logging_obj: LiteLLMLoggingObj | None) -> Callable[[], Awaitable[None]]: + if logging_obj is None or logging_obj.on_detached_stream_failure is None: + return _no_stream_failure_to_release + return cls(logging_obj, logging_obj.on_detached_stream_failure)._start_holding() + + def _start_holding(self) -> Callable[[], Awaitable[None]]: + self.logging_obj.on_detached_stream_failure = self.hold + return self.release + + async def hold(self, failure: Exception) -> None: + if self.held is None: + self.held = failure + + async def release(self) -> None: + self.logging_obj.on_detached_stream_failure = self.report + if self.held is None: + return + await asyncio.shield( + spawn_logging_task( + asyncio.get_running_loop(), self._report_held(self.held), task_name="stream failure report" + ) + ) + + async def _report_held(self, failure: Exception) -> None: + try: + await self.report(failure) + except Exception as hook_failure: # noqa: BLE001 # a failing failure hook must not skip the stream cleanup + verbose_proxy_logger.warning( + "Stream failure hook raised: %s(%s)", type(hook_failure).__name__, sanitize_for_log(hook_failure) + ) + + class ProxyBaseLLMRequestProcessing: def __init__(self, data: dict, served_model: str | None = None): self.data = data @@ -2434,14 +2480,20 @@ class ProxyBaseLLMRequestProcessing: self.data["model"] = alias_target aliased_model: Final = self.data.get("model") + if llm_router is not None and route_type in ROUTER_SCHEDULED_ROUTE_TYPES and isinstance(aliased_model, str): + self.data.update( + llm_router.priority_header_update( + model=aliased_model, kwargs=self.data, header=request.headers.get(SCHEDULER_PRIORITY_HEADER) + ) + ) litellm_call_id: Final = resolve_litellm_call_id(request.headers.get("x-litellm-call-id")) self.data["litellm_call_id"] = litellm_call_id bind_telemetry_call_id(litellm_call_id) - DDSpanTagger.tag_call_id(self.data.get("litellm_call_id")) + DDSpanTagger.tag_call_id(litellm_call_id) DDSpanTagger.tag_request( user_api_key_dict=user_api_key_dict, - requested_model=self.data.get("model"), + requested_model=aliased_model, ) ### AUTO STREAM USAGE TRACKING ### @@ -2529,7 +2581,6 @@ class ProxyBaseLLMRequestProcessing: # have mutated `self.data` in place, and the audit-trail snapshot taken in # add_litellm_data_to_request predates that mutation. refresh_proxy_server_request_body_snapshot(self.data, guardrails_applied=True) - verbose_proxy_logger.debug("receiving data: %s", self.data) if "messages" in self.data and self.data["messages"]: logging_obj.update_messages(self.data["messages"]) @@ -3155,7 +3206,7 @@ class ProxyBaseLLMRequestProcessing: request_data=self.data, request=request, ) - if route_type == "aresponses": + if route_type in ("aresponses", "aget_responses"): selected_data_generator = ( ProxyBaseLLMRequestProcessing._wrap_responses_stream_for_container_ownership( original_stream_response=response, @@ -3498,6 +3549,8 @@ class ProxyBaseLLMRequestProcessing: request_data: Final = self.data async def _on_detached_stream_failure(exc: Exception) -> None: + if not logging_obj.claim_stream_failure_report(): + return try: await proxy_logging_obj.post_call_failure_hook( user_api_key_dict=user_api_key_dict, @@ -4180,7 +4233,7 @@ class ProxyBaseLLMRequestProcessing: e = transformed_exception litellm_debug_info: Final = getattr(e, "litellm_debug_info", "") verbose_proxy_logger.debug( - "\033[1;31mAn error occurred: %s %s\n\n Debug this by setting `--debug`, e.g. `litellm --model gpt-3.5-turbo --debug`", + "An error occurred: %s %s", e, litellm_debug_info, ) @@ -4448,11 +4501,15 @@ class ProxyBaseLLMRequestProcessing: client_disconnected = False delivered_chunk = False recent_tail = SSE_STREAM_START_TAIL # rebind-ok: rolling window over the yielded bytes + stream_logging_obj: Final[object] = request_data.get("litellm_logging_obj") # pyright: ignore[reportUnknownVariableType, reportUnknownMemberType] # legacy request data is narrowed to Logging below guarded_stream: Final[AsyncGenerator[object, None]] = proxy_logging_obj.async_post_call_streaming_iterator_hook( user_api_key_dict=user_api_key_dict, response=response, request_data=request_data, ) + release_stream_failure: Final = _ClientStreamFailureReport.hold_while_streaming( + stream_logging_obj if isinstance(stream_logging_obj, LiteLLMLoggingObj) else None + ) try: str_so_far = "" async for chunk in guarded_stream: @@ -4523,15 +4580,23 @@ class ProxyBaseLLMRequestProcessing: verbose_proxy_logger.exception( "litellm.proxy.proxy_server.async_data_generator(): Exception occured - %s", e ) - transformed_exception: Final = await proxy_logging_obj.post_call_failure_hook( - user_api_key_dict=user_api_key_dict, - original_exception=e, - request_data=request_data, + already_reported: Final = ( + isinstance(stream_logging_obj, LiteLLMLoggingObj) + and not stream_logging_obj.claim_stream_failure_report() + ) + transformed_exception: Final = ( + None + if already_reported + else await proxy_logging_obj.post_call_failure_hook( + user_api_key_dict=user_api_key_dict, + original_exception=e, + request_data=request_data, + ) ) if transformed_exception is not None: e = transformed_exception verbose_proxy_logger.debug( - "\x1b[1;31mAn error occurred: %s\n\n Debug this by setting `--debug`, e.g. `litellm --model gpt-3.5-turbo --debug`", + "An error occurred: %s", e, ) @@ -4549,15 +4614,18 @@ class ProxyBaseLLMRequestProcessing: seal: Final = "" if seal_open_frame is None else seal_open_frame(recent_tail) yield seal + error_frame if seal else error_frame finally: - await ProxyBaseLLMRequestProcessing.finalize_streaming_generator_cleanup( - request=request, - request_data=request_data, - response=response, - stream_completed=stream_completed, - client_disconnected=client_disconnected, - user_api_key_dict=user_api_key_dict, - proxy_logging_obj=proxy_logging_obj, - ) + try: + await release_stream_failure() + finally: + await ProxyBaseLLMRequestProcessing.finalize_streaming_generator_cleanup( + request=request, + request_data=request_data, + response=response, + stream_completed=stream_completed, + client_disconnected=client_disconnected, + user_api_key_dict=user_api_key_dict, + proxy_logging_obj=proxy_logging_obj, + ) @staticmethod def async_sse_data_generator( diff --git a/litellm/proxy/common_utils/codex_model_catalog.py b/litellm/proxy/common_utils/codex_model_catalog.py index 9b42f99305e..47cd1db9f39 100644 --- a/litellm/proxy/common_utils/codex_model_catalog.py +++ b/litellm/proxy/common_utils/codex_model_catalog.py @@ -24,7 +24,7 @@ from functools import cache from itertools import accumulate, pairwise from pathlib import Path from types import MappingProxyType, NoneType -from typing import TYPE_CHECKING, Annotated, Final, Literal +from typing import TYPE_CHECKING, Annotated, Final, Literal, TypeAlias from pydantic import ConfigDict, StringConstraints, TypeAdapter, ValidationError @@ -102,6 +102,7 @@ class CodexFallbackModel(LiteLLMBaseModel): experimental_supported_tools: tuple[()] = () context_window: int | None base_instructions: str + supports_search_tool: bool = False class CodexStockUpgrade(LiteLLMBaseModel): @@ -110,6 +111,12 @@ class CodexStockUpgrade(LiteLLMBaseModel): model: str +class CodexReasoningLevel(LiteLLMBaseModel): + model_config = ConfigDict(frozen=True, extra="allow") + + effort: str + + class CodexStockModel(LiteLLMBaseModel): """One `ModelInfo` entry as Codex ships it or prints it from `codex debug models`. @@ -128,6 +135,9 @@ class CodexStockModel(LiteLLMBaseModel): upgrade: CodexStockUpgrade | None = None service_tiers: tuple[CodexServiceTier, ...] = () default_service_tier: str | None = None + supports_search_tool: bool = False + supported_reasoning_levels: tuple[CodexReasoningLevel, ...] = () + context_window: int | None = None class CodexStockCatalog(LiteLLMBaseModel): @@ -135,21 +145,24 @@ class CodexStockCatalog(LiteLLMBaseModel): CodexCatalogEntry = CodexFallbackModel | CodexStockModel +CodexAliasDefaults: TypeAlias = Literal["codex", "deployment"] @dataclass(frozen=True, slots=True) class CodexCatalogRow: """What the catalog needs to know about one listed model: its public id, the listing's mode and - input limit, the upstream model behind it, and the `model_info` values the operator set; - `service_tiers` holds one raw `model_info.service_tiers` value per deployment behind the id, None - where a deployment sets none.""" + input limit, the upstream model behind it, the reasoning effort its deployments pin, and the + `model_info` values the operator set; `service_tiers` holds one raw `model_info.service_tiers` + value per deployment behind the id, None where a deployment sets none.""" id: str mode: str | None = None max_input_tokens: int | None = None upstream_model: str | None = None + reasoning_effort: str | None = None display_name: str | None = None service_tiers: tuple[object, ...] = () + search_tool_support: tuple[bool | None, ...] = () @cache @@ -242,6 +255,12 @@ def configured_service_tiers( return offered +def offered_search_tool(per_deployment: Sequence[bool | None]) -> bool | None: + if False in per_deployment: + return False + return True if per_deployment and None not in per_deployment else None + + def _codex_can_drive(row: CodexCatalogRow) -> bool: return "*" not in row.id and (row.mode is None or row.mode in CODEX_CHAT_MODES) @@ -254,18 +273,49 @@ def _stock_for(row: CodexCatalogRow, stock: Mapping[str, CodexStockModel]) -> Co return upstream if upstream is not None else stock.get(row.upstream_model.partition("/")[2]) +def _alias_context_window(row: CodexCatalogRow, stock_model: CodexStockModel) -> Mapping[str, int]: + if row.max_input_tokens is None or stock_model.context_window is None: + return MappingProxyType({}) + return MappingProxyType({"context_window": min(stock_model.context_window, row.max_input_tokens)}) + + +def _alias_reasoning_level(row: CodexCatalogRow, stock_model: CodexStockModel) -> str | None: + efforts: Final = frozenset(level.effort for level in stock_model.supported_reasoning_levels) + return row.reasoning_effort if row.reasoning_effort in efforts else None + + +def _deployment_defaults(row: CodexCatalogRow, stock_model: CodexStockModel) -> Mapping[str, object]: + """What an alias's deployments decide in place of the defaults Codex picks for the model they route to: + no service tier, verbosity, upgrade nudge or startup promo of Codex's own, so what the deployment + pins (or OpenAI's API default) stays in force, the pinned reasoning effort when Codex offers it and + none otherwise, and a window no larger than the alias's own limit.""" + return MappingProxyType( + { + "service_tiers": (), + "default_service_tier": None, + "default_verbosity": None, + "upgrade": None, + "availability_nux": None, + "default_reasoning_level": _alias_reasoning_level(row, stock_model), + **_alias_context_window(row, stock_model), + } + ) + + def _entry( index: int, row: CodexCatalogRow, stock: Mapping[str, CodexStockModel], served: frozenset[str], instructions: str, + alias_defaults: CodexAliasDefaults, ) -> CodexCatalogEntry: stock_model: Final = _stock_for(row, stock) stock_tiers: Final = MappingProxyType( {tier.id: tier for tier in (stock_model.service_tiers if stock_model is not None else ())} ) configured: Final = configured_service_tiers(row.service_tiers, row.id, stock_tiers) + search_tool: Final = offered_search_tool(row.search_tool_support) if stock_model is None: return CodexFallbackModel( slug=row.id, @@ -274,11 +324,13 @@ def _entry( service_tiers=configured if configured is not None else (), context_window=row.max_input_tokens, base_instructions=instructions, + supports_search_tool=search_tool is True, ) upgrade: Final = ( stock_model.upgrade if stock_model.upgrade is not None and stock_model.upgrade.model in served else None ) - stock_name: Final = stock_model.display_name if row.id == stock_model.slug else row.id + is_alias: Final = row.id != stock_model.slug + stock_name: Final = row.id if is_alias else stock_model.display_name listing: Final = { "slug": row.id, "display_name": row.display_name if row.display_name is not None else stock_name, @@ -286,6 +338,8 @@ def _entry( "visibility": "list", "supported_in_api": True, "upgrade": upgrade, + **({} if search_tool is None else {"supports_search_tool": search_tool}), + **(_deployment_defaults(row, stock_model) if is_alias and alias_defaults == "deployment" else {}), } if configured is None: return stock_model.model_copy(update=listing) @@ -351,6 +405,7 @@ def codex_models_response_json( stock: Mapping[str, CodexStockModel] | None = None, instructions: str | None = None, byte_limit: int | None = CODEX_CATALOG_BYTE_LIMIT, + alias_defaults: CodexAliasDefaults = "codex", ) -> CodexCatalogBody: """Codex's `ModelsResponse` body for `rows`, in listing order, cut to Codex's byte limit. @@ -359,13 +414,18 @@ def codex_models_response_json( byte limit silently and keeps its bundled one, so the body holds only the entries that fit, the ones offering a service tier taken first and the rest in listing order, an entry too large for the bytes left passed over, every kept entry at its listing position; `byte_limit=None` - keeps every entry. + keeps every entry. A row listed under another name than the Codex model its `upstream_model` + names (an alias) takes that model's entry; `alias_defaults="deployment"` drops the defaults + Codex picks for that model in favor of what the alias's deployments pin, while `"codex"` keeps + them, as Codex would use them for the model's own name. """ known: Final = bundled_codex_models() if stock is None else stock prompt: Final = codex_base_instructions() if instructions is None else instructions drivable: Final = tuple(row for row in rows if _codex_can_drive(row)) served: Final = frozenset(row.id for row in drivable) - entries: Final = tuple(_entry(index, row, known, served, prompt) for index, row in enumerate(drivable)) + entries: Final = tuple( + _entry(index, row, known, served, prompt, alias_defaults) for index, row in enumerate(drivable) + ) serialized: Final = tuple(_serialized(entry) for entry in entries) kept: Final = _kept_positions(entries, serialized, byte_limit) return CodexCatalogBody( @@ -385,6 +445,7 @@ def _catalog_row( upstream_model=llm_router.get_routable_upstream_model(lookup_id, team_id) if llm_router is not None else None, display_name=llm_router.get_configured_display_name(label_id) if llm_router is not None else None, service_tiers=llm_router.get_configured_service_tiers(lookup_id, team_id) if llm_router is not None else (), + search_tool_support=llm_router.get_search_tool_support(lookup_id, team_id) if llm_router is not None else (), ) diff --git a/litellm/proxy/common_utils/html_forms/native_client_consent.py b/litellm/proxy/common_utils/html_forms/native_client_consent.py index dac92c4e787..aeadc93221c 100644 --- a/litellm/proxy/common_utils/html_forms/native_client_consent.py +++ b/litellm/proxy/common_utils/html_forms/native_client_consent.py @@ -62,7 +62,7 @@ button {{ flex: 1; padding: 10px; border-radius: 6px; font-size: 15px; cursor: p

Approving issues it a personal credential that expires within {CLI_JWT_EXPIRATION_HOURS} hours. lite logout stops it from being renewed. Only approve if you started this sign-in yourself.

-{_team_field(teams)} +{team_select_field(teams)}
@@ -74,7 +74,7 @@ button {{ flex: 1; padding: 10px; border-radius: 6px; font-size: 15px; cursor: p """ -def _team_field(teams: Sequence[tuple[str, str]]) -> str: +def team_select_field(teams: Sequence[tuple[str, str]], *, require_choice: bool = False) -> str: if not teams: return "" if len(teams) == 1: @@ -83,9 +83,12 @@ def _team_field(teams: Sequence[tuple[str, str]]) -> str: f'' f"

Requests are attributed to team {escape(team_label)}.

" ) + placeholder: Final = '' if require_choice else "" options: Final = "".join( f'' for team_id, team_label in teams ) + required: Final = " required" if require_choice else "" return ( - f'' + '' + f'' ) diff --git a/litellm/proxy/common_utils/http_parsing_utils.py b/litellm/proxy/common_utils/http_parsing_utils.py index c4c3f0ad634..56cd14d987d 100644 --- a/litellm/proxy/common_utils/http_parsing_utils.py +++ b/litellm/proxy/common_utils/http_parsing_utils.py @@ -845,5 +845,3 @@ def _add_vector_store_id_from_path(request_data: dict, request: Request) -> None "populate_request_with_path_params: Updated request_data with vector_store_ids=%s", request_data.get("vector_store_ids"), ) - else: - verbose_proxy_logger.debug("populate_request_with_path_params: No vector_store_id present in path=%s", path) diff --git a/litellm/proxy/common_utils/openai_error_payload.py b/litellm/proxy/common_utils/openai_error_payload.py index 2f01dbe11f7..3c91e87ee51 100644 --- a/litellm/proxy/common_utils/openai_error_payload.py +++ b/litellm/proxy/common_utils/openai_error_payload.py @@ -2,14 +2,17 @@ ``type`` is a required string and ``param`` is nullable, neither of which the literal string ``"None"`` satisfies.""" +import sys from collections.abc import Mapping from types import MappingProxyType from typing import Final -from fastapi import status +from fastapi import HTTPException, status from litellm.constants import STRINGIFIED_NONE -from litellm.proxy._types import ProxyException +from litellm.proxy._types import ProxyErrorTypes, ProxyException, proxy_exception_status_code +from litellm.proxy.db.db_lookup_gate import DBLookupDeadlineExceeded +from litellm.proxy.db.exception_handler import PrismaDBExceptionHandler, exception_chain LITELLM_CALL_ID_HEADER: Final = "x-litellm-call-id" @@ -21,6 +24,19 @@ _OPENAI_ERROR_TYPE_BY_STATUS: Final[Mapping[int, str]] = MappingProxyType( } ) +_AUTH_FAILURE_STATUS_CODES: Final = frozenset({status.HTTP_401_UNAUTHORIZED, status.HTTP_403_FORBIDDEN}) + +_FAILOVER_SQLSTATES: Final = frozenset({"25006", "57P01", "57P02", "57P03"}) + +_FAILOVER_REFUSALS: Final = ( + "is not currently accepting connections", + "the database system is starting up", + "the database system is shutting down", + "the database system is in recovery mode", + "the database system is not yet accepting connections", + "terminating connection due to administrator command", +) + def attribute_of(value: object, name: str, default: object = None) -> object: return getattr(value, name, default) @@ -61,6 +77,82 @@ def openai_error_param(exc: object) -> str | None: return carried if isinstance(carried, str) and carried != STRINGIFIED_NONE else None +def proxy_exception_for(exc: Exception, default_status_code: int) -> ProxyException: + match exc: + case ProxyException(): + return exc + case _ if _is_database_outage(exc): + return ProxyException( + message=PrismaDBExceptionHandler.database_unavailable_message(exc), + type=ProxyErrorTypes.no_db_connection.value, + param=None, + code=status.HTTP_503_SERVICE_UNAVAILABLE, + ) + case HTTPException(status_code=status_code, detail=detail): + return _openai_shaped_proxy_exception(exc, str(detail), status_code) + case _: + return _openai_shaped_proxy_exception( + exc, str(exc) or type(exc).__name__, error_status_code(exc, default_status_code) + ) + + +def _is_database_outage(exc: Exception) -> bool: + return any(map(_is_database_outage_link, exception_chain(exc))) + + +def _is_database_outage_link(exc: BaseException) -> bool: + match exc: + case DBLookupDeadlineExceeded(): + return True + case Exception() if _prisma_is_loaded(): + return _is_prisma_outage(exc) + case _: + return False + + +def _prisma_is_loaded() -> bool: + return sys.modules.get("prisma") is not None + + +def _is_prisma_outage(exc: Exception) -> bool: + if PrismaDBExceptionHandler.is_prisma_engine_internal_error(exc): + return True + if type(exc).__module__.partition(".")[0] != "prisma": + return False + return PrismaDBExceptionHandler.is_database_service_unavailable_error(exc) or _is_failover_refusal(exc) + + +def _is_failover_refusal(exc: Exception) -> bool: + if PrismaDBExceptionHandler.is_read_only_transaction_error(exc): + return True + if PrismaDBExceptionHandler.postgres_sqlstate(exc) in _FAILOVER_SQLSTATES: + return True + message: Final = str(exc).lower() + return any(refusal in message for refusal in _FAILOVER_REFUSALS) + + +def _openai_shaped_proxy_exception(exc: Exception, message: str, status_code: int) -> ProxyException: + answered_status: Final = int(proxy_exception_status_code(message, str(status_code))) + return ProxyException( + message=message, + type=_catch_all_error_type(exc, answered_status), + param=openai_error_param(exc), + code=answered_status, + ) + + +def _catch_all_error_type(exc: Exception, status_code: int) -> str: + if _rejects_the_caller(exc, status_code): + return ProxyErrorTypes.auth_error.value + return openai_error_type(exc, status_code) + + +def _rejects_the_caller(exc: Exception, status_code: int) -> bool: + raised_as_http_answer: Final = isinstance(exc, HTTPException) + status_from_upstream: Final = error_status_code(exc, 0) == status_code + return status_code in _AUTH_FAILURE_STATUS_CODES and (raised_as_http_answer or not status_from_upstream) + + def litellm_call_id_headers(litellm_call_id: str | None) -> dict[str, str] | None: # mutable-ok: ProxyException.headers if litellm_call_id is None: return None diff --git a/litellm/proxy/common_utils/token_count_log.py b/litellm/proxy/common_utils/token_count_log.py new file mode 100644 index 00000000000..04c07a29117 --- /dev/null +++ b/litellm/proxy/common_utils/token_count_log.py @@ -0,0 +1,133 @@ +import json +import re +from asyncio import CancelledError +from collections.abc import Awaitable, Callable, Mapping +from dataclasses import dataclass +from types import MappingProxyType +from typing import Final, TypeVar + +from fastapi import status + +from litellm._logging import verbose_proxy_logger +from litellm.proxy.common_utils.openai_error_payload import error_status_code +from litellm.types.token_count import TokenCountSource +from litellm.types.utils import TokenCountResponse + +_BARE_LOGFMT_VALUE: Final = re.compile(r"[\w.:/@+-]+", re.ASCII) +_JSON_ESCAPED_BRACES: Final = str.maketrans({"{": "\\u007b", "}": "\\u007d"}) + + +def _logfmt_value(value: str | None) -> str: + if value is None: + return "None" + if _BARE_LOGFMT_VALUE.fullmatch(value): + return value + return json.dumps(value).translate(_JSON_ESCAPED_BRACES) + + +_Counted: Final = TypeVar("_Counted") +_Rejection: Final = TypeVar("_Rejection") +_ProviderCount: Final = TypeVar("_ProviderCount", bound=Mapping[str, object]) + + +@dataclass(frozen=True, slots=True) +class _CountFields: + model_used: str | None + input_tokens: int | None + count_source: TokenCountSource | None + + +_FAILED_COUNT: Final = _CountFields(model_used=None, input_tokens=None, count_source=None) + + +@dataclass(frozen=True, slots=True) +class _CountRequest: + litellm_call_id: str + request_model: str | None + model_id: str | None + + +def deployment_model_id(deployment: Mapping[str, object] | None) -> str | None: + match deployment: + case {"model_info": {"id": str() as model_id}}: + return model_id + case _: + return None + + +def _log_token_count(request: _CountRequest, fields: _CountFields, status_code: int) -> None: + verbose_proxy_logger.info( + "token count - litellm_call_id=%s request_model=%s model_id=%s model_used=%s input_tokens=%s " + "count_source=%s status_code=%s", + _logfmt_value(request.litellm_call_id), + _logfmt_value(request.request_model), + _logfmt_value(request.model_id), + _logfmt_value(fields.model_used), + fields.input_tokens, + fields.count_source, + status_code, + extra=MappingProxyType( + { + "litellm_call_id": request.litellm_call_id, + "request_model": request.request_model, + "model_id": request.model_id, + "model_used": fields.model_used, + "input_tokens": fields.input_tokens, + "count_source": fields.count_source, + "status_code": status_code, + } + ), + ) + + +def rejected_token_count(rejection: _Rejection, litellm_call_id: str, request_model: str | None) -> _Rejection: + _log_token_count( + _CountRequest(litellm_call_id, request_model, model_id=None), + _FAILED_COUNT, + error_status_code(rejection, status.HTTP_500_INTERNAL_SERVER_ERROR), + ) + return rejection + + +async def _logged( + count: Awaitable[_Counted], request: _CountRequest, fields_of: Callable[[_Counted], _CountFields] +) -> _Counted: + try: + counted: Final = await count + except CancelledError: + raise + except BaseException as e: + _log_token_count(request, _FAILED_COUNT, error_status_code(e, status.HTTP_500_INTERNAL_SERVER_ERROR)) + raise + _log_token_count(request, fields_of(counted), status.HTTP_200_OK) + return counted + + +def _token_count_response_fields(counted: TokenCountResponse) -> _CountFields: + return _CountFields( + model_used=counted.model_used, input_tokens=counted.total_tokens, count_source=counted.count_source + ) + + +async def logged_token_count( + count: Awaitable[TokenCountResponse], litellm_call_id: str, request_model: str, model_id: str | None +) -> TokenCountResponse: + return await _logged(count, _CountRequest(litellm_call_id, request_model, model_id), _token_count_response_fields) + + +async def logged_provider_token_count( + count: Awaitable[_ProviderCount], + litellm_call_id: str, + request_model: str, + model_id: str | None, + model_used: Callable[[], str], +) -> _ProviderCount: + def provider_fields(counted: _ProviderCount) -> _CountFields: + input_tokens: Final = counted.get("input_tokens") + return _CountFields( + model_used=model_used(), + input_tokens=input_tokens if isinstance(input_tokens, int) and not isinstance(input_tokens, bool) else None, + count_source="provider", + ) + + return await _logged(count, _CountRequest(litellm_call_id, request_model, model_id), provider_fields) diff --git a/litellm/proxy/common_utils/token_count_settings.py b/litellm/proxy/common_utils/token_count_settings.py index 22b35bd1001..dd04e531f2d 100644 --- a/litellm/proxy/common_utils/token_count_settings.py +++ b/litellm/proxy/common_utils/token_count_settings.py @@ -13,6 +13,7 @@ from litellm.types.token_count import TokenCountProvider, TokenCountSourceFields from litellm.types.utils import TokenCountResponse CANNOT_COUNT_MODEL_STATUSES: Final = frozenset({400, 404}) +REGION_DENIED_STATUSES: Final = frozenset({401, 403}) TOKENIZER_LOAD_WAIT_SECONDS: Final = 5.0 TOKENIZER_LOAD_REUSE_SECONDS: Final = 60.0 TOKENIZER_LOAD_MAX_RUNNING: Final = 4 @@ -47,6 +48,7 @@ class TokenCountModel: model: str region: str | None litellm_provider: TokenCountProvider | None = None + configured: bool = False @dataclass(frozen=True, slots=True) @@ -66,7 +68,13 @@ class ProviderCountFailure: def cannot_count_model(self) -> bool: return not self.rejected_before_provider_call and self.status_code in CANNOT_COUNT_MODEL_STATUSES + @property + def denied_in_region(self) -> bool: + return not self.rejected_before_provider_call and self.status_code in REGION_DENIED_STATUSES + def with_hint(self, hint: str) -> "ProviderCountFailure": + if self.rejected_before_provider_call: + return self return replace(self, message=_with_hint(self.message, hint)) def to_proxy_exception(self) -> ProxyException: @@ -111,7 +119,7 @@ def _count_provider(value: object) -> TokenCountProvider | None: return None -def _count_model(value: Mapping[str, object]) -> TokenCountModel | None: +def _count_model(value: Mapping[str, object], configured: bool) -> TokenCountModel | None: model: Final = _non_blank(value.get("model")) return ( None @@ -120,6 +128,7 @@ def _count_model(value: Mapping[str, object]) -> TokenCountModel | None: model=model, region=_non_blank(value.get("region")), litellm_provider=_count_provider(value.get("litellm_provider")), + configured=configured, ) ) @@ -146,12 +155,12 @@ def _resolved_count_model( ) -> TokenCountModel | None: configured_mapping: Final = as_str_mapping(configured) if configured_mapping is not None: - return _count_model(configured_mapping) + return _count_model(configured_mapping, configured=True) default_mapping: Final = as_str_mapping(default) return ( None if default_mapping is None - else _within_deployment_geography(_count_model(default_mapping), deployment_region) + else _within_deployment_geography(_count_model(default_mapping, configured=False), deployment_region) ) diff --git a/litellm/proxy/credential_endpoints/endpoints.py b/litellm/proxy/credential_endpoints/endpoints.py index d20b5602186..57c7a753d71 100644 --- a/litellm/proxy/credential_endpoints/endpoints.py +++ b/litellm/proxy/credential_endpoints/endpoints.py @@ -5,6 +5,7 @@ CRUD endpoints for storing reusable credentials. import time import unicodedata from collections.abc import Mapping +from types import MappingProxyType from typing import ( Annotated, Final, @@ -23,7 +24,7 @@ from litellm.constants import ( GITHUB_COPILOT_PER_USER_AUTH_TYPE, ) from litellm.litellm_core_utils.credential_accessor import CredentialAccessor -from litellm.litellm_core_utils.litellm_logging import get_masked_values +from litellm.litellm_core_utils.litellm_logging import get_masked_values, has_sensitive_keyword from litellm.llms.anthropic.wif import ( ExportedJwks, NotAnInternalIssuerCredential, @@ -83,6 +84,11 @@ _CREDENTIAL_DICT_ADAPTER: Final = TypeAdapter(dict[str, object]) _GITHUB_COPILOT_PROVIDER: Final = "github_copilot" _DISPLAY_NAME_MAX_LENGTH: Final = 255 _DISPLAY_NAME_FORBIDDEN_CATEGORIES: Final = frozenset({"Cc", "Cf", "Cs", "Zl", "Zp"}) +_MASK_UNMASKED_LENGTH: Final = 4 +_MASK_ASTERISKS: Final = 4 +_SHORT_SECRET_MASK: Final = "*****" +_MASKED_READ_BACK_DEPTH: Final = 20 +_NO_FIELDS: Final[Mapping[str, object]] = MappingProxyType({}) def _normalized_github_copilot_values( @@ -395,7 +401,14 @@ async def get_credentials( """ try: masked_credentials: Final = [ - _credential_view(credential, get_masked_values(credential.credential_values)) + _credential_view( + credential, + get_masked_values( + credential.credential_values, + unmasked_length=_MASK_UNMASKED_LENGTH, + number_of_asterisks=_MASK_ASTERISKS, + ), + ) for credential in litellm.credential_list ] return {"success": True, "credentials": masked_credentials} @@ -423,7 +436,11 @@ async def get_credential_by_name( if credential.credential_name == credential_name: return _credential_view( credential, - get_masked_values(credential.credential_values, unmasked_length=4, number_of_asterisks=4), + get_masked_values( + credential.credential_values, + unmasked_length=_MASK_UNMASKED_LENGTH, + number_of_asterisks=_MASK_ASTERISKS, + ), ) raise HTTPException( status_code=404, @@ -521,8 +538,8 @@ async def get_credential_by_model( raise HTTPException(status_code=404, detail="Model not found") masked_credential_values: Final = get_masked_values( credential_values, - unmasked_length=4, - number_of_asterisks=4, + unmasked_length=_MASK_UNMASKED_LENGTH, + number_of_asterisks=_MASK_ASTERISKS, ) credential: Final = CredentialItem( credential_name=f"{model.model_name}-credential-{model_id}", @@ -908,6 +925,48 @@ def update_db_credential( return merged_credential +def _is_masked_read_back(value: object) -> bool: + if not isinstance(value, str): + return False + if value == _SHORT_SECRET_MASK: + return True + shown: Final = _MASK_UNMASKED_LENGTH // 2 + return len(value) == _MASK_UNMASKED_LENGTH + _MASK_ASTERISKS and value[shown:-shown] == "*" * _MASK_ASTERISKS + + +def _as_fields(value: object) -> Mapping[str, object] | None: + try: + return _CREDENTIAL_DICT_ADAPTER.validate_python(value, strict=True) + except ValidationError: + return None + + +def _kept_value(key: str, value: object, stored: Mapping[str, object], depth: int) -> tuple[str, object] | None: + if not has_sensitive_keyword(key): + return key, value + fields: Final = _as_fields(value) + if fields is not None and depth < _MASKED_READ_BACK_DEPTH: + return key, _without_masked_read_backs(fields, _as_fields(stored.get(key)) or _NO_FIELDS, depth + 1) + if not _is_masked_read_back(value): + return key, value + if key in stored: + return key, stored[key] + return None + + +def _without_masked_read_backs( + requested: Mapping[str, object], stored: Mapping[str, object], depth: int = 0 +) -> Mapping[str, object]: + kept: Final = (_kept_value(key, value, stored, depth) for key, value in requested.items()) + return _CREDENTIAL_DICT_ADAPTER.validate_python( + MappingProxyType(dict(entry for entry in kept if entry is not None)) + ) + + +def _stored_objects(stored_values: Mapping[str, object]) -> Mapping[str, object]: + return MappingProxyType({key: value for key, value in stored_values.items() if _as_fields(value) is not None}) + + @router.patch( "/credentials/{credential_name:path}", dependencies=[Depends(user_api_key_auth)], @@ -936,12 +995,12 @@ async def update_credential( ) requested_display_name: Final = _normalized_display_name(credential.display_name) _reject_overlapping_credential_values(credential) - incoming_values: Final = _CREDENTIAL_DICT_ADAPTER.validate_python( + requested_values: Final = _CREDENTIAL_DICT_ADAPTER.validate_python( _resolve_deployment_credentials(llm_router, credential.model_id) if credential.model_id else credential.credential_values or {} ) - _reject_non_admin_wif_fields(_incoming_wif_fields(incoming_values, credential), user_api_key_dict) + _reject_non_admin_wif_fields(_incoming_wif_fields(requested_values, credential), user_api_key_dict) if prisma_client is None: raise HTTPException( status_code=500, @@ -952,19 +1011,20 @@ async def update_credential( if db_credential is None: raise _not_found_unless_config_defined(credential_name, "Credential not found in DB.") _reject_non_admin_wif_fields(_stored_wif_fields(db_credential), user_api_key_dict) + decrypted_stored_credential: Final = decrypted_credential(db_credential) + decrypted_values: Final = _CREDENTIAL_DICT_ADAPTER.validate_python( + decrypted_stored_credential.credential_values + ) + incoming_values: Final = _without_masked_read_backs(requested_values, _stored_objects(decrypted_values)) patch: Final = CredentialItem( credential_name=credential_name, display_name=( requested_display_name if "display_name" in credential.model_fields_set else db_credential.display_name ), credential_info=_CREDENTIAL_DICT_ADAPTER.validate_python(credential.credential_info), - credential_values=incoming_values, + credential_values=_CREDENTIAL_DICT_ADAPTER.validate_python(incoming_values), credential_values_to_delete=credential.credential_values_to_delete, ) - decrypted_stored_credential: Final = decrypted_credential(db_credential) - decrypted_values: Final = _CREDENTIAL_DICT_ADAPTER.validate_python( - decrypted_stored_credential.credential_values - ) stored_info: Final = _CREDENTIAL_DICT_ADAPTER.validate_python( db_credential.credential_info # pyright: ignore[reportUnknownMemberType] # untyped credential field ) diff --git a/litellm/proxy/db/accounting_ledger.py b/litellm/proxy/db/accounting_ledger.py new file mode 100644 index 00000000000..91f8307283e --- /dev/null +++ b/litellm/proxy/db/accounting_ledger.py @@ -0,0 +1,269 @@ +from __future__ import annotations + +import hashlib +import json +from collections.abc import AsyncGenerator, Callable +from contextlib import AbstractAsyncContextManager, asynccontextmanager +from dataclasses import dataclass +from datetime import datetime, timedelta, timezone +from typing import TYPE_CHECKING, Final, Literal, TypeAlias + +from pydantic import AwareDatetime, ConfigDict, JsonValue, TypeAdapter +from typing_extensions import assert_never + +from litellm.accounting import CostEvent, DeliveryTarget, EventKind, InboundUsageEvent, OutboundUsageEvent +from litellm.proxy.db.db_span import db_span +from litellm.proxy.db.routing_prisma_wrapper import writer_wrapper + +if TYPE_CHECKING: + from prisma import Prisma + + from litellm.proxy.utils import PrismaClient + +AccountingEvent: TypeAlias = InboundUsageEvent | OutboundUsageEvent | CostEvent +_JSON: Final = TypeAdapter(dict[str, JsonValue]) +_INSTANT: Final[TypeAdapter[datetime]] = TypeAdapter(AwareDatetime) +_STRINGS: Final = TypeAdapter(tuple[dict[str, str], ...]) +_TIMEOUT: Final = timedelta(seconds=10) + + +class AccountingConflictError(ValueError): + pass + + +_Transaction: TypeAlias = AbstractAsyncContextManager["Prisma"] + + +@dataclass(frozen=True, slots=True) +class _AcceptedEvent: + event_id: str + kind: EventKind + source_event_id: str | None + occurred_at: datetime + payload: str + payload_hash: str + targets: tuple[str, ...] + schema_version: int + version: int + + +def _json(value: object) -> str: + return json.dumps(value, sort_keys=True, separators=(",", ":"), allow_nan=False) + + +def _prepare( + event: AccountingEvent, + targets: tuple[DeliveryTarget, ...], + envelope: str, + schema_version: int, + version: int, +) -> _AcceptedEvent: + if type(schema_version) is not int or type(version) is not int or min(schema_version, version) < 1: + raise ValueError("Accounting versions must be positive integers") + validated: Final = type(event).model_validate_json(event.model_dump_json()) + payload: Final = _JSON.validate_json(envelope) + if payload.get("event") != validated.model_dump(mode="json"): + raise ValueError("Accounting envelope must contain the matching public event") + destinations: Final = tuple(sorted(frozenset(DeliveryTarget(target).value for target in targets))) + serialized: Final = _json(payload) + identity: Final = _json((schema_version, version, destinations, payload)) + kind: Final = ( + EventKind.COST + if isinstance(validated, CostEvent) + else EventKind.INBOUND_USAGE + if isinstance(validated, InboundUsageEvent) + else EventKind.OUTBOUND_USAGE + ) + return _AcceptedEvent( + event_id=validated.event_id, + kind=kind, + source_event_id=validated.usage_event_id if isinstance(validated, CostEvent) else None, + occurred_at=validated.occurred_at if isinstance(validated, CostEvent) else validated.ended_at, + payload=serialized, + payload_hash=hashlib.sha256(identity.encode()).hexdigest(), + targets=destinations, + schema_version=schema_version, + version=version, + ) + + +_INSERT_EVENT: Final = """ +INSERT INTO "LiteLLM_AccountingEvent" + (event_id, kind, source_event_id, schema_version, payload_hash, occurred_at, payload) +VALUES ($1, $2::"AccountingEventKind", $3, $4::int, $5, $6::timestamp, $7::jsonb) +ON CONFLICT (event_id) DO NOTHING RETURNING event_id +""" +_INSERT_DELIVERIES: Final = """ +INSERT INTO "LiteLLM_AccountingDelivery" (event_id, target, version) +SELECT $1, value::"AccountingDeliveryTarget", $3::int FROM jsonb_array_elements_text($2::jsonb) +""" +_LOCK_SOURCE: Final = """ +SELECT event_id FROM "LiteLLM_AccountingEvent" +WHERE event_id = $1 AND kind = 'outbound_usage' FOR UPDATE +""" +_EXISTING_COST: Final = """ +SELECT event_id FROM "LiteLLM_AccountingEvent" WHERE kind = 'cost' AND source_event_id = $1 +""" +_LOCK_EVENT: Final = """ +SELECT payload_hash FROM "LiteLLM_AccountingEvent" WHERE event_id = $1 FOR UPDATE +""" +_COMPLETED_FAMILY: Final = """ +root.source_event_id IS NULL AND root.kind IN ('inbound_usage', 'outbound_usage') +AND root.recorded_at < $1::timestamp +AND (root.kind = 'inbound_usage' OR EXISTS ( + SELECT 1 FROM "LiteLLM_AccountingEvent" AS cost WHERE cost.source_event_id = root.event_id AND cost.kind = 'cost' +)) +AND NOT EXISTS ( + SELECT 1 FROM "LiteLLM_AccountingEvent" AS member + WHERE (member.event_id = root.event_id OR (member.kind = 'cost' AND member.source_event_id = root.event_id)) + AND (member.recorded_at >= $1::timestamp + OR EXISTS (SELECT 1 FROM "LiteLLM_AccountingDelivery" AS delivery + WHERE delivery.event_id = member.event_id AND delivery.state != 'applied')) +) +""" +_RETENTION_CANDIDATES: Final = ( + 'SELECT root.event_id FROM "LiteLLM_AccountingEvent" AS root WHERE ' + + _COMPLETED_FAMILY + + " ORDER BY root.recorded_at, root.event_id LIMIT $2::int FOR UPDATE OF root SKIP LOCKED" +) +_ELIGIBLE_GROUP: Final = ( + 'SELECT root.event_id FROM "LiteLLM_AccountingEvent" AS root WHERE root.event_id = $2 AND ' + _COMPLETED_FAMILY +) +_DELETE_DELIVERIES: Final = """ +DELETE FROM "LiteLLM_AccountingDelivery" WHERE event_id IN ( + SELECT event_id FROM "LiteLLM_AccountingEvent" WHERE event_id = $1 OR (kind = 'cost' AND source_event_id = $1) +) +""" +_DELETE_EVENTS: Final = """ +DELETE FROM "LiteLLM_AccountingEvent" WHERE event_id = $1 OR (kind = 'cost' AND source_event_id = $1) +""" + + +_Conflict: TypeAlias = Literal["missing_source", "competing_cost", "identity_conflict"] + + +async def _accept(db: Prisma, record: _AcceptedEvent) -> Literal["inserted", "duplicate"] | _Conflict: + if record.source_event_id is not None: + source: Final = _STRINGS.validate_python(await db.query_raw(_LOCK_SOURCE, record.source_event_id)) + if not source: + return "missing_source" + costs: Final = _STRINGS.validate_python(tuple(await db.query_raw(_EXISTING_COST, record.source_event_id))) + if any(cost["event_id"] != record.event_id for cost in costs): + return "competing_cost" + inserted: Final = _STRINGS.validate_python( + await db.query_raw( + _INSERT_EVENT, + record.event_id, + record.kind.value, + record.source_event_id, + record.schema_version, + record.payload_hash, + record.occurred_at.astimezone(timezone.utc).isoformat(), + record.payload, + ) + ) + if not inserted: + existing: Final = _STRINGS.validate_python(tuple(await db.query_raw(_LOCK_EVENT, record.event_id))) + if not existing or existing[0]["payload_hash"] != record.payload_hash: + return "identity_conflict" + return "duplicate" + await db.execute_raw(_INSERT_DELIVERIES, record.event_id, _json(record.targets), record.version) + return "inserted" + + +async def _delete_completed(db: Prisma, event_id: str, cutoff: str) -> int: + if not _STRINGS.validate_python(await db.query_raw(_ELIGIBLE_GROUP, cutoff, event_id)): + return 0 + await db.execute_raw(_DELETE_DELIVERIES, event_id) + return await db.execute_raw(_DELETE_EVENTS, event_id) + + +class AccountingLedger: + def __init__(self, transaction: Callable[[], _Transaction]) -> None: + self._transaction: Final = transaction + + @classmethod + def for_client(cls, client: PrismaClient) -> AccountingLedger: + from prisma.client import TransactionManager + + managers: Final = TypeAdapter(TransactionManager, config=ConfigDict(arbitrary_types_allowed=True)) + + @asynccontextmanager + async def transaction() -> AsyncGenerator[Prisma]: + primary: Final = writer_wrapper(client.db) + manager: Final = managers.validate_python(primary.tx(timeout=_TIMEOUT)) + async with db_span("accounting_ledger", "LiteLLM_AccountingEvent"), manager as db: + await db.execute_raw("SET LOCAL statement_timeout = 5000") + await db.execute_raw("SET LOCAL lock_timeout = 1000") + yield db + + return cls(transaction) + + async def insert_event( + self, + event: AccountingEvent, + targets: tuple[DeliveryTarget, ...], + *, + envelope: str, + schema_version: int = 1, + version: int = 1, + ) -> Literal["inserted", "duplicate"]: + """Accept T5/T6's serialized envelope, containing its public event under `event`. + + The immutable acceptance hash includes the target set and delivery version. + Changing either for an accepted event conflicts. T7 must provide a separate + add-target or new-version workflow that preserves receipts and prevents + duplicate contributions; redelivery cannot silently create or reset work. + + The Prisma adapter opens one interactive transaction per event, including + two SET LOCAL statements and a source-row lock for costs. I/O is async, + but awaiting this method inline adds commit latency per event, potentially + several times per request. T5 owns bounded asynchronous capture and an + explicit batching strategy; looping over this method does not batch commits. + Success acknowledges commit, independently of HTTP response acknowledgement. + """ + record: Final = _prepare(event, targets, envelope, schema_version, version) + async with self._transaction() as db: + result: Final = await _accept(db, record) + match result: + case "inserted" | "duplicate": + return result + case "missing_source": + raise AccountingConflictError("Cost source must be a durably accepted outbound usage event") + case "competing_cost": + raise AccountingConflictError("Usage event already has an authoritative cost") + case "identity_conflict": + raise AccountingConflictError("Event identity conflicts with its accepted content or delivery set") + case _: + assert_never(result) + + async def purge_completed( + self, + *, + redelivery_before: datetime | None = None, + recovery_before: datetime | None = None, + limit: int = 100, + ) -> int: + """Delete at most `limit` completed families once both retention owners permit it. + + T8 must supply a coherent recovery watermark including outstanding holds. + Omitting either watermark disables deletion. Each usage row and its cost + remain together so a retained charge never loses its source or vice versa. + Applied receipts are deleted with the family, ending its retained dedup + protection. The caller must guarantee events recorded before + redelivery_before cannot be redelivered through supported paths. + T8's recovery_before must also protect checkpoints, + outstanding holds and unfinished settlements; age alone is insufficient. + """ + if type(limit) is not int or not 1 <= limit <= 1000: + raise ValueError("Accounting retention batch size must be between 1 and 1000") + if redelivery_before is None or recovery_before is None: + return 0 + cutoff: Final = min( + _INSTANT.validate_python(redelivery_before).astimezone(timezone.utc), + _INSTANT.validate_python(recovery_before).astimezone(timezone.utc), + ).isoformat() + async with self._transaction() as db: + roots: Final = _STRINGS.validate_python(tuple(await db.query_raw(_RETENTION_CANDIDATES, cutoff, limit))) + deleted: Final = tuple([await _delete_completed(db, root["event_id"], cutoff) for root in roots]) + return sum(deleted) diff --git a/litellm/proxy/db/budget_window_spend_writer.py b/litellm/proxy/db/budget_window_spend_writer.py index 82c95cfe998..99b49331932 100644 --- a/litellm/proxy/db/budget_window_spend_writer.py +++ b/litellm/proxy/db/budget_window_spend_writer.py @@ -64,6 +64,16 @@ _ROLL_WINDOW_SPEND_SQL: Final = ( "AND window_start < ($4::timestamptz AT TIME ZONE 'UTC')" ) +_OPEN_WINDOW_SPEND_SQL: Final = ( + 'INSERT INTO "LiteLLM_BudgetWindowSpend" ' + "(entity_type, entity_id, window_duration, window_start, spend, created_at, updated_at) " + "VALUES ($1, $2, $3, ($4::timestamptz AT TIME ZONE 'UTC'), 0, " + "($4::timestamptz AT TIME ZONE 'UTC'), ($4::timestamptz AT TIME ZONE 'UTC')) " + "ON CONFLICT (entity_type, entity_id, window_duration) DO UPDATE SET " + "window_start = EXCLUDED.window_start, spend = 0, updated_at = EXCLUDED.updated_at " + "WHERE \"LiteLLM_BudgetWindowSpend\".window_start <= ($5::timestamptz AT TIME ZONE 'UTC')" +) + _SEED_FROM_SPEND_LOGS_KEY_SQL: Final = ( "SELECT COALESCE(SUM(spend), 0.0) AS total, " "COALESCE(SUM(spend) FILTER (WHERE \"startTime\" < ($3::timestamptz AT TIME ZONE 'UTC')), 0.0) AS before_batch " @@ -389,3 +399,29 @@ async def roll_window_spend_row( to_naive_utc(new_window_start), to_naive_utc(datetime.now(timezone.utc)), ) + + +async def open_window_spend_row( + prisma_client: "PrismaClient", + entity_type: str, + entity_id: str, + window_duration: str, + window_start: datetime, + replaces_window_start: datetime | None, +) -> None: + """Start a window at `window_start` unless another writer already started one. + + The row is created when it does not exist, and moved onto the new window only + while it still holds `replaces_window_start`, the ended window the caller saw. + A writer that lost the race leaves the winner's window in place, so reading + the row back gives every writer the same window start. + """ + async with db_span("open_window_spend_row", "LiteLLM_BudgetWindowSpend"): + await prisma_client.db.execute_raw( + _OPEN_WINDOW_SPEND_SQL, + entity_type, + entity_id, + window_duration, + to_naive_utc(window_start), + None if replaces_window_start is None else to_naive_utc(replaces_window_start), + ) diff --git a/litellm/proxy/db/check_migration.py b/litellm/proxy/db/check_migration.py index 83cc4501466..d126f112f90 100644 --- a/litellm/proxy/db/check_migration.py +++ b/litellm/proxy/db/check_migration.py @@ -4,7 +4,7 @@ import os import subprocess from typing import Final -from litellm._logging import print_startup_message, verbose_logger +from litellm._logging import print_startup_message, print_startup_warning, verbose_logger def extract_sql_commands(diff_output: str) -> list[str]: @@ -63,7 +63,7 @@ def check_prisma_schema_diff_helper(db_url: str) -> tuple[bool, list[str]]: run_prisma, ) except ImportError as e: - print_startup_message( + print_startup_warning( f"Skipping the migration diff: litellm-proxy-extras has no Prisma runner. Error: {e}", ) return False, [] @@ -96,14 +96,14 @@ def check_prisma_schema_diff_helper(db_url: str) -> tuple[bool, list[str]]: else: return False, [] except subprocess.TimeoutExpired: - print_startup_message( + print_startup_warning( f"Timed out after {timeout}s generating the migration diff. " f"Raise {PRISMA_COMMAND_TIMEOUT_ENV_VAR} if this database needs longer.", ) return False, [] except subprocess.CalledProcessError as e: error_message: Final = f"Failed to generate migration diff. Error: {e.stderr}" - print_startup_message(error_message) + print_startup_warning(error_message) return False, [] diff --git a/litellm/proxy/db/db_transaction_queue/spend_log_cleanup.py b/litellm/proxy/db/db_transaction_queue/spend_log_cleanup.py index 7f5efcdaec3..170eb450339 100644 --- a/litellm/proxy/db/db_transaction_queue/spend_log_cleanup.py +++ b/litellm/proxy/db/db_transaction_queue/spend_log_cleanup.py @@ -421,7 +421,10 @@ class SpendLogCleanup: general_settings=None, redis_cache: RedisCache | None = None, partition_manager: SpendLogsPartitionManager | None = None, + *, + clock: Callable[[], float] = time.monotonic, ): + self._clock = clock self.retention_seconds: int | None = None self.partition_manager = partition_manager or SpendLogsPartitionManager() from litellm.proxy.proxy_server import general_settings as default_settings @@ -586,7 +589,7 @@ class SpendLogCleanup: async def _probe_storage(self, prisma_client: PrismaClient, deadline: float) -> StorageProbe | None: """Read what the spend-log tables weigh from the catalog, or None when the probe fails or has no budget.""" - if time.monotonic() >= deadline: + if self._clock() >= deadline: return None timeout_ms: Final = self._timeout_ms(deadline) try: @@ -624,7 +627,7 @@ class SpendLogCleanup: stale.allocated_bytes, _ANALYZE_SQL, ) - if time.monotonic() >= deadline: + if self._clock() >= deadline: return None timeout_ms: Final = self._timeout_ms(deadline) try: @@ -653,7 +656,7 @@ class SpendLogCleanup: async def _load_size_state(self, prisma_client: PrismaClient, deadline: float) -> SizeCleanupState | None: """The reclaimable count saved by the last check, or None on the first check or when it cannot be read.""" - if time.monotonic() >= deadline: + if self._clock() >= deadline: return None timeout_ms: Final = self._timeout_ms(deadline) try: @@ -686,7 +689,7 @@ class SpendLogCleanup: the tool-index rows that expire with their spend logs. When fewer rows than that remain, the step is everything up to now. """ - if time.monotonic() >= deadline: + if self._clock() >= deadline: return None timeout_ms: Final = self._timeout_ms(deadline) async with db_span("size_step_cutoff", "LiteLLM_SpendLogs"), bounded_tx(prisma_client, timeout_ms) as tx: @@ -718,11 +721,11 @@ class SpendLogCleanup: Interpolating this into SQL is safe by construction: an int cannot carry SQL, and SET does not accept a bind parameter. """ - remaining_ms: Final = int((deadline - time.monotonic()) * 1000) + remaining_ms: Final = int((deadline - self._clock()) * 1000) return max(1, min(int(self.batch_timeout_seconds * 1000), remaining_ms)) @staticmethod - def _group_deadline(overall_deadline: float, groups_remaining: int) -> float: + def _group_deadline(overall_deadline: float, groups_remaining: int, now: float) -> float: """ Give each pending cleanup group an equal share of the time left. @@ -731,10 +734,9 @@ class SpendLogCleanup: """ if groups_remaining == 1: return overall_deadline - current_time: Final = time.monotonic() - if current_time >= overall_deadline: + if now >= overall_deadline: return overall_deadline - return current_time + (overall_deadline - current_time) / groups_remaining + return now + (overall_deadline - now) / groups_remaining def _remaining_timeout_ms(self, deadline: float) -> RemainingTimeoutMs: """ @@ -748,7 +750,7 @@ class SpendLogCleanup: """ def remaining() -> int | None: - return None if time.monotonic() >= deadline else self._timeout_ms(deadline) + return None if self._clock() >= deadline else self._timeout_ms(deadline) return remaining @@ -841,7 +843,7 @@ class SpendLogCleanup: run_count = 0 consecutive_failures = 0 while True: - if time.monotonic() >= deadline: + if self._clock() >= deadline: verbose_proxy_logger.info( "Run budget exhausted during %s cleanup after %d rows; the next run resumes from here", table_name, @@ -858,13 +860,13 @@ class SpendLogCleanup: prisma_client, cutoff_date, table_name, time_column, total_deleted, "batch_cap_reached", deadline ) # Find rows and delete them in one go without fetching to application - batch_started_at = time.monotonic() + batch_started_at = self._clock() try: batch_result = await self._execute_delete_batch( prisma_client, delete_sql, cutoff_date, table_name, deadline ) except Exception as batch_exc: - if time.monotonic() >= deadline: + if self._clock() >= deadline: # The statement timeout was clamped to the budget that was # left, so this batch was cancelled by the deadline itself. # That is the bound working, not a database fault, and @@ -920,7 +922,7 @@ class SpendLogCleanup: consecutive_failures = 0 deleted_count = batch_result - SpendLogCleanupMetrics.record_batch(table_name, deleted_count, time.monotonic() - batch_started_at) + SpendLogCleanupMetrics.record_batch(table_name, deleted_count, self._clock() - batch_started_at) verbose_proxy_logger.info("Deleted %s %s rows in this batch", deleted_count, table_name) if deleted_count == 0: @@ -957,7 +959,7 @@ class SpendLogCleanup: operator the backlog was not drained; the gauge simply keeps its value from the last run that finished inside its budget. """ - if time.monotonic() >= deadline: + if self._clock() >= deadline: return TableCleanupResult(table_name=table_name, rows_deleted=rows_deleted, stop_reason=stop_reason) remaining: Final = await self._count_remaining(prisma_client, cutoff_date, table_name, time_column, deadline) if remaining is not None: @@ -1070,7 +1072,7 @@ class SpendLogCleanup: # behind any long-running reader for as long as that reader lives, which # is the one way this job could still outlast its budget without bound. remaining_timeout_ms: Final = self._remaining_timeout_ms(deadline) - if time.monotonic() >= deadline: + if self._clock() >= deadline: verbose_proxy_logger.info("Run budget already spent, skipping partition maintenance this run") elif self.general_settings.get( "use_spend_logs_partitioning", False @@ -1082,7 +1084,7 @@ class SpendLogCleanup: verbose_proxy_logger.info("Dropped %d expired spend-log partitions: %s", len(dropped), dropped) logs_result: Final = await self._delete_old_logs( - prisma_client, cutoff_date, self._group_deadline(deadline, groups_remaining=2) + prisma_client, cutoff_date, self._group_deadline(deadline, groups_remaining=2, now=self._clock()) ) verbose_proxy_logger.info("Deleted %s logs", logs_result.rows_deleted) @@ -1210,7 +1212,7 @@ class SpendLogCleanup: self, prisma_client: PrismaClient, deadline: float, still_over_target: Callable[[], Awaitable[bool]] ) -> tuple[str, ...]: remaining_timeout_ms: Final = self._remaining_timeout_ms(deadline) - if time.monotonic() >= deadline or not self._setting("use_spend_logs_partitioning"): + if self._clock() >= deadline or not self._setting("use_spend_logs_partitioning"): return () if not await self.partition_manager.is_partitioned(prisma_client, remaining_timeout_ms): return () @@ -1257,7 +1259,7 @@ class SpendLogCleanup: needed: Final = rows_still_needed(state.logs_deleted + state.index_deleted) if needed <= 0: return state.stopped("target_reached") - if time.monotonic() >= deadline: + if self._clock() >= deadline: return state.stopped("budget_exhausted") if state.batches_left <= 0: return state.stopped("batch_cap_reached") @@ -1318,11 +1320,11 @@ class SpendLogCleanup: except Exception: # noqa: BLE001 # retained observations are retried by the next cleanup job verbose_proxy_logger.warning("Auto-router baseline retention remains pending") sessions_result: Final = await self._delete_old_autorouter_session_rows( - prisma_client, session_cutoff, self._group_deadline(deadline, 3) + prisma_client, session_cutoff, self._group_deadline(deadline, 3, self._clock()) ) verbose_proxy_logger.info("Deleted %s expired auto-router session rollup rows", sessions_result.rows_deleted) user_sessions_result: Final = await self._delete_old_autorouter_user_session_rows( - prisma_client, session_cutoff, self._group_deadline(deadline, 2) + prisma_client, session_cutoff, self._group_deadline(deadline, 2, self._clock()) ) verbose_proxy_logger.info( "Deleted %s expired auto-router user session rollup rows", user_sessions_result.rows_deleted @@ -1443,7 +1445,7 @@ class SpendLogCleanup: async def _run_passes(self, prisma_client: PrismaClient, age_rules: bool, size_rule: bool) -> None: lock_acquired = False - run_started_at: Final = time.monotonic() + run_started_at: Final = self._clock() progress: Final = _RunProgress() progress_token: Final = _run_progress.set(progress) try: @@ -1493,7 +1495,7 @@ class SpendLogCleanup: SpendLogCleanupMetrics.record_run("skipped_locked") return - deadline: Final = time.monotonic() + self.run_budget_seconds + deadline: Final = self._clock() + self.run_budget_seconds size_group: Final = int(active_size_rule is not None) configured_group_count: Final = ( int(delete_spend_logs and self.retention_seconds is not None) @@ -1506,7 +1508,7 @@ class SpendLogCleanup: spend_log_results: Final = ( await self._clean_spend_log_tables( prisma_client, - self._group_deadline(deadline, configured_group_count), + self._group_deadline(deadline, configured_group_count, self._clock()), ) if delete_spend_logs and self.retention_seconds is not None else () @@ -1526,7 +1528,7 @@ class SpendLogCleanup: await self._clean_session_rollup( prisma_client, autorouter_retention_seconds, - self._group_deadline(deadline, remaining_groups_after_spend_logs), + self._group_deadline(deadline, remaining_groups_after_spend_logs, self._clock()), ) if autorouter_retention_seconds is not None else () @@ -1535,7 +1537,7 @@ class SpendLogCleanup: await self._clean_health_checks( prisma_client, health_check_retention_seconds, - self._group_deadline(deadline, remaining_groups_after_sessions), + self._group_deadline(deadline, remaining_groups_after_sessions, self._clock()), ) if health_check_retention_seconds is not None else () @@ -1544,7 +1546,7 @@ class SpendLogCleanup: await self._clean_daily_tag_spend( prisma_client, daily_tag_spend_retention_seconds, - self._group_deadline(deadline, 1 + size_group), + self._group_deadline(deadline, 1 + size_group, self._clock()), ) if daily_tag_spend_retention_seconds is not None else () @@ -1561,12 +1563,12 @@ class SpendLogCleanup: ) outcome: Final = self._run_outcome(results) SpendLogCleanupMetrics.record_run(outcome) - self._log_run_summary(outcome, results, time.monotonic() - run_started_at, size_report) + self._log_run_summary(outcome, results, self._clock() - run_started_at, size_report) except asyncio.CancelledError: verbose_proxy_logger.error( "Spend log cleanup cancelled after %.2fs (rows_deleted=%d, batches=%d); the next run resumes from here", - time.monotonic() - run_started_at, + self._clock() - run_started_at, progress.rows_deleted, progress.batches, ) diff --git a/litellm/proxy/db/exception_handler.py b/litellm/proxy/db/exception_handler.py index 5dfcaa4b2f8..3f7ea334a99 100644 --- a/litellm/proxy/db/exception_handler.py +++ b/litellm/proxy/db/exception_handler.py @@ -36,7 +36,7 @@ _LOCK_TIMEOUT_SQLSTATE: Final = "55P03" _LOCK_TIMEOUT_PHRASE: Final = "canceling statement due to lock timeout" -def _exception_chain(e: BaseException) -> Iterator[BaseException]: +def exception_chain(e: BaseException) -> Iterator[BaseException]: current = e # rebind-ok: advances one link per iteration of the bounded walk for _ in range(_MAX_EXCEPTION_CHAIN_DEPTH): yield current @@ -49,7 +49,7 @@ def _exception_chain(e: BaseException) -> Iterator[BaseException]: def _database_service_unavailable_errors(e: BaseException) -> tuple[Exception, ...]: return tuple( link - for link in _exception_chain(e) + for link in exception_chain(e) if isinstance(link, Exception) and PrismaDBExceptionHandler.is_database_service_unavailable_error(link) ) diff --git a/litellm/proxy/example_config_yaml/custom_callbacks.py b/litellm/proxy/example_config_yaml/custom_callbacks.py index 5ae55060930..d11e27e0718 100644 --- a/litellm/proxy/example_config_yaml/custom_callbacks.py +++ b/litellm/proxy/example_config_yaml/custom_callbacks.py @@ -28,7 +28,7 @@ class MyCustomHandler(CustomLogger): def __init__(self): blue_color_code: Final = "\033[94m" reset_color_code: Final = "\033[0m" - print_verbose(f"{blue_color_code}Initialized LiteLLM custom logger") + print_verbose(f"{blue_color_code}Initialized LiteLLM custom logger{reset_color_code}") try: print_verbose("Logger Initialized with following methods:") methods: Final = [ @@ -40,7 +40,6 @@ class MyCustomHandler(CustomLogger): # Pretty print_verbose the methods for method in methods: print_verbose(f" - {method}") - print_verbose(f"{reset_color_code}") except Exception: pass diff --git a/litellm/proxy/google_endpoints/agents_endpoints.py b/litellm/proxy/google_endpoints/agents_endpoints.py index 00b23d846c2..7e3c2ddafe0 100644 --- a/litellm/proxy/google_endpoints/agents_endpoints.py +++ b/litellm/proxy/google_endpoints/agents_endpoints.py @@ -160,9 +160,10 @@ async def create_gemini_agent( -H "Authorization: Bearer sk-..." \\ -H "Content-Type: application/json" \\ -d '{ - "name": "my-custom-slides-agent", - "base_agent": "waverunner", - "instructions": "You are a helpful assistant that creates slides.", + "id": "my-custom-slides-agent", + "base_agent": "antigravity-preview-09-2026", + "system_instruction": "You are a helpful assistant that creates slides.", + "agent_config": {"type": "antigravity", "model": "gemini-3.8-flash"}, "base_environment": { "type": "remote", "sources": [ diff --git a/litellm/proxy/google_endpoints/endpoints.py b/litellm/proxy/google_endpoints/endpoints.py index 3d1a9ab4cfe..c018f071b3c 100644 --- a/litellm/proxy/google_endpoints/endpoints.py +++ b/litellm/proxy/google_endpoints/endpoints.py @@ -1,11 +1,11 @@ from collections.abc import Mapping from itertools import chain from types import MappingProxyType -from typing import Final +from typing import Annotated, Final from fastapi import APIRouter, Depends, HTTPException, Request, Response from fastapi.responses import JSONResponse, ORJSONResponse -from pydantic import BaseModel, ConfigDict, Field, JsonValue, TypeAdapter, ValidationError +from pydantic import BaseModel, BeforeValidator, ConfigDict, Field, JsonValue, TypeAdapter, ValidationError from litellm.litellm_core_utils.json_validation_rule import normalize_json_schema_types from litellm.proxy._types import * @@ -21,18 +21,73 @@ from litellm.proxy.common_utils.http_parsing_utils import ( # noqa: F401 # leg _read_request_body, # pyright: ignore[reportPrivateUsage,reportUnusedImport] # backwards-compatible package export read_request_body, ) +from litellm.proxy.common_utils.openai_error_payload import LITELLM_CALL_ID_HEADER +from litellm.proxy.common_utils.token_count_log import rejected_token_count from litellm.proxy.common_utils.token_count_settings import count_source_fields from litellm.types.llms.vertex_ai import TokenCountDetailsResponse +def _google_repeated_field(value: JsonValue) -> JsonValue: + match value: + case None: + return [] + case dict(): + return [value] + case list(): + return [item for item in value if item is not None] + case _: + return value + + +def _google_content(value: JsonValue) -> JsonValue: + match value: + case {"parts": parts}: + return {**value, "parts": _google_repeated_field(parts)} + case _: + return value + + +def _google_contents(value: JsonValue) -> JsonValue: + match _google_repeated_field(value): + case list() as contents: + return [_google_content(content) for content in contents] + case other: + return other + + +_GOOGLE_PART_TEXT_AND_METADATA_FIELDS: Final = frozenset( + {"text", "thought", "thoughtSignature", "thought_signature", "partMetadata", "part_metadata"} +) + + +def _google_part_has_non_text_content(part: Mapping[str, JsonValue]) -> bool: + return any(field is not None for key, field in part.items() if key not in _GOOGLE_PART_TEXT_AND_METADATA_FIELDS) + + +def _google_system_part(value: JsonValue) -> JsonValue: + match value: + case dict() if value.get("text") is None and _google_part_has_non_text_content(value): + return {key: field for key, field in value.items() if key != "text"} + case dict(): + return {"text": None, **value} + case _: + return value + + +_GOOGLE_REPEATED_FIELD: Final = BeforeValidator(_google_repeated_field) + + class _GoogleCountTokensTextPart(BaseModel): model_config = ConfigDict(frozen=True) - text: str + text: str | None class _GoogleCountTokensSystemInstruction(BaseModel): model_config = ConfigDict(frozen=True) - parts: tuple[_GoogleCountTokensTextPart, ...] + parts: Annotated[ + tuple[Annotated[_GoogleCountTokensTextPart, BeforeValidator(_google_system_part)], ...], + _GOOGLE_REPEATED_FIELD, + ] = () class _GoogleCountTokensFunctionDeclaration(BaseModel): @@ -45,16 +100,16 @@ class _GoogleCountTokensFunctionDeclaration(BaseModel): class _GoogleCountTokensTool(BaseModel): model_config = ConfigDict(frozen=True, populate_by_name=True) - function_declarations: tuple[_GoogleCountTokensFunctionDeclaration, ...] = Field( + function_declarations: Annotated[tuple[_GoogleCountTokensFunctionDeclaration, ...], _GOOGLE_REPEATED_FIELD] = Field( default=(), alias="functionDeclarations" ) class _GoogleCountTokensRequest(BaseModel): model_config = ConfigDict(frozen=True, extra="ignore", populate_by_name=True) - contents: tuple[Mapping[str, JsonValue], ...] = () + contents: Annotated[tuple[Mapping[str, JsonValue], ...], BeforeValidator(_google_contents)] = () system_instruction: _GoogleCountTokensSystemInstruction | None = Field(default=None, alias="systemInstruction") - tools: tuple[_GoogleCountTokensTool, ...] = () + tools: Annotated[tuple[_GoogleCountTokensTool, ...], _GOOGLE_REPEATED_FIELD] = () router: Final = APIRouter( @@ -110,7 +165,11 @@ def _google_count_tokens_request(model_name: str, data: object) -> TokenCountReq GoogleGenAIAdapter().translate_generate_content_to_completion(model_name, contents).get("messages", []) ) system: Final = ( - [{"type": "text", "text": part.text} for part in validated_data.system_instruction.parts] + [ + {"type": "text", "text": part.text} + for part in validated_data.system_instruction.parts + if part.text is not None + ] if validated_data.system_instruction is not None else None ) @@ -286,25 +345,35 @@ async def google_count_tokens(request: Request, model_name: str): from litellm.proxy.common_utils.http_parsing_utils import read_request_body from litellm.proxy.proxy_server import token_counter as internal_token_counter + litellm_call_id: Final = resolve_litellm_call_id(request.headers.get(LITELLM_CALL_ID_HEADER)) data: Final = await read_request_body(request=request) try: token_request: Final = _google_count_tokens_request(model_name, data) except ValidationError: - return _google_error_response( - request, - ProxyException( - message="Invalid Google countTokens request body", type="invalid_request_error", param=None, code=400 + return rejected_token_count( + _google_error_response( + request, + ProxyException( + message="Invalid Google countTokens request body", + type="invalid_request_error", + param=None, + code=400, + ), ), + litellm_call_id, + model_name, ) try: - token_response: Final = await internal_token_counter(request=token_request, call_endpoint=True) + token_response: Final = await internal_token_counter( + request=token_request, call_endpoint=True, litellm_call_id=litellm_call_id + ) except ProxyException as error: return _google_error_response(request, error) except HTTPException as error: return _google_error_response(request, proxy_exception_from_http_exception(error, {})) except Exception as error: - log_llm_api_exception(error, resolve_litellm_call_id(request.headers.get("x-litellm-call-id"))) + log_llm_api_exception(error, litellm_call_id) return _google_error_response( request, ProxyException(message="Internal server error", type="internal_server_error", param=None, code=500), diff --git a/litellm/proxy/guardrails/_content_utils.py b/litellm/proxy/guardrails/_content_utils.py index b4830b7c771..51934c99db6 100644 --- a/litellm/proxy/guardrails/_content_utils.py +++ b/litellm/proxy/guardrails/_content_utils.py @@ -62,6 +62,20 @@ def is_non_conversational_call_type(call_type: str) -> bool: return call_type in NON_CONVERSATIONAL_CALL_TYPES +_PASSTHROUGH_EMBEDDINGS_ENDPOINT: Final = re.compile(r"/?(?:[\w-]+/)*embeddings/?") + + +def is_non_conversational_request(call_type: str, data: Mapping[str, object]) -> bool: + if is_non_conversational_call_type(call_type): + return True + endpoint: Final = data.get("endpoint") + return ( + call_type == "allm_passthrough_route" + and isinstance(endpoint, str) + and _PASSTHROUGH_EMBEDDINGS_ENDPOINT.fullmatch(endpoint) is not None + ) + + TEXT_PART_TYPES: Final[frozenset[str]] = frozenset( {"text", "input_text", "output_text", "summary_text", "reasoning_text"} ) @@ -305,6 +319,11 @@ def iter_message_text(data: Mapping[str, object]) -> Iterator[str]: yield from _iter_text_parts_in_content(message.get("content")) +def _is_tool_message(message: object) -> bool: + fields: Final = _text_object(message) + return fields is not None and str(fields.get("role") or "").lower() == "tool" + + def _call_item(item: object) -> tuple[str, object] | None: """Return ``(field, value)`` for a Responses tool-call input item, else None.""" fields: Final = _text_object(item) @@ -316,11 +335,14 @@ def walk_user_text( data: dict[str, object], visit: Callable[[str], str], visit_tool: Callable[[JsonValue], JsonValue] | None = None, + *, + skip_tool_message: bool = False, ) -> int: """Rewrite every text fragment in place via ``visit``. Mutates ``data["messages"]`` and ``data["input"]`` (including tool payloads), ``data["system"]`` and - ``data["instructions"]``. Returns the number + ``data["instructions"]``. ``skip_tool_message`` leaves ``role: tool`` messages and ``tool_result`` + blocks as sent. Returns the number of fragments visited so callers can short-circuit when nothing was inspected. """ @@ -353,6 +375,8 @@ def walk_user_text( def _rewrite_part(part: Mapping[str, object], native: bool) -> Mapping[str, object]: nonlocal visited + if skip_tool_message and part.get("type") == "tool_result": + return part text: Final = _part_text(part) rewritten: Final = {**part, **({"text": visit(text)} if text is not None else {})} if text is not None: @@ -384,18 +408,17 @@ def walk_user_text( return content messages: Final = data.get("messages") - if isinstance(messages, list): - for message in messages: - if not isinstance(message, dict): - continue - if "content" in message: - message["content"] = _rewrite_content(message["content"]) - calls = message.get("tool_calls") - if isinstance(calls, list): - for call in calls: - function = call.get("function") if isinstance(call, dict) else None - if isinstance(function, dict) and "arguments" in function: - function["arguments"] = _rewrite_arguments(function["arguments"]) + for message in _object_list(messages) or (): + if (skip_tool_message and _is_tool_message(message)) or not isinstance(message, dict): + continue + if "content" in message: + message["content"] = _rewrite_content(message["content"]) + calls = message.get("tool_calls") + if isinstance(calls, list): + for call in calls: + function = call.get("function") if isinstance(call, dict) else None + if isinstance(function, dict) and "arguments" in function: + function["arguments"] = _rewrite_arguments(function["arguments"]) if "system" in data: data["system"] = _rewrite_content(data["system"]) # rebind-ok: preserve the native hook's in-place contract diff --git a/litellm/proxy/guardrails/auto_router_compression.py b/litellm/proxy/guardrails/auto_router_compression.py index 1267fb15db8..3071bcbb1dc 100644 --- a/litellm/proxy/guardrails/auto_router_compression.py +++ b/litellm/proxy/guardrails/auto_router_compression.py @@ -14,7 +14,7 @@ from typing import TYPE_CHECKING, Final from litellm._logging import verbose_proxy_logger from litellm.litellm_core_utils.core_helpers import get_or_create_metadata_bucket -from litellm.router_utils.auto_router_model_naming import AUTO_ROUTER_MODEL_PREFIX +from litellm.router_strategy.auto_router.auto_router_model_naming import AUTO_ROUTER_MODEL_PREFIX from litellm.types.utils import GenericGuardrailAPIInputs if TYPE_CHECKING: diff --git a/litellm/proxy/guardrails/guardrail_hooks/bedrock_guardrails.py b/litellm/proxy/guardrails/guardrail_hooks/bedrock_guardrails.py index adda465ad95..9fa37e1827e 100644 --- a/litellm/proxy/guardrails/guardrail_hooks/bedrock_guardrails.py +++ b/litellm/proxy/guardrails/guardrail_hooks/bedrock_guardrails.py @@ -49,6 +49,7 @@ from litellm.llms.base_llm.guardrail_translation.utils import ( from litellm.llms.bedrock.base_aws_llm import BaseAWSLLM, bedrock_bearer_token, run_aws_signing from litellm.llms.bedrock.guardrail_attachments import find_request_attachments from litellm.llms.custom_httpx.http_handler import ( + AsyncHTTPHandler, get_async_httpx_client, httpxSpecialProvider, ) @@ -286,9 +287,12 @@ class BedrockGuardrail(CustomGuardrail, BaseAWSLLM): streaming_sampling_rate: int | None = None, streaming_end_of_stream_only: bool | None = None, streaming_buffer_release_on_scan: bool | None = None, + async_handler: AsyncHTTPHandler | None = None, **kwargs, ): - self.async_handler = get_async_httpx_client(llm_provider=httpxSpecialProvider.GuardrailCallback) + self.async_handler = async_handler or get_async_httpx_client( + llm_provider=httpxSpecialProvider.GuardrailCallback + ) self._set_streaming_params( BedrockGuardrailStreamingParams.from_extras( MappingProxyType( diff --git a/litellm/proxy/guardrails/guardrail_hooks/generic_guardrail_api/example_config.yaml b/litellm/proxy/guardrails/guardrail_hooks/generic_guardrail_api/example_config.yaml index 9b5c4e557f3..665d8cde4cc 100644 --- a/litellm/proxy/guardrails/guardrail_hooks/generic_guardrail_api/example_config.yaml +++ b/litellm/proxy/guardrails/guardrail_hooks/generic_guardrail_api/example_config.yaml @@ -6,20 +6,19 @@ model_list: model: gpt-4 api_key: os.environ/OPENAI_API_KEY -litellm_settings: - guardrails: - - guardrail_name: "my-generic-guardrail" - litellm_params: - guardrail: generic_guardrail_api - mode: pre_call # Options: pre_call, post_call, during_call, [pre_call, post_call] - api_key: os.environ/GENERIC_GUARDRAIL_API_KEY # Optional if using Bearer auth - api_base: http://localhost:8080 # Required. Endpoint /beta/litellm_basic_guardrail_api is automatically appended - unreachable_fallback: fail_closed # Options: fail_closed (default, raise), fail_open (proceed if endpoint unreachable or upstream returns 502/503/504) - default_on: false # Set to true to apply to all requests by default - additional_provider_specific_params: - # Any additional parameters your guardrail API needs - api_version: "v1" - custom_param: "value" +guardrails: + - guardrail_name: "my-generic-guardrail" + litellm_params: + guardrail: generic_guardrail_api + mode: pre_call # Options: pre_call, post_call, during_call, [pre_call, post_call] + api_key: os.environ/GENERIC_GUARDRAIL_API_KEY # Optional if using Bearer auth + api_base: http://localhost:8080 # Required. Endpoint /beta/litellm_basic_guardrail_api is automatically appended + unreachable_fallback: fail_closed # Options: fail_closed (default, raise), fail_open (proceed if endpoint unreachable or upstream returns 502/503/504) + default_on: false # Set to true to apply to all requests by default + additional_provider_specific_params: + # Any additional parameters your guardrail API needs + api_version: "v1" + custom_param: "value" # Usage examples: diff --git a/litellm/proxy/guardrails/guardrail_hooks/openai/moderations.py b/litellm/proxy/guardrails/guardrail_hooks/openai/moderations.py index 98be35079c3..16b3c45f6f8 100644 --- a/litellm/proxy/guardrails/guardrail_hooks/openai/moderations.py +++ b/litellm/proxy/guardrails/guardrail_hooks/openai/moderations.py @@ -169,7 +169,7 @@ class OpenAIModerationGuardrail(OpenAIGuardrailBase, CustomGuardrail): from litellm.types.llms.openai import OpenAIModerationResponse - return OpenAIModerationResponse(**response.json()) + return OpenAIModerationResponse.model_validate(response.json()) def _check_moderation_result(self, moderation_response: "OpenAIModerationResponse") -> None: """ diff --git a/litellm/proxy/guardrails/guardrail_hooks/panw_prisma_airs/panw_prisma_airs.py b/litellm/proxy/guardrails/guardrail_hooks/panw_prisma_airs/panw_prisma_airs.py index d50001ba636..3940a320fb8 100644 --- a/litellm/proxy/guardrails/guardrail_hooks/panw_prisma_airs/panw_prisma_airs.py +++ b/litellm/proxy/guardrails/guardrail_hooks/panw_prisma_airs/panw_prisma_airs.py @@ -30,6 +30,7 @@ from litellm.integrations.custom_guardrail import ( from litellm.llms.base_llm.guardrail_translation.utils import ( effective_scan_only_tool_results_for_guardrail, effective_skip_system_message_for_guardrail, + effective_skip_tool_message_for_guardrail, role_out_of_guardrail_scope, ) from litellm.llms.custom_httpx.http_handler import ( @@ -37,12 +38,16 @@ from litellm.llms.custom_httpx.http_handler import ( get_async_httpx_client, httpxSpecialProvider, ) -from litellm.llms.openai.responses.guardrail_translation.handler import scannable_instructions +from litellm.llms.openai.responses.guardrail_translation.handler import ( + scannable_instructions, + tool_output_texts, +) from litellm.proxy._types import UserAPIKeyAuth from litellm.proxy.common_utils.callback_utils import ( add_guardrail_scan_id, add_guardrail_to_applied_guardrails_header, ) +from litellm.responses.litellm_completion_transformation.transformation import TOOL_CALL_OUTPUT_ITEM_TYPES from litellm.types.guardrails import GuardrailEventHooks from litellm.types.llms.base import LiteLLMBaseModel from litellm.types.llms.openai import AllMessageValues @@ -112,12 +117,16 @@ class _ResponsesInputItem(LiteLLMBaseModel): type: str | None = None role: str | None = None content: str | tuple[_ResponsesContentPart, ...] | None = None + output: object = None + call_id: object = None - def text_count(self, *, skip_system: bool) -> int: - if role_out_of_guardrail_scope( - (self.role or "").lower(), skip_system_message=skip_system, skip_tool_message=False - ): + def text_count(self, *, skip_system: bool, skip_tool: bool) -> int: + is_tool_output: Final = self.type in TOOL_CALL_OUTPUT_ITEM_TYPES + role: Final = "tool" if is_tool_output else (self.role or "").lower() + if role_out_of_guardrail_scope(role, skip_system_message=skip_system, skip_tool_message=skip_tool): return 0 + if is_tool_output: + return len(tool_output_texts(self)) if isinstance(self.content, str): return 1 if self.content is None: @@ -1692,13 +1701,14 @@ class PanwPrismaAirsHandler(CustomGuardrail): request_data: Mapping[str, object], *, skip_system: bool, + skip_tool: bool, ) -> frozenset[int] | None: """Return the ``texts`` indices flattened from Responses ``reasoning`` input items. The Responses translation handler gives those model-authored items the default ``user`` role, so the latest-turn selection must not mistake one for a human turn. Empty for requests without a Responses ``input`` item list; None when the raw items - (after the leading ``instructions`` text, both minus whatever ``skip_system`` drops) + (after the leading ``instructions`` text, both minus whatever ``skip_system`` and ``skip_tool`` drop) do not account for every entry of ``texts``. """ try: @@ -1708,7 +1718,7 @@ class PanwPrismaAirsHandler(CustomGuardrail): if not isinstance(raw_input, tuple): return frozenset() offset: Final = 0 if scannable_instructions(request_data, skip_system=skip_system) is None else 1 - counts: Final = tuple(item.text_count(skip_system=skip_system) for item in raw_input) + counts: Final = tuple(item.text_count(skip_system=skip_system, skip_tool=skip_tool) for item in raw_input) if offset + sum(counts) != len(texts): return None starts: Final = itertools.accumulate(counts, initial=offset) @@ -1738,7 +1748,10 @@ class PanwPrismaAirsHandler(CustomGuardrail): if sources is None: return None reasoning: Final = self._reasoning_item_text_indices( - texts, request_data, skip_system=effective_skip_system_message_for_guardrail(self) + texts, + request_data, + skip_system=effective_skip_system_message_for_guardrail(self), + skip_tool=effective_skip_tool_message_for_guardrail(self), ) if reasoning is None: return None diff --git a/litellm/proxy/health_check.py b/litellm/proxy/health_check.py index 0d2f8dc9a0c..60d2abe0ab4 100644 --- a/litellm/proxy/health_check.py +++ b/litellm/proxy/health_check.py @@ -27,7 +27,7 @@ from litellm.constants import ( HEALTH_CHECK_TIMEOUT_SECONDS, ) from litellm.litellm_core_utils.health_check_helpers import native_health_check_mode -from litellm.router_utils.auto_router_model_naming import ( +from litellm.router_strategy.auto_router.auto_router_model_naming import ( StrategyRouterDependency, classify_strategy_router_model, strategy_router_dependencies, @@ -131,6 +131,52 @@ def _should_inject_health_check_max_tokens(model_info: Mapping[str, object], mod return (mode or "chat") in _MAX_TOKEN_SUPPORT_MODES +_AUDIO_OUTPUT_PROBE_PROVIDERS: Final[frozenset[str]] = frozenset({"openai", "azure"}) + + +def _health_check_requires_audio_output( + model_info: Mapping[str, object], probe_params: Mapping[str, object], mode: str | None, deployment_model: str | None +) -> bool: + if (mode or "chat") != "chat": + return False + operator_modalities: Final = probe_params.get("modalities") + if isinstance(operator_modalities, list) and "audio" not in operator_modalities: + return False + model: Final = probe_params.get("model") + if not isinstance(model, str): + return False + provider_param: Final = probe_params.get("custom_llm_provider") + try: + _, provider, _, _ = litellm.get_llm_provider( + model=model, custom_llm_provider=provider_param if isinstance(provider_param, str) else None + ) + except litellm.exceptions.BadRequestError: + return False + if provider not in _AUDIO_OUTPUT_PROBE_PROVIDERS: + return False + base_model: Final = model_info.get("base_model") or probe_params.get("base_model") + checked_model: Final = base_model if isinstance(base_model, str) and model == deployment_model else model + checked_model_prefix: Final = checked_model.partition("/")[0] + return litellm.supports_audio_output( + model=checked_model, + custom_llm_provider=checked_model_prefix if checked_model_prefix in _AUDIO_OUTPUT_PROBE_PROVIDERS else provider, + ) + + +def _health_check_audio_output_params( + model_info: Mapping[str, object], probe_params: Mapping[str, object], mode: str | None, deployment_model: str | None +) -> Mapping[str, object]: + if not _health_check_requires_audio_output(model_info, probe_params, mode, deployment_model): + return MappingProxyType({}) + voice: Final = model_info.get("health_check_voice") + return MappingProxyType( + { + "modalities": ["text", "audio"], + "audio": {"voice": voice if isinstance(voice, str) else "alloy", "format": "wav"}, + } + ) + + # Health-check modes that forward `reasoning_effort` to the provider (chat-style calls). _HEALTH_CHECK_MODES_SUPPORTING_REASONING_EFFORT: Final = frozenset((None, "chat", "completion")) @@ -782,9 +828,12 @@ def _resolve_health_check_max_tokens(model_info: dict, litellm_params: dict) -> _PROBE_PARAMS_ADAPTER: Final = TypeAdapter(dict[str, object]) +_MODEL_INFO_ADAPTER: Final = TypeAdapter(Mapping[str, object]) -def update_litellm_params_for_health_check(model_info: dict, litellm_params: dict) -> dict: +def update_litellm_params_for_health_check( + model_info: dict, litellm_params: dict, deployment_model: str | None = None +) -> dict: """ Update the litellm params for health check. @@ -800,7 +849,15 @@ def update_litellm_params_for_health_check(model_info: dict, litellm_params: dic - updates the `model` param with the `health_check_model` if it exists Doc: https://docs.litellm.ai/docs/proxy/health#wildcard-routes - updates the `voice` param with the `health_check_voice` for `audio_speech` mode if it exists Doc: https://docs.litellm.ai/docs/proxy/health#text-to-speech-models - for Bedrock models with region routing (bedrock/region/model), strips the litellm routing prefix but preserves the model ID, and pins `custom_llm_provider` to `bedrock` (only when the deployment hasn't already set one, so an explicit `bedrock_converse` survives) so the bare model id still resolves to the provider (e.g. cross-region ids like `us.cohere.embed-v4:0`) + - asks OpenAI and Azure chat models that support audio output for `modalities` text + audio and a wav + `audio` in the `health_check_voice` (default "alloy"), since those models reject text-only requests. + `base_model` (from `model_info`, then `litellm_params`) decides it only while the probe still targets + `deployment_model` (default: the incoming `litellm_params` model), so a `health_check_model` or a `model` + in `health_check_params` is judged on its own. Keys already set through `health_check_params` are kept, + and `modalities` set there without "audio" turns the audio fields off """ + incoming_model: Final = _PROBE_PARAMS_ADAPTER.validate_python(litellm_params).get("model") + base_model_owner: Final = deployment_model or (incoming_model if isinstance(incoming_model, str) else None) mode: Final = resolve_health_check_mode( model_info, litellm_params, # any-ok: untyped router config dict @@ -875,7 +932,14 @@ def update_litellm_params_for_health_check(model_info: dict, litellm_params: dic ) probe_params: Final = _PROBE_PARAMS_ADAPTER.validate_python(litellm_params) - return {key: value for key, value in probe_params.items() if not is_model_capability_field(key)} + audio_output_params: Final = _health_check_audio_output_params( + _MODEL_INFO_ADAPTER.validate_python(model_info), probe_params, mode, base_model_owner + ) + return { + key: value + for key, value in {**audio_output_params, **probe_params}.items() + if not is_model_capability_field(key) + } _update_litellm_params_for_health_check: Final = update_litellm_params_for_health_check diff --git a/litellm/proxy/health_endpoints/_health_endpoints.py b/litellm/proxy/health_endpoints/_health_endpoints.py index 53c54fe15bf..396a00ab1a1 100644 --- a/litellm/proxy/health_endpoints/_health_endpoints.py +++ b/litellm/proxy/health_endpoints/_health_endpoints.py @@ -32,7 +32,6 @@ from litellm.proxy._types import ( EnterpriseLicenseData, Litellm_EntityType, LitellmUserRoles, - ProxyErrorTypes, ProxyException, SpecialModelNames, UserAPIKeyAuth, @@ -47,6 +46,7 @@ from litellm.proxy.auth.auth_utils import ( from litellm.proxy.auth.model_checks import get_key_models from litellm.proxy.auth.user_api_key_auth import user_api_key_auth from litellm.proxy.common_utils import http_parsing_utils +from litellm.proxy.common_utils.openai_error_payload import proxy_exception_for from litellm.proxy.db.db_lookup_gate import db_lookup_stall_tracker from litellm.proxy.db.exception_handler import PrismaDBExceptionHandler from litellm.proxy.db.health_check_latest import ( @@ -683,21 +683,9 @@ async def health_services_endpoint( except Exception as e: verbose_proxy_logger.error("litellm.proxy.proxy_server.health_services_endpoint(): Exception occured - %s", e) verbose_proxy_logger.debug(traceback.format_exc()) - if isinstance(e, HTTPException): - raise ProxyException( - message=getattr(e, "detail", f"Authentication Error({e})"), - type=ProxyErrorTypes.auth_error, - param=getattr(e, "param", "None"), - code=getattr(e, "status_code", status.HTTP_500_INTERNAL_SERVER_ERROR), - ) - elif isinstance(e, ProxyException): - raise e - raise ProxyException( - message="Authentication Error, " + str(e), - type=ProxyErrorTypes.auth_error, - param=getattr(e, "param", "None"), - code=status.HTTP_500_INTERNAL_SERVER_ERROR, - ) + if isinstance(e, ProxyException): + raise + raise proxy_exception_for(e, default_status_code=status.HTTP_500_INTERNAL_SERVER_ERROR) from e def convert_health_check_to_dict(check) -> dict: @@ -2330,9 +2318,11 @@ async def test_model_connection( stored_params=_OBJECT_MAPPING.validate_python(config_litellm_params), request_params=_OBJECT_MAPPING.validate_python(request_litellm_params), ) + stored_model: Final = _OBJECT_MAPPING.validate_python(config_litellm_params).get("model") litellm_params = update_litellm_params_for_health_check( model_info=dict(probe_model_info), litellm_params=litellm_params, + deployment_model=stored_model if isinstance(stored_model, str) else None, ) ## Auth check, on the final probe params so health_check_params cannot retarget it afterwards diff --git a/litellm/proxy/hooks/autorouter_baseline_cache.py b/litellm/proxy/hooks/autorouter_baseline_cache.py index c4232609124..1147ce7ec12 100644 --- a/litellm/proxy/hooks/autorouter_baseline_cache.py +++ b/litellm/proxy/hooks/autorouter_baseline_cache.py @@ -37,8 +37,8 @@ from litellm.proxy.spend_tracking.savings import ( _effective_model_info, # pyright: ignore[reportPrivateUsage] # existing deployment-price owner _proxy_llm_router, # pyright: ignore[reportPrivateUsage] # existing optional proxy-router owner ) +from litellm.router_strategy.auto_router.baseline_request import baseline_request from litellm.router_strategy.complexity_router.context_compaction import compaction_applied -from litellm.router_utils.baseline_request import baseline_request from litellm.types.llms.base import LiteLLMBaseModel from litellm.types.router import BaselineRouteStamp from litellm.types.utils import CallTypes, ModelInfo, Usage diff --git a/litellm/proxy/hooks/model_budget_shared_windows.py b/litellm/proxy/hooks/model_budget_shared_windows.py new file mode 100644 index 00000000000..880dd0eb218 --- /dev/null +++ b/litellm/proxy/hooks/model_budget_shared_windows.py @@ -0,0 +1,176 @@ +from collections.abc import Awaitable, Callable +from dataclasses import dataclass +from datetime import datetime, timezone +from typing import TYPE_CHECKING, Final, Protocol, TypeAlias + +from litellm._logging import verbose_proxy_logger +from litellm.caching.in_memory_cache import InMemoryCache +from litellm.proxy.db.budget_window_spend_writer import open_window_spend_row +from litellm.proxy.db.db_transaction_queue.window_spend_update_queue import ( + WindowSpendTransaction, + build_window_spend_transaction, +) +from litellm.repositories.table_repositories import BudgetWindowSpendRepository +from litellm.router_strategy.budget_limiter import budget_window_seconds + +if TYPE_CHECKING: + from litellm.proxy.utils import PrismaClient + +MODEL_BUDGET_WINDOW_ENTITY_TYPE: Final = "model_max_budget" +_READ_TTL_SECONDS: Final = 5 + + +@dataclass(frozen=True, slots=True) +class SharedWindow: + started_at: float + spend: float + + def is_open(self, budget_duration: str, now: float) -> bool: + return now < self.started_at + budget_window_seconds(self.started_at, budget_duration) + + +class LocalTTLCache(Protocol): + def get_cache(self, key: str) -> object: ... + + def set_cache(self, key: str, value: object, *, ttl: float) -> None: ... + + def delete_cache(self, key: str) -> None: ... + + +class SharedWindows(Protocol): + async def read(self, spend_key: str, budget_duration: str) -> SharedWindow | None: ... + + async def open(self, spend_key: str, budget_duration: str, now: float) -> float | None: ... + + async def add(self, spend_key: str, budget_duration: str, started_at: float, spend: float) -> None: ... + + +PrismaClientSource: TypeAlias = Callable[[], "PrismaClient | None"] +WindowSpendSink: TypeAlias = Callable[[WindowSpendTransaction], Awaitable[None]] + + +def _proxy_prisma_client() -> "PrismaClient | None": + try: + from litellm.proxy.proxy_server import prisma_client + except ImportError: + return None + return prisma_client + + +async def _queue_on_proxy_spend_writer(transaction: WindowSpendTransaction) -> None: + from litellm.proxy.proxy_server import proxy_logging_obj + + await proxy_logging_obj.db_spend_update_writer.window_spend_update_queue.add_update(transaction) + + +@dataclass(frozen=True, slots=True) +class _Reading: + window: SharedWindow | None + + +class DatabaseSharedWindows: + def __init__( + self, + prisma_client_source: PrismaClientSource = _proxy_prisma_client, + sink: WindowSpendSink = _queue_on_proxy_spend_writer, + read_ttl_seconds: int = _READ_TTL_SECONDS, + ) -> None: + self._prisma_client_source = prisma_client_source + self._sink = sink + self._read_ttl_seconds = read_ttl_seconds + self._readings: LocalTTLCache = InMemoryCache(max_size_in_memory=10_000, default_ttl=read_ttl_seconds) + + async def read(self, spend_key: str, budget_duration: str) -> SharedWindow | None: + cached: Final = self._readings.get_cache(key=spend_key) + if isinstance(cached, _Reading): + return cached.window + window: Final = await self._read_row(spend_key=spend_key, budget_duration=budget_duration) + self._readings.set_cache(key=spend_key, value=_Reading(window=window), ttl=self._read_ttl_seconds) + return window + + async def open(self, spend_key: str, budget_duration: str, now: float) -> float | None: + """When the window every replica shares started, opening one at `now` if none is open. + + Without a database every window is this replica's own, so it starts at `now`. None means the database did + not answer, so this replica cannot know which window the others are in yet. + """ + prisma_client: Final = self._prisma_client_source() + if prisma_client is None: + return now + try: + seen: Final = await _fetch_row( + prisma_client=prisma_client, spend_key=spend_key, budget_duration=budget_duration, use_writer=True + ) + if seen is not None and seen.is_open(budget_duration=budget_duration, now=now): + return seen.started_at + await open_window_spend_row( + prisma_client=prisma_client, + entity_type=MODEL_BUDGET_WINDOW_ENTITY_TYPE, + entity_id=spend_key, + window_duration=budget_duration, + window_start=datetime.fromtimestamp(now, tz=timezone.utc), + replaces_window_start=None + if seen is None + else datetime.fromtimestamp(seen.started_at, tz=timezone.utc), + ) + opened: Final = await _fetch_row( + prisma_client=prisma_client, spend_key=spend_key, budget_duration=budget_duration, use_writer=True + ) + except Exception: # noqa: BLE001 # an unreachable database leaves this replica on its own window + verbose_proxy_logger.exception("Unable to open the shared model budget window") + return None + if opened is None or not opened.is_open(budget_duration=budget_duration, now=now): + return None + return opened.started_at + + async def add(self, spend_key: str, budget_duration: str, started_at: float, spend: float) -> None: + if self._prisma_client_source() is None: + return + try: + await self._sink( + build_window_spend_transaction( + entity_type=MODEL_BUDGET_WINDOW_ENTITY_TYPE, + entity_id=spend_key, + window_duration=budget_duration, + window_start=datetime.fromtimestamp(started_at, tz=timezone.utc), + spend=spend, + ) + ) + except Exception: # noqa: BLE001 # spend tracking must never fail the success callback + verbose_proxy_logger.debug("Unable to queue shared model budget spend", exc_info=True) + + async def _read_row(self, spend_key: str, budget_duration: str) -> SharedWindow | None: + prisma_client: Final = self._prisma_client_source() + if prisma_client is None: + return None + try: + return await _fetch_row( + prisma_client=prisma_client, spend_key=spend_key, budget_duration=budget_duration, use_writer=False + ) + except Exception: # noqa: BLE001 # an unreadable row leaves enforcement on this replica's own counter + verbose_proxy_logger.exception("Unable to read shared model budget spend") + return None + + +async def _fetch_row( + prisma_client: "PrismaClient", spend_key: str, budget_duration: str, use_writer: bool +) -> SharedWindow | None: + row: Final = await BudgetWindowSpendRepository(prisma_client, use_writer=use_writer).table.find_unique( + where={ + "entity_type_entity_id_window_duration": { + "entity_type": MODEL_BUDGET_WINDOW_ENTITY_TYPE, + "entity_id": spend_key, + "window_duration": budget_duration, + } + } + ) + if row is None: + return None + window_start: Final = row.window_start + started_at: Final = ( + window_start if window_start.tzinfo is not None else window_start.replace(tzinfo=timezone.utc) + ).timestamp() + return SharedWindow(started_at=started_at, spend=float(row.spend or 0.0)) + + +PROXY_SHARED_WINDOWS: Final = DatabaseSharedWindows() diff --git a/litellm/proxy/hooks/model_max_budget_limiter.py b/litellm/proxy/hooks/model_max_budget_limiter.py index bc9cee1cb1d..1c4a61cfad8 100644 --- a/litellm/proxy/hooks/model_max_budget_limiter.py +++ b/litellm/proxy/hooks/model_max_budget_limiter.py @@ -1,25 +1,41 @@ import asyncio +import functools +import itertools import json import time -from collections.abc import Callable, Iterable, Mapping, Sequence +from collections.abc import Callable, Collection, Iterable, Iterator, Mapping, Sequence from dataclasses import dataclass from datetime import datetime, timezone from types import MappingProxyType -from typing import Final, cast # noqa: TID251 # untyped callback payload requires explicit narrowing +from typing import ( + TYPE_CHECKING, + Final, + TypeAlias, + cast, # noqa: TID251 # untyped callback payload requires explicit narrowing +) import litellm from litellm._internal_context import with_service_target from litellm._logging import verbose_proxy_logger from litellm.caching.caching import DualCache from litellm.integrations.custom_logger import Span +from litellm.litellm_core_utils.batch_utils import batch_charged_once_marker_key, batch_id_to_charge_once from litellm.litellm_core_utils.duration_parser import duration_in_seconds from litellm.litellm_core_utils.litellm_logging import StandardLoggingPayloadSetup -from litellm.llms.bedrock.common_utils import get_bedrock_base_model +from litellm.llms.bedrock.common_utils import get_bedrock_base_model, get_bedrock_cross_region_inference_regions from litellm.proxy._types import Litellm_EntityType, UserAPIKeyAuth +from litellm.proxy.hooks.model_budget_shared_windows import ( + PROXY_SHARED_WINDOWS, + LocalTTLCache, + SharedWindow, + SharedWindows, +) from litellm.router_strategy.budget_limiter import RouterBudgetLimiting, budget_window_seconds -from litellm.router_utils.batch_utils import batch_charged_once_marker_key, batch_id_to_charge_once from litellm.types.llms.openai import AllMessageValues -from litellm.types.utils import BudgetConfig, StandardLoggingPayload +from litellm.types.utils import BudgetConfig, LlmProviders, StandardLoggingPayload + +if TYPE_CHECKING: + from litellm.router import Router VIRTUAL_KEY_SPEND_CACHE_KEY_PREFIX: Final = "virtual_key_spend" END_USER_SPEND_CACHE_KEY_PREFIX: Final = "end_user_model_spend" @@ -39,10 +55,18 @@ _SPEND_CACHE_KEY_PREFIXES: Final = MappingProxyType( _LEGACY_REQUEST_MODEL_SCOPES: Final = frozenset({Litellm_EntityType.KEY, Litellm_EntityType.END_USER}) +_PER_REPLICA_SCOPES: Final = frozenset({Litellm_EntityType.END_USER}) + _PROCESS_STARTED_AT: Final = time.monotonic() _LATEST_RESET_AT: Final = datetime(9999, 12, 31, tzinfo=timezone.utc).timestamp() +_GLOB_WILDCARD: Final = "*" + +ModelAccessGroups: TypeAlias = Callable[[str, str | None], Collection[str]] + +_PROVIDER_PREFIXES: Final = tuple(f"{provider.value}/" for provider in LlmProviders) + _BUDGET_START_TIME_KEY_PREFIXES: Final = MappingProxyType( { Litellm_EntityType.KEY: "virtual_key_budget_start_time", @@ -68,6 +92,15 @@ class ResolvedModelBudget: budget_config: BudgetConfig +@dataclass(frozen=True, slots=True) +class RoutedModels: + served_names: frozenset[str] + group_members: Mapping[str, frozenset[str]] + + def members(self, access_group: str) -> frozenset[str]: + return self.group_members.get(access_group, frozenset()) + + def team_member_budget_entity_id(user_id: str, team_id: str) -> str: return f"{len(user_id)}:{user_id}:{team_id}" @@ -131,43 +164,403 @@ def model_budget_start_time_cache_key( return f"{_BUDGET_START_TIME_KEY_PREFIXES[entity_type]}:{entity_id}:{budget_model}:{budget_duration}" -def resolve_model_budget(model: str, model_max_budget: Mapping[str, object]) -> ResolvedModelBudget | None: - """Find the `model_max_budget` entry that governs `model`, or None.""" - for candidate in _budget_model_candidates(model): - raw_budget_config = model_max_budget.get(candidate) - if raw_budget_config is None: - continue - if (budget_config := _usable_budget_config(raw_budget_config)) is None: - # An entry that will not validate cannot be keyed, so it cannot be - # enforced or incremented. Skip to the next candidate rather than - # raising: raising would abort every other scope's increment and turn - # a config typo into a 500, and stopping here would let one malformed - # specific entry disable a perfectly good bare-family budget beside - # it. The candidate chain already falls through an ABSENT entry, and - # an unparseable one is indistinguishable from absent to enforcement. - # `validate_model_max_budget` rejects these on the write path, so - # reaching here means config.yaml or a direct DB edit. - verbose_proxy_logger.warning( - "Ignoring unusable model_max_budget entry for %s; it cannot be enforced or tracked", - candidate, - ) - continue - return ResolvedModelBudget(budget_model=candidate, budget_config=budget_config) - return None +def model_access_groups_of(router: "Router", model: str, team_id: str | None = None) -> frozenset[str]: + """Access groups serving `model`, or the team's own model of that name, leaving out any named after a model the + router serves. + + An entry with that name already budgets that model, so reading it as the group too would quietly widen it. + """ + return frozenset( + group + for group in router.get_model_access_groups(model_name=model, team_id=team_id) + if group not in router.model_names + ) -def team_model_budget_applies(model: str, key_model_max_budget: Mapping[str, object] | None) -> bool: - """A key entry that spend-gates `model` overrides the team cap: it is then gated on and billed to the key alone.""" +def routed_models_of(router: "Router", team_id: str | None = None) -> RoutedModels: + serves_every_name: Final = ( + router.default_deployment is not None or router.router_general_settings.pass_through_all_models + ) + served_names: Final = frozenset(router.model_names) | ( + frozenset({_GLOB_WILDCARD}) if serves_every_name else frozenset() + ) + team_members: Final = _team_public_names_by_group(router=router, team_id=team_id) + return RoutedModels( + served_names=served_names, + group_members=MappingProxyType( + { + group: frozenset(members) | team_members.get(group, frozenset()) + for group, members in router.get_model_access_groups().items() + if group not in served_names + } + ), + ) + + +def _team_public_names_by_group(router: "Router", team_id: str | None) -> Mapping[str, frozenset[str]]: + if team_id is None: + return MappingProxyType({}) + groups_by_name: Final = MappingProxyType( + { + name: model_access_groups_of(router=router, model=name, team_id=team_id) + for name in router.team_public_model_names_of(team_id) + } + ) + return MappingProxyType( + { + group: frozenset(name for name, groups in groups_by_name.items() if group in groups) + for group in frozenset[str]().union(*groups_by_name.values()) + } + ) + + +def proxy_model_access_groups(model: str, team_id: str | None = None) -> frozenset[str]: + router: Final = _proxy_router() + return frozenset() if router is None else model_access_groups_of(router=router, model=model, team_id=team_id) + + +def proxy_routed_models(team_id: str | None = None) -> RoutedModels: + router: Final = _proxy_router() + if router is None: + return RoutedModels(served_names=frozenset(), group_members=MappingProxyType({})) + return routed_models_of(router=router, team_id=team_id) + + +def _proxy_router() -> "Router | None": + try: + from litellm.proxy.proxy_server import llm_router + except ImportError: + return None + return llm_router + + +def resolve_model_budget( + model: str, + model_max_budget: Mapping[str, object], + model_access_groups: ModelAccessGroups = proxy_model_access_groups, + team_id: str | None = None, +) -> ResolvedModelBudget | None: + """Find the `model_max_budget` entry that governs `model`, or None. + + An entry named after the model wins, then one named after a model access + group serving it, then the most specific glob (`claude-opus*`). Every model + an access group or glob entry covers draws from that entry's one counter. + """ + resolved: Final = ( + _usable_entry(entry=entry, raw_budget_config=model_max_budget[entry]) + for entry in _governing_entry_names( + model=model, model_max_budget=model_max_budget, model_access_groups=model_access_groups, team_id=team_id + ) + ) + return next((entry for entry in resolved if entry is not None), None) + + +def _governing_entry_names( + model: str, + model_max_budget: Mapping[str, object], + model_access_groups: ModelAccessGroups, + team_id: str | None, +) -> Iterator[str]: + candidates: Final = _budget_model_candidates(model) + yield from (candidate for candidate in candidates if candidate in model_max_budget) + group_entries: Final = tuple( + sorted(entry for entry in model_max_budget if _GLOB_WILDCARD not in entry and entry not in candidates) + ) + if group_entries: + groups: Final = model_access_groups(model, team_id) + yield from (entry for entry in group_entries if entry in groups) + yield from sorted( + (entry for entry in model_max_budget if _GLOB_WILDCARD in entry and _glob_matches(entry, candidates)), + key=_glob_precedence, + reverse=True, + ) + + +def _glob_matches(pattern: str, names: Iterable[str]) -> bool: + return any(_glob_matches_name(pattern=pattern, name=name) for name in names) + + +def _glob_matches_name(pattern: str, name: str) -> bool: + """Whole-name match where `*` is the only wildcard, in linear time whatever the pattern holds. + + Taking each literal piece between two wildcards at its first occurrence is + always safe, since a later occurrence only leaves less room for the rest, so + the match never needs to backtrack the way a `.*` regex does. + """ + if _GLOB_WILDCARD not in pattern: + return pattern == name + head, *middle, tail = pattern.split(_GLOB_WILDCARD) + middle_end: Final = len(name) - len(tail) + if middle_end < len(head) or not name.startswith(head) or not name.endswith(tail): + return False + return functools.reduce(_after_piece(name=name, end=middle_end), middle, len(head)) >= 0 + + +def _after_piece(name: str, end: int) -> Callable[[int, str], int]: + def step(position: int, piece: str) -> int: + found: Final = name.find(piece, position, end) if position >= 0 else -1 + return found + len(piece) if found >= 0 else -1 + + return step + + +def _glob_precedence(pattern: str) -> tuple[int, int, str]: + """More literal characters first, then fewer wildcards, so padding a pattern with `*` never makes it win.""" + wildcards: Final = pattern.count(_GLOB_WILDCARD) + return len(pattern) - wildcards, -wildcards, pattern + + +@dataclass(frozen=True, slots=True) +class _RequestForm: + """Request names that an entry governs. + + Every such name matches all of ``name_globs`` and also resolves through + ``candidate_globs``. Its last ``/`` segment is among them unless + ``last_segment_open``. + """ + + name_globs: tuple[str, ...] + candidate_globs: tuple[str, ...] = () + last_segment_open: bool = False + + +def entries_outranked_by(entry: str, model_max_budget: Collection[str], routed_models: RoutedModels) -> Iterator[str]: + """Entries that `entry` can take precedence over for some model a request can name. + + A model or group entry is resolved before any pattern, and a pattern before + every less specific one, so `entry` outranks a pattern that some request it + governs also resolves to. A group entry with a wildcard route among its + members outranks every pattern. + """ + patterns: Final = tuple(other for other in model_max_budget if _GLOB_WILDCARD in other) + if _GLOB_WILDCARD in entry: + entry_precedence: Final = _glob_precedence(entry) + pattern_forms: Final = tuple(_pattern_request_forms(pattern=entry, routed_models=routed_models)) + yield from ( + other + for other in patterns + if _glob_precedence(other) < entry_precedence and _resolves_any(pattern=other, forms=pattern_forms) + ) + return + entry_members: Final = routed_models.members(entry) + covers_wildcard_route: Final = any(_GLOB_WILDCARD in member for member in entry_members) + entry_forms: Final = tuple( + _entry_request_forms(entry=entry, entry_members=entry_members, routed_models=routed_models) + ) + yield from (other for other in patterns if covers_wildcard_route or _resolves_any(pattern=other, forms=entry_forms)) + yield from ( + other + for other in model_max_budget + if _GLOB_WILDCARD not in other + and _ranks_ahead_of_group( + entry=entry, entry_members=entry_members, group=other, group_members=routed_models.members(other) + ) + ) + + +def _resolves_any(pattern: str, forms: Iterable[_RequestForm]) -> bool: + return any(_resolves(pattern=pattern, form=form) for form in forms) + + +def _resolves(pattern: str, form: _RequestForm) -> bool: + return ( + _globs_share_a_name(pattern, *form.name_globs) + or any(_globs_share_a_name(pattern, candidate) for candidate in form.candidate_globs) + or (form.last_segment_open and "/" not in pattern and _globs_share_a_name(f"*/{pattern}", *form.name_globs)) + ) + + +def _globs_share_a_name(*globs: str) -> bool: + """Whether one name matches every glob. + + Globs that each hold a `*` share a name exactly when their literal heads + are prefixes of one another and so are their literal tails: the longest + head, every middle piece and the longest tail, in that order, matches all + of them. + """ + literal: Final = next((glob for glob in globs if _GLOB_WILDCARD not in glob), None) + if literal is not None: + return all(_glob_matches_name(pattern=glob, name=literal) for glob in globs) + heads: Final = sorted((glob.partition(_GLOB_WILDCARD)[0] for glob in globs), key=len) + tails: Final = sorted((glob.rpartition(_GLOB_WILDCARD)[2] for glob in globs), key=len) + return all(longer.startswith(shorter) for shorter, longer in itertools.pairwise(heads)) and all( + longer.endswith(shorter) for shorter, longer in itertools.pairwise(tails) + ) + + +def _served_form(name: str) -> _RequestForm: + return _RequestForm(name_globs=(name,), candidate_globs=_budget_model_candidates(name)) + + +def _wildcard_routes(routed_models: RoutedModels) -> tuple[str, ...]: + return tuple(sorted(name for name in routed_models.served_names if _GLOB_WILDCARD in name)) + + +def _entry_request_forms( + entry: str, entry_members: frozenset[str], routed_models: RoutedModels +) -> Iterator[_RequestForm]: + yield from ( + _served_form(name) + for name in _names_governed_by(entry=entry, entry_members=entry_members, routed_models=routed_models) + ) + routes: Final = _wildcard_routes(routed_models) + yield from ( + _RequestForm(name_globs=(route, f"*/{entry}"), candidate_globs=_budget_model_candidates(entry)) + for route in routes + ) + yield from _bedrock_request_forms( + bedrock_models=tuple(model for model in _bedrock_base_models() if entry in _bedrock_names(model)), + routes=routes, + ) + + +def _pattern_request_forms(pattern: str, routed_models: RoutedModels) -> Iterator[_RequestForm]: + yield _RequestForm(name_globs=(pattern,)) + yield from ( + _served_form(name) + for name in routed_models.served_names + if _GLOB_WILDCARD not in name and _glob_matches(pattern, _budget_model_candidates(name)) + ) + routes: Final = _wildcard_routes(routed_models) + yield from (_RequestForm(name_globs=(route, pattern), last_segment_open=True) for route in routes) + if "/" not in pattern: + yield from (_RequestForm(name_globs=(route, f"*/{pattern}"), candidate_globs=(pattern,)) for route in routes) + yield from ( + _narrowed_to(pattern=pattern, form=form) + for form in _bedrock_request_forms(bedrock_models=_bedrock_base_models(), routes=routes) + if _resolves(pattern=pattern, form=form) + ) + + +def _narrowed_to(pattern: str, form: _RequestForm) -> _RequestForm: + if any(_globs_share_a_name(pattern, candidate) for candidate in form.candidate_globs): + return form + return _RequestForm(name_globs=(*form.name_globs, pattern), candidate_globs=form.candidate_globs) + + +def _bedrock_request_forms(bedrock_models: Iterable[str], routes: Sequence[str]) -> Iterator[_RequestForm]: + """Wildcard-routed request names that resolve to a Bedrock model: its id, under a cross-region prefix or with a + context or throughput suffix, as the whole name or after any routing prefix, region path or ARN.""" + forms: Final = itertools.chain.from_iterable( + _bedrock_model_request_forms(model=model, routes=routes) for model in bedrock_models + ) + yield from (form for form in forms if _globs_share_a_name(*form.name_globs)) + + +def _bedrock_model_request_forms(model: str, routes: Sequence[str]) -> Iterator[_RequestForm]: + names: Final = _bedrock_names(model) + return ( + _RequestForm(name_globs=(route, f"{prefix}{last_segment}"), candidate_globs=(last_segment, *names)) + for route, (last_segment, prefix) in itertools.product( + routes, itertools.product(_bedrock_last_segments(model), ("", "*/")) + ) + ) + + +def _bedrock_last_segments(model: str) -> tuple[str, ...]: + regioned: Final = (model, *(f"{region}.{model}" for region in get_bedrock_cross_region_inference_regions())) + _, version_separator, version = model.rpartition(":") + suffixes: Final = ("", "[*]", *((":*k",) if version_separator and version.isdigit() else ())) + return tuple(f"{name}{suffix}" for name, suffix in itertools.product(regioned, suffixes)) + + +def _model_cost() -> Mapping[str, object]: + return litellm.model_cost + + +def _bedrock_base_models() -> tuple[str, ...]: + return tuple( + model + for model, cost_entry in _model_cost().items() + if _priced_as_bedrock(cost_entry) and get_bedrock_base_model(model) == model + ) + + +def _names_governed_by(entry: str, entry_members: frozenset[str], routed_models: RoutedModels) -> Iterator[str]: + yield entry + yield from (f"{prefix}{entry}" for prefix in _PROVIDER_PREFIXES) + yield from ( + name + for name in routed_models.served_names + if _GLOB_WILDCARD not in name and entry in _budget_model_candidates(name) + ) + yield from (member for member in entry_members if _GLOB_WILDCARD not in member) + + +def _ranks_ahead_of_group(entry: str, entry_members: frozenset[str], group: str, group_members: Iterable[str]) -> bool: + return any( + _GLOB_WILDCARD in member + or entry in _budget_model_candidates(member) + or (member in entry_members and entry < group) + for member in group_members + ) + + +def _usable_entry(entry: str, raw_budget_config: object) -> ResolvedModelBudget | None: + if (budget_config := _usable_budget_config(raw_budget_config)) is None: + # An entry that will not validate cannot be keyed, so it cannot be + # enforced or incremented. Skip to the next candidate rather than + # raising: raising would abort every other scope's increment and turn + # a config typo into a 500, and stopping here would let one malformed + # specific entry disable a perfectly good bare-family budget beside + # it. The candidate chain already falls through an ABSENT entry, and + # an unparseable one is indistinguishable from absent to enforcement. + # `validate_model_max_budget` rejects these on the write path, so + # reaching here means config.yaml or a direct DB edit. + verbose_proxy_logger.warning( + "Ignoring unusable model_max_budget entry for %s; it cannot be enforced or tracked", + entry, + ) + return None + return ResolvedModelBudget(budget_model=entry, budget_config=budget_config) + + +def team_model_budget_entries( + model: str, team_model_max_budget: Mapping[str, object], key_model_max_budget: Mapping[str, object] | None +) -> Mapping[str, object]: + """The team entries that budget `model` for this key. + + A key entry named after `model` that spend-gates it replaces the team entry named after it, so that model is + gated on and billed to the key's entry. The team's pattern and group entries still apply beside it. + """ + exact_candidates: Final = _budget_model_candidates(model) + if not _key_entry_replaces_team_entry( + model=model, exact_candidates=exact_candidates, key_model_max_budget=key_model_max_budget + ): + return team_model_max_budget + return MappingProxyType( + {entry: config for entry, config in team_model_max_budget.items() if entry not in exact_candidates} + ) + + +def _key_entry_replaces_team_entry( + model: str, exact_candidates: tuple[str, ...], key_model_max_budget: Mapping[str, object] | None +) -> bool: if not key_model_max_budget: - return True - resolved: Final = resolve_model_budget(model=model, model_max_budget=key_model_max_budget) - return resolved is None or not _spend_gated(resolved.budget_config) + return False + resolved: Final = resolve_model_budget( + model=model, + model_max_budget=MappingProxyType( + { + candidate: key_model_max_budget[candidate] + for candidate in exact_candidates + if candidate in key_model_max_budget + } + ), + model_access_groups=lambda _model, _team_id: frozenset(), + ) + return resolved is not None and _spend_gated(resolved.budget_config) def _spend_gated(budget_config: BudgetConfig) -> bool: return budget_config.max_budget is not None and budget_config.max_budget >= 0 +def entry_names_model(entry: str, model: str) -> bool: + """Whether `entry` budgets `model` under the model's own name, rather than as a pattern or an access group.""" + return entry in _budget_model_candidates(model) + + def _budget_model_candidates(model: str) -> tuple[str, ...]: """Names a budget may be configured under for a request on `model`, most specific first. @@ -189,13 +582,18 @@ def _bedrock_candidates(model: str) -> tuple[str, ...]: of those would produce a garbage candidate. """ base_model: Final = get_bedrock_base_model(model) - cost_entry: Final = litellm.model_cost.get(base_model) - if not isinstance(cost_entry, dict) or not str(cost_entry.get("litellm_provider", "")).startswith("bedrock"): - return () + return _bedrock_names(base_model) if _priced_as_bedrock(_model_cost().get(base_model)) else () + + +def _bedrock_names(base_model: str) -> tuple[str, ...]: _, _, without_vendor = base_model.partition(".") return (base_model, without_vendor) if without_vendor else (base_model,) +def _priced_as_bedrock(cost_entry: object) -> bool: + return str(_metadata_value(cost_entry, "litellm_provider") or "").startswith("bedrock") + + @dataclass(frozen=True, slots=True) class _WindowReading: current_spend: float @@ -208,6 +606,7 @@ async def build_model_max_budget_usage( model_max_budget: Mapping[str, object] | None, cache: DualCache | None, now: datetime | None = None, + shared_windows: SharedWindows = PROXY_SHARED_WINDOWS, ) -> dict[str, dict[str, object]]: """Current-window spend per configured budget model, as `/key/info` and `/user/info` report it. @@ -231,17 +630,18 @@ async def build_model_max_budget_usage( ) if not budgets: return {} + spend_keys: Final = tuple( + model_budget_spend_cache_key( + entity_type=entity_type, + entity_id=entity_id, + budget_model=budget_model, + budget_duration=budget_config.budget_duration, + ) + for budget_model, budget_config in budgets + ) windows: Final = await _read_windows( cache=cache, - spend_keys=tuple( - model_budget_spend_cache_key( - entity_type=entity_type, - entity_id=entity_id, - budget_model=budget_model, - budget_duration=budget_config.budget_duration, - ) - for budget_model, budget_config in budgets - ), + spend_keys=spend_keys, start_time_keys=tuple( model_budget_start_time_cache_key( entity_type=entity_type, @@ -253,21 +653,57 @@ async def build_model_max_budget_usage( ), ) current_time: Final = (now or datetime.now(timezone.utc)).timestamp() + shared: Final = tuple( + [ + ( + await _open_shared_window( + shared_windows=shared_windows, + spend_key=spend_key, + budget_duration=budget_config.budget_duration, + now=current_time, + ) + if cache.redis_cache is None + else None + ) + for spend_key, (_, budget_config) in zip(spend_keys, budgets, strict=True) + ] + ) + readings: Final = tuple( + _fuller_reading(local=window, shared=shared_window) + for window, shared_window in zip(windows, shared, strict=True) + ) return { budget_model: { - "current_spend": round(window.current_spend, 4), + "current_spend": round(reading.current_spend, 4), "budget_limit": budget_config.max_budget, "time_period": budget_config.budget_duration, "budget_reset_at": _window_reset_at( - started_at=window.started_at, + started_at=reading.started_at, budget_duration=budget_config.budget_duration, now=current_time, ), } - for (budget_model, budget_config), window in zip(budgets, windows, strict=True) + for (budget_model, budget_config), reading in zip(budgets, readings, strict=True) } +async def _open_shared_window( + shared_windows: SharedWindows, spend_key: str, budget_duration: str | None, now: float +) -> SharedWindow | None: + if budget_duration is None: + return None + window: Final = await shared_windows.read(spend_key=spend_key, budget_duration=budget_duration) + if window is None or not window.is_open(budget_duration=budget_duration, now=now): + return None + return window + + +def _fuller_reading(local: _WindowReading, shared: SharedWindow | None) -> _WindowReading: + if shared is None or shared.spend <= local.current_spend: + return local + return _WindowReading(current_spend=shared.spend, started_at=shared.started_at) + + @with_service_target("model_budgets") async def _read_windows( cache: DualCache, spend_keys: Sequence[str], start_time_keys: Sequence[str] @@ -307,6 +743,10 @@ def _window_reset_at(started_at: float | None, budget_duration: str | None, now: return datetime.fromtimestamp(ends_at, tz=timezone.utc).isoformat() +def is_enforced_budget_entry(raw_budget_config: object) -> bool: + return _usable_budget_config(raw_budget_config) is not None + + def _usable_budget_config(raw_budget_config: object) -> BudgetConfig | None: try: budget_config: Final = BudgetConfig.model_validate(raw_budget_config) @@ -337,18 +777,44 @@ def _as_float(value: object) -> float | None: def _resolve_entity_model_budgets( model: str, entity_budgets: Iterable[tuple[Litellm_EntityType, str | None, object]], + model_access_groups: ModelAccessGroups, + team_id: str | None, ) -> tuple[tuple[Litellm_EntityType, str, ResolvedModelBudget], ...]: """Drop the scopes that do not budget `model`, keeping only what can be incremented.""" return tuple( (entity_type, entity_id, resolved) for entity_type, entity_id, model_max_budget in entity_budgets if entity_id is not None and isinstance(model_max_budget, Mapping) and model_max_budget - for resolved in (resolve_model_budget(model=model, model_max_budget=model_max_budget),) + for resolved in ( + resolve_model_budget( + model=model, + model_max_budget=model_max_budget, + model_access_groups=model_access_groups, + team_id=team_id, + ), + ) if resolved is not None and resolved.budget_config.budget_duration is not None ) +def _requested_model_name( + metadata: Mapping[str, object], standard_logging_payload: StandardLoggingPayload +) -> str | None: + """The model name the request was gated on: a team-scoped deployment's public name, since the router renames + its model group to a unique internal one, else the model group, else the deployment's model.""" + team_public_model_name: Final = _metadata_value(metadata.get("model_info"), "team_public_model_name") + if ( + isinstance(team_public_model_name, str) + and team_public_model_name + and _GLOB_WILDCARD not in team_public_model_name + ): + return team_public_model_name + return standard_logging_payload.get("model_group") or standard_logging_payload.get("model") + + def _metadata_value(metadata: object, key: str) -> object | None: + if not isinstance(metadata, Mapping): + return None metadata_mapping: Final[Mapping[str, object]] = cast( # cast-ok: callback metadata has string keys Mapping[str, object], metadata ) @@ -367,9 +833,17 @@ class _PROXY_VirtualKeyModelMaxBudgetLimiter(RouterBudgetLimiting): Example: key=$LITELLM_API_KEY, model=gpt-4o, max_budget=100, time_period=1d """ - def __init__(self, dual_cache: DualCache, clock: Callable[[], float] = time.time): + def __init__( + self, + dual_cache: DualCache, + clock: Callable[[], float] = time.time, + model_access_groups: ModelAccessGroups = proxy_model_access_groups, + shared_windows: SharedWindows = PROXY_SHARED_WINDOWS, + ): self.dual_cache = dual_cache self._clock = clock + self._model_access_groups = model_access_groups + self._shared_windows = shared_windows self.redis_increment_operation_queue = [] self._redis_increment_queue_lock = asyncio.Lock() self._redis_increment_flush_lock = asyncio.Lock() @@ -393,6 +867,7 @@ class _PROXY_VirtualKeyModelMaxBudgetLimiter(RouterBudgetLimiting): return await self._is_entity_within_model_budget( entity_type=Litellm_EntityType.KEY, entity_id=user_api_key_dict.token, + team_id=user_api_key_dict.team_id, model_max_budget=user_api_key_dict.model_max_budget, model=model, exceeded_message=( @@ -422,6 +897,7 @@ class _PROXY_VirtualKeyModelMaxBudgetLimiter(RouterBudgetLimiting): user_id: str, user_model_max_budget: Mapping[str, object], model: str, + team_id: str | None = None, ) -> bool: """ Check if the internal user is within the model budget @@ -432,6 +908,7 @@ class _PROXY_VirtualKeyModelMaxBudgetLimiter(RouterBudgetLimiting): return await self._is_entity_within_model_budget( entity_type=Litellm_EntityType.USER, entity_id=user_id, + team_id=team_id, model_max_budget=user_model_max_budget, model=model, exceeded_message=f"LiteLLM User: {user_id}, exceeded budget for model={model}", @@ -443,6 +920,7 @@ class _PROXY_VirtualKeyModelMaxBudgetLimiter(RouterBudgetLimiting): end_user_id: str, end_user_model_max_budget: Mapping[str, object], model: str, + team_id: str | None = None, ) -> bool: """ Check if the end_user is within the model budget @@ -453,6 +931,7 @@ class _PROXY_VirtualKeyModelMaxBudgetLimiter(RouterBudgetLimiting): return await self._is_entity_within_model_budget( entity_type=Litellm_EntityType.END_USER, entity_id=end_user_id, + team_id=team_id, model_max_budget=end_user_model_max_budget, model=model, exceeded_message=f"LiteLLM End User: {end_user_id}, exceeded budget for model={model}", @@ -467,18 +946,19 @@ class _PROXY_VirtualKeyModelMaxBudgetLimiter(RouterBudgetLimiting): model: str, ) -> bool: """ - Check if the team is within the model budget, unless the key's own - `model_max_budget` overrides it for `model` + Check if the team is within the model budget, leaving out a team entry named after `model` that the key's + own `model_max_budget` replaces Raises: BudgetExceededError: If the team has exceeded the model budget """ - if not team_model_budget_applies(model=model, key_model_max_budget=key_model_max_budget): - return True return await self._is_entity_within_model_budget( entity_type=Litellm_EntityType.TEAM, entity_id=team_id, - model_max_budget=team_model_max_budget, + team_id=team_id, + model_max_budget=team_model_budget_entries( + model=model, team_model_max_budget=team_model_max_budget, key_model_max_budget=key_model_max_budget + ), model=model, exceeded_message=f"LiteLLM Team: {team_id}, exceeded budget for model={model}", ) @@ -494,6 +974,7 @@ class _PROXY_VirtualKeyModelMaxBudgetLimiter(RouterBudgetLimiting): return await self._is_entity_within_model_budget( entity_type=Litellm_EntityType.TEAM_MEMBER, entity_id=team_member_budget_entity_id(user_id=user_id, team_id=team_id), + team_id=team_id, model_max_budget=team_member_model_max_budget, model=model, exceeded_message=( @@ -505,13 +986,19 @@ class _PROXY_VirtualKeyModelMaxBudgetLimiter(RouterBudgetLimiting): self, entity_type: Litellm_EntityType, entity_id: str | None, + team_id: str | None, model_max_budget: Mapping[str, object] | None, model: str, exceeded_message: str, ) -> bool: if not model_max_budget: return True - resolved: Final = resolve_model_budget(model=model, model_max_budget=model_max_budget) + resolved: Final = resolve_model_budget( + model=model, + model_max_budget=model_max_budget, + model_access_groups=self._model_access_groups, + team_id=team_id, + ) if resolved is None: verbose_proxy_logger.debug("Model %s not found in %s model_max_budget", model, entity_type.value) return True @@ -520,15 +1007,26 @@ class _PROXY_VirtualKeyModelMaxBudgetLimiter(RouterBudgetLimiting): if max_budget is None or max_budget < 0: return True - current_spend: Final = await self._get_spend_for_model_budget( + local_spend: Final = await self._get_spend_for_model_budget( entity_type=entity_type, entity_id=entity_id, model=model, resolved=resolved, ) + current_spend: Final = ( + local_spend + if local_spend >= max_budget + else await self._with_shared_spend( + entity_type=entity_type, entity_id=entity_id, resolved=resolved, local_spend=local_spend + ) + ) if current_spend >= max_budget: raise litellm.BudgetExceededError( - message=exceeded_message, + message=( + exceeded_message + if resolved.budget_model in _budget_model_candidates(model) + else f"{exceeded_message}, budget_model={resolved.budget_model}" + ), current_cost=current_spend, max_budget=max_budget, entity_type=entity_type.value, @@ -566,6 +1064,30 @@ class _PROXY_VirtualKeyModelMaxBudgetLimiter(RouterBudgetLimiting): return current_spend return current_spend + _as_spend(await self._cached_spend(legacy_spend_key)) + async def _with_shared_spend( + self, + entity_type: Litellm_EntityType, + entity_id: str | None, + resolved: ResolvedModelBudget, + local_spend: float, + ) -> float: + """Without Redis each replica's counter holds only its own share, so the window every replica adds to + in the database is the floor.""" + if not self._shares_windows_in_database(entity_type): + return local_spend + shared: Final = await _open_shared_window( + shared_windows=self._shared_windows, + spend_key=model_budget_spend_cache_key( + entity_type=entity_type, + entity_id=entity_id, + budget_model=resolved.budget_model, + budget_duration=resolved.budget_config.budget_duration, + ), + budget_duration=resolved.budget_config.budget_duration, + now=self._clock(), + ) + return local_spend if shared is None else max(local_spend, shared.spend) + async def _cached_spend(self, spend_key: str) -> float | None: redis_cache: Final = self.dual_cache.redis_cache if redis_cache is None: @@ -604,13 +1126,10 @@ class _PROXY_VirtualKeyModelMaxBudgetLimiter(RouterBudgetLimiting): ) payload_metadata: Final = standard_logging_payload.get("metadata") or {} - # Use model_group (the user-facing model alias, e.g. "gpt-4o") when - # available. The enforcement path receives the model name from - # request_data["model"] which is the model group alias, so the spend - # tracking cache key must resolve from the same name. Falling back to - # the deployment-level "model" field preserves behaviour for non-proxy - # or non-router deployments where model_group is None. - model: Final = standard_logging_payload.get("model_group") or standard_logging_payload.get("model") + model: Final = _requested_model_name( + metadata=_metadata, # pyright: ignore[reportUnknownArgumentType] # callback metadata is partially untyped + standard_logging_payload=standard_logging_payload, + ) if model is None: return @@ -624,6 +1143,10 @@ class _PROXY_VirtualKeyModelMaxBudgetLimiter(RouterBudgetLimiting): payload_metadata, # pyright: ignore[reportUnknownArgumentType] # callback metadata is partially untyped "user_api_key_team_id", ) + team_model_max_budget: Final = _metadata_value( + _metadata, # pyright: ignore[reportUnknownArgumentType] # callback metadata is partially untyped + "user_api_key_team_model_max_budget", + ) team_member_entity_id: Final = ( team_member_budget_entity_id(user_id=team_member_user_id, team_id=team_member_team_id) if team_member_user_id is not None and team_member_team_id is not None @@ -637,16 +1160,17 @@ class _PROXY_VirtualKeyModelMaxBudgetLimiter(RouterBudgetLimiting): ), ( Litellm_EntityType.TEAM, - payload_metadata.get("user_api_key_team_id"), + team_member_team_id, ( - _metadata.get("user_api_key_team_model_max_budget") - if team_model_budget_applies( + team_model_budget_entries( model=model, + team_model_max_budget=team_model_max_budget, key_model_max_budget=( key_model_max_budget if isinstance(key_model_max_budget, Mapping) else None ), ) - else None + if isinstance(team_model_max_budget, Mapping) + else team_model_max_budget ), ), ( @@ -669,7 +1193,12 @@ class _PROXY_VirtualKeyModelMaxBudgetLimiter(RouterBudgetLimiting): ), ) - resolved_budgets: Final = _resolve_entity_model_budgets(model=model, entity_budgets=entity_budgets) + resolved_budgets: Final = _resolve_entity_model_budgets( + model=model, + entity_budgets=entity_budgets, + model_access_groups=self._model_access_groups, + team_id=team_member_team_id, + ) if not resolved_budgets: verbose_proxy_logger.debug( "Not running _PROXY_VirtualKeyModelMaxBudgetLimiter.async_log_success_event: " @@ -723,17 +1252,114 @@ class _PROXY_VirtualKeyModelMaxBudgetLimiter(RouterBudgetLimiting): ttl_seconds=duration_in_seconds(budget_duration), ): return + start_time_key: Final = model_budget_start_time_cache_key( + entity_type=entity_type, + entity_id=entity_id, + budget_model=resolved.budget_model, + budget_duration=budget_duration, + ) + shares_window: Final = self._shares_windows_in_database(entity_type) + if shares_window: + await self._join_shared_window( + spend_key=spend_key, start_time_key=start_time_key, budget_duration=budget_duration + ) await self._increment_spend_for_key( budget_config=resolved.budget_config, spend_key=spend_key, - start_time_key=model_budget_start_time_cache_key( - entity_type=entity_type, - entity_id=entity_id, - budget_model=resolved.budget_model, - budget_duration=budget_duration, - ), + start_time_key=start_time_key, response_cost=response_cost, ) + if shares_window: + await self._share_spend( + spend_key=spend_key, + start_time_key=start_time_key, + budget_duration=budget_duration, + response_cost=response_cost, + ) + + def _shares_windows_in_database(self, entity_type: Litellm_EntityType) -> bool: + """End-user ids are whatever the client sends, so their windows stay on each replica rather than adding a + database row per id.""" + return self.dual_cache.redis_cache is None and entity_type not in _PER_REPLICA_SCOPES + + async def _join_shared_window(self, spend_key: str, start_time_key: str, budget_duration: str) -> None: + """Without Redis, start this replica's window where the database says every replica's window starts. + + Every replica then sends the same window start with its spend, so no flush reads as a newer window that + replaces the spend the others already added. While the database cannot say, this replica keeps its spend + unshared and sends it once a later charge joins the shared window. + """ + now: Final = self._clock() + local: Final = _local_windows(self.dual_cache) + unshared_key: Final = _unshared_spend_key(start_time_key) + if local.get_cache(key=unshared_key) is None and _open_local_window_start( + local=local, start_time_key=start_time_key, budget_duration=budget_duration, now=now + ): + return + started_at: Final = await self._shared_windows.open( + spend_key=spend_key, budget_duration=budget_duration, now=now + ) + unshared_spend: Final = _as_float(local.get_cache(key=unshared_key)) + local_window_open: Final = _open_local_window_start( + local=local, start_time_key=start_time_key, budget_duration=budget_duration, now=now + ) + if local_window_open and unshared_spend is None: + return + if not local_window_open: + _start_local_window( + local=local, + spend_key=spend_key, + start_time_key=start_time_key, + started_at=now if started_at is None else started_at, + budget_duration=budget_duration, + now=now, + spend=0.0, + ) + if started_at is None: + local.set_cache(key=unshared_key, value=0.0, ttl=budget_window_seconds(now, budget_duration)) + else: + local.delete_cache(key=unshared_key) + return + if started_at is None or unshared_spend is None: + return + _start_local_window( + local=local, + spend_key=spend_key, + start_time_key=start_time_key, + started_at=started_at, + budget_duration=budget_duration, + now=now, + spend=_as_float(local.get_cache(key=spend_key)) or 0.0, + ) + local.delete_cache(key=unshared_key) + await self._shared_windows.add( + spend_key=spend_key, budget_duration=budget_duration, started_at=started_at, spend=unshared_spend + ) + + async def _share_spend( + self, spend_key: str, start_time_key: str, budget_duration: str, response_cost: float + ) -> None: + now: Final = self._clock() + local: Final = _local_windows(self.dual_cache) + unshared_key: Final = _unshared_spend_key(start_time_key) + unshared_spend: Final = _as_float(local.get_cache(key=unshared_key)) + if unshared_spend is not None: + local.set_cache( + key=unshared_key, + value=unshared_spend + response_cost, + ttl=budget_window_seconds(now, budget_duration), + ) + return + await self._shared_windows.add( + spend_key=spend_key, + budget_duration=budget_duration, + started_at=await self._get_or_set_budget_start_time( + start_time_key=start_time_key, + current_time=now, + ttl_seconds=budget_window_seconds(now, budget_duration), + ), + spend=response_cost, + ) async def _claim_batch_charge(self, spend_key: str, batch_id: str, ttl_seconds: int) -> bool: marker_key: Final = batch_charged_once_marker_key(spend_key=spend_key, batch_id=batch_id) @@ -743,4 +1369,33 @@ class _PROXY_VirtualKeyModelMaxBudgetLimiter(RouterBudgetLimiting): return polls == 1 +def _local_windows(dual_cache: DualCache) -> LocalTTLCache: + return dual_cache.in_memory_cache + + +def _open_local_window_start(local: LocalTTLCache, start_time_key: str, budget_duration: str, now: float) -> bool: + started_at: Final = _as_float(local.get_cache(key=start_time_key)) + return started_at is not None and now - started_at <= budget_window_seconds(started_at, budget_duration) + + +def _start_local_window( + local: LocalTTLCache, + spend_key: str, + start_time_key: str, + started_at: float, + budget_duration: str, + now: float, + spend: float, +) -> None: + ttl: Final = started_at + budget_window_seconds(started_at, budget_duration) - now + local.delete_cache(key=spend_key) + local.delete_cache(key=start_time_key) + local.set_cache(key=spend_key, value=spend, ttl=ttl) + local.set_cache(key=start_time_key, value=started_at, ttl=ttl) + + +def _unshared_spend_key(start_time_key: str) -> str: + return f"{start_time_key}:unshared" + + PROXY_VirtualKeyModelMaxBudgetLimiter = _PROXY_VirtualKeyModelMaxBudgetLimiter diff --git a/litellm/proxy/hooks/parallel_request_limiter_v3.py b/litellm/proxy/hooks/parallel_request_limiter_v3.py index 567b8452ae2..a3a6f582dce 100644 --- a/litellm/proxy/hooks/parallel_request_limiter_v3.py +++ b/litellm/proxy/hooks/parallel_request_limiter_v3.py @@ -45,11 +45,14 @@ from litellm.caching.redis_cache import log_redis_failure from litellm.constants import DYNAMIC_RATE_LIMIT_ERROR_THRESHOLD_PER_MINUTE, INTERNAL_CALL_ORIGIN_METADATA_KEY from litellm.cost_calculator import get_usage_object from litellm.integrations.custom_logger import CustomLogger +from litellm.litellm_core_utils.audio_utils.utils import estimate_audio_tokens +from litellm.litellm_core_utils.core_helpers import as_str_mapping from litellm.litellm_core_utils.prompt_templates.common_utils import ( get_str_from_messages, + split_media_for_tpm, ) from litellm.litellm_core_utils.ptu_pricing import is_ptu_cost_attribution_enabled -from litellm.litellm_core_utils.token_counter import offload_token_count +from litellm.litellm_core_utils.token_counter import estimate_image_tokens, offload_token_count from litellm.llms.azure.ptu_capacity import normalized_tokens from litellm.proxy._types import UserAPIKeyAuth from litellm.proxy.auth.auth_utils import ( @@ -73,6 +76,7 @@ from litellm.proxy.hooks.batch_enqueued_tokens import ( canonical_provider_batch_id, ) from litellm.proxy.hooks.rate_limiter_utils import resolve_llm_provider_for_rate_limit +from litellm.proxy.spend_tracking.input_tokens import tokenizer_models from litellm.responses.litellm_completion_transformation.compaction_items import billable_input_since_newest_compaction from litellm.router_utils.add_retry_fallback_headers import ( ensure_response_additional_headers, @@ -98,6 +102,7 @@ if TYPE_CHECKING: from opentelemetry.trace import Span as _Span from litellm.proxy.utils import InternalUsageCache as _InternalUsageCache + from litellm.router import Router from litellm.types.agents import AgentResponse from litellm.types.caching import RedisPipelineIncrementOperation @@ -135,6 +140,18 @@ class RateLimitedModel: return requested_limit if requested_limit is not None else limits.get(self.group) +def _resolve_media_models(router: "Router | None", model: str, team_id: str | None) -> tuple[str, ...]: + if router is None: + return (model,) + return tuple(dict.fromkeys(router.resolved_litellm_models(model, team_id, use_base_model=True))) or (model,) + + +def _resolve_media_models_via_proxy_router(model: str, team_id: str | None) -> tuple[str, ...]: + from litellm.proxy.proxy_server import llm_router + + return _resolve_media_models(llm_router, model, team_id) + + def _resolve_model_group_alias_via_proxy_router(model: str) -> str | None: from litellm.proxy.proxy_server import llm_router @@ -143,6 +160,12 @@ def _resolve_model_group_alias_via_proxy_router(model: str) -> str | None: return resolve_model_group_alias(llm_router.model_group_alias, model) +def _tokenizer_models_via_proxy_router(model: str) -> tuple[str, ...]: + from litellm.proxy.proxy_server import llm_router + + return tokenizer_models(model, llm_router) + + def _resolve_ptu_team_ceiling_via_proxy_router(team_id: str, model_group: str) -> PTUTeamCeiling | None: from litellm.proxy.proxy_server import llm_router @@ -862,19 +885,23 @@ class _PROXY_MaxParallelRequestsHandler_v3(CustomLogger): time_provider: Callable[[], datetime] | None = None, tag_rate_limit_resolver: TagRateLimitResolver = resolve_tag_rate_limits_from_db, model_group_resolver: Callable[[str], str | None] = _resolve_model_group_alias_via_proxy_router, + media_model_resolver: Callable[[str, str | None], tuple[str, ...]] = _resolve_media_models_via_proxy_router, ptu_team_ceiling_resolver: Callable[ [str, str], PTUTeamCeiling | None ] = _resolve_ptu_team_ceiling_via_proxy_router, fail_closed_resolver: Callable[[], bool] = _fail_closed_rate_limit_enforcement_from_general_settings, force_hash_tag_grouping_resolver: Callable[[], bool] = _force_redis_hash_tag_grouping_from_litellm_settings, + tokenizer_models_resolver: Callable[[str], tuple[str, ...]] = _tokenizer_models_via_proxy_router, ): self.internal_usage_cache = internal_usage_cache self._time_provider = time_provider or datetime.now self._tag_rate_limit_resolver = tag_rate_limit_resolver self._model_group_resolver = model_group_resolver + self._media_model_resolver = media_model_resolver self._ptu_team_ceiling_resolver = ptu_team_ceiling_resolver self._fail_closed_resolver = fail_closed_resolver self._force_hash_tag_grouping_resolver = force_hash_tag_grouping_resolver + self._tokenizer_models_resolver = tokenizer_models_resolver if self.internal_usage_cache.dual_cache.redis_cache is not None: self.batch_rate_limiter_script = self.internal_usage_cache.dual_cache.redis_cache.async_register_script( BATCH_RATE_LIMITER_SCRIPT @@ -1133,11 +1160,12 @@ class _PROXY_MaxParallelRequestsHandler_v3(CustomLogger): def _estimate_tokens_for_request( self, - data: dict, + data: object, model: str | None = None, min_configured_tpm_limit: int | None = None, call_type: str | None = None, configured_output_tokens: int | None = None, + team_id: str | None = None, ) -> int: """ Estimate total tokens this request will consume so we can reserve them @@ -1164,6 +1192,8 @@ class _PROXY_MaxParallelRequestsHandler_v3(CustomLogger): min_configured_tpm_limit=min_configured_tpm_limit, call_type=call_type, configured_output_tokens=configured_output_tokens, + team_id=team_id, + media_model_resolver=self._media_model_resolver, ) total_estimated: Final = estimated_input_tokens + max_tokens_estimate @@ -1184,6 +1214,7 @@ class _PROXY_MaxParallelRequestsHandler_v3(CustomLogger): call_type: str | None, configured_output_tokens: int | None, raw_estimate: int, + team_id: str | None = None, ) -> int: """The team PTU ceiling counts Azure normalized tokens, so its reservation weighs the output budget the way the ceiling does instead of the raw sum the other scopes reserve.""" @@ -1194,6 +1225,8 @@ class _PROXY_MaxParallelRequestsHandler_v3(CustomLogger): min_configured_tpm_limit=min_configured_tpm_limit, call_type=call_type, configured_output_tokens=configured_output_tokens, + team_id=team_id, + media_model_resolver=self._media_model_resolver, ) normalized: Final = normalized_tokens( ceiling, prompt_tokens=estimated_input_tokens, completion_tokens=max_tokens_estimate @@ -1206,6 +1239,9 @@ class _PROXY_MaxParallelRequestsHandler_v3(CustomLogger): min_configured_tpm_limit: int | None = None, call_type: str | None = None, configured_output_tokens: int | None = None, + include_media: bool = True, + team_id: str | None = None, + media_model_resolver: Callable[[str, str | None], tuple[str, ...]] | None = None, ) -> tuple[int, int]: """ Estimate input tokens and output (max_tokens) budget separately, so @@ -1229,10 +1265,12 @@ class _PROXY_MaxParallelRequestsHandler_v3(CustomLogger): floor entirely, so the reservation reflects what this tenant's model actually emits rather than one constant shared by every tenant. """ - if not isinstance(data, dict): + request_data: Final = as_str_mapping(data) + if not isinstance(data, dict) or request_data is None: return 0, 0 + request_model: Final = request_data.get("model") translated_data: Final = self._translate_google_genai_native_request(data, call_type) - estimable_data: Final = translated_data if translated_data is not None else data + estimable_data: Final = translated_data if translated_data is not None else request_data selected_fields: Final[tuple[object | None, object | None, object | None]] = ( (None, None, estimable_data.get("input")) if call_type in RESPONSES_API_CALL_TYPES or call_type in EMBEDDING_API_CALL_TYPES @@ -1249,10 +1287,27 @@ class _PROXY_MaxParallelRequestsHandler_v3(CustomLogger): ) ) messages, prompt, raw_input = selected_fields - input_text: Final = ( + original_input: Final = ( billable_input_since_newest_compaction(raw_input) if call_type in RESPONSES_API_CALL_TYPES else raw_input ) + media_source: Final = messages if messages is not None else original_input + projected, media = ( + split_media_for_tpm(media_source) + if include_media and (isinstance(messages, list) or call_type in RESPONSES_API_CALL_TYPES) + else (original_input, ()) + ) + input_text: Final = projected if call_type in RESPONSES_API_CALL_TYPES else original_input + fallback_model: Final = request_model if isinstance(request_model, str) else None + resolved_models: Final = ( + media_model_resolver(fallback_model or "", team_id) + if media and media_model_resolver is not None + else (fallback_model or "",) + ) + media_tokens: Final = sum( + self._estimate_media_block_tokens(block, resolved_models, fallback_model) for block in media + ) + total_chars: Final = ( len(get_str_from_messages(messages)) if isinstance(messages, list) and messages @@ -1267,7 +1322,9 @@ class _PROXY_MaxParallelRequestsHandler_v3(CustomLogger): else 0 ) - estimated_input_tokens: Final = max(1, total_chars // DEFAULT_CHARS_PER_TOKEN) if total_chars > 0 else 0 + estimated_input_tokens: Final = ( + max(1, total_chars // DEFAULT_CHARS_PER_TOKEN) if total_chars > 0 else 0 + ) + media_tokens explicit_max_tokens: Final = self._get_explicit_output_cap(data, call_type) generates_no_output: Final = ( @@ -1283,7 +1340,7 @@ class _PROXY_MaxParallelRequestsHandler_v3(CustomLogger): max_tokens_estimate: Final = ( 0 if generates_no_output - or (explicit_max_tokens is None and total_chars == 0 and configured_output_tokens is None) + or (explicit_max_tokens is None and estimated_input_tokens == 0 and configured_output_tokens is None) else explicit_max_tokens if explicit_max_tokens is not None else configured_output_tokens @@ -1293,6 +1350,24 @@ class _PROXY_MaxParallelRequestsHandler_v3(CustomLogger): return estimated_input_tokens, max_tokens_estimate * self.get_output_candidate_count(data, call_type) + @staticmethod + def _estimate_media_block_tokens( + block: Mapping[str, object], models: tuple[str, ...], fallback_model: str | None + ) -> int: + if block.get("type") == "input_audio": + audio: Final = _callback_kwargs_mapping(block.get("input_audio")) + data: Final = audio.get("data") + return estimate_audio_tokens(data if isinstance(data, str) else None, models, fallback_model=fallback_model) + image: Final = _callback_kwargs_mapping(block.get("image_url")) + url: Final = image.get("url") + detail: Final = image.get("detail") + return estimate_image_tokens( + models, + url if isinstance(url, str) else "", + detail if isinstance(detail, str) else "auto", + fallback_model=fallback_model, + ) + def _is_redis_cluster(self) -> bool: """ Check if the dual cache is using Redis cluster. @@ -3943,22 +4018,27 @@ class _PROXY_MaxParallelRequestsHandler_v3(CustomLogger): try: estimate: Final = max( 0, - int( - token_counter( - model=model or "", - messages=countable_messages, - text=selected_text, - tools=countable_tools, - tool_choice=countable_tool_choice, - use_default_image_token_count=True, + *( + int( + token_counter( + model=tokenizer_model, + messages=countable_messages, + text=selected_text, + tools=countable_tools, + tool_choice=countable_tool_choice, + use_default_image_token_count=True, + ) ) + for tokenizer_model in self._tokenizer_models_resolver(model or "") ), ) return estimate + audio_token_estimate except Exception: # noqa: BLE001 # tokenizer failures degrade to the cheap estimate if call_type in RERANK_API_CALL_TYPES and isinstance(selected_text, str): return max(0, len(selected_text) // DEFAULT_CHARS_PER_TOKEN) - estimated_input_tokens, _ = self._estimate_input_and_output_tokens(data=data, call_type=call_type) + estimated_input_tokens, _ = self._estimate_input_and_output_tokens( + data=data, call_type=call_type, include_media=False + ) return estimated_input_tokens + audio_token_estimate async def _reserve_project_io_tokens_or_raise( @@ -4003,6 +4083,7 @@ class _PROXY_MaxParallelRequestsHandler_v3(CustomLogger): data=data, min_configured_tpm_limit=min_configured_otpm_limit, call_type=call_type, + include_media=False, ) raw_estimated_input_tokens: Final = await offload_token_count(self._estimate_precise_input_tokens)( data=data, model=requested_model, call_type=call_type @@ -4360,12 +4441,13 @@ class _PROXY_MaxParallelRequestsHandler_v3(CustomLogger): # Post-call reconciliation refunds the over-reservation # delta when actual usage comes in below the floor. estimated_tokens: Final = max( - self._estimate_tokens_for_request( + await offload_token_count(self._estimate_tokens_for_request)( data=data, model=requested_model, min_configured_tpm_limit=min_configured_tpm_limit, call_type=call_type, configured_output_tokens=configured_output_tokens, + team_id=user_api_key_dict.team_id, ), 1, ) @@ -4383,13 +4465,14 @@ class _PROXY_MaxParallelRequestsHandler_v3(CustomLogger): ) capped_request: Final = _REQUEST_RATE_LIMIT_DATA.validate_python(data) - ptu_estimated_tokens: Final = self._estimate_ptu_tokens_for_request( + ptu_estimated_tokens: Final = await offload_token_count(self._estimate_ptu_tokens_for_request)( ceiling=stash.ptu_ceiling, data=capped_request, min_configured_tpm_limit=min_configured_tpm_limit, call_type=call_type, configured_output_tokens=configured_output_tokens, raw_estimate=estimated_tokens, + team_id=user_api_key_dict.team_id, ) if stash.ptu_ceiling is not None and ptu_estimated_tokens > stash.ptu_ceiling.tpm_limit: if not reuses_request_slot: diff --git a/litellm/proxy/hooks/responses_id_security.py b/litellm/proxy/hooks/responses_id_security.py index 27b5924c540..771d68a0ea0 100644 --- a/litellm/proxy/hooks/responses_id_security.py +++ b/litellm/proxy/hooks/responses_id_security.py @@ -31,7 +31,7 @@ if TYPE_CHECKING: _RESPONSES_API_PROVIDER_PREFIX: Final = "/openai" -_RESPONSES_API_CREATE_ROUTES: Final = frozenset({"/v1/responses", "/responses"}) +_RESPONSES_API_ROUTES: Final = frozenset({"/v1/responses", "/responses"}) _ADDRESSED_RESPONSE_ID_FIELD_BY_CALL_TYPE: Final[Mapping[str, str]] = MappingProxyType( { "aresponses": "previous_response_id", @@ -104,7 +104,7 @@ def _rewrite_advertised_id( return event -def _is_responses_api_create_route(request_route: str | None) -> bool: +def _streams_response_ids(request_route: str | None) -> bool: if request_route is None: return False canonical: Final = ( @@ -112,7 +112,8 @@ def _is_responses_api_create_route(request_route: str | None) -> bool: if request_route.startswith(_RESPONSES_API_PROVIDER_PREFIX + "/") else request_route ) - return canonical in _RESPONSES_API_CREATE_ROUTES + parent, _, response_id = canonical.rpartition("/") + return canonical in _RESPONSES_API_ROUTES or (parent in _RESPONSES_API_ROUTES and response_id != "") class ResponsesIDSecurity(CustomLogger): @@ -339,7 +340,7 @@ class ResponsesIDSecurity(CustomLogger): async for chunk in response: if ( isinstance(chunk, BaseLiteLLMOpenAIResponseObject) - and _is_responses_api_create_route(user_api_key_dict.request_route) + and _streams_response_ids(user_api_key_dict.request_route) and not general_settings.get("disable_responses_id_security", False) ): chunk = self._encrypt_response_id(chunk, user_api_key_dict, request_encryption_cache) diff --git a/litellm/proxy/litellm_pre_call_utils.py b/litellm/proxy/litellm_pre_call_utils.py index 1e7cdc44c70..14d941ff62c 100644 --- a/litellm/proxy/litellm_pre_call_utils.py +++ b/litellm/proxy/litellm_pre_call_utils.py @@ -32,6 +32,7 @@ from litellm.constants import ( BILLED_RETRY_ATTEMPT_METADATA_KEY, CALLER_SESSION_ID_METADATA_KEY, CLIENT_OUTPUT_CEILING_METADATA_KEY, + COMPLEXITY_ROUTER_CHILD_SESSION_ID_METADATA_KEY, CONSUMED_REQUEST_TAGS_METADATA_KEY, INTERNAL_CALL_ORIGIN_METADATA_KEY, LITELLM_PROXY_MASTER_KEY_ALIAS, @@ -117,6 +118,9 @@ _SESSION_ID_VALUE_RE: Final = re.compile(r"^[a-zA-Z0-9_\-]{8,}$") _SHA256_HEX_RE: Final = re.compile(r"^[0-9a-f]{64}$") +SCHEDULER_PRIORITY_HEADER: Final = "x-litellm-priority" +ROUTER_SCHEDULED_ROUTE_TYPES: Final = frozenset({"acompletion", "atext_completion"}) + # W3C Trace Context traceparent header: https://www.w3.org/TR/trace-context/ # e.g. "00-4bf92f3577b34da6a3ce929d0e0e4736-00f067aa0ba902b7-01" _TRACEPARENT_RE: Final = re.compile(r"^[0-9a-f]{2}-([0-9a-f]{32})-[0-9a-f]{16}-[0-9a-f]{2}$", re.IGNORECASE) @@ -210,13 +214,46 @@ def _caller_session_beside_trace_header( return get_chain_id_from_headers(session_headers) or _caller_body_session_id(data, metadata_variable_name) -def _drop_client_caller_session(request_body: Mapping[str, object]) -> None: +def _child_tier_session_metadata( + normalized_headers: Mapping[str, str], data: Mapping[str, object], metadata_variable_name: str +) -> Mapping[str, str | None]: + parent: Final = normalized_headers.get("x-parent-session-id") + if not parent or not _SESSION_ID_VALUE_RE.fullmatch(parent): + return {} + own_headers: Final = { + key: value + for key, value in normalized_headers.items() + if key not in ("x-parent-session-id", "x-litellm-trace-id") + } + active: Final = data.get(metadata_variable_name) + inactive: Final = data.get("litellm_metadata") + inactive_session: Final = ( + _caller_body_session_id(data, "litellm_metadata") + if metadata_variable_name == "metadata" + and not (isinstance(active, Mapping) and "session_id" in active) + and isinstance(inactive, Mapping) + else None + ) + own_session: Final = ( + get_chain_id_from_headers(own_headers) + or _get_anthropic_session_id_from_metadata(data.get("metadata")) + or _caller_body_session_id(data, metadata_variable_name) + or inactive_session + or _session_id_from_baggage(normalized_headers.get("baggage", "")) + ) + return {COMPLEXITY_ROUTER_CHILD_SESSION_ID_METADATA_KEY: own_session if own_session != parent else None} + + +def _drop_client_session_metadata(request_body: Mapping[str, object]) -> None: for metadata_key in ("metadata", "litellm_metadata"): if isinstance(metadata := request_body.get(metadata_key), dict): - metadata.pop(CALLER_SESSION_ID_METADATA_KEY, None) + for key in (CALLER_SESSION_ID_METADATA_KEY, COMPLEXITY_ROUTER_CHILD_SESSION_ID_METADATA_KEY): + cast(dict[str, object], metadata).pop(key, None) # cast-ok: request metadata is a str-keyed JSON object -_PROXY_SET_METADATA_KEYS: Final = frozenset({CALLER_SESSION_ID_METADATA_KEY, BAGGAGE_MAPPED_TAGS_METADATA_KEY}) +_PROXY_SET_METADATA_KEYS: Final = frozenset( + {CALLER_SESSION_ID_METADATA_KEY, BAGGAGE_MAPPED_TAGS_METADATA_KEY, COMPLEXITY_ROUTER_CHILD_SESSION_ID_METADATA_KEY} +) _METADATA_TAGS_ADAPTER: Final = TypeAdapter(tuple[object, ...]) @@ -363,6 +400,8 @@ _UNTRUSTED_ROOT_CONTROL_FIELDS: Final = ( "fallback_depth", "_target_order", "attempted_targets", + "_excluded_deployment_ids", + "_retry_skipped_deployment_ids", "proxy_server_request", "standard_logging_object", "secret_fields", @@ -444,6 +483,7 @@ _UNTRUSTED_METADATA_CONTROL_FIELDS: Final = ( "_pipeline_managed_guardrails", "client_disconnected", "error_information", + "_failover_excluded_ids", PRE_CALL_EXECUTED_GUARDRAILS_KEY, ) @@ -651,7 +691,7 @@ def _metadata_string_tags(metadata_objects: Iterable[Mapping[str, object]]) -> t def _strip_untrusted_request_header_controls( - headers: Any, + headers: object, *, allow_client_message_redaction_opt_out: bool = False, ) -> None: @@ -1412,12 +1452,34 @@ def _tenant_service_name(user_api_key_dict: UserAPIKeyAuth) -> str | None: ) +def litellm_auth_header_name(headers: Headers) -> str: + if "x-litellm-api-key" in headers: + return "x-litellm-api-key" + if "authorization" in headers: + return "authorization" + return "x-api-key" + + +def forwarded_anthropic_oauth_token(headers: Headers) -> str | None: + from litellm.llms.anthropic.common_utils import is_anthropic_oauth_key + + forwarded: Final = clean_headers(headers, authenticated_with_header=litellm_auth_header_name(headers)) + return next( + ( + value.removeprefix("Bearer ") + for header, value in forwarded.items() + if header.lower() == "authorization" and is_anthropic_oauth_key(value) + ), + None, + ) + + def clean_headers( headers: Headers, litellm_key_header_name: str | None = None, forward_llm_provider_auth_headers: bool = False, authenticated_with_header: str | None = None, -) -> dict: +) -> dict[str, str]: """ Removes litellm api key from headers @@ -1633,7 +1695,7 @@ class LiteLLMProxyRequestSetup: @staticmethod def add_internal_user_from_user_mapping( - general_settings: dict | None, + general_settings: Mapping[str, object] | None, user_api_key_dict: UserAPIKeyAuth, headers: dict, ) -> UserAPIKeyAuth: @@ -1652,7 +1714,7 @@ class LiteLLMProxyRequestSetup: return user_api_key_dict @staticmethod - def get_user_from_headers(headers: dict, general_settings: dict | None = None) -> str | None: + def get_user_from_headers(headers: dict, general_settings: Mapping[str, object] | None = None) -> str | None: """ Get the user from the specified header if `general_settings.user_header_name` is set. """ @@ -1673,7 +1735,9 @@ class LiteLLMProxyRequestSetup: return user @staticmethod - def get_openai_org_id_from_headers(headers: dict, general_settings: dict | None = None) -> str | None: + def get_openai_org_id_from_headers( + headers: dict, general_settings: Mapping[str, object] | None = None + ) -> str | None: """ Get the OpenAI Org ID from the headers. """ @@ -1764,7 +1828,7 @@ class LiteLLMProxyRequestSetup: headers: dict, request_data: Mapping[str, object], user_api_key_dict: UserAPIKeyAuth, - general_settings: dict[str, object] | None = None, + general_settings: Mapping[str, object] | None = None, ) -> LitellmDataForBackendLLMCall: """ - Adds user from headers @@ -1830,7 +1894,7 @@ class LiteLLMProxyRequestSetup: metadata_from_headers: Final = LitellmMetadataFromRequestHeaders() request_body: Final = cast(Mapping[str, object], data) # cast-ok: request body is a str-keyed JSON object - _drop_client_caller_session(request_body) + _drop_client_session_metadata(request_body) spend_logs_metadata: Final = LiteLLMProxyRequestSetup._get_spend_logs_metadata_from_request_headers(headers) if spend_logs_metadata is not None: metadata_from_headers["spend_logs_metadata"] = spend_logs_metadata @@ -1845,6 +1909,9 @@ class LiteLLMProxyRequestSetup: agent_id_from_header: Final = headers.get("x-litellm-agent-id") # Explicit litellm headers take precedence; fall back to any x-*-session-id header. chain_id: Final = get_chain_id_from_headers(dict(headers)) + child_tier_metadata: Final = _child_tier_session_metadata( + normalized_headers, request_body, _metadata_variable_name + ) if agent_id_from_header: metadata_from_headers["agent_id"] = agent_id_from_header @@ -1914,9 +1981,15 @@ class LiteLLMProxyRequestSetup: if isinstance(data[_metadata_variable_name], dict): data[_metadata_variable_name].update( - {**metadata_from_headers, CALLER_SESSION_ID_METADATA_KEY: caller_session_beside_trace} - if caller_session_beside_trace - else metadata_from_headers + { + **metadata_from_headers, + **child_tier_metadata, + **( + {CALLER_SESSION_ID_METADATA_KEY: caller_session_beside_trace} + if caller_session_beside_trace + else {} + ), + } ) return data @@ -2510,26 +2583,13 @@ async def add_litellm_data_to_request( forward_llm_auth = general_settings.get("forward_llm_provider_auth_headers", False) if not forward_llm_auth: forward_llm_auth = getattr(litellm, "forward_llm_provider_auth_headers", False) - # Determine which header was used for authentication - # This enables forwarding provider keys (e.g., x-api-key) when they weren't used for LiteLLM auth - authenticated_with_header = None - if "x-litellm-api-key" in request.headers: - # If x-litellm-api-key is present, it was used for auth - authenticated_with_header = "x-litellm-api-key" - elif "authorization" in request.headers: - # Authorization header was used for auth - authenticated_with_header = "authorization" - else: - # x-api-key or another header was used for auth - authenticated_with_header = "x-api-key" - _headers: Final[dict[str, str]] = clean_headers( request.headers, litellm_key_header_name=( general_settings.get("litellm_key_header_name") if general_settings is not None else None ), forward_llm_provider_auth_headers=forward_llm_auth, - authenticated_with_header=authenticated_with_header, + authenticated_with_header=litellm_auth_header_name(request.headers), ) _strip_untrusted_request_header_controls( _headers, @@ -2964,13 +3024,7 @@ async def add_litellm_data_to_request( getattr(request.state, "litellm_roi_estimator", False) is True ) - verbose_proxy_logger.debug( - "[PROXY] returned data from litellm_pre_call_utils: %s", - data, - ) - # Team/Project credential overrides from model_config - # Placed after the debug log to avoid leaking credential secrets in logs _apply_credential_overrides_from_model_config( data=data, user_api_key_dict=user_api_key_dict, @@ -3230,7 +3284,7 @@ def _per_user_credential_names_for_groups( GITHUB_COPILOT_AUTH_TYPE_KEY, GITHUB_COPILOT_PER_USER_AUTH_TYPE, ) - from litellm.router_utils.auto_router_model_naming import classify_strategy_router_model + from litellm.router_strategy.auto_router.auto_router_model_naming import classify_strategy_router_model names: Final[list[str]] = [] # mutable-ok: accumulates one name per per-user deployment for group in model_groups: diff --git a/litellm/proxy/management_endpoints/auto_router_endpoints.py b/litellm/proxy/management_endpoints/auto_router_endpoints.py index 9c46e711cf6..3dceab6b7f7 100644 --- a/litellm/proxy/management_endpoints/auto_router_endpoints.py +++ b/litellm/proxy/management_endpoints/auto_router_endpoints.py @@ -49,6 +49,8 @@ from litellm.proxy.management_endpoints.common_daily_activity import daily_activ from litellm.proxy.management_helpers.auto_router_permissions import ( authorize_member_auto_router_dependencies, authorize_member_auto_router_team, + auto_router_environment_reference_error, + raise_auto_router_environment_reference_error, validate_member_auto_router_config, ) from litellm.repositories.autorouter_session_repository import AutoRouterSessionRepository @@ -58,16 +60,16 @@ from litellm.repositories.table_repositories import PrismaTableRepository from litellm.repositories.team_repository import TeamRepository from litellm.repositories.user_repository import UserRepository from litellm.repositories.verification_token_repository import VerificationTokenRepository +from litellm.router_strategy.auto_router.auto_router_model_naming import ( + StrategyRouterDependencyRole, + classify_strategy_router_model, + strategy_router_dependencies, +) from litellm.router_strategy.complexity_router import ComplexityRouter from litellm.router_strategy.complexity_router.request_models import ( AutoRouterRoutingTestRequest, RequestComplexityRouterConfig, ) -from litellm.router_utils.auto_router_model_naming import ( - StrategyRouterDependencyRole, - classify_strategy_router_model, - strategy_router_dependencies, -) from litellm.types.llms.base import LiteLLMBaseModel from litellm.types.management_endpoints.auto_router_endpoints import ( SHADOW_EVAL_TURN_VALVE, @@ -229,9 +231,12 @@ def _shadow_eval_attempts(prisma_client: "PrismaClient") -> _ShadowEvalAttemptTa return _ShadowEvalAttemptRepository(prisma_client).table +_RAW_ROWS: Final = TypeAdapter(Sequence[dict[str, object]], config=ConfigDict(strict=True)) + + async def _query_raw(prisma_client: "PrismaClient", query: str, *args: object) -> Sequence[Mapping[str, object]]: async with db_span("auto_router_report_query", sql_relation(query)): - return await prisma_client.db.query_raw(query, *args) + return _RAW_ROWS.validate_python(await prisma_client.db.query_raw(query, *args)) async def _execute_raw(prisma_client: "PrismaClient", query: str, *args: object) -> int: @@ -402,7 +407,11 @@ async def validate_complexity_router_config( """ member_team: Final = await _authorize_router_dry_run(user_api_key_dict=user_api_key_dict, team_id=data.team_id) - from litellm.router_utils.auto_router_model_naming import ( + raise_auto_router_environment_reference_error( + auto_router_environment_reference_error(data.complexity_router_config, user_api_key_dict) + ) + + from litellm.router_strategy.auto_router.auto_router_model_naming import ( validate_complexity_router_config_write, ) @@ -560,6 +569,12 @@ async def preview_auto_router_routing( detail={"error": CommonProxyErrors.no_llm_router.value}, ) resolved: Final = await _resolve_saved_routing_test(data, user_api_key_dict, llm_router) + if data.saved_model_id is None: + raise_auto_router_environment_reference_error( + auto_router_environment_reference_error( + data.complexity_router_config.model_dump(exclude_none=True), user_api_key_dict + ) + ) actor: Final = ( await _authorize_member_dry_run_config( config=resolved.complexity_router_config.model_dump(exclude_none=True), diff --git a/litellm/proxy/management_endpoints/common_daily_activity.py b/litellm/proxy/management_endpoints/common_daily_activity.py index f948a49441a..66f386b792d 100644 --- a/litellm/proxy/management_endpoints/common_daily_activity.py +++ b/litellm/proxy/management_endpoints/common_daily_activity.py @@ -3,6 +3,7 @@ from collections.abc import Awaitable, Callable, Mapping, Sequence from collections.abc import Set as AbstractSet from dataclasses import dataclass, replace from datetime import date, datetime, timedelta +from itertools import groupby from types import MappingProxyType from typing import Final, Literal, NoReturn, Protocol @@ -28,6 +29,10 @@ from litellm.types.proxy.management_endpoints.common_daily_activity import ( DailySpendData, DailySpendMetadata, GroupedData, + GuardrailKeyMetric, + GuardrailMetadata, + GuardrailMetric, + GuardrailSpendMetrics, KeyMetadata, KeyMetricWithMetadata, MetricWithMetadata, @@ -39,6 +44,7 @@ from litellm.types.repositories.daily_activity import ( DailyActivityTable, EntityRollupRow, GroupingSetsRow, + GuardrailSpendRow, KeyMetadataRow, RollupMetricsRow, SpendLogsWindow, @@ -1013,17 +1019,68 @@ def _fold_entity_rollups_sync( ) +def _guardrail_metric(day: DailySpendData, rows: Sequence[GuardrailSpendRow]) -> GuardrailMetric: + return GuardrailMetric( + metrics=GuardrailSpendMetrics( + spend=sum(row.spend for row in rows), + untracked_units=sum(row.untracked_units for row in rows), + ), + metadata=GuardrailMetadata(guardrail_name=rows[0].guardrail_name), + api_key_breakdown={ + row.api_key: GuardrailKeyMetric( + metrics=GuardrailSpendMetrics(spend=row.spend, untracked_units=row.untracked_units), + metadata=day.breakdown.api_keys[row.api_key].metadata, + ) + for row in rows + if row.api_key in day.breakdown.api_keys + }, + ) + + +def _day_with_guardrails(day: DailySpendData, rows: Sequence[GuardrailSpendRow]) -> DailySpendData: + by_guardrail: Final = groupby(sorted(rows, key=lambda row: row.guardrail_id), key=lambda row: row.guardrail_id) + guardrails: Final = {guardrail_id: _guardrail_metric(day, tuple(group)) for guardrail_id, group in by_guardrail} + return day.model_copy(update={"breakdown": day.breakdown.model_copy(update={"guardrails": guardrails})}) + + +def _with_guardrail_breakdown( + results: Sequence[DailySpendData], rows: Sequence[GuardrailSpendRow] +) -> tuple[DailySpendData, ...]: + rows_by_date: Final = MappingProxyType( + {day: tuple(group) for day, group in groupby(sorted(rows, key=lambda row: row.date), key=lambda row: row.date)} + ) + return tuple(_day_with_guardrails(day, rows_by_date.get(day.date.strftime("%Y-%m-%d"), ())) for day in results) + + +async def _guardrail_spend_or_empty( + repository: DailyActivityRepository, scope: DailyActivityScope +) -> tuple[GuardrailSpendRow, ...]: + from prisma.errors import PrismaError + + try: + return await repository.guardrail_spend(scope) + except PrismaError as exc: + verbose_proxy_logger.warning("Returning daily activity without its guardrail breakdown: %s", exc) + return () + + async def get_daily_activity_aggregated( repository: DailyActivityRepository, scope: DailyActivityScope, *, entity_metadata_field: Mapping[str, dict[str, object]] | None = None, include_entity_breakdown: bool = False, + include_guardrail_breakdown: bool = False, api_key_limit: int = constants.USAGE_TOP_API_KEYS_DEFAULT, ) -> SpendAnalyticsPaginatedResponse: try: - aggregated_rows: Final = await repository.aggregated( - scope, include_entity_breakdown=include_entity_breakdown, api_key_limit=api_key_limit + aggregated_rows, guardrail_rows = await asyncio.gather( + repository.aggregated( + scope, include_entity_breakdown=include_entity_breakdown, api_key_limit=api_key_limit + ), + _guardrail_spend_or_empty(repository, scope) + if include_guardrail_breakdown and not scope.model + else asyncio.sleep(0, result=()), ) records: Final = aggregated_rows.grouping_rows aggregated: Final = await _aggregate_grouping_sets_records( @@ -1058,8 +1115,13 @@ async def get_daily_activity_aggregated( api_key_metadata=entity_key_metadata, entity_metadata_field=entity_metadata_field, ) + results: Final = ( + list(await asyncio.to_thread(_with_guardrail_breakdown, aggregated["results"], guardrail_rows)) + if guardrail_rows + else aggregated["results"] + ) return SpendAnalyticsPaginatedResponse( - results=aggregated["results"], + results=results, metadata=DailySpendMetadata( total_spend=aggregated["totals"].spend, total_flat_cost=aggregated["totals"].flat_cost, diff --git a/litellm/proxy/management_endpoints/daily_activity_routes.py b/litellm/proxy/management_endpoints/daily_activity_routes.py index 842873129e4..79e515944ce 100644 --- a/litellm/proxy/management_endpoints/daily_activity_routes.py +++ b/litellm/proxy/management_endpoints/daily_activity_routes.py @@ -300,6 +300,7 @@ def _register_aggregated_route(router: APIRouter, resolver: EntityScopeResolver, resolved.scope, entity_metadata_field=resolved.entity_metadata, include_entity_breakdown=resolver.include_entity_breakdown, + include_guardrail_breakdown=resolver.include_guardrail_breakdown, api_key_limit=api_key_limit, ) if resolver.entity != "team": diff --git a/litellm/proxy/management_endpoints/daily_activity_scopes.py b/litellm/proxy/management_endpoints/daily_activity_scopes.py index bc373388a4e..77246f5dda6 100644 --- a/litellm/proxy/management_endpoints/daily_activity_scopes.py +++ b/litellm/proxy/management_endpoints/daily_activity_scopes.py @@ -56,6 +56,7 @@ class EntityScopeResolver: resolve: EntityScopeResolve include_entity_breakdown: bool operation_names: OperationNames + include_guardrail_breakdown: bool = False def _query_ids(value: str | None) -> tuple[str, ...] | None: @@ -364,6 +365,7 @@ USER_RESOLVER = EntityScopeResolver( query=_user_query, resolve=_resolve_user, include_entity_breakdown=False, + include_guardrail_breakdown=True, operation_names=MappingProxyType( { "aggregated": "get_user_daily_activity_aggregated", @@ -385,6 +387,7 @@ TEAM_RESOLVER = EntityScopeResolver( query=_team_query, resolve=_resolve_team, include_entity_breakdown=True, + include_guardrail_breakdown=True, operation_names=MappingProxyType( { "aggregated": "get_team_daily_activity_aggregated", @@ -423,6 +426,7 @@ ORGANIZATION_RESOLVER = EntityScopeResolver( query=_organization_query, resolve=_resolve_organization, include_entity_breakdown=True, + include_guardrail_breakdown=True, operation_names=MappingProxyType( { "aggregated": "get_organization_daily_activity_aggregated", diff --git a/litellm/proxy/management_endpoints/internal_user_endpoints.py b/litellm/proxy/management_endpoints/internal_user_endpoints.py index d6bf9220551..bb901f22649 100644 --- a/litellm/proxy/management_endpoints/internal_user_endpoints.py +++ b/litellm/proxy/management_endpoints/internal_user_endpoints.py @@ -46,6 +46,7 @@ from litellm.proxy.auth.password_policy import ( ) from litellm.proxy.auth.user_api_key_auth import user_api_key_auth from litellm.proxy.common_utils.auth_cache_invalidation_pubsub import evict_and_broadcast +from litellm.proxy.common_utils.openai_error_payload import proxy_exception_for from litellm.proxy.common_utils.user_api_key_cache import ( AUTH_OBJECTS_TARGET, object_permission_cache_key, @@ -499,7 +500,7 @@ async def new_user( - permissions: Optional[dict] - [Not Implemented Yet] User-specific permissions, eg. turning off pii masking. - metadata: Optional[dict] - Metadata for user, store information for user. Example metadata = {"team": "core-infra", "app": "app2", "email": "ishaan@berri.ai" } - max_parallel_requests: Optional[int] - Rate limit a user based on the number of parallel requests. Raises 429 error, if user's parallel requests > x. - - model_max_budget: Optional[dict] - Model-specific max budget for user. [Docs](https://docs.litellm.ai/docs/proxy/users#add-model-specific-budgets-to-keys) + - model_max_budget: Optional[dict] - Model-specific max budget for user, keyed by model name, `*` pattern, or model access group. [Docs](https://docs.litellm.ai/docs/proxy/users#add-model-specific-budgets-to-keys) - budget_fallbacks: Optional[Dict[str, List[str]]] - Per-model fallback chain tried in order when that model's own `model_max_budget` is exceeded, e.g. {"gpt-4o": ["gpt-4o-mini"]}. - model_rpm_limit: Optional[float] - Model-specific rpm limit for user. [Docs](https://docs.litellm.ai/docs/proxy/users#add-model-specific-limits-to-keys) - mcp_rpm_limit: Optional[dict] - Per-MCP-server rpm limit, keyed by MCP server name {"github": 100, "slack": 200}. Enforced for keys and teams only; values set on a user are stored but not enforced per user. @@ -1702,7 +1703,7 @@ async def user_update( - permissions: Optional[dict] - [Not Implemented Yet] User-specific permissions, eg. turning off pii masking. - metadata: Optional[dict] - Metadata for user, store information for user. Example metadata = {"team": "core-infra", "app": "app2", "email": "ishaan@berri.ai" } - max_parallel_requests: Optional[int] - Rate limit a user based on the number of parallel requests. Raises 429 error, if user's parallel requests > x. - - model_max_budget: Optional[dict] - Model-specific max budget for user. [Docs](https://docs.litellm.ai/docs/proxy/users#add-model-specific-budgets-to-keys) + - model_max_budget: Optional[dict] - Model-specific max budget for user, keyed by model name, `*` pattern, or model access group. [Docs](https://docs.litellm.ai/docs/proxy/users#add-model-specific-budgets-to-keys) - budget_fallbacks: Optional[Dict[str, List[str]]] - Per-model fallback chain tried in order when that model's own `model_max_budget` is exceeded, e.g. {"gpt-4o": ["gpt-4o-mini"]}. - model_rpm_limit: Optional[float] - Model-specific rpm limit for user. [Docs](https://docs.litellm.ai/docs/proxy/users#add-model-specific-limits-to-keys) - mcp_rpm_limit: Optional[dict] - Per-MCP-server rpm limit, keyed by MCP server name {"github": 100, "slack": 200}. Enforced for keys and teams only; values set on a user are stored but not enforced per user. @@ -1729,21 +1730,9 @@ async def user_update( except Exception as e: verbose_proxy_logger.exception("litellm.proxy.proxy_server.user_update(): Exception occured - %s", e) verbose_proxy_logger.debug(traceback.format_exc()) - if isinstance(e, HTTPException): - raise ProxyException( - message=getattr(e, "detail", f"Authentication Error({e})"), - type=ProxyErrorTypes.auth_error, - param=getattr(e, "param", "None"), - code=getattr(e, "status_code", status.HTTP_400_BAD_REQUEST), - ) - elif isinstance(e, ProxyException): - raise e - raise ProxyException( - message="Authentication Error, " + str(e), - type=ProxyErrorTypes.auth_error, - param=getattr(e, "param", "None"), - code=status.HTTP_400_BAD_REQUEST, - ) + if isinstance(e, ProxyException): + raise + raise proxy_exception_for(e, default_status_code=status.HTTP_400_BAD_REQUEST) from e async def bulk_update_processed_users( diff --git a/litellm/proxy/management_endpoints/key_management_endpoints.py b/litellm/proxy/management_endpoints/key_management_endpoints.py index f7b72b263d4..55e59ca5776 100644 --- a/litellm/proxy/management_endpoints/key_management_endpoints.py +++ b/litellm/proxy/management_endpoints/key_management_endpoints.py @@ -75,6 +75,7 @@ from litellm.proxy.common_utils.config_sync_pubsub import ( coordination_redis_cache, publish_config_change, ) +from litellm.proxy.common_utils.openai_error_payload import proxy_exception_for from litellm.proxy.common_utils.rbac_utils import check_org_admin_can_generate_keys from litellm.proxy.common_utils.timezone_utils import get_budget_reset_time from litellm.proxy.common_utils.user_api_key_cache import AUTH_OBJECTS_TARGET, UserApiKeyCache @@ -2328,7 +2329,7 @@ async def generate_key_fn( - throttle_on_budget_exceeded: Optional[bool] - When the key exceeds its max_budget, throttle its tpm/rpm to the global budget_exceeded_throttle_percentage instead of blocking the key entirely. - enable_prompt_caching: Optional[bool] - Auto-inject prompt caching breakpoints (Anthropic cache_control markers) on requests made with this key. Supported Claude models on Anthropic, Bedrock, Vertex AI, and Azure AI only. - permissions: Optional[dict] - key-specific permissions. Currently just used for turning off pii masking (if connected). Example - {"pii": false} - - model_max_budget: Optional[Dict[str, BudgetConfig]] - Model-specific budgets {"gpt-4": {"budget_limit": 0.0005, "time_period": "30d"}}}. IF null or {} then no model specific budget. + - model_max_budget: Optional[Dict[str, BudgetConfig]] - Model-specific budgets keyed by model name, `*` pattern like "claude-opus*", or model access group, e.g. {"gpt-4": {"budget_limit": 0.0005, "time_period": "30d"}}}. IF null or {} then no model specific budget. - budget_fallbacks: Optional[Dict[str, List[str]]] - Per-model fallback chain tried in order when that model's own `model_max_budget` is exceeded, e.g. {"gpt-4o": ["gpt-4o-mini"]}. - model_rpm_limit: Optional[dict] - key-specific model rpm limit. Example - {"text-davinci-002": 1000, "gpt-3.5-turbo": 1000}. IF null or {} then no model specific rpm limit. - model_tpm_limit: Optional[dict] - key-specific model tpm limit. Example - {"text-davinci-002": 1000, "gpt-3.5-turbo": 1000}. IF null or {} then no model specific tpm limit. @@ -2538,7 +2539,7 @@ async def generate_service_account_key_fn( - metadata: Optional[dict] - Metadata for key, store information for key. Example metadata = {"team": "core-infra", "app": "app2", "email": "ishaan@berri.ai" } - guardrails: Optional[List[str]] - List of active guardrails for the key - permissions: Optional[dict] - key-specific permissions. Currently just used for turning off pii masking (if connected). Example - {"pii": false} - - model_max_budget: Optional[Dict[str, BudgetConfig]] - Model-specific budgets {"gpt-4": {"budget_limit": 0.0005, "time_period": "30d"}}}. IF null or {} then no model specific budget. + - model_max_budget: Optional[Dict[str, BudgetConfig]] - Model-specific budgets keyed by model name, `*` pattern like "claude-opus*", or model access group, e.g. {"gpt-4": {"budget_limit": 0.0005, "time_period": "30d"}}}. IF null or {} then no model specific budget. - budget_fallbacks: Optional[Dict[str, List[str]]] - Per-model fallback chain tried in order when that model's own `model_max_budget` is exceeded, e.g. {"gpt-4o": ["gpt-4o-mini"]}. - model_rpm_limit: Optional[dict] - key-specific model rpm limit. Example - {"text-davinci-002": 1000, "gpt-3.5-turbo": 1000}. IF null or {} then no model specific rpm limit. - model_tpm_limit: Optional[dict] - key-specific model tpm limit. Example - {"text-davinci-002": 1000, "gpt-3.5-turbo": 1000}. IF null or {} then no model specific tpm limit. @@ -3855,7 +3856,7 @@ async def update_key_fn( - enforced_params: Optional[List[str]] - List of enforced params for the key (Enterprise only). [Docs](https://docs.litellm.ai/docs/proxy/enterprise#enforce-required-params-for-llm-requests) - spend: Optional[float] - Amount spent by key - max_budget: Optional[float] - Max budget for key - - model_max_budget: Optional[Dict[str, BudgetConfig]] - Model-specific budgets {"gpt-4": {"budget_limit": 0.0005, "time_period": "30d"}} + - model_max_budget: Optional[Dict[str, BudgetConfig]] - Model-specific budgets keyed by model name, `*` pattern like "claude-opus*", or model access group, e.g. {"gpt-4": {"budget_limit": 0.0005, "time_period": "30d"}} - budget_fallbacks: Optional[Dict[str, List[str]]] - Per-model fallback chain tried in order when that model's own `model_max_budget` is exceeded, e.g. {"gpt-4o": ["gpt-4o-mini"]}. - budget_duration: Optional[str] - Budget reset period ("30d", "1h", etc.) - soft_budget: Optional[float] - Soft budget limit (warning vs. hard stop). Will trigger a slack alert when this soft budget is reached. Set to null to remove the soft budget. @@ -4087,21 +4088,9 @@ async def update_key_fn( # update based on remaining passed in values except Exception as e: verbose_proxy_logger.exception("litellm.proxy.proxy_server.update_key_fn(): Exception occured - %s", e) - if isinstance(e, HTTPException): - raise ProxyException( - message=getattr(e, "detail", f"Authentication Error({e})"), - type=ProxyErrorTypes.auth_error, - param=getattr(e, "param", "None"), - code=getattr(e, "status_code", status.HTTP_400_BAD_REQUEST), - ) - elif isinstance(e, ProxyException): - raise e - raise ProxyException( - message="Authentication Error, " + str(e), - type=ProxyErrorTypes.auth_error, - param=getattr(e, "param", "None"), - code=status.HTTP_400_BAD_REQUEST, - ) + if isinstance(e, ProxyException): + raise + raise proxy_exception_for(e, default_status_code=status.HTTP_400_BAD_REQUEST) from e @router.post( @@ -6303,7 +6292,7 @@ async def regenerate_key_fn( - tags: Optional[List[str]] - Tags for organizing keys (Enterprise only) - spend: Optional[float] - Amount spent by key - max_budget: Optional[float] - Max budget for key - - model_max_budget: Optional[Dict[str, BudgetConfig]] - Model-specific budgets {"gpt-4": {"budget_limit": 0.0005, "time_period": "30d"}} + - model_max_budget: Optional[Dict[str, BudgetConfig]] - Model-specific budgets keyed by model name, `*` pattern like "claude-opus*", or model access group, e.g. {"gpt-4": {"budget_limit": 0.0005, "time_period": "30d"}} - budget_fallbacks: Optional[Dict[str, List[str]]] - Per-model fallback chain tried in order when that model's own `model_max_budget` is exceeded, e.g. {"gpt-4o": ["gpt-4o-mini"]}. - budget_duration: Optional[str] - Budget reset period ("30d", "1h", etc.) - soft_budget: Optional[float] - Soft budget limit (warning vs. hard stop). Will trigger a slack alert when this soft budget is reached. @@ -7244,21 +7233,9 @@ async def list_keys( except Exception as e: verbose_proxy_logger.exception("Error in list_keys: %s", e) - if isinstance(e, HTTPException): - raise ProxyException( - message=getattr(e, "detail", f"error({e})"), - type=ProxyErrorTypes.internal_server_error, - param=getattr(e, "param", "None"), - code=getattr(e, "status_code", fastapi.status.HTTP_500_INTERNAL_SERVER_ERROR), - ) - elif isinstance(e, ProxyException): - raise e - raise ProxyException( - message="Authentication Error, " + str(e), - type=ProxyErrorTypes.internal_server_error, - param=getattr(e, "param", "None"), - code=fastapi.status.HTTP_500_INTERNAL_SERVER_ERROR, - ) + if isinstance(e, ProxyException): + raise + raise proxy_exception_for(e, default_status_code=fastapi.status.HTTP_500_INTERNAL_SERVER_ERROR) from e async def _apply_non_admin_alias_scope( @@ -7402,21 +7379,9 @@ async def key_aliases( except Exception as e: verbose_proxy_logger.exception("Error in key_aliases: %s", e) - if isinstance(e, HTTPException): - raise ProxyException( - message=getattr(e, "detail", f"error({e})"), - type=ProxyErrorTypes.internal_server_error, - param=getattr(e, "param", "None"), - code=getattr(e, "status_code", status.HTTP_500_INTERNAL_SERVER_ERROR), - ) - elif isinstance(e, ProxyException): - raise e - raise ProxyException( - message="Authentication Error, " + str(e), - type=ProxyErrorTypes.internal_server_error, - param=getattr(e, "param", "None"), - code=status.HTTP_500_INTERNAL_SERVER_ERROR, - ) + if isinstance(e, ProxyException): + raise + raise proxy_exception_for(e, default_status_code=status.HTTP_500_INTERNAL_SERVER_ERROR) from e def _validate_sort_params( diff --git a/litellm/proxy/management_endpoints/model_management_endpoints.py b/litellm/proxy/management_endpoints/model_management_endpoints.py index e625ea6f9f2..e7ad7d04070 100644 --- a/litellm/proxy/management_endpoints/model_management_endpoints.py +++ b/litellm/proxy/management_endpoints/model_management_endpoints.py @@ -12,6 +12,7 @@ model/{model_id}/update - PATCH endpoint for model update. import asyncio import datetime +import itertools import json from collections.abc import AsyncGenerator, Awaitable, Callable, Mapping, Sequence from contextlib import AbstractAsyncContextManager, asynccontextmanager, suppress @@ -42,6 +43,7 @@ from litellm.litellm_core_utils.ptu_pricing import ( ptu_config_error, ) from litellm.litellm_core_utils.sensitive_data_masker import redact_credentials_in_payload +from litellm.llms.azure.ptu_capacity import is_str_keyed_mapping from litellm.proxy._types import ( BlockModelRequest, CommonProxyErrors, @@ -75,6 +77,7 @@ from litellm.proxy.common_utils.encrypt_decrypt_utils import ( decrypt_value_helper, encrypt_value_helper, ) +from litellm.proxy.common_utils.openai_error_payload import proxy_exception_for from litellm.proxy.common_utils.user_api_key_cache import UserApiKeyCache from litellm.proxy.db.routing_prisma_wrapper import WriterPinnedClient from litellm.proxy.management.teams.authz import TEAM_ADMIN_ONLY, is_team_admin @@ -100,8 +103,22 @@ from litellm.proxy.management_helpers.auto_router_permissions import ( authorize_member_auto_router_dependencies, authorize_member_auto_router_team, authorize_member_auto_router_write, + auto_router_environment_reference_error, + raise_auto_router_environment_reference_error, ) from litellm.proxy.management_helpers.model_allowlist_rename_sync import sync_model_allowlists_for_renamed_model +from litellm.proxy.management_helpers.model_quota_policy import ( + ENFORCE_PROJECT_MODEL_QUOTA_SETTING, + ModelQuotaPolicy, + QuotaLimit, + deployment_route, + exempts_any_route, + limits_added_by_team_write, + parse_model_quota_setting, + required_limits, + team_write_serves, + unmet_limits, +) from litellm.proxy.spend_tracking.ptu_feature_flag import ( PTU_COST_ATTRIBUTION_ENV_VAR, is_ptu_cost_attribution_enabled, @@ -111,9 +128,27 @@ from litellm.repositories.chunked_in import find_many_in from litellm.repositories.credentials_repository import CredentialsRepository from litellm.repositories.model_repository import ModelRepository from litellm.repositories.prisma_protocols import TableActions +from litellm.repositories.project_repository import ProjectRepository from litellm.repositories.table_repositories import ModelTableRepository from litellm.repositories.team_repository import TeamRepository from litellm.router import Router +from litellm.router_strategy.auto_router.auto_router_model_naming import ( + GATED_AUTO_ROUTER_CAPABILITIES, + STRATEGY_ROUTER_PARAM_FIELDS, + GatedAutoRouterCapability, + capability_limit_violation, + carries_complexity_router_settings, + count_capability_routers, + gated_capabilities_of, + is_complexity_router_model, + validate_complexity_router_config_placement, + validate_complexity_router_config_write, + validate_strategy_router_model_write, +) +from litellm.router_strategy.auto_router.auto_router_tuning_baseline import ( + is_mutable_tuned_candidate, + tuning_quota_violation, +) from litellm.router_strategy.complexity_router import ( DEFAULT_CLASSIFIER_CONTEXT_WINDOW_SIZE, ClassificationRubric, @@ -127,20 +162,6 @@ from litellm.router_strategy.complexity_router import ( normalize_classification_prompt, ) from litellm.router_strategy.complexity_router.config import resolve_complexity_router_config_write -from litellm.router_utils.auto_router_model_naming import ( - GATED_AUTO_ROUTER_CAPABILITIES, - STRATEGY_ROUTER_PARAM_FIELDS, - GatedAutoRouterCapability, - capability_limit_violation, - carries_complexity_router_settings, - count_capability_routers, - gated_capabilities_of, - is_complexity_router_model, - validate_complexity_router_config_placement, - validate_complexity_router_config_write, - validate_strategy_router_model_write, -) -from litellm.router_utils.auto_router_tuning_baseline import is_mutable_tuned_candidate, tuning_quota_violation from litellm.types.llms.base import LiteLLMBaseModel from litellm.types.llms.bedrock import AwsSessionTag from litellm.types.proxy.management_endpoints.model_management_endpoints import ( @@ -152,6 +173,7 @@ from litellm.types.router import ( SPECIAL_MODEL_INFO_PARAMS, Deployment, GenericLiteLLMParams, + LiteLLM_Params, ModelInfo, updateDeployment, updateLiteLLMParams, @@ -762,26 +784,93 @@ async def _auto_router_capability_slot( ENFORCE_RPM_TPM_ON_MODEL_ADD_SETTING: Final = "enforce_rpm_tpm_on_model_add" -def _raise_if_rate_limits_required_but_missing(*, litellm_params: GenericLiteLLMParams, enforced: bool) -> None: - """Require both rpm and tpm (each a positive value) when the operator opts in via config.yaml. +_ROUTING_KEYS: Final = ("model", "custom_llm_provider", "api_base") +_RATE_LIMIT_KEYS: Final = ("rpm", "tpm") +_NOTHING_SENT: Final[Mapping[str, object]] = MappingProxyType({}) - Off by default, so deployments keep adding models without limits. When - ``enforce_rpm_tpm_on_model_add: true`` is set under general_settings, a model added - without both rpm and tpm set to a positive value is rejected rather than stored - unbounded (or effectively excluded from routing by a zero/negative limit). - """ - if not enforced: + +def _merged_litellm_params( + incoming: GenericLiteLLMParams | None, existing: GenericLiteLLMParams | None, keys: tuple[str, ...] +) -> Mapping[str, object]: + sent: Final = _NOTHING_SENT if incoming is None else _dump_without_none(incoming) + stored: Final = _NOTHING_SENT if existing is None else _decrypted_litellm_params(existing) + return MappingProxyType({key: sent.get(key, stored.get(key)) for key in keys}) + + +def _written_routing_params( + incoming: GenericLiteLLMParams | None, existing: GenericLiteLLMParams | None +) -> Mapping[str, object]: + return _merged_litellm_params(incoming, existing, _ROUTING_KEYS) + + +def _quota_policy(general_settings: Mapping[str, object], setting: str) -> ModelQuotaPolicy | None: + try: + return parse_model_quota_setting(general_settings.get(setting)) + except ValidationError as e: + raise ProxyException( + message=f"general_settings.{setting} is invalid: {e}", + type=ProxyErrorTypes.internal_server_error.value, + code=status.HTTP_500_INTERNAL_SERVER_ERROR, + param=None, + ) from e + + +def _raise_if_rate_limits_required_but_missing( + *, model_name: str, litellm_params: LiteLLM_Params, team_model: bool, policy: ModelQuotaPolicy | None +) -> None: + """Off by default, so deployments keep adding models without limits. Once the operator opts in under + general_settings, the policy decides per model name and provider which of rpm and tpm a new model needs, + and a model missing one, or carrying a zero or negative one, is rejected rather than stored unbounded + (or effectively excluded from routing).""" + if policy is None: return - missing: Final = tuple( - field - for field, value in (("rpm", litellm_params.rpm), ("tpm", litellm_params.tpm)) - if value is None or value <= 0 + _raise_on_missing_rate_limits( + model_name, + unmet_limits( + required_limits( + policy, model_name, deployment_route(_written_routing_params(litellm_params, None), team_model) + ), + MappingProxyType({"rpm": litellm_params.rpm, "tpm": litellm_params.tpm}), + ), ) + + +def _raise_if_model_update_adds_missing_rate_limits( + *, + existing: Deployment, + written_name: str, + written_team_model: bool, + incoming_params: GenericLiteLLMParams | None, + remaining_params: GenericLiteLLMParams, + policy: ModelQuotaPolicy | None, +) -> None: + if policy is None: + return + before: Final = required_limits( + policy, + existing.model_info.team_public_model_name or existing.model_name, + deployment_route( + _written_routing_params(None, existing.litellm_params), existing.model_info.team_id is not None + ), + ) + after: Final = required_limits( + policy, + written_name, + deployment_route(_written_routing_params(incoming_params, remaining_params), written_team_model), + ) + written_limits: Final = _merged_litellm_params(incoming_params, remaining_params, _RATE_LIMIT_KEYS) + checked: Final = after - before + _raise_on_missing_rate_limits( + written_name, unmet_limits(checked, MappingProxyType({limit: written_limits.get(limit) for limit in checked})) + ) + + +def _raise_on_missing_rate_limits(model_name: str, missing: tuple[QuotaLimit, ...]) -> None: if not missing: return raise ProxyException( message=( - f"{' and '.join(missing)} must be set to a positive value when " + f"{' and '.join(missing)} must be set to a positive value for '{model_name}' when " f"'{ENFORCE_RPM_TPM_ON_MODEL_ADD_SETTING}' is enabled in general_settings" ), type=ProxyErrorTypes.validation_error.value, @@ -790,6 +879,113 @@ def _raise_if_rate_limits_required_but_missing(*, litellm_params: GenericLiteLLM ) +def _project_limit(metadata: object, limits_key: str, model: str) -> object: + limits: Final = metadata.get(limits_key) if is_str_keyed_mapping(metadata) else None + return limits.get(model) if is_str_keyed_mapping(limits) else None + + +def _projects_short_on( + projects: Sequence["prisma_models.LiteLLM_ProjectTable"], model: str, added: frozenset[QuotaLimit] +) -> tuple[str, ...]: + return tuple( + project.project_alias or project.project_id + for project in projects + if model in project.models + and unmet_limits( + added, + MappingProxyType( + { + "rpm": _project_limit(project.metadata, "model_rpm_limit", model), + "tpm": _project_limit(project.metadata, "model_tpm_limit", model), + } + ), + ) + ) + + +async def _raise_if_team_write_leaves_projects_short( + *, + prisma_client: PrismaClient, + general_settings: Mapping[str, object], + llm_router: Router | None, + team_id: str | None, + public_name: str, + replaced_id: str | None, + written_params: Mapping[str, object] | None, +) -> None: + if team_id is None: + return + policy: Final = _quota_policy(general_settings, ENFORCE_PROJECT_MODEL_QUOTA_SETTING) + if policy is None or not exempts_any_route(policy): + return + projects: Final = await ProjectRepository(prisma_client).table.find_many(where={"team_id": team_id}) + listed: Final = frozenset(itertools.chain.from_iterable(project.models for project in projects)) + served: Final = sorted(model for model in listed if team_write_serves(llm_router, team_id, public_name, model)) + shortfall: Final = next( + ( + (model, added, short) + for model in served + if ( + added := limits_added_by_team_write( + policy, llm_router, team_id, public_name, replaced_id, written_params, model + ) + ) + and (short := _projects_short_on(projects, model, added)) + ), + None, + ) + if shortfall is None: + return + short_model, short_limits, short_projects = shortfall + raise ProxyException( + message=( + f"projects {', '.join(short_projects)} list '{short_model}' without a positive " + f"{' and '.join(sorted(short_limits))} " + f"quota, which '{ENFORCE_PROJECT_MODEL_QUOTA_SETTING}' requires once this team model change applies. " + "Set those limits on the projects first" + ), + type=ProxyErrorTypes.validation_error.value, + code=status.HTTP_400_BAD_REQUEST, + param=None, + ) + + +async def _raise_if_team_update_leaves_projects_short( + *, + prisma_client: PrismaClient, + general_settings: Mapping[str, object], + llm_router: Router | None, + existing: Deployment, + written_team_id: str | None, + written_name: str, + incoming_params: GenericLiteLLMParams | None, + remaining_params: GenericLiteLLMParams, +) -> None: + if written_team_id is None and existing.model_info.team_id is None: + return + stored_name: Final = existing.model_info.team_public_model_name or existing.model_name + await _raise_if_team_write_leaves_projects_short( + prisma_client=prisma_client, + general_settings=general_settings, + llm_router=llm_router, + team_id=written_team_id, + public_name=written_name, + replaced_id=existing.model_info.id, + written_params=_written_routing_params(incoming_params, remaining_params), + ) + if (written_team_id, written_name) == (existing.model_info.team_id, stored_name): + return + await _raise_if_team_write_leaves_projects_short( + prisma_client=prisma_client, + general_settings=general_settings, + llm_router=llm_router, + team_id=existing.model_info.team_id, + public_name=stored_name, + replaced_id=existing.model_info.id, + written_params=None, + ) + + _PTU_PRICED_PAIR: Final = frozenset({"ptu_count", "cost_per_ptu_per_hour"}) @@ -1308,6 +1504,7 @@ async def patch_model( ProxyException: For various error conditions including authentication and database errors """ from litellm.proxy.proxy_server import ( + general_settings_view, litellm_proxy_admin_name, llm_router, premium_user, @@ -1434,6 +1631,29 @@ async def patch_model( existing_params=remaining_params, ) + written_team_id: Final = ( + patch_data.model_info.team_id if patch_data.model_info else None + ) or db_model.model_info.team_id + written_name: Final = _get_public_model_name(effective_patch, db_model) + _raise_if_model_update_adds_missing_rate_limits( + existing=db_model, + written_name=written_name, + written_team_model=written_team_id is not None, + incoming_params=incoming_params, + remaining_params=remaining_params, + policy=_quota_policy(general_settings_view(), ENFORCE_RPM_TPM_ON_MODEL_ADD_SETTING), + ) + await _raise_if_team_update_leaves_projects_short( + prisma_client=prisma_client, + general_settings=general_settings_view(), + llm_router=llm_router, + existing=db_model, + written_team_id=written_team_id, + written_name=written_name, + incoming_params=incoming_params, + remaining_params=remaining_params, + ) + effective_params: Final = _effective_complexity_router_params(incoming_params, remaining_params) requested_model_name: Final = patch_data.model_name stored_model_name: str | None = None @@ -2413,6 +2633,14 @@ class ModelManagementAuthChecks: ModelManagementAuthChecks._reject_team_inline_api_key_secret_reference( model_params=model_params, incoming_params=incoming_params, incoming_model_params=incoming_model_params ) + raise_auto_router_environment_reference_error( + auto_router_environment_reference_error( + config=_OPTIONAL_JSON_OBJECT.validate_python( + incoming_params.get("complexity_router_config") if incoming_params is not None else None + ), + user_api_key_dict=user_api_key_dict, + ) + ) # Federation fields choose which server-side secret is read and where the org-scoped token # it buys is sent, so only a proxy admin may point a federated deployment somewhere else. # Evaluated on the RESULTING deployment: a patch attaching a credential by name inherits @@ -2509,6 +2737,7 @@ async def delete_model( from litellm.proxy.proxy_server import ( MODEL_RECONCILE_LOCK, + general_settings_view, llm_router, premium_user, prisma_client, @@ -2542,6 +2771,15 @@ async def delete_model( incoming_params=None, allow_missing_team=True, ) + await _raise_if_team_write_leaves_projects_short( + prisma_client=prisma_client, + general_settings=general_settings_view(), + llm_router=llm_router, + team_id=model_params.model_info.team_id, + public_name=model_params.model_info.team_public_model_name or model_params.model_name, + replaced_id=model_params.model_info.id, + written_params=None, + ) # update DB if store_model_in_db is True: @@ -2608,21 +2846,9 @@ async def delete_model( except Exception as e: verbose_proxy_logger.exception("Failed to delete model. Due to error - %s", e) - if isinstance(e, HTTPException): - raise ProxyException( - message=getattr(e, "detail", f"Authentication Error({e})"), - type=ProxyErrorTypes.auth_error, - param=getattr(e, "param", "None"), - code=getattr(e, "status_code", status.HTTP_400_BAD_REQUEST), - ) - elif isinstance(e, ProxyException): - raise e - raise ProxyException( - message="Authentication Error, " + str(e), - type=ProxyErrorTypes.auth_error, - param=getattr(e, "param", "None"), - code=status.HTTP_400_BAD_REQUEST, - ) + if isinstance(e, ProxyException): + raise + raise proxy_exception_for(e, default_status_code=status.HTTP_400_BAD_REQUEST) from e async def delete_team_model_alias( @@ -2662,6 +2888,13 @@ async def delete_team_model_alias( return removed_model_aliases +def _model_not_added_to_db() -> HTTPException: + return HTTPException( + status_code=500, + detail={"error": "Failed to add model to db. Check your server logs for more details."}, + ) + + @router.post( "/model/new", description="Allows adding new models to the model list in the config.yaml", @@ -2708,6 +2941,8 @@ async def add_new_model( """ from litellm.proxy.proxy_server import ( general_settings, + general_settings_view, + llm_router, premium_user, prisma_client, proxy_config, @@ -2766,8 +3001,19 @@ async def add_new_model( ) _raise_if_rate_limits_required_but_missing( + model_name=model_params.model_name, litellm_params=model_params.litellm_params, - enforced=bool(general_settings.get(ENFORCE_RPM_TPM_ON_MODEL_ADD_SETTING, False)), + team_model=model_params.model_info.team_id is not None, + policy=_quota_policy(general_settings_view(), ENFORCE_RPM_TPM_ON_MODEL_ADD_SETTING), + ) + await _raise_if_team_write_leaves_projects_short( + prisma_client=prisma_client, + general_settings=general_settings_view(), + llm_router=llm_router, + team_id=model_params.model_info.team_id, + public_name=model_params.model_name, + replaced_id=None, + written_params=_written_routing_params(model_params.litellm_params, None), ) clean_model_info: Final = ModelInfo.model_validate( @@ -2830,6 +3076,8 @@ async def add_new_model( if isinstance(e, HTTPException): raise verbose_proxy_logger.exception("Exception in add_new_model: %s", e) + if model_response is None: + raise _model_not_added_to_db() from e else: raise HTTPException( @@ -2838,10 +3086,7 @@ async def add_new_model( ) if model_response is None: - raise HTTPException( - status_code=500, - detail={"error": "Failed to add model to db. Check your server logs for more details."}, - ) + raise _model_not_added_to_db() ## CREATE AUDIT LOG ## asyncio.create_task( @@ -2871,21 +3116,9 @@ async def add_new_model( except Exception as e: verbose_proxy_logger.exception("litellm.proxy.proxy_server.add_new_model(): Exception occured - %s", e) - if isinstance(e, HTTPException): - raise ProxyException( - message=getattr(e, "detail", f"Authentication Error({e})"), - type=ProxyErrorTypes.auth_error, - param=getattr(e, "param", "None"), - code=getattr(e, "status_code", status.HTTP_400_BAD_REQUEST), - ) - elif isinstance(e, ProxyException): - raise e - raise ProxyException( - message="Authentication Error, " + str(e), - type=ProxyErrorTypes.auth_error, - param=getattr(e, "param", "None"), - code=status.HTTP_400_BAD_REQUEST, - ) + if isinstance(e, ProxyException): + raise + raise proxy_exception_for(e, default_status_code=status.HTTP_400_BAD_REQUEST) from e #### MODEL MANAGEMENT #### @@ -2906,6 +3139,7 @@ async def update_model( """ from litellm.proxy.proxy_server import ( LITELLM_PROXY_ADMIN_NAME, + general_settings_view, llm_router, premium_user, prisma_client, @@ -2970,6 +3204,30 @@ async def update_model( incoming_params=model_params.litellm_params, existing_params=deployment.litellm_params, ) + renamed_to: Final = ( + model_params.model_name + if model_params.model_name not in (None, deployment.model_name) and deployment.model_info.team_id is None + else None + ) + written_name: Final = renamed_to or deployment.model_info.team_public_model_name or deployment.model_name + _raise_if_model_update_adds_missing_rate_limits( + existing=deployment, + written_name=written_name, + written_team_model=deployment.model_info.team_id is not None, + incoming_params=model_params.litellm_params, + remaining_params=deployment.litellm_params, + policy=_quota_policy(general_settings_view(), ENFORCE_RPM_TPM_ON_MODEL_ADD_SETTING), + ) + await _raise_if_team_update_leaves_projects_short( + prisma_client=prisma_client, + general_settings=general_settings_view(), + llm_router=llm_router, + existing=deployment, + written_team_id=deployment.model_info.team_id, + written_name=written_name, + incoming_params=model_params.litellm_params, + remaining_params=deployment.litellm_params, + ) effective_params: Final = _effective_complexity_router_params( model_params.litellm_params, deployment.litellm_params ) @@ -3009,12 +3267,6 @@ async def update_model( if value is not None or _existing_litellm_params_dict.get(key) is not None } - renamed_to: Final = ( - model_params.model_name - if model_params.model_name not in (None, deployment.model_name) - and deployment.model_info.team_id is None - else None - ) base_update: Final[PrismaCompatibleUpdateDBModel] = { "litellm_params": json.dumps(merged_dictionary), "updated_by": user_api_key_dict.user_id or LITELLM_PROXY_ADMIN_NAME, @@ -3095,21 +3347,9 @@ async def update_model( return None if model_response is None else _model_write_response(model_response, member_write) except Exception as e: verbose_proxy_logger.exception("litellm.proxy.proxy_server.update_model(): Exception occured - %s", e) - if isinstance(e, HTTPException): - raise ProxyException( - message=getattr(e, "detail", f"Authentication Error({e})"), - type=ProxyErrorTypes.auth_error, - param=getattr(e, "param", "None"), - code=getattr(e, "status_code", status.HTTP_400_BAD_REQUEST), - ) - elif isinstance(e, ProxyException): - raise e - raise ProxyException( - message="Authentication Error, " + str(e), - type=ProxyErrorTypes.auth_error, - param=getattr(e, "param", "None"), - code=status.HTTP_400_BAD_REQUEST, - ) + if isinstance(e, ProxyException): + raise + raise proxy_exception_for(e, default_status_code=status.HTTP_400_BAD_REQUEST) from e @router.post( diff --git a/litellm/proxy/management_endpoints/organization_endpoints.py b/litellm/proxy/management_endpoints/organization_endpoints.py index e1d19d8efae..8a1b9c112dc 100644 --- a/litellm/proxy/management_endpoints/organization_endpoints.py +++ b/litellm/proxy/management_endpoints/organization_endpoints.py @@ -41,6 +41,7 @@ from litellm.proxy.auth.auth_checks import ( ) from litellm.proxy.auth.user_api_key_auth import user_api_key_auth from litellm.proxy.common_utils.auth_cache_invalidation_pubsub import evict_and_broadcast +from litellm.proxy.common_utils.openai_error_payload import proxy_exception_for from litellm.proxy.common_utils.timezone_utils import get_budget_reset_time from litellm.proxy.common_utils.user_api_key_cache import UserApiKeyCache from litellm.proxy.management_endpoints.budget_management_endpoints import ( @@ -1396,21 +1397,9 @@ async def organization_member_add( ) except Exception as e: verbose_proxy_logger.exception("Error adding member to organization: %s", e) - if isinstance(e, HTTPException): - raise ProxyException( - message=getattr(e, "detail", f"Authentication Error({e})"), - type=ProxyErrorTypes.auth_error, - param=getattr(e, "param", "None"), - code=getattr(e, "status_code", status.HTTP_500_INTERNAL_SERVER_ERROR), - ) - elif isinstance(e, ProxyException): - raise e - raise ProxyException( - message="Authentication Error, " + str(e), - type=ProxyErrorTypes.auth_error, - param=getattr(e, "param", "None"), - code=status.HTTP_500_INTERNAL_SERVER_ERROR, - ) + if isinstance(e, ProxyException): + raise + raise proxy_exception_for(e, default_status_code=status.HTTP_500_INTERNAL_SERVER_ERROR) from e async def find_member_if_email(user_email: str, prisma_client: PrismaClient) -> LiteLLM_UserTable: diff --git a/litellm/proxy/management_endpoints/router_settings_endpoints.py b/litellm/proxy/management_endpoints/router_settings_endpoints.py index 1f4ca442d20..41c4b5cfaf7 100644 --- a/litellm/proxy/management_endpoints/router_settings_endpoints.py +++ b/litellm/proxy/management_endpoints/router_settings_endpoints.py @@ -10,7 +10,7 @@ GET /router/fields - Get router settings field definitions without values (for U import inspect from collections.abc import Mapping from types import MappingProxyType -from typing import Any, Final, get_args +from typing import Final, get_args from fastapi import APIRouter, Depends from pydantic import Field @@ -32,7 +32,7 @@ router: Final = APIRouter() class RouterSettingsResponse(LiteLLMBaseModel): fields: list[RouterSettingsField] = Field(description="List of all configurable router settings with metadata") - current_values: dict[str, Any] = Field(description="Current values of router settings") + current_values: dict[str, object] = Field(description="Current values of router settings") routing_strategy_descriptions: dict[str, str] = Field(description="Descriptions for each routing strategy option") routing_group_strategies: tuple[str, ...] = Field( description="Strategies supported when constructing a routing group" diff --git a/litellm/proxy/management_endpoints/team_endpoints.py b/litellm/proxy/management_endpoints/team_endpoints.py index 1fa18e9b2b8..50b700e712d 100644 --- a/litellm/proxy/management_endpoints/team_endpoints.py +++ b/litellm/proxy/management_endpoints/team_endpoints.py @@ -11,6 +11,7 @@ All /team management endpoints import asyncio import copy +import itertools import json import math import traceback @@ -131,6 +132,7 @@ from litellm.proxy.common_utils.auth_cache_invalidation_pubsub import ( ) from litellm.proxy.common_utils.callback_utils import encrypt_callback_vars from litellm.proxy.common_utils.json_merge_patch import apply_json_merge_patch +from litellm.proxy.common_utils.openai_error_payload import proxy_exception_for from litellm.proxy.common_utils.user_api_key_cache import ( UserApiKeyCache, team_membership_auth_cache_key, @@ -139,7 +141,12 @@ from litellm.proxy.common_utils.user_api_key_cache import ( from litellm.proxy.db.db_span import db_span from litellm.proxy.hooks.key_management_event_hooks import KeyManagementEventHooks from litellm.proxy.hooks.model_max_budget_limiter import ( + RoutedModels, build_model_max_budget_usage, + entries_outranked_by, + entry_names_model, + is_enforced_budget_entry, + proxy_routed_models, resolve_model_budget, ) from litellm.proxy.management.teams.authz import TEAM_OR_ORG_ADMIN, TeamRole, is_team_admin, team_access_denied @@ -1467,8 +1474,10 @@ def _check_team_model_budget_update_authority( data: UpdateTeamRequest, user_api_key_dict: UserAPIKeyAuth, existing_model_max_budget: Mapping[str, object] | None, + routed_models_source: Callable[[str | None], RoutedModels] = proxy_routed_models, ) -> None: - """Like `_check_team_budget_update_authority`: only a proxy admin may raise, re-window or drop a per-model cap.""" + """Like `_check_team_budget_update_authority`: only a proxy admin may raise, re-window or drop a per-model cap, or + add an entry that takes precedence over one.""" if user_api_key_dict.user_role == LitellmUserRoles.PROXY_ADMIN: return if "model_max_budget" not in data.model_fields_set or not existing_model_max_budget: @@ -1487,29 +1496,97 @@ def _check_team_model_budget_update_authority( ) }, ) - for model_name, proposed in requested.items(): - governing = resolve_model_budget(model=model_name, model_max_budget=existing_model_max_budget) - if governing is None: - continue - cap = governing.budget_config - if cap.max_budget is None: - continue - if ( - proposed.max_budget is None - or proposed.max_budget > cap.max_budget - or proposed.budget_duration != cap.budget_duration - ): - raise HTTPException( - status_code=403, - detail={ - "error": ( - f"Only a proxy admin can raise a team's model_max_budget for {model_name!r} or change its " - f"budget_duration. Current max_budget={cap.max_budget} per {cap.budget_duration} " - f"(entry {governing.budget_model!r}), requested={proposed.max_budget} per " - f"{proposed.budget_duration}." - ) - }, + routed_models: Final = routed_models_source(data.team_id) + for entry, proposed in requested.items(): + existing = _existing_model_cap(existing_model_max_budget.get(entry)) + if existing is not None: + _check_existing_model_cap_kept(entry=entry, cap_entry=entry, proposed=proposed, existing=existing) + if is_enforced_budget_entry(existing) or not is_enforced_budget_entry(proposed): + continue + governing = resolve_model_budget(model=entry, model_max_budget=existing_model_max_budget, team_id=data.team_id) + if governing is not None and entry_names_model(entry=governing.budget_model, model=entry): + _check_existing_model_cap_kept( + entry=entry, cap_entry=governing.budget_model, proposed=proposed, existing=governing.budget_config ) + _check_new_entry_outranks_no_cap( + entry=entry, + existing_model_max_budget=existing_model_max_budget, + routed_models=routed_models, + team_id=data.team_id, + ) + + +def _check_existing_model_cap_kept(entry: str, cap_entry: str, proposed: BudgetConfig, existing: BudgetConfig) -> None: + if existing.max_budget is None or not _looser_model_cap(proposed=proposed, cap=existing): + return + raise HTTPException( + status_code=403, + detail={ + "error": ( + f"Only a proxy admin can raise a team's model_max_budget for {entry!r} or change its " + f"budget_duration. Current max_budget={existing.max_budget} per {existing.budget_duration} " + f"(entry {cap_entry!r}), requested={proposed.max_budget} per {proposed.budget_duration}." + ) + }, + ) + + +def _check_new_entry_outranks_no_cap( + entry: str, + existing_model_max_budget: Mapping[str, object], + routed_models: RoutedModels, + team_id: str | None, +) -> None: + """A new entry gets its own counter, so the models it takes from a capped entry stop drawing from that cap.""" + outranked: Final = next( + _capped_entries_outranked_by( + entry=entry, + existing_model_max_budget=existing_model_max_budget, + routed_models=routed_models, + team_id=team_id, + ), + None, + ) + if outranked is None: + return + outranked_name, cap = outranked + raise HTTPException( + status_code=403, + detail={ + "error": ( + f"Only a proxy admin can add a team model_max_budget entry {entry!r} that takes precedence over " + f"{outranked_name!r}, since the models they share would stop drawing from its max_budget=" + f"{cap.max_budget} per {cap.budget_duration}." + ) + }, + ) + + +def _capped_entries_outranked_by( + entry: str, + existing_model_max_budget: Mapping[str, object], + routed_models: RoutedModels, + team_id: str | None, +) -> Iterator[tuple[str, BudgetConfig]]: + governing: Final = resolve_model_budget(model=entry, model_max_budget=existing_model_max_budget, team_id=team_id) + outranked_names: Final = itertools.chain( + () + if governing is None or entry_names_model(entry=governing.budget_model, model=entry) + else (governing.budget_model,), + entries_outranked_by(entry=entry, model_max_budget=existing_model_max_budget, routed_models=routed_models), + ) + outranked_caps: Final = ((name, _existing_model_cap(existing_model_max_budget[name])) for name in outranked_names) + yield from ( + (name, cap) for name, cap in outranked_caps if name != entry and cap is not None and cap.max_budget is not None + ) + + +def _looser_model_cap(proposed: BudgetConfig, cap: BudgetConfig) -> bool: + return ( + proposed.max_budget is None + or (cap.max_budget is not None and proposed.max_budget > cap.max_budget) + or (is_enforced_budget_entry(cap) and proposed.budget_duration != cap.budget_duration) + ) def _should_auto_add_team_creator( @@ -1572,7 +1649,7 @@ async def new_team( - prompts: Optional[List[str]] - List of prompts that the team is allowed to use. - organization_id: Optional[str] - The organization id of the team. Default is None. Create via `/organization/new`. - model_aliases: Optional[dict] - Model aliases for the team. [Docs](https://docs.litellm.ai/docs/proxy/team_based_routing#create-team-with-model-alias) - - model_max_budget: Optional[dict] - Per-model max budget every key on the team inherits unless the key sets its own for that model. Example: {"gpt-4o": {"max_budget": 10, "budget_duration": "1d"}} + - model_max_budget: Optional[dict] - Per-model max budget every key on the team inherits unless the key sets its own for that model, keyed by model name, `*` pattern, or model access group. Example: {"gpt-4o": {"max_budget": 10, "budget_duration": "1d"}} - guardrails: Optional[List[str]] - Guardrails for the team. [Docs](https://docs.litellm.ai/docs/proxy/guardrails) - policies: Optional[List[str]] - Policies for the team. [Docs](https://docs.litellm.ai/docs/proxy/guardrails/guardrail_policies) - disable_global_guardrails: Optional[bool] - Whether to disable global guardrails for the team. Proxy admin only. @@ -2350,7 +2427,7 @@ async def update_team( - tags: Optional[List[str]] - Tags for [tracking spend](https://litellm.vercel.app/docs/proxy/enterprise#tracking-spend-for-custom-tags) and/or doing [tag-based routing](https://litellm.vercel.app/docs/proxy/tag_routing). - organization_id: Optional[str] - The organization id of the team. Default is None. Create via `/organization/new`. - model_aliases: Optional[dict] - Model aliases for the team. [Docs](https://docs.litellm.ai/docs/proxy/team_based_routing#create-team-with-model-alias) - - model_max_budget: Optional[dict] - Per-model max budget every key on the team inherits unless the key sets its own for that model. Example: {"gpt-4o": {"max_budget": 10, "budget_duration": "1d"}} + - model_max_budget: Optional[dict] - Per-model max budget every key on the team inherits unless the key sets its own for that model, keyed by model name, `*` pattern, or model access group. Example: {"gpt-4o": {"max_budget": 10, "budget_duration": "1d"}} - guardrails: Optional[List[str]] - Guardrails for the team. [Docs](https://docs.litellm.ai/docs/proxy/guardrails) - policies: Optional[List[str]] - Policies for the team. [Docs](https://docs.litellm.ai/docs/proxy/guardrails/guardrail_policies) - disable_global_guardrails: Optional[bool] - Whether to disable global guardrails for the team. Proxy admin only. @@ -5450,21 +5527,9 @@ async def team_info( e, traceback.format_exc(), ) - if isinstance(e, HTTPException): - raise ProxyException( - message=getattr(e, "detail", f"Authentication Error({e})"), - type=ProxyErrorTypes.auth_error, - param=getattr(e, "param", "None"), - code=getattr(e, "status_code", status.HTTP_400_BAD_REQUEST), - ) - elif isinstance(e, ProxyException): - raise e - raise ProxyException( - message="Authentication Error, " + str(e), - type=ProxyErrorTypes.auth_error, - param=getattr(e, "param", "None"), - code=status.HTTP_400_BAD_REQUEST, - ) + if isinstance(e, ProxyException): + raise + raise proxy_exception_for(e, default_status_code=status.HTTP_400_BAD_REQUEST) from e @router.get( diff --git a/litellm/proxy/management_endpoints/ui_sso.py b/litellm/proxy/management_endpoints/ui_sso.py index 22c4f27d94a..a980b9c33ff 100644 --- a/litellm/proxy/management_endpoints/ui_sso.py +++ b/litellm/proxy/management_endpoints/ui_sso.py @@ -16,6 +16,7 @@ import json import os import re import secrets +from collections import Counter from collections.abc import Awaitable, Callable, Mapping, Sequence from copy import deepcopy from html import escape @@ -42,7 +43,7 @@ if TYPE_CHECKING: import jwt from fastapi import APIRouter, Depends, Header, HTTPException, Request, Response, status from fastapi.responses import RedirectResponse -from pydantic import BaseModel, ConfigDict, TypeAdapter, ValidationError, field_validator +from pydantic import AliasPath, BaseModel, ConfigDict, Field, TypeAdapter, ValidationError, field_validator import litellm from litellm._internal_context import with_service_target @@ -106,6 +107,7 @@ from litellm.proxy.common_utils.html_forms.default_credentials_hint import shoul from litellm.proxy.common_utils.html_forms.jwt_display_template import ( jwt_display_template, ) +from litellm.proxy.common_utils.html_forms.native_client_consent import team_select_field from litellm.proxy.common_utils.html_forms.ui_login import build_ui_login_form from litellm.proxy.common_utils.user_api_key_cache import AUTH_OBJECTS_TARGET, UserApiKeyCache from litellm.proxy.db.exception_handler import PrismaDBExceptionHandler @@ -184,6 +186,8 @@ _CLI_SSO_START_RATE_LIMIT_WINDOW_SECONDS: Final = 60 _CLI_SSO_START_RATE_LIMIT_MAX_ATTEMPTS: Final = 30 _CLI_SSO_USER_CODE_ALPHABET: Final = "ABCDEFGHJKLMNPQRSTUVWXYZ23456789" _CLI_SSO_LOGIN_ID_RE: Final = re.compile(r"^cli-[A-Za-z0-9_-]{12,124}$") +CLI_SSO_BROWSER_TEAM_CHOICE: Final = "browser_team_choice" +CLI_SSO_CHOSEN_TEAM_ID: Final = "chosen_team_id" _CLI_SSO_USER_CODE_RE = re.compile(rf"^[{_CLI_SSO_USER_CODE_ALPHABET}]{{4}}-[{_CLI_SSO_USER_CODE_ALPHABET}]{{4}}$") _CLI_SSO_SCALAR_TYPES: Final = (str, int, float, bool) _CLI_SSO_DEST_KEY_RE: Final = re.compile(r"^[A-Za-z0-9_.-]+$") @@ -670,6 +674,7 @@ def _render_cli_sso_verification_page( verify_url: str, browser_complete_token: str, prefill_user_code: str | None = None, + team_choices: Sequence[tuple[str, str]] = (), ) -> str: escaped_verify_url: Final = escape(verify_url, quote=True) escaped_browser_complete_token: Final = escape(browser_complete_token, quote=True) @@ -716,6 +721,15 @@ def _render_cli_sso_verification_page( letter-spacing: 0.08em; text-transform: uppercase; }} + select {{ + box-sizing: border-box; + width: 100%; + padding: 12px; + margin-bottom: 18px; + border: 1px solid #cbd5e1; + border-radius: 6px; + font-size: 16px; + }} button {{ margin-top: 16px; width: 100%; @@ -735,6 +749,7 @@ def _render_cli_sso_verification_page(

{instructions}

+ {team_select_field(team_choices, require_choice=True)} @@ -823,13 +838,46 @@ async def cli_sso_complete(request: Request, login_id: str): ): raise HTTPException(status_code=400, detail="Invalid verification code") - flow["user_code_verified"] = True - _set_cli_sso_flow(login_id=login_id, cache=cli_sso_session_cache, flow=flow) + team_choice_flow: Final = _CliSsoTeamChoiceFlow.model_validate(flow) + chosen_team_id: Final = _browser_chosen_team_id(team_choice_flow, form_values) + if chosen_team_id is not None and chosen_team_id not in team_choice_flow.teams: + raise HTTPException(status_code=400, detail="Choose one of the teams you belong to") + + _set_cli_sso_flow( + login_id=login_id, + cache=cli_sso_session_cache, + flow={ + **flow, + "user_code_verified": True, + CLI_SSO_CHOSEN_TEAM_ID: chosen_team_id, + "session_data": ( + flow["session_data"] + if chosen_team_id is None + else { + **flow["session_data"], + "teams": [chosen_team_id, *(team for team in team_choice_flow.teams if team != chosen_team_id)], + } + ), + }, + ) html_content: Final = render_cli_sso_success_page() return HTMLResponse(content=html_content, status_code=200) +class _CliSsoTeamChoiceFlow(BaseModel): + model_config = ConfigDict(frozen=True) + + browser_team_choice: bool = Field(default=False, validation_alias=CLI_SSO_BROWSER_TEAM_CHOICE) + teams: tuple[str, ...] = Field(default=(), validation_alias=AliasPath("session_data", "teams")) + + +def _browser_chosen_team_id(flow: _CliSsoTeamChoiceFlow, form_values: Mapping[str, Sequence[str]]) -> str | None: + if not flow.browser_team_choice: + return None + return (form_values.get("team_id") or [""])[0] or None + + def normalize_email(email: str | None) -> str | None: """ Normalize email address to lowercase for consistent storage and comparison. @@ -2416,6 +2464,18 @@ def _cli_sso_session_teams(team_details: Sequence[CliSsoTeamDetail]) -> list[str return [detail.team_id for detail in team_details if detail.team_id is not None] +def _browser_team_choices( + flow: _CliSsoTeamChoiceFlow, team_details: Sequence[CliSsoTeamDetail] +) -> tuple[tuple[str, str], ...]: + if not flow.browser_team_choice: + return () + labeled: Final = tuple( + (detail.team_id, detail.team_alias or detail.team_id) for detail in team_details if detail.team_id is not None + ) + label_counts: Final = Counter(label for _, label in labeled) + return tuple((team_id, label if label_counts[label] == 1 else f"{label} ({team_id})") for team_id, label in labeled) + + def selected_cli_sso_team_detail(team_details: object, team_id: str | None) -> CliSsoTeamDetail | None: """``None`` means the team's grants are unknown. An empty grant is a real value meaning unrestricted, so an unknown one must not be minted as empty.""" @@ -2484,6 +2544,7 @@ async def _complete_cli_sso_callback_session( request.scope.get("litellm_microsoft_interactive_subject"), resolved_user_id, prisma_client ) resolved_teams: Final = _cli_sso_session_teams(team_details) + team_choices: Final = _browser_team_choices(_CliSsoTeamChoiceFlow.model_validate(flow), team_details) attribution_metadata: Final = build_cli_sso_attribution_metadata(result=result) if attribution_metadata: await _persist_cli_sso_user_metadata( @@ -2521,6 +2582,7 @@ async def _complete_cli_sso_callback_session( verify_url=verify_url, browser_complete_token=browser_complete_token, prefill_user_code=prefill_user_code, + team_choices=team_choices, ), status_code=200, ) diff --git a/litellm/proxy/management_helpers/auto_router_availability.py b/litellm/proxy/management_helpers/auto_router_availability.py index 9b511ce0817..ce7859aff2d 100644 --- a/litellm/proxy/management_helpers/auto_router_availability.py +++ b/litellm/proxy/management_helpers/auto_router_availability.py @@ -7,14 +7,14 @@ from typing import Final from pydantic import Json, TypeAdapter, ValidationError from litellm.proxy.common_utils.encrypt_decrypt_utils import decrypt_value_helper -from litellm.router_utils.auto_router_model_naming import ( +from litellm.router_strategy.auto_router.auto_router_model_naming import ( GATED_AUTO_ROUTER_CAPABILITIES, capability_limit_violation, classify_strategy_router_model, count_capability_routers, gated_capabilities_of, ) -from litellm.router_utils.auto_router_tuning_baseline import ( +from litellm.router_strategy.auto_router.auto_router_tuning_baseline import ( is_mutable_tuned_candidate, mutable_tuned_identities, tuning_quota_violation, diff --git a/litellm/proxy/management_helpers/auto_router_permissions.py b/litellm/proxy/management_helpers/auto_router_permissions.py index a4428eb3a85..8597f0d3667 100644 --- a/litellm/proxy/management_helpers/auto_router_permissions.py +++ b/litellm/proxy/management_helpers/auto_router_permissions.py @@ -5,8 +5,8 @@ from types import MappingProxyType from typing import TYPE_CHECKING, Final, Literal from fastapi import HTTPException -from pydantic import ConfigDict, Field, ValidationError -from typing_extensions import ReadOnly, TypedDict +from pydantic import ConfigDict, Field, TypeAdapter, ValidationError +from typing_extensions import ReadOnly, TypedDict, assert_never from litellm.models.organization import LiteLLM_OrganizationTable from litellm.models.project import LiteLLM_ProjectTable @@ -34,12 +34,16 @@ from litellm.repositories.prisma_protocols import DatabaseClient from litellm.repositories.project_repository import ProjectRepository from litellm.repositories.table_repositories import TeamMembershipRepository from litellm.router import Router +from litellm.router_strategy.auto_router.auto_router_model_naming import ( + classify_strategy_router_model, + strategy_router_dependencies, +) from litellm.router_strategy.complexity_router.config import ( ComplexityRouterConfigWrite, + normalize_classifier_config_aliases, resolve_complexity_router_config_write, ) from litellm.router_strategy.complexity_router.request_models import RequestComplexityRouterConfig -from litellm.router_utils.auto_router_model_naming import classify_strategy_router_model, strategy_router_dependencies from litellm.types.llms.base import LiteLLMBaseModel from litellm.types.router import Deployment, updateDeployment @@ -47,6 +51,36 @@ if TYPE_CHECKING: from prisma import types as prisma_types +def auto_router_environment_reference_error( + config: Mapping[str, object] | None, user_api_key_dict: UserAPIKeyAuth +) -> Literal["environment_reference_denied"] | None: + if config is None or user_api_key_dict.user_role == LitellmUserRoles.PROXY_ADMIN: + return None + classifier: Final = normalize_classifier_config_aliases(config).get("opensource_classifier_config") + if not isinstance(classifier, Mapping): + return None + fields: Final = TypeAdapter(Mapping[str, object]).validate_python(classifier) + if any( + isinstance(value, str) and value.startswith("os.environ/") + for value in (fields.get("api_key"), fields.get("api_base")) + ): + return "environment_reference_denied" + return None + + +def raise_auto_router_environment_reference_error(error: Literal["environment_reference_denied"] | None) -> None: + match error: + case None: + return + case "environment_reference_denied": + raise HTTPException( + status_code=403, + detail="Only proxy admins can submit classifier connection environment references", + ) + case _: + assert_never(error) + + class _MemberRouterThinking(LiteLLMBaseModel): model_config = ConfigDict(extra="forbid", frozen=True) diff --git a/litellm/proxy/management_helpers/model_quota_policy.py b/litellm/proxy/management_helpers/model_quota_policy.py new file mode 100644 index 00000000000..752c78df862 --- /dev/null +++ b/litellm/proxy/management_helpers/model_quota_policy.py @@ -0,0 +1,327 @@ +import re +from collections.abc import Callable, Mapping, Sequence +from dataclasses import dataclass +from types import MappingProxyType +from typing import TYPE_CHECKING, Final, Literal, TypeAlias + +from pydantic import BaseModel, ConfigDict, Field, field_validator + +import litellm +from litellm.exceptions import BadRequestError +from litellm.litellm_core_utils.get_llm_provider_logic import get_llm_provider, is_openai_compatible_endpoint +from litellm.llms.azure.ptu_capacity import is_str_keyed_mapping +from litellm.llms.openai_like.json_loader import JSONProviderRegistry +from litellm.router_utils.common_utils import provider_for_generic_call +from litellm.router_utils.pattern_match_deployments import PatternMatchRouter, PatternUtils +from litellm.secret_managers.main import get_secret_str + +if TYPE_CHECKING: + from litellm import Router + +QuotaLimit: TypeAlias = Literal["rpm", "tpm"] + +ENFORCE_PROJECT_MODEL_QUOTA_SETTING: Final = "enforce_project_model_quota" + +_LIMITS: Final[tuple[QuotaLimit, ...]] = ("rpm", "tpm") +_ROUTER_PATTERNS: Final = PatternMatchRouter() + + +def _is_known_provider(provider: str) -> bool: + return provider in litellm.provider_list or JSONProviderRegistry.exists(provider) + + +class ModelQuotaPolicy(BaseModel): + model_config = ConfigDict(frozen=True, extra="forbid") + + default: frozenset[QuotaLimit] = frozenset(_LIMITS) + providers: Mapping[str, frozenset[QuotaLimit]] = Field(default_factory=dict) + models: Mapping[str, frozenset[QuotaLimit]] = Field(default_factory=dict) + + @field_validator("providers") + @classmethod + def _known_providers(cls, providers: Mapping[str, frozenset[QuotaLimit]]) -> Mapping[str, frozenset[QuotaLimit]]: + unknown: Final = sorted(provider for provider in providers if not _is_known_provider(provider)) + if unknown: + raise ValueError(f"unknown provider ids {unknown}") + return providers + + +REQUIRE_BOTH_LIMITS: Final = ModelQuotaPolicy() +_POLICY_KEYS: Final = frozenset(ModelQuotaPolicy.model_fields) + + +@dataclass(frozen=True, slots=True) +class TeamDeployment: + provider: str | None + called_model: str | None + + +@dataclass(frozen=True, slots=True) +class ModelRoute: + providers: frozenset[str] = frozenset() + team_deployments: frozenset[TeamDeployment] = frozenset() + + +RouteOf: TypeAlias = Callable[[str], ModelRoute] +NO_ROUTE: Final = ModelRoute() + + +def parse_model_quota_setting(setting: object) -> ModelQuotaPolicy | None: + """Any falsy value is off and any other value requires both limits, as the boolean setting always + behaved, so only a mapping that names a policy key is read as a per-provider and per-model policy.""" + if not setting: + return None + if is_str_keyed_mapping(setting) and not _POLICY_KEYS.isdisjoint(setting): + return ModelQuotaPolicy.model_validate(setting) + return REQUIRE_BOTH_LIMITS + + +def _wildcard_matches(pattern: str, model: str) -> bool: + return re.match(_ROUTER_PATTERNS.pattern_to_regex(pattern), model) is not None + + +def _router_specificity(pattern: str) -> tuple[int, int]: + return PatternUtils.calculate_pattern_specificity(_ROUTER_PATTERNS.pattern_to_regex(pattern)) + + +def _most_specific_model_pattern(model: str, entries: Mapping[str, frozenset[QuotaLimit]]) -> str | None: + matching: Final = tuple(pattern for pattern in entries if "*" in pattern and _wildcard_matches(pattern, model)) + return max(matching, key=_router_specificity, default=None) + + +def _model_entry(entries: Mapping[str, frozenset[QuotaLimit]], model: str) -> frozenset[QuotaLimit] | None: + exact: Final = entries.get(model) + if exact is not None: + return exact + pattern: Final = _most_specific_model_pattern(model, entries) + return None if pattern is None else entries[pattern] + + +def _provider_limits(policy: ModelQuotaPolicy, provider: str | None) -> frozenset[QuotaLimit]: + return policy.default if provider is None else policy.providers.get(provider, policy.default) + + +def _team_deployment_limits(policy: ModelQuotaPolicy, deployment: TeamDeployment) -> frozenset[QuotaLimit]: + entry: Final = None if deployment.called_model is None else _model_entry(policy.models, deployment.called_model) + return _provider_limits(policy, deployment.provider) if entry is None else entry + + +def required_limits(policy: ModelQuotaPolicy, model: str, route: ModelRoute) -> frozenset[QuotaLimit]: + """A model entry (exact name, then the most specific `*` pattern) wins over the providers of the + model's deployments, which win over the default. A model served by several providers needs every + limit any of them requires. A team picks its model's public name, so a team deployment matches + model entries by the model it calls instead.""" + entry: Final = None if route.team_deployments else _model_entry(policy.models, model) + if entry is not None: + return entry + if not route.providers and not route.team_deployments: + return policy.default + return frozenset[QuotaLimit]().union( + *(_team_deployment_limits(policy, deployment) for deployment in route.team_deployments), + *(_provider_limits(policy, provider) for provider in route.providers), + ) + + +def _is_positive(value: object) -> bool: + return isinstance(value, int) and not isinstance(value, bool) and value > 0 + + +def unmet_limits(required: frozenset[QuotaLimit], values: Mapping[QuotaLimit, object]) -> tuple[QuotaLimit, ...]: + return tuple( + limit + for limit in _LIMITS + if (limit in required or values.get(limit) is not None) and not _is_positive(values.get(limit)) + ) + + +def no_route(_model: str) -> ModelRoute: + return NO_ROUTE + + +def _resolved_api_base(api_base: object) -> object: + if isinstance(api_base, str) and api_base.startswith("os.environ/"): + return get_secret_str(api_base) + return api_base + + +def _provider_behind_api_base(litellm_params: Mapping[str, object]) -> str | None: + model: Final = litellm_params.get("model") + api_base: Final = _resolved_api_base(litellm_params.get("api_base")) + if litellm_params.get("custom_llm_provider") or not isinstance(model, str) or not isinstance(api_base, str): + return None + if model.split("/", 1)[0] in litellm.provider_list or not is_openai_compatible_endpoint(api_base): + return None + try: + _, provider, _, _ = get_llm_provider(model=model, api_base=api_base) + except BadRequestError: + return None + return provider + + +def deployment_provider(litellm_params: object) -> str | None: + if not is_str_keyed_mapping(litellm_params): + return None + return _provider_behind_api_base(litellm_params) or provider_for_generic_call(litellm_params) + + +def _called_model(litellm_params: Mapping[str, object]) -> str | None: + model: Final = litellm_params.get("model") + if not isinstance(model, str): + return None + prefix, _, rest = model.partition("/") + return rest if rest and _is_known_provider(prefix) else model + + +def team_deployment(litellm_params: object) -> TeamDeployment: + if not is_str_keyed_mapping(litellm_params): + return TeamDeployment(provider=None, called_model=None) + return TeamDeployment(provider=deployment_provider(litellm_params), called_model=_called_model(litellm_params)) + + +def deployment_route(litellm_params: Mapping[str, object], team_model: bool) -> ModelRoute: + if team_model: + return ModelRoute(team_deployments=frozenset((team_deployment(litellm_params),))) + provider: Final = deployment_provider(litellm_params) + return ModelRoute(providers=frozenset() if provider is None else frozenset((provider,))) + + +def _named_deployments(llm_router: "Router", model: str, team_id: str | None) -> tuple[Mapping[str, object], ...]: + return ( + *llm_router.get_all_deployments(model_name=model, team_id=team_id), + *llm_router.get_model_list_from_routing_groups(model_name=model), + ) + + +def _routed_deployments(llm_router: "Router", model: str, team_id: str | None) -> Sequence[Mapping[str, object]]: + target: Final = llm_router.routable_model_group(model) + return _named_deployments(llm_router, target, team_id) or llm_router.wildcard_route_deployments(target, team_id) + + +def _is_team_deployment(deployment: Mapping[str, object]) -> bool: + model_info: Final = deployment.get("model_info") + return is_str_keyed_mapping(model_info) and model_info.get("team_id") is not None + + +def router_model_routes(llm_router: "Router | None", team_id: str | None) -> RouteOf: + if llm_router is None: + return no_route + + def route_of(model: str) -> ModelRoute: + deployments: Final = _routed_deployments(llm_router, model, team_id) + shared: Final = tuple(deployment for deployment in deployments if not _is_team_deployment(deployment)) + return ModelRoute( + providers=frozenset( + provider + for deployment in shared + if (provider := deployment_provider(deployment.get("litellm_params"))) is not None + ), + team_deployments=frozenset( + team_deployment(deployment.get("litellm_params")) + for deployment in deployments + if _is_team_deployment(deployment) + ), + ) + + return route_of + + +def _deployment_id(deployment: Mapping[str, object]) -> object: + model_info: Final = deployment.get("model_info") + return model_info.get("id") if is_str_keyed_mapping(model_info) else None + + +def _routable_name(llm_router: "Router | None", model: str) -> str: + return model if llm_router is None else llm_router.routable_model_group(model) + + +def _patterns_tried_before(patterns: Sequence[str], regex: str) -> Sequence[str]: + if regex in patterns: + return patterns[: patterns.index(regex)] + specificity: Final = PatternUtils.calculate_pattern_specificity(regex) + return tuple(rival for rival in patterns if PatternUtils.calculate_pattern_specificity(rival) >= specificity) + + +def _team_pattern_serves(llm_router: "Router", team_id: str, pattern: str, model: str) -> bool: + regex: Final = _ROUTER_PATTERNS.pattern_to_regex(pattern) + if re.match(regex, model) is None or _named_deployments(llm_router, model, team_id): + return False + team_router: Final = llm_router.team_pattern_routers.get(team_id) + patterns: Final = () if team_router is None else tuple(team_router.patterns) + return not any(re.match(rival, model) is not None for rival in _patterns_tried_before(patterns, regex)) + + +def team_write_serves(llm_router: "Router | None", team_id: str, public_name: str, model: str) -> bool: + """Whether a request from the team for ``model`` reaches the team route named ``public_name``: the name + itself or an alias of it, or, for a `*` name, a model no named deployment shadows and no team pattern the + router tries first takes.""" + target: Final = _routable_name(llm_router, model) + if "*" not in public_name or llm_router is None: + return target == public_name + return _team_pattern_serves(llm_router, team_id, public_name, target) + + +def _served_params(litellm_params: object, public_name: str, model: str) -> object: + if "*" not in public_name or not is_str_keyed_mapping(litellm_params): + return litellm_params + matched: Final = re.match(_ROUTER_PATTERNS.pattern_to_regex(public_name), model) + called: Final = litellm_params.get("model") + if matched is None or not isinstance(called, str): + return litellm_params + return MappingProxyType( + { + **litellm_params, + "model": PatternMatchRouter.set_deployment_model_name( + matched_pattern=matched, litellm_deployment_litellm_model=called + ), + } + ) + + +def team_route_after_write( + llm_router: "Router | None", + team_id: str, + public_name: str, + replaced_id: str | None, + written_params: Mapping[str, object] | None, + model: str, +) -> ModelRoute | None: + deployments: Final = () if llm_router is None else llm_router.get_all_deployments(public_name, team_id=team_id) + kept: Final = tuple( + deployment.get("litellm_params") + for deployment in deployments + if _is_team_deployment(deployment) and _deployment_id(deployment) != replaced_id + ) + team_params: Final = kept if written_params is None else (*kept, written_params) + target: Final = _routable_name(llm_router, model) + if team_params: + return ModelRoute( + team_deployments=frozenset( + team_deployment(_served_params(litellm_params, public_name, target)) for litellm_params in team_params + ) + ) + if llm_router is None or not _routed_deployments(llm_router, model, None): + return None + return router_model_routes(llm_router, None)(model) + + +def limits_added_by_team_write( + policy: ModelQuotaPolicy, + llm_router: "Router | None", + team_id: str, + public_name: str, + replaced_id: str | None, + written_params: Mapping[str, object] | None, + model: str, +) -> frozenset[QuotaLimit]: + after: Final = team_route_after_write(llm_router, team_id, public_name, replaced_id, written_params, model) + if after is None: + return frozenset() + now: Final = router_model_routes(llm_router, team_id)(model) + return required_limits(policy, model, after) - required_limits(policy, model, now) + + +def exempts_any_route(policy: ModelQuotaPolicy) -> bool: + return any( + limits != REQUIRE_BOTH_LIMITS.default + for limits in (policy.default, *policy.providers.values(), *policy.models.values()) + ) diff --git a/litellm/proxy/management_helpers/team_roster_sync.py b/litellm/proxy/management_helpers/team_roster_sync.py index dc0ba2e47d4..08be455a55d 100644 --- a/litellm/proxy/management_helpers/team_roster_sync.py +++ b/litellm/proxy/management_helpers/team_roster_sync.py @@ -40,6 +40,7 @@ from litellm.proxy.management_helpers.access_group_team_sync import ( ) from litellm.proxy.utils import PrismaClient, ProxyLogging from litellm.repositories.chunked_in import delete_many_in, find_many_in, update_many_in +from litellm.repositories.team_repository import TeamRepository if TYPE_CHECKING: from prisma import Prisma @@ -144,7 +145,7 @@ def _changes_nothing(plan: RosterPlan) -> bool: async def _unchanged_roster(prisma_client: PrismaClient, team_id: str) -> RosterSync | TeamGone: - team_row: Final = await prisma_client.writer_db.litellm_teamtable.find_unique(where={"team_id": team_id}) + team_row: Final = await TeamRepository(prisma_client, use_writer=True).table.find_unique(where={"team_id": team_id}) if team_row is None: return TeamGone(team_id=team_id) team: Final = LiteLLM_TeamTable.model_validate(team_row.model_dump()) diff --git a/litellm/proxy/mcp_server/discoverable_endpoints.py b/litellm/proxy/mcp_server/discoverable_endpoints.py index eb12b15cdae..07a267d6caa 100644 --- a/litellm/proxy/mcp_server/discoverable_endpoints.py +++ b/litellm/proxy/mcp_server/discoverable_endpoints.py @@ -300,12 +300,13 @@ def decode_state_hash(encrypted_state: str) -> dict: if decrypted_json is None: raise ValueError("Failed to decrypt state parameter") - state_data: Final = json.loads(decrypted_json) + state_data: Final = _DECODED_STATE.validate_python(json.loads(decrypted_json)) return state_data _MANAGED_AUTH_CODE_PREFIX: Final = "llm_scope_" _DECODED_JSON: Final = TypeAdapter(object) +_DECODED_STATE: Final = TypeAdapter(dict[str, object], config=ConfigDict(strict=True)) class _ManagedAuthorizationCode(LiteLLMBaseModel): diff --git a/litellm/proxy/openai_files_endpoints/files_endpoints.py b/litellm/proxy/openai_files_endpoints/files_endpoints.py index d2ceefffe47..5d63c3db222 100644 --- a/litellm/proxy/openai_files_endpoints/files_endpoints.py +++ b/litellm/proxy/openai_files_endpoints/files_endpoints.py @@ -6,9 +6,12 @@ ###################################################################### import asyncio +import functools +import itertools import traceback -from collections.abc import Mapping, Sequence -from typing import Any, BinaryIO, Final, TypedDict, cast, get_args +from collections.abc import Iterable, Iterator, Mapping, Sequence +from dataclasses import dataclass +from typing import Any, BinaryIO, Final, NoReturn, TypedDict, cast, get_args import httpx from fastapi import ( @@ -28,12 +31,13 @@ from typing_extensions import ReadOnly import litellm from litellm import CreateFileRequest, get_secret_str from litellm._logging import verbose_proxy_logger +from litellm.constants import ANTHROPIC_DEFAULT_FILE_LIST_LIMIT from litellm.litellm_core_utils.cloud_storage_security import ( is_managed_cloud_storage_uri, ) from litellm.litellm_core_utils.core_helpers import get_or_create_metadata_bucket from litellm.llms.base_llm.files.litellm_db_storage_backend import LITELLM_DB_STORAGE_BACKEND_NAME -from litellm.llms.base_llm.files.transformation import BaseFileEndpoints +from litellm.llms.base_llm.files.transformation import BaseFileEndpoints, FileListModelScope from litellm.llms.base_llm.managed_resources.isolation import build_list_page from litellm.proxy._types import * from litellm.proxy.auth.user_api_key_auth import user_api_key_auth @@ -112,6 +116,9 @@ from litellm.types.llms.openai import ( OpenAIFileObject, OpenAIFilesPurpose, ) +from litellm.types.proxy.auth.user_api_key_auth import user_api_key_has_admin_view +from litellm.types.router import Deployment +from litellm.types.utils import LlmProviders router: Final = APIRouter() @@ -1673,6 +1680,185 @@ def _as_file_list_page(response: object) -> object: return FileListPage.model_validate(page) +async def _list_owned_managed_files( + managed_files_obj: BaseFileEndpoints, + user_api_key_dict: UserAPIKeyAuth, + purpose: str | None, + limit: int | None, + after: str | None, + before: str | None, + model_scope: FileListModelScope | None, +) -> FileListPage: + return await managed_files_obj.afile_list( + purpose=purpose, + litellm_parent_otel_span=user_api_key_dict.parent_otel_span, + user_api_key_dict=user_api_key_dict, + limit=limit, + after=after, + before=before, + model_scope=model_scope, + ) + + +@dataclass(frozen=True, slots=True) +class _UnscopedFileList: + status_code: int + detail: str + + +@dataclass(frozen=True, slots=True) +class _ListedFiles: + model_scope: FileListModelScope | None + custom_llm_provider: str | None + + +def _raise_unscoped_file_list(failure: _UnscopedFileList) -> NoReturn: + raise HTTPException(status_code=failure.status_code, detail=failure.detail) + + +def _single_target_model_name(target_model_names: str) -> str | _UnscopedFileList: + target_model_names_list: Final = target_model_names.split(",") + if len(target_model_names_list) != 1: + return _UnscopedFileList( + status_code=400, + detail="target_model_names on list files must be a list of one model name. Example: ['gpt-4o']", + ) + return target_model_names_list[0] + + +async def _requested_custom_llm_provider(request: Request, provider: str | None) -> str | None: + return ( + provider + or get_custom_llm_provider_from_request_headers(request=request) + or get_custom_llm_provider_from_request_query(request=request) + or await get_custom_llm_provider_from_request_body(request=request) + ) + + +def _default_file_list_limit(custom_llm_provider: str | None) -> int | None: + return ANTHROPIC_DEFAULT_FILE_LIST_LIMIT if custom_llm_provider == LlmProviders.ANTHROPIC.value else None + + +def _deployment_model_mapping_keys(deployment: Deployment) -> frozenset[str]: + return frozenset(key for key in (deployment.model_name, deployment.model_info.id) if key is not None) + + +def _model_mapping_keys(deployments: Iterable[Deployment]) -> frozenset[str]: + return frozenset(itertools.chain.from_iterable(map(_deployment_model_mapping_keys, deployments))) + + +def _deployments_serving_model(llm_router: Router, model: str) -> tuple[Deployment, ...]: + deployment: Final = llm_router.get_deployment(model_id=model) if llm_router.has_model_id(model) else None + if deployment is not None: + return (deployment,) + return tuple(Deployment.model_validate(listed) for listed in llm_router.get_model_list(model_name=model) or ()) + + +def _resolved_deployment_provider(deployment: Deployment) -> str | None: + try: + return litellm.get_llm_provider( + model=deployment.litellm_params.model, + custom_llm_provider=deployment.litellm_params.custom_llm_provider, + )[1] + except litellm.BadRequestError: + return None + + +def _deployments_on_provider(llm_router: Router | None, custom_llm_provider: str) -> Iterator[Deployment]: + if llm_router is None: + return iter(()) + return ( + deployment + for deployment_id in llm_router.get_model_ids() + if (deployment := llm_router.get_deployment(model_id=deployment_id)) is not None + and _resolved_deployment_provider(deployment) == custom_llm_provider + ) + + +def _routed_model_name_on_provider( + llm_router: Router, custom_llm_provider: str, provider_model_names: frozenset[str], model_name: str +) -> bool: + if model_name in llm_router.model_names: + return model_name in provider_model_names + return llm_router.pattern_router.routes_to_provider(model_name, custom_llm_provider) + + +def _stored_model_name_routes_to_provider( + llm_router: Router, custom_llm_provider: str, provider_model_names: frozenset[str], model_name: str +) -> bool: + routing_group: Final = llm_router.get_routing_group(model_name) + routed_model_names: Final = ( + tuple(routing_group.models) if routing_group is not None else (llm_router.routable_model_group(model_name),) + ) + return any( + _routed_model_name_on_provider(llm_router, custom_llm_provider, provider_model_names, routed_model_name) + for routed_model_name in routed_model_names + ) + + +def _files_on_provider(llm_router: Router | None, custom_llm_provider: str) -> _ListedFiles | _UnscopedFileList: + from litellm.proxy.pass_through_endpoints.managed_id_rewriter import passthrough_file_model_id + + if custom_llm_provider not in litellm.provider_list: + return _UnscopedFileList(status_code=400, detail=f"Unknown provider '{custom_llm_provider}' for listing files.") + passthrough_model_id: Final = passthrough_file_model_id(custom_llm_provider) + deployments: Final = tuple(_deployments_on_provider(llm_router, custom_llm_provider)) + model_mapping_keys: Final = _model_mapping_keys(deployments) | frozenset( + (passthrough_model_id,) if passthrough_model_id is not None else () + ) + if llm_router is None: + return _ListedFiles(FileListModelScope(model_mapping_keys), custom_llm_provider) + return _ListedFiles( + FileListModelScope( + model_mapping_keys, + routes_stored_model_name=functools.partial( + _stored_model_name_routes_to_provider, + llm_router, + custom_llm_provider, + frozenset(deployment.model_name for deployment in deployments), + ), + ), + custom_llm_provider, + ) + + +def _files_serving_model(llm_router: Router, model: str) -> _ListedFiles: + deployments: Final = _deployments_serving_model(llm_router, model) + providers: Final = frozenset(map(_resolved_deployment_provider, deployments)) + return _ListedFiles( + FileListModelScope(_model_mapping_keys(deployments)), next(iter(providers)) if len(providers) == 1 else None + ) + + +async def _listed_files( + llm_router: Router | None, + user_api_key_dict: UserAPIKeyAuth, + custom_llm_provider: str | None, + target_model_names: str | None, + routed_model: str | None, +) -> _ListedFiles | _UnscopedFileList: + if routed_model is not None and llm_router is not None: + return _files_serving_model(llm_router, routed_model) + if target_model_names: + target_model_name: Final = _single_target_model_name(target_model_names) + if isinstance(target_model_name, _UnscopedFileList): + return target_model_name + if llm_router is None: + return _UnscopedFileList( + status_code=500, detail="LLM Router not initialized. Ensure models added to proxy." + ) + await get_authorized_credentials_for_model( + llm_router=llm_router, + model_id=target_model_name, + user_api_key_dict=user_api_key_dict, + operation_context="file list", + ) + return _files_serving_model(llm_router, target_model_name) + if custom_llm_provider is None: + return _ListedFiles(None, None) + return _files_on_provider(llm_router, custom_llm_provider) + + @router.get( "/{provider}/v1/files", dependencies=[Depends(user_api_key_auth)], @@ -1697,6 +1883,8 @@ async def list_files( purpose: str | None = None, limit: int | None = None, after: str | None = None, + after_id: str | None = None, + before_id: str | None = None, ): """ Returns information about a specific file. that can be used across - Assistants API, Batch API @@ -1739,6 +1927,10 @@ async def list_files( ) response: Any | None = None + owned_files_hook: Final = proxy_logging_obj.get_proxy_hook("managed_files") + list_owned_files_only: Final = litellm.require_managed_files is True and not user_api_key_has_admin_view( + user_api_key_dict + ) # Check for model-based credential routing (no file_id encoding check for list) should_route, model_used, _, credentials = await handle_model_based_routing( @@ -1750,7 +1942,36 @@ async def list_files( check_file_id_encoding=False, ) - if should_route and credentials is not None: + if list_owned_files_only: + if after and after_id and after != after_id: + raise HTTPException( + status_code=400, + detail="Pass the list cursor as either 'after' or 'after_id', not both with different ids.", + ) + if not isinstance(owned_files_hook, BaseFileEndpoints): + raise HTTPException( + status_code=500, + detail="Managed file listing is unavailable, so require_managed_files cannot scope the list to the caller.", + ) + listed_files: Final = await _listed_files( + llm_router=llm_router, + user_api_key_dict=user_api_key_dict, + custom_llm_provider=await _requested_custom_llm_provider(request=request, provider=provider), + target_model_names=target_model_names, + routed_model=model_used if should_route else None, + ) + if isinstance(listed_files, _UnscopedFileList): + _raise_unscoped_file_list(listed_files) + response = await _list_owned_managed_files( # rebind-ok: each dispatch branch binds response + managed_files_obj=owned_files_hook, + user_api_key_dict=user_api_key_dict, + purpose=purpose, + limit=limit if limit is not None else _default_file_list_limit(listed_files.custom_llm_provider), + after=after or after_id, + before=before_id, + model_scope=listed_files.model_scope, + ) + elif should_route and credentials is not None: # Use model-based routing with credentials from config prepare_data_with_credentials(data=data, credentials=credentials, include_internal_credentials=True) response = await litellm.afile_list( @@ -1762,12 +1983,9 @@ async def list_files( verbose_proxy_logger.debug("Listed files using model: %s", model_used) elif target_model_names and isinstance(target_model_names, str): - target_model_names_list: Final = target_model_names.split(",") - if len(target_model_names_list) != 1: - raise HTTPException( - status_code=400, - detail="target_model_names on list files must be a list of one model name. Example: ['gpt-4o']", - ) + target_model_name: Final = _single_target_model_name(target_model_names) + if isinstance(target_model_name, _UnscopedFileList): + _raise_unscoped_file_list(target_model_name) if llm_router is None: raise HTTPException( status_code=500, @@ -1775,7 +1993,7 @@ async def list_files( ) credentials = await get_authorized_credentials_for_model( llm_router=llm_router, - model_id=target_model_names_list[0], + model_id=target_model_name, user_api_key_dict=user_api_key_dict, operation_context="file list", ) @@ -1786,20 +2004,17 @@ async def list_files( **data, ) else: - custom_llm_provider: Final = ( - provider - or get_custom_llm_provider_from_request_headers(request=request) - or get_custom_llm_provider_from_request_query(request=request) - or await get_custom_llm_provider_from_request_body(request=request) - ) + custom_llm_provider: Final = await _requested_custom_llm_provider(request=request, provider=provider) managed_files_obj: Final = proxy_logging_obj.get_proxy_hook("managed_files") if custom_llm_provider is None and isinstance(managed_files_obj, BaseFileEndpoints): - response = await managed_files_obj.afile_list( - purpose=purpose, - litellm_parent_otel_span=user_api_key_dict.parent_otel_span, + response = await _list_owned_managed_files( # rebind-ok: each dispatch branch binds response + managed_files_obj=managed_files_obj, user_api_key_dict=user_api_key_dict, + purpose=purpose, limit=limit, after=after, + before=None, + model_scope=None, ) else: resolved_custom_llm_provider: Final = custom_llm_provider or "openai" diff --git a/litellm/proxy/pass_through_endpoints/llm_passthrough_endpoints.py b/litellm/proxy/pass_through_endpoints/llm_passthrough_endpoints.py index 9eef4f0ef9d..972ec18d487 100644 --- a/litellm/proxy/pass_through_endpoints/llm_passthrough_endpoints.py +++ b/litellm/proxy/pass_through_endpoints/llm_passthrough_endpoints.py @@ -50,6 +50,7 @@ from litellm.constants import ( from litellm.exceptions import BlockedPiiEntityError, GuardrailRaisedException from litellm.integrations.custom_guardrail import guardrail_request_data_with_streaming, is_guardrail_intervention from litellm.litellm_core_utils.aws_partition import get_aws_dns_suffix +from litellm.litellm_core_utils.fallback_generalizations import match_routing_generalization from litellm.llms.anthropic.common_utils import AnthropicModelInfo, merge_anthropic_beta_headers from litellm.llms.azure.passthrough.transformation import ( foreign_azure_deployment, @@ -87,6 +88,7 @@ from litellm.proxy.common_request_processing import ( ProxyBaseLLMRequestProcessing, model_deployments_support_stream_options, open_sse_before_first_byte, + resolve_litellm_call_id, ) from litellm.proxy.common_utils.http_parsing_utils import ( # noqa: F401 # legacy module exports _read_request_body, # pyright: ignore[reportPrivateUsage,reportUnusedImport] # backwards-compatible package export @@ -99,10 +101,16 @@ from litellm.proxy.common_utils.http_parsing_utils import ( # noqa: F401 # leg safe_get_request_headers, safe_set_request_parsed_body, ) +from litellm.proxy.common_utils.openai_error_payload import LITELLM_CALL_ID_HEADER from litellm.proxy.common_utils.resource_ownership import is_proxy_admin from litellm.proxy.common_utils.sse_keepalive import ( wrap_passthrough_sse_bytes_with_keepalive_pings, ) +from litellm.proxy.common_utils.token_count_log import ( + deployment_model_id, + logged_provider_token_count, + rejected_token_count, +) from litellm.proxy.pass_through_endpoints.common_utils import get_litellm_virtual_key from litellm.proxy.pass_through_endpoints.injected_stream_usage import ( stream_usage_relay, @@ -691,6 +699,20 @@ async def typesafe_proxy_route( return await endpoint_func(request, fastapi_response, user_api_key_dict) +_COST_MAP_ENTRIES: Final = TypeAdapter(Mapping[str, object]) + + +def typesafe_allowlist_model_names() -> tuple[str, ...]: + if not passthrough_endpoint_router.has_credentials(custom_llm_provider="typesafe"): + return () + cost_map: Final = _COST_MAP_ENTRIES.validate_python(litellm.model_cost) # pyright: ignore[reportUnknownMemberType] # legacy registry is validated at this boundary + priced_names: Final = (name.removeprefix("typesafe/") for name in cost_map if name.startswith("typesafe/")) + jev_models_typesafe_serves: Final = sorted( + name for name in priced_names if match_routing_generalization(name) == "typesafe" + ) + return ("typesafe/*", *jev_models_typesafe_serves) + + @router.post( "/laya/v1/systemone", tags=["Laya Pass-through", "pass-through"], @@ -1259,6 +1281,7 @@ async def handle_bedrock_count_tokens( from litellm.llms.bedrock.count_tokens.handler import BedrockCountTokensHandler from litellm.proxy.proxy_server import llm_router + litellm_call_id: Final = resolve_litellm_call_id(request.headers.get(LITELLM_CALL_ID_HEADER)) try: # Initialize the handler handler: Final = BedrockCountTokensHandler() @@ -1266,40 +1289,45 @@ async def handle_bedrock_count_tokens( # Extract model from request body model: Final = _optional_str(request_body.get("model")) if not model: - raise HTTPException(status_code=400, detail={"error": "Model is required in request body"}) + raise rejected_token_count( + HTTPException(status_code=400, detail={"error": "Model is required in request body"}), + litellm_call_id, + None, + ) # Get model parameters from router litellm_params: Final = {"user_api_key_dict": user_api_key_dict} resolved_model = model # Default fallback - if llm_router: - deployments: Final = llm_router.get_model_list(model_name=model) - if deployments and len(deployments) > 0: - # Get the first matching deployment - deployment: Final = deployments[0] - model_litellm_params: Final = deployment.get("litellm_params", {}) + deployments: Final = llm_router.get_model_list(model_name=model) if llm_router else None + deployment: Final = deployments[0] if deployments else None + if deployment is not None: + model_litellm_params: Final = deployment.get("litellm_params", {}) - # Get the resolved model ID from the configuration - if "model" in model_litellm_params: - resolved_model = model_litellm_params["model"] + # Get the resolved model ID from the configuration + if "model" in model_litellm_params: + resolved_model = model_litellm_params["model"] - # Copy all litellm_params - BaseAWSLLM will handle AWS credential discovery - for key, value in model_litellm_params.items(): - if key != "user_api_key_dict": # Don't overwrite user_api_key_dict - litellm_params[key] = value + # Copy all litellm_params - BaseAWSLLM will handle AWS credential discovery + for key, value in model_litellm_params.items(): + if key != "user_api_key_dict": # Don't overwrite user_api_key_dict + litellm_params[key] = value verbose_proxy_logger.debug("Count tokens litellm_params: %s", litellm_params) verbose_proxy_logger.debug("Resolved model: %s", resolved_model) - # Handle the count tokens request - result: Final = await handler.handle_count_tokens_request( - request_data=request_body, - litellm_params=litellm_params, - resolved_model=resolved_model, + return await logged_provider_token_count( + handler.handle_count_tokens_request( + request_data=request_body, + litellm_params=litellm_params, + resolved_model=resolved_model, + ), + litellm_call_id=litellm_call_id, + request_model=model, + model_id=deployment_model_id(deployment), + model_used=partial(handler.count_tokens_model_id, resolved_model), ) - return result - except BedrockError as e: # Convert BedrockError to HTTPException for FastAPI verbose_proxy_logger.error("BedrockError in handle_bedrock_count_tokens: %s", e) diff --git a/litellm/proxy/pass_through_endpoints/llm_provider_handlers/anthropic_passthrough_logging_handler.py b/litellm/proxy/pass_through_endpoints/llm_provider_handlers/anthropic_passthrough_logging_handler.py index 7c7eb51bc5d..5415314f29b 100644 --- a/litellm/proxy/pass_through_endpoints/llm_provider_handlers/anthropic_passthrough_logging_handler.py +++ b/litellm/proxy/pass_through_endpoints/llm_provider_handlers/anthropic_passthrough_logging_handler.py @@ -29,6 +29,7 @@ from litellm.llms.anthropic.messages.stream_assembly import ( split_sse_chunk_into_events, ) from litellm.llms.bedrock.common_utils import BEDROCK_INVOKE_TRACE_FIELD +from litellm.llms.custom_httpx.sse_lines import split_sse_lines from litellm.proxy._types import PassThroughEndpointLoggingTypedDict from litellm.proxy.auth.auth_utils import get_end_user_id_from_request_body from litellm.proxy.pass_through_endpoints.llm_provider_handlers.batch_attribution import ( @@ -61,7 +62,7 @@ _JSON_OBJECT: Final = TypeAdapter(Mapping[str, object], config=ConfigDict(hide_i def _event_payload(event: str) -> Mapping[str, object] | None: data_lines: Final = tuple( - line.strip()[len("data:") :].strip() for line in event.splitlines() if line.strip().startswith("data:") + line.strip()[len("data:") :].strip() for line in split_sse_lines(event) if line.strip().startswith("data:") ) if not data_lines or data_lines[0] in ("", "[DONE]"): return None @@ -362,7 +363,7 @@ class AnthropicPassthroughLoggingHandler: ) -> str | None: for raw in all_chunks: text = raw.decode("utf-8") if isinstance(raw, bytes) else raw - for line in text.splitlines(): + for line in split_sse_lines(text): if not line.startswith("data:"): continue try: @@ -402,7 +403,7 @@ class AnthropicPassthroughLoggingHandler: """ for raw in reversed(all_chunks): text = raw.decode("utf-8") if isinstance(raw, bytes) else raw - for line in reversed(text.splitlines()): + for line in reversed(split_sse_lines(text)): if not line.startswith("data:"): continue try: diff --git a/litellm/proxy/pass_through_endpoints/llm_provider_handlers/tinyfish_passthrough_logging_handler.py b/litellm/proxy/pass_through_endpoints/llm_provider_handlers/tinyfish_passthrough_logging_handler.py index 2afc1d17bc2..0c4a3f64852 100644 --- a/litellm/proxy/pass_through_endpoints/llm_provider_handlers/tinyfish_passthrough_logging_handler.py +++ b/litellm/proxy/pass_through_endpoints/llm_provider_handlers/tinyfish_passthrough_logging_handler.py @@ -21,6 +21,7 @@ from litellm.llms.custom_httpx.http_handler import ( AsyncHTTPHandler, get_async_httpx_client, ) +from litellm.llms.custom_httpx.sse_lines import split_sse_lines from litellm.proxy._types import PassThroughEndpointLoggingTypedDict from litellm.types.llms.custom_http import httpxSpecialProvider from litellm.types.passthrough_endpoints.tinyfish import ( @@ -81,7 +82,7 @@ def sse_poller_spawned(logging_obj: LiteLLMLoggingObj) -> bool: def run_id_from_sse_frames(frames: bytes) -> str | None: - return _run_id_from_sse_chunks(frames.decode("utf-8", errors="replace").splitlines()) + return _run_id_from_sse_chunks(split_sse_lines(frames.decode("utf-8", errors="replace"))) def resolve_tinyfish_agent_api_base() -> str: diff --git a/litellm/proxy/pass_through_endpoints/managed_id_rewriter.py b/litellm/proxy/pass_through_endpoints/managed_id_rewriter.py index a5a04fb68d2..cae8ccc93ee 100644 --- a/litellm/proxy/pass_through_endpoints/managed_id_rewriter.py +++ b/litellm/proxy/pass_through_endpoints/managed_id_rewriter.py @@ -51,6 +51,7 @@ from litellm.llms.base_llm.managed_resources.isolation import ( can_access_resource, resolve_resource_owner_id, ) +from litellm.llms.custom_httpx.sse_lines import split_sse_lines from litellm.proxy._types import UserAPIKeyAuth from litellm.proxy.batches_endpoints.common_utils import validate_batch_list_limit from litellm.proxy.common_utils.sse_keepalive import split_complete_sse_frames @@ -242,6 +243,12 @@ def _passthrough_sentinel_model_id(provider: str) -> str: return f"_passthrough_{provider}" +def passthrough_file_model_id(provider: str) -> str | None: + if (provider, "/v1/files") not in _LIST_ROUTE_TABLE: + return None + return _passthrough_sentinel_model_id(provider) + + # Key under which the provider marker is stored in a file row's model_mappings. # Its value lands in flat_model_file_ids (built from model_mappings.values()), # giving the file table a DB-queryable provider scope it otherwise lacks. @@ -824,7 +831,7 @@ _SSE_EVENT_ADAPTER: Final = TypeAdapter(Mapping[str, JsonValue]) def _first_streamed_response(frames: bytes) -> tuple[str, Mapping[str, JsonValue]] | None: - for line in frames.decode("utf-8", errors="replace").splitlines(): + for line in split_sse_lines(frames.decode("utf-8", errors="replace")): if not line.startswith(_SSE_DATA_PREFIX): continue try: diff --git a/litellm/proxy/pass_through_endpoints/pass_through_endpoints.py b/litellm/proxy/pass_through_endpoints/pass_through_endpoints.py index f2ea1752a86..e017eee3d27 100644 --- a/litellm/proxy/pass_through_endpoints/pass_through_endpoints.py +++ b/litellm/proxy/pass_through_endpoints/pass_through_endpoints.py @@ -30,6 +30,7 @@ from pydantic import TypeAdapter from starlette.datastructures import UploadFile as StarletteUploadFile from starlette.routing import BaseRoute, Route from starlette.websockets import WebSocketState +from typing_extensions import ReadOnly from websockets.asyncio.client import connect from websockets.exceptions import ( ConnectionClosedError, @@ -54,6 +55,7 @@ from litellm.integrations.custom_guardrail import ( without_server_streaming_classification, ) from litellm.integrations.custom_logger import CustomLogger +from litellm.integrations.otel.model.semconv import PASSTHROUGH_OPERATION_KEY, GenAIOperation from litellm.litellm_core_utils.core_helpers import ( bind_budget_reservation_to_callbacks, get_metadata_variable_name_from_kwargs, @@ -151,6 +153,7 @@ from .success_handler import PassThroughEndpointLogging from .upstream_usage_headers import ( UpstreamReportedUsage, apply_upstream_reported_model, + apply_upstream_reported_operation, apply_upstream_reported_usage, ) @@ -171,8 +174,17 @@ def _is_mergeable_client_metadata(key: str, value: object) -> bool: return not key.startswith("user_api_key_") and (key != "model_info" or isinstance(value, Mapping)) +class _RegisteredPassThroughRoute(TypedDict): + endpoint_id: ReadOnly[str] + path: ReadOnly[str | None] + type: ReadOnly[str] + methods: ReadOnly[str | bool | list[str] | tuple[str, ...] | Mapping[str, object]] + auth: ReadOnly[bool] + passthrough_params: ReadOnly[Mapping[str, object]] + + # Global registry to track registered pass-through routes and prevent memory leaks -_registered_pass_through_routes: Final[dict[str, dict[str, str | bool | list[str] | Mapping[str, object]]]] = {} +_registered_pass_through_routes: Final[dict[str, _RegisteredPassThroughRoute]] = {} def get_response_body(response: httpx.Response) -> dict | None: @@ -1134,6 +1146,7 @@ async def pass_through_request( guardrails_config: dict | None = None, timeout: float | None = None, upstream_headers_filter: Callable[[Mapping[str, str]], Mapping[str, str]] = _unfiltered_headers, + operation: GenAIOperation | None = None, ): """ Pass through endpoint handler, makes the httpx request for pass-through endpoints and ensures logging hooks are called @@ -1155,6 +1168,7 @@ async def pass_through_request( timeout: Optional per-endpoint timeout in seconds. Falls back to general_settings.pass_through_request_timeout, then 600s. upstream_headers_filter: Optional last rewrite of the headers sent upstream, after x-pass- expansion + operation: Optional GenAI operation the route reports, unless the upstream names its own """ from litellm.exceptions import ModifyResponseException from litellm.litellm_core_utils.litellm_logging import Logging @@ -1353,6 +1367,8 @@ async def pass_through_request( call_type="pass_through_endpoint", ) logging_obj.model_call_details["litellm_call_id"] = litellm_call_id + if operation is not None: + logging_obj.model_call_details[PASSTHROUGH_OPERATION_KEY] = operation ## PASSTHROUGH MANAGED ID RESOLUTION (INPUT) ## # Resolve managed IDs in path, query params, and body back to raw @@ -1553,6 +1569,7 @@ async def pass_through_request( logging_obj=logging_obj, headers=response.headers, ) + apply_upstream_reported_operation(logging_obj, response.headers) relay_response: Final = await _log_passthrough_upstream_failure( response=response, @@ -1646,6 +1663,7 @@ async def pass_through_request( logging_obj=logging_obj, headers=response.headers, ) + apply_upstream_reported_operation(logging_obj, response.headers) if _is_streaming_response(response) is True: logging_obj.stream = True @@ -2161,6 +2179,7 @@ def create_pass_through_route( config_file_path: str | None = None, timeout: float | None = None, upstream_headers_filter: Callable[[Mapping[str, str]], Mapping[str, str]] = _unfiltered_headers, + operation: GenAIOperation | None = None, ): # check if target is an adapter.py or a url from litellm._uuid import uuid @@ -2230,7 +2249,7 @@ def create_pass_through_route( status_code=status.HTTP_405_METHOD_NOT_ALLOWED, detail=f"Method {request.method} is not allowed for pass-through endpoint {path}.", ) - target_params: Final = { + target_params: Final[dict[str, object]] = { "target": target, "custom_headers": custom_headers, "forward_headers": _forward_headers, @@ -2262,7 +2281,9 @@ def create_pass_through_route( # Ensure custom_headers is a dict. Botocore returns a HeadersDict # for SigV4-prepared requests, which is a Mapping but not a dict. - headers_dict: Final = dict(param_custom_headers) if isinstance(param_custom_headers, Mapping) else {} + headers_dict: Final[dict[str, object]] = ( + {**param_custom_headers} if isinstance(param_custom_headers, Mapping) else {} + ) # Ensure query_params and custom_body are dicts or None final_query_params: Final = query_params_data if isinstance(query_params_data, dict) else {} @@ -2301,6 +2322,7 @@ def create_pass_through_route( guardrails_config=cast(dict | None, param_guardrails), timeout=cast(float | None, param_timeout), upstream_headers_filter=upstream_headers_filter, + operation=operation, ) finally: if hasattr(request.state, LITELLM_PASS_THROUGH_CUSTOM_BODY_STATE_KEY): @@ -3094,9 +3116,7 @@ class SafeRouteAdder: return f"{path}/{{subpath:path}}" return None - def registered_route_methods( - route_info: Mapping[str, str | bool | Sequence[str] | Mapping[str, object]], - ) -> tuple[tuple[str, str], ...]: + def registered_route_methods(route_info: _RegisteredPassThroughRoute) -> tuple[tuple[str, str], ...]: starlette_path: Final = registered_route_path(route_info) methods: Final = route_info.get("methods") if starlette_path is None or not isinstance(methods, (list, tuple)): @@ -3232,6 +3252,7 @@ class InitPassThroughEndpointHelpers: guardrails=guardrails, config_file_path=config_file_path, timeout=timeout, + operation=GenAIOperation.LITELLM_PASSTHROUGH, ), methods=methods, dependencies=dependencies, @@ -3316,6 +3337,7 @@ class InitPassThroughEndpointHelpers: guardrails=guardrails, config_file_path=config_file_path, timeout=timeout, + operation=GenAIOperation.LITELLM_PASSTHROUGH, ), methods=methods, dependencies=dependencies, @@ -3450,7 +3472,7 @@ class InitPassThroughEndpointHelpers: return (comparison_route, *forwarded) @staticmethod - def get_registered_pass_through_route(route: str, method: str | None = None) -> dict[str, Any] | None: + def get_registered_pass_through_route(route: str, method: str | None = None) -> _RegisteredPassThroughRoute | None: """Get passthrough params for a given route and optionally filter by HTTP method""" comparison_route: Final = InitPassThroughEndpointHelpers._route_for_registry_lookup(route) for key in _registered_pass_through_routes: diff --git a/litellm/proxy/pass_through_endpoints/passthrough_endpoint_router.py b/litellm/proxy/pass_through_endpoints/passthrough_endpoint_router.py index 270a1cc2f3b..1d0b3d00434 100644 --- a/litellm/proxy/pass_through_endpoints/passthrough_endpoint_router.py +++ b/litellm/proxy/pass_through_endpoints/passthrough_endpoint_router.py @@ -1,4 +1,5 @@ import json +import os from collections.abc import Callable from typing import TYPE_CHECKING, Final @@ -88,6 +89,14 @@ class PassthroughEndpointRouter: ) return _resolve_oidc_reference(get_secret_str(_env_variable_name)) + def has_credentials(self, custom_llm_provider: str) -> bool: + if self._get_deployment_api_key(custom_llm_provider=custom_llm_provider, region_name=None) is not None: + return True + env_variable_name: Final = self._get_default_env_variable_name_passthrough_endpoint( + custom_llm_provider=custom_llm_provider, + ) + return bool(os.environ.get(env_variable_name)) + def _get_deployment_api_key( self, custom_llm_provider: str, diff --git a/litellm/proxy/pass_through_endpoints/upstream_usage_headers.py b/litellm/proxy/pass_through_endpoints/upstream_usage_headers.py index e9d93fb306d..223f6a5e760 100644 --- a/litellm/proxy/pass_through_endpoints/upstream_usage_headers.py +++ b/litellm/proxy/pass_through_endpoints/upstream_usage_headers.py @@ -5,18 +5,21 @@ price the request from the response body. Those targets report the totals for the whole HTTP request in ``x-litellm-*`` response headers instead; LiteLLM records the reported values without recomputing them. A target may also name the request in ``x-litellm-upstream-model`` so its spend can be told apart from -other requests that carry no ``model`` in the body. +other requests that carry no ``model`` in the body, and name the GenAI +operation it performed, which labels the request's trace. """ import math from collections.abc import Mapping from dataclasses import dataclass +from types import MappingProxyType from typing import Final import httpx from litellm._logging import verbose_proxy_logger from litellm.constants import MAX_SPEND_LOG_MODEL_NAME_LENGTH +from litellm.integrations.otel.model.semconv import PASSTHROUGH_OPERATION_KEY, GenAIOperation from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj from litellm.types.utils import Usage @@ -25,6 +28,8 @@ UPSTREAM_TOTAL_TOKENS_HEADER: Final = "x-litellm-total-tokens" # Deliberately not x-litellm-model-name/-id/-group: the gateway already sends # those to clients, and pass-through relays upstream headers back to the client. UPSTREAM_MODEL_HEADER: Final = "x-litellm-upstream-model" +UPSTREAM_OPERATION_NAME_HEADER: Final = "x-litellm-operation-name" +_OPERATIONS_BY_NAME: Final = MappingProxyType({operation.value: operation for operation in GenAIOperation}) # model_call_details key holding what the upstream reported, so later stages of # the success path can tell an upstream-reported cost apart from one LiteLLM @@ -175,3 +180,19 @@ def has_upstream_reported_usage(logging_obj: LiteLLMLoggingObj) -> bool: means zero, never a fallback to someone else's estimate. """ return isinstance(logging_obj.model_call_details.get(UPSTREAM_REPORTED_USAGE_KEY), UpstreamReportedUsage) + + +def apply_upstream_reported_operation(logging_obj: LiteLLMLoggingObj, headers: Mapping[str, str]) -> None: + """Record the GenAI operation the upstream named, overriding the route's label. An unknown name is ignored.""" + raw_operation: Final = headers.get(UPSTREAM_OPERATION_NAME_HEADER) + if raw_operation is None: + return + operation: Final = _OPERATIONS_BY_NAME.get(raw_operation) + if operation is None: + verbose_proxy_logger.warning( + "pass_through_endpoint: upstream sent unknown %s=%r; ignoring it", + UPSTREAM_OPERATION_NAME_HEADER, + raw_operation, + ) + return + logging_obj.model_call_details[PASSTHROUGH_OPERATION_KEY] = operation # rebind-ok: annotates the request's record diff --git a/litellm/proxy/policy_engine/init_policies.py b/litellm/proxy/policy_engine/init_policies.py index 59d15b0ba0a..2d0e9d25368 100644 --- a/litellm/proxy/policy_engine/init_policies.py +++ b/litellm/proxy/policy_engine/init_policies.py @@ -11,7 +11,7 @@ from collections.abc import Mapping, Sequence from itertools import chain from typing import TYPE_CHECKING, Any, Final, Optional -from litellm._logging import print_startup_message, verbose_proxy_logger +from litellm._logging import print_startup_message, print_startup_warning, verbose_proxy_logger from litellm.proxy.policy_engine.attachment_registry import get_attachment_registry from litellm.proxy.policy_engine.policy_registry import get_policy_registry from litellm.proxy.policy_engine.policy_validator import PolicyValidator @@ -93,7 +93,7 @@ def _print_policies_on_startup( ) else: print_startup_message("\n".join((header, *policy_lines))) - print_startup_message( + print_startup_warning( f"\n{_yellow_color_code}Warning: No policy_attachments configured. Policies will not be applied to any requests.{_reset_color_code}\n", ) sys.stdout.flush() diff --git a/litellm/proxy/proxy_cli.py b/litellm/proxy/proxy_cli.py index 909f6de40cd..0d8ab98a0b1 100644 --- a/litellm/proxy/proxy_cli.py +++ b/litellm/proxy/proxy_cli.py @@ -10,16 +10,17 @@ import sys import urllib.parse as urlparse from collections.abc import Callable, Iterable, Mapping, Sequence from pathlib import Path -from typing import TYPE_CHECKING, Any, Final +from typing import TYPE_CHECKING, Annotated, Any, Final import click import httpx from click.core import ParameterSource from dotenv import load_dotenv -from pydantic import ConfigDict +from pydantic import BeforeValidator, ConfigDict, TypeAdapter +from typing_extensions import ReadOnly, TypedDict import litellm -from litellm._logging import print_startup_message +from litellm._logging import StartupOutputSettings, print_startup_message, print_startup_warning, terminal_text from litellm.constants import DEFAULT_NUM_WORKERS_LITELLM_PROXY from litellm.proxy.db.pgbouncer import ( PgBouncerError, @@ -205,7 +206,7 @@ def deprecated_v2_flag_passed_on_cli() -> bool: def _print_enforce_prisma_migration_check_notice() -> None: - print_startup_message( + print_startup_warning( "\033[1;33mLiteLLM Proxy: --enforce_prisma_migration_check is " "deprecated and has no effect, because the proxy always exits " "when database setup fails at startup. You can safely remove it.\033[0m", @@ -227,6 +228,36 @@ def _print_or_hold_enforce_prisma_migration_check_notice( return print_once +def _empty_as_none(value: object) -> object: + return value or None + + +class _ConfigStartupOutputSettings(TypedDict, total=False): + litellm_settings: ReadOnly[Annotated[StartupOutputSettings | None, BeforeValidator(_empty_as_none)]] + + +_CONFIG_STARTUP_OUTPUT_SETTINGS: Final = TypeAdapter(_ConfigStartupOutputSettings) + + +def _apply_config_suppress_startup_output(litellm_settings: StartupOutputSettings | None) -> None: + if litellm_settings is None or litellm_settings.get("suppress_startup_output") is not True: + return + litellm.suppress_startup_output = True + os.environ["LITELLM_SUPPRESS_STARTUP_OUTPUT"] = "true" + + +def _apply_config_logging_settings(litellm_settings: StartupOutputSettings | None) -> None: + """Turn on the config's json_logs and suppress_startup_output before any worker starts. Workers that + uvicorn or granian spawn import litellm afresh and read both from the env at import, so they log JSON + and stay quiet from their first line instead of from when load_config reaches the key.""" + _apply_config_suppress_startup_output(litellm_settings) + if litellm_settings is None or litellm_settings.get("json_logs") is not True: + return + litellm.json_logs = True + os.environ["JSON_LOGS"] = "true" + litellm.turn_on_json() + + class ProxyInitializationHelpers: @staticmethod def echo_litellm_version(): @@ -373,7 +404,7 @@ class ProxyInitializationHelpers: if "timeout_worker_healthcheck" in inspect.signature(uvicorn.Config.__init__).parameters: uvicorn_args["timeout_worker_healthcheck"] = timeout_worker_healthcheck else: - print_startup_message( + print_startup_warning( f"\033[1;33mLiteLLM Proxy: --timeout_worker_healthcheck " f"requires uvicorn>=0.37.0, but installed uvicorn=={uvicorn.__version__}. " f"Ignoring the flag.\033[0m", @@ -396,7 +427,7 @@ class ProxyInitializationHelpers: import uvicorn if max_requests_before_restart is None: - print_startup_message( + print_startup_warning( "\033[1;33mLiteLLM Proxy: --max_requests_before_restart_jitter " "has no effect without --max_requests_before_restart\033[0m\n", ) @@ -404,7 +435,7 @@ class ProxyInitializationHelpers: if "limit_max_requests_jitter" in inspect.signature(uvicorn.Config.__init__).parameters: uvicorn_args["limit_max_requests_jitter"] = jitter else: - print_startup_message( + print_startup_warning( f"\033[1;33mLiteLLM Proxy: --max_requests_before_restart_jitter " f"requires uvicorn>=0.41.0, but installed uvicorn=={uvicorn.__version__}. " f"Ignoring the flag.\033[0m", @@ -571,12 +602,12 @@ class ProxyInitializationHelpers: print_startup_message(f"\033[1;32mLiteLLM Proxy: Starting server on {host}:{port} using Granian\033[0m\n") if max_requests_before_restart is not None: - print_startup_message( + print_startup_warning( "\033[1;33mLiteLLM: --max_requests_before_restart is not supported by Granian " "(Granian uses workers_lifetime in seconds, not a per-request limit).\033[0m\n", ) if ciphers is not None: - print_startup_message("\033[1;33mLiteLLM: --ciphers is not applied when using --run_granian.\033[0m\n") + print_startup_warning("\033[1;33mLiteLLM: --ciphers is not applied when using --run_granian.\033[0m\n") kwargs: Final[dict[str, object]] = { "target": "litellm.proxy.proxy_server:app", @@ -698,7 +729,7 @@ class ProxyInitializationHelpers: gunicorn_options["max_requests"] = max_requests_before_restart if max_requests_before_restart_jitter is not None: if max_requests_before_restart is None: - print_startup_message( + print_startup_warning( "\033[1;33mLiteLLM Proxy: --max_requests_before_restart_jitter " "has no effect without --max_requests_before_restart\033[0m\n", ) @@ -739,7 +770,7 @@ class ProxyInitializationHelpers: with open(os.devnull, "w") as devnull: subprocess.Popen(command, stdout=devnull, stderr=devnull) except Exception as e: - print_startup_message(f""" + print_startup_warning(f""" LiteLLM Warning: proxy started with `ollama` model\n`ollama serve` failed with Exception{e}. \nEnsure you run `ollama serve` """) @@ -1325,6 +1356,19 @@ def run_server( os.environ[k] = v litellm_settings = None + env_config_file: Final = os.environ.get("CONFIG_FILE_PATH") + if ( + env_config_file + and os.environ.get("LITELLM_CONFIG_BUCKET_NAME") is None + and ProxyConfig().is_yaml(config_file_path=env_config_file) + ): + import asyncio + + _apply_config_suppress_startup_output( + _CONFIG_STARTUP_OUTPUT_SETTINGS.validate_python( + asyncio.run(ProxyConfig().read_config_file(config_file_path=env_config_file)) + ).get("litellm_settings") + ) if config is not None: """ Allow user to pass in db url via config @@ -1342,17 +1386,9 @@ def run_server( ### LITELLM SETTINGS ### litellm_settings = _config.get("litellm_settings", None) - if ( - litellm_settings is not None - and "json_logs" in litellm_settings - and litellm_settings["json_logs"] is True - ): - import litellm - - litellm.json_logs = True - os.environ["JSON_LOGS"] = "true" - - litellm.turn_on_json() + _apply_config_logging_settings( + _CONFIG_STARTUP_OUTPUT_SETTINGS.validate_python(_config).get("litellm_settings") + ) if held_prisma_notice is not None: held_prisma_notice() ### GENERAL SETTINGS ### @@ -1450,7 +1486,9 @@ def run_server( _bad_scheme = unsupported_db_scheme(_candidate_url) if _bad_scheme is not None: print( - f"\033[1;31mLiteLLM Proxy: {unsupported_db_scheme_message(_db_env, _bad_scheme)}\033[0m", + terminal_text( + f"\033[1;31mLiteLLM Proxy: {unsupported_db_scheme_message(_db_env, _bad_scheme)}\033[0m" + ), file=sys.stderr, flush=True, ) @@ -1553,7 +1591,7 @@ def run_server( env_value=os.getenv("USE_V2_MIGRATION_RESOLVER"), ) if deprecated_v2_flag_passed_on_cli() and use_v2_resolver: - print_startup_message( + print_startup_warning( "\033[1;33mLiteLLM Proxy: --use_v2_migration_resolver is " "deprecated and has no effect, because the v2 migration " "resolver is now the default. You can safely remove it. To " @@ -1561,7 +1599,7 @@ def run_server( "--use_legacy_migration_resolver.\033[0m", ) if not use_v2_resolver: - print_startup_message( + print_startup_warning( "\033[1;33mLiteLLM Proxy: Using the legacy (v1) migration " "resolver. It performs the diff-and-force recovery that can " "cause schema thrashing during rolling deploys where two " @@ -1583,22 +1621,26 @@ def run_server( # issues, and any `prisma db push` against a # partitioned LiteLLM_SpendLogs. print( - f"\033[1;31mLiteLLM Proxy: Database migration cannot proceed. {e}\033[0m", + terminal_text(f"\033[1;31mLiteLLM Proxy: Database migration cannot proceed. {e}\033[0m"), file=sys.stderr, flush=True, ) sys.exit(2) if not setup_ok: print( - "\033[1;31mLiteLLM Proxy: Database setup failed after multiple retries. " - "The proxy cannot start safely. Please check your database connection and migration status.\033[0m" + terminal_text( + "\033[1;31mLiteLLM Proxy: Database setup failed after multiple retries. " + "The proxy cannot start safely. Please check your database connection and migration status.\033[0m" + ) ) sys.exit(1) else: print( - "\033[1;31mLiteLLM Proxy: a database URL is set but the prisma CLI is neither on PATH nor importable " - "as a package, so the database cannot be set up. Install it with `pip install 'litellm[extra_proxy]'` " - "or run a shipped LiteLLM image.\033[0m" + terminal_text( + "\033[1;31mLiteLLM Proxy: a database URL is set but the prisma CLI is neither on PATH nor importable " + "as a package, so the database cannot be set up. Install it with `pip install 'litellm[extra_proxy]'` " + "or run a shipped LiteLLM image.\033[0m" + ) ) sys.exit(1) pgbouncer_settings: Final = PgBouncerSettings() @@ -1609,8 +1651,10 @@ def run_server( ) if isinstance(pooled_database_url, PgBouncerError): print( - f"\033[1;31mLiteLLM Proxy: LITELLM_PGBOUNCER_ENABLED is set but the in-container pgbouncer " - f"could not start: {pooled_database_url.reason}\033[0m", + terminal_text( + f"\033[1;31mLiteLLM Proxy: LITELLM_PGBOUNCER_ENABLED is set but the in-container pgbouncer " + f"could not start: {pooled_database_url.reason}\033[0m" + ), file=sys.stderr, flush=True, ) @@ -1675,7 +1719,7 @@ def run_server( run_gunicorn=run_gunicorn is True, ) if single_worker_warning is not None: - print_startup_message(f"\033[1;33m{single_worker_warning}\033[0m\n") + print_startup_warning(f"\033[1;33m{single_worker_warning}\033[0m\n") if run_gunicorn is False and run_hypercorn is False and run_granian is False: if limit_concurrency is not None: uvicorn_args["limit_concurrency"] = limit_concurrency diff --git a/litellm/proxy/proxy_server.py b/litellm/proxy/proxy_server.py index 3b36ea5afce..5d034a72934 100644 --- a/litellm/proxy/proxy_server.py +++ b/litellm/proxy/proxy_server.py @@ -100,7 +100,11 @@ from litellm.litellm_core_utils.litellm_logging import ( ) from litellm.litellm_core_utils.safe_json_dumps import safe_dumps from litellm.litellm_core_utils.safe_json_loads import safe_json_loads -from litellm.litellm_core_utils.token_counter import offload_token_count +from litellm.litellm_core_utils.token_counter import ( + UnsupportedContentTypeError, + deployment_openai_model, + offload_token_count, +) from litellm.llms.bedrock.count_tokens.kimi_k3 import ( HUGGING_FACE_SOURCE, KimiK3Encodings, @@ -168,12 +172,7 @@ from litellm.proxy.common_utils.token_count_settings import ( ) from litellm.proxy.management_helpers.auto_router_availability import AutoRouterCatalogEntry, build_auto_router_catalog from litellm.proxy.management_helpers.model_group_custom_fields import model_group_custom_fields -from litellm.router_utils.access_windows import access_windows_config_error -from litellm.router_utils.add_retry_fallback_headers import ( - get_fallback_errors_from_headers, - get_hidden_params_dict, -) -from litellm.router_utils.auto_router_model_naming import ( +from litellm.router_strategy.auto_router.auto_router_model_naming import ( GATED_AUTO_ROUTER_CAPABILITIES, STRATEGY_ROUTER_PARAM_FIELDS, capability_limit_violation, @@ -181,12 +180,17 @@ from litellm.router_utils.auto_router_model_naming import ( count_capability_routers, validate_complexity_router_config_placement, ) -from litellm.router_utils.auto_router_tuning_baseline import ( +from litellm.router_strategy.auto_router.auto_router_tuning_baseline import ( TUNING_BASELINE_PARAM_NAME, mutable_tuned_identities, snapshot_tuning_baselines, tuning_limit_violation, ) +from litellm.router_utils.access_windows import access_windows_config_error +from litellm.router_utils.add_retry_fallback_headers import ( + get_fallback_errors_from_headers, + get_hidden_params_dict, +) from litellm.router_utils.common_utils import resolve_model_group_alias from litellm.router_utils.routing_groups import parse_routing_groups from litellm.types.caching import RedisPipelineIncrementOperation @@ -306,6 +310,7 @@ import litellm._redis from litellm import Router from litellm._internal_context import service_target, with_service_target from litellm._logging import ( + STARTUP_OUTPUT_SETTINGS, print_startup_message, redact_string, verbose_proxy_logger, @@ -524,6 +529,7 @@ from litellm.proxy.common_utils.openai_error_payload import ( LITELLM_CALL_ID_HEADER, headers_with_litellm_call_id, litellm_call_id_headers, + proxy_exception_for, with_litellm_call_id, ) from litellm.proxy.common_utils.periodic_reload_schedule import ( @@ -552,6 +558,11 @@ from litellm.proxy.common_utils.timezone_utils import ( get_budget_reset_settings, get_budget_reset_time, ) +from litellm.proxy.common_utils.token_count_log import ( + deployment_model_id, + logged_token_count, + rejected_token_count, +) from litellm.proxy.common_utils.user_api_key_cache import ( UserApiKeyCache, end_user_cache_key, @@ -661,7 +672,11 @@ from litellm.proxy.list_api.common import ( problem_response, request_validation_problem, ) -from litellm.proxy.litellm_pre_call_utils import LiteLLMProxyRequestSetup, add_litellm_data_to_request +from litellm.proxy.litellm_pre_call_utils import ( + SCHEDULER_PRIORITY_HEADER, + LiteLLMProxyRequestSetup, + add_litellm_data_to_request, +) from litellm.proxy.logging_endpoints.callback_logs_endpoints import ( rust_control_plane_router, ) @@ -5791,6 +5806,12 @@ class ProxyConfig: # verbose_proxy_logger.debug(f"loaded config={json.dumps(config, indent=4)}") return config + async def read_config_file(self, config_file_path: str) -> Mapping[str, object]: + """The config file with its includes merged, without the bucket, database and secret steps of get_config.""" + return await self._process_includes( + config=self._load_yaml_file(config_file_path), config_file_path=os.path.abspath(config_file_path) + ) + async def _process_includes(self, config: dict, config_file_path: str) -> dict: """ Process includes by appending their contents to the main config @@ -6415,13 +6436,8 @@ class ProxyConfig: search_tools_parsed: Final[list[SearchToolTypedDict]] = [] - print_startup_message("\033[32mLiteLLM: Proxy initialized with Search Tools:\033[0m") - for search_tool in search_tools_raw: - # Display loaded search tool search_tool_name = search_tool.get("search_tool_name", "") - search_provider = search_tool.get("litellm_params", {}).get("search_provider", "") - print_startup_message(f"\033[32m {search_tool_name} ({search_provider})\033[0m") # Handle os.environ/ variables in litellm_params litellm_params = search_tool.get("litellm_params", {}) @@ -6591,13 +6607,15 @@ class ProxyConfig: from litellm.types.integrations.prometheus import validate_caller_identity_settings validate_caller_identity_settings(litellm_settings) + if STARTUP_OUTPUT_SETTINGS.validate_python(litellm_settings).get("suppress_startup_output") is True: + litellm.suppress_startup_output = True # ANSI escape code for blue text blue_color_code: Final = "\033[94m" reset_color_code: Final = "\033[0m" for key, value in litellm_settings.items(): if key == "cache" and value is True: - print_startup_message(f"{blue_color_code}\nSetting Cache on Proxy") + print_startup_message(f"\n{blue_color_code}Setting Cache on Proxy{reset_color_code}") from litellm.caching.caching import Cache cache_params = {} @@ -6912,6 +6930,8 @@ class ProxyConfig: setattr(litellm, key, value) elif key == "drop_params": litellm.drop_params = drop_params_flag(value, "litellm_settings.drop_params", verbose_proxy_logger) + elif key == "suppress_startup_output": + continue else: verbose_proxy_logger.debug( "%s setting litellm.%s=%s%s", @@ -7267,6 +7287,13 @@ class ProxyConfig: ## SEARCH TOOLS SETTINGS search_tools: Final[list[SearchToolTypedDict] | None] = self.parse_search_tools(config) + if search_tools: + print_startup_message("\033[32mLiteLLM: Proxy initialized with Search Tools:\033[0m") + for tool in search_tools: + print_startup_message( + f"\033[32m {tool.get('search_tool_name', '')} " + f"({tool.get('litellm_params', {}).get('search_provider', '')})\033[0m" + ) ## SANDBOX TOOLS SETTINGS from litellm.sandbox.sandbox_tools import register_sandbox_tools @@ -9669,12 +9696,9 @@ async def initialize( master_key, \ user_custom_auth, \ prisma_client - from litellm.proxy.common_utils.banner import LITELLM_BANNER, show_banner + from litellm.proxy.common_utils.banner import LITELLM_BANNER - if litellm.json_logs: - print_startup_message(LITELLM_BANNER) - else: - show_banner() + print_startup_message(f"\n{LITELLM_BANNER}\n") if os.getenv("LITELLM_DONT_SHOW_FEEDBACK_BOX", "").lower() != "true": generate_feedback_box() user_model = model @@ -9816,7 +9840,7 @@ async def async_assistants_data_generator(response, user_api_key_dict: UserAPIKe request_data=request_data, ) verbose_proxy_logger.debug( - "\x1b[1;31mAn error occurred: %s\n\n Debug this by setting `--debug`, e.g. `litellm --model gpt-3.5-turbo --debug`", + "An error occurred: %s", e, ) if isinstance(e, HTTPException): @@ -10646,7 +10670,7 @@ async def async_data_generator( ) client_error: Final[Exception] = e if replacement is None else replacement verbose_proxy_logger.debug( - "\x1b[1;31mAn error occurred: %s\n\n Debug this by setting `--debug`, e.g. `litellm --model gpt-3.5-turbo --debug`", + "An error occurred: %s", e, ) @@ -12381,6 +12405,12 @@ async def model_list( hidden_names: Final = blocked_names | unhealthy_names + from litellm.proxy.pass_through_endpoints.llm_passthrough_endpoints import typesafe_allowlist_model_names + + asks_for_allowlist_names: Final = ( + include_model_access_groups is True and return_wildcard_routes is True and only_model_access_groups is not True + ) + # If scope=expand and user has admin privileges, return all proxy models if should_expand_scope: # Get all proxy models as if user is a proxy admin @@ -12401,7 +12431,10 @@ async def model_list( all_models = get_complete_model_list( key_models=[], team_models=[], - proxy_model_list=proxy_model_list, + proxy_model_list=[ + *proxy_model_list, + *(typesafe_allowlist_model_names() if asks_for_allowlist_names else ()), + ], user_model=None, infer_model_from_keys=False, return_wildcard_routes=include_wildcard_routes, @@ -12462,7 +12495,7 @@ async def model_list( # Otherwise, use the normal behavior (current implementation) # Get available models for the user - all_models = await get_available_models_for_user( + available_models: Final = await get_available_models_for_user( user_api_key_dict=user_api_key_dict, llm_router=llm_router, general_settings=general_settings, @@ -12475,6 +12508,11 @@ async def model_list( return_wildcard_routes=include_wildcard_routes, user_api_key_cache=user_api_key_cache, ) + offers_typesafe_allowlist_names: Final = ( + asks_for_allowlist_names and team_id is None and user_api_key_has_admin_view(user_api_key_dict) + ) + typesafe_names_to_offer: Final = typesafe_allowlist_model_names() if offers_typesafe_allowlist_names else () + all_models = [*available_models, *(name for name in typesafe_names_to_offer if name not in available_models)] undiscoverable_names: Final = undiscoverable_model_names( all_models, llm_router, user_api_key_dict, team_id or user_api_key_dict.team_id @@ -14628,6 +14666,7 @@ async def run_thread( # ) # async def get_available_routes(user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth)): from litellm.litellm_core_utils.tool_fields import DropPolicy, drop_policy +from litellm.llms.anthropic.count_tokens.token_counter import AnthropicTokenCounter from litellm.llms.base_llm.base_utils import BaseTokenCounter from litellm.llms.openai.responses.count_tokens.token_counter import OpenAITokenCounter from litellm.proxy.db.routing_prisma_wrapper import WriterPinnedClient @@ -14649,6 +14688,14 @@ from litellm.responses.litellm_completion_transformation.count_request import ( ) +def _with_client_oauth_token( + counter: BaseTokenCounter | None, client_oauth_token: str | None +) -> BaseTokenCounter | None: + if client_oauth_token is None or not isinstance(counter, AnthropicTokenCounter): + return counter + return AnthropicTokenCounter(client_oauth_token=client_oauth_token) + + def _get_provider_token_counter( deployment: dict, model_to_use: str ) -> tuple[BaseTokenCounter | None, str | None, str | None]: @@ -14839,6 +14886,7 @@ async def _try_native_responses_count( async def _provider_token_count( count_with: Callable[[str, str | None], Awaitable[Union["TokenCountResponse", ProviderCountFailure, None]]], model_to_use: str, + request_model: str, settings: TokenCountSettings, local_estimate_allowed: bool, ) -> Union["TokenCountResponse", ProviderCountFailure, None]: @@ -14861,17 +14909,28 @@ async def _provider_token_count( if count_model is None: return counted.model_copy(update={"count_source": "provider"}) return counted.model_copy(update={"count_source": "token_count_model", "model_used": count_model.model}) - failure: Final = ( - counted - if count_model is None or count_model.region is None - else counted.with_hint( - f"This model counts tokens with {count_model.model} in {count_model.region}. " - "If that region is not enabled for the AWS account, enable it or set token_count_model in model_info" - ) + pinned_count_model: Final = None if count_model is None or count_model.region is None else count_model + region_hint: Final = ( + None + if pinned_count_model is None + else f"This model counts tokens with {pinned_count_model.model} in {pinned_count_model.region}. " + "If that region is not enabled for the AWS account, enable it or set token_count_model in model_info" ) - if count_model is None and failure.cannot_count_model and settings.framing is not None and local_estimate_allowed: - return failure - raise failure.to_proxy_exception() + failure: Final = counted if region_hint is None else counted.with_hint(region_hint) + framing_can_stand_in: Final = (count_model is None or not count_model.configured) and ( + failure.cannot_count_model or (pinned_count_model is not None and failure.denied_in_region) + ) + if not (framing_can_stand_in and settings.framing is not None and local_estimate_allowed): + raise failure.to_proxy_exception() + if pinned_count_model is not None: + verbose_proxy_logger.warning( + "Token count for %s answered %s from %s in %s, so it falls back to the framed local estimate", + request_model, + failure.status_code, + pinned_count_model.model, + pinned_count_model.region, + ) + return failure @dataclass(frozen=True, slots=True) @@ -15244,16 +15303,21 @@ def _system_message(system: object) -> ChatCompletionSystemMessage | None: dependencies=[Depends(user_api_key_auth)], response_model=TokenCountResponse, ) -async def token_counter(request: TokenCountRequest, call_endpoint: bool = False): +async def token_counter( + request: TokenCountRequest, + call_endpoint: bool = False, + litellm_call_id: Annotated[str | None, Header(alias=LITELLM_CALL_ID_HEADER)] = None, +): """ Args: request: TokenCountRequest call_endpoint: bool - When set to "True" it will call the token counting endpoint - e.g Anthropic or Google AI Studio Token Counting APIs. + litellm_call_id: the x-litellm-call-id header, logged with the count so it joins the inference call's logs Returns: TokenCountResponse """ - return await count_request_tokens(request=request, call_endpoint=call_endpoint) + return await count_request_tokens(request=request, call_endpoint=call_endpoint, litellm_call_id=litellm_call_id) async def count_request_tokens( @@ -15264,6 +15328,69 @@ async def count_request_tokens( context_management: JsonValue = None, request_litellm_params: Mapping[str, JsonValue] = MappingProxyType({}), responses_request: Mapping[str, object] | None = None, + litellm_call_id: str | None = None, + client_oauth_token: str | None = None, +) -> TokenCountResponse: + call_id: Final = resolve_litellm_call_id(litellm_call_id) + if request.prompt is None and request.messages is None and request.contents is None: + raise rejected_token_count( + HTTPException(status_code=400, detail="prompt or messages or contents must be provided"), + call_id, + request.model, + ) + routed: Final = await _routed_count_deployment(request.model, responses_request) + count: Final = _count_request_tokens( + request=request, + routed=routed, + call_endpoint=call_endpoint, + messages_format=messages_format, + output_format=output_format, + context_management=context_management, + request_litellm_params=request_litellm_params, + responses_request=responses_request, + client_oauth_token=client_oauth_token, + ) + return await logged_token_count( + _with_anthropic_content_errors(count) if messages_format == "anthropic" else count, + litellm_call_id=call_id, + request_model=request.model, + model_id=deployment_model_id(routed), + ) + + +async def _with_anthropic_content_errors(count: Awaitable[TokenCountResponse]) -> TokenCountResponse: + try: + return await count + except UnsupportedContentTypeError as e: + raise ProxyException(message=str(e), type="invalid_request_error", param="messages", code=400) from e + + +async def _routed_count_deployment( + model: str, responses_request: Mapping[str, object] | None +) -> Mapping[str, object] | None: + if llm_router is None: + return None + try: + return await llm_router.async_get_available_deployment( + model=model, request_kwargs=dict(_responses_routing_kwargs(responses_request)) + ) + except Exception: + verbose_proxy_logger.exception( + "litellm.proxy.proxy_server.token_counter(): Exception occured while getting deployment" + ) + return None + + +async def _count_request_tokens( + request: TokenCountRequest, + routed: Mapping[str, object] | None, + call_endpoint: bool, + messages_format: TokenCountMessagesFormat, + output_format: JsonValue, + context_management: JsonValue, + request_litellm_params: Mapping[str, JsonValue], + responses_request: Mapping[str, object] | None, + client_oauth_token: str | None, ) -> TokenCountResponse: prompt: Final = request.prompt messages: Final = request.messages @@ -15271,26 +15398,9 @@ async def count_request_tokens( tools: Final = request.tools system: Final = request.system - ######################################################### - # Validate request - ######################################################### - if prompt is None and messages is None and contents is None: - raise HTTPException(status_code=400, detail="prompt or messages or contents must be provided") - - deployment: dict[str, Any] | None = None + deployment: dict[str, Any] | None = None if routed is None else dict(routed) litellm_model_name = None model_info: ModelMapInfo | None = None - if llm_router is not None: - # get 1 deployment corresponding to the model - try: - deployment = await llm_router.async_get_available_deployment( - model=request.model, - request_kwargs=dict(_responses_routing_kwargs(responses_request)), - ) - except Exception: - verbose_proxy_logger.exception( - "litellm.proxy.proxy_server.token_counter(): Exception occured while getting deployment" - ) if deployment is not None: litellm_model_name = deployment.get("litellm_params", {}).get("model") model_info = deployment.get("model_info", {}) @@ -15321,7 +15431,8 @@ async def count_request_tokens( custom_llm_provider: str | None = None if call_endpoint is True and deployment is not None: # Auto-route to the correct provider based on model - provider_counter, _model, custom_llm_provider = _get_provider_token_counter(deployment, model_to_use) + routed_counter, _model, custom_llm_provider = _get_provider_token_counter(deployment, model_to_use) + provider_counter = _with_client_oauth_token(routed_counter, client_oauth_token) if _model is not None: model_to_use = _model @@ -15389,6 +15500,7 @@ async def count_request_tokens( chat_params=MappingProxyType({}) if chat_count is None else chat_count.params, ), model_to_use=model_to_use, + request_model=request.model, settings=settings, local_estimate_allowed=litellm.disable_token_counter is not True and contents_estimable, ) @@ -15444,7 +15556,7 @@ async def count_request_tokens( count_source="local_estimate", ) estimate: Final = await _local_token_estimate( - model=model_to_use, + model=deployment_openai_model(deployment_view) or model_to_use, prompt=prompt if counted_messages is None else None, messages=counted_messages, tools=counted_tools, @@ -18354,7 +18466,6 @@ async def async_queue_request( "body": copy.copy(data), # use copy instead of deepcopy } - verbose_proxy_logger.debug("receiving data: %s", data) data["model"] = ( general_settings.get("completion_model", None) # server default or user_model # model name passed via cli args @@ -18402,6 +18513,11 @@ async def async_queue_request( raise HTTPException(status_code=500, detail={"error": CommonProxyErrors.no_llm_router.value}) router: Final = llm_router + data.update( + router.priority_header_update( + model=data["model"], kwargs=data, header=request.headers.get(SCHEDULER_PRIORITY_HEADER) + ) + ) queued_priority, _ = router.split_request_priority(model=data["model"], kwargs=data) if "stream" in data and data["stream"] is True: # use generate_responses to stream responses @@ -18435,25 +18551,13 @@ async def async_queue_request( await proxy_logging_obj.post_call_failure_hook( user_api_key_dict=user_api_key_dict, original_exception=e, request_data=data ) - if isinstance(e, HTTPException): - raise ProxyException( - message=getattr(e, "detail", f"Authentication Error({e})"), - type=ProxyErrorTypes.auth_error, - param=getattr(e, "param", "None"), - code=getattr(e, "status_code", status.HTTP_400_BAD_REQUEST), - ) - elif isinstance(e, ProxyException): - raise e - elif isinstance(e, litellm.BadRequestError): + if isinstance(e, litellm.BadRequestError): raise ProxyException( message=e.message, type="invalid_request_error", param=getattr(e, "param", None), code=e.status_code - ) - raise ProxyException( - message="Authentication Error, " + str(e), - type=ProxyErrorTypes.auth_error, - param=getattr(e, "param", "None"), - code=status.HTTP_400_BAD_REQUEST, - ) + ) from e + if isinstance(e, ProxyException): + raise + raise proxy_exception_for(e, default_status_code=status.HTTP_400_BAD_REQUEST) from e @app.get("/fallback/login", tags=["experimental"], include_in_schema=False) @@ -19732,21 +19836,9 @@ async def update_config( except Exception as e: verbose_proxy_logger.error("litellm.proxy.proxy_server.update_config(): Exception occured - %s", e) verbose_proxy_logger.debug(traceback.format_exc()) - if isinstance(e, HTTPException): - raise ProxyException( - message=getattr(e, "detail", f"Authentication Error({e})"), - type=ProxyErrorTypes.auth_error, - param=getattr(e, "param", "None"), - code=getattr(e, "status_code", status.HTTP_400_BAD_REQUEST), - ) - elif isinstance(e, ProxyException): - raise e - raise ProxyException( - message="Authentication Error, " + str(e), - type=ProxyErrorTypes.auth_error, - param=getattr(e, "param", "None"), - code=status.HTTP_400_BAD_REQUEST, - ) + if isinstance(e, ProxyException): + raise + raise proxy_exception_for(e, default_status_code=status.HTTP_400_BAD_REQUEST) from e ### CONFIG GENERAL SETTINGS @@ -19888,12 +19980,14 @@ async def update_config_general_settings( ) try: - ConfigGeneralSettings.model_validate({data.field_name: requested_value}) + validated: Final = ConfigGeneralSettings.model_validate({data.field_name: requested_value}) except Exception: raise HTTPException( status_code=400, detail={"error": f"Invalid type of field value={type(requested_value)} passed in."}, ) + parsed_value: Final[object] = _UNTYPED_VALUE.validate_python(getattr(validated, data.field_name)) + stored_value: Final = parsed_value if isinstance(parsed_value, bool) else requested_value if data.field_name == "alerting_args": try: @@ -19922,10 +20016,10 @@ async def update_config_general_settings( proxy_config.reject_config_owned_writes( section_name="general_settings", - changed_keys={data.field_name: cast(JsonValue, requested_value)}, # cast-ok: validated above + changed_keys={data.field_name: cast(JsonValue, stored_value)}, # cast-ok: validated above ) - field_value = requested_value + field_value = stored_value if data.field_name == "plugins": field_value = _preserve_redacted_plugin_keys(field_value, general_settings.get("plugins")) @@ -20927,21 +21021,9 @@ async def get_config( } except Exception as e: verbose_proxy_logger.exception("litellm.proxy.proxy_server.get_config(): Exception occured - %s", e) - if isinstance(e, HTTPException): - raise ProxyException( - message=getattr(e, "detail", f"Authentication Error({e})"), - type=ProxyErrorTypes.auth_error, - param=getattr(e, "param", "None"), - code=getattr(e, "status_code", status.HTTP_400_BAD_REQUEST), - ) - elif isinstance(e, ProxyException): - raise e - raise ProxyException( - message="Authentication Error, " + str(e), - type=ProxyErrorTypes.auth_error, - param=getattr(e, "param", "None"), - code=status.HTTP_400_BAD_REQUEST, - ) + if isinstance(e, ProxyException): + raise + raise proxy_exception_for(e, default_status_code=status.HTTP_500_INTERNAL_SERVER_ERROR) from e @router.get( diff --git a/litellm/proxy/public_endpoints/agent_create_fields.json b/litellm/proxy/public_endpoints/agent_create_fields.json index f289a6c1805..53b32d249c7 100644 --- a/litellm/proxy/public_endpoints/agent_create_fields.json +++ b/litellm/proxy/public_endpoints/agent_create_fields.json @@ -127,8 +127,8 @@ { "key": "agent_id", "label": "Agent ID", - "placeholder": "asst_abc123", - "tooltip": "The agent/assistant ID from your Azure AI Foundry project (e.g., asst_abc123)", + "placeholder": "my-agent", + "tooltip": "The agent name from your Azure AI Foundry project, optionally with a version (e.g., my-agent or my-agent:2), or a classic assistant ID (e.g., asst_abc123)", "required": true, "field_type": "text", "default_value": null, diff --git a/litellm/proxy/public_endpoints/provider_create_fields.json b/litellm/proxy/public_endpoints/provider_create_fields.json index d96f2976508..fd17079b15f 100644 --- a/litellm/proxy/public_endpoints/provider_create_fields.json +++ b/litellm/proxy/public_endpoints/provider_create_fields.json @@ -1,4 +1,32 @@ [ + { + "provider": "AIAND", + "provider_display_name": "ai&", + "litellm_provider": "aiand", + "credential_fields": [ + { + "key": "api_base", + "label": "API Base", + "placeholder": "https://api.aiand.com/v1", + "tooltip": null, + "required": false, + "field_type": "text", + "options": null, + "default_value": null + }, + { + "key": "api_key", + "label": "API Key", + "placeholder": null, + "tooltip": null, + "required": true, + "field_type": "password", + "options": null, + "default_value": null + } + ], + "default_model_placeholder": "aiand/openai/gpt-oss-120b" + }, { "provider": "SCALEDOWN", "provider_display_name": "ScaleDown", @@ -3491,6 +3519,34 @@ ], "default_model_placeholder": "inferenceapis/deepseek-ai/DeepSeek-V4-Flash" }, + { + "provider": "StreamLake", + "provider_display_name": "StreamLake", + "litellm_provider": "streamlake", + "credential_fields": [ + { + "key": "api_base", + "label": "API Base", + "placeholder": "https://vanchin.streamlake.ai/api/gateway/v1/endpoints", + "tooltip": null, + "required": false, + "field_type": "text", + "options": null, + "default_value": null + }, + { + "key": "api_key", + "label": "API Key", + "placeholder": null, + "tooltip": null, + "required": true, + "field_type": "password", + "options": null, + "default_value": null + } + ], + "default_model_placeholder": "streamlake/" + }, { "provider": "Snowflake", "provider_display_name": "Snowflake", @@ -4117,6 +4173,34 @@ ], "default_model_placeholder": "gpt-3.5-turbo" }, + { + "provider": "ZeroGPU", + "provider_display_name": "ZeroGPU", + "litellm_provider": "zerogpu", + "credential_fields": [ + { + "key": "api_base", + "label": "API Base", + "placeholder": "https://api.zerogpu.ai/v1", + "tooltip": null, + "required": false, + "field_type": "text", + "options": null, + "default_value": null + }, + { + "key": "api_key", + "label": "API Key", + "placeholder": null, + "tooltip": null, + "required": true, + "field_type": "password", + "options": null, + "default_value": null + } + ], + "default_model_placeholder": "zerogpu/gpt-oss-120b" + }, { "provider": "CURSOR", "provider_display_name": "Cursor", @@ -4144,5 +4228,33 @@ } ], "default_model_placeholder": "cursor/claude-4-sonnet" + }, + { + "provider": "BIGMODEL", + "provider_display_name": "BigModel (Zhipu AI)", + "litellm_provider": "bigmodel", + "credential_fields": [ + { + "key": "api_key", + "label": "BigModel (Zhipu AI) API Key", + "placeholder": null, + "tooltip": null, + "required": true, + "field_type": "password", + "options": null, + "default_value": null + }, + { + "key": "api_base", + "label": "API Base", + "placeholder": "https://open.bigmodel.cn", + "tooltip": null, + "required": false, + "field_type": "text", + "options": null, + "default_value": "https://open.bigmodel.cn" + } + ], + "default_model_placeholder": "bigmodel/glm-5.3" } ] diff --git a/litellm/proxy/response_api_endpoints/endpoints.py b/litellm/proxy/response_api_endpoints/endpoints.py index 97bbf893e3e..9e642a02d49 100644 --- a/litellm/proxy/response_api_endpoints/endpoints.py +++ b/litellm/proxy/response_api_endpoints/endpoints.py @@ -39,6 +39,7 @@ from litellm.litellm_core_utils.core_helpers import as_str_mapping, get_metadata from litellm.litellm_core_utils.internal_call_metadata import is_background_response, requests_background from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj from litellm.litellm_core_utils.litellm_logging import StandardLoggingPayloadSetup +from litellm.litellm_core_utils.token_counter import usage_tokenizer_model from litellm.litellm_core_utils.tool_fields import TOOL_FIELDS, first_validation_error from litellm.llms.openai.responses.guardrail_translation.handler import ( OpenAIResponsesHandler, @@ -56,6 +57,7 @@ from litellm.proxy.common_request_processing import ( cost_headers, create_response, resolve_counted_tool_fields, + resolve_litellm_call_id, ) from litellm.proxy.common_utils.error_body_call_id import error_body_call_id, with_call_id from litellm.proxy.common_utils.http_parsing_utils import ( # noqa: F401 # legacy module exports @@ -69,6 +71,7 @@ from litellm.proxy.common_utils.openai_error_payload import ( error_status_code, openai_error_type_for_status, ) +from litellm.proxy.common_utils.token_count_log import rejected_token_count from litellm.proxy.common_utils.token_count_settings import count_source_fields from litellm.proxy.hooks.proxy_track_cost_callback import ProxyDBLogger from litellm.proxy.hooks.responses_id_security import ResponsesIDSecurity, decrypted_response_id @@ -83,6 +86,7 @@ from litellm.proxy.route_llm_request import raise_if_required_body_param_missing from litellm.proxy.utils import count_request_input_tokens, handle_exception_on_proxy from litellm.responses.litellm_completion_transformation.compaction_items import messages_since_newest_compaction from litellm.responses.litellm_completion_transformation.count_request import MODEL_FILE_ID_MAPPING_FIELD +from litellm.responses.retrieve_stream_query import RETRIEVE_INCLUDE_QUERY_KEYS, RETRIEVE_STREAM_QUERY_KEYS from litellm.responses.streaming_iterator import GuardedResponsesWsFrame, ResponsesWsFrameGuard, spawn_logging_task from litellm.router import Router from litellm.types.llms.base import LiteLLMBaseModel @@ -94,6 +98,7 @@ from litellm.types.llms.openai import ( from litellm.types.responses.main import DeleteResponseResult from litellm.types.token_count import TokenCountSourceFields from litellm.types.utils import ADDRESSED_RESPONSE_ID_FIELD, TokenCountResponse +from litellm.utils import get_base_model_from_metadata if TYPE_CHECKING: from litellm.proxy.utils import ProxyLogging @@ -102,11 +107,43 @@ router: Final = APIRouter() _RESPONSES_WS_CONFIG_VALUE_ADAPTER: Final[TypeAdapter[object | None]] = TypeAdapter(object | None) _DECODED_JSON: Final = TypeAdapter(object) _PROXY_SERVER_REQUEST_ADAPTER: Final[TypeAdapter[Mapping[str, object]]] = TypeAdapter(Mapping[str, object]) +_RETRIEVE_QUERY_PARAMS: Final = tuple(sorted(RETRIEVE_INCLUDE_QUERY_KEYS | RETRIEVE_STREAM_QUERY_KEYS)) +_RETRIEVE_QUERY_OPENAPI: Final = { + "parameters": [ + { + "name": "stream", + "in": "query", + "required": False, + "schema": {"type": "boolean"}, + "description": "Replay the response's events as server-sent events (OpenAI, Azure, and Azure AI Foundry)", + }, + { + "name": "starting_after", + "in": "query", + "required": False, + "schema": {"type": "integer", "minimum": 0}, + "description": "With stream=true, replay only the events after this sequence number", + }, + { + "name": "include", + "in": "query", + "required": False, + "schema": {"type": "array", "items": {"type": "string"}}, + "description": "Additional output data to include, forwarded to the provider", + }, + { + "name": "include_obfuscation", + "in": "query", + "required": False, + "schema": {"type": "boolean"}, + "description": "With stream=true, whether delta events carry obfuscation padding", + }, + ] +} _ResponseDocSchemas: TypeAlias = dict[int | str, dict[str, object]] # fastapi's responses kwarg -RESPONSES_API_RESPONSE_SCHEMAS: Final[_ResponseDocSchemas] = {200: {"model": ResponsesAPIResponse}} -RESPONSES_API_CREATE_RESPONSE_SCHEMAS: Final[_ResponseDocSchemas] = { +RESPONSES_API_RESPONSE_SCHEMAS: Final[_ResponseDocSchemas] = { 200: { "model": ResponsesAPIResponse, "content": { @@ -250,19 +287,19 @@ async def _resolve_cursor_model_variant_before_auth(request: Request) -> None: "/v1/responses", dependencies=[Depends(user_api_key_auth)], tags=["responses"], - responses=RESPONSES_API_CREATE_RESPONSE_SCHEMAS, + responses=RESPONSES_API_RESPONSE_SCHEMAS, ) @router.post( "/responses", dependencies=[Depends(user_api_key_auth)], tags=["responses"], - responses=RESPONSES_API_CREATE_RESPONSE_SCHEMAS, + responses=RESPONSES_API_RESPONSE_SCHEMAS, ) @router.post( "/openai/v1/responses", dependencies=[Depends(user_api_key_auth)], tags=["responses"], - responses=RESPONSES_API_CREATE_RESPONSE_SCHEMAS, + responses=RESPONSES_API_RESPONSE_SCHEMAS, ) async def responses_api( request: Request, @@ -535,7 +572,10 @@ async def cursor_model_list( def _dispatched_prompt_token_counter(logging_obj: LiteLLMLoggingObj) -> Callable[[], int]: return lambda: count_request_input_tokens( - model=str(logging_obj.model_call_details.get("model") or ""), + model=usage_tokenizer_model( + str(logging_obj.model_call_details.get("model") or ""), + get_base_model_from_metadata(logging_obj.model_call_details), + ), request_input=messages_since_newest_compaction(logging_obj.model_call_details.get("messages")), system_input=None, ) @@ -742,18 +782,21 @@ async def cursor_chat_completions( dependencies=[Depends(user_api_key_auth)], tags=["responses"], responses=RESPONSES_API_RESPONSE_SCHEMAS, + openapi_extra=_RETRIEVE_QUERY_OPENAPI, ) @router.get( "/responses/{response_id}", dependencies=[Depends(user_api_key_auth)], tags=["responses"], responses=RESPONSES_API_RESPONSE_SCHEMAS, + openapi_extra=_RETRIEVE_QUERY_OPENAPI, ) @router.get( "/openai/v1/responses/{response_id}", dependencies=[Depends(user_api_key_auth)], tags=["responses"], responses=RESPONSES_API_RESPONSE_SCHEMAS, + openapi_extra=_RETRIEVE_QUERY_OPENAPI, ) async def get_response( response_id: str, @@ -778,6 +821,10 @@ async def get_response( # Get provider response curl -X GET http://localhost:4000/v1/responses/resp_abc123 \ -H "Authorization: Bearer $LITELLM_MASTER_KEY" + + # Resume a background response's event stream after sequence number 7 + curl -N "http://localhost:4000/v1/responses/resp_abc123?stream=true&starting_after=7" \ + -H "Authorization: Bearer $LITELLM_MASTER_KEY" ``` """ from litellm.proxy.proxy_server import ( @@ -825,6 +872,14 @@ async def get_response( data: Final = await read_request_body(request=request) read_settles_billing: Final = not carries_client_side_overrides(data) data["response_id"] = response_id + retrieve_query: Final = { + key: values[0] if len(values) == 1 else values + for key in _RETRIEVE_QUERY_PARAMS + if (values := request.query_params.getlist(key)) + } + if retrieve_query: + body_extra_query: Final[object] = data.get("extra_query") + data["extra_query"] = {**(body_extra_query if isinstance(body_extra_query, dict) else {}), **retrieve_query} processor: Final = ProxyBaseLLMRequestProcessing(data=data) try: response: Final[object] = await processor.base_process_llm_request( @@ -836,7 +891,12 @@ async def get_response( llm_router=llm_router, general_settings=general_settings, proxy_config=proxy_config, - select_data_generator=select_data_generator, + select_data_generator=partial( + _streamed_retrieval_data_generator, + partial(select_data_generator, responses_stream_errors=True), + response_id, + read_settles_billing, + ), model=None, user_model=user_model, user_temperature=user_temperature, @@ -910,12 +970,24 @@ async def _bill_finished_background_response( fastapi_response: Response, read_settles_billing: bool, ) -> None: + _report_charge( + await _settle_finished_background_read(response, response_id, user_api_key_dict, read_settles_billing), + fastapi_response, + ) + + +async def _settle_finished_background_read( + response: object, + response_id: str, + user_api_key_dict: UserAPIKeyAuth, + read_settles_billing: bool, +) -> "_BilledCharge | None": from litellm.proxy.proxy_server import proxy_logging_obj if not isinstance(response, ResponsesAPIResponse) or not is_background_response(response): - return + return None if response.status not in TERMINAL_RESPONSE_STATUSES: - return + return None managed_files_hook: Final = _managed_files_hook(proxy_logging_obj) track_untracked: Final = ( partial( @@ -926,12 +998,11 @@ async def _bill_finished_background_response( if managed_files_hook is not None else None ) - charge: Final = await _settle_background_billing( + return await _settle_background_billing( (lambda cost_check: cost_check.bill_if_finished(response_id, response, track_untracked)) if read_settles_billing else (lambda cost_check: cost_check.bill_from_deployment(response_id, track_untracked)) ) - _report_charge(charge, fastapi_response) class _BilledCharge(Protocol): @@ -1081,27 +1152,53 @@ def _streamed_background_data_generator( user_api_key_dict=user_api_key_dict, request_tags=_background_response_spend_tags(request_data), ) - return _bill_streamed_background_response(response, chunks, track_untracked) + return _bill_streamed_background_response( + response, chunks, partial(_bill_finished_stream, track_untracked=track_untracked) + ) + + +def _streamed_retrieval_data_generator( + select_data_generator: Callable[..., AsyncIterator[str | bytes]], + response_id: str, + read_settles_billing: bool, + response: object, + user_api_key_dict: UserAPIKeyAuth, + request_data: Mapping[str, object], + request: Request | None = None, +) -> AsyncIterator[str | bytes]: + chunks: Final = select_data_generator( + response=response, user_api_key_dict=user_api_key_dict, request_data=request_data, request=request + ) + return _bill_streamed_background_response( + response, + chunks, + partial( + _settle_finished_background_read, + response_id=response_id, + user_api_key_dict=user_api_key_dict, + read_settles_billing=read_settles_billing, + ), + ) async def _bill_streamed_background_response( stream: object, chunks: AsyncIterator[str | bytes], - track_untracked: Callable[[str, ResponsesAPIResponse], Awaitable[bool]], + bill: Callable[[ResponsesAPIResponse], Awaitable[object]], ) -> AsyncIterator[str | bytes]: async for chunk in chunks: completed: object = ProxyBaseLLMRequestProcessing.extract_completed_responses_response(stream) if not isinstance(completed, ResponsesAPIResponse): yield chunk continue - await _bill_finished_stream(completed, track_untracked) + await bill(completed) yield chunk async for remaining_chunk in chunks: yield remaining_chunk return late_completed: Final = ProxyBaseLLMRequestProcessing.extract_completed_responses_response(stream) if isinstance(late_completed, ResponsesAPIResponse): - await _bill_finished_stream(late_completed, track_untracked) + await bill(late_completed) async def _bill_finished_stream( @@ -1407,7 +1504,12 @@ class _TokenCountPayload(TypedDict): class _TokenCounter(Protocol): def __call__( - self, *, request: TokenCountRequest, call_endpoint: bool, responses_request: Mapping[str, object] | None + self, + *, + request: TokenCountRequest, + call_endpoint: bool, + responses_request: Mapping[str, object] | None, + litellm_call_id: str | None, ) -> Awaitable[TokenCountResponse]: ... @@ -1648,18 +1750,23 @@ async def responses_input_tokens( Returns: `{"object": "response.input_tokens", "input_tokens": }` """ + litellm_call_id: Final = resolve_litellm_call_id(request.headers.get(LITELLM_CALL_ID_HEADER)) data: Final = await read_request_body(request=request) model_name: Final = data.get("model") input_value: Final = data.get("input") if not isinstance(model_name, str) or not model_name: - return _missing_responses_param_response("model") + return rejected_token_count(_missing_responses_param_response("model"), litellm_call_id, None) if input_value is None: - return _missing_responses_param_response("input") + return rejected_token_count(_missing_responses_param_response("input"), litellm_call_id, model_name) if isinstance(input_value, (str, list)) and not input_value: - return _responses_invalid_request_response( - message="""One of "input" or "previous_response_id" or 'prompt' or 'conversation' must be provided.""", - param=None, - code="missing_required_parameter", + return rejected_token_count( + _responses_invalid_request_response( + message="""One of "input" or "previous_response_id" or 'prompt' or 'conversation' must be provided.""", + param=None, + code="missing_required_parameter", + ), + litellm_call_id, + model_name, ) counted_fields: Final = { @@ -1667,7 +1774,11 @@ async def responses_input_tokens( } token_fields: Final = resolve_counted_tool_fields(counted_fields, llm_router, user_api_key_dict.team_id) if isinstance(token_fields, ProxyException): - return _responses_invalid_request_response(message=token_fields.message, param=token_fields.param, code=None) + return rejected_token_count( + _responses_invalid_request_response(message=token_fields.message, param=token_fields.param, code=None), + litellm_call_id, + model_name, + ) try: payload: Final[_TokenCountPayload] = { @@ -1680,27 +1791,44 @@ async def responses_input_tokens( } token_request: Final = TokenCountRequest.model_validate(payload) except ValidationError as e: - return _responses_invalid_request_response( - message=first_validation_error(e), param=str(e.errors(include_url=False)[0]["loc"][0]), code=None + return rejected_token_count( + _responses_invalid_request_response( + message=first_validation_error(e), param=str(e.errors(include_url=False)[0]["loc"][0]), code=None + ), + litellm_call_id, + model_name, ) except Exception as e: - return _responses_invalid_request_response( - message=f"Invalid request for token counting: {e}", param=None, code=None + return rejected_token_count( + _responses_invalid_request_response( + message=f"Invalid request for token counting: {e}", param=None, code=None + ), + litellm_call_id, + model_name, ) request_fields: Final = _PROXY_SERVER_REQUEST_ADAPTER.validate_python(data) - responses_request: Final = await _with_managed_file_id_mapping( - _with_authorized_previous_response( - {**{name: value for name, value in request_fields.items() if name not in counted_fields}, **token_fields}, - response_id_security, + try: + responses_request: Final = await _with_managed_file_id_mapping( + _with_authorized_previous_response( + { + **{name: value for name, value in request_fields.items() if name not in counted_fields}, + **token_fields, + }, + response_id_security, + user_api_key_dict, + ), + managed_files, user_api_key_dict, - ), - managed_files, - user_api_key_dict, - ) + ) + except ProxyException as e: + raise rejected_token_count(e, litellm_call_id, model_name) try: token_response: Final = await token_counter( - request=token_request, call_endpoint=True, responses_request=responses_request + request=token_request, + call_endpoint=True, + responses_request=responses_request, + litellm_call_id=litellm_call_id, ) except ProxyException as e: if e.type != _PROVIDER_COUNT_ERROR_TYPE: diff --git a/litellm/proxy/response_polling/background_streaming.py b/litellm/proxy/response_polling/background_streaming.py index 5f6a7432afb..1eb76f8f558 100644 --- a/litellm/proxy/response_polling/background_streaming.py +++ b/litellm/proxy/response_polling/background_streaming.py @@ -18,6 +18,7 @@ from starlette.types import Message from typing_extensions import ReadOnly, TypedDict from litellm._logging import verbose_proxy_logger +from litellm.llms.custom_httpx.sse_lines import split_sse_lines from litellm.proxy.auth.user_api_key_auth import UserAPIKeyAuth from litellm.proxy.common_request_processing import ProxyBaseLLMRequestProcessing from litellm.proxy.response_polling.polling_handler import ResponsePollingHandler @@ -81,7 +82,7 @@ class _StreamsBody(Protocol): def _sse_frame_data(frame: str) -> str | None: - return next((line[6:].strip() for line in frame.splitlines() if line.startswith("data: ")), None) + return next((line[6:].strip() for line in split_sse_lines(frame) if line.startswith("data: ")), None) async def _never_receive() -> Message: diff --git a/litellm/proxy/route_llm_request.py b/litellm/proxy/route_llm_request.py index cb226929167..db1951ec9e2 100644 --- a/litellm/proxy/route_llm_request.py +++ b/litellm/proxy/route_llm_request.py @@ -256,7 +256,6 @@ REQUIRED_PRESENT_BODY_PARAMS_BY_ROUTE: Final[Mapping[str, tuple[str, ...]]] = Ma "avideo_create_character": ("name", "video"), "acreate_container": ("name",), "aupload_container_file": ("file",), - "acreate_agent": ("name",), "acreate_interaction": ("input",), "acreate_eval": ("data_source_config", "testing_criteria"), "acreate_run": ("data_source",), @@ -264,7 +263,7 @@ REQUIRED_PRESENT_BODY_PARAMS_BY_ROUTE: Final[Mapping[str, tuple[str, ...]]] = Ma ) REQUIRED_ONE_OF_BODY_PARAMS_BY_ROUTE: Final[Mapping[str, tuple[str, str]]] = MappingProxyType( - {"acreate_interaction": ("model", "agent")} + {"acreate_interaction": ("model", "agent"), "acreate_agent": ("id", "name")} ) JSON_OBJECT_ADAPTER: Final[TypeAdapter[dict[str, object]]] = TypeAdapter(dict[str, object]) diff --git a/litellm/proxy/schema.prisma b/litellm/proxy/schema.prisma index 83a0e6f9e05..2965174114b 100644 --- a/litellm/proxy/schema.prisma +++ b/litellm/proxy/schema.prisma @@ -1163,6 +1163,7 @@ model LiteLLM_ManagedFileTable { @@index([unified_file_id]) @@index([flat_model_file_ids], type: Gin) @@index([team_id, created_at(sort: Desc)]) + @@index([created_by, created_at(sort: Desc)]) } model LiteLLM_ManagedObjectTable { // for batches or finetuning jobs which use the @@ -2060,3 +2061,73 @@ model LiteLLM_TelemetryReport { @@index([window_end]) @@index([created_at]) } + +enum AccountingEventKind { + inbound_usage + outbound_usage + cost +} + +enum AccountingDeliveryState { + pending + applied + parked +} + +enum AccountingDeliveryTarget { + LiteLLM_VerificationToken + LiteLLM_UserTable + LiteLLM_TeamTable + LiteLLM_TeamMembership + LiteLLM_OrganizationTable + LiteLLM_OrganizationMembership + LiteLLM_EndUserTable + LiteLLM_AgentsTable + LiteLLM_TagTable + LiteLLM_ProjectTable + LiteLLM_ModelAccessGroupBudgetTable + LiteLLM_BudgetTable + LiteLLM_BudgetWindowSpend + LiteLLM_DailyUserSpend + LiteLLM_DailyTeamSpend + LiteLLM_DailyOrganizationSpend + LiteLLM_DailyEndUserSpend + LiteLLM_DailyAgentSpend + LiteLLM_DailyTagSpend + LiteLLM_DailyModelUsage + LiteLLM_DailyToolSpend + LiteLLM_AutoRouterDailySpend +} + +// Durable accounting ledger. One row per usage or cost event; payload holds the +// private event envelope versioned by schema_version. Usage rows retain request-scoped +// pricing context; cost rows include resolved rates and the finalized pricing snapshot. +model LiteLLM_AccountingEvent { + event_id String @id + kind AccountingEventKind + source_event_id String? + schema_version Int + payload_hash String + occurred_at DateTime + recorded_at DateTime @default(now()) + payload Json + + @@index([recorded_at]) + @@index([kind, source_event_id]) +} + +// One row per (event, target table, version): pending work for the projector and, +// once applied in the same transaction as the target write, the receipt that stops a retry. +model LiteLLM_AccountingDelivery { + event_id String + target AccountingDeliveryTarget + version Int + state AccountingDeliveryState @default(pending) + attempts Int @default(0) + next_attempt_at DateTime @default(now()) + applied_at DateTime? + last_error String? + + @@id([event_id, target, version]) + @@index([target, state, next_attempt_at]) +} diff --git a/litellm/proxy/spend_tracking/budget_reservation.py b/litellm/proxy/spend_tracking/budget_reservation.py index 0b91e57f01e..08840b44532 100644 --- a/litellm/proxy/spend_tracking/budget_reservation.py +++ b/litellm/proxy/spend_tracking/budget_reservation.py @@ -7,6 +7,7 @@ import time from collections.abc import AsyncIterator, Mapping, Sequence from dataclasses import dataclass from datetime import datetime, timedelta, timezone +from itertools import chain from types import MappingProxyType from typing import Final, NoReturn, SupportsFloat, SupportsIndex, SupportsInt, cast @@ -39,7 +40,7 @@ from litellm.proxy.common_utils.user_api_key_cache import ( tag_cache_key, team_membership_reservation_cache_key, ) -from litellm.proxy.spend_tracking.input_tokens import count_input_tokens, count_input_tokens_for_model +from litellm.proxy.spend_tracking.input_tokens import count_input_tokens, count_input_tokens_for_model, tokenizer_models from litellm.proxy.spend_tracking.spend_counter_batch import PendingSpendIncrement, spend_counter_batch_scope from litellm.proxy.utils import PrismaClient, ProxyLogging from litellm.router import Router @@ -1599,7 +1600,19 @@ async def count_request_input_tokens( models: Final = _get_request_models(request_body=request_body, route=route, llm_router=llm_router) if not models: return MappingProxyType({}) - return await count_input_tokens(request_body=request_body, raw_body=raw_body, models=models) + counted_as: Final = MappingProxyType({model: tokenizer_models(model, llm_router) for model in models}) + counts: Final = await count_input_tokens( + request_body=request_body, + raw_body=raw_body, + models=tuple(dict.fromkeys(chain.from_iterable(counted_as.values()))), + ) + return MappingProxyType( + { + model: count + for model, names in counted_as.items() + if (count := max((counts[name] for name in names if name in counts), default=None)) is not None + } + ) def _estimate_input_tokens( diff --git a/litellm/proxy/spend_tracking/input_tokens.py b/litellm/proxy/spend_tracking/input_tokens.py index 927152296e9..0139869c6c6 100644 --- a/litellm/proxy/spend_tracking/input_tokens.py +++ b/litellm/proxy/spend_tracking/input_tokens.py @@ -15,14 +15,16 @@ import asyncio import json from collections.abc import Mapping, Sequence from types import MappingProxyType -from typing import Final +from typing import TYPE_CHECKING, Final import litellm from litellm._logging import verbose_proxy_logger +from litellm.litellm_core_utils.token_counter import served_openai_models, unresolved_tokenizer_model from litellm.responses.litellm_completion_transformation.compaction_items import ( billable_input_since_newest_compaction, holds_compaction_summary, ) +from litellm.router_utils.common_utils import resolve_model_group_alias from litellm.rust_bridge import runtime from litellm.rust_bridge.catalog import Route, RouteContext from litellm.rust_bridge.token_counter import ( @@ -33,6 +35,9 @@ from litellm.rust_bridge.token_counter import ( rust_tokenizer, ) +if TYPE_CHECKING: + from litellm.router import Router + TOKENIZE_OFF_EVENT_LOOP_MIN_CHARS: Final = 30_000 _INPUT_SIZE_FIELDS: Final = ("messages", "prompt", "input", "query", "documents", "tools", "tool_choice") @@ -47,6 +52,25 @@ def _approximate_input_size(request_body: Mapping[str, object]) -> int: return sum(len(str(request_body.get(field, ""))) for field in _INPUT_SIZE_FIELDS) +def tokenizer_models(model: str, llm_router: Router | None) -> tuple[str, ...]: + """The names to count a request for `model` with, keeping the largest count. + + An alias resolves to its target group. A group served only by OpenAI models counts as those models, so it gets + their tokenizer. Any other group counts as its OpenAI models, if any, and as the requested name with the encoding + tiktoken gives that name as written, so its other deployments keep that count without loading their vendor's + tokenizer. A name the router does not index counts as written.""" + if llm_router is None: + return (model,) + group: Final = resolve_model_group_alias(llm_router.model_group_alias, model) or model + served: Final = served_openai_models(llm_router.deployments_named(group) or ()) + if not served: + return (model,) + openai_served: Final = tuple(served_model for served_model in served if served_model is not None) + if len(openai_served) == len(served): + return openai_served + return (unresolved_tokenizer_model(model), *openai_served) + + async def count_input_tokens( request_body: dict, raw_body: bytes | None, diff --git a/litellm/proxy/spend_tracking/key_metadata_recovery.py b/litellm/proxy/spend_tracking/key_metadata_recovery.py index 5442c0f3f81..8fd4fbfcb8b 100644 --- a/litellm/proxy/spend_tracking/key_metadata_recovery.py +++ b/litellm/proxy/spend_tracking/key_metadata_recovery.py @@ -6,7 +6,7 @@ from datetime import datetime, timedelta from types import MappingProxyType from typing import Final, Literal, TypeVar -from pydantic import TypeAdapter +from pydantic import ConfigDict, TypeAdapter from typing_extensions import ReadOnly, TypedDict from litellm._logging import verbose_proxy_logger @@ -155,6 +155,7 @@ class _DailyUserSpendOwnerRow(LiteLLMBaseModel): last_owner: str | None = None +_RAW_ROWS: Final = TypeAdapter(Sequence[dict[str, object]], config=ConfigDict(strict=True)) _TOKEN_DIGEST_ROWS: Final = TypeAdapter(tuple[_TokenDigestRow, ...]) _SPEND_LOG_DIGEST_ROWS: Final = TypeAdapter(tuple[_SpendLogDigestRow, ...]) _DAILY_USER_SPEND_OWNER_ROWS: Final = TypeAdapter(tuple[_DailyUserSpendOwnerRow, ...]) @@ -194,7 +195,7 @@ async def _rows_within_the_statement_timeout( await transaction.execute_raw(_SPEND_LOG_STATEMENT_TIMEOUT_SQL) for setting in planner_settings: await transaction.execute_raw(setting) - return await transaction.query_raw(sql, *params) + return _RAW_ROWS.validate_python(await transaction.query_raw(sql, *params)) async def _reverse_hash_key_metadata( diff --git a/litellm/proxy/utils.py b/litellm/proxy/utils.py index 0ddfc5ce62f..9f58c267231 100644 --- a/litellm/proxy/utils.py +++ b/litellm/proxy/utils.py @@ -168,7 +168,7 @@ from litellm.litellm_core_utils.served_output_texts import ( record_served_output_texts, served_stream_output_texts, ) -from litellm.litellm_core_utils.token_counter import offload_token_count +from litellm.litellm_core_utils.token_counter import offload_token_count, usage_tokenizer_model from litellm.llms import load_guardrail_translation_mappings from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler from litellm.proxy._types import ( @@ -1139,7 +1139,9 @@ def _estimated_prompt_usage( None, ) return _estimate_dispatched_failure_usage( - model=str(model_call_details.get("model") or ""), + model=usage_tokenizer_model( + str(model_call_details.get("model") or ""), get_base_model_from_metadata(model_call_details) + ), request_input=( messages_since_newest_compaction(dispatched_input) if dispatched_call_type in _RESPONSES_CALL_TYPES diff --git a/litellm/realtime_api/main.py b/litellm/realtime_api/main.py index 7b9068ff95e..e9b534bdd89 100644 --- a/litellm/realtime_api/main.py +++ b/litellm/realtime_api/main.py @@ -31,7 +31,12 @@ from litellm.types.realtime import ( ) from litellm.types.router import GenericLiteLLMParams from litellm.types.utils import CallTypes, LlmProviders -from litellm.utils import ProviderConfigManager, resolve_api_key_secret_reference +from litellm.utils import ( + ModelInfoLookupMiss, + ProviderConfigManager, + lookup_model_info_for_registration, + resolve_api_key_secret_reference, +) from ..litellm_core_utils.core_helpers import as_str_mapping, normalize_drop_params from ..litellm_core_utils.credential_accessor import CredentialAccessor @@ -42,8 +47,13 @@ from ..llms.azure.common_utils import get_azure_ad_token from ..llms.azure.realtime.handler import AzureOpenAIRealtime, azure_realtime_protocol_for_client from ..llms.bedrock.realtime.handler import BedrockRealtime, raise_if_session_committed from ..llms.custom_httpx.http_handler import realtime_ssl_for_url +from ..llms.openai.common_utils import is_openai_backed_api_base from ..llms.openai.live.handler import OpenAILiveSessions -from ..llms.openai.realtime.handler import OpenAIRealtime +from ..llms.openai.realtime.handler import ( + OpenAIRealtime, + confirm_gateway_session_started, + confirm_session_started, +) from ..llms.openai.workload_identity import openai_static_api_key, resolve_openai_bearer_token_async from ..llms.vertex_ai.audio_transcription.realtime_transformation import is_vertex_speech_to_text_model from ..llms.vertex_ai.realtime.transformation import VertexAIRealtimeConfig, vertex_realtime_config @@ -740,6 +750,18 @@ def _is_transcription_only_realtime_model(model: str, custom_llm_provider: str) return "/v1/realtime/transcription_sessions" in (model_info.get("supported_endpoints") or ()) +_REALTIME_SERVED_ENDPOINTS: Final = ("/v1/realtime", "/v1/audio/transcriptions", "/v1/live") +_GATEWAY_FIRST_EVENT_WAIT_SECONDS: Final = 3.0 + + +def _cost_map_lists_outside_realtime(model: str) -> bool: + model_info: Final = lookup_model_info_for_registration(model, "openai") + endpoints: Final = ( + () if isinstance(model_info, ModelInfoLookupMiss) else model_info.get("supported_endpoints") or () + ) + return bool(endpoints) and not any(endpoint.startswith(_REALTIME_SERVED_ENDPOINTS) for endpoint in endpoints) + + _TRANSCRIPTION_QUERY_PARAMS: Final[RealtimeQueryParams] = {"intent": "transcription"} @@ -785,6 +807,7 @@ async def realtime_health_check( api_version: str | None = None, realtime_protocol: str | None = None, model_params: Mapping[str, object] | None = None, + gateway_first_event_wait_seconds: float = _GATEWAY_FIRST_EVENT_WAIT_SECONDS, ) -> bool: """ Health check for realtime API - tries connection to the realtime API websocket @@ -800,9 +823,16 @@ async def realtime_health_check( without the OpenAI-Beta header is bridged to, with transcription-only models adding intent=transcription Returns: - bool - True if connection is successful, False otherwise + bool - True once the connection is open, and on OpenAI's own hosts once the first server event is not an + error, since OpenAI accepts the websocket handshake with missing or invalid credentials and only reports + the failure in its first server event. Behind any other OpenAI api_base the first event is read for + `gateway_first_event_wait_seconds` only, and a gateway that stays silent that long counts as healthy. + An `invalid_model` error also counts as healthy unless litellm's + cost map lists only endpoints realtime never serves for the model: OpenAI checks the key first, and Live + and transcription models are served through other endpoints. The listed `mode` is not read, since a + deployment's own `mode: realtime` replaces it when the router registers the deployment Raises: - Exception - if the connection is not successful + Exception - if the connection is not successful or if OpenAI's first server event is any other error """ import websockets @@ -822,10 +852,11 @@ async def realtime_health_check( str | None, api_version or resolved_params.get("api_version") ) url: str | None = None + openai_api_base: Final = resolved_api_base or litellm.api_base or "https://api.openai.com/" health_check_api_key: Final = ( await resolve_openai_bearer_token_async( static_api_key=openai_static_api_key(resolved_api_key), - api_base=resolved_api_base, + api_base=openai_api_base, litellm_params=resolved_params, ) if custom_llm_provider == LlmProviders.OPENAI.value @@ -850,10 +881,7 @@ async def realtime_health_check( query_params=azure_query_params, ) elif custom_llm_provider == "openai": - url = openai_realtime.construct_url( - api_base=resolved_api_base or "https://api.openai.com/", - query_params={"model": model}, - ) + url = openai_realtime.construct_url(api_base=openai_api_base, query_params={"model": model}) elif custom_llm_provider == "xai": url = xai_realtime.construct_url( api_base=resolved_api_base or "https://api.x.ai/v1", query_params={"model": model} @@ -899,8 +927,23 @@ async def realtime_health_check( additional_headers=auth_headers, max_size=REALTIME_WEBSOCKET_MAX_MESSAGE_SIZE_BYTES, ssl=realtime_ssl_for_url(url), - ): - return True + ) as connection: + if custom_llm_provider != "openai": + return True + if not is_openai_backed_api_base(url): + return await confirm_gateway_session_started( + connection, + model, + sent_credentials=bool(auth_headers), + model_listed_outside_realtime=_cost_map_lists_outside_realtime(model), + first_event_wait_seconds=gateway_first_event_wait_seconds, + ) + return await confirm_session_started( + connection, + model, + sent_credentials=bool(auth_headers), + model_listed_outside_realtime=_cost_map_lists_outside_realtime(model), + ) _realtime_health_check = realtime_health_check diff --git a/litellm/repositories/daily_activity_repository.py b/litellm/repositories/daily_activity_repository.py index 10c603fe56f..4ca23e4e89e 100644 --- a/litellm/repositories/daily_activity_repository.py +++ b/litellm/repositories/daily_activity_repository.py @@ -19,6 +19,7 @@ from litellm.repositories.daily_activity_sql import ( build_cache_leakage_keys_sql, build_entity_rollup_sql, build_export_sql, + build_guardrail_spend_sql, build_key_page_sql, build_key_search_sql, build_model_top_keys_sql, @@ -36,6 +37,7 @@ from litellm.types.repositories.daily_activity import ( ExportRow, ExportType, GroupingSetsRow, + GuardrailSpendRow, KeyMetadataRow, KeyPage, KeySpendRow, @@ -100,6 +102,7 @@ class DailyActivityDatabase(Protocol): _GROUPING_ADAPTER: Final = TypeAdapter(tuple[GroupingSetsRow, ...]) _ENTITY_ADAPTER: Final = TypeAdapter(tuple[EntityRollupRow, ...]) +_GUARDRAIL_SPEND_ADAPTER: Final = TypeAdapter(tuple[GuardrailSpendRow, ...]) _KEY_SPEND_ADAPTER: Final = TypeAdapter(tuple[KeySpendRow, ...]) _KEY_PAGE_TOTAL_ADAPTER: Final[TypeAdapter[int]] = TypeAdapter(int) _USER_SPEND_ADAPTER: Final = TypeAdapter(tuple[UserSpendRow, ...]) @@ -191,6 +194,9 @@ class DailyActivityRepository: distinct_api_keys=distinct_api_keys, ) + async def guardrail_spend(self, scope: DailyActivityScope) -> tuple[GuardrailSpendRow, ...]: + return _GUARDRAIL_SPEND_ADAPTER.validate_python(await self._query(build_guardrail_spend_sql(scope))) + async def search_keys(self, scope: DailyActivityScope, *, search: str, limit: int) -> tuple[str, ...]: if not 1 <= limit <= constants.USAGE_KEY_SEARCH_MAX: raise ValueError(f"limit must be between 1 and {constants.USAGE_KEY_SEARCH_MAX}") diff --git a/litellm/repositories/daily_activity_sql.py b/litellm/repositories/daily_activity_sql.py index 3d27e7d937e..7ec9fa67a67 100644 --- a/litellm/repositories/daily_activity_sql.py +++ b/litellm/repositories/daily_activity_sql.py @@ -261,6 +261,25 @@ def build_entity_rollup_sql(scope: DailyActivityScope, *, api_key_limit: int) -> return SqlQuery(sql=sql, params=(*where_params, PTU_SENTINEL_API_KEY, api_key_limit)) +def build_guardrail_spend_sql(scope: DailyActivityScope) -> SqlQuery: + pg_table: Final = PRISMA_TO_PG_TABLE[scope.table] + where_clause, where_params = build_where_clause(scope) + sql: Final = f""" + SELECT g.date, g.guardrail_id, COALESCE(t.guardrail_name, g.guardrail_id) AS guardrail_name, g.api_key, + COALESCE(SUM(g.cost), 0)::float AS spend, + COALESCE(SUM(CASE WHEN g.cost IS NULL THEN g.units ELSE g.untracked_units END), 0)::bigint AS untracked_units + FROM "LiteLLM_DailyGuardrailUsageUnits" g + LEFT JOIN "LiteLLM_GuardrailsTable" t ON t.guardrail_id = g.guardrail_id + WHERE g.date >= $1 AND g.date <= $2 + AND EXISTS ( + SELECT 1 FROM "{pg_table}" + WHERE {where_clause} AND "{pg_table}".date = g.date AND "{pg_table}".api_key = g.api_key + ) + GROUP BY g.date, g.guardrail_id, t.guardrail_name, g.api_key + """ + return SqlQuery(sql=sql, params=where_params) + + def _key_spend_select() -> str: return """ COALESCE(SUM(spend), 0)::float AS spend, diff --git a/litellm/responses/additional_tools.py b/litellm/responses/additional_tools.py index 4b897ff58c0..ce530447c0d 100644 --- a/litellm/responses/additional_tools.py +++ b/litellm/responses/additional_tools.py @@ -1,5 +1,8 @@ -from collections.abc import Sequence +import json +from collections.abc import Iterator, Mapping, Sequence from dataclasses import dataclass +from itertools import groupby +from types import MappingProxyType from typing import Final, cast # noqa: TID251 # validating the openai tool union strips vendor keys from raw tools from pydantic import ValidationError @@ -15,8 +18,8 @@ class _InputItemType(LiteLLMBaseModel): type: str = "" -class _AdditionalToolsItem(LiteLLMBaseModel): - tools: tuple[dict[str, object], ...] = () +class _ToolList(LiteLLMBaseModel): + tools: tuple[Mapping[str, object], ...] = () @dataclass(frozen=True, slots=True) @@ -33,12 +36,54 @@ def _is_additional_tools_item(item: object) -> bool: return False -def _tools_of_item(item: object) -> tuple[ALL_RESPONSES_API_TOOL_PARAMS, ...]: +def _tool_list_of(value: object) -> tuple[Mapping[str, object], ...]: try: - parsed: Final = _AdditionalToolsItem.model_validate(item) + return _ToolList.model_validate(value).tools except ValidationError: return () - return tuple(cast("ALL_RESPONSES_API_TOOL_PARAMS", tool) for tool in parsed.tools) + + +def _tools_of_item(item: object) -> tuple[ALL_RESPONSES_API_TOOL_PARAMS, ...]: + return tuple(cast("ALL_RESPONSES_API_TOOL_PARAMS", tool) for tool in _tool_list_of(item)) + + +def _tool_identity(tool: Mapping[str, object]) -> str: + name: Final = tool.get("name") + if isinstance(name, str) and name: + return f"{tool.get('type')}:{name}" + return json.dumps(tool, sort_keys=True, default=str) + + +def _members_of_copies(copies: Sequence[Mapping[str, object]]) -> Iterator[Mapping[str, object]]: + for namespace in copies: + yield from _tool_list_of(namespace) + + +def _merged(copies: Sequence[Mapping[str, object]]) -> Mapping[str, object]: + newest: Final = copies[-1] + if newest.get("type") != "namespace" or len(copies) == 1: + return newest + members: Final = tuple(_members_of_copies(copies)) + return {**newest, "tools": list(_unique_tools(members))} if members else newest + + +def _identity_of(keyed_tool: tuple[str, Mapping[str, object]]) -> str: + return keyed_tool[0] + + +def _unique_tools(tools: Sequence[Mapping[str, object]]) -> tuple[Mapping[str, object], ...]: + """Codex re-sends its tool list in the input on every turn, so the same tool arrives many times. + Keep each tool once, at its first position, with the newest copy's definition, and merge the + members of a namespace sent more than once.""" + keyed: Final = tuple((_tool_identity(tool), tool) for tool in tools) + copies_by_identity: Final = MappingProxyType( + { + identity: tuple(tool for _, tool in group) + for identity, group in groupby(sorted(keyed, key=_identity_of), key=_identity_of) + } + ) + first_seen_order: Final = tuple(dict.fromkeys(identity for identity, _ in keyed)) + return tuple(_merged(copies_by_identity[identity]) for identity in first_seen_order) def hoist_additional_tools( @@ -58,4 +103,8 @@ def hoist_additional_tools( len(items), ) remaining_input: Final = [item for item in input if not _is_additional_tools_item(item)] - return HoistedAdditionalTools(input=remaining_input, tools=(*existing, *hoisted), hoisted=hoisted) + unique: Final = tuple( + cast("ALL_RESPONSES_API_TOOL_PARAMS", tool) # cast-ok: a merged namespace is rebuilt from the same tool dicts + for tool in _unique_tools((*existing, *hoisted)) + ) + return HoistedAdditionalTools(input=remaining_input, tools=unique, hoisted=hoisted) diff --git a/litellm/responses/bridge_check.py b/litellm/responses/bridge_check.py index 504150b330c..826de8cfdc9 100644 --- a/litellm/responses/bridge_check.py +++ b/litellm/responses/bridge_check.py @@ -9,6 +9,7 @@ from litellm.llms.azure_ai.chat.transformation import AzureAIGPT5Config from litellm.llms.azure_ai.common_utils import ( azure_ai_supports_native_responses, foundry_chat_rejects_function_tools_while_reasoning, + is_foundry_project_agent, ) from litellm.llms.openai.chat.gpt_reasoning_transformation import OpenAIGPT5Config from litellm.secret_managers.main import get_secret_str @@ -181,6 +182,9 @@ def responses_api_bridge_check( elif pinned_mode == "chat" and backend_serves_chat_completions(model_info): model_info["mode"] = "chat" + if custom_llm_provider == LlmProviders.AZURE_AI.value and is_foundry_project_agent(model): + model_info["mode"] = "responses" + if web_search_options is not None and custom_llm_provider == "xai": model_info["mode"] = "responses" model = model.replace("responses/", "") diff --git a/litellm/responses/litellm_completion_transformation/client_tool_search.py b/litellm/responses/litellm_completion_transformation/client_tool_search.py new file mode 100644 index 00000000000..030bb014b7a --- /dev/null +++ b/litellm/responses/litellm_completion_transformation/client_tool_search.py @@ -0,0 +1,268 @@ +import json +from collections.abc import Iterable, Mapping, Sequence +from dataclasses import dataclass +from itertools import chain +from types import MappingProxyType +from typing import Final, cast # noqa: TID251 # loaded tool specs are forwarded as the client sent them + +from openai.types.responses.response_input_param import ( + FunctionCallOutput, + ResponseFunctionToolCallParam, + ResponseInputItemParam, +) +from pydantic import ConfigDict, TypeAdapter, ValidationError + +from litellm.types.llms.base import LiteLLMBaseModel +from litellm.types.llms.openai import ( + ALL_RESPONSES_API_TOOL_PARAMS, + ChatCompletionToolParam, + ChatCompletionToolParamFunctionChunk, + ResponseInputParam, +) + +from .custom_tools import function_chat_tool +from .tool_search import CLIENT_TOOL_SEARCH_FUNCTION_NAME, has_client_tool_search + +__all__ = [ + "ClientToolSearchBridge", + "bridge_client_tool_search", + "client_tool_search_chat_tool", + "client_tool_search_loaded_tools", +] + +_DEFAULT_SEARCH_DESCRIPTION: Final = ( + "Search the deferred tools by keyword. The matching tools are loaded and become callable on the next turn." +) +_DEFAULT_SEARCH_PARAMETERS: Final = MappingProxyType( + { + "type": "object", + "properties": { + "query": {"type": "string", "description": "Search query for deferred tools."}, + "limit": {"type": "integer", "description": "Maximum number of tools to return. Defaults to 8."}, + }, + "required": ["query"], + "additionalProperties": False, + } +) + + +class _ClientToolSearchItem(LiteLLMBaseModel): + model_config = ConfigDict(frozen=True) + + type: str = "" + execution: str | None = None + call_id: str | None = None + arguments: object = None + tools: tuple[Mapping[str, object], ...] = () + + +class _ToolSpec(LiteLLMBaseModel): + model_config = ConfigDict(frozen=True) + + type: str = "" + name: str = "" + description: str = "" + defer_loading: object = None + tools: tuple[Mapping[str, object], ...] = () + + +class _ClientToolSearchTool(LiteLLMBaseModel): + model_config = ConfigDict(frozen=True) + + description: str = "" + parameters: Mapping[str, object] | None = None + + +@dataclass(frozen=True, slots=True) +class _LoadedTool: + namespace: str | None + namespace_description: str + spec: Mapping[str, object] + + @property + def callable_name(self) -> str: + name: Final = str(self.spec.get("name") or "") + return name if self.namespace is None else f"{self.namespace}__{name}" + + +@dataclass(frozen=True, slots=True) +class ClientToolSearchBridge: + input: str | ResponseInputParam + tools: tuple[ALL_RESPONSES_API_TOOL_PARAMS, ...] + bridged: bool + + +def client_tool_search_chat_tool(tool: Mapping[str, object]) -> ChatCompletionToolParam: + spec: Final = _ClientToolSearchTool.model_validate(tool) + function: Final = ChatCompletionToolParamFunctionChunk( + name=CLIENT_TOOL_SEARCH_FUNCTION_NAME, + description=spec.description or _DEFAULT_SEARCH_DESCRIPTION, + parameters=dict(spec.parameters or _DEFAULT_SEARCH_PARAMETERS), + ) + return function_chat_tool(function, None, False) + + +def _client_tool_search_item(item: object) -> _ClientToolSearchItem | None: + try: + parsed: Final = _ClientToolSearchItem.model_validate(item) + except ValidationError: + return None + if parsed.type not in ("tool_search_call", "tool_search_output") or parsed.execution != "client": + return None + return parsed + + +_INPUT_ITEMS: Final = TypeAdapter(tuple[object, ...]) + + +def _searched_tools(item: object) -> tuple[Mapping[str, object], ...]: + parsed: Final = _client_tool_search_item(item) + if parsed is None or parsed.type != "tool_search_output" or not parsed.call_id: + return () + return parsed.tools + + +def client_tool_search_loaded_tools(input: object) -> tuple[Mapping[str, object], ...]: + if not isinstance(input, (list, tuple)): + return () + return tuple(chain.from_iterable(map(_searched_tools, _INPUT_ITEMS.validate_python(input)))) + + +def _tool_spec(tool: object) -> _ToolSpec | None: + try: + return _ToolSpec.model_validate(tool) + except ValidationError: + return None + + +def _as_tool_param(spec: Mapping[str, object]) -> ALL_RESPONSES_API_TOOL_PARAMS: + return cast("ALL_RESPONSES_API_TOOL_PARAMS", spec) # cast-ok: client tool specs are forwarded as sent + + +def _without_deferral(spec: Mapping[str, object]) -> Mapping[str, object]: + return {key: value for key, value in spec.items() if key != "defer_loading"} + + +def _loaded_tools(tool: Mapping[str, object]) -> tuple[_LoadedTool, ...]: + spec: Final = _tool_spec(tool) + if spec is None: + return () + if spec.type != "namespace": + return (_LoadedTool(namespace=None, namespace_description="", spec=_without_deferral(tool)),) + return tuple( + _LoadedTool(namespace=spec.name, namespace_description=spec.description, spec=_without_deferral(member)) + for member in spec.tools + ) + + +def _all_loaded_tools(tools: Iterable[Mapping[str, object]]) -> tuple[_LoadedTool, ...]: + return tuple(chain.from_iterable(map(_loaded_tools, tools))) + + +def _callable_names(tool: object) -> tuple[str, ...]: + spec: Final = _tool_spec(tool) + if spec is None: + return () + if spec.type != "namespace": + return (spec.name,) + return tuple(f"{spec.name}__{member.get('name') or ''}" for member in spec.tools) + + +def _first_occurrences(loaded: Sequence[_LoadedTool], taken: frozenset[str]) -> tuple[_LoadedTool, ...]: + first_index: Final = {tool.callable_name: index for index, tool in reversed(tuple(enumerate(loaded)))} + return tuple( + tool + for index, tool in enumerate(loaded) + if first_index[tool.callable_name] == index and tool.callable_name not in taken + ) + + +def _regrouped(loaded: Sequence[_LoadedTool]) -> tuple[ALL_RESPONSES_API_TOOL_PARAMS, ...]: + namespaces: Final = {tool.namespace: tool.namespace_description for tool in reversed(loaded) if tool.namespace} + ordered_namespaces: Final = tuple(dict.fromkeys(tool.namespace for tool in loaded if tool.namespace)) + top_level: Final = tuple(tool.spec for tool in loaded if tool.namespace is None) + grouped: Final = tuple( + { + "type": "namespace", + "name": namespace, + "description": namespaces[namespace], + "tools": tuple(tool.spec for tool in loaded if tool.namespace == namespace), + } + for namespace in ordered_namespaces + ) + return tuple(_as_tool_param(tool) for tool in (*top_level, *grouped)) + + +def _is_deferred(tool: object) -> bool: + spec: Final = _tool_spec(tool) + return spec is not None and spec.defer_loading is True + + +def _without_deferred(tool: ALL_RESPONSES_API_TOOL_PARAMS) -> ALL_RESPONSES_API_TOOL_PARAMS | None: + spec: Final = _tool_spec(tool) + if spec is None: + return tool + if spec.type != "namespace": + return None if spec.defer_loading is True else tool + eager_members: Final = tuple(member for member in spec.tools if not _is_deferred(member)) + if len(eager_members) == len(spec.tools): + return tool + if not eager_members: + return None + return _as_tool_param({**tool, "tools": eager_members}) + + +def _search_output_text(loaded: Sequence[_LoadedTool]) -> str: + if not loaded: + return "No tools matched the search." + return "Loaded these tools, which are now callable: " + ", ".join(tool.callable_name for tool in loaded) + + +def _search_arguments_json(arguments: object) -> str: + return arguments if isinstance(arguments, str) else json.dumps(arguments or {}) + + +def _bridged_item(item: ResponseInputItemParam) -> ResponseInputItemParam | None: + parsed: Final = _client_tool_search_item(item) + if parsed is None: + return item + if not parsed.call_id: + return None + if parsed.type == "tool_search_call": + return ResponseFunctionToolCallParam( + type="function_call", + call_id=parsed.call_id, + name=CLIENT_TOOL_SEARCH_FUNCTION_NAME, + arguments=_search_arguments_json(parsed.arguments), + ) + return FunctionCallOutput( + type="function_call_output", call_id=parsed.call_id, output=_search_output_text(_all_loaded_tools(parsed.tools)) + ) + + +def bridge_client_tool_search( + input: str | ResponseInputParam, + tools: Sequence[ALL_RESPONSES_API_TOOL_PARAMS] | None, + loaded_earlier: Sequence[Mapping[str, object]] = (), +) -> ClientToolSearchBridge: + existing: Final = tuple(tools or ()) + searches_on_client: Final = has_client_tool_search(existing) + items: Final = () if isinstance(input, str) else tuple(input) + search_items: Final = tuple(parsed for item in items if (parsed := _client_tool_search_item(item)) is not None) + if not searches_on_client and not search_items: + return ClientToolSearchBridge(input=input, tools=existing, bridged=False) + eager: Final = ( + tuple(kept for tool in existing if (kept := _without_deferred(tool)) is not None) + if searches_on_client + else existing + ) + loaded: Final = _all_loaded_tools((*loaded_earlier, *client_tool_search_loaded_tools(input))) + taken: Final = frozenset(chain.from_iterable(map(_callable_names, eager))) + bridged_input: Final = ( + input if isinstance(input, str) else [bridged for item in input if (bridged := _bridged_item(item)) is not None] + ) + return ClientToolSearchBridge( + input=bridged_input, + tools=(*eager, *_regrouped(_first_occurrences(loaded, taken))), + bridged=True, + ) diff --git a/litellm/responses/litellm_completion_transformation/count_request.py b/litellm/responses/litellm_completion_transformation/count_request.py index 7679b4ede71..8e8e4066bb8 100644 --- a/litellm/responses/litellm_completion_transformation/count_request.py +++ b/litellm/responses/litellm_completion_transformation/count_request.py @@ -20,7 +20,7 @@ from litellm.responses.litellm_completion_transformation.transformation import ( LiteLLMCompletionResponsesConfig, ) from litellm.responses.main import previous_response_client_ids -from litellm.types.llms.openai import ResponseInputParam +from litellm.types.llms.openai import ALL_RESPONSES_API_TOOL_PARAMS, ResponseInputParam from litellm.utils import ProviderConfigManager _COUNTED_CHAT_PARAMS: Final = ( @@ -119,14 +119,13 @@ def _with_hoisted_additional_tools(responses_request: Mapping[str, object]) -> M if not isinstance(responses_input, list): return responses_request input_items: Final = cast(ResponseInputParam, responses_input) # cast-ok: forwarded as sent, as inference does - hoisted: Final = hoist_additional_tools(input_items, None) + top_level_tools: Final = cast( # cast-ok: tools are forwarded as sent, as inference does + "tuple[ALL_RESPONSES_API_TOOL_PARAMS, ...]", _ITEMS.validate_python(responses_request.get("tools") or ()) + ) + hoisted: Final = hoist_additional_tools(input_items, top_level_tools) if not hoisted.hoisted: return responses_request - return { - **responses_request, - "input": hoisted.input, - "tools": [*_ITEMS.validate_python(responses_request.get("tools") or ()), *hoisted.hoisted], - } + return {**responses_request, "input": hoisted.input, "tools": list(hoisted.tools)} def _with_emulated_file_search(responses_request: Mapping[str, object]) -> Mapping[str, object]: diff --git a/litellm/responses/litellm_completion_transformation/handler.py b/litellm/responses/litellm_completion_transformation/handler.py index ea3bda1b8b5..141e97d902d 100644 --- a/litellm/responses/litellm_completion_transformation/handler.py +++ b/litellm/responses/litellm_completion_transformation/handler.py @@ -2,17 +2,21 @@ Handler for transforming responses api requests to litellm.completion requests """ -from collections.abc import Coroutine, Mapping +from collections.abc import Coroutine, Mapping, Sequence +from dataclasses import dataclass from typing import Final from pydantic import TypeAdapter import litellm -from litellm.responses.additional_tools import hoist_additional_tools +from litellm.responses.additional_tools import HoistedAdditionalTools, hoist_additional_tools +from litellm.responses.litellm_completion_transformation.client_tool_search import bridge_client_tool_search from litellm.responses.litellm_completion_transformation.compaction_items import holds_compaction_summary +from litellm.responses.litellm_completion_transformation.session_handler import ResponsesSessionHandler, StoredTurns from litellm.responses.litellm_completion_transformation.streaming_iterator import ( LiteLLMCompletionStreamingIterator, ) +from litellm.responses.litellm_completion_transformation.tool_search import has_client_tool_search from litellm.responses.litellm_completion_transformation.transformation import ( LiteLLMCompletionResponsesConfig, with_compaction_items_as_params, @@ -28,6 +32,28 @@ from litellm.types.utils import ModelResponse _REQUEST_KWARGS_ADAPTER: Final = TypeAdapter(dict[str, object]) +@dataclass(frozen=True, slots=True) +class _BridgedRequest: + input: str | ResponseInputParam + responses_api_request: ResponsesAPIOptionalRequestParams + + +def _bridged_request( + hoisted: HoistedAdditionalTools, + responses_api_request: ResponsesAPIOptionalRequestParams, + loaded_earlier: Sequence[Mapping[str, object]], +) -> _BridgedRequest: + searched: Final = bridge_client_tool_search(hoisted.input, hoisted.tools, loaded_earlier) + return _BridgedRequest( + input=searched.input, + responses_api_request=( + {**responses_api_request, "tools": list(searched.tools)} + if hoisted.hoisted or searched.bridged + else responses_api_request + ), + ) + + class LiteLLMCompletionTransformationHandler: def response_api_handler( self, @@ -48,10 +74,22 @@ class LiteLLMCompletionTransformationHandler: | Coroutine[object, object, ResponsesAPIResponse | BaseResponsesAPIStreamingIterator] ): hoisted: Final = hoist_additional_tools(input, responses_api_request.get("tools")) - bridged_input: Final = hoisted.input - bridged_request: Final[ResponsesAPIOptionalRequestParams] = ( - {**responses_api_request, "tools": list(hoisted.tools)} if hoisted.hoisted else responses_api_request - ) + previous_response_id: Final = responses_api_request.get("previous_response_id") + if _is_async and previous_response_id and has_client_tool_search(hoisted.tools): + return self._async_response_api_handler_after_earlier_searches( + previous_response_client_ids, + previous_response_id, + hoisted, + model=model, + responses_api_request=responses_api_request, + custom_llm_provider=custom_llm_provider, + stream=stream, + extra_headers=extra_headers, + request_kwargs=_REQUEST_KWARGS_ADAPTER.validate_python(kwargs), + ) + bridged: Final = _bridged_request(hoisted, responses_api_request, ()) + bridged_input: Final = bridged.input + bridged_request: Final = bridged.responses_api_request litellm_completion_request: Final[dict] = ( LiteLLMCompletionResponsesConfig.transform_responses_api_request_to_chat_completion_request( model=model, @@ -73,13 +111,8 @@ class LiteLLMCompletionTransformationHandler: **kwargs, ) - completion_args: Final = {} - completion_args.update(kwargs) - completion_args.update(litellm_completion_request) - completion_args["_skip_responses_api_bridge"] = True - litellm_completion_response: Final[ModelResponse | litellm.CustomStreamWrapper] = litellm.completion( - **completion_args, + **{**kwargs, **litellm_completion_request, "_skip_responses_api_bridge": True}, ) if isinstance(litellm_completion_response, ModelResponse): @@ -104,9 +137,53 @@ class LiteLLMCompletionTransformationHandler: ) raise ValueError(f"Unexpected response type: {type(litellm_completion_response)}") + async def _async_response_api_handler_after_earlier_searches( + self, + previous_response_client_ids: tuple[str, ...], + previous_response_id: str, + hoisted: HoistedAdditionalTools, + /, + *, + model: str, + responses_api_request: ResponsesAPIOptionalRequestParams, + custom_llm_provider: str | None, + stream: bool | None, + extra_headers: Mapping[str, object] | None, + request_kwargs: Mapping[str, object], + ) -> ResponsesAPIResponse | BaseResponsesAPIStreamingIterator: + stored_turns: Final = await ResponsesSessionHandler.get_stored_turns_for_previous_response_id( + previous_response_id, previous_response_client_ids + ) + bridged: Final = _bridged_request( + hoisted, + responses_api_request, + ResponsesSessionHandler.client_tool_search_tools_loaded_before( + stored_turns, previous_response_id, previous_response_client_ids + ), + ) + return await self.async_response_api_handler( + previous_response_client_ids, + stored_turns, + litellm_completion_request=( + LiteLLMCompletionResponsesConfig.transform_responses_api_request_to_chat_completion_request( + model=model, + input=bridged.input, + responses_api_request=bridged.responses_api_request, + custom_llm_provider=custom_llm_provider, + stream=stream, + extra_headers=extra_headers, + **request_kwargs, + ) + ), + request_input=bridged.input, + responses_api_request=bridged.responses_api_request, + **request_kwargs, + ) + async def async_response_api_handler( self, previous_response_client_ids: tuple[str, ...] = (), + stored_turns: StoredTurns | None = None, /, *, litellm_completion_request: dict, @@ -122,16 +199,12 @@ class LiteLLMCompletionTransformationHandler: instructions=responses_api_request.get("instructions"), request_kwargs=_REQUEST_KWARGS_ADAPTER.validate_python(kwargs), previous_response_client_ids=previous_response_client_ids, + stored_turns=stored_turns, input_replaces_history=holds_compaction_summary(with_compaction_items_as_params(request_input)), ) - acompletion_args: Final = {} - acompletion_args.update(kwargs) - acompletion_args.update(litellm_completion_request) - acompletion_args["_skip_responses_api_bridge"] = True - litellm_completion_response: Final[ModelResponse | litellm.CustomStreamWrapper] = await litellm.acompletion( - **acompletion_args, + **{**kwargs, **litellm_completion_request, "_skip_responses_api_bridge": True}, ) if isinstance(litellm_completion_response, ModelResponse): responses_api_response: Final[ResponsesAPIResponse] = ( diff --git a/litellm/responses/litellm_completion_transformation/session_handler.py b/litellm/responses/litellm_completion_transformation/session_handler.py index 1ab6293b432..ce2396355a2 100644 --- a/litellm/responses/litellm_completion_transformation/session_handler.py +++ b/litellm/responses/litellm_completion_transformation/session_handler.py @@ -9,6 +9,10 @@ import litellm from litellm._logging import verbose_proxy_logger from litellm.constants import REDACTED_BY_LITELLM, REDACTED_TOOL_CALL_ARGUMENTS_PLACEHOLDER from litellm.litellm_core_utils.cold_storage_handler import ColdStorageHandler +from litellm.responses.litellm_completion_transformation.client_tool_search import ( + bridge_client_tool_search, + client_tool_search_loaded_tools, +) from litellm.responses.litellm_completion_transformation.compaction_items import ( holds_compaction_summary, input_items, @@ -88,6 +92,12 @@ class _ReplayStart: at_output: bool +@dataclass(frozen=True, slots=True) +class StoredTurns: + spend_logs: tuple["SpendLogsPayload", ...] + proxy_server_requests: tuple[Mapping[str, object] | None, ...] + + def _compaction_point( index: int, spend_log: "SpendLogsPayload", proxy_server_request: Mapping[str, object] | None ) -> _ReplayStart | None: @@ -190,6 +200,7 @@ class ResponsesSessionHandler: previous_response_id: str, item_cache_control: bool = False, client_response_ids: tuple[str, ...] = (), + stored_turns: StoredTurns | None = None, ) -> ChatCompletionSession: """ Return the chat completion message history for a previous response id @@ -200,23 +211,21 @@ class ResponsesSessionHandler: ) verbose_proxy_logger.debug("inside get_chat_completion_message_history_for_previous_response_id") - all_spend_logs: Final = [ - spend_log - for spend_log in await ResponsesSessionHandler.get_all_spend_logs_for_previous_response_id( + turns: Final = ( + stored_turns + if stored_turns is not None + else await ResponsesSessionHandler.get_stored_turns_for_previous_response_id( previous_response_id, client_response_ids ) - if _is_a_conversation_turn(spend_log) - ] + ) + all_spend_logs: Final = turns.spend_logs verbose_proxy_logger.debug("found %s spend logs for this response id", len(all_spend_logs)) litellm_session_id: str | None = None if len(all_spend_logs) > 0: litellm_session_id = all_spend_logs[0].get("session_id") - proxy_server_requests: Final = [ - await ResponsesSessionHandler.get_proxy_server_request_from_spend_log(spend_log=spend_log) - for spend_log in all_spend_logs - ] + proxy_server_requests: Final = turns.proxy_server_requests replayable_turns: Final = _turns_through_referenced_response( all_spend_logs, _referenced_request_ids(previous_response_id, client_response_ids) ) @@ -252,6 +261,45 @@ class ResponsesSessionHandler: instructions=_latest_replayable_instructions(proxy_server_requests), ) + @staticmethod + async def get_stored_turns_for_previous_response_id( + previous_response_id: str, + client_response_ids: tuple[str, ...] = (), + ) -> StoredTurns: + spend_logs: Final = tuple( + spend_log + for spend_log in await ResponsesSessionHandler.get_all_spend_logs_for_previous_response_id( + previous_response_id, client_response_ids + ) + if _is_a_conversation_turn(spend_log) + ) + return StoredTurns( + spend_logs=spend_logs, + proxy_server_requests=tuple( + [ + await ResponsesSessionHandler.get_proxy_server_request_from_spend_log(spend_log=spend_log) + for spend_log in spend_logs + ] + ), + ) + + @staticmethod + def client_tool_search_tools_loaded_before( + stored_turns: StoredTurns, + previous_response_id: str, + client_response_ids: tuple[str, ...] = (), + ) -> tuple[Mapping[str, object], ...]: + turns: Final = _turns_through_referenced_response( + stored_turns.spend_logs, _referenced_request_ids(previous_response_id, client_response_ids) + ) + return tuple( + chain.from_iterable( + client_tool_search_loaded_tools(request.get("input")) + for request in stored_turns.proxy_server_requests[:turns] + if request is not None + ) + ) + @staticmethod def _history_of_turns( spend_logs: Sequence["SpendLogsPayload"], @@ -310,7 +358,7 @@ class ResponsesSessionHandler: if response_input_param: chat_completion_message_history.extend( LiteLLMCompletionResponsesConfig.transform_responses_api_input_to_messages( - input=response_input_param, + input=bridge_client_tool_search(response_input_param, None).input, responses_api_request={}, replay_reasoning=True, item_cache_control=item_cache_control, @@ -325,7 +373,7 @@ class ResponsesSessionHandler: if (responses_api_output := _stored_responses_api_output(_response_output)) is not None: chat_completion_message_history.extend( LiteLLMCompletionResponsesConfig.transform_responses_api_input_to_messages( - input=responses_api_output, + input=bridge_client_tool_search(responses_api_output, None).input, responses_api_request={}, replay_reasoning=True, item_cache_control=item_cache_control, diff --git a/litellm/responses/litellm_completion_transformation/streaming_iterator.py b/litellm/responses/litellm_completion_transformation/streaming_iterator.py index b5ef9e95741..892da541935 100644 --- a/litellm/responses/litellm_completion_transformation/streaming_iterator.py +++ b/litellm/responses/litellm_completion_transformation/streaming_iterator.py @@ -1,7 +1,8 @@ import time import uuid -from collections.abc import Sequence +from collections.abc import Mapping, Sequence from itertools import filterfalse +from types import MappingProxyType from typing import Any, Final, cast import litellm @@ -18,9 +19,9 @@ from litellm.responses.litellm_completion_transformation.custom_tools import ( ) from litellm.responses.litellm_completion_transformation.reasoning_items import mint_reasoning_item_id from litellm.responses.litellm_completion_transformation.tool_search import ( + ToolSearchExecution, build_tool_search_call, - has_server_tool_search, - is_anthropic_tool_search_use, + tool_search_routing, ) from litellm.responses.litellm_completion_transformation.transformation import ( LiteLLMCompletionResponsesConfig, @@ -30,6 +31,7 @@ from litellm.responses.utils import ResponsesAPIRequestUtils from litellm.types.llms.openai import ( PART_UNION_TYPES, BaseLiteLLMOpenAIResponseObject, + ChatCompletionAnnotation, ContentPartAddedEvent, ContentPartDoneEvent, ContentPartDonePartOutputText, @@ -56,6 +58,7 @@ from litellm.types.llms.openai import ( WebSearchCallInProgressEvent, WebSearchCallSearchingEvent, ) +from litellm.types.responses.main import GenericResponseOutputItemContentAnnotation from litellm.types.utils import Delta as ChatCompletionDelta from litellm.types.utils import ( ModelResponse, @@ -105,7 +108,6 @@ def _delta_carries_output(delta: ChatCompletionDelta) -> bool: getattr(delta, "reasoning_content", None), delta.tool_calls, delta.function_call, - getattr(delta, "annotations", None), getattr(delta, "images", None), getattr(delta, "audio", None), ) @@ -150,7 +152,8 @@ class LiteLLMCompletionStreamingIterator(ResponsesAPIStreamingIterator): self.sent_output_text_done_event: bool = False self.sent_output_content_part_done_event: bool = False self.sent_output_item_done_event: bool = False - self.sent_annotation_events: bool = False + self._annotation_index: int = 0 + self._annotations_awaiting_message: tuple[ChatCompletionAnnotation, ...] = () self.litellm_model_response: ModelResponse | TextCompletionResponse | None = None self.completed_response = None self.final_text: str = "" @@ -165,6 +168,7 @@ class LiteLLMCompletionStreamingIterator(ResponsesAPIStreamingIterator): self._upstream_exhausted: bool = False self._response_id_primed: bool = False self._pending_tool_events: list[BaseLiteLLMOpenAIResponseObject] = [] + self._tool_calls_held_behind_text: tuple[object, ...] = () self._tool_output_index_by_call_id: dict[str, int] = {} self._tool_args_by_call_id: dict[str, str] = {} self._tool_item_id_by_call_id: dict[str, str] = {} # mutable-ok: filled per call id as tool call events stream @@ -189,16 +193,21 @@ class LiteLLMCompletionStreamingIterator(ResponsesAPIStreamingIterator): self._namespace_tool_names = LiteLLMCompletionResponsesConfig.namespace_tool_name_map(request_tools) self._web_search_calls: dict[str, object] = {} # mutable-ok: latest call by provider id self._queued_web_search_call_ids: set[str] = set() # mutable-ok: emitted call ids - self._tool_search_requested: bool = has_server_tool_search(request_tools) - self._tool_search_call_ids: frozenset[str] = frozenset() + self._tool_search = tool_search_routing(request_tools) + self._tool_search_executions: Mapping[str, ToolSearchExecution] = MappingProxyType({}) - def _is_tool_search_call(self, call_id: str, fn_name: str) -> bool: - if call_id in self._tool_search_call_ids: - return True - if not self._tool_search_requested or not is_anthropic_tool_search_use(call_id, fn_name): - return False - self._tool_search_call_ids = self._tool_search_call_ids | {call_id} - return True + async def aclose(self) -> None: + await self.litellm_custom_stream_wrapper.aclose() + + def _tool_search_execution(self, call_id: str, fn_name: str) -> ToolSearchExecution | None: + known: Final = self._tool_search_executions.get(call_id) + if known is not None: + return known + execution: Final = self._tool_search.execution_of(call_id, fn_name) + if execution is None: + return None + self._tool_search_executions = MappingProxyType({**self._tool_search_executions, call_id: execution}) + return execution def _next_output_item_added(self, output_index: int, item: BaseLiteLLMOpenAIResponseObject) -> OutputItemAddedEvent: self._sequence_number += 1 @@ -213,18 +222,22 @@ class LiteLLMCompletionStreamingIterator(ResponsesAPIStreamingIterator): def _queue_output_item_added(self, output_index: int, item: BaseLiteLLMOpenAIResponseObject) -> None: self._pending_tool_events.append(self._next_output_item_added(output_index, item)) - def _queue_tool_search_call_added(self, call_id: str, output_index: int, args_delta: str) -> None: + def _queue_tool_search_call_added( + self, call_id: str, output_index: int, args_delta: str, execution: ToolSearchExecution + ) -> None: if call_id not in self._tool_args_by_call_id: self._tool_args_by_call_id[call_id] = "" - item: Final = build_tool_search_call(call_id, "", "in_progress") + item: Final = build_tool_search_call(call_id, "", "in_progress", execution) self._tool_item_id_by_call_id[call_id] = item.id self._queue_output_item_added(output_index, BaseLiteLLMOpenAIResponseObject(**item.model_dump())) self._tool_args_by_call_id[call_id] += args_delta - def _queue_tool_search_call_done(self, call_id: str, output_index: int, final_args: str) -> None: - self._queue_tool_search_call_added(call_id, output_index, "") + def _queue_tool_search_call_done( + self, call_id: str, output_index: int, final_args: str, execution: ToolSearchExecution + ) -> None: + self._queue_tool_search_call_added(call_id, output_index, "", execution) item: Final = build_tool_search_call( - call_id, final_args or self._tool_args_by_call_id.get(call_id, ""), "completed" + call_id, final_args or self._tool_args_by_call_id.get(call_id, ""), "completed", execution ) self._sequence_number += 1 self._pending_tool_events.append( @@ -338,7 +351,7 @@ class LiteLLMCompletionStreamingIterator(ResponsesAPIStreamingIterator): namespace_kwargs: Final = {"namespace": tool_namespace} if tool_namespace else {} return {**item_kwargs, "name": tool_name, **namespace_kwargs} - def _is_reasoning_end(self, chunk): + def _is_reasoning_end(self, chunk: ModelResponseStream) -> bool: if not chunk.choices: return False delta: Final = chunk.choices[0].delta @@ -349,7 +362,9 @@ class LiteLLMCompletionStreamingIterator(ResponsesAPIStreamingIterator): if hasattr(delta, "thinking_blocks") and delta.thinking_blocks: return False - return delta.content or delta.function_call or delta.tool_calls or chunk.choices[0].finish_reason is not None + return bool( + delta.content or delta.function_call or delta.tool_calls or chunk.choices[0].finish_reason is not None + ) def _reserve_web_search_indexes(self, provider_fields: object) -> None: if not isinstance(provider_fields, dict): @@ -388,6 +403,15 @@ class LiteLLMCompletionStreamingIterator(ResponsesAPIStreamingIterator): return "" return self._tool_call_id_by_index.get(index, "") + def _hold_tool_calls_behind_text(self, tool_calls: object) -> None: + if isinstance(tool_calls, list): + self._tool_calls_held_behind_text = (*self._tool_calls_held_behind_text, *tool_calls) + + def _release_held_tool_calls(self) -> tuple[object, ...]: + held: Final = self._tool_calls_held_behind_text + self._tool_calls_held_behind_text = () + return held + def _queue_tool_call_delta_events(self, tool_calls: object) -> None: """ Convert chat-completions streaming `tool_calls` deltas into Responses API streaming events. @@ -418,11 +442,14 @@ class LiteLLMCompletionStreamingIterator(ResponsesAPIStreamingIterator): else: fn_name = str(getattr(fn, "name", "") or "") fn_args_delta = serialize_tool_call_arguments(getattr(fn, "arguments", "")) + if call_id not in self._tool_output_index_by_call_id: + self._queue_held_annotations() output_index = self._get_or_assign_tool_output_index(call_id) - if self._is_tool_search_call(call_id, fn_name): - self._queue_tool_search_call_added(call_id, output_index, fn_args_delta) + if (search_execution := self._tool_search_execution(call_id, fn_name)) is not None: + self._queue_tool_search_call_added(call_id, output_index, fn_args_delta, search_execution) continue + self._started_tool_call = True if call_id not in self._tool_args_by_call_id: self._tool_args_by_call_id[call_id] = "" @@ -488,8 +515,8 @@ class LiteLLMCompletionStreamingIterator(ResponsesAPIStreamingIterator): self._queue_web_search_events(call_id, web_search_call) self._queued_web_search_call_ids.add(call_id) continue - if self._is_tool_search_call(call_id, fn_name): - self._queue_tool_search_call_done(call_id, output_index, fn_args) + if (search_execution := self._tool_search_execution(call_id, fn_name)) is not None: + self._queue_tool_search_call_done(call_id, output_index, fn_args, search_execution) continue # Track if this is a new tool call that wasn't streamed @@ -771,8 +798,7 @@ class LiteLLMCompletionStreamingIterator(ResponsesAPIStreamingIterator): return event def _queue_message_item_added_events(self) -> None: - if self._cached_item_id is None: - self._cached_item_id = f"msg_{uuid.uuid4()}" + item_id: Final = self._message_item_id() self.sent_message_item_added_event = True self.sent_content_part_added_event = True self._sequence_number += 1 @@ -781,7 +807,7 @@ class LiteLLMCompletionStreamingIterator(ResponsesAPIStreamingIterator): output_index=self._message_index(), item=BaseLiteLLMOpenAIResponseObject( **{ - "id": self._cached_item_id, + "id": item_id, "type": "message", "role": "assistant", "status": "in_progress", @@ -1070,6 +1096,7 @@ class LiteLLMCompletionStreamingIterator(ResponsesAPIStreamingIterator): if self.litellm_model_response: self._queue_compaction_item_added() self._queue_compaction_item_done() + self._queue_held_annotations() if self._pending_response_events: return self._pending_response_events.pop(0) # If tool calls exist, emit tool events before finishing/response.completed. @@ -1152,7 +1179,11 @@ class LiteLLMCompletionStreamingIterator(ResponsesAPIStreamingIterator): delta: Final = chunk.choices[0].delta if chunk.choices else None if delta and getattr(delta, "reasoning_content", None): self._accumulated_reasoning_content_parts.append(delta.reasoning_content) - if not self._is_reasoning_end(chunk): + if self._is_reasoning_end(chunk): + self._queue_reasoning_done_events() + + def _queue_reasoning_done_events(self) -> None: + if not self._reasoning_active or self._reasoning_done_emitted: return reasoning_content: Final = "".join(self._accumulated_reasoning_content_parts) self._cached_reasoning_item_id = ( @@ -1226,9 +1257,7 @@ class LiteLLMCompletionStreamingIterator(ResponsesAPIStreamingIterator): self._snapshot_chunk_for_stream_chunk_builder(chunk) ) self._queue_reasoning_done_events_on_reasoning_end(chunk) - response_api_chunk = self._transform_chat_completion_chunk_to_response_api_chunk(chunk) - if response_api_chunk: - self._pending_response_events.append(response_api_chunk) + self._queue_chunk_events(chunk) if self._pending_response_events: return self._pending_response_events.pop(0) @@ -1289,9 +1318,7 @@ class LiteLLMCompletionStreamingIterator(ResponsesAPIStreamingIterator): self._snapshot_chunk_for_stream_chunk_builder(cast(ModelResponseStream, chunk)) ) self._queue_reasoning_done_events_on_reasoning_end(chunk) - response_api_chunk = self._transform_chat_completion_chunk_to_response_api_chunk(chunk) - if response_api_chunk: - self._pending_response_events.append(response_api_chunk) + self._queue_chunk_events(chunk) if self._pending_response_events: return self._pending_response_events.pop(0) # Otherwise, loop to next chunk @@ -1302,6 +1329,58 @@ class LiteLLMCompletionStreamingIterator(ResponsesAPIStreamingIterator): self.finished = True raise e + def _queue_chunk_events(self, chunk: ModelResponseStream) -> None: + self._hold_chunk_annotations(chunk) + response_api_chunk: Final = self._transform_chat_completion_chunk_to_response_api_chunk(chunk) + if response_api_chunk: + self._pending_response_events.append(response_api_chunk) + if self.sent_message_item_added_event: + self._queue_held_annotations() + + def _hold_chunk_annotations(self, chunk: ModelResponseStream) -> None: + chunk_annotations: Final = (getattr(chunk.choices[0].delta, "annotations", None) or ()) if chunk.choices else () + self._annotations_awaiting_message = (*self._annotations_awaiting_message, *chunk_annotations) + + def _queue_held_annotations(self) -> None: + annotations: Final = self._annotations_awaiting_message + if not annotations: + return + self._annotations_awaiting_message = () + self._queue_reasoning_done_events() + self._queue_annotation_added_events(annotations) + + def _queue_annotation_added_events(self, annotations: Sequence[ChatCompletionAnnotation]) -> None: + if not self.sent_message_item_added_event: + self._queue_message_item_added_events() + item_id: Final = self._message_item_id() + response_annotations: Final = ( + LiteLLMCompletionResponsesConfig.transform_chat_completion_annotations_to_response_output_annotations( + annotations=annotations + ) + ) + self._pending_response_events.extend( + self._annotation_added_event(item_id, annotation) for annotation in response_annotations + ) + + def _message_item_id(self) -> str: + if self._cached_item_id is None: + self._cached_item_id = f"msg_{uuid.uuid4()}" + return self._cached_item_id + + def _annotation_added_event( + self, item_id: str, annotation: GenericResponseOutputItemContentAnnotation + ) -> OutputTextAnnotationAddedEvent: + event: Final = OutputTextAnnotationAddedEvent( + type=ResponsesAPIStreamEvents.OUTPUT_TEXT_ANNOTATION_ADDED, + item_id=item_id, + output_index=self._message_index(), + content_index=0, + annotation_index=self._annotation_index, + annotation=annotation.model_dump(), + ) + self._annotation_index += 1 + return event + def _transform_chat_completion_chunk_to_response_api_chunk( self, chunk: ModelResponseStream ) -> ResponsesAPIStreamingResponse | None: @@ -1310,37 +1389,9 @@ class LiteLLMCompletionStreamingIterator(ResponsesAPIStreamingIterator): This currently handles emitting the OutputTextDeltaEvent, which is used by other tools using the responses API and the ReasoningSummaryTextDeltaEvent, which is used by the responses API to emit reasoning content. - It also handles emitting annotation.added events when annotations are detected in the chunk. """ - if self._cached_item_id is None: - self._cached_item_id = f"msg_{uuid.uuid4()}" - item_id: Final = self._cached_item_id + item_id: Final = self._message_item_id() - # Check if this chunk has annotations first (before processing text/reasoning) - # This ensures we detect and queue annotation events from the annotation chunk - if chunk.choices and hasattr(chunk.choices[0].delta, "annotations"): - annotations: Final = chunk.choices[0].delta.annotations - if annotations and self.sent_annotation_events is False: - self.sent_annotation_events = True - # Store annotation events to emit them one by one - if not hasattr(self, "_pending_annotation_events"): - response_annotations = LiteLLMCompletionResponsesConfig.transform_chat_completion_annotations_to_response_output_annotations( - annotations=annotations - ) - self._pending_annotation_events = [] - for idx, annotation in enumerate(response_annotations): - annotation_dict = ( - annotation.model_dump() if hasattr(annotation, "model_dump") else dict(annotation) - ) - event = OutputTextAnnotationAddedEvent( - type=ResponsesAPIStreamEvents.OUTPUT_TEXT_ANNOTATION_ADDED, - item_id=item_id, - output_index=self._message_index(), - content_index=0, - annotation_index=idx, - annotation=annotation_dict, - ) - self._pending_annotation_events.append(event) # Priority 1: Handle reasoning content (highest priority) if ( chunk.choices @@ -1364,6 +1415,7 @@ class LiteLLMCompletionStreamingIterator(ResponsesAPIStreamingIterator): if delta_content: if not self.sent_message_item_added_event: self._queue_message_item_added_events() + self._hold_tool_calls_behind_text(getattr(chunk.choices[0].delta, "tool_calls", None)) self._sequence_number += 1 text_delta_event: Final = OutputTextDeltaEvent( type=ResponsesAPIStreamEvents.OUTPUT_TEXT_DELTA, @@ -1378,18 +1430,11 @@ class LiteLLMCompletionStreamingIterator(ResponsesAPIStreamingIterator): # Priority 3: Handle tool call deltas (if any) -> queue events and emit them # For each tool call delta, we emit events one at a time to match OpenAI's streaming behavior if chunk.choices and hasattr(chunk.choices[0].delta, "tool_calls") and chunk.choices[0].delta.tool_calls: - self._queue_tool_call_delta_events(chunk.choices[0].delta.tool_calls) + self._queue_tool_call_delta_events([*self._release_held_tool_calls(), *chunk.choices[0].delta.tool_calls]) # Return one pending tool event at a time if self._pending_tool_events: return self._pending_tool_events.pop(0) - # Priority 4: If we have pending annotation events, emit the next one - # This happens when the current chunk has no text/reasoning content - if hasattr(self, "_pending_annotation_events") and self._pending_annotation_events: - event = self._pending_annotation_events.pop(0) - return event - - # Priority 5: If we have pending tool events (from earlier chunk), emit the next one if self._pending_tool_events: return self._pending_tool_events.pop(0) @@ -1432,7 +1477,10 @@ class LiteLLMCompletionStreamingIterator(ResponsesAPIStreamingIterator): def _is_unstreamed_empty_message(self, item: object) -> bool: if getattr(item, "type", None) != "message" or self._message_output_index is not None: return False - return not any(getattr(part, "text", None) for part in attribute_items(item, "content")) + return not any( + getattr(part, "text", None) or getattr(part, "annotations", None) + for part in attribute_items(item, "content") + ) def finished_round_event(self) -> ResponseCompletedEvent | ResponseIncompleteEvent | None: if not isinstance(self.litellm_model_response, ModelResponse): diff --git a/litellm/responses/litellm_completion_transformation/tool_search.py b/litellm/responses/litellm_completion_transformation/tool_search.py index 780a23e02b2..5a1b27f9092 100644 --- a/litellm/responses/litellm_completion_transformation/tool_search.py +++ b/litellm/responses/litellm_completion_transformation/tool_search.py @@ -1,4 +1,5 @@ from collections.abc import Iterable, Iterator, Mapping, Sequence, Set +from dataclasses import dataclass from typing import TYPE_CHECKING, Final, Literal, TypeAlias from pydantic import ConfigDict, TypeAdapter, ValidationError @@ -18,25 +19,31 @@ if TYPE_CHECKING: __all__ = [ "ANTHROPIC_TOOL_SEARCH_TOOL_NAME", "ANTHROPIC_TOOL_SEARCH_TOOL_TYPE", + "CLIENT_TOOL_SEARCH_FUNCTION_NAME", "CompletionRoute", "ToolSearchCallStatus", + "ToolSearchExecution", + "ToolSearchRouting", "answers_tool_search", "anthropic_tool_search_chat_tool", "build_tool_search_call", "chat_config_builds_anthropic_request", "chat_messages_without_tool_search_calls", "chat_route_rejects_unanswered_tool_calls", + "has_client_tool_search", "has_server_tool_search", "holds_tool_search_use", "input_without_unanswered_anthropic_tool_search_calls", "is_anthropic_tool_search_chat_tool", "is_anthropic_tool_search_use", + "is_client_tool_search_tool", "is_openai_tool_search_tool", "is_server_tool_search_tool", "provider_builds_anthropic_request", "provider_chat_config", "runs_tool_search_on_the_server", "tool_search_call_ids", + "tool_search_routing", "tools_with_anthropic_tool_search_mapped", "tools_without_anthropic_tool_search", "unanswered_tool_search_call_ids", @@ -46,7 +53,9 @@ __all__ = [ ANTHROPIC_TOOL_SEARCH_TOOL_TYPE: Final = "tool_search_tool_regex_20251119" ANTHROPIC_TOOL_SEARCH_TOOL_NAME: Final = "tool_search_tool_regex" +CLIENT_TOOL_SEARCH_FUNCTION_NAME: Final = "tool_search" ToolSearchCallStatus: TypeAlias = Literal["in_progress", "completed", "incomplete"] +ToolSearchExecution: TypeAlias = Literal["server", "client"] _ARGUMENTS_ADAPTER: Final = TypeAdapter(dict[str, object]) _MESSAGE_FIELDS_ADAPTER: Final = TypeAdapter(Mapping[str, object]) @@ -79,6 +88,35 @@ def has_server_tool_search(tools: Sequence[object] | None) -> bool: return any(is_server_tool_search_tool(tool) for tool in tools or ()) +def is_client_tool_search_tool(tool: object) -> bool: + try: + parsed: Final = _ToolSearchFields.model_validate(tool) + except ValidationError: + return False + return parsed.type == "tool_search" and parsed.execution == "client" + + +def has_client_tool_search(tools: Sequence[object] | None) -> bool: + return any(is_client_tool_search_tool(tool) for tool in tools or ()) + + +@dataclass(frozen=True, slots=True) +class ToolSearchRouting: + server: bool + client: bool + + def execution_of(self, tool_id: str, tool_name: str) -> ToolSearchExecution | None: + if self.server and is_anthropic_tool_search_use(tool_id, tool_name): + return "server" + if self.client and tool_name == CLIENT_TOOL_SEARCH_FUNCTION_NAME: + return "client" + return None + + +def tool_search_routing(tools: Sequence[object] | None) -> ToolSearchRouting: + return ToolSearchRouting(server=has_server_tool_search(tools), client=has_client_tool_search(tools)) + + def anthropic_tool_search_chat_tool() -> AnthropicToolSearchToolRegex: return AnthropicToolSearchToolRegex(type=ANTHROPIC_TOOL_SEARCH_TOOL_TYPE, name=ANTHROPIC_TOOL_SEARCH_TOOL_NAME) @@ -346,13 +384,18 @@ def _parsed_arguments(arguments_json: str) -> Mapping[str, object] | None: return None -def build_tool_search_call(tool_id: str, arguments_json: str, status: ToolSearchCallStatus) -> OutputToolSearchCall: +def build_tool_search_call( + tool_id: str, + arguments_json: str, + status: ToolSearchCallStatus, + execution: ToolSearchExecution = "server", +) -> OutputToolSearchCall: arguments: Final = _parsed_arguments(arguments_json) return OutputToolSearchCall( id=openai_shaped_tool_call_item_id("tool_search_call", tool_id), call_id=tool_id, arguments={} if arguments is None else arguments, - execution="server", + execution=execution, status="incomplete" if arguments is None else status, type="tool_search_call", ) diff --git a/litellm/responses/litellm_completion_transformation/transformation.py b/litellm/responses/litellm_completion_transformation/transformation.py index bc92bc9cb3a..ce8841c9190 100644 --- a/litellm/responses/litellm_completion_transformation/transformation.py +++ b/litellm/responses/litellm_completion_transformation/transformation.py @@ -64,6 +64,7 @@ from litellm.llms.snowflake.chat.transformation import is_snowflake_claude_model from litellm.responses.bridge_check import chat_target_accepts_reasoning_summary from litellm.responses.litellm_completion_transformation.session_handler import ( ResponsesSessionHandler, + StoredTurns, ) from litellm.types.llms.anthropic import AnthropicToolSearchToolRegex from litellm.types.llms.base import CachedTokensDetails @@ -124,6 +125,7 @@ from litellm.types.utils import ( Usage, ) +from .client_tool_search import client_tool_search_chat_tool from .compaction_items import ( carries_only_compaction, compaction_output_item, @@ -151,16 +153,17 @@ from .custom_tools import ( from .reasoning_items import decode_thinking_blocks, encode_thinking_blocks, mint_reasoning_item_id from .tool_search import ( CompletionRoute, + ToolSearchRouting, answers_tool_search, anthropic_tool_search_chat_tool, build_tool_search_call, has_server_tool_search, holds_tool_search_use, is_anthropic_tool_search_chat_tool, - is_anthropic_tool_search_use, is_server_tool_search_tool, provider_builds_anthropic_request, tool_search_call_ids, + tool_search_routing, without_tool_search_calls, without_tool_search_uses, ) @@ -321,7 +324,7 @@ def _responses_file_part(item: Mapping[str, object]) -> _ResponsesFilePart: ) -def _decode_responses_media(item: Mapping[str, object]) -> _ResponsesMediaPart | None: +def decode_responses_media(item: Mapping[str, object]) -> _ResponsesMediaPart | None: kind: Final = item.get("type") if kind in ("input_image", "image_url", "computer_screenshot") and any(key in item for key in ("image_url", "url")): image: Final = _responses_image_part(item) @@ -383,6 +386,52 @@ def _attribute_fields(value: object) -> dict[str, object]: return dict(cast("Iterable[tuple[str, object]]", value)) # cast-ok: dict() raises on non-pair values, as before +def tool_output_to_chat_content( + output: object, +) -> str | list[ToolMessageContentPart]: + if output is None: + return "" + if isinstance(output, str): + return output + + single_media: Final = decode_responses_media(output) if isinstance(output, Mapping) else None + if single_media is not None: + return [single_media] + if isinstance(output, list): + normalized_blocks: Final[list[ToolMessageContentPart]] = [] + text_acc: Final[list[str]] = [] + for part in output: + if not isinstance(part, dict): + continue + part_type = part.get("type") + if part_type in ("input_text", "output_text", "text"): + txt = part.get("text") + if isinstance(txt, str) and txt: + text_acc.append(txt) + normalized_blocks.append({"type": "text", "text": txt}) + elif (media := decode_responses_media(part)) is not None: + normalized_blocks.append(media) + + if any(b.get("type") != "text" for b in normalized_blocks): + return normalized_blocks + if text_acc: + return "".join(text_acc) + try: + return json.dumps(output) + except Exception: + return str(output) + + try: + return json.dumps(output) + except Exception: + return str(output) + + +TOOL_CALL_OUTPUT_ITEM_TYPES: Final = frozenset( + {"function_call_output", "custom_tool_call_output", "computer_call_output", "tool_result"} +) + + def _input_item_role(input_item: Mapping[str, object]) -> str: return cast(str, input_item.get("role") or "user") # cast-ok: client-supplied role forwarded verbatim, unvalidated @@ -1296,6 +1345,7 @@ class LiteLLMCompletionResponsesConfig: request_kwargs: Mapping[str, object] = MappingProxyType({}), previous_response_client_ids: tuple[str, ...] = (), input_replaces_history: bool = False, + stored_turns: StoredTurns | None = None, ) -> dict[str, object]: """ Async hook to get the chain of previous input and output pairs and return a list of Chat Completion messages @@ -1311,6 +1361,7 @@ class LiteLLMCompletionResponsesConfig: ResponsesSessionHandler.get_chat_completion_message_history_for_previous_response_id, item_cache_control=keeps_item_marks, client_response_ids=previous_response_client_ids, + stored_turns=stored_turns, ) chat_completion_session: Final = ( await lookup(previous_response_id) @@ -2371,12 +2422,7 @@ class LiteLLMCompletionResponsesConfig: """ Check if the input item is a tool call output """ - return input_item.get("type") in [ - "function_call_output", - "custom_tool_call_output", - "computer_call_output", - "tool_result", # Anthropic/MCP format - ] + return input_item.get("type") in TOOL_CALL_OUTPUT_ITEM_TYPES @staticmethod def _is_input_item_function_call(input_item: Mapping[str, object]) -> bool: @@ -2400,58 +2446,7 @@ class LiteLLMCompletionResponsesConfig: if not call_id: return [] - def _normalize_function_call_output_to_tool_content( - output: object, - ) -> str | list[ToolMessageContentPart]: - """ - Preserve structured media for downstream chat adapters and token estimation. - Text-only outputs retain their existing string representation. - """ - if output is None: - return "" - if isinstance(output, str): - return output - - single_media: Final = _decode_responses_media(output) if isinstance(output, Mapping) else None - if single_media is not None: - return [single_media] - # Some adapters represent tool output as a list of "input_*" parts - if isinstance(output, list): - normalized_blocks: Final[list[ToolMessageContentPart]] = [] - text_acc: Final[list[str]] = [] - for part in output: - if not isinstance(part, dict): - continue - part_type = part.get("type") - if part_type in ("input_text", "output_text", "text"): - txt = part.get("text") - if isinstance(txt, str) and txt: - text_acc.append(txt) - normalized_blocks.append({"type": "text", "text": txt}) - elif (media := _decode_responses_media(part)) is not None: - normalized_blocks.append(media) - - if any(b.get("type") != "text" for b in normalized_blocks): - return normalized_blocks - if text_acc: - return "".join(text_acc) - try: - # last resort: keep something meaningful for providers that require a string - import json as _json - - return _json.dumps(output) - except Exception: - return str(output) - - # Fallback for dict/number/etc. - try: - import json as _json - - return _json.dumps(output) - except Exception: - return str(output) - - tool_content: Final = _normalize_function_call_output_to_tool_content(tool_call_output.get("output")) + tool_content: Final = tool_output_to_chat_content(tool_call_output.get("output")) output_cache_control: Final = _input_item_cache_control(tool_call_output) tool_output_message: Final = ( ChatCompletionToolMessage(role="tool", content=tool_content, tool_call_id=str(call_id)) @@ -2606,7 +2601,7 @@ class LiteLLMCompletionResponsesConfig: content_list.append(item) elif isinstance(item, dict): if ( - media := _decode_responses_media( + media := decode_responses_media( fields := _validate_responses_media(_STR_KEY_DICT_ADAPTER, item) ) ) is not None: @@ -2828,9 +2823,11 @@ class LiteLLMCompletionResponsesConfig: if tool_type == "custom": converted: Final = convert_custom_tool_to_function_tool(tool) return ResponsesToolChatForm(chat_tools=() if converted is None else (converted,), web_search_options=None) - if tool_type == "tool_search" and validated_tool_search_execution(tool.get("execution")) != "client": + if tool_type == "tool_search" and validated_tool_search_execution(tool.get("execution")) == "client": + return ResponsesToolChatForm(chat_tools=(client_tool_search_chat_tool(tool),), web_search_options=None) + if tool_type == "tool_search": return ResponsesToolChatForm(chat_tools=(anthropic_tool_search_chat_tool(),), web_search_options=None) - if tool_type in ("computer_use", "image_generation", "local_shell", "shell", "tool_search"): + if tool_type in ("computer_use", "image_generation", "local_shell", "shell"): verbose_logger.warning( "Dropping Responses API tool of type '%s': it has no Chat Completions " "equivalent and the target provider would reject the request.", @@ -2970,7 +2967,7 @@ class LiteLLMCompletionResponsesConfig: request_tools: Final = responses_api_request.get("tools") if responses_api_request is not None else None custom_tool_names: Final = extract_custom_tool_names(request_tools) namespace_tool_names: Final = LiteLLMCompletionResponsesConfig.namespace_tool_name_map(request_tools) - tool_search_requested: Final = has_server_tool_search(request_tools) + tool_search: Final = tool_search_routing(request_tools) web_search_calls: Final = LiteLLMCompletionResponsesConfig._web_search_calls_by_call_id( chat_completion_response @@ -2987,7 +2984,7 @@ class LiteLLMCompletionResponsesConfig: if ( server_tool_call := LiteLLMCompletionResponsesConfig._server_tool_call_item( - tool_id, tool_name, tool_arguments, web_search_calls, tool_search_requested + tool_id, tool_name, tool_arguments, web_search_calls, tool_search ) ) is not None: responses_tools.append(server_tool_call) @@ -3052,14 +3049,15 @@ class LiteLLMCompletionResponsesConfig: tool_name: str, tool_arguments: str, web_search_calls: Mapping[str, ResponseFunctionWebSearch], - tool_search_requested: bool, + tool_search: ToolSearchRouting, ) -> ResponseFunctionWebSearch | OutputToolSearchCall | None: web_search_call: Final = web_search_calls.get(tool_id) if web_search_call is not None: return web_search_call - if tool_search_requested and is_anthropic_tool_search_use(tool_id, tool_name): - return build_tool_search_call(tool_id, tool_arguments, "completed") - return None + execution: Final = tool_search.execution_of(tool_id, tool_name) + if execution is None: + return None + return build_tool_search_call(tool_id, tool_arguments, "completed", execution) @staticmethod def _web_search_calls_by_call_id( @@ -3565,7 +3563,7 @@ class LiteLLMCompletionResponsesConfig: choice=choice, ) message_output_items.extend(image_generation_items) - elif choice.message.content is not None: + elif choice.message.content is not None or getattr(choice.message, "annotations", None): message_output_items.append( GenericResponseOutputItem( type="message", @@ -3639,13 +3637,13 @@ class LiteLLMCompletionResponsesConfig: return OutputText( type="output_text", - text=message.content, + text=message.content or "", annotations=transformed_annotations, ) @staticmethod def transform_chat_completion_annotations_to_response_output_annotations( - annotations: list[ChatCompletionAnnotation] | None, + annotations: Sequence[ChatCompletionAnnotation] | None, ) -> list[GenericResponseOutputItemContentAnnotation]: response_output_annotations: Final[list[GenericResponseOutputItemContentAnnotation]] = [] diff --git a/litellm/responses/main.py b/litellm/responses/main.py index 8451834eab2..5bed6037fa4 100644 --- a/litellm/responses/main.py +++ b/litellm/responses/main.py @@ -106,7 +106,17 @@ if TYPE_CHECKING: else: MCPTool = Any -from .streaming_iterator import BaseResponsesAPIStreamingIterator +from .retrieve_stream_query import ( + RETRIEVE_INCLUDE_QUERY_KEYS, + InvalidRetrieveStreamQuery, + RetrieveStreamQuery, + parse_retrieve_stream_query, +) +from .streaming_iterator import ( + BaseResponsesAPIStreamingIterator, + ResponsesAPIStreamingIterator, + SyncResponsesAPIStreamingIterator, +) __all__ = ( "acancel_responses", @@ -192,6 +202,7 @@ def mock_responses_api_response( _STR_MAPPING: Final = TypeAdapter(Mapping[str, object]) +_STR_DICT: Final = TypeAdapter(dict[str, object]) _FORWARDED_VALUE: Final = TypeAdapter(object) @@ -2013,6 +2024,53 @@ def delete_responses( ) +def _requested_retrieve_stream_query( + stream: bool | None, + starting_after: int | None, + extra_query: Mapping[str, object] | None, + custom_llm_provider: str | None, + drop_malformed: bool, +) -> RetrieveStreamQuery: + explicit: Final = { + key: value for key, value in (("stream", stream), ("starting_after", starting_after)) if value is not None + } + requested: Final = {**explicit, **(extra_query or {})} + parsed: Final = parse_retrieve_stream_query( + requested.get("stream"), requested.get("starting_after"), drop_malformed=drop_malformed + ) + if isinstance(parsed, InvalidRetrieveStreamQuery): + raise litellm.BadRequestError( + message=parsed.message, + model=None, + llm_provider=custom_llm_provider, + body={"message": parsed.message, "type": "invalid_request_error", "param": parsed.param}, + ) + return parsed + + +def _supported_retrieve_stream_query( + requested: RetrieveStreamQuery, + responses_api_provider_config: BaseResponsesAPIConfig, + custom_llm_provider: str, + drop_params: object, +) -> RetrieveStreamQuery: + if not requested.stream: + return RetrieveStreamQuery(stream=False, starting_after=None) + if responses_api_provider_config.supports_streamed_retrieval(): + return requested + if drops_unsupported_params(drop_params): + return RetrieveStreamQuery(stream=False, starting_after=None) + raise UnsupportedParamsError( + status_code=400, + llm_provider=custom_llm_provider, + message=( + f"{custom_llm_provider} does not support streaming a stored response (stream=true on " + "GET /v1/responses/{response_id}). To drop it, set `litellm.drop_params=True` or for proxy:\n\n" + "`litellm_settings:\n drop_params: true`\n" + ), + ) + + @client async def aget_responses( response_id: str, @@ -2024,8 +2082,10 @@ async def aget_responses( timeout: float | httpx.Timeout | None = None, # LiteLLM specific params, custom_llm_provider: str | None = None, + stream: bool | None = None, + starting_after: int | None = None, **kwargs, -) -> ResponsesAPIResponse: +) -> ResponsesAPIResponse | BaseResponsesAPIStreamingIterator: """ Async: Fetch a response by its ID. @@ -2058,6 +2118,8 @@ async def aget_responses( extra_query=extra_query, extra_body=extra_body, timeout=timeout, + stream=stream, + starting_after=starting_after, **kwargs, ) @@ -2071,7 +2133,7 @@ async def aget_responses( response = init_response # Update the responses_api_response_id with the model_id - if not isinstance(response, ResponsesAPIResponse): # pyright: ignore[reportUnnecessaryIsInstance] # handlers can return non-ResponsesAPIResponse objects at runtime + if not isinstance(response, ResponsesAPIResponse): return response return ResponsesAPIRequestUtils.update_responses_api_response_id_with_model_id( responses_api_response=response, @@ -2101,8 +2163,14 @@ def get_responses( timeout: float | httpx.Timeout | None = None, # LiteLLM specific params, custom_llm_provider: str | None = None, + stream: bool | None = None, + starting_after: int | None = None, **kwargs, -) -> ResponsesAPIResponse | Coroutine[object, object, ResponsesAPIResponse]: +) -> ( + ResponsesAPIResponse + | SyncResponsesAPIStreamingIterator + | Coroutine[object, object, ResponsesAPIResponse | ResponsesAPIStreamingIterator] +): """ Fetch a response by its ID. @@ -2146,6 +2214,20 @@ def get_responses( if responses_api_provider_config is None: raise ValueError(f"GET responses is not supported for {custom_llm_provider}") + stream_query: Final = _supported_retrieve_stream_query( + requested=_requested_retrieve_stream_query( + stream=stream, + starting_after=starting_after, + extra_query=extra_query, + custom_llm_provider=custom_llm_provider, + drop_malformed=drops_unsupported_params(litellm_params.drop_params), + ), + responses_api_provider_config=responses_api_provider_config, + custom_llm_provider=custom_llm_provider, + drop_params=litellm_params.drop_params, + ) + litellm_metadata: Final = _STR_DICT.validate_python(kwargs.get("litellm_metadata") or {}) + local_vars.update(kwargs) # Pre Call logging @@ -2169,7 +2251,13 @@ def get_responses( litellm_params=litellm_params, logging_obj=litellm_logging_obj, extra_headers=extra_headers, + extra_query={ + key: value for key, value in (extra_query or {}).items() if key in RETRIEVE_INCLUDE_QUERY_KEYS + }, extra_body=extra_body, + stream=stream_query.stream, + starting_after=stream_query.starting_after, + litellm_metadata=litellm_metadata, timeout=timeout or request_timeout, _is_async=_is_async, client=kwargs.get("client"), @@ -2180,7 +2268,7 @@ def get_responses( if isinstance(response, ResponsesAPIResponse): response = ResponsesAPIRequestUtils.update_responses_api_response_id_with_model_id( responses_api_response=response, - litellm_metadata=kwargs.get("litellm_metadata", {}), + litellm_metadata=litellm_metadata, custom_llm_provider=custom_llm_provider, ) @@ -2341,6 +2429,7 @@ async def acancel_responses( timeout: float | httpx.Timeout | None = None, # LiteLLM specific params, custom_llm_provider: str | None = None, + litellm_metadata: Mapping[str, object] | None = None, **kwargs, ) -> ResponsesAPIResponse: """ @@ -2365,6 +2454,7 @@ async def acancel_responses( cancel_responses, response_id=response_id, custom_llm_provider=custom_llm_provider, + litellm_metadata=litellm_metadata, extra_headers=extra_headers, extra_query=extra_query, extra_body=extra_body, @@ -2380,7 +2470,12 @@ async def acancel_responses( response = await init_response else: response = init_response - return response + + return ResponsesAPIRequestUtils.update_responses_api_response_id_with_model_id( + responses_api_response=response, + litellm_metadata=litellm_metadata, + custom_llm_provider=custom_llm_provider, + ) except Exception as e: raise litellm.exception_type( model=None, @@ -2402,6 +2497,7 @@ def cancel_responses( timeout: float | httpx.Timeout | None = None, # LiteLLM specific params, custom_llm_provider: str | None = None, + litellm_metadata: Mapping[str, object] | None = None, **kwargs, ) -> ResponsesAPIResponse | Coroutine[object, object, ResponsesAPIResponse]: """ @@ -2471,7 +2567,13 @@ def cancel_responses( shared_session=kwargs.get("shared_session"), ) - return response + if not isinstance(response, ResponsesAPIResponse): + return response + return ResponsesAPIRequestUtils.update_responses_api_response_id_with_model_id( + responses_api_response=response, + litellm_metadata=litellm_metadata, + custom_llm_provider=custom_llm_provider, + ) except Exception as e: raise litellm.exception_type( model=None, diff --git a/litellm/responses/retrieve_stream_query.py b/litellm/responses/retrieve_stream_query.py new file mode 100644 index 00000000000..086aa39efc6 --- /dev/null +++ b/litellm/responses/retrieve_stream_query.py @@ -0,0 +1,83 @@ +from collections.abc import Mapping +from dataclasses import dataclass +from typing import Final, Literal + +from pydantic import TypeAdapter + +RETRIEVE_STREAM_QUERY_KEYS: Final = frozenset({"stream", "starting_after"}) +RETRIEVE_INCLUDE_QUERY_KEYS: Final = frozenset({"include", "include[]", "include_obfuscation"}) +_QUERY_ADAPTER: Final = TypeAdapter(Mapping[str, object]) +_MAX_STARTING_AFTER_DIGITS: Final = len(str(2**63 - 1)) + + +@dataclass(frozen=True, slots=True) +class RetrieveStreamQuery: + stream: bool + starting_after: int | None + + +@dataclass(frozen=True, slots=True) +class InvalidRetrieveStreamQuery: + param: Literal["stream", "starting_after"] + message: str + + +_NO_STREAM: Final = RetrieveStreamQuery(stream=False, starting_after=None) +_FULL_REPLAY: Final = RetrieveStreamQuery(stream=True, starting_after=None) + + +def _parsed_stream(value: object) -> bool | InvalidRetrieveStreamQuery: + match value: + case None: + return False + case bool(): + return value + case str() if value.lower() in ("true", "false"): + return value.lower() == "true" + case _: + return InvalidRetrieveStreamQuery("stream", f"Invalid 'stream': expected true or false, got {value!r}") + + +def _parsed_starting_after(value: object) -> int | None | InvalidRetrieveStreamQuery: + match value: + case None: + return None + case int() if not isinstance(value, bool) and value >= 0: + return value + case str() if value.isascii() and value.isdigit() and len(value) <= _MAX_STARTING_AFTER_DIGITS: + return int(value) + case _: + return InvalidRetrieveStreamQuery( + "starting_after", f"Invalid 'starting_after': expected an integer >= 0, got {value!r}" + ) + + +def parse_retrieve_stream_query( + stream: object, starting_after: object, drop_malformed: bool +) -> RetrieveStreamQuery | InvalidRetrieveStreamQuery: + parsed_stream: Final = _parsed_stream(stream) + if isinstance(parsed_stream, InvalidRetrieveStreamQuery): + return _NO_STREAM if drop_malformed else parsed_stream + if not parsed_stream: + return _NO_STREAM + parsed_starting_after: Final = _parsed_starting_after(starting_after) + if isinstance(parsed_starting_after, InvalidRetrieveStreamQuery): + return _FULL_REPLAY if drop_malformed else parsed_starting_after + return RetrieveStreamQuery(stream=True, starting_after=parsed_starting_after) + + +def requests_streamed_retrieval(request: Mapping[str, object]) -> bool: + extra_query: Final = request.get("extra_query") + return ( + "response_id" in request + and isinstance(extra_query, Mapping) + and _parsed_stream(_QUERY_ADAPTER.validate_python(extra_query).get("stream")) is True + ) + + +def without_retrieve_stream_defaults( + deployment_params: Mapping[str, object], request: Mapping[str, object] +) -> Mapping[str, object]: + if "response_id" not in request: + return deployment_params + return {key: value for key, value in deployment_params.items() if key not in RETRIEVE_STREAM_QUERY_KEYS} diff --git a/litellm/responses/streaming_iterator.py b/litellm/responses/streaming_iterator.py index 50ab3e4f75a..8959c32fff2 100644 --- a/litellm/responses/streaming_iterator.py +++ b/litellm/responses/streaming_iterator.py @@ -39,9 +39,17 @@ from litellm.constants import ( ) from litellm.exceptions import MidStreamFallbackError, RateLimitError from litellm.litellm_core_utils.asyncify import run_async_function -from litellm.litellm_core_utils.core_helpers import process_response_headers +from litellm.litellm_core_utils.core_helpers import ( + process_response_headers, + provider_reported_usage_cost, + set_response_cost_in_hidden_params, +) from litellm.litellm_core_utils.exception_mapping_utils import with_deployment_api_base -from litellm.litellm_core_utils.internal_call_metadata import without_budget_reservation +from litellm.litellm_core_utils.internal_call_metadata import ( + is_background_response, + requests_background, + without_budget_reservation, +) from litellm.litellm_core_utils.litellm_logging import BilledRoundsSpend from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj from litellm.litellm_core_utils.llm_response_utils.get_api_base import get_api_base @@ -63,9 +71,10 @@ from litellm.types.llms.openai import ( ResponsesAPIResponse, ResponsesAPIStreamEvents, ResponsesAPIStreamingResponse, + replayable_responses_input, ) from litellm.types.responses.main import GenericResponseOutputItem, OutputText -from litellm.types.utils import CallTypes +from litellm.types.utils import CallTypes, ModelResponse from litellm.utils import async_post_call_success_deployment_hook if TYPE_CHECKING: @@ -288,7 +297,7 @@ def stream_error_status_and_message(error_obj: object) -> tuple[int, str]: return _status_code_for_error_fields(error_type, error_code), message -def _map_stream_error_to_exception( +def map_stream_error_to_exception( error_obj: object, model: str, custom_llm_provider: str, @@ -365,7 +374,9 @@ class BaseResponsesAPIStreamingIterator: """ _pending_logging_tasks: tuple[asyncio.Task[object], ...] = () + _started_tool_call: bool = False _earlier_rounds_spend: BilledRoundsSpend | None = None + _replays_stored_stream: bool = False def __init__( self, @@ -488,12 +499,16 @@ class BaseResponsesAPIStreamingIterator: _args_delta: Final = getattr(openai_responses_api_chunk, "delta", None) if isinstance(_args_delta, str): self._generated_tool_arguments += _args_delta + if _event_type in _CLIENT_RUN_TOOL_ARGUMENTS_DELTA_EVENTS: + self._started_tool_call = True _stream_model_id: Final = _model_id_from_metadata(self.litellm_metadata) if _event_type in ( ResponsesAPIStreamEvents.OUTPUT_ITEM_ADDED, ResponsesAPIStreamEvents.OUTPUT_ITEM_DONE, ): _item: Final[object] = getattr(openai_responses_api_chunk, "item", None) + if getattr(_item, "type", None) in _CLIENT_RUN_TOOL_CALL_ITEM_TYPES: + self._started_tool_call = True if _item is not None: ResponsesAPIRequestUtils.encode_container_id_on_output_item( item=_item, @@ -560,7 +575,7 @@ class BaseResponsesAPIStreamingIterator: openai_types.ResponsesAPIStreamEvents.RESPONSE_FAILED, ): _response_obj: Final[object] = getattr(openai_responses_api_chunk, "response", None) - _estimate_wanted: Final[bool] = _chunk_type in ( + _estimate_wanted: Final[bool] = not self._replays_stored_stream and _chunk_type in ( openai_types.ResponsesAPIStreamEvents.RESPONSE_COMPLETED, openai_types.ResponsesAPIStreamEvents.RESPONSE_INCOMPLETE, ) @@ -573,6 +588,7 @@ class BaseResponsesAPIStreamingIterator: self.request_data.get("input"), self.request_data, self._generated_content + self._generated_tool_arguments, + use_default_image_token_count=False, ) if _estimate_wanted else None @@ -726,7 +742,7 @@ class BaseResponsesAPIStreamingIterator: self._earlier_rounds_spend = earlier def _map_error_event_exception(self, error_obj: object) -> Exception: - return _map_stream_error_to_exception( + return map_stream_error_to_exception( error_obj, self.model or "", self.custom_llm_provider or "", @@ -976,6 +992,40 @@ class BaseResponsesAPIStreamingIterator: except Exception: pass + def _record_partial_usage_for_failure(self) -> None: + generated_text: Final = self._generated_content + self._generated_tool_arguments + if ( + not generated_text + or self._replays_stored_stream + or requests_background(self.request_data) + or is_background_response(self._created_response) + or self._completed_response_logged + or self.logging_obj.model_call_details.get("combined_usage_object") is not None + ): + return + estimate: Final = _estimate_usage_safely( + self.model or "", + self.request_data.get("input"), + self.request_data, + generated_text, + use_default_image_token_count=True, + ) + if estimate is None: + return + usage: Final = ResponseAPILoggingUtils._transform_response_api_usage_to_chat_usage( # pyright: ignore[reportPrivateUsage] # same shared transform the success path above uses + estimate + ) + served_tier: Final[object] = getattr(self._created_response, "service_tier", None) + assembled: Final = ModelResponse( + model=self.model, usage=usage, service_tier=served_tier if isinstance(served_tier, str) else None + ) + if self._earlier_rounds_spend is None: + self.logging_obj.record_assembled_response_for_failure(assembled) + return + self.logging_obj.record_failure_after_earlier_rounds( + self._earlier_rounds_spend, usage, self.logging_obj.response_cost_calculator(result=assembled) or 0.0 + ) + def _handle_failure(self, exception: Exception): """ Trigger failure handlers before bubbling the exception. @@ -985,6 +1035,7 @@ class BaseResponsesAPIStreamingIterator: if self._failure_handled: return self._failure_handled = True + self._record_partial_usage_for_failure() traceback_exception: Final = traceback.format_exc() end_time: Final = datetime.now() @@ -1044,21 +1095,31 @@ class BaseResponsesAPIStreamingIterator: if pending: await asyncio.wait(pending) + @property + def started_tool_call(self) -> bool: + """Whether the stream began a tool call, which a text continuation could never finish.""" + return self._started_tool_call + def partial_response_on_disconnect(self) -> ResponseIncompleteEvent | None: """ The response.incomplete event to bill when the client went away mid-stream, the same shape the success handler assembles for a natural end of stream. Its response is the response.created payload (it carries the served service_tier) plus the text and tool arguments relayed so far, with counted - usage since the provider never sent any. None when nothing was relayed yet - or the stream already reached its terminal event and billed itself. + usage since the provider never sent any. None when nothing was relayed yet, + the stream already reached its terminal event and billed itself, or its failure + log already billed the relayed output. """ created: Final = self._created_response generated: Final = self._generated_content + self._generated_tool_arguments - if self.completed_response is not None or created is None or not generated: + if self._replays_stored_stream or created is None or not generated or self._billed_without_disconnect(): return None usage: Final = _estimate_usage_safely( - self.model or "", self.request_data.get("input"), self.request_data, generated + self.model or "", + self.request_data.get("input"), + self.request_data, + generated, + use_default_image_token_count=False, ) if usage is None: return None @@ -1072,6 +1133,9 @@ class BaseResponsesAPIStreamingIterator: stamp_responses_usage_cost(partial, self.logging_obj) return ResponseIncompleteEvent(type=ResponsesAPIStreamEvents.RESPONSE_INCOMPLETE, response=partial) + def _billed_without_disconnect(self) -> bool: + return self.completed_response is not None or self._failure_handled + def _note_yielded_event(self, event: ResponsesAPIStreamingResponse) -> None: self._yielded_first_chunk = True if event.type not in PRE_OUTPUT_LIFECYCLE_EVENT_TYPES: @@ -1100,6 +1164,8 @@ class BaseResponsesAPIStreamingIterator: def _raise_if_ended_without_terminal_event(self) -> None: if self.completed_response is not None: return + if self._replays_stored_stream and not self._yielded_first_chunk: + return error: Final = self._stream_ended_early_error() self._handle_failure(error) if self._output_started: @@ -1147,6 +1213,7 @@ class ResponsesAPIStreamingIterator(BaseResponsesAPIStreamingIterator): custom_llm_provider: str | None = None, request_data: dict[str, object] | None = None, call_type: str | None = None, + replays_stored_stream: bool = False, ): super().__init__( response, @@ -1158,6 +1225,7 @@ class ResponsesAPIStreamingIterator(BaseResponsesAPIStreamingIterator): request_data, call_type, ) + self._replays_stored_stream = replays_stored_stream self.stream_iterator = SSEDecoder().aiter_bytes(response.aiter_bytes()) def __aiter__(self): @@ -1170,6 +1238,9 @@ class ResponsesAPIStreamingIterator(BaseResponsesAPIStreamingIterator): await self._await_pending_logging() raise + async def aclose(self) -> None: + await self.response.aclose() + async def _next_event(self) -> ResponsesAPIStreamingResponse: try: self._check_max_streaming_duration() @@ -1208,6 +1279,9 @@ class ResponsesAPIStreamingIterator(BaseResponsesAPIStreamingIterator): raise StopAsyncIteration from e self._raise_for_transport_error(e) except httpx.TimeoutException as e: + if self.completed_response is not None: + self.finished = True + raise StopAsyncIteration from e self._raise_for_transport_timeout(e) except httpx.HTTPError as e: # Handle HTTP errors @@ -1239,6 +1313,7 @@ class SyncResponsesAPIStreamingIterator(BaseResponsesAPIStreamingIterator): custom_llm_provider: str | None = None, request_data: dict[str, object] | None = None, call_type: str | None = None, + replays_stored_stream: bool = False, ): super().__init__( response, @@ -1250,11 +1325,15 @@ class SyncResponsesAPIStreamingIterator(BaseResponsesAPIStreamingIterator): request_data, call_type, ) + self._replays_stored_stream = replays_stored_stream self.stream_iterator = SSEDecoder().iter_bytes(response.iter_bytes()) def __iter__(self): return self + def close(self) -> None: + self.response.close() + def __next__(self): try: self._check_max_streaming_duration() @@ -1293,6 +1372,9 @@ class SyncResponsesAPIStreamingIterator(BaseResponsesAPIStreamingIterator): raise StopIteration from e self._raise_for_transport_error(e) except httpx.TimeoutException as e: + if self.completed_response is not None: + self.finished = True + raise StopIteration from e self._raise_for_transport_timeout(e) except httpx.HTTPError as e: # Handle HTTP errors @@ -1690,13 +1772,26 @@ def _usage_as_model(usage: object) -> ResponseAPIUsage | None: return None -_TOOL_ARGUMENTS_DELTA_EVENTS: Final = frozenset( +_CLIENT_RUN_TOOL_CALL_ITEM_TYPES: Final = frozenset( + { + "function_call", + "custom_tool_call", + "mcp_approval_request", + "computer_call", + "local_shell_call", + "shell_call", + "apply_patch_call", + } +) +_CLIENT_RUN_TOOL_ARGUMENTS_DELTA_EVENTS: Final = frozenset( { ResponsesAPIStreamEvents.FUNCTION_CALL_ARGUMENTS_DELTA, ResponsesAPIStreamEvents.CUSTOM_TOOL_CALL_INPUT_DELTA, - ResponsesAPIStreamEvents.MCP_CALL_ARGUMENTS_DELTA, } ) +_TOOL_ARGUMENTS_DELTA_EVENTS: Final = _CLIENT_RUN_TOOL_ARGUMENTS_DELTA_EVENTS | { + ResponsesAPIStreamEvents.MCP_CALL_ARGUMENTS_DELTA +} def _estimate_usage_from_text( @@ -1704,6 +1799,8 @@ def _estimate_usage_from_text( request_input: object, responses_api_request: Mapping[str, object], generated_text: str, + *, + use_default_image_token_count: bool = False, ) -> ResponseAPIUsage: messages: Final = LiteLLMCompletionResponsesConfig.transform_responses_api_input_to_messages( # pyright: ignore[reportUnknownMemberType] # the transformer's signature is partially untyped input=request_input, # pyright: ignore[reportArgumentType] # the raw Responses API input is a str or ResponseInputParam list, matching the helper's declared union @@ -1711,7 +1808,7 @@ def _estimate_usage_from_text( only_since_compaction=True, ) input_tokens: Final = litellm.token_counter( # pyright: ignore[reportUnknownMemberType] # token_counter's public signature is untyped - model=model, messages=messages + model=model, messages=messages, use_default_image_token_count=use_default_image_token_count ) output_tokens: Final = litellm.token_counter( # pyright: ignore[reportUnknownMemberType] # token_counter's public signature is untyped model=model, text=generated_text, count_response_tokens=True @@ -1728,6 +1825,8 @@ def _estimate_usage_safely( request_input: object, responses_api_request: Mapping[str, object], generated_text: str, + *, + use_default_image_token_count: bool, ) -> ResponseAPIUsage | None: try: return _estimate_usage_from_text( @@ -1735,6 +1834,7 @@ def _estimate_usage_safely( request_input=request_input, responses_api_request=responses_api_request, generated_text=generated_text, + use_default_image_token_count=use_default_image_token_count, ) except Exception as e: verbose_logger.debug("Could not estimate usage from stream text, billing $0: %s", e) @@ -1744,20 +1844,32 @@ def _estimate_usage_safely( def stamp_responses_usage_cost( response_obj: ResponsesAPIResponse | None, logging_obj: LiteLLMLoggingObj | None ) -> None: - if response_obj is None or logging_obj is None: + """The terminal response's ``usage.cost`` is the bill litellm writes to the spend row. It is priced on a copy + shaped the way the success handler shapes the spend row's result (the reported ``usage.cost`` in the + response-cost header, the usage in chat shape), so the client and the row read the same number.""" + if response_obj is None: return usage_obj: Final[ResponseAPIUsage | None] = _usage_as_model(getattr(response_obj, "usage", None)) if usage_obj is None: return - response_obj.usage = usage_obj # rebind-ok: the stamped cost has to ride on the response the client receives - if isinstance(getattr(usage_obj, "cost", None), (int, float)): + response_obj.usage = usage_obj # rebind-ok: the typed usage has to ride on the response the client receives + if logging_obj is None: return + priced: Final = response_obj.model_copy( + update={"usage": ResponseAPILoggingUtils.transform_response_api_usage_to_chat_usage(usage_obj)} + ) + priced.hidden_params = {} + set_response_cost_in_hidden_params( + priced, provider_reported_usage_cost(usage_obj, logging_obj.model_call_details.get("custom_llm_provider")) + ) try: - cost: Final[float | None] = logging_obj.response_cost_calculator(result=response_obj) - except Exception: + bill: Final = logging_obj.response_cost_calculator(result=priced) + except Exception: # noqa: BLE001 # a pricing failure leaves the client usage as the upstream sent it return - if isinstance(cost, (int, float)) and cost > 0: - setattr(usage_obj, "cost", cost) + if isinstance(bill, bool) or not isinstance(bill, (int, float)): + return + if bill > 0 or isinstance(getattr(usage_obj, "cost", None), (int, float)): + setattr(usage_obj, "cost", float(bill)) def opening_item_payload(payload: Mapping[str, object]) -> Mapping[str, object]: @@ -2253,7 +2365,7 @@ class _ResponsesWsTurn: ) if failed_event is None: return None - return _map_stream_error_to_exception( + return map_stream_error_to_exception( _ws_event_error(failed_event), model, custom_llm_provider, logging_obj=connection_logging_obj ) @@ -2268,15 +2380,17 @@ def _ws_event_error(event: Mapping[str, object]) -> object: return response.get("error") if _is_json_object(response) else None -def _restore_input_item_ids(items: Sequence[object]) -> Sequence[object]: - return ResponsesAPIRequestUtils.restore_encrypted_content_item_ids_in_input(copy.deepcopy(list(items))) +def _replayable_input_items(items: Sequence[object]) -> object: + return replayable_responses_input( + ResponsesAPIRequestUtils.restore_encrypted_content_item_ids_in_input(copy.deepcopy(list(items))) + ) def _restored_container_fields(container: Mapping[str, object]) -> Mapping[str, object]: input_items: Final = container.get("input") previous_response_id: Final = container.get("previous_response_id") restored: Final = { - "input": _restore_input_item_ids(input_items) if _is_json_array(input_items) else input_items, + "input": _replayable_input_items(input_items) if _is_json_array(input_items) else input_items, "previous_response_id": ( ResponsesAPIRequestUtils.decode_previous_response_id_to_original_previous_response_id(previous_response_id) if isinstance(previous_response_id, str) diff --git a/litellm/responses/utils.py b/litellm/responses/utils.py index a6b042a2234..05d6a36c1f6 100644 --- a/litellm/responses/utils.py +++ b/litellm/responses/utils.py @@ -1,8 +1,10 @@ import base64 +import os import re from collections.abc import Callable, Collection, Iterable, Mapping, Sequence from functools import reduce -from typing import Any, Final, Optional, TypeVar, Union, cast, get_type_hints, overload +from types import MappingProxyType +from typing import Any, Final, Optional, TypeVar, Union, cast, get_args, get_type_hints, overload from pydantic import BaseModel, TypeAdapter from typing_extensions import TypedDict as ExtraItemsTypedDict @@ -14,6 +16,7 @@ from litellm.litellm_core_utils.core_helpers import as_str_mapping, attribute_or from litellm.litellm_core_utils.dot_notation_indexing import delete_nested_value, is_nested_path from litellm.litellm_core_utils.get_provider_specific_headers import ProviderSpecificHeaderUtils from litellm.llms.base_llm.responses.transformation import BaseResponsesAPIConfig, ReasoningSummaryLevel +from litellm.llms.openai.chat.gpt_transformation import OpenAIGPTConfig from litellm.types.llms.openai import ( AllMessageValues, InputTokensDetails, @@ -29,6 +32,7 @@ from litellm.types.responses.main import DecodedResponseId from litellm.types.utils import ( CacheCreationTokenDetails, CompletionTokensDetailsWrapper, + ModelInfo, PromptTokensDetailsWrapper, ProviderSpecificHeader, SpecialEnums, @@ -399,7 +403,7 @@ class ResponsesAPIRequestUtils: def update_responses_api_response_id_with_model_id( responses_api_response: ResponsesAPIResponse, custom_llm_provider: str | None, - litellm_metadata: dict[str, object] | None = None, + litellm_metadata: Mapping[str, object] | None = None, ) -> ResponsesAPIResponse: ... @@ -408,7 +412,7 @@ class ResponsesAPIRequestUtils: def update_responses_api_response_id_with_model_id( responses_api_response: dict[str, object], custom_llm_provider: str | None, - litellm_metadata: dict[str, object] | None = None, + litellm_metadata: Mapping[str, object] | None = None, ) -> dict[str, object]: ... @@ -418,7 +422,7 @@ class ResponsesAPIRequestUtils: def update_responses_api_response_id_with_model_id( responses_api_response: ResponsesAPIResponse | dict[str, Any], custom_llm_provider: str | None, - litellm_metadata: dict[str, Any] | None = None, + litellm_metadata: Mapping[str, Any] | None = None, ) -> ResponsesAPIResponse | dict[str, object]: """Update the responses_api_response_id with model_id and custom_llm_provider. @@ -762,6 +766,12 @@ class ResponsesAPIRequestUtils: model_id=model_id, response_id=decoded_response_id, ) + except ValueError: + return DecodedResponseId( + custom_llm_provider=None, + model_id=None, + response_id=response_id, + ) except Exception as e: verbose_logger.debug("Error decoding response_id '%s': %s", response_id, e) return DecodedResponseId( @@ -1110,7 +1120,7 @@ class ResponsesAPIRequestUtils: def _update_container_ids_in_response( responses_api_response: ResponsesAPIResponse | dict[str, object], custom_llm_provider: str | None, - litellm_metadata: dict[str, Any] | None = None, + litellm_metadata: Mapping[str, Any] | None = None, ) -> ResponsesAPIResponse | dict[str, object]: """Encode container IDs in the response output with provider/model info. @@ -1382,3 +1392,98 @@ def auto_reasoning_summary(model: str, custom_llm_provider: object) -> Reasoning provider, model.removeprefix(f"{provider}/") ) return "detailed" if responses_config is None else responses_config.auto_reasoning_summary() + + +def opt_in_auto_reasoning_summary(model: str | None, custom_llm_provider: object) -> ReasoningSummaryLevel | None: + if not (litellm.reasoning_auto_summary or os.getenv("LITELLM_REASONING_AUTO_SUMMARY", "false").lower() == "true"): + return None + return "detailed" if model is None else auto_reasoning_summary(model, custom_llm_provider) + + +def reasoning_with_summary_default( + reasoning: Mapping[str, object], summary_alias: object, model: str, custom_llm_provider: object +) -> Mapping[str, object]: + if "summary" in reasoning: + return {**reasoning} + summary: Final = ( + summary_alias if summary_alias is not None else opt_in_auto_reasoning_summary(model, custom_llm_provider) + ) + return {**reasoning} if summary is None else {**reasoning, "summary": summary} + + +_SUMMARY_VALUES: Final = frozenset((*get_args(ReasoningSummaryLevel), None)) + + +def _openai_model_info(model: str) -> ModelInfo | None: + from litellm.utils import ModelInfoLookupMiss, lookup_model_info_for_registration + + model_info: Final = lookup_model_info_for_registration(model.removeprefix("responses/"), "openai") + return None if isinstance(model_info, ModelInfoLookupMiss) else model_info + + +def _declared_values(values: Sequence[str] | None) -> frozenset[str | None] | None: + return None if values is None else frozenset(values) + + +def _openai_reasoning_field_values(model: str) -> Mapping[str, frozenset[str | None] | None]: + model_info: Final = _openai_model_info(model) + if model_info is None: + return MappingProxyType({"summary": _SUMMARY_VALUES, "mode": None, "context": None}) + if not model_info.get("supports_reasoning"): + return MappingProxyType({}) + return MappingProxyType( + { + "summary": _SUMMARY_VALUES, + "mode": _declared_values(model_info.get("reasoning_modes")), + "context": _declared_values(model_info.get("reasoning_contexts")), + } + ) + + +def _openai_accepts_reasoning_field( + key: str, value: object, values_by_field: Mapping[str, frozenset[str | None] | None] +) -> bool: + if key == "effort": + return True + if key not in values_by_field: + return False + allowed: Final = values_by_field[key] + return allowed is None or (isinstance(value, str | None) and value in allowed) + + +def _openai_accepted_reasoning(reasoning: Mapping[str, object], model: str) -> Mapping[str, object]: + values_by_field: Final = _openai_reasoning_field_values(model) + return { + key: value for key, value in reasoning.items() if _openai_accepts_reasoning_field(key, value, values_by_field) + } + + +def _additional_drop_paths(additional_drop_params: object) -> tuple[str, ...]: + if additional_drop_params.__class__ is not list: + return () + return tuple(path for path in iter_items(additional_drop_params) if isinstance(path, str)) + + +def openai_bridge_reasoning( + *, + requested: Mapping[str, object], + effort_kept: bool, + summary_alias: object, + model: str, + drop_params: bool, + additional_drop_params: object, +) -> Mapping[str, object] | None: + drop_paths: Final = _additional_drop_paths(additional_drop_params) + if "reasoning_effort" in drop_paths: + return None + kept: Final = requested if effort_kept else {key: value for key, value in requested.items() if key != "effort"} + with_summary: Final = reasoning_with_summary_default(kept, summary_alias, model, "openai") + accepted: Final = ( + _openai_accepted_reasoning(with_summary, model) + if drop_params and OpenAIGPTConfig.is_openai_catalog_model(model) + else {**with_summary} + ) + remaining: Final = as_str_mapping( + _apply_nested_drop_params({"reasoning_effort": accepted}, list(drop_paths)).get("reasoning_effort") + ) + return remaining or None diff --git a/litellm/router.py b/litellm/router.py index c8153b596d6..3809a5d6555 100644 --- a/litellm/router.py +++ b/litellm/router.py @@ -7,6 +7,29 @@ # # Thank you ! We ❤️ you! - Krrish & Ishaan +""" +litellm.Router: load balancing, retries, fallbacks and cooldowns across deployments. + +Public surface. The router is moving behind a narrow interface; code outside +the router should end up using a Router through two kinds of members only: + +- endpoint methods (acompletion, aembedding, aresponses, aanthropic_messages, + the files, batches, assistants and vector store wrappers, ...), each a thin + wrapper around one call; +- entry points (being added) that replace direct access to internals: registry() for + deployment lookups, settings() for configuration reads, health() for + cooldowns, blocks and usage, select() to pick a deployment without calling + it, apply() for runtime changes, observe() for routing events, + register_plugin() for strategies and sub-routers, and retire() to release + the router. + +Everything else on the class is internal. The members outside code uses today +are listed in tests/code_coverage_tests/router_surface_allowlist.json, and a CI +check (router_surface_check.py next to it) fails on any new outside use, so the +list only shrinks while callers move to the entry points. The same interface +is documented for the Rust core in litellm-rust/crates/router-core. +""" + import asyncio import contextlib import copy @@ -85,6 +108,15 @@ from litellm.integrations.custom_logger import CustomLogger from litellm.integrations.otel.routing import routing_decision_attributes from litellm.integrations.otel.runtime import phase_attributes, phase_event, phase_span from litellm.litellm_core_utils.asyncify import run_async_function +from litellm.litellm_core_utils.batch_utils import ( + batch_create_routing, + deployment_supported_endpoints, + get_router_metadata_variable_name, + is_batch_retrieve_call_type, + replace_model_in_jsonl, + should_replace_model_in_jsonl, + without_deployments_that_cannot_batch, +) from litellm.litellm_core_utils.completion_timeout import CompletionTimeout from litellm.litellm_core_utils.core_helpers import ( coerce_token_limit, @@ -130,7 +162,11 @@ from litellm.litellm_core_utils.sensitive_data_masker import ( SensitiveDataMasker, mask_sensitive_structure, ) -from litellm.litellm_core_utils.token_counter import offload_token_count +from litellm.litellm_core_utils.token_counter import ( + offload_token_count, + served_openai_models, + single_encoding_openai_model, +) from litellm.litellm_core_utils.tool_fields import TOOL_FIELDS, drop_policy from litellm.llms.anthropic.common_utils import AnthropicModelInfo, anthropic_error_frame_exception from litellm.llms.base_llm.passthrough.transformation import replace_path_segment @@ -148,6 +184,16 @@ from litellm.llms.openai_like.model_info import ( get_openai_compatible_model_info, ) from litellm.responses.bridge_check import keep_registered_mode +from litellm.responses.retrieve_stream_query import requests_streamed_retrieval, without_retrieve_stream_defaults +from litellm.router_strategy.auto_router.auto_router_model_naming import ( + AUTO_ROUTER_MODEL_PREFIX, + STRATEGY_ROUTER_PARAM_FIELDS, + GatedAutoRouterCapability, + capability_limit_violation, + claimed_capabilities, + classify_strategy_router_model, + count_capability_routers, +) from litellm.router_strategy.base_routing_strategy import BaseRoutingStrategy from litellm.router_strategy.budget_limiter import RouterBudgetLimiting from litellm.router_strategy.complexity_router.context_compaction import ( @@ -187,24 +233,6 @@ from litellm.router_utils.add_retry_fallback_headers import ( replace_complexity_router_headers, response_total_token_count, ) -from litellm.router_utils.auto_router_model_naming import ( - AUTO_ROUTER_MODEL_PREFIX, - STRATEGY_ROUTER_PARAM_FIELDS, - GatedAutoRouterCapability, - capability_limit_violation, - claimed_capabilities, - classify_strategy_router_model, - count_capability_routers, -) -from litellm.router_utils.batch_utils import ( - batch_create_routing, - deployment_supported_endpoints, - get_router_metadata_variable_name, - is_batch_retrieve_call_type, - replace_model_in_jsonl, - should_replace_model_in_jsonl, - without_deployments_that_cannot_batch, -) from litellm.router_utils.client_initalization_utils import InitalizeCachedClient, MaxParallelRequestsLimit from litellm.router_utils.clientside_credential_handler import ( get_dynamic_litellm_params, @@ -212,9 +240,12 @@ from litellm.router_utils.clientside_credential_handler import ( ) from litellm.router_utils.common_utils import ( MID_STREAM_CONTINUATION_KWARG, + as_retry_skipped_deployment_ids, deployments_the_caller_may_use, filter_team_based_models, filter_web_search_deployments, + format_content_policy_fallback_hint, + format_content_policy_no_fallback_note, format_fallback_outcome_message, format_no_fallback_group_message, get_request_team_id, @@ -238,11 +269,12 @@ from litellm.router_utils.cooldown_handlers import ( async_get_cooldown_deployments_with_debug_info, get_cooldown_deployment_info, get_cooldown_deployments, - is_advisor_orchestration_failure, is_background_response_poll_not_found, is_caller_scoped_auth_failure, is_caller_timeout_408, + is_failure_outside_selected_deployment, is_video_lookup_not_found, + mark_deployment_selection_failure, set_cooldown_deployments, ) from litellm.router_utils.deployment_pricing import deployment_pricing_models @@ -303,14 +335,20 @@ from litellm.router_utils.kubernetes_pod_discovery import ( ) from litellm.router_utils.pre_call_checks.continuation_prefill_check import ( MID_STREAM_CONTINUATION_MARKER, + RESPONSES_CONTINUATION_KWARG, ContinuationOutput, ContinuationPrefillDeploymentCheck, ContinuedPartial, + ResponsesContinuation, + ResponsesContinuationSeam, constrains_continuation, + constrains_responses_continuation, continuation_deployments, continuation_output_ceilings, continued_text, deployment_can_continue, + responses_continuation_input, + responses_continuation_input_for, ) from litellm.router_utils.pre_call_checks.deployment_affinity_check import ( DeploymentAffinityCheck, @@ -349,6 +387,7 @@ from litellm.router_utils.request_priority import ( InvalidPriority, parse_default_priority, priority_error, + priority_header_fields, request_drops_params, resolve_request_priority, unqueueable_priority_message, @@ -455,6 +494,7 @@ from litellm.utils import ( provider_rejectable_params, resolve_api_key_secret_reference, set_live_deployment_replay, + token_counter, ) from .router_utils.pattern_match_deployments import PatternMatchRouter @@ -486,7 +526,6 @@ if TYPE_CHECKING: from litellm.types.llms.openai import ( ResponseAPIUsage, ResponseIncompleteEvent, - ResponseInputParam, ResponsesAPIResponse, ) @@ -623,6 +662,7 @@ _DEPLOYMENT_PARAMS_ADAPTER: Final[TypeAdapter[Mapping[str, object] | GenericLite _OPAQUE_VALUE_ADAPTER: Final = TypeAdapter(object) _DEPLOYMENT_SELECTED_EVENT: Final = "litellm.request.deployment_selected" _CONTENT_BLOCKS_ADAPTER: Final = TypeAdapter(list[dict[str, object]]) +_DEPLOYMENTS_ADAPTER: Final = TypeAdapter(Sequence[Mapping[str, object]]) def _extend_trailing_text_block(blocks: Sequence[Mapping[str, object]], text: str) -> Sequence[Mapping[str, object]]: @@ -684,8 +724,33 @@ def _configured_model_info(deployment: Mapping[str, object]) -> Mapping[str, obj return _MODEL_INFO_ADAPTER.validate_python(deployment.get("model_info") or {}) -def _as_retry_skipped_deployment_ids(value: object) -> tuple[str, ...]: - return tuple(item for item in value if isinstance(item, str)) if isinstance(value, tuple) else () +def _search_tool_support(deployment: DeploymentTypedDict) -> bool | None: + from litellm.responses.litellm_completion_transformation.tool_search import chat_config_builds_anthropic_request + + configured: Final = _configured_model_info(deployment).get("supports_search_tool") + if isinstance(configured, bool): + return configured + params: Final = _LITELLM_PARAMS_ADAPTER.validate_python(deployment["litellm_params"]) + model: Final = params.get("model") + provider: Final = params.get("custom_llm_provider") + if not isinstance(model, str): + return None + try: + resolved_model, resolved_provider = resolve_model_and_provider_for_metadata( + model=model, custom_llm_provider=provider if isinstance(provider, str) else None + ) + chat_config: Final = ProviderConfigManager.get_provider_chat_config( + model=resolved_model, provider=LlmProviders(resolved_provider) + ) + except (litellm.BadRequestError, ValueError): + return None + return True if chat_config_builds_anthropic_request(chat_config) else None + + +def _every_deployment_refused( + deployments: Sequence[Mapping[str, object]], refused_deployment_ids: tuple[str, ...] +) -> bool: + return all(_configured_model_info(deployment).get("id") in refused_deployment_ids for deployment in deployments) def _silent_experiment_targets(silent_model: object) -> tuple[str, ...]: @@ -828,6 +893,10 @@ def _request_model_group(kwargs: Mapping[str, object]) -> str | None: return model_group if isinstance(model_group, str) else None +def _mid_stream_error_before_output(error: "MidStreamFallbackError") -> bool: + return not error.generated_content or error.is_pre_first_chunk + + def _mid_stream_retry_trigger(error: "MidStreamFallbackError") -> Exception: """The provider's own error, which is what the retry policy and should_retry_this_error classify.""" return error.original_exception if error.original_exception is not None else error @@ -958,6 +1027,10 @@ def _responses_stream_holds_event(item: object, held_event_count: int) -> bool: return getattr(item, "type", None) in PRE_OUTPUT_LIFECYCLE_EVENT_TYPES +def _responses_event_announces_background_run(item: object) -> bool: + return getattr(getattr(item, "response", None), "background", None) is True + + class FallbackAwareAnthropicMessagesStream: """ Bare async generators can't carry the `_hidden_params` attribute the @@ -1348,7 +1421,7 @@ class Router: }, ] - router = Router(model_list=model_list, fallbacks=[{"azure-gpt-3.5-turbo": "openai-gpt-3.5-turbo"}]) + router = Router(model_list=model_list, fallbacks=[{"azure-gpt-3.5-turbo": ["openai-gpt-3.5-turbo"]}]) ``` """ @@ -1488,6 +1561,7 @@ class Router: self._cached_deployment_tracks_usage = lru_cache(maxsize=DEFAULT_MAX_LRU_CACHE_SIZE)( self._deployment_tracks_usage ) + self.served_openai_models = lru_cache(maxsize=DEFAULT_MAX_LRU_CACHE_SIZE)(self._served_openai_models) self._discovered_model_info_cache: InMemoryCache = InMemoryCache( max_size_in_memory=max(len(model_list or ()), 1), default_ttl=2 * MODEL_INFO_REFRESH_SECONDS, @@ -1519,6 +1593,7 @@ class Router: self.allowed_fails = allowed_fails else: self.allowed_fails = litellm.allowed_fails + self.explicit_allowed_fails = allowed_fails self.cooldown_time = cooldown_time or DEFAULT_COOLDOWN_TIME_SECONDS self.cooldown_cache = CooldownCache(cache=self.cache, default_cooldown_time=self.cooldown_time) self.disable_cooldowns = disable_cooldowns @@ -1573,6 +1648,10 @@ class Router: if default_fallbacks is not None or litellm.default_fallbacks is not None: _fallbacks = default_fallbacks or litellm.default_fallbacks + if isinstance(_fallbacks, str): + raise TypeError( + f"default_fallbacks must be a list of model names, got '{_fallbacks}'. Use ['{_fallbacks}']" + ) if self.fallbacks is not None: self.fallbacks.append({"*": _fallbacks}) else: @@ -2816,7 +2895,7 @@ class Router: self._initialize_core_endpoints() self._initialize_specialized_endpoints() - def validate_fallbacks(self, fallback_param: list | None): + def validate_fallbacks(self, fallback_param: Sequence[Mapping[str, object]] | None): """ Validate the fallbacks parameter. """ @@ -2829,6 +2908,13 @@ class Router: raise ValueError( f"Dictionary '{fallback_dict}' must have exactly one key, but has {len(fallback_dict)} keys." ) + ((model_group, targets),) = fallback_dict.items() + if isinstance(targets, list) or check_non_standard_fallback_format(fallbacks=[fallback_dict]): + continue + raise TypeError( + f"Fallbacks for '{model_group}' must be a list of model names, got '{targets}'. " + f"Use {{'{model_group}': ['{targets}']}}" + ) def _add_encrypted_content_affinity_check(self, enable_global_affinity: bool) -> None: def _move_before_deployment_affinity( @@ -3866,7 +3952,8 @@ class Router: ) -> Mapping[str, object]: """The request as the deployment received it, merged in the order _update_kwargs_with_deployment applies.""" deployment_params: Final = deployment.litellm_params.model_dump(exclude_none=True) if deployment else {} - defaults: Final = {key: value for key, value in self.default_litellm_params.items() if value is not None} + default_params: Final = _REQUEST_KWARGS_ADAPTER.validate_python(self.default_litellm_params) + defaults: Final = {key: value for key, value in default_params.items() if value is not None} deployment_tool_choice: Final = ( {"tool_choice": deployment_params["tool_choice"]} if deployment_params.get("tool_choice") is not None @@ -3945,67 +4032,6 @@ class Router: extended: Final = _extend_trailing_text_block(blocks, new_text) return [*messages[:-1], {**last, "content": extended, "prefix": True}] - @staticmethod - def _build_responses_continuation_input( - input_val: Union[str, "ResponseInputParam"] | None, - generated_content: str, - ) -> "ResponseInputParam": - """ - Convert Responses-API input + partial assistant output into a - continuation input that asks the fallback model to pick up where the - prior assistant message stopped. - - Best effort across providers. The chat-completions path uses - Anthropic's `prefix: True` prefill trick on the assistant message; - the Responses-API input schema has no direct equivalent, so we - append an instruction (developer role) plus a prior assistant - message containing the partial output. Providers without prefill - semantics (OpenAI, Vertex) treat this as conversational context - and may regenerate — same trade-off as the chat-completions path - for non-Anthropic fallbacks. - """ - # base/continuation are List[Any] because ResponseInputParam items - # are a wide Union of TypedDicts (EasyInputMessageParam, Message, - # ResponseOutputMessageParam, ...) — annotating as List[Dict[str, Any]] - # rejects the list() spread of input_val. We cast the combined list to - # ResponseInputParam at the return. - base: list[object] - if isinstance(input_val, str): - base = [ - { - "type": "message", - "role": "user", - "content": [{"type": "input_text", "text": input_val}], - } - ] - elif isinstance(input_val, list): - base = list(input_val) - else: - base = [] - continuation: Final[list[object]] = [ - { - "type": "message", - "role": "developer", - "content": [ - { - "type": "input_text", - "text": ( - "The previous assistant response was interrupted " - "mid-stream. Continue exactly where it stopped — " - "do not repeat any of its content. Your response " - "must read as a seamless continuation." - ), - } - ], - }, - { - "type": "message", - "role": "assistant", - "content": [{"type": "output_text", "text": generated_content}], - }, - ] - return cast("ResponseInputParam", base + continuation) - async def _aresponses_streaming_iterator( self, response: "BaseResponsesAPIStreamingIterator", @@ -4027,9 +4053,12 @@ class Router: Full parity with the chat-completions path: - Pre-first-chunk: retry with the original input unchanged. - - Partial content: inject a developer instruction + prior - assistant message carrying the generated text so the fallback - model continues rather than restarts. + - Partial content: continue from the generated text, as an + assistant prefill on a fallback that takes one and as assistant + history plus a user request to continue on any other. A request + whose output is constrained (a JSON schema, a forced tool), or a + stream that began a tool call, is not continued, and the primary's + error surfaces instead. - Usage combining: merge partial-stream usage onto the fallback's response.completed event so accounting reflects both attempts. - Stream cleanup: shielded aclose() on both source and fallback @@ -4179,11 +4208,16 @@ class Router: async def stream_with_fallbacks(): held_lifecycle_events: tuple[object, ...] = () # rebind-ok: flushed at first output, dropped on fallback + response_id_exposed = False # rebind-ok: set once, before an early-released lifecycle event is yielded try: async for item in cast( # cast-ok: response iterators are async streams AsyncIterator[object], source_iterator ): - if _responses_stream_holds_event(item, len(held_lifecycle_events)): + if not response_id_exposed and self._aresponses_background_stream_can_release( + item, source_iterator, initial_kwargs + ): + response_id_exposed = True + if not response_id_exposed and _responses_stream_holds_event(item, len(held_lifecycle_events)): held_lifecycle_events = (*held_lifecycle_events, item) continue for held_event in held_lifecycle_events: @@ -4193,6 +4227,8 @@ class Router: for held_event in held_lifecycle_events: yield held_event except MidStreamFallbackError as e: + if response_id_exposed: + self._raise_released_stream_error(e, initial_kwargs) async with contextlib.aclosing( self._aresponses_fallback_attempt( e, source_iterator, initial_kwargs, wrapper.adopt_fallback_headers, held_lifecycle_events @@ -4218,6 +4254,90 @@ class Router: wrapper: Final = FallbackResponsesStreamWrapper(stream_with_fallbacks()) return wrapper + def _aresponses_background_stream_can_release( + self, + item: object, + source_iterator: "BaseResponsesAPIStreamingIterator", + kwargs: Mapping[str, object], + ) -> bool: + from litellm.responses.streaming_iterator import ResponsesAPIStreamingIterator + + if ( + type(source_iterator) is not ResponsesAPIStreamingIterator + or source_iterator.custom_llm_provider != "openai" + ): + return False + if not _responses_event_announces_background_run(item): + return False + model_group: Final = kwargs.get("model") + return isinstance(model_group, str) and not self._stream_can_fall_back(model_group, kwargs) + + def _raise_released_stream_error( + self, e: "MidStreamFallbackError", initial_kwargs: Mapping[str, object] + ) -> NoReturn: + original: Final = e.original_exception + model_group: Final = initial_kwargs.get("model") + if ( + litellm.expose_router_debug_in_errors + and isinstance(original, litellm.ContentPolicyViolationError) + and isinstance(model_group, str) + and not fallbacks_disabled_for_request(initial_kwargs) + and _mid_stream_error_before_output(e) + ): + hop_depth: Final = initial_kwargs.get("fallback_depth") + original.message += format_content_policy_no_fallback_note( + model_group, + fallback_lookup_groups(initial_kwargs, model_group), + _request_fallback_list( + initial_kwargs, + "content_policy_fallbacks", + cast("list[object] | None", self.content_policy_fallbacks), # cast-ok: untyped router attribute + ), + _request_fallback_list( + initial_kwargs, + "fallbacks", + cast("list[object] | None", self.fallbacks), # cast-ok: untyped router attribute + ), + isinstance(hop_depth, int) and hop_depth > 0, + ) + Router._raise_original_mid_stream_error(e) + + def _responses_continuation( + self, + e: "MidStreamFallbackError", + source_iterator: "BaseResponsesAPIStreamingIterator", + request_kwargs: Mapping[str, object], + ) -> ResponsesContinuation | None: + """What a fallback continues from once a Responses stream broke after text, raising the primary's error + when the request constrains its output or the stream began a tool call, since a continued JSON document or + tool call would not parse, and when a content filter cut it, so no other model finishes filtered text.""" + if _mid_stream_error_before_output(e): + return None + if source_iterator.started_tool_call or isinstance(e.original_exception, litellm.ContentPolicyViolationError): + Router._raise_original_mid_stream_error(e) + cut_deployment_id: Final = (get_hidden_params(source_iterator) or {}).get("model_id") + cut_deployment: Final = ( + self.get_deployment(model_id=cut_deployment_id) if isinstance(cut_deployment_id, str) else None + ) + if constrains_responses_continuation(self._params_sent_to_deployment(request_kwargs, cut_deployment)): + Router._raise_original_mid_stream_error(e) + earlier: Final = request_kwargs.get(RESPONSES_CONTINUATION_KWARG) + if isinstance(earlier, ResponsesContinuation): + return earlier.extended(e.generated_content) + return ResponsesContinuation(request_kwargs.get("input"), e.generated_content) + + @staticmethod + def _responses_continuation_ceilings( + e: "MidStreamFallbackError", request_kwargs: Mapping[str, object] + ) -> Mapping[str, object]: + """The caller's output ceilings less what the cut stream already emitted, raising the primary's error once + nothing is left.""" + emitted_tokens: Final = token_counter(model=e.model or "", text=e.generated_content) + reduced: Final = continuation_output_ceilings(request_kwargs, emitted_tokens) + if reduced is None: + Router._raise_original_mid_stream_error(e) + return reduced + async def _aresponses_fallback_attempt( self, e: "MidStreamFallbackError", @@ -4236,6 +4356,11 @@ class Router: """ from litellm.exceptions import MidStreamFallbackError + continuation: Final = self._responses_continuation(e, source_iterator, initial_kwargs) + reduced_ceilings: Final[Mapping[str, object]] = ( + Router._responses_continuation_ceilings(e, initial_kwargs) if continuation is not None else {} + ) + seam: Final = ResponsesContinuationSeam(continuation.emitted_text if continuation is not None else "") partial_usage: Final = Router._extract_partial_responses_usage(source_iterator) fallback_response = None # rebind-ok: pre-init so finally can close it if a fallback was actually attempted fallback_yielded = False # rebind-ok: flipped on the first fallback item so a fallback that dies before its first event still replays the primary's held announcement @@ -4253,11 +4378,10 @@ class Router: initial_kwargs["original_function"] = ( # rebind-ok: the fallback chain re-enters on the same kwargs self._ageneric_api_call_with_fallbacks_responses_attempt ) - if e.generated_content and not e.is_pre_first_chunk: - initial_kwargs["input"] = Router._build_responses_continuation_input( # rebind-ok: fallback hop input - initial_kwargs.get("input"), - e.generated_content, - ) + if continuation is not None: + initial_kwargs.update(reduced_ceilings) + initial_kwargs[RESPONSES_CONTINUATION_KWARG] = continuation # rebind-ok: shaped per fallback deployment + initial_kwargs["input"] = responses_continuation_input(continuation) # rebind-ok: fallback hop input # The Responses-API path stores observability metadata # under "litellm_metadata" (not the default "metadata") — # see _ageneric_api_call_with_fallbacks. Mirroring that @@ -4286,7 +4410,7 @@ class Router: ) prepared_fallback_hidden_params: Final = adopt_headers(fallback_response) if hasattr(fallback_response, "__aiter__"): - async for fallback_item in fallback_response: + async for fallback_item in seam.splice(fallback_response): Router._apply_fallback_hidden_params_to_item(fallback_item, prepared_fallback_hidden_params) if partial_usage is not None: Router._combine_responses_fallback_usage(fallback_item, partial_usage) @@ -4718,7 +4842,13 @@ class Router: @staticmethod def _stamp_retry_skip_deployment_id(exception: Exception, kwargs: Mapping[str, object]) -> None: effective_model_info: Final = kwargs.get("model_info") - deployment_id: Final = effective_model_info.get("id") if isinstance(effective_model_info, Mapping) else None + if not isinstance(effective_model_info, Mapping): + return + model_info: Final = _MODEL_INFO_ADAPTER.validate_python(effective_model_info) + configured_deployment_id: Final = ( + model_info.get("original_model_id") if isinstance(exception, litellm.UnsupportedEndpointError) else None + ) + deployment_id: Final = configured_deployment_id or model_info.get("id") if isinstance(deployment_id, str) and deployment_id: exception.retry_skip_deployment_id = deployment_id # pyright: ignore[reportAttributeAccessIssue] # dynamic stamp, read by _deployment_ids_to_skip_on_retry @@ -4731,7 +4861,7 @@ class Router: Handles inserting this as either "metadata" or "litellm_metadata" depending on the metadata_variable_name """ # 1) copy your defaults and pull out metadata - defaults: Final = self.default_litellm_params.copy() + defaults: Final = dict(without_retrieve_stream_defaults(self.default_litellm_params, kwargs)) metadata_defaults: Final = defaults.pop("metadata", {}) or {} # 2) add any non-metadata defaults that aren't already in kwargs @@ -4809,16 +4939,18 @@ class Router: splits_stream_timeout: bool = False, ) -> None: """ - 4 jobs: + 5 jobs: - Adds selected deployment, model_info and api_base to kwargs["metadata"] (used for logging) - Adds default litellm params to kwargs, if set. - Merges tools from deployment with request (proxy-configured tools + request tools). - On a fallback hop, drops the encrypted reasoning this deployment cannot decrypt, keeping its summary. + - On a Responses continuation, sends the partial response as prefill where this deployment takes one. """ for key in self._forwarded_alias_marker_keys_the_deployment_sets( deployment=deployment, forwarded_keys=kwargs.pop(_ALIAS_MARKER_FORWARDED_PARAMS_KWARG, ()) ): kwargs.pop(key, None) + kwargs.pop("daily_reset_time", None) # pyright: ignore[reportUnknownMemberType] # kwargs is an untyped dict defaults: Final = _LITELLM_PARAMS_ADAPTER.validate_python(self.default_litellm_params) self._merge_tools_from_deployment(deployment=deployment, kwargs=kwargs, defaults=defaults) @@ -4970,12 +5102,13 @@ class Router: router_timeout=_router_timeout, router_stream_timeout=_router_stream_timeout, ) + timeout_request: Final = {**kwargs, "stream": True} if requests_streamed_retrieval(kwargs) else kwargs kwargs.update( CompletionTimeout.stream_request_kwargs( - passthrough_timeout(kwargs={**kwargs, "stream": False}), passthrough_timeout(kwargs=kwargs) + passthrough_timeout(kwargs={**kwargs, "stream": False}), passthrough_timeout(kwargs=timeout_request) ) - if splits_stream_timeout and kwargs.get("stream") - else {"timeout": passthrough_timeout(kwargs=kwargs)} + if splits_stream_timeout and timeout_request.get("stream") + else {"timeout": passthrough_timeout(kwargs=timeout_request)} ) elif splits_stream_timeout: request_kwargs: Final = _REQUEST_KWARGS_ADAPTER.validate_python(kwargs) @@ -5017,6 +5150,11 @@ class Router: (_FALLBACK_HOP_ADAPTER.validate_python(deployment),), unmarked_origin=deployment_that_just_failed, ) + if RESPONSES_CONTINUATION_KWARG in hop_kwargs: + del kwargs[RESPONSES_CONTINUATION_KWARG] # rebind-ok: this method prepares the call's kwargs in place + kwargs["input"] = responses_continuation_input_for( # rebind-ok: the deployment's continuation input + hop_kwargs, _FALLBACK_HOP_ADAPTER.validate_python(deployment) + ) def _get_async_openai_model_client(self, deployment: dict, kwargs: dict): """ @@ -5339,14 +5477,22 @@ class Router: request_priority: Final = resolve_request_priority( requested=kwargs.get("priority"), default_priority=self.default_priority, - drops_params=lambda: request_drops_params( - kwargs, self.default_litellm_params, self._request_deployment_params(model=model, kwargs=kwargs) - ), + drops_params=lambda: self._drops_params(model=model, kwargs=kwargs), ) if isinstance(request_priority, InvalidPriority): raise priority_error(model=model, message=request_priority.message) return request_priority, {key: value for key, value in kwargs.items() if key != "priority"} + def priority_header_update( + self, model: str, kwargs: Mapping[str, object], header: str | None + ) -> Mapping[str, int | str]: + return priority_header_fields(header, drops_params=lambda: self._drops_params(model=model, kwargs=kwargs)) + + def _drops_params(self, model: str, kwargs: Mapping[str, object]) -> bool: + return request_drops_params( + kwargs, self.default_litellm_params, self._request_deployment_params(model=model, kwargs=kwargs) + ) + async def _schedule_factory( self, model: str, @@ -5553,7 +5699,7 @@ class Router: def _image_generation(self, prompt: str, model: str, **kwargs): model_name: Final = "" try: - verbose_router_logger.debug("Inside _image_generation()- model: %s; kwargs: %s", model, kwargs) + verbose_router_logger.debug("Inside _image_generation()- model: %s", model) deployment: Final = self.get_available_deployment( model=model, messages=[{"role": "user", "content": "prompt"}], @@ -5615,7 +5761,7 @@ class Router: async def _aimage_generation(self, prompt: str, model: str, **kwargs): model_name = model try: - verbose_router_logger.debug("Inside _image_generation()- model: %s; kwargs: %s", model, kwargs) + verbose_router_logger.debug("Inside _image_generation()- model: %s", model) parent_otel_span: Final = get_parent_otel_span_from_kwargs(kwargs) deployment: Final = await self.async_get_available_deployment( model=model, @@ -5700,7 +5846,7 @@ class Router: async def _atranscription(self, file: FileTypes, model: str, **kwargs): model_name: Final = model try: - verbose_router_logger.debug("Inside _atranscription()- model: %s; kwargs: %s", model, kwargs) + verbose_router_logger.debug("Inside _atranscription()- model: %s", model) parent_otel_span: Final = get_parent_otel_span_from_kwargs(kwargs) deployment: Final = await self.async_get_available_deployment( model=model, @@ -5793,7 +5939,7 @@ class Router: async def _aspeech(self, model: str, input: str, voice: str | None = None, **kwargs): model_name: Final = model try: - verbose_router_logger.debug("Inside _aspeech()- model: %s; kwargs: %s", model, kwargs) + verbose_router_logger.debug("Inside _aspeech()- model: %s", model) parent_otel_span: Final = get_parent_otel_span_from_kwargs(kwargs) deployment: Final = await self.async_get_available_deployment( model=model, @@ -5855,7 +6001,7 @@ class Router: async def _arerank(self, model: str, **kwargs): model_name = None try: - verbose_router_logger.debug("Inside _rerank()- model: %s; kwargs: %s", model, kwargs) + verbose_router_logger.debug("Inside _rerank()- model: %s", model) deployment: Final = await self.async_get_available_deployment( model=model, specific_deployment=kwargs.pop("specific_deployment", None), @@ -5964,7 +6110,7 @@ class Router: async def _atext_completion(self, model: str, prompt: str, **kwargs): try: - verbose_router_logger.debug("Inside _atext_completion()- model: %s; kwargs: %s", model, kwargs) + verbose_router_logger.debug("Inside _atext_completion()- model: %s", model) parent_otel_span: Final = get_parent_otel_span_from_kwargs(kwargs) deployment: Final = await self.async_get_available_deployment( model=model, @@ -6034,7 +6180,7 @@ class Router: async def _aadapter_completion(self, adapter_id: str, model: str, **kwargs): try: - verbose_router_logger.debug("Inside _aadapter_completion()- model: %s; kwargs: %s", model, kwargs) + verbose_router_logger.debug("Inside _aadapter_completion()- model: %s", model) parent_otel_span: Final = get_parent_otel_span_from_kwargs(kwargs) deployment: Final = await self.async_get_available_deployment( model=model, @@ -6128,7 +6274,7 @@ class Router: kwargs=kwargs, metadata_variable_name="litellm_metadata", ) - verbose_router_logger.debug("Inside aguardrail() - guardrail_name: %s; kwargs: %s", guardrail_name, kwargs) + verbose_router_logger.debug("Inside aguardrail() - guardrail_name: %s", guardrail_name) response: Final = await self.async_function_with_fallbacks(**kwargs) return response @@ -6209,9 +6355,7 @@ class Router: controls: Final = per_request_fallback_controls(kwargs) kwargs[MID_STREAM_FALLBACK_CONTROLS_KEY] = controls # rebind-ok: forwarded to every hop self._update_kwargs_before_fallbacks(model=model, kwargs=kwargs, metadata_variable_name="litellm_metadata") - verbose_router_logger.debug( - "Inside ageneric_api_call_with_fallbacks() - model: %s; kwargs: %s", model, kwargs - ) + verbose_router_logger.debug("Inside ageneric_api_call_with_fallbacks() - model: %s", model) response: Final = await self.async_function_with_fallbacks(**kwargs) return response except Exception as e: @@ -6298,7 +6442,7 @@ class Router: generic_function_name: Final[str] = getattr(original_generic_function, "__name__", "") response_kwargs: Final = { - **data, + **without_retrieve_stream_defaults(data, kwargs), "caching": self.cache_responses, **kwargs, "model": model_name, @@ -6384,6 +6528,9 @@ class Router: hop_kwargs: Final = mid_stream_fallback_hop_kwargs( model=model, original_generic_function=original_generic_function, controls=controls, kwargs=kwargs ) + shared_logging: Final = kwargs.get("litellm_logging_obj") + if isinstance(shared_logging, LiteLLMLogging): + shared_logging.carry_failed_attempt_usage() response: Final = await self._ageneric_api_call_with_fallbacks_helper( model=model, original_generic_function=original_generic_function, **kwargs ) @@ -6493,7 +6640,7 @@ class Router: model: Final = cast(str, initial_kwargs.get("model")) # cast-ok: kwargs always carries the model group has_generated_content = not ( # rebind-ok: set once real content is seen, the buffer cap is hit, or neither a retry nor a fallback can take over self._anthropic_messages_stream_can_retry(initial_kwargs) - or self._anthropic_messages_stream_can_fall_back(model, initial_kwargs) + or self._stream_can_fall_back(model, initial_kwargs) ) buffered_lifecycle_chunks: tuple[bytes, ...] = () # rebind-ok: flushed once committed or on decline try: @@ -6716,7 +6863,7 @@ class Router: budget, _ = self._stream_retry_budget(frame_error, kwargs) if budget > attempted_retries_for_request(kwargs): return frame_error - if self._anthropic_messages_stream_can_fall_back(model_group, kwargs): + if self._stream_can_fall_back(model_group, kwargs): return frame_error return None @@ -7028,9 +7175,7 @@ class Router: handler_name: Final = original_function.__name__ metadata_variable_name: Final = get_router_metadata_variable_name(function_name="generic_api_call") try: - verbose_router_logger.debug( - "Inside _generic_api_call() - handler: %s, model: %s; kwargs: %s", handler_name, model, kwargs - ) + verbose_router_logger.debug("Inside _generic_api_call() - handler: %s, model: %s", handler_name, model) self._update_kwargs_before_fallbacks( model=model, kwargs=kwargs, @@ -7105,7 +7250,7 @@ class Router: def _embedding(self, input: str | list[object], model: str, **kwargs): model_name = None try: - verbose_router_logger.debug("Inside embedding()- model: %s; kwargs: %s", model, kwargs) + verbose_router_logger.debug("Inside embedding()- model: %s", model) with embedding_deployment_selection(): deployment: Final = self.get_available_deployment( model=model, @@ -7194,7 +7339,7 @@ class Router: async def _aembedding(self, input: str | list[object], model: str, **kwargs): model_name = None try: - verbose_router_logger.debug("Inside _aembedding()- model: %s; kwargs: %s", model, kwargs) + verbose_router_logger.debug("Inside _aembedding()- model: %s", model) parent_otel_span: Final = get_parent_otel_span_from_kwargs(kwargs) with embedding_deployment_selection(): deployment: Final = await self.async_get_available_deployment( @@ -7278,7 +7423,7 @@ class Router: try: from litellm.router_utils.common_utils import add_model_file_id_mappings - verbose_router_logger.debug("Inside _atext_completion()- model: %s; kwargs: %s", model, kwargs) + verbose_router_logger.debug("Inside _atext_completion()- model: %s", model) parent_otel_span: Final = get_parent_otel_span_from_kwargs(kwargs) healthy_deployments: Final = await self.async_get_healthy_deployments( model=model, @@ -7516,7 +7661,7 @@ class Router: **kwargs, ) -> LiteLLMBatch: try: - verbose_router_logger.debug("Inside _acreate_batch()- model: %s; kwargs: %s", model, kwargs) + verbose_router_logger.debug("Inside _acreate_batch()- model: %s", model) parent_otel_span: Final = get_parent_otel_span_from_kwargs(kwargs) with batch_create_routing(): deployment: Final = await self.async_get_available_deployment( @@ -7715,7 +7860,7 @@ class Router: **kwargs, ) -> LiteLLMBatch: try: - verbose_router_logger.debug("Inside _acancel_batch()- model: %s; kwargs: %s", model, kwargs) + verbose_router_logger.debug("Inside _acancel_batch()- model: %s", model) parent_otel_span: Final = get_parent_otel_span_from_kwargs(kwargs) deployment: Final = await self.async_get_available_deployment( model=model, @@ -8731,7 +8876,9 @@ class Router: ) return response else: - error_message = f"model={model_group}. content_policy_fallback={mask_sensitive_structure(content_policy_fallbacks)}. fallbacks={mask_sensitive_structure(fallbacks)}.\n\nSet 'content_policy_fallback' - https://docs.litellm.ai/docs/routing#fallbacks" + error_message = format_content_policy_fallback_hint( + model_group, content_policy_fallbacks, fallbacks + ) verbose_router_logger.info( msg=f"Got 'ContentPolicyViolationError'. No content_policy_fallback set. Defaulting \ to fallbacks, if available.{error_message}" @@ -8940,7 +9087,7 @@ class Router: return () if litellm.should_retry(status_code): return () - already_skipped_ids: Final = _as_retry_skipped_deployment_ids(already_skipped) + already_skipped_ids: Final = as_retry_skipped_deployment_ids(already_skipped) skipped: Final = tuple(sorted(frozenset((*already_skipped_ids, failed_deployment_id)))) verbose_router_logger.debug( "Retry skips deployments that already answered %s to this request: %s", status_code, skipped @@ -9054,6 +9201,10 @@ class Router: ) if first_skipped_ids: kwargs["_retry_skipped_deployment_ids"] = first_skipped_ids # rebind-ok: the next attempt reads it + if isinstance(original_exception, litellm.UnsupportedEndpointError) and _every_deployment_refused( + _DEPLOYMENTS_ADAPTER.validate_python(_healthy_deployments), first_skipped_ids + ): + raise else: raise @@ -9133,6 +9284,10 @@ class Router: ) if skipped_ids: kwargs["_retry_skipped_deployment_ids"] = skipped_ids # rebind-ok: the next attempt reads it + if isinstance(e, litellm.UnsupportedEndpointError) and _every_deployment_refused( + _DEPLOYMENTS_ADAPTER.validate_python(_healthy_deployments), skipped_ids + ): + raise _timeout = self._time_to_sleep_before_retry( e=e, remaining_retries=remaining_retries, @@ -9229,7 +9384,7 @@ class Router: status_code: Final = getattr(error, "status_code", None) if status_code is not None and not litellm.should_retry(status_code): # 401/403 are special cases - allow retry if multiple deployments exist (handled below) - if status_code not in (401, 403): + if status_code not in (401, 403) and not isinstance(error, litellm.UnsupportedEndpointError): raise error if isinstance(error, litellm.NotFoundError): @@ -9579,10 +9734,10 @@ class Router: try: exception: Final = kwargs.get("exception", None) - if is_advisor_orchestration_failure(exception): + if is_failure_outside_selected_deployment(exception): verbose_router_logger.debug( "Router: Exiting 'deployment_callback_on_failure' without cooldown. " - "Failure originated from advisor orchestration, not the selected deployment." + "Failure came from advisor orchestration or deployment selection, not the selected deployment." ) return False @@ -9879,7 +10034,7 @@ class Router: ) return has_unattempted_fallback_target(resolved, kwargs) - def _anthropic_messages_order_levels(self, model_group: str, kwargs: Mapping[str, Any]) -> tuple[int, ...]: + def _stream_order_levels(self, model_group: str, kwargs: Mapping[str, Any]) -> tuple[int, ...]: """ The distinct deployment order levels the fallback dispatcher would see for this request, computed the same way: the tier a pre-routing hook selected wins over the requested group. @@ -9897,7 +10052,7 @@ class Router: ) ) - def _anthropic_messages_stream_can_fall_back(self, model_group: str, kwargs: Mapping[str, Any]) -> bool: + def _stream_can_fall_back(self, model_group: str, kwargs: Mapping[str, Any]) -> bool: """ Whether async_function_with_fallbacks_common_utils could still route a MidStreamFallbackError somewhere for this request (order levels, weighted @@ -9909,7 +10064,7 @@ class Router: return False if self.enable_weighted_failover: return True - order_levels: Final = self._anthropic_messages_order_levels(model_group, kwargs) + order_levels: Final = self._stream_order_levels(model_group, kwargs) if len(order_levels) > 1: current_target: Final = kwargs.get("_target_order") skip_up_to: Final = current_target if current_target is not None else order_levels[0] @@ -10282,28 +10437,38 @@ class Router: model_info[field] = backend_value @staticmethod - def _cost_map_backend_model(deployment: Deployment) -> str: - model_info_base_model: Final = deployment.model_info.base_model + def _cost_map_backend_model(deployment: Deployment | DeploymentTypedDict) -> str: + model_info_base_model: Final = ( + deployment.model_info.base_model + if isinstance(deployment, Deployment) + else _configured_model_info(deployment).get("base_model") + ) if isinstance(model_info_base_model, str) and model_info_base_model: return model_info_base_model - params_base_model: Final = deployment.litellm_params.get("base_model") + params: Final = _LITELLM_PARAMS_ADAPTER.validate_python( + deployment.litellm_params.model_dump(exclude_none=True) + if isinstance(deployment, Deployment) + else deployment["litellm_params"] + ) + params_base_model: Final = params.get("base_model") if isinstance(params_base_model, str) and params_base_model: return params_base_model - params: Final = _LITELLM_PARAMS_ADAPTER.validate_python(deployment.litellm_params.model_dump(exclude_none=True)) + model: Final = ( + deployment.litellm_params.model + if isinstance(deployment, Deployment) + else deployment["litellm_params"].get("model", "") + ) invoked_model: Final = params.get("model_id") if ( isinstance(invoked_model, str) and invoked_model - and ( - deployment.litellm_params.custom_llm_provider == "bedrock" - or deployment.litellm_params.model.startswith("bedrock/") - ) + and (params.get("custom_llm_provider") == "bedrock" or model.startswith("bedrock/")) ): profile_model: Final = invoked_model if invoked_model.startswith("bedrock/") else f"bedrock/{invoked_model}" profile_info: Final = lookup_model_info_for_registration(model=profile_model, custom_llm_provider="bedrock") if not isinstance(profile_info, ModelInfoLookupMiss): return profile_model - return deployment.litellm_params.model + return model @staticmethod def _inherit_builtin_service_tier_pricing( @@ -11755,6 +11920,14 @@ class Router: indices: Final = self.model_name_to_deployment_indices.get(model_name) return None if indices is None else tuple(self.model_list[idx] for idx in indices) + def _served_openai_models(self, model_name: str) -> tuple[str | None, ...]: + return served_openai_models(self.deployments_named(model_name) or ()) + + def team_public_model_names_of(self, team_id: str) -> frozenset[str]: + """The public names `team_id` serves its own deployments under.""" + with self._deployment_index_lock: + return frozenset(name for owner, name in self.team_model_to_deployment_indices if owner == team_id) + def _team_deployments_named(self, team_id: str, public_model_name: str) -> tuple[DeploymentTypedDict, ...] | None: """The deployments `team_id` serves under `public_model_name`, or None when that pair is not indexed.""" with self._deployment_index_lock: @@ -12086,6 +12259,15 @@ class Router: for deployment in self._routable_deployments(model_name, team_id) ) + def get_search_tool_support(self, model_name: str, team_id: str | None = None) -> tuple[bool | None, ...]: + """ + Whether each deployment a request from team_id to model_name can route + to (see _routable_deployments) answers Codex's client `tool_search`: + its model_info.supports_search_tool when that is a bool, else True when + its route builds an Anthropic Messages request, else None (unknown). + """ + return tuple(_search_tool_support(deployment) for deployment in self._routable_deployments(model_name, team_id)) + def get_routable_upstream_model(self, model_name: str, team_id: str | None = None) -> str | None: """ Return the `litellm_params.model` of the first deployment a request @@ -13863,7 +14045,9 @@ class Router: ] return named or self._get_wildcard_deployments(model_name=model_group) - def resolved_litellm_models(self, model_name: str, team_id: str | None = None) -> tuple[str, ...]: + def resolved_litellm_models( + self, model_name: str, team_id: str | None = None, *, use_base_model: bool = False + ) -> tuple[str, ...]: """The provider model strings `model_name` can actually be served by on this proxy. `get_model_list` composes every channel the request path itself uses (exact name, @@ -13876,6 +14060,12 @@ class Router: deployment behind it - so the fallback for an empty result is the caller's policy, never this function's. """ + if use_base_model: + return tuple( + backend_model + for deployment in self.get_model_list(model_name=model_name, team_id=team_id) or () + if (backend_model := self._cost_map_backend_model(deployment)) + ) return tuple( litellm_model for deployment in self.get_model_list(model_name=model_name, team_id=team_id) or () @@ -13896,6 +14086,7 @@ class Router: self._ptu_share_teams.cache_clear() self._cached_team_ptu_ceiling.cache_clear() self._cached_deployment_tracks_usage.cache_clear() + self.served_openai_models.cache_clear() self._zero_cost_cache.clear() self._routing_group_rows = None @@ -14155,6 +14346,7 @@ class Router: messages: Sequence[Mapping[str, object]] | None, input: str | list[object] | None, request_kwargs: Mapping[str, object] | None = None, + tokenizer_model: str = "", ) -> int: """ Count input tokens for context-window pre-call checks. @@ -14185,7 +14377,7 @@ class Router: system_message: Final = anthropic_system_to_openai_message(extras.get("system")) if messages is not None: counted_messages: Final = (system_message, *messages) if system_message is not None else messages - return litellm.token_counter(messages=counted_messages, tools=tools) + return litellm.token_counter(model=tokenizer_model, messages=counted_messages, tools=tools) if input is not None: from openai.types.responses.response_create_params import ResponseInputParam @@ -14200,6 +14392,7 @@ class Router: only_since_compaction=True, ) return litellm.token_counter( + model=tokenizer_model, messages=cast(list, input_messages), # cast-ok: transformed chat messages tools=tools, ) @@ -14256,6 +14449,10 @@ class Router: messages=cast(list[dict[str, str]] | None, messages), # cast-ok: forwarded to the sync counter input=cast(str | list | None, input), # cast-ok: forwarded to the sync counter request_kwargs=request_kwargs, + tokenizer_model=single_encoding_openai_model( + self.served_openai_models(model) or served_openai_models(healthy_deployments) + ) + or "", ) except Exception as e: # noqa: BLE001 # best-effort: an uncountable prompt must not fail the request verbose_router_logger.error( @@ -14270,6 +14467,8 @@ class Router: request_kwargs: Mapping[str, object] | None, input_token_count: int | None, count_inline: bool, + model: str, + deployments: Sequence[Mapping[str, object]], ) -> int | None: if input_token_count is not None: return input_token_count @@ -14280,6 +14479,10 @@ class Router: messages=cast(list[dict[str, str]] | None, messages), # cast-ok: forwarded to the sync counter input=cast(str | list[object] | None, input), # cast-ok: forwarded to the sync counter request_kwargs=request_kwargs, + tokenizer_model=single_encoding_openai_model( + self.served_openai_models(model) or served_openai_models(deployments) + ) + or "", ) except Exception as e: verbose_router_logger.error( @@ -14445,7 +14648,6 @@ class Router: Filter out model in model group, if: - model context window < message length. For azure openai models, requires 'base_model' is set. - https://docs.litellm.ai/docs/proxy/cost_tracking#spend-tracking-for-azure-openai-models - - filter models above rpm limits - if region given, filter out models not in that region / unknown region - [TODO] function call and model doesn't support function calling """ @@ -14460,8 +14662,6 @@ class Router: _context_window_error = False _potential_error_str = "" - _rate_limit_error = False - parent_otel_span: Final = get_parent_otel_span_from_kwargs(request_kwargs) has_countable_input: Final = (messages is not None or input is not None) and not compaction_pending( request_kwargs @@ -14477,6 +14677,8 @@ class Router: count_inline=has_countable_input and not skip_inline_token_count and any(limit is not None for limit in deployment_max_input_tokens), + model=model, + deployments=_returned_deployments, ) request_settings: Final[Mapping[str, object]] = request_kwargs if request_kwargs is not None else {} requested_params: Final[frozenset[str]] = ( @@ -14485,13 +14687,6 @@ class Router: else frozenset() ) - ## get model group RPM ## - dt: Final = get_utc_datetime() - current_minute: Final = dt.strftime("%H-%M") - rpm_key: Final = f"{model}:rpm:{current_minute}" - model_group_cache: Final = ( - self.cache.get_cache(key=rpm_key, local_only=True, parent_otel_span=parent_otel_span) or {} - ) # check the in-memory cache used by lowest_latency and usage-based routing. Only check the local cache. for idx, deployment in enumerate(_returned_deployments): # Cache nested dict access to avoid repeated temporary dict allocations _litellm_params = deployment.get("litellm_params", {}) @@ -14514,24 +14709,6 @@ class Router: ) continue - model_id = _model_info.get("id", "") - ## RPM CHECK ## - ### get local router cache ### - current_request_cache_local = ( - self.cache.get_cache(key=model_id, local_only=True, parent_otel_span=parent_otel_span) or 0 - ) - ### get usage based cache ### - if isinstance(model_group_cache, dict) and self.routing_strategy != "usage-based-routing-v2": - model_group_cache[model_id] = model_group_cache.get(model_id, 0) - - current_request = max(current_request_cache_local, model_group_cache[model_id]) - - if isinstance(_litellm_params, dict) and _litellm_params.get("rpm", None) is not None: - if isinstance(_litellm_params["rpm"], int) and _litellm_params["rpm"] <= current_request: - invalid_model_indices.add(idx) - _rate_limit_error = True - continue - ## REGION CHECK ## if request_kwargs is not None and request_kwargs.get("allowed_model_region") is not None: allowed_model_region = request_kwargs.get("allowed_model_region") @@ -14568,12 +14745,6 @@ class Router: ) if len(excluded_indices) == len(_returned_deployments): - """ - - no healthy deployments available b/c context window checks or rate limit error - - - First check for rate limit errors (if this is true, it means the model passed the context window check but failed the rate limit check) - """ - group_deployments: Final = ( tuple(request_deployments) if request_deployments is not None @@ -14595,12 +14766,7 @@ class Router: ), model=model, ) - if _rate_limit_error is True: # allow generic fallback logic to take place - raise RouterRateLimitErrorBasic( - model=model, - ) - - elif _context_window_error is True: + if _context_window_error is True: raise litellm.ContextWindowExceededError( message=f"litellm._pre_call_checks: Context Window exceeded for given call. No models have context window large enough for this call.\n{_potential_error_str}", model=model, @@ -15184,7 +15350,7 @@ class Router: ## RETRY SKIP ## -> drop deployments that already refused this request with a ## non-retryable status, unless that leaves nothing, so the caller still gets ## the provider's own error instead of a no-deployments error. - _retry_skipped_deployment_ids: Final = _as_retry_skipped_deployment_ids( + _retry_skipped_deployment_ids: Final = as_retry_skipped_deployment_ids( request_kwargs.pop("_retry_skipped_deployment_ids", None) if request_kwargs else None ) healthy_deployments = ( @@ -15473,6 +15639,7 @@ class Router: phase_event(_DEPLOYMENT_SELECTED_EVENT, pick_attributes) return deployment except Exception as e: + mark_deployment_selection_failure(e) traceback_exception: Final = traceback.format_exc() # if router rejects call -> log to langfuse/otel/etc. if request_kwargs is not None: @@ -15641,6 +15808,7 @@ class Router: return deployment except Exception as e: + mark_deployment_selection_failure(e) traceback_exception: Final = traceback.format_exc() if request_kwargs is not None: logging_obj: Final = request_kwargs.get("litellm_logging_obj", None) @@ -16180,7 +16348,7 @@ class Router: to the deployment that actually served the request. Every attempt therefore writes or clears, never just writes. """ - from litellm.router_utils.baseline_request import capture_baseline_parameters + from litellm.router_strategy.auto_router.baseline_request import capture_baseline_parameters from litellm.types.router import BaselineRouteStamp phase_attributes(routing_decision_attributes(routing_decision)) @@ -16414,7 +16582,7 @@ class Router: ) ## RETRY SKIP ## -> see async counterpart in async_get_healthy_deployments. - _retry_skipped_deployment_ids: Final = _as_retry_skipped_deployment_ids( + _retry_skipped_deployment_ids: Final = as_retry_skipped_deployment_ids( request_kwargs.pop("_retry_skipped_deployment_ids", None) if request_kwargs else None ) healthy_deployments = ( diff --git a/litellm/router_utils/auto_router_model_naming.py b/litellm/router_strategy/auto_router/auto_router_model_naming.py similarity index 100% rename from litellm/router_utils/auto_router_model_naming.py rename to litellm/router_strategy/auto_router/auto_router_model_naming.py diff --git a/litellm/router_utils/auto_router_tuning_baseline.py b/litellm/router_strategy/auto_router/auto_router_tuning_baseline.py similarity index 100% rename from litellm/router_utils/auto_router_tuning_baseline.py rename to litellm/router_strategy/auto_router/auto_router_tuning_baseline.py diff --git a/litellm/router_utils/baseline_request.py b/litellm/router_strategy/auto_router/baseline_request.py similarity index 100% rename from litellm/router_utils/baseline_request.py rename to litellm/router_strategy/auto_router/baseline_request.py diff --git a/litellm/router_strategy/budget_limiter.py b/litellm/router_strategy/budget_limiter.py index eab232eae18..1d502dd8d95 100644 --- a/litellm/router_strategy/budget_limiter.py +++ b/litellm/router_strategy/budget_limiter.py @@ -36,12 +36,12 @@ from litellm._logging import verbose_router_logger from litellm.caching.caching import DualCache from litellm.caching.redis_cache import RedisCache, RedisPipelineIncrementOperation, log_redis_failure from litellm.integrations.custom_logger import CustomLogger, Span +from litellm.litellm_core_utils.batch_utils import batch_charged_once_marker_key, batch_id_to_charge_once from litellm.litellm_core_utils.core_helpers import ( get_metadata_variable_name_from_kwargs, ) from litellm.litellm_core_utils.duration_parser import duration_in_seconds_from from litellm.router_strategy.tag_based_routing import get_tags_from_request_kwargs -from litellm.router_utils.batch_utils import batch_charged_once_marker_key, batch_id_to_charge_once from litellm.router_utils.cooldown_callbacks import ( get_prometheus_logger_from_callbacks, ) diff --git a/litellm/router_strategy/complexity_router/README.md b/litellm/router_strategy/complexity_router/README.md index 3df1803d264..d06248a555f 100644 --- a/litellm/router_strategy/complexity_router/README.md +++ b/litellm/router_strategy/complexity_router/README.md @@ -477,6 +477,12 @@ unless `modality_routing` is also on. ### Session pin retention +With `classification_mode: user_turn`, a child request carrying `x-parent-session-id` classifies +its own new asks and stores the tier under its own session ID. Its continuations reuse that tier +without replacing the parent's tier. Existing trace grouping, per-tier model affinity and deployment +affinity retain their session identities. A child without a distinct, usable session ID classifies +without storing a tier pin. `session_affinity: true` retains precedence and the existing shared-pin behavior + `session_affinity_ttl_seconds` is the idle window for both the model pin selected by session affinity and the deployment pin. Every request that reuses a pin refreshes its TTL, so a session actively sending requests stays pinned. After the window passes with no pin reuse, the next request classifies again and creates a fresh pin. Omit the setting to track the default of 3600 seconds. ### Mid-task stall escalation diff --git a/litellm/router_strategy/complexity_router/complexity_router.py b/litellm/router_strategy/complexity_router/complexity_router.py index 82aaa221d31..43af0485a2d 100644 --- a/litellm/router_strategy/complexity_router/complexity_router.py +++ b/litellm/router_strategy/complexity_router/complexity_router.py @@ -23,6 +23,7 @@ import random import re import time from collections.abc import Awaitable, Callable, Iterator, Mapping, Sequence +from dataclasses import dataclass from functools import partial from itertools import accumulate, chain, islice, takewhile from threading import Lock @@ -37,6 +38,7 @@ from litellm._internal_context import with_service_target from litellm._logging import verbose_router_logger from litellm.caching.affinity_cache import ROUTER_SESSION_PINS_TARGET, claim_affinity_pin, read_affinity_pin from litellm.constants import ( + COMPLEXITY_ROUTER_CHILD_SESSION_ID_METADATA_KEY, EMPTY_MAPPING, INTERNAL_CALL_ORIGIN_METADATA_KEY, OUTPUT_TOKEN_CEILING_PARAMS, @@ -1389,6 +1391,11 @@ def _session_affinity_cache_value(model: str, tier: ComplexityTier | str | None) return {"model": model, "tier": tier_value} +@dataclass(frozen=True, slots=True) +class _JevConnectionError: + message: str + + class ComplexityRouter(CustomLogger): """ Complexity router that classifies requests and routes to appropriate models. @@ -1404,7 +1411,7 @@ class ComplexityRouter(CustomLogger): - Question complexity (multiple questions) """ - def _build_jev_client(self, config: OpenSourceClassifierConfig) -> JevClassifierClient: + def _build_jev_client(self, config: OpenSourceClassifierConfig) -> JevClassifierClient | _JevConnectionError: if config.deployment_name is not None: return RouterJevClassifierClient(self.litellm_router_instance, config.deployment_name) if config.provider in ("laya", "bespoke"): @@ -1425,12 +1432,22 @@ class ComplexityRouter(CustomLogger): http_client=get_async_httpx_client(httpxSpecialProvider.PassThroughEndpoint), provider="databricks", ) - api_key: Final = config.api_key or get_secret_str("TYPESAFE_API_KEY") - if not api_key: - raise ValueError( + api_key: Final = ( + get_secret_str(config.api_key) + if config.api_key is not None and config.api_key.startswith("os.environ/") + else config.api_key or get_secret_str("TYPESAFE_API_KEY") + ) + if not api_key or not api_key.strip(): + return _JevConnectionError( "opensource_classifier_config.api_key or TYPESAFE_API_KEY is required for classifier_type 'oss_classifier'" ) - api_base: Final = config.api_base or get_secret_str("TYPESAFE_API_BASE") or "https://api.typesafe.ai" + api_base: Final = ( + get_secret_str(config.api_base) + if config.api_base is not None and config.api_base.startswith("os.environ/") + else config.api_base or get_secret_str("TYPESAFE_API_BASE") or "https://api.typesafe.ai" + ) + if not api_base or not api_base.strip(): + return _JevConnectionError("opensource_classifier_config.api_base must resolve to a non-empty value") return HttpJevClassifierClient( api_key=api_key, api_base=api_base, @@ -1473,13 +1490,18 @@ class ComplexityRouter(CustomLogger): self.config.default_model = default_model jev_config: Final = self.config.opensource_classifier_config - self._jev_client: JevClassifierClient | None = ( + jev_client_result: Final = ( jev_client if jev_client is not None else self._build_jev_client(jev_config) if self.config.classifier_type == "oss_classifier" and jev_config is not None else None ) + match jev_client_result: + case _JevConnectionError(message=message): + raise ValueError(message) + case _: + self._jev_client: JevClassifierClient | None = jev_client_result self._tier_affinity_config = hashlib.sha256( self.config.model_dump_json(include=MappingProxyType({"tiers": True, "tier_model_configs": True})).encode() @@ -4358,17 +4380,17 @@ class ComplexityRouter(CustomLogger): return newest_ask is not None and newest_ask.startswith(_CODEX_COMPACTION_SUMMARY_PREFIX) @staticmethod - def _iter_metadata_dicts(request_kwargs: dict) -> list[dict]: + def _iter_metadata_dicts(request_kwargs: Mapping[str, object]) -> list[Mapping[str, object]]: """Metadata may land on `metadata` or `litellm_metadata` depending on the endpoint, mirroring DeploymentAffinityCheck's precedence.""" return [ - metadata + cast(Mapping[str, object], metadata) # cast-ok: request metadata is a str-keyed JSON object for metadata_key in ("litellm_metadata", "metadata") if isinstance(metadata := request_kwargs.get(metadata_key), dict) ] @staticmethod - def _get_session_id_from_request_kwargs(request_kwargs: dict) -> str | None: + def _get_session_id_from_request_kwargs(request_kwargs: Mapping[str, object]) -> str | None: """Resolve a client-supplied session_id.""" for metadata in ComplexityRouter._iter_metadata_dicts(request_kwargs): session_id = metadata.get("session_id") @@ -4376,6 +4398,21 @@ class ComplexityRouter(CustomLogger): return str(session_id) return None + def _get_tier_pin_session_id(self, request_kwargs: Mapping[str, object]) -> str | None: + if self.config.classification_mode == "user_turn" and not self.config.session_affinity: + child_metadata: Final = next( + ( + metadata + for metadata in self._iter_metadata_dicts(request_kwargs) + if COMPLEXITY_ROUTER_CHILD_SESSION_ID_METADATA_KEY in metadata + ), + None, + ) + if child_metadata is not None: + child_session: Final = child_metadata[COMPLEXITY_ROUTER_CHILD_SESSION_ID_METADATA_KEY] + return child_session if isinstance(child_session, str) and child_session else None + return self._get_session_id_from_request_kwargs(request_kwargs) + @staticmethod def _get_user_api_key_hash_from_request_kwargs(request_kwargs: dict) -> str | None: """Resolve the proxy-derived API key hash, the same trust boundary @@ -4460,7 +4497,7 @@ class ComplexityRouter(CustomLogger): conversation_continuing: Final = _conversation_is_continuing(resolved_messages) use_session_affinity: Final = self._uses_tier_pin - session_id: Final = self._get_session_id_from_request_kwargs(request_kwargs) if use_session_affinity else None + session_id: Final = self._get_tier_pin_session_id(request_kwargs) if use_session_affinity else None cache_key = self._get_session_affinity_cache_key(session_id, request_kwargs) if session_id is not None else None # In 'user_turn' mode a held pin is replayed only on continuation turns; a new human diff --git a/litellm/router_strategy/least_busy.py b/litellm/router_strategy/least_busy.py index 6f3e0936641..8e0c3d6a7e7 100644 --- a/litellm/router_strategy/least_busy.py +++ b/litellm/router_strategy/least_busy.py @@ -10,7 +10,7 @@ from litellm._logging import verbose_router_logger from litellm.caching.caching import DualCache from litellm.caching.redis_cache import log_redis_failure from litellm.integrations.custom_logger import CustomLogger -from litellm.router_utils.batch_utils import is_batch_retrieve_call_type +from litellm.litellm_core_utils.batch_utils import is_batch_retrieve_call_type IN_FLIGHT_COUNT_TTL_SECONDS: Final = 60 * 60 diff --git a/litellm/router_strategy/lowest_cost.py b/litellm/router_strategy/lowest_cost.py index 5894da9cb4f..17d03fd4ff8 100644 --- a/litellm/router_strategy/lowest_cost.py +++ b/litellm/router_strategy/lowest_cost.py @@ -10,7 +10,7 @@ from litellm._internal_context import with_service_target from litellm._logging import verbose_router_logger from litellm.caching.caching import DualCache from litellm.integrations.custom_logger import CustomLogger -from litellm.router_utils.batch_utils import is_batch_retrieve_call_type +from litellm.litellm_core_utils.batch_utils import is_batch_retrieve_call_type from litellm.router_utils.deployment_pricing import deployment_pricing_models, str_keyed diff --git a/litellm/router_strategy/lowest_latency.py b/litellm/router_strategy/lowest_latency.py index 4e994d3fdc6..c352934db6c 100644 --- a/litellm/router_strategy/lowest_latency.py +++ b/litellm/router_strategy/lowest_latency.py @@ -13,9 +13,9 @@ from litellm import ModelResponse, token_counter, verbose_logger from litellm._internal_context import with_service_target from litellm.caching.caching import DualCache from litellm.integrations.custom_logger import CustomLogger +from litellm.litellm_core_utils.batch_utils import is_batch_retrieve_call_type from litellm.litellm_core_utils.core_helpers import get_parent_otel_span_from_kwargs, safe_divide_seconds from litellm.responses.utils import ResponseAPILoggingUtils -from litellm.router_utils.batch_utils import is_batch_retrieve_call_type from litellm.types.llms.openai import ResponsesAPIResponse from litellm.types.utils import LiteLLMPydanticObjectBase diff --git a/litellm/router_strategy/lowest_tpm_rpm.py b/litellm/router_strategy/lowest_tpm_rpm.py index 2d373e0c266..9636d7f009d 100644 --- a/litellm/router_strategy/lowest_tpm_rpm.py +++ b/litellm/router_strategy/lowest_tpm_rpm.py @@ -9,7 +9,7 @@ from litellm._internal_context import with_service_target from litellm._logging import verbose_router_logger from litellm.caching.caching import DualCache from litellm.integrations.custom_logger import CustomLogger -from litellm.router_utils.batch_utils import is_batch_retrieve_call_type +from litellm.litellm_core_utils.batch_utils import is_batch_retrieve_call_type from litellm.types.utils import LiteLLMPydanticObjectBase from litellm.utils import print_verbose diff --git a/litellm/router_strategy/lowest_tpm_rpm_v2.py b/litellm/router_strategy/lowest_tpm_rpm_v2.py index 527ea830d55..0719b30d36d 100644 --- a/litellm/router_strategy/lowest_tpm_rpm_v2.py +++ b/litellm/router_strategy/lowest_tpm_rpm_v2.py @@ -15,8 +15,8 @@ from litellm._internal_context import with_service_target from litellm._logging import verbose_logger, verbose_router_logger from litellm.caching.caching import DualCache from litellm.integrations.custom_logger import CustomLogger +from litellm.litellm_core_utils.batch_utils import is_batch_retrieve_call_type from litellm.litellm_core_utils.core_helpers import get_parent_otel_span_from_kwargs -from litellm.router_utils.batch_utils import is_batch_retrieve_call_type from litellm.types.router import RouterErrors from litellm.types.utils import LiteLLMPydanticObjectBase, StandardLoggingPayload from litellm.utils import get_utc_datetime, print_verbose diff --git a/litellm/router_utils/common_utils.py b/litellm/router_utils/common_utils.py index a00d84babf3..2451422b5e6 100644 --- a/litellm/router_utils/common_utils.py +++ b/litellm/router_utils/common_utils.py @@ -4,7 +4,7 @@ from collections.abc import Mapping, Sequence from types import MappingProxyType from typing import TYPE_CHECKING, Final, TypeVar -from pydantic import TypeAdapter +from pydantic import TypeAdapter, ValidationError if TYPE_CHECKING: from litellm.types.llms.openai import OpenAIFileObject @@ -38,6 +38,10 @@ _OBJECT_MAPPING_ADAPTER: Final[TypeAdapter[Mapping[object, object]]] = TypeAdapt _DEPLOYMENT_ROWS_ADAPTER: Final[TypeAdapter[tuple[Mapping[str, object], ...]]] = TypeAdapter( tuple[Mapping[str, object], ...] ) +_DEPLOYMENT_IDS_ADAPTER: Final = TypeAdapter(tuple[str, ...]) +_FALLBACK_ENTRIES_ADAPTER: Final[TypeAdapter[tuple[Mapping[str, object], ...]]] = TypeAdapter( + tuple[Mapping[str, object], ...] +) def with_admin_api_key_secret_reference(deployment: Deployment) -> Deployment: @@ -57,6 +61,31 @@ def without_router_only_kwargs(kwargs: Mapping[str, _V]) -> dict[str, _V]: return {key: value for key, value in kwargs.items() if key not in ROUTER_ONLY_CALL_KWARGS} +def as_retry_skipped_deployment_ids(value: object) -> tuple[str, ...]: + if not isinstance(value, tuple): + return () + items: Final[tuple[object, ...]] = value + return tuple(item for item in items if isinstance(item, str)) + + +def as_excluded_deployment_ids(value: object) -> tuple[str, ...]: + if value is None: + return () + try: + return _DEPLOYMENT_IDS_ADAPTER.validate_python(value) + except ValidationError: + return () + + +def deployment_ids_failed_in_request(request_kwargs: Mapping[str, object]) -> frozenset[str]: + return frozenset( + ( + *as_excluded_deployment_ids(request_kwargs.get("_excluded_deployment_ids")), + *as_retry_skipped_deployment_ids(request_kwargs.get("_retry_skipped_deployment_ids")), + ) + ) + + def request_user_api_key_auth(request_kwargs: Mapping[str, object]) -> object: """The caller's auth object, from whichever metadata bucket this surface writes to.""" metadata_value: Final = request_kwargs.get("metadata") @@ -230,6 +259,40 @@ def format_fallback_outcome_message( return f"{lead} Fallback model group(s) configured: {targets}." +def format_content_policy_fallback_hint( + model_group: str | None, content_policy_fallbacks: object, fallbacks: object +) -> str: + return ( + f"model={model_group}. content_policy_fallback={mask_sensitive_structure(content_policy_fallbacks)}. " + f"fallbacks={mask_sensitive_structure(fallbacks)}.\n\nSet 'content_policy_fallback' - " + "https://docs.litellm.ai/docs/routing#fallbacks" + ) + + +def _as_fallback_entries(fallbacks: object) -> tuple[Mapping[str, object], ...] | None: + try: + return _FALLBACK_ENTRIES_ADAPTER.validate_python(fallbacks) + except ValidationError: + return None + + +def format_content_policy_no_fallback_note( + model_group: str, + lookup_groups: tuple[str, ...], + content_policy_fallbacks: object, + fallbacks: object, + nested_fallback_hop: bool, +) -> str: + outcome: Final = "" if nested_fallback_hop else format_fallback_outcome_message(model_group, None, "") + if content_policy_fallbacks is not None: + return outcome + hint: Final = f"\n{format_content_policy_fallback_hint(model_group, content_policy_fallbacks, fallbacks)}" + fallback_entries: Final = _as_fallback_entries(fallbacks) if fallbacks is not None else None + if fallback_entries is None or not lookup_groups or nested_fallback_hop: + return hint + outcome + return hint + format_no_fallback_group_message(lookup_groups, fallback_entries) + + def get_litellm_params_sensitive_credential_hash(litellm_params: dict) -> str: """ Hash of the credential params, used for mapping the file id to the right model diff --git a/litellm/router_utils/cooldown_handlers.py b/litellm/router_utils/cooldown_handlers.py index 330500789a4..a1b1e327802 100644 --- a/litellm/router_utils/cooldown_handlers.py +++ b/litellm/router_utils/cooldown_handlers.py @@ -13,7 +13,7 @@ from datetime import datetime from types import MappingProxyType from typing import TYPE_CHECKING, Any, Final -from pydantic import TypeAdapter +from pydantic import TypeAdapter, ValidationError import litellm from litellm._internal_context import service_target @@ -57,6 +57,7 @@ else: Span = Any _ADVISOR_ORCHESTRATION_FAILURE_ATTR: Final = "_litellm_advisor_orchestration_failure" +_DEPLOYMENT_SELECTION_FAILURE_ATTR: Final = "_litellm_deployment_selection_failure" _CREDENTIAL_VALUES_ADAPTER: Final = TypeAdapter(Mapping[str, object]) @@ -79,6 +80,16 @@ def is_advisor_orchestration_failure(exception: BaseException | None) -> bool: return bool(getattr(exception, _ADVISOR_ORCHESTRATION_FAILURE_ATTR, False)) +def mark_deployment_selection_failure(exception: BaseException) -> None: + setattr(exception, _DEPLOYMENT_SELECTION_FAILURE_ATTR, True) + + +def is_failure_outside_selected_deployment(exception: BaseException | None) -> bool: + return is_advisor_orchestration_failure(exception) or bool( + getattr(exception, _DEPLOYMENT_SELECTION_FAILURE_ATTR, False) + ) + + _BACKGROUND_RESPONSE_POLL_CALL_ORIGINS: Final[frozenset[InternalCallOrigin]] = frozenset( {BACKGROUND_RESPONSE_COST_POLL_CALL_ORIGIN, BACKGROUND_RESPONSE_STATUS_POLL_CALL_ORIGIN} ) @@ -345,7 +356,7 @@ def _should_run_cooldown_logic( ) return False - if isinstance(original_exception, litellm.MalformedRequestFieldError): + if isinstance(original_exception, (litellm.MalformedRequestFieldError, litellm.UnsupportedEndpointError)): verbose_router_logger.debug( "Should Not Run Cooldown Logic: litellm rejected the request before calling the deployment" ) @@ -406,17 +417,35 @@ def _should_run_cooldown_logic( return True -_FALLBACK_ENTRIES_ADAPTER: Final = TypeAdapter(tuple[Mapping[str, list[str | Mapping[str, object]]] | str, ...]) +_FALLBACK_ENTRIES_ADAPTER: Final = TypeAdapter(tuple[object, ...]) +_FALLBACK_ENTRY_ADAPTER: Final = TypeAdapter(Mapping[str, list[str | Mapping[str, object]] | str]) def _fallback_target_name(target: str | Mapping[str, object]) -> str: return target if isinstance(target, str) else str(target.get("model", "")) +def _fallback_target_names( + targets: Sequence[str | Mapping[str, object]] | str, +) -> list[str]: # mutable-ok: mirrors get_fallback_model_group's fallbacks shape + return [targets] if isinstance(targets, str) else [_fallback_target_name(target) for target in targets] + + def _fallback_chain_names( - entry: Mapping[str, Sequence[str | Mapping[str, object]]], -) -> Mapping[str, list[str]]: # mutable-ok: mirrors get_fallback_model_group's fallbacks shape - return {key: [_fallback_target_name(target) for target in targets] for key, targets in entry.items()} + entry: object, +) -> Mapping[str, list[str]] | None: # mutable-ok: mirrors get_fallback_model_group's fallbacks shape + try: + validated: Final = _FALLBACK_ENTRY_ADAPTER.validate_python(entry) + except ValidationError: + return None + return {key: _fallback_target_names(targets) for key, targets in validated.items()} + + +def _fallback_entries(configured: object) -> tuple[object, ...]: + try: + return _FALLBACK_ENTRIES_ADAPTER.validate_python(configured) + except ValidationError: + return () def _has_fallback_group(litellm_router_instance: LitellmRouter, requested_model_group: str | None) -> bool: @@ -426,9 +455,7 @@ def _has_fallback_group(litellm_router_instance: LitellmRouter, requested_model_ if requested_model_group is None or not configured: return False chains: Final = tuple( - _fallback_chain_names(entry) - for entry in _FALLBACK_ENTRIES_ADAPTER.validate_python(configured) - if isinstance(entry, Mapping) + chain for chain in map(_fallback_chain_names, _fallback_entries(configured)) if chain is not None ) fallback_group, _ = get_fallback_model_group(fallbacks=chains, model_group=requested_model_group) return bool(fallback_group) @@ -781,14 +808,17 @@ def _is_allowed_fails_set_on_router( litellm_router_instance: LitellmRouter, ) -> bool: """ - Check if Router.allowed_fails is set or is Non-default Value + Check if Router.allowed_fails was passed to the Router or is a Non-default Value Returns: - - True if Router.allowed_fails is set or is Non-default Value - - False if Router.allowed_fails is None or is Default Value + - True if allowed_fails was passed to the Router, even when it equals the default + - True if Router.allowed_fails is a Non-default Value + - False if Router.allowed_fails is None, or is the Default Value and was not passed """ if litellm_router_instance.allowed_fails is None: return False + if litellm_router_instance.explicit_allowed_fails is not None: + return True if litellm_router_instance.allowed_fails != litellm.allowed_fails: return True return False diff --git a/litellm/router_utils/fallback_event_handlers.py b/litellm/router_utils/fallback_event_handlers.py index 6c93fe6d239..6d1de1f9f6c 100644 --- a/litellm/router_utils/fallback_event_handlers.py +++ b/litellm/router_utils/fallback_event_handlers.py @@ -13,6 +13,7 @@ from pydantic import TypeAdapter import litellm from litellm._logging import verbose_router_logger from litellm.integrations.custom_logger import CustomLogger +from litellm.litellm_core_utils.batch_utils import get_router_metadata_variable_name from litellm.litellm_core_utils.core_helpers import get_metadata_variable_name_from_kwargs, safe_deep_copy from litellm.litellm_core_utils.credential_accessor import reject_api_key_secret_reference from litellm.litellm_core_utils.get_llm_provider_logic import inferred_provider @@ -22,7 +23,6 @@ from litellm.router_utils.add_retry_fallback_headers import ( add_fallback_headers_to_response, get_fallback_error_info, ) -from litellm.router_utils.batch_utils import get_router_metadata_variable_name from litellm.router_utils.cooldown_handlers import ( _first_present, # pyright: ignore[reportPrivateUsage] - shared internal helper, used across router_utils cast_exception_status_to_int, @@ -261,7 +261,10 @@ def is_bad_request_without_fallback(exception: Exception, fallback_on_unsupporte return False if isinstance(exception, litellm.UnsupportedParamsError): return True - if isinstance(exception, (litellm.ContextWindowExceededError, litellm.ContentPolicyViolationError)): + if isinstance( + exception, + (litellm.ContextWindowExceededError, litellm.ContentPolicyViolationError, litellm.UnsupportedEndpointError), + ): return False return exception.status_code == 400 and bool(getattr(exception, "llm_provider", "")) diff --git a/litellm/router_utils/get_retry_from_policy.py b/litellm/router_utils/get_retry_from_policy.py index 7c412dc759b..835cfaacfd5 100644 --- a/litellm/router_utils/get_retry_from_policy.py +++ b/litellm/router_utils/get_retry_from_policy.py @@ -13,6 +13,7 @@ from litellm.exceptions import ( RateLimitError, ServiceUnavailableError, Timeout, + UnsupportedEndpointError, ) from litellm.types.router import RetryPolicy @@ -59,6 +60,8 @@ def get_num_retries_from_retry_policy( policy: Final = resolve_retry_policy(retry_policy, model_group, model_group_retry_policy) if policy is None: return None + if isinstance(exception, UnsupportedEndpointError): + return policy.DefaultRetries by_class: Final = ( _RETRIES_BY_EXCEPTION_TYPE[cls](policy) for cls in type(exception).__mro__ if cls in _RETRIES_BY_EXCEPTION_TYPE ) diff --git a/litellm/router_utils/pre_call_checks/continuation_prefill_check.py b/litellm/router_utils/pre_call_checks/continuation_prefill_check.py index 8f211ef67db..d2a46fc316d 100644 --- a/litellm/router_utils/pre_call_checks/continuation_prefill_check.py +++ b/litellm/router_utils/pre_call_checks/continuation_prefill_check.py @@ -1,12 +1,13 @@ """Keeps a mid-stream continuation on deployments whose model supports assistant prefill and whose own params leave -the output unconstrained.""" +the output unconstrained, and shapes a Responses API continuation for the deployment that serves it.""" -from collections.abc import AsyncIterable, AsyncIterator, Mapping, Sequence +import json +from collections.abc import AsyncIterable, AsyncIterator, Callable, Mapping, Sequence from dataclasses import dataclass from itertools import accumulate from os.path import commonprefix from types import MappingProxyType -from typing import Final +from typing import Final, TypeVar from pydantic import TypeAdapter, ValidationError @@ -14,7 +15,7 @@ import litellm from litellm.integrations.custom_logger import CustomLogger, Span from litellm.litellm_core_utils.rules import Rules from litellm.router_utils.common_utils import MID_STREAM_CONTINUATION_KWARG -from litellm.types.llms.openai import AllMessageValues +from litellm.types.llms.openai import AllMessageValues, OutputTextDeltaEvent from litellm.types.utils import ModelResponse, ModelResponseStream, Usage from litellm.utils import supports_assistant_prefill @@ -28,7 +29,9 @@ MID_STREAM_CONTINUATION_MARKER: Final = _ContinuationMarker() _STR_KEYED_DICT_ADAPTER: Final = TypeAdapter(dict[str, object]) _NO_FIELDS: Final[Mapping[str, object]] = MappingProxyType({}) _UNCONSTRAINED_RESPONSE_FORMAT: Final[Mapping[str, str]] = MappingProxyType({"type": "text"}) -_OUTPUT_CEILING_KEYS: Final = ("max_tokens", "max_completion_tokens") +_OUTPUT_CEILING_KEYS: Final = ("max_tokens", "max_completion_tokens", "max_output_tokens") +_QUOTED_ENDING_CHARS: Final = 100 +RESPONSES_CONTINUATION_KWARG: Final = "_responses_continuation" def _str_keyed(value: object) -> Mapping[str, object]: @@ -38,32 +41,55 @@ def _str_keyed(value: object) -> Mapping[str, object]: return _NO_FIELDS -def deployment_supports_prefill(deployment: object) -> bool: +def _underlying_model(deployment: object) -> str | None: deployment_map: Final = _str_keyed(deployment) model_info: Final = _str_keyed(deployment_map.get("model_info")) - declared: Final = model_info.get("supports_assistant_prefill") - if isinstance(declared, bool): - return declared litellm_params: Final = _str_keyed(deployment_map.get("litellm_params")) candidates: Final = (model_info.get("base_model"), litellm_params.get("base_model"), litellm_params.get("model")) - model: Final = next((candidate for candidate in candidates if isinstance(candidate, str) and candidate), None) + return next((candidate for candidate in candidates if isinstance(candidate, str) and candidate), None) + + +def deployment_supports_prefill(deployment: object) -> bool: + declared: Final = _str_keyed(_str_keyed(deployment).get("model_info")).get("supports_assistant_prefill") + if isinstance(declared, bool): + return declared + model: Final = _underlying_model(deployment) return model is not None and supports_assistant_prefill(model=model) -def constrains_continuation(params: Mapping[str, object]) -> bool: +def _forces_tool_call(tool_choice: object) -> bool: + return tool_choice == "required" or isinstance(tool_choice, Mapping) + + +def _forces_responses_tool_call(tool_choice: object) -> bool: + choice: Final = _str_keyed(tool_choice) + leaves_text_open: Final = choice.get("type") == "allowed_tools" and choice.get("mode") == "auto" + return _forces_tool_call(tool_choice) and not leaves_text_open + + +def _constrains(params: Mapping[str, object], forces_tool_call: Callable[[object], bool]) -> bool: sent: Final = {**params, **_str_keyed(params.get("extra_body"))} choice_count: Final = sent.get("n") response_format: Final = sent.get("response_format") - tool_choice: Final = sent.get("tool_choice") + text_format: Final = _str_keyed(sent.get("text")).get("format") return ( (isinstance(choice_count, int) and choice_count > 1) or (response_format is not None and response_format != _UNCONSTRAINED_RESPONSE_FORMAT) - or tool_choice == "required" - or isinstance(tool_choice, Mapping) + or (text_format is not None and text_format != _UNCONSTRAINED_RESPONSE_FORMAT) + or sent.get("text_format") is not None + or forces_tool_call(sent.get("tool_choice")) or sent.get("merge_reasoning_content_in_choices") is True ) +def constrains_continuation(params: Mapping[str, object]) -> bool: + return _constrains(params, _forces_tool_call) + + +def constrains_responses_continuation(params: Mapping[str, object]) -> bool: + return _constrains(params, _forces_responses_tool_call) + + def deployment_can_continue(deployment: object) -> bool: litellm_params: Final = _str_keyed(_str_keyed(deployment).get("litellm_params")) return deployment_supports_prefill(deployment) and not constrains_continuation(litellm_params) @@ -99,6 +125,7 @@ def _delta_text(chunk: ModelResponseStream) -> str: _CONTENT_BLOCKS_ADAPTER: Final = TypeAdapter(list[dict[str, object]]) +_INPUT_ITEMS_ADAPTER: Final = TypeAdapter(list[object]) def _prefill_text(prefill_message: Mapping[str, object]) -> str: @@ -114,7 +141,7 @@ def _prefill_text(prefill_message: Mapping[str, object]) -> str: ) -def _resendable_whitespace(prefill: str) -> str: +def resendable_whitespace(prefill: str) -> str: return prefill[len(prefill.rstrip()) :] if prefill.strip() else "" @@ -124,7 +151,7 @@ def continued_text(prefill_message: Mapping[str, object], generated_content: str return None echo: Final = len(prefill) if prefill and generated_content.startswith(prefill) else 0 after_echo: Final = generated_content[echo:] - return after_echo[len(commonprefix((after_echo, _resendable_whitespace(prefill)))) :] + return after_echo[len(commonprefix((after_echo, resendable_whitespace(prefill)))) :] def _reduced_ceilings(params: Mapping[str, object], emitted_tokens: int) -> Mapping[str, int]: @@ -211,7 +238,7 @@ class ContinuationOutput: self._rules: Final = Rules() self._held: tuple[ModelResponseStream, ...] = () self._echo_settled = not self._prefill_text - self._seam = _resendable_whitespace(self._prefill_text) + self._seam = resendable_whitespace(self._prefill_text) async def splice(self, stream: AsyncIterable[object]) -> AsyncIterator[object]: async for item in stream: @@ -262,3 +289,91 @@ class ContinuationOutput: self._text += _delta_text(chunk) self._rules.post_call_rules(input=self._text, model=self._model) return chunks + + +@dataclass(frozen=True, slots=True) +class ResponsesContinuation: + prior_input: object + emitted_text: str + + def extended(self, generated_content: str) -> "ResponsesContinuation": + return ResponsesContinuation(self.prior_input, f"{self.emitted_text}{generated_content}") + + +def deployment_takes_responses_prefill(deployment: object) -> bool: + """Claude takes a trailing assistant turn as prefill with no `prefix` flag, which a Responses input item cannot + carry.""" + model: Final = _underlying_model(deployment) + return model is not None and "claude" in model.lower() and deployment_supports_prefill(deployment) + + +def _continuation_request(emitted_text: str) -> Mapping[str, object]: + seam: Final = ( + "It already ends with whitespace, so do not add another space before your first word." + if emitted_text[-1:].isspace() + else "It ends without trailing whitespace, so begin with a space if your first word starts a new word." + ) + ending: Final = json.dumps(emitted_text[-_QUOTED_ENDING_CHARS:], ensure_ascii=False) + instruction: Final = ( + f"The previous assistant response was interrupted mid-stream. It ended with {ending}. Continue exactly where " + "it stopped, so your first characters are the ones that would have come right after it, and do not repeat " + f"any of its content. {seam} Your response must read as a seamless continuation." + ) + return {"type": "message", "role": "user", "content": [{"type": "input_text", "text": instruction}]} + + +def _input_items(request_input: object) -> tuple[object, ...]: + if isinstance(request_input, str): + return ({"type": "message", "role": "user", "content": [{"type": "input_text", "text": request_input}]},) + try: + return tuple(_INPUT_ITEMS_ADAPTER.validate_python(request_input)) + except ValidationError: + return () + + +def responses_continuation_input(continuation: ResponsesContinuation) -> Sequence[object]: + """The prior input, the partial response as assistant history, and a user request to continue it.""" + partial: Final = { + "type": "message", + "role": "assistant", + "content": [{"type": "output_text", "text": continuation.emitted_text}], + } + return [*_input_items(continuation.prior_input), partial, _continuation_request(continuation.emitted_text)] + + +def responses_continuation_input_for(request_kwargs: Mapping[str, object], deployment: Mapping[str, object]) -> object: + """The continuation input as the deployment receives it, without the request to continue where the deployment + takes the partial response as prefill. It reads the input the router already stripped of reasoning this + deployment cannot decrypt, never the continuation's prior input.""" + request_input: Final = request_kwargs.get("input") + continuation: Final = request_kwargs.get(RESPONSES_CONTINUATION_KWARG) + if not isinstance(continuation, ResponsesContinuation): + return request_input + items: Final = _input_items(request_input) + if items[-1:] != (_continuation_request(continuation.emitted_text),) or not deployment_takes_responses_prefill( + deployment + ): + return request_input + return list(items[:-1]) + + +_StreamItem = TypeVar("_StreamItem") + + +class ResponsesContinuationSeam: + """Drops whitespace a fallback sends again at the start of its text when the client already has it, since + Anthropic strips a prefill's trailing whitespace and the model then writes it back.""" + + def __init__(self, emitted_text: str) -> None: + self._seam = resendable_whitespace(emitted_text) + + async def splice(self, stream: AsyncIterable[_StreamItem]) -> AsyncIterator[_StreamItem]: + async for item in stream: + yield self._past(item) + + def _past(self, item: _StreamItem) -> _StreamItem: + if not self._seam or not isinstance(item, OutputTextDeltaEvent): + return item + matched: Final = len(commonprefix((item.delta, self._seam))) + self._seam = self._seam[matched:] if matched == len(item.delta) else "" + return item.model_copy(update={"delta": item.delta[matched:]}) if matched else item diff --git a/litellm/router_utils/pre_call_checks/deployment_affinity_check.py b/litellm/router_utils/pre_call_checks/deployment_affinity_check.py index 8693eaa5151..daf7d6bb345 100644 --- a/litellm/router_utils/pre_call_checks/deployment_affinity_check.py +++ b/litellm/router_utils/pre_call_checks/deployment_affinity_check.py @@ -31,6 +31,7 @@ from litellm.caching.dual_cache import DualCache from litellm.constants import SESSION_DEPLOYMENT_AFFINITY_TTL_METADATA_KEY, SESSION_ID_GENERATED_METADATA_KEY from litellm.integrations.custom_logger import CustomLogger, Span from litellm.responses.utils import ResponsesAPIRequestUtils +from litellm.router_utils.common_utils import deployment_ids_failed_in_request from litellm.types.llms.openai import AllMessageValues from litellm.types.utils import CallTypes @@ -429,6 +430,9 @@ class DeploymentAffinityCheck(CustomLogger): session_affinity_active: Final = ( enable_session_id or self._get_marker_session_affinity_ttl(request_kwargs=request_kwargs) is not None ) + failed_deployment_ids: Final = deployment_ids_failed_in_request( + cast(Mapping[str, object], request_kwargs) # cast-ok: request kwargs keys are param names + ) user_key: Final = ( self.get_user_key_from_request_kwargs(request_kwargs=request_kwargs) if (session_affinity_active or enable_user_key) @@ -458,7 +462,7 @@ class DeploymentAffinityCheck(CustomLogger): elif isinstance(session_cache_result, str): session_model_id = session_cache_result - if session_model_id: + if session_model_id and session_model_id not in failed_deployment_ids: session_deployment: Final = self._find_deployment_by_model_id( healthy_deployments=typed_healthy_deployments, model_id=session_model_id, @@ -493,7 +497,7 @@ class DeploymentAffinityCheck(CustomLogger): # Backwards / safety: allow raw string values. model_id = cache_result - if not model_id: + if not model_id or model_id in failed_deployment_ids: return typed_healthy_deployments deployment = self._find_deployment_by_model_id( diff --git a/litellm/router_utils/pre_call_checks/encrypted_content_affinity_check.py b/litellm/router_utils/pre_call_checks/encrypted_content_affinity_check.py index 5d47bf63a38..806c3db7601 100644 --- a/litellm/router_utils/pre_call_checks/encrypted_content_affinity_check.py +++ b/litellm/router_utils/pre_call_checks/encrypted_content_affinity_check.py @@ -51,6 +51,7 @@ from litellm.litellm_core_utils.prompt_templates.common_utils import ( strip_encrypted_reasoning_from_messages, ) from litellm.responses.utils import ResponsesAPIRequestUtils +from litellm.router_utils.common_utils import as_excluded_deployment_ids, as_retry_skipped_deployment_ids from litellm.types.llms.openai import AllMessageValues from litellm.types.router import Deployment from litellm.utils import get_order_filtered_deployments @@ -182,6 +183,14 @@ class EncryptedContentAffinityCheck(CustomLogger): None, ) + @staticmethod + def _deployment_model_id(deployment: Mapping[str, object]) -> str | None: + model_info: Final = deployment.get("model_info") + if not isinstance(model_info, Mapping): + return None + deployment_id: Final = cast(Mapping[str, object], model_info).get("id") # cast-ok: narrowed by isinstance + return None if deployment_id is None else str(deployment_id) + @staticmethod def _find_deployment_by_model_id(healthy_deployments: list[dict], model_id: str) -> dict | None: for deployment in healthy_deployments: @@ -345,7 +354,8 @@ class EncryptedContentAffinityCheck(CustomLogger): typed_healthy_deployments: Final = cast(list[dict[str, object]], healthy_deployments) if not self._is_enabled_for_model_group(model): return typed_healthy_deployments - target_order: Final = _REQUEST_KWARGS_ADAPTER.validate_python(request_kwargs).get("_target_order") + typed_request_kwargs: Final = _REQUEST_KWARGS_ADAPTER.validate_python(request_kwargs) + target_order: Final = typed_request_kwargs.get("_target_order") candidates: Final = ( get_order_filtered_deployments(typed_healthy_deployments, target_order=target_order) if isinstance(target_order, int) @@ -375,8 +385,31 @@ class EncryptedContentAffinityCheck(CustomLogger): model_id, ) + previous_response_id: Final = typed_request_kwargs.get("previous_response_id") + previous_response_origin: Final = ResponsesAPIRequestUtils.get_model_id_from_response_id( + None if previous_response_id is None else str(previous_response_id) + ) + previous_response_binds_origin: Final = previous_response_origin == model_id + excluded_ids: Final[frozenset[str]] = ( + frozenset() + if previous_response_binds_origin + else frozenset(as_excluded_deployment_ids(typed_request_kwargs.get("_excluded_deployment_ids"))) + ) + retry_skipped_ids: Final[frozenset[str]] = ( + frozenset() + if previous_response_binds_origin + else frozenset(as_retry_skipped_deployment_ids(typed_request_kwargs.get("_retry_skipped_deployment_ids"))) + ) + not_excluded_candidates: Final = [ + candidate for candidate in candidates if self._deployment_model_id(candidate) not in excluded_ids + ] + untried_candidates: Final = [ + candidate + for candidate in not_excluded_candidates + if self._deployment_model_id(candidate) not in retry_skipped_ids + ] or not_excluded_candidates deployment: Final = self._find_deployment_by_model_id( - healthy_deployments=candidates, + healthy_deployments=untried_candidates, model_id=model_id, ) if deployment is not None: @@ -392,7 +425,7 @@ class EncryptedContentAffinityCheck(CustomLogger): # Follow-up switched model_name (LIT-2531): pin by Azure resource instead. boundary_matches, _originating = self._find_deployments_on_same_encryption_boundary( - healthy_deployments=candidates, + healthy_deployments=untried_candidates, model_id=model_id, ) if boundary_matches: diff --git a/litellm/router_utils/pre_call_checks/io_token_rate_limit_check.py b/litellm/router_utils/pre_call_checks/io_token_rate_limit_check.py index 2e350a2f87b..0b3d48c9e1d 100644 --- a/litellm/router_utils/pre_call_checks/io_token_rate_limit_check.py +++ b/litellm/router_utils/pre_call_checks/io_token_rate_limit_check.py @@ -22,7 +22,7 @@ from litellm import token_counter from litellm._internal_context import with_service_target from litellm._logging import verbose_router_logger from litellm.caching.dual_cache import DualCache -from litellm.litellm_core_utils.token_counter import offload_token_count +from litellm.litellm_core_utils.token_counter import deployment_openai_model, offload_token_count from litellm.llms.azure.ptu_capacity import is_str_keyed_mapping from litellm.router_utils.routing_read_batch import ROUTER_USAGE_TARGET from litellm.types.router import RouterCacheEnum, RouterErrors @@ -127,6 +127,12 @@ def _get_cache_keys(deployment: dict, current_minute: str) -> tuple[str, str] | return itpm_key, otpm_key +def _tokenizer_model(deployment: object) -> str: + params: Final = deployment.get("litellm_params") if is_str_keyed_mapping(deployment) else None + served: Final = params.get("model") if is_str_keyed_mapping(params) else None + return deployment_openai_model(deployment) or (served if isinstance(served, str) else "") + + def _estimate_input_tokens(request_kwargs: dict[str, Any] | None, model: str = "") -> int: if not request_kwargs: return 0 @@ -427,7 +433,7 @@ def io_token_pre_call_check( return deployment request_kwargs: Final = get_io_token_rate_limit_request_kwargs() - _model: Final = (deployment.get("litellm_params") or {}).get("model") or "" + _model: Final = _tokenizer_model(deployment) estimated_input: Final = _estimate_input_tokens(request_kwargs, model=_model) max_tokens: Final = _resolve_max_tokens(request_kwargs, deployment) @@ -491,7 +497,7 @@ async def async_io_token_pre_call_check( return deployment request_kwargs: Final = get_io_token_rate_limit_request_kwargs() - _model: Final = (deployment.get("litellm_params") or {}).get("model") or "" + _model: Final = _tokenizer_model(deployment) estimated_input: Final = await offload_token_count(_estimate_input_tokens)(request_kwargs, model=_model) max_tokens: Final = _resolve_max_tokens(request_kwargs, deployment) diff --git a/litellm/router_utils/pre_call_checks/model_rate_limit_check.py b/litellm/router_utils/pre_call_checks/model_rate_limit_check.py index ea3fdd601dc..f4b41211c6e 100644 --- a/litellm/router_utils/pre_call_checks/model_rate_limit_check.py +++ b/litellm/router_utils/pre_call_checks/model_rate_limit_check.py @@ -5,15 +5,19 @@ When enabled via router_settings.optional_pre_call_checks: ["enforce_model_rate_ - tpm/rpm: combined TPM + optional RPM (legacy) - itpm/otpm: separate input/output tokens per minute +- tpd/rpd: tokens and requests per UTC calendar day When a deployment sets both itpm/otpm and tpm/rpm, both are enforced. A warning is logged the first time such a deployment is seen. """ import contextlib -from typing import TYPE_CHECKING, Any, Final +from collections.abc import Callable, Mapping +from datetime import datetime, timedelta +from typing import TYPE_CHECKING, Any, Final, Literal import httpx +from pydantic import BaseModel, ConfigDict import litellm from litellm._internal_context import with_service_target @@ -33,7 +37,8 @@ from litellm.router_utils.pre_call_checks.io_token_rate_limit_check import ( io_token_refund_failure, ) from litellm.router_utils.routing_read_batch import ROUTER_USAGE_TARGET -from litellm.types.router import RouterErrors +from litellm.types.caching import RedisPipelineIncrementOperation +from litellm.types.router import RouterErrors, parse_daily_reset_time from litellm.types.utils import StandardLoggingPayload from litellm.utils import get_utc_datetime @@ -47,6 +52,76 @@ else: class RoutingArgs: ttl: int = 60 # 1min (RPM/TPM expire key) + daily_ttl: int = 86400 + + +DAY_FORMAT: Final = "%Y-%m-%d" + + +def daily_window_day(now: datetime, reset_offset: timedelta) -> str: + return (now - reset_offset).strftime(DAY_FORMAT) + + +def seconds_until_daily_reset(now: datetime, reset_offset: timedelta = timedelta(0)) -> int: + window_start: Final = (now - reset_offset).replace(hour=0, minute=0, second=0, microsecond=0) + next_reset: Final = window_start + timedelta(days=1) + reset_offset + return max(1, int((next_reset - now).total_seconds())) + + +class _DailyLimitParams(BaseModel): + """rpd, tpd and daily_reset_time live in litellm_params only.""" + + model_config = ConfigDict(frozen=True, extra="ignore", from_attributes=True) + model: str | None = None + tpd: int | None = None + rpd: int | None = None + daily_reset_time: str | None = None + + def reset_offset(self) -> timedelta: + return parse_daily_reset_time(self.daily_reset_time) + + +class _DailyLimitModelInfo(BaseModel): + model_config = ConfigDict(frozen=True, extra="ignore", from_attributes=True) + id: str | None = None + + +class _DailyLimitDeployment(BaseModel): + model_config = ConfigDict(frozen=True, extra="ignore", from_attributes=True) + model_name: str = "" + litellm_params: _DailyLimitParams = _DailyLimitParams() + model_info: _DailyLimitModelInfo = _DailyLimitModelInfo() + + def limits(self) -> tuple[int | None, int | None]: + return self.litellm_params.tpd, self.litellm_params.rpd + + def reset_offset(self) -> timedelta: + return self.litellm_params.reset_offset() + + def cache_keys(self, now: datetime) -> tuple[str, str]: + prefix: Final = f"{self.model_info.id}:{self.litellm_params.model}" + current_day: Final = daily_window_day(now, self.reset_offset()) + return f"{prefix}:tpd:{current_day}", f"{prefix}:rpd:{current_day}" + + def limit_error(self, kind: Literal["tpd", "rpd"], limit: int, usage: int, now: datetime) -> litellm.RateLimitError: + return litellm.RateLimitError( + message=f"Model rate limit exceeded. {kind.upper()} limit={limit}, current usage={usage}", + llm_provider="", + model=self.litellm_params.model, + response=httpx.Response( + status_code=429, + content=f"{RouterErrors.user_defined_ratelimit_error.value} {kind} limit={limit}. current usage={usage}. id={self.model_info.id}, model_group={self.model_name}", + headers={"retry-after": str(seconds_until_daily_reset(now, self.reset_offset()))}, + request=httpx.Request(method="model_rate_limit_check", url="https://github.com/BerriAI/litellm"), + ), + ) + + +def _reset_offset_from_kwargs(kwargs: Mapping[str, object]) -> timedelta: + litellm_params: Final = kwargs.get("litellm_params") + if litellm_params is None: + return timedelta(0) + return _DailyLimitParams.model_validate(litellm_params).reset_offset() class ModelRateLimitingCheck(CustomLogger): @@ -60,12 +135,60 @@ class ModelRateLimitingCheck(CustomLogger): this check actively enforces those limits across ALL routing strategies. """ - def __init__(self, dual_cache: DualCache): + def __init__(self, dual_cache: DualCache, clock: Callable[[], datetime] = get_utc_datetime): self.dual_cache = dual_cache + self.clock = clock # model_ids already warned about itpm/otpm + tpm/rpm on the same deployment, # so the warning is logged once per deployment rather than per request. self._io_token_conflict_warned_ids: set[str] = set() + def _increment(self, key: str, value: int, ttl: int) -> int: + return self.dual_cache.increment_cache(key=key, value=value, ttl=ttl) + + async def _async_increment( + self, key: str, value: int, ttl: int, parent_otel_span: Span | None = None + ) -> int | None: + count: Final = await self.dual_cache.async_increment_cache( + key=key, value=value, ttl=ttl, parent_otel_span=parent_otel_span + ) + return None if count is None else int(count) + + @staticmethod + def _request_count_operations( + rpm_key: str | None, rpd_key: str | None, increment_value: int + ) -> tuple[RedisPipelineIncrementOperation, ...]: + return tuple( + RedisPipelineIncrementOperation(key=key, increment_value=increment_value, ttl=ttl) + for key, ttl in ((rpm_key, RoutingArgs.ttl), (rpd_key, RoutingArgs.daily_ttl)) + if key is not None + ) + + async def _async_refund_request_counts( + self, rpm_key: str | None, rpd_key: str | None, parent_otel_span: Span | None + ) -> None: + operations: Final = self._request_count_operations(rpm_key, rpd_key, -1) + if operations: + await self.dual_cache.async_increment_cache_pipeline( + increment_list=list(operations), parent_otel_span=parent_otel_span + ) + + async def _async_increment_request_counts( + self, rpm_key: str | None, rpd_key: str | None, parent_otel_span: Span | None + ) -> tuple[int | None, int | None]: + operations: Final = self._request_count_operations(rpm_key, rpd_key, 1) + if not operations: + return None, None + counts: Final = await self.dual_cache.async_increment_cache_pipeline( + increment_list=list(operations), parent_otel_span=parent_otel_span + ) + if counts is None or len(counts) != len(operations): + return None, None + count_by_key: Final = {op["key"]: int(count) for op, count in zip(operations, counts)} + return ( + None if rpm_key is None else count_by_key.get(rpm_key), + None if rpd_key is None else count_by_key.get(rpd_key), + ) + def _warn_io_token_and_tpm_rpm_coexist_once(self, deployment: dict) -> None: tpm_limit, rpm_limit = self._get_deployment_limits(deployment) if tpm_limit is None and rpm_limit is None: @@ -129,6 +252,21 @@ class ModelRateLimitingCheck(CustomLogger): return tpm, rpm + def _check_daily_limits(self, deployment: _DailyLimitDeployment, now: datetime) -> None: + tpd_limit, rpd_limit = deployment.limits() + if tpd_limit is None and rpd_limit is None: + return + tpd_key, rpd_key = deployment.cache_keys(now) + if tpd_limit is not None: + current_tpd: Final = self._get_current_tpm(tpd_key, tpd_limit) + if current_tpd is not None and current_tpd >= tpd_limit: + raise deployment.limit_error("tpd", tpd_limit, current_tpd, now) + if rpd_limit is not None: + current_rpd: Final = self._increment(rpd_key, 1, RoutingArgs.daily_ttl) + if current_rpd > rpd_limit: + self._increment(rpd_key, -1, RoutingArgs.daily_ttl) + raise deployment.limit_error("rpd", rpd_limit, current_rpd, now) + def _get_cache_keys(self, deployment: dict, current_minute: str) -> tuple[str, str]: """Get the cache keys for TPM and RPM tracking.""" model_id: Final = deployment.get("model_info", {}).get("id") @@ -178,13 +316,10 @@ class ModelRateLimitingCheck(CustomLogger): ) io_reservation_made = True + dt: Final = self.clock() + daily: Final = _DailyLimitDeployment.model_validate(deployment) tpm_limit, rpm_limit = self._get_deployment_limits(deployment) - # If no limits are set, allow the request - if tpm_limit is None and rpm_limit is None: - return deployment - - dt: Final = get_utc_datetime() current_minute: Final = dt.strftime("%H-%M") tpm_key, rpm_key = self._get_cache_keys(deployment, current_minute) @@ -213,8 +348,9 @@ class ModelRateLimitingCheck(CustomLogger): # Check RPM limit (atomic increment-first to avoid race conditions) if rpm_limit is not None: - current_rpm: Final = self.dual_cache.increment_cache(key=rpm_key, value=1, ttl=RoutingArgs.ttl) + current_rpm: Final = self._increment(rpm_key, 1, RoutingArgs.ttl) if current_rpm is not None and current_rpm > rpm_limit: + self._increment(rpm_key, -1, RoutingArgs.ttl) raise litellm.RateLimitError( message=f"Model rate limit exceeded. RPM limit={rpm_limit}, current usage={current_rpm}", llm_provider="", @@ -230,6 +366,12 @@ class ModelRateLimitingCheck(CustomLogger): ), ) + try: + self._check_daily_limits(daily, dt) + except litellm.RateLimitError: + if rpm_limit is not None: + self._increment(rpm_key, -1, RoutingArgs.ttl) + raise return deployment except litellm.RateLimitError: @@ -259,15 +401,14 @@ class ModelRateLimitingCheck(CustomLogger): ) io_reservation_made = True + dt: Final = self.clock() + daily: Final = _DailyLimitDeployment.model_validate(deployment) + tpd_limit, rpd_limit = daily.limits() tpm_limit, rpm_limit = self._get_deployment_limits(deployment) - # If no limits are set, allow the request - if tpm_limit is None and rpm_limit is None: - return deployment - - dt: Final = get_utc_datetime() current_minute: Final = dt.strftime("%H-%M") tpm_key, rpm_key = self._get_cache_keys(deployment, current_minute) + tpd_key, rpd_key = daily.cache_keys(dt) model_id: Final = deployment.get("model_info", {}).get("id") model_name: Final = deployment.get("litellm_params", {}).get("model") @@ -293,30 +434,37 @@ class ModelRateLimitingCheck(CustomLogger): num_retries=0, # Don't retry - return 429 immediately ) - # Check RPM limit (atomic increment-first to avoid race conditions) - if rpm_limit is not None: - current_rpm: Final = await self.dual_cache.async_increment_cache( - key=rpm_key, - value=1, - ttl=RoutingArgs.ttl, - parent_otel_span=parent_otel_span, - ) - if current_rpm is not None and current_rpm > rpm_limit: - raise litellm.RateLimitError( - message=f"Model rate limit exceeded. RPM limit={rpm_limit}, current usage={current_rpm}", - llm_provider="", - model=model_name, - response=httpx.Response( - status_code=429, - content=f"{RouterErrors.user_defined_ratelimit_error.value} rpm limit={rpm_limit}. current usage={current_rpm}. id={model_id}, model_group={model_group}", - headers={"retry-after": str(60)}, - request=httpx.Request( - method="model_rate_limit_check", - url="https://github.com/BerriAI/litellm", - ), + if tpd_limit is not None: + current_tpd: Final = await self._async_get_current_tpm(tpd_key, tpd_limit, parent_otel_span) + if current_tpd is not None and current_tpd >= tpd_limit: + raise daily.limit_error("tpd", tpd_limit, current_tpd, dt) + + charged_rpm_key: Final = rpm_key if rpm_limit is not None else None + charged_rpd_key: Final = rpd_key if rpd_limit is not None else None + current_rpm, current_rpd = await self._async_increment_request_counts( + charged_rpm_key, charged_rpd_key, parent_otel_span + ) + if rpm_limit is not None and current_rpm is not None and current_rpm > rpm_limit: + await self._async_refund_request_counts(charged_rpm_key, charged_rpd_key, parent_otel_span) + raise litellm.RateLimitError( + message=f"Model rate limit exceeded. RPM limit={rpm_limit}, current usage={current_rpm}", + llm_provider="", + model=model_name, + response=httpx.Response( + status_code=429, + content=f"{RouterErrors.user_defined_ratelimit_error.value} rpm limit={rpm_limit}. current usage={current_rpm}. id={model_id}, model_group={model_group}", + headers={"retry-after": str(60)}, + request=httpx.Request( + method="model_rate_limit_check", + url="https://github.com/BerriAI/litellm", ), - num_retries=0, # Don't retry - return 429 immediately - ) + ), + num_retries=0, # Don't retry - return 429 immediately + ) + + if rpd_limit is not None and current_rpd is not None and current_rpd > rpd_limit: + await self._async_refund_request_counts(charged_rpm_key, charged_rpd_key, parent_otel_span) + raise daily.limit_error("rpd", rpd_limit, current_rpd, dt) return deployment @@ -373,17 +521,17 @@ class ModelRateLimitingCheck(CustomLogger): if not model or not total_tokens: return - dt: Final = get_utc_datetime() + dt: Final = self.clock() current_minute: Final = dt.strftime("%H-%M") tpm_key: Final = f"{model_id}:{model}:tpm:{current_minute}" + reset_offset: Final = _reset_offset_from_kwargs(kwargs) # pyright: ignore[reportUnknownArgumentType] # CustomLogger passes an untyped kwargs dict + tpd_key: Final = f"{model_id}:{model}:tpd:{daily_window_day(dt, reset_offset)}" verbose_router_logger.debug("[TPM TRACKING] Incrementing %s by %s", tpm_key, total_tokens) - await self.dual_cache.async_increment_cache( - key=tpm_key, - value=total_tokens, - ttl=RoutingArgs.ttl, - ) + tokens: Final = int(total_tokens) + await self._async_increment(tpm_key, tokens, RoutingArgs.ttl) + await self._async_increment(tpd_key, tokens, RoutingArgs.daily_ttl) except Exception as e: verbose_router_logger.debug("Error in ModelRateLimitingCheck.async_log_success_event: %s", e) @@ -434,15 +582,15 @@ class ModelRateLimitingCheck(CustomLogger): if not model or not total_tokens: return - dt: Final = get_utc_datetime() + dt: Final = self.clock() current_minute: Final = dt.strftime("%H-%M") tpm_key: Final = f"{model_id}:{model}:tpm:{current_minute}" + reset_offset: Final = _reset_offset_from_kwargs(kwargs) # pyright: ignore[reportUnknownArgumentType] # CustomLogger passes an untyped kwargs dict + tpd_key: Final = f"{model_id}:{model}:tpd:{daily_window_day(dt, reset_offset)}" - self.dual_cache.increment_cache( - key=tpm_key, - value=total_tokens, - ttl=RoutingArgs.ttl, - ) + tokens: Final = int(total_tokens) + self._increment(tpm_key, tokens, RoutingArgs.ttl) + self._increment(tpd_key, tokens, RoutingArgs.daily_ttl) except Exception as e: verbose_router_logger.debug("Error in ModelRateLimitingCheck.log_success_event: %s", e) diff --git a/litellm/router_utils/pre_call_checks/prompt_caching_deployment_check.py b/litellm/router_utils/pre_call_checks/prompt_caching_deployment_check.py index bb3475cdcbe..c04bab4d360 100644 --- a/litellm/router_utils/pre_call_checks/prompt_caching_deployment_check.py +++ b/litellm/router_utils/pre_call_checks/prompt_caching_deployment_check.py @@ -19,6 +19,7 @@ from litellm.integrations.anthropic_cache_control_hook import ( from litellm.integrations.custom_logger import CustomLogger, Span from litellm.litellm_core_utils.token_counter import offload_token_count from litellm.llms.bedrock.common_utils import bedrock_cache_point_ttl_supported, bedrock_capability_model +from litellm.router_utils.common_utils import deployment_ids_failed_in_request from litellm.types.llms.openai import AllMessageValues, ChatCompletionToolParam from litellm.types.utils import CallTypes, StandardLoggingPayload from litellm.utils import ( @@ -152,7 +153,9 @@ class PromptCachingDeploymentCheck(CustomLogger): request_tools, ), ) - if model_id_dict is not None: + if model_id_dict is not None and model_id_dict["model_id"] not in deployment_ids_failed_in_request( + request_data or {} + ): model_id: Final = model_id_dict["model_id"] for deployment in healthy_deployments: if deployment["model_info"]["id"] == model_id: diff --git a/litellm/router_utils/request_priority.py b/litellm/router_utils/request_priority.py index 14608cc1bcf..61627d4b0cf 100644 --- a/litellm/router_utils/request_priority.py +++ b/litellm/router_utils/request_priority.py @@ -47,6 +47,15 @@ def resolve_request_priority( return priority +def priority_header_fields(header: str | None, drops_params: Callable[[], bool]) -> Mapping[str, int | str]: + if not header: + return {} + priority: Final = _as_priority(header) + if isinstance(priority, InvalidPriority): + return {} if drops_params() else {"priority": header} + return {"priority": priority} + + def parse_default_priority(value: object) -> int | None | InvalidPriority: if value is None: return None diff --git a/litellm/router_utils/search_api_router.py b/litellm/router_utils/search_api_router.py index 1cfb311d796..26326a7e6d4 100644 --- a/litellm/router_utils/search_api_router.py +++ b/litellm/router_utils/search_api_router.py @@ -155,10 +155,9 @@ class SearchAPIRouter: available_search_tool_names: Final = [tool.get("search_tool_name") for tool in router_instance.search_tools] verbose_router_logger.debug( - "Inside SearchAPIRouter.async_search_with_fallbacks() - search_tool_name: %s, Available Search Tools: %s, kwargs: %s", + "Inside SearchAPIRouter.async_search_with_fallbacks() - search_tool_name: %s, Available Search Tools: %s", search_tool_name, available_search_tool_names, - kwargs, ) # Use the existing retry/fallback infrastructure diff --git a/litellm/rust_bridge/AGENTS.md b/litellm/rust_bridge/AGENTS.md index c197b21bad0..c2a030ca4d9 100644 --- a/litellm/rust_bridge/AGENTS.md +++ b/litellm/rust_bridge/AGENTS.md @@ -46,6 +46,12 @@ - A failure after execution starts is terminal and never triggers fallback - Creating an unstarted native coroutine acquires no clients or credentials and captures no execution context +# Native extension + +- `_native` ships in every wheel and the sdist builds it, so it is always importable +- Import it with `from litellm.rust_bridge import _native` and use the attributes `_native.pyi` declares +- Never add a `None` branch, `getattr` default or stand-in class for a missing extension + # Verification - Check cross-language behavior against a freshly installed extension, covering unstarted-call release, setup ordering, exception identity, sync and async streams, cancellation and GC diff --git a/litellm/rust_bridge/__init__.py b/litellm/rust_bridge/__init__.py index 8f6f4390b8a..52cc3c8cff1 100644 --- a/litellm/rust_bridge/__init__.py +++ b/litellm/rust_bridge/__init__.py @@ -1,10 +1,5 @@ """LiteLLM Rust bridge package.""" from litellm.rust_bridge.configuration import rust -from litellm.rust_bridge.loader import ( - get_native_bridge, - native_bridge_available, - reset_native_bridge_cache, -) -__all__ = ["get_native_bridge", "native_bridge_available", "reset_native_bridge_cache", "rust"] +__all__ = ["rust"] diff --git a/litellm/rust_bridge/bindings.py b/litellm/rust_bridge/bindings.py index d16f150a2aa..91570c6a8bc 100644 --- a/litellm/rust_bridge/bindings.py +++ b/litellm/rust_bridge/bindings.py @@ -3,7 +3,7 @@ from __future__ import annotations from collections.abc import Callable from typing import Final, Generic, TypeVar -from litellm.rust_bridge.loader import get_native_bridge +from litellm.rust_bridge import _native BindingT = TypeVar("BindingT") @@ -18,32 +18,24 @@ _UNSET: Final = _Unset() class NativeBinding(Generic[BindingT]): """Resolve one native attribute with an explicit, resettable test override.""" - def __init__(self, attribute: str, *, validate: Callable[[object], BindingT | None]) -> None: + def __init__( + self, attribute: str, *, validate: Callable[[object], BindingT | None], source: object = _native + ) -> None: self._attribute: Final = attribute self._validate: Final = validate + self._source: Final = source self._override: BindingT | None | _Unset = _UNSET def load(self) -> BindingT | None: if not isinstance(self._override, _Unset): return self._override - native: Final = get_native_bridge() - if native is None: - return None - return self._validate(getattr(native, self._attribute, None)) + return self._validate(getattr(self._source, self._attribute, None)) + + def with_source(self, source: object) -> NativeBinding[BindingT]: + return NativeBinding(self._attribute, validate=self._validate, source=source) def override(self, value: BindingT | None) -> None: self._override = value def reset(self) -> None: self._override = _UNSET - - -def native_exception_types() -> tuple[type[BaseException], type[BaseException]] | None: - native: Final = get_native_bridge() - if native is None: - return None - declined: Final = getattr(native, "RustBridgeDeclined", None) - upstream: Final = getattr(native, "RustUpstreamError", None) - if not isinstance(declined, type) or not isinstance(upstream, type): - return None - return declined, upstream diff --git a/litellm/rust_bridge/catalog.py b/litellm/rust_bridge/catalog.py index 74cd28161a4..fe52f8416d0 100644 --- a/litellm/rust_bridge/catalog.py +++ b/litellm/rust_bridge/catalog.py @@ -96,6 +96,8 @@ class Feature(str, Enum): """litellm.include_cost_in_streaming_usage, where Python adds cost to streamed usage.""" THINKING_SIGNATURE_RETRY = "thinking_signature_retry" """Replayed thinking blocks, which Python strips and retries once if Anthropic rejects their signature.""" + TOOL_CUSTOM_FIELD = "tool_custom_field" + """Tools carrying a non-spec custom object, which Python drops or hoists for the provider.""" CLIENT_HEADERS = "client_headers" """Proxy-forwarded headers that Python merges into extra_headers.""" DEPLOYMENT_HOOK = "deployment_hook" @@ -176,6 +178,7 @@ MESSAGES_PYTHON_FEATURES: Final = COMMON_PYTHON_FEATURES | { Feature.CACHE_CONTROL_INJECTION, Feature.STREAM_COST_INJECTION, Feature.THINKING_SIGNATURE_RETRY, + Feature.TOOL_CUSTOM_FIELD, } RESPONSES_PYTHON_FEATURES: Final = COMMON_PYTHON_FEATURES | { diff --git a/litellm/rust_bridge/clickhouse.py b/litellm/rust_bridge/clickhouse.py index cf2c8fdd3e2..fe2809ef856 100644 --- a/litellm/rust_bridge/clickhouse.py +++ b/litellm/rust_bridge/clickhouse.py @@ -1,12 +1,10 @@ import os -from collections.abc import Awaitable, Mapping, Sequence +from collections.abc import Mapping, Sequence from dataclasses import dataclass -from typing import Final, Protocol, runtime_checkable - -from pydantic import ConfigDict, TypeAdapter +from typing import Final from litellm.constants import DEFAULT_AGENT_TRACING_RETENTION_DAYS, DEFAULT_CLICKHOUSE_DATABASE -from litellm.rust_bridge.loader import get_native_bridge +from litellm.rust_bridge import _native @dataclass(frozen=True, slots=True, repr=False) @@ -16,27 +14,6 @@ class SpendStorageConfig: retention_days: int = DEFAULT_AGENT_TRACING_RETENTION_DAYS -class NativeSpendConfig(Protocol): - def __init__(self, database: str, url: str, retention_days: int) -> None: ... - - -class NativeSpendStorage(Protocol): - def __init__(self, config: NativeSpendConfig) -> None: ... - def ensure_schema(self) -> Awaitable[None]: ... - def insert_rows(self, rows: Sequence[Mapping[str, object]]) -> Awaitable[None]: ... - - -@runtime_checkable -class NativeSpendBridge(Protocol): - NativeClickHouseSpendConfig: type[NativeSpendConfig] - NativeClickHouseSpendStorage: type[NativeSpendStorage] - - -_NATIVE: Final[TypeAdapter[NativeSpendBridge]] = TypeAdapter( - NativeSpendBridge, config=ConfigDict(arbitrary_types_allowed=True) -) - - def spend_storage_config(environ: Mapping[str, str] = os.environ) -> SpendStorageConfig: url: Final = environ.get("CLICKHOUSE_URL") if not url: @@ -53,12 +30,8 @@ def spend_storage_config(environ: Mapping[str, str] = os.environ) -> SpendStorag class ClickHouseSpendStorage: def __init__(self, config: SpendStorageConfig) -> None: - bridge: Final = get_native_bridge() - if bridge is None: - raise RuntimeError("ClickHouse spend logging requires the Rust extension") - native: Final = _NATIVE.validate_python(bridge) - self._native: Final = native.NativeClickHouseSpendStorage( - native.NativeClickHouseSpendConfig(config.database, config.url, config.retention_days) + self._native: Final = _native.NativeClickHouseSpendStorage( + _native.NativeClickHouseSpendConfig(config.database, config.url, config.retention_days) ) async def ensure_schema(self) -> None: diff --git a/litellm/rust_bridge/fork_guard.py b/litellm/rust_bridge/fork_guard.py index c94665fb8db..82eb5c96295 100644 --- a/litellm/rust_bridge/fork_guard.py +++ b/litellm/rust_bridge/fork_guard.py @@ -11,32 +11,22 @@ site, so the runtime can never start there. Workers forked from it are unaffecte from __future__ import annotations +from collections.abc import Callable from typing import Final -from litellm.rust_bridge.loader import get_native_bridge +from litellm.rust_bridge import _native class NativeStateStartedBeforeFork(RuntimeError): pass -class _NeverRaised(RuntimeError): - """Stands in for a native exception when the extension is unavailable or predates it.""" +ForkedAfterNativeRuntimeStarted: Final = _native.ForkedAfterNativeRuntimeStarted +ProcessReservedForForking: Final = _native.ProcessReservedForForking -_native: Final = get_native_bridge() -ForkedAfterNativeRuntimeStarted: Final[type[RuntimeError]] = getattr( - _native, "ForkedAfterNativeRuntimeStarted", _NeverRaised -) -ProcessReservedForForking: Final[type[RuntimeError]] = getattr(_native, "ProcessReservedForForking", _NeverRaised) - - -def reserve_process_for_forking(where: str) -> None: +def reserve_process_for_forking(where: str, reserve: Callable[[], None] = _native.reserve_process_for_forking) -> None: """Forbid native routes in this process. Raises if one already ran here.""" - native: Final = get_native_bridge() - reserve: Final = getattr(native, "reserve_process_for_forking", None) - if not callable(reserve): - return try: reserve() except RuntimeError as error: diff --git a/litellm/rust_bridge/host/routes/ocr.py b/litellm/rust_bridge/host/routes/ocr.py index 8f563a381ef..827d0ecbbe0 100644 --- a/litellm/rust_bridge/host/routes/ocr.py +++ b/litellm/rust_bridge/host/routes/ocr.py @@ -7,12 +7,13 @@ from typing import Final from pydantic import TypeAdapter import litellm +from litellm.litellm_core_utils.core_helpers import drops_unsupported_params from litellm.llms.base_llm.ocr.transformation import PROVIDER_NATIVE_RESPONSE_KEY, OCRResponse from litellm.rust_bridge import failures from litellm.rust_bridge.failures import UpstreamFailure from litellm.rust_bridge.public_call import optional_str -__all__ = ("UpstreamFailure", "map_failure", "response") +__all__ = ("UpstreamFailure", "drops_unsupported_params", "map_failure", "response") _RESPONSE_ADAPTER: Final = TypeAdapter(dict[str, object]) diff --git a/litellm/rust_bridge/loader.py b/litellm/rust_bridge/loader.py deleted file mode 100644 index 022c38f5a85..00000000000 --- a/litellm/rust_bridge/loader.py +++ /dev/null @@ -1,35 +0,0 @@ -"""Loader for the packaged LiteLLM Rust extension.""" - -from __future__ import annotations - -from types import ModuleType -from typing import Final - -_BRIDGE_SENTINEL: Final = object() -_cached_bridge: ModuleType | None | object = _BRIDGE_SENTINEL - - -def get_native_bridge() -> ModuleType | None: - """Return the packaged Rust extension, or ``None`` when unavailable.""" - global _cached_bridge - if _cached_bridge is not _BRIDGE_SENTINEL: - return _cached_bridge if isinstance(_cached_bridge, ModuleType) else None - - try: - from litellm.rust_bridge import _native - except ImportError: - _cached_bridge = None - return None - _cached_bridge = _native - return _native - - -def reset_native_bridge_cache() -> None: - """Forget the cached extension so the next lookup reimports it from disk.""" - global _cached_bridge - _cached_bridge = _BRIDGE_SENTINEL - - -def native_bridge_available() -> bool: - """Whether the packaged Rust extension is importable.""" - return get_native_bridge() is not None diff --git a/litellm/rust_bridge/messages/detectors.py b/litellm/rust_bridge/messages/detectors.py index 5f75858d350..52917126b3b 100644 --- a/litellm/rust_bridge/messages/detectors.py +++ b/litellm/rust_bridge/messages/detectors.py @@ -43,6 +43,11 @@ def thinking_signature_retry(request: NativeCall) -> bool: return any(_replays_thinking(message) for message in optional_sequence(request.resolved.get("messages")) or ()) +def tool_custom_field(request: NativeCall) -> bool: + tools: Final = optional_sequence(request.resolved.get("tools")) or () + return any("custom" in (optional_mapping(tool) or {}) for tool in tools) + + def stream_cost_injection(request: NativeCall) -> bool: """Python adds response cost to streaming usage when the global setting is truthy.""" return streaming(request) and bool(litellm.include_cost_in_streaming_usage) diff --git a/litellm/rust_bridge/responses/websocket.py b/litellm/rust_bridge/responses/websocket.py index f10631958bb..83a1fa53376 100644 --- a/litellm/rust_bridge/responses/websocket.py +++ b/litellm/rust_bridge/responses/websocket.py @@ -2,32 +2,33 @@ from __future__ import annotations +from collections.abc import Awaitable from dataclasses import dataclass from typing import Final, Protocol import httpx from websockets.exceptions import ConnectionClosedOK +from litellm.rust_bridge import _native from litellm.rust_bridge.host.timeouts import timeout_to_seconds -from litellm.rust_bridge.loader import get_native_bridge class RustResponsesWebSocket(Protocol): - async def send_text(self, text: str) -> None: ... + def send_text(self, text: str) -> Awaitable[None]: ... - async def recv_text(self) -> str | None: ... + def recv_text(self) -> Awaitable[str | None]: ... - async def close(self) -> None: ... + def close(self) -> Awaitable[None]: ... class RustResponsesWebSocketConnection(Protocol): @classmethod - async def connect( + def connect( cls, url: str, headers: dict[str, str], timeout_seconds: float | None, - ) -> RustResponsesWebSocket: ... + ) -> Awaitable[RustResponsesWebSocket]: ... class _Unset: @@ -53,16 +54,10 @@ def set_rust_responses_websocket( _STATE.connection = connection -def load_rust_responses_websocket() -> RustResponsesWebSocketConnection | None: +def load_rust_responses_websocket() -> RustResponsesWebSocketConnection: if _STATE.connection is not None: return _STATE.connection - native_bridge: Final = get_native_bridge() - if native_bridge is None: - return None - connection_type: Final[RustResponsesWebSocketConnection | None] = getattr( - native_bridge, "ResponsesWebSocketConnection", None - ) - return connection_type + return _native.ResponsesWebSocketConnection class _ConnectionAdapter: @@ -89,8 +84,6 @@ async def connect( timeout: float | httpx.Timeout | None, ) -> _ConnectionAdapter | None: connection_type: Final = load_rust_responses_websocket() - if connection_type is None: - return None try: connection: Final = await connection_type.connect( url=url, diff --git a/litellm/rust_bridge/runtime.py b/litellm/rust_bridge/runtime.py index cf632c09074..e22ebe73b08 100644 --- a/litellm/rust_bridge/runtime.py +++ b/litellm/rust_bridge/runtime.py @@ -7,7 +7,8 @@ from typing import Final, Generic, NoReturn, TypeAlias, TypeVar from typing_extensions import assert_never from litellm.exceptions import APIError -from litellm.rust_bridge.bindings import NativeBinding, native_exception_types +from litellm.rust_bridge import _native +from litellm.rust_bridge.bindings import NativeBinding from litellm.rust_bridge.catalog import RouteContext, Rules, decision from litellm.rust_bridge.configuration import Decision from litellm.rust_bridge.response_metadata import mark_rust_response @@ -153,15 +154,11 @@ def attempt( ) -> RustAttempt[ResultT]: if native_call is None: return RustUnavailable() - exceptions: Final = native_exception_types() - if exceptions is None: - return RustHandled(adapt(native_call())) - declined, upstream = exceptions try: value: Final = native_call() - except declined as error: + except _native.RustBridgeDeclined as error: return RustDeclined(reason=_decline_reason(error)) - except upstream as error: + except _native.RustUpstreamError as error: _raise_upstream(error, context) return RustHandled(adapt(value)) @@ -174,15 +171,11 @@ async def aattempt( ) -> RustAttempt[ResultT]: if native_call is None: return RustUnavailable() - exceptions: Final = native_exception_types() - if exceptions is None: - return RustHandled(adapt(await native_call())) - declined, upstream = exceptions try: value: Final = await native_call() - except declined as error: + except _native.RustBridgeDeclined as error: return RustDeclined(reason=_decline_reason(error)) - except upstream as error: + except _native.RustUpstreamError as error: _raise_upstream(error, context) return RustHandled(adapt(value)) diff --git a/litellm/secret_managers/aws_secret_manager_v2.py b/litellm/secret_managers/aws_secret_manager_v2.py index 98d12e497da..de8566e6fdc 100644 --- a/litellm/secret_managers/aws_secret_manager_v2.py +++ b/litellm/secret_managers/aws_secret_manager_v2.py @@ -21,6 +21,8 @@ from types import MappingProxyType from typing import TYPE_CHECKING, Final import httpx +from pydantic import ConfigDict, TypeAdapter, with_config +from typing_extensions import ReadOnly, TypedDict import litellm from litellm._logging import verbose_logger @@ -41,6 +43,15 @@ if TYPE_CHECKING: from botocore.awsrequest import HTTPHeaders +@with_config(ConfigDict(extra="allow", strict=True)) +class _SecretStringResponse(TypedDict): + SecretString: ReadOnly[str] + + +_SECRET_STRING_RESPONSE: Final = TypeAdapter(_SecretStringResponse) +_AWS_SECRET_MANAGER_RESPONSE: Final = TypeAdapter(dict[str, object], config=ConfigDict(strict=True)) + + class AWSSecretsManagerV2(BaseAWSLLM, BaseSecretManager): def __init__( self, @@ -154,7 +165,7 @@ class AWSSecretsManagerV2(BaseAWSLLM, BaseSecretManager): try: response: Final = await async_client.post(url=endpoint_url, headers=headers, data=body.decode("utf-8")) response.raise_for_status() - return response.json()["SecretString"] + return _SECRET_STRING_RESPONSE.validate_python(response.json())["SecretString"] except httpx.TimeoutException: raise ValueError("Timeout error occurred") except Exception as e: @@ -204,7 +215,7 @@ class AWSSecretsManagerV2(BaseAWSLLM, BaseSecretManager): try: response: Final = sync_client.post(url=endpoint_url, headers=headers, data=body.decode("utf-8")) - return response.json()["SecretString"] + return _SECRET_STRING_RESPONSE.validate_python(response.json())["SecretString"] except httpx.TimeoutException: raise ValueError("Timeout error occurred") except httpx.HTTPStatusError as e: @@ -424,7 +435,7 @@ class AWSSecretsManagerV2(BaseAWSLLM, BaseSecretManager): try: response: Final = await async_client.post(url=endpoint_url, headers=headers, data=body.decode("utf-8")) response.raise_for_status() - return response.json() + return _AWS_SECRET_MANAGER_RESPONSE.validate_python(response.json()) except httpx.HTTPStatusError as err: raise ValueError(f"HTTP error occurred: {err.response.text}") except httpx.TimeoutException: @@ -481,7 +492,7 @@ class AWSSecretsManagerV2(BaseAWSLLM, BaseSecretManager): try: response: Final = await async_client.post(url=endpoint_url, headers=headers, data=body.decode("utf-8")) response.raise_for_status() - return response.json() + return _AWS_SECRET_MANAGER_RESPONSE.validate_python(response.json()) except httpx.HTTPStatusError as err: raise ValueError(f"HTTP error occurred: {err.response.text}") except httpx.TimeoutException: @@ -533,7 +544,7 @@ class AWSSecretsManagerV2(BaseAWSLLM, BaseSecretManager): try: response: Final = await async_client.post(url=endpoint_url, headers=headers, data=body.decode("utf-8")) response.raise_for_status() - return response.json() + return _AWS_SECRET_MANAGER_RESPONSE.validate_python(response.json()) except httpx.HTTPStatusError as err: raise ValueError(f"HTTP error occurred: {err.response.text}") except httpx.TimeoutException: @@ -613,7 +624,7 @@ class AWSSecretsManagerV2(BaseAWSLLM, BaseSecretManager): try: response: Final = await async_client.post(url=endpoint_url, headers=headers, data=body.decode("utf-8")) response.raise_for_status() - return response.json() + return _AWS_SECRET_MANAGER_RESPONSE.validate_python(response.json()) except httpx.HTTPStatusError as err: raise ValueError(f"HTTP error occurred: {err.response.text}") except httpx.TimeoutException: diff --git a/litellm/secret_managers/get_azure_ad_token_provider.py b/litellm/secret_managers/get_azure_ad_token_provider.py index 2b707f179d0..4967e199218 100644 --- a/litellm/secret_managers/get_azure_ad_token_provider.py +++ b/litellm/secret_managers/get_azure_ad_token_provider.py @@ -1,14 +1,27 @@ import os +import time from collections.abc import Callable +from dataclasses import dataclass +from types import TracebackType from typing import TYPE_CHECKING, Final from litellm._logging import verbose_logger +from litellm.litellm_core_utils.single_flight import SingleFlight from litellm.types.secret_managers.get_azure_ad_token_provider import ( AzureCredentialType, ) +_HELD_TOKEN_EXPIRY_MARGIN_SECONDS: Final = 60 + if TYPE_CHECKING: - from azure.core.credentials import TokenProvider + from azure.core.credentials import ( + AccessToken, + AccessTokenInfo, + SupportsTokenInfo, + TokenCredential, + TokenRequestOptions, + ) + from typing_extensions import TypeIs # noqa: TID251 # tells the two azure-core credential protocols apart def infer_credential_type_from_environment() -> AzureCredentialType: @@ -37,6 +50,86 @@ def infer_credential_type_from_environment() -> AzureCredentialType: return AzureCredentialType.DefaultAzureCredential +@dataclass(slots=True) +class _HeldToken: + token: "AccessToken | AccessTokenInfo | None" = None + + def still_valid(self) -> str | None: + held: Final = self.token + if held is None or held.expires_on - time.time() <= _HELD_TOKEN_EXPIRY_MARGIN_SECONDS: + return None + return held.token + + +@dataclass(slots=True) +class _TokenInfoWatcher: + credential: "SupportsTokenInfo" + held: _HeldToken + + def get_token_info(self, *scopes: str, options: "TokenRequestOptions | None" = None) -> "AccessTokenInfo": + token: Final = self.credential.get_token_info(*scopes, options=options) + self.held.token = token + return token + + def close(self) -> None: + self.credential.close() + + def __enter__(self) -> "SupportsTokenInfo": + return self.credential.__enter__() + + def __exit__( + self, + exc_type: type[BaseException] | None, + exc_value: BaseException | None, + traceback: TracebackType | None, + ) -> None: + self.credential.__exit__(exc_type, exc_value, traceback) + + +@dataclass(slots=True) +class _TokenWatcher: + credential: "TokenCredential" + held: _HeldToken + + def get_token( + self, + *scopes: str, + claims: str | None = None, + tenant_id: str | None = None, + enable_cae: bool = False, + **kwargs: object, # kwargs-ok: azure-core forwards its request options verbatim to the wrapped credential + ) -> "AccessToken": + token: Final = self.credential.get_token( + *scopes, claims=claims, tenant_id=tenant_id, enable_cae=enable_cae, **kwargs + ) + self.held.token = token + return token + + +def _supports_token_info( + credential: "TokenCredential | SupportsTokenInfo", +) -> "TypeIs[SupportsTokenInfo]": + return hasattr(credential, "get_token_info") + + +def single_flight_bearer_token_provider( + credential: "TokenCredential | SupportsTokenInfo", scope: str +) -> Callable[[], str]: + from azure.identity import get_bearer_token_provider + + held: Final = _HeldToken() + watched: Final = ( + _TokenInfoWatcher(credential, held) if _supports_token_info(credential) else _TokenWatcher(credential, held) + ) + provider: Final = get_bearer_token_provider(watched, scope) + token_request: Final[SingleFlight[str]] = SingleFlight() + + def bearer_token() -> str: + return token_request.run(provider, while_busy=held.still_valid()) + + return bearer_token + + def get_azure_ad_token_provider( azure_scope: str | None = None, azure_credential: AzureCredentialType | None = None, @@ -65,7 +158,6 @@ def get_azure_ad_token_provider( DefaultAzureCredential, ManagedIdentityCredential, WorkloadIdentityCredential, - get_bearer_token_provider, ) if azure_scope is None: @@ -77,7 +169,7 @@ def get_azure_ad_token_provider( else None or os.environ.get("AZURE_CREDENTIAL") or infer_credential_type_from_environment() ) verbose_logger.info("For Azure AD Token Provider, choosing credential type: %s", cred) - credential: TokenProvider | None = None + credential: TokenCredential | SupportsTokenInfo | None = None if cred == AzureCredentialType.ClientSecretCredential: credential = ClientSecretCredential( client_id=os.environ["AZURE_CLIENT_ID"], @@ -133,4 +225,4 @@ def get_azure_ad_token_provider( if credential is None: raise ValueError("No credential provided") - return get_bearer_token_provider(credential, azure_scope) + return single_flight_bearer_token_provider(credential, azure_scope) diff --git a/litellm/secret_managers/main.py b/litellm/secret_managers/main.py index b33cf0e6b7e..588bdb1409c 100644 --- a/litellm/secret_managers/main.py +++ b/litellm/secret_managers/main.py @@ -5,7 +5,6 @@ import time import traceback from collections.abc import Callable from dataclasses import dataclass -from functools import lru_cache from typing import Final import httpx @@ -14,6 +13,7 @@ from pydantic import TypeAdapter, ValidationError import litellm from litellm._logging import verbose_logger from litellm.caching.caching import DualCache +from litellm.litellm_core_utils.single_flight import single_flight_lru_cache from litellm.llms.custom_httpx.http_handler import HTTPHandler from litellm.secret_managers.get_azure_ad_token_provider import ( get_azure_ad_token_provider, @@ -27,7 +27,7 @@ _PARSED_LITERAL: Final = TypeAdapter(object) _SECRET_MANAGER_CLIENT: Final = TypeAdapter(object) -@lru_cache(maxsize=128) +@single_flight_lru_cache def _cached_azure_oidc_token_provider(audience: str) -> Callable[[], str]: return get_azure_ad_token_provider(azure_scope=audience) diff --git a/litellm/tool_loop.py b/litellm/tool_loop.py index aaa0d62eea7..d0b2850bb5b 100644 --- a/litellm/tool_loop.py +++ b/litellm/tool_loop.py @@ -63,6 +63,8 @@ def _assistant_tool_call(tool_call: ChatCompletionMessageToolCall) -> ChatComple def _assistant_message( message: Message, tool_calls: tuple[ChatCompletionMessageToolCall, ...], replays_provider_specific_fields: bool ) -> ChatCompletionAssistantMessage: + from litellm.completion_extras.litellm_responses_transformation.history import retained_replay_fields + return cast( # cast-ok: dict literal with the optional message fields spread in only when set "ChatCompletionAssistantMessage", { @@ -78,7 +80,7 @@ def _assistant_message( "provider_specific_fields", getattr(message, "provider_specific_fields", None) if replays_provider_specific_fields - else None, + else retained_replay_fields(getattr(message, "provider_specific_fields", None)), ), ) if value is not None diff --git a/litellm/tracing/otlp_http.py b/litellm/tracing/otlp_http.py index 493cc7cf984..81dbab6c023 100644 --- a/litellm/tracing/otlp_http.py +++ b/litellm/tracing/otlp_http.py @@ -1,20 +1,9 @@ import json -from typing import Final, Protocol, runtime_checkable +from typing import Final -from pydantic import ConfigDict, TypeAdapter from typing_extensions import ReadOnly, TypedDict -from litellm.rust_bridge.loader import get_native_bridge - - -@runtime_checkable -class NativeOtlpError(Protocol): - def trace_encode_error(self, message: str) -> bytes: ... - - -_NATIVE: Final[TypeAdapter[NativeOtlpError]] = TypeAdapter( - NativeOtlpError, config=ConfigDict(arbitrary_types_allowed=True) -) +from litellm.rust_bridge import _native class OTLPError(TypedDict): @@ -22,8 +11,7 @@ class OTLPError(TypedDict): def encode_error(message: str) -> bytes: - native: Final = get_native_bridge() - return b"" if native is None else _NATIVE.validate_python(native).trace_encode_error(message) + return _native.trace_encode_error(message) def encode_otlp_response(content_type: str | None, error: str | None = None) -> tuple[bytes, str]: diff --git a/litellm/types/agents.py b/litellm/types/agents.py index 97dd67d3ff8..826aa5d9c98 100644 --- a/litellm/types/agents.py +++ b/litellm/types/agents.py @@ -3,7 +3,7 @@ from datetime import datetime from typing import TYPE_CHECKING, Annotated, Any, Final, Literal, TypeAlias from urllib.parse import urlsplit -from pydantic import ConfigDict, Field, PrivateAttr, StrictInt, field_validator +from pydantic import BaseModel, ConfigDict, Field, PrivateAttr, StrictInt, field_validator from typing_extensions import ReadOnly, Required, TypedDict from litellm.types.llms.base import LiteLLMBaseModel, LiteLLMPydanticObjectBase @@ -343,6 +343,18 @@ class ListAgentsResponse(LiteLLMBaseModel): agents: list[AgentResponse] +class AgentCreateRequest(BaseModel): + model_config = ConfigDict(frozen=True, extra="forbid") + + id: str + base_agent: str | None = None + agent_config: Mapping[str, object] | None = None + system_instruction: str | None = None + base_environment: str | Mapping[str, object] | None = None + description: str | None = None + tools: Sequence[Mapping[str, object]] | None = None + + class AgentCreateResponse(LiteLLMPydanticObjectBase): """ Response from a provider-side agent creation or get call (e.g. Gemini v1beta/agents). diff --git a/litellm/types/integrations/rag/bedrock_knowledgebase.py b/litellm/types/integrations/rag/bedrock_knowledgebase.py index 7156d8101e1..7288eca03b4 100644 --- a/litellm/types/integrations/rag/bedrock_knowledgebase.py +++ b/litellm/types/integrations/rag/bedrock_knowledgebase.py @@ -1,4 +1,4 @@ -from typing import Any, Literal +from typing import Literal from typing_extensions import ReadOnly, TypedDict @@ -40,7 +40,7 @@ class BedrockKBRetrievalResult(TypedDict, total=False): content: BedrockKBContent | None location: BedrockKBLocation | None score: float | None - metadata: dict[str, Any] | None + metadata: dict[str, object] | None class BedrockKBResponse(TypedDict, total=False): @@ -87,21 +87,21 @@ class BedrockKBMetadataConfiguration(TypedDict, total=False): class BedrockKBModelConfiguration(TypedDict, total=False): """Model configuration for reranking.""" - additionalModelRequestFields: dict[str, Any] | None + additionalModelRequestFields: dict[str, object] | None modelArn: str | None class BedrockKBRerankingConfiguration(TypedDict, total=False): """Configuration for reranking in vector search.""" - bedrockRerankingConfiguration: dict[str, Any] | None # This could be further typed if needed + bedrockRerankingConfiguration: dict[str, object] | None # This could be further typed if needed type: str | None class BedrockKBVectorSearchConfiguration(TypedDict, total=False): """Configuration for vector search.""" - filter: dict[str, Any] | None + filter: dict[str, object] | None implicitFilterConfiguration: BedrockKBImplicitFilterConfiguration | None numberOfResults: int | None overrideSearchType: str | None diff --git a/litellm/types/litellm_params.py b/litellm/types/litellm_params.py index 717b74e5741..2065093f295 100644 --- a/litellm/types/litellm_params.py +++ b/litellm/types/litellm_params.py @@ -189,6 +189,9 @@ class DeploymentOptions: tpm: int | None = None itpm: int | None = None otpm: int | None = None + rpd: int | None = None + tpd: int | None = None + daily_reset_time: str | None = None kubernetes_pod_discovery: bool | None = None default_api_key_rpm_limit: int | None = None default_api_key_tpm_limit: int | None = None diff --git a/litellm/types/llms/azure_ai.py b/litellm/types/llms/azure_ai.py index 722bc53f429..419e6c0cec5 100644 --- a/litellm/types/llms/azure_ai.py +++ b/litellm/types/llms/azure_ai.py @@ -1,6 +1,6 @@ from typing import Literal -from typing_extensions import Required, TypedDict +from typing_extensions import NotRequired, ReadOnly, Required, TypedDict class ImageEmbeddingInput(TypedDict, total=False): @@ -15,3 +15,9 @@ class ImageEmbeddingRequest(TypedDict, total=False): input: Required[list[ImageEmbeddingInput]] dimensions: int encoding_format: EncodingFormat + + +class FoundryAgentReference(TypedDict): + type: ReadOnly[Literal["agent_reference"]] + name: ReadOnly[str] + version: ReadOnly[NotRequired[str]] diff --git a/litellm/types/llms/bedrock_invoke_agents.py b/litellm/types/llms/bedrock_invoke_agents.py index 62f3c18ca7a..b334c986d6b 100644 --- a/litellm/types/llms/bedrock_invoke_agents.py +++ b/litellm/types/llms/bedrock_invoke_agents.py @@ -4,7 +4,7 @@ Type definitions for AWS Bedrock Invoke Agent API responses. https://docs.aws.amazon.com/bedrock/latest/APIReference/API_agent-runtime_InvokeAgent.html """ -from typing import Any, Final +from typing import Final from typing_extensions import TypedDict @@ -39,7 +39,7 @@ class InvokeAgentModelInvocationInput(TypedDict, total=False): """Model invocation input details.""" foundationModel: str | None - inferenceConfiguration: dict[str, Any] | None + inferenceConfiguration: dict[str, object] | None text: str | None traceId: str | None type: str | None @@ -49,9 +49,9 @@ class InvokeAgentModelInvocationOutput(TypedDict, total=False): """Model invocation output details.""" metadata: InvokeAgentMetadata | None - parsedResponse: dict[str, Any] | None - rawResponse: dict[str, Any] | None - reasoningContent: dict[str, Any] | None + parsedResponse: dict[str, object] | None + rawResponse: dict[str, object] | None + reasoningContent: dict[str, object] | None traceId: str | None diff --git a/litellm/types/llms/gemini.py b/litellm/types/llms/gemini.py index c300c26bcd3..2ad81e64e05 100644 --- a/litellm/types/llms/gemini.py +++ b/litellm/types/llms/gemini.py @@ -1,5 +1,6 @@ +from collections.abc import Mapping from enum import Enum -from typing import Any, Literal +from typing import Literal from typing_extensions import Required, TypedDict @@ -235,7 +236,7 @@ class GeminiVideoGenerationInstance(TypedDict, total=False): """Instance data for Gemini video generation request""" prompt: Required[str] - image: dict[str, Any] + image: Mapping[str, object] class GeminiVideoGenerationParameters(LiteLLMBaseModel): @@ -263,7 +264,7 @@ class GeminiVideoGenerationParameters(LiteLLMBaseModel): negativePrompt: str | None = None """Text describing what not to include in the video.""" - lastFrame: Any | None = None + lastFrame: object | None = None """ The final image for interpolation video to transition. Should be used with the 'image' parameter. @@ -275,7 +276,7 @@ class GeminiVideoGenerationParameters(LiteLLMBaseModel): Only supported in Veo 3.1 (list of VideoGenerationReferenceImage objects). """ - video: Any | None = None + video: object | None = None """ Video to be used for video extension (Video object). Only supported in Veo 3.1 & Veo 3 Fast. @@ -354,5 +355,5 @@ class GeminiLongRunningOperationResponse(LiteLLMBaseModel): response: GeminiOperationResponse | None = None """Response object when operation is complete""" - error: dict[str, Any] | None = None + error: dict[str, object] | None = None """Error details if operation failed""" diff --git a/litellm/types/llms/langgraph.py b/litellm/types/llms/langgraph.py index 7e34329992d..83f7bb090d1 100644 --- a/litellm/types/llms/langgraph.py +++ b/litellm/types/llms/langgraph.py @@ -4,7 +4,8 @@ Type definitions for LangGraph API. LangGraph provides a streaming and non-streaming API for running agents. """ -from typing import Any, Literal +from collections.abc import Mapping +from typing import Literal from typing_extensions import TypedDict @@ -29,8 +30,8 @@ class LangGraphRequest(TypedDict, total=False): assistant_id: str input: LangGraphInput stream_mode: str | None - config: dict[str, Any] | None - metadata: dict[str, Any] | None + config: Mapping[str, object] | None + metadata: Mapping[str, object] | None # Response Types - Streaming @@ -38,7 +39,7 @@ class LangGraphStreamEvent(TypedDict, total=False): """Single event in a LangGraph stream response.""" event: str - data: Any + data: object # Response Types - Non-streaming @@ -55,7 +56,7 @@ class LangGraphResponse(TypedDict, total=False): """Non-streaming response structure from LangGraph.""" messages: list[LangGraphResponseMessage] - values: dict[str, Any] + values: dict[str, object] # Parsed response for internal use diff --git a/litellm/types/llms/mistral.py b/litellm/types/llms/mistral.py index e64aa9c13ab..cd61f32f430 100644 --- a/litellm/types/llms/mistral.py +++ b/litellm/types/llms/mistral.py @@ -1,6 +1,6 @@ from typing import Literal -from typing_extensions import TypedDict +from typing_extensions import NotRequired, ReadOnly, TypedDict class FunctionCall(TypedDict): @@ -22,3 +22,4 @@ class MistralTextBlock(TypedDict): class MistralThinkingBlock(TypedDict): type: Literal["thinking"] thinking: list[MistralTextBlock] + closed: NotRequired[ReadOnly[bool]] diff --git a/litellm/types/llms/openai.py b/litellm/types/llms/openai.py index 4912f9f1375..6ce51abcd8a 100644 --- a/litellm/types/llms/openai.py +++ b/litellm/types/llms/openai.py @@ -1,5 +1,5 @@ import builtins -from collections.abc import Iterable, Mapping +from collections.abc import Iterable, Mapping, Sequence from enum import Enum from os import PathLike from typing import IO, TYPE_CHECKING, Any, Final, Generic, Literal, Optional, TypeAlias, Union @@ -66,6 +66,7 @@ from pydantic import ( ConfigDict, Discriminator, Field, + FieldSerializationInfo, NonNegativeInt, PrivateAttr, SerializerFunctionWrapHandler, @@ -1342,6 +1343,10 @@ class ResponsesAPIStreamOptions(TypedDict, total=False): include_obfuscation: bool +class ResponsesAPIModeration(TypedDict, total=False): + model: Required[ReadOnly[str]] + + class ResponsesAPIOptionalRequestParams(TypedDict, total=False): """TypedDict for Optional parameters supported by the responses API.""" @@ -1369,6 +1374,7 @@ class ResponsesAPIOptionalRequestParams(TypedDict, total=False): prompt_cache_key: str | None prompt_cache_retention: str | None prompt_cache_options: ReadOnly[PromptCacheOptions | None] + moderation: ReadOnly[ResponsesAPIModeration | None] stream_options: ResponsesAPIStreamOptions | None top_logprobs: int | None partial_images: int | None # Number of partial images to generate (1-3) for streaming image generation @@ -1482,15 +1488,66 @@ One of: completed, failed, in_progress, cancelled, queued, or incomplete. """ -_NULL_DROPPED_OUTPUT_ITEM_KEYS: Final = frozenset( - ( - ("reasoning", "status"), - ("reasoning", "content"), - ("reasoning", "encrypted_content"), - ("tool_search_call", "created_by"), - ("tool_search_output", "created_by"), - ) -) +_NULL_DROPPED_REASONING_ITEM_KEYS: Final = frozenset(("status", "content", "encrypted_content")) + + +def _as_json_object(value: object) -> Mapping[str, object] | None: + return value if isinstance(value, dict) else None + + +def _as_json_array(value: object) -> Sequence[object] | None: + return value if isinstance(value, list) else None + + +def _drops_created_by(value: object, *, drops_set_created_by: bool) -> bool: + return value is None or drops_set_created_by + + +def _drops(item_type: object, key: object, value: object, *, drops_set_created_by: bool) -> bool: + if key == "created_by": + return _drops_created_by(value, drops_set_created_by=drops_set_created_by) + return value is None and item_type == "reasoning" and key in _NULL_DROPPED_REASONING_ITEM_KEYS + + +def _without_created_by(entry: object, *, drops_set_created_by: bool) -> object: + entry_object: Final = _as_json_object(entry) + if entry_object is None: + return entry + return { + k: v + for k, v in entry_object.items() + if k != "created_by" or not _drops_created_by(v, drops_set_created_by=drops_set_created_by) + } + + +def _replayable_output_value(item_type: object, key: object, value: object, *, drops_set_created_by: bool) -> object: + entries: Final = _as_json_array(value) + if item_type != "shell_call_output" or key != "output" or entries is None: + return value + return [_without_created_by(entry, drops_set_created_by=drops_set_created_by) for entry in entries] + + +def replayable_responses_item( + item: Mapping[str, object], *, drops_set_created_by: bool = False +) -> Mapping[str, object]: + item_type: Final = item.get("type") + return { + k: _replayable_output_value(item_type, k, v, drops_set_created_by=drops_set_created_by) + for k, v in item.items() + if not _drops(item_type, k, v, drops_set_created_by=drops_set_created_by) + } + + +def replayable_responses_input(value: object, *, drops_set_created_by: bool = False) -> object: + items: Final = _as_json_array(value) + if items is None: + return value + return [ + replayable_responses_item(obj, drops_set_created_by=drops_set_created_by) + if (obj := _as_json_object(item)) is not None + else item + for item in items + ] class ResponsesAPIResponse(BaseLiteLLMOpenAIResponseObject): @@ -1565,34 +1622,16 @@ class ResponsesAPIResponse(BaseLiteLLMOpenAIResponseObject): @field_serializer("output", mode="wrap") @classmethod - def _serialize_output_filter_reasoning_nulls(cls, value, handler, _info): + def _serialize_output_as_replayable( + cls, value: builtins.object, handler: SerializerFunctionWrapHandler, _info: FieldSerializationInfo + ): """ - Filter null status/content/encrypted_content from reasoning output items. - - Mirrors the request-side filtering in - OpenAIResponsesAPIConfig._handle_reasoning_item() which filters these - same fields before sending requests to providers. - - Without this, reasoning items include null fields that cause SDK errors - (e.g., the OpenAI C# SDK crashes on status=null). - - Issue: https://github.com/BerriAI/litellm/issues/16824 + Drop the nulls the SDK types default in but providers never send: created_by on every output item + (OpenAI rejects it when `output` is replayed as `input`), and status/content/encrypted_content on + reasoning items (the OpenAI C# SDK crashes on status=null, issue #16824). """ - serialized: Final = handler(value) - if not isinstance(serialized, list): - return serialized - return [ - ( - { - k: v - for k, v in item.items() - if v is not None or (item.get("type"), k) not in _NULL_DROPPED_OUTPUT_ITEM_KEYS - } - if isinstance(item, dict) - else item - ) - for item in serialized - ] + serialized: Final[object] = handler(value) + return replayable_responses_input(serialized) @property def output_text(self) -> str: diff --git a/litellm/types/llms/vertex_ai.py b/litellm/types/llms/vertex_ai.py index f1176f777c7..7cb5432d009 100644 --- a/litellm/types/llms/vertex_ai.py +++ b/litellm/types/llms/vertex_ai.py @@ -376,7 +376,7 @@ class RequestBody(TypedDict, total=False): class CachedContentRequestBody(TypedDict, total=False): contents: Required[list[ContentType]] system_instruction: SystemInstructions - tools: Tools + tools: Tools | None toolConfig: ToolConfig model: Required[str] # Format: models/{model} ttl: str # ending in 's' - Example: "3.5s". diff --git a/litellm/types/mcp_server/tool_registry.py b/litellm/types/mcp_server/tool_registry.py index 738d37c9503..080e27b6ed3 100644 --- a/litellm/types/mcp_server/tool_registry.py +++ b/litellm/types/mcp_server/tool_registry.py @@ -1,5 +1,5 @@ from collections.abc import Callable -from typing import Any, ClassVar +from typing import ClassVar from pydantic import ConfigDict, Field @@ -10,7 +10,7 @@ class MCPTool(LiteLLMBaseModel): model_config: ClassVar[ConfigDict] = ConfigDict(arbitrary_types_allowed=True) name: str description: str - input_schema: dict[str, Any] + input_schema: dict[str, object] handler: Callable server_id: str | None = Field(default=None, frozen=True) @@ -18,18 +18,18 @@ class MCPTool(LiteLLMBaseModel): class ToolSchema(LiteLLMBaseModel): name: str description: str - inputSchema: dict[str, Any] + inputSchema: dict[str, object] class ListToolsResponse(LiteLLMBaseModel): tools: list[ToolSchema] nextCursor: str | None = None - _meta: dict[str, Any] | None = None + _meta: dict[str, object] | None = None class CallToolRequest(LiteLLMBaseModel): method: str = "tools/call" - params: dict[str, Any] + params: dict[str, object] class ContentItem(LiteLLMBaseModel): diff --git a/litellm/types/proxy/guardrails/guardrail_hooks/enkryptai.py b/litellm/types/proxy/guardrails/guardrail_hooks/enkryptai.py index d1eba1dd4a9..f936c9d85cf 100644 --- a/litellm/types/proxy/guardrails/guardrail_hooks/enkryptai.py +++ b/litellm/types/proxy/guardrails/guardrail_hooks/enkryptai.py @@ -1,5 +1,3 @@ -from typing import Any - from pydantic import Field from typing_extensions import TypedDict @@ -20,7 +18,7 @@ class EnkryptAIPolicyViolationDetail(TypedDict, total=False): class EnkryptAIPIIDetail(TypedDict, total=False): """Details for PII detection.""" - pii: dict[str, Any] + pii: dict[str, object] class EnkryptAIToxicityDetail(TypedDict, total=False): @@ -85,8 +83,8 @@ class EnkryptAIResponseDetails(TypedDict, total=False): toxicity: EnkryptAIToxicityDetail | None keyword_detected: EnkryptAIKeywordDetail | None bias: EnkryptAIBiasDetail | None - prompt_injection: dict[str, Any] | None - jailbreak: dict[str, Any] | None + prompt_injection: dict[str, object] | None + jailbreak: dict[str, object] | None class EnkryptAIResponse(TypedDict, total=False): @@ -107,7 +105,7 @@ class EnkryptAIProcessedResult(TypedDict): | EnkryptAIToxicityDetail | EnkryptAIKeywordDetail | EnkryptAIBiasDetail - | dict[str, Any], + | dict[str, object], ] diff --git a/litellm/types/proxy/management_endpoints/common_daily_activity.py b/litellm/types/proxy/management_endpoints/common_daily_activity.py index 213c911cfdc..3f1a7980b27 100644 --- a/litellm/types/proxy/management_endpoints/common_daily_activity.py +++ b/litellm/types/proxy/management_endpoints/common_daily_activity.py @@ -65,6 +65,34 @@ class MetricWithMetadata(MetricBase): api_key_breakdown: dict[str, KeyMetricWithMetadata] = Field(default_factory=dict) # api_key -> {metrics, metadata} +class GuardrailSpendMetrics(LiteLLMBaseModel): + model_config = ConfigDict(frozen=True) + + spend: float = 0.0 + untracked_units: int = 0 + + +class GuardrailKeyMetric(LiteLLMBaseModel): + model_config = ConfigDict(frozen=True) + + metrics: GuardrailSpendMetrics + metadata: KeyMetadata + + +class GuardrailMetadata(LiteLLMBaseModel): + model_config = ConfigDict(frozen=True) + + guardrail_name: str + + +class GuardrailMetric(LiteLLMBaseModel): + model_config = ConfigDict(frozen=True) + + metrics: GuardrailSpendMetrics + metadata: GuardrailMetadata + api_key_breakdown: Mapping[str, GuardrailKeyMetric] = Field(default_factory=dict) + + class BreakdownMetrics(LiteLLMBaseModel): """Breakdown of spend by different dimensions""" @@ -75,6 +103,7 @@ class BreakdownMetrics(LiteLLMBaseModel): endpoints: dict[str, MetricWithMetadata] = Field(default_factory=dict) # endpoint -> {metrics, metadata} api_keys: dict[str, KeyMetricWithMetadata] = Field(default_factory=dict) # api_key -> {metrics, metadata} entities: dict[str, MetricWithMetadata] = Field(default_factory=dict) # entity -> {metrics, metadata} + guardrails: Mapping[str, GuardrailMetric] = Field(default_factory=dict) # guardrail_id -> spend class DailySpendData(LiteLLMBaseModel): diff --git a/litellm/types/repositories/daily_activity.py b/litellm/types/repositories/daily_activity.py index 4111b83a891..b013ce43113 100644 --- a/litellm/types/repositories/daily_activity.py +++ b/litellm/types/repositories/daily_activity.py @@ -168,6 +168,16 @@ class EntityRollupRow(RollupMetricsRow): distinct_api_keys: int | None +@dataclass(frozen=True, slots=True) +class GuardrailSpendRow: + date: str + guardrail_id: str + guardrail_name: str + api_key: str + spend: float + untracked_units: int + + @dataclass(frozen=True, slots=True) class AggregatedRows: grouping_rows: tuple[GroupingSetsRow, ...] diff --git a/litellm/types/router.py b/litellm/types/router.py index ba9b82e2a57..60c9e596588 100644 --- a/litellm/types/router.py +++ b/litellm/types/router.py @@ -4,6 +4,7 @@ litellm.Router Types - includes RouterConfig, UpdateRouterConfig, ModelInfo etc import datetime import enum +import re from collections.abc import Container, Mapping, Sequence from dataclasses import dataclass, field from typing import ( @@ -518,6 +519,19 @@ def holds_secret_pointer(param_name: str) -> bool: _RESERVED_INIT_KEYS: Final = frozenset({"self", "params", "__class__"}) +_DAILY_RESET_TIME_PATTERN: Final = re.compile(r"\d{2}:\d{2}") + + +def parse_daily_reset_time(value: str | None) -> datetime.timedelta: + """`daily_reset_time` is "HH:MM" in UTC, when the rpd/tpd window starts over; unset means midnight UTC.""" + if value is None: + return datetime.timedelta(0) + if _DAILY_RESET_TIME_PATTERN.fullmatch(value) is None: + raise ValueError(f"daily_reset_time must be HH:MM in UTC, got {value!r}") + parsed: Final = datetime.time.fromisoformat(value) + return datetime.timedelta(hours=parsed.hour, minutes=parsed.minute) + + class GenericLiteLLMParams(CredentialLiteLLMParams, CustomPricingLiteLLMParams): """ LiteLLM Params without 'model' arg (used across completion / assistants api) @@ -533,6 +547,9 @@ class GenericLiteLLMParams(CredentialLiteLLMParams, CustomPricingLiteLLMParams): rpm: int | None = None itpm: int | None = None otpm: int | None = None + tpd: int | None = None + rpd: int | None = None + daily_reset_time: str | None = None timeout: float | str | httpx.Timeout | SDKTimeout | None = None # if str, pass in as os.environ/ # read timeout of a live stream, a faked stream takes the longer of this and timeout. If str, pass in as os.environ/ stream_timeout: float | str | None = None @@ -624,6 +641,13 @@ class GenericLiteLLMParams(CredentialLiteLLMParams, CustomPricingLiteLLMParams): valkey_text_field: str | None = None valkey_embedding_field: str | None = None + @field_validator("daily_reset_time") + @classmethod + def _daily_reset_time_is_utc_hh_mm(cls, value: str | None) -> str | None: + if value is not None: + parse_daily_reset_time(value) + return value + @field_validator("timeout") @classmethod def normalize_timeout( @@ -738,6 +762,9 @@ class LiteLLMParamsTypedDict(TypedDict, total=False): rpm: int | None itpm: int | None otpm: int | None + tpd: ReadOnly[int | None] + rpd: ReadOnly[int | None] + daily_reset_time: ReadOnly[str | None] order: int | None weight: int | None max_parallel_requests: int | None diff --git a/litellm/types/utils.py b/litellm/types/utils.py index 2869f9b2577..266a6a20131 100644 --- a/litellm/types/utils.py +++ b/litellm/types/utils.py @@ -225,6 +225,8 @@ class ProviderSpecificModelInfo(TypedDict, total=False): supports_xhigh_reasoning_effort: bool | None supports_max_reasoning_effort: bool | None reasoning_effort_levels: ReadOnly[Sequence[str] | None] + reasoning_modes: ReadOnly[Sequence[str] | None] + reasoning_contexts: ReadOnly[Sequence[str] | None] default_reasoning_effort: ReadOnly[Literal["none", "minimal", "low", "medium", "high", "xhigh"] | None] supports_output_config: bool | None supports_image_size: bool | None @@ -2876,7 +2878,7 @@ class TranscriptionUsageTokensObject(LiteLLMBaseModel): input_tokens: int output_tokens: int total_tokens: int - input_token_details: TranscriptionUsageInputTokenDetailsObject + input_token_details: TranscriptionUsageInputTokenDetailsObject | None = None class TranscriptionResponse(OpenAIObject): @@ -4422,6 +4424,7 @@ class LlmProviders(str, Enum): JINA_AI = "jina_ai" XAI = "xai" ZAI = "zai" + BIGMODEL = "bigmodel" CUSTOM_OPENAI = "custom_openai" TEXT_COMPLETION_OPENAI = "text-completion-openai" COHERE = "cohere" @@ -4573,6 +4576,7 @@ class LlmProviders(str, Enum): POE = "poe" CHUTES = "chutes" NEOSANTARA = "neosantara" + AIAND = "aiand" PARASAIL = "parasail" XIAOMI_MIMO = "xiaomi_mimo" TENSORMESH = "tensormesh" @@ -4585,10 +4589,12 @@ class LlmProviders(str, Enum): PRISM = "prism" OPENINFER = "openinfer" INFERENCEAPIS = "inferenceapis" + ZEROGPU = "zerogpu" DARKBLOOM = "darkbloom" META = "meta" SAIL = "sail" REKA = "reka" + STREAMLAKE = "streamlake" LITELLM_AGENT = "litellm_agent" CURSOR = "cursor" BEDROCK_MANTLE = "bedrock_mantle" diff --git a/litellm/utils.py b/litellm/utils.py index 1e095966a43..26ce38d63b3 100644 --- a/litellm/utils.py +++ b/litellm/utils.py @@ -304,7 +304,7 @@ except (ImportError, AttributeError, TypeError): # Convert to str (if necessary) claude_json_str = json.dumps(json_data) import importlib.metadata -from collections.abc import AsyncIterator, Callable, Collection, Iterable, Iterator, Mapping, Sequence +from collections.abc import AsyncIterator, Callable, Collection, Iterable, Iterator, Mapping, Sequence, Sized from typing import TYPE_CHECKING, Any, Final, Literal, Protocol, TypeAlias, TypeVar, cast, runtime_checkable from typing_extensions import assert_never @@ -606,9 +606,23 @@ def custom_llm_setup(): litellm.provider_list.append(custom_llm["provider"]) if custom_llm["provider"] not in litellm._custom_providers: + _warn_if_built_in_provider_shadows_custom_handler(custom_llm["provider"]) litellm._custom_providers.append(custom_llm["provider"]) +def _warn_if_built_in_provider_shadows_custom_handler(provider: str) -> None: + from litellm.llms.openai_like.json_loader import JSONProviderRegistry + + if provider not in LlmProvidersSet and not JSONProviderRegistry.exists(provider): + return + verbose_logger.warning( + "custom_provider_map provider '%s' has the same name as a built-in LiteLLM provider, which handles " + "'%s/' models instead of your custom_handler. Rename the provider and its models to use your handler", + provider, + provider, + ) + + def add_custom_logger_callback_to_specific_event(callback: str, logging_event: Literal["success", "failure"]) -> None: """ Add a custom logger callback to the specific event @@ -2018,16 +2032,15 @@ def client(original_function): # MODEL CALL result = original_function(*args, **kwargs) end_time = datetime.datetime.now() - if _is_streaming_request( - kwargs=kwargs, - call_type=call_type, - ): + if _is_streaming_request(kwargs=kwargs, call_type=call_type) or _is_converted_stream_result(result): if "complete_response" in kwargs and kwargs["complete_response"] is True: chunks = [] for idx, chunk in enumerate(result): chunks.append(chunk) return litellm.stream_chunk_builder(chunks, messages=kwargs.get("messages", None)) else: + logging_obj.stream = True + logging_obj.model_call_details["stream"] = True # RETURN RESULT update_response_metadata: _ResponseMetadataUpdater = litellm_utils.update_response_metadata update_response_metadata( @@ -2564,6 +2577,8 @@ _NEVER_STREAMING_CALL_TYPES: Final = frozenset( } ) +_RESULT_DECIDES_STREAMING_CALL_TYPES: Final = frozenset({"get_responses", "aget_responses"}) + def _is_streaming_request( kwargs: dict[str, object], @@ -2575,7 +2590,7 @@ def _is_streaming_request( - if "stream=True" in kwargs (litellm chat completion, litellm text completion, litellm messages) - if call_type is generate_content_stream or agenerate_content_stream (litellm google genai) """ - if call_type in _NEVER_STREAMING_CALL_TYPES: + if call_type in _NEVER_STREAMING_CALL_TYPES or call_type in _RESULT_DECIDES_STREAMING_CALL_TYPES: return False if "stream" in kwargs and kwargs["stream"] is True: return True @@ -4067,7 +4082,9 @@ def get_optional_params_transcription( "timestamp_granularities": None, } - non_default_params = {k: v for k, v in passed_params.items() if (k in default_params and v != default_params[k])} + non_default_params: Final = { + k: v for k, v in passed_params.items() if (k in default_params and v != default_params[k]) + } optional_params = {} ## raise exception if non-default value passed for non-openai/azure embedding calls @@ -4104,6 +4121,19 @@ def get_optional_params_transcription( model=model, drop_params=drop_params if drop_params is not None else False, ) + elif custom_llm_provider == "bedrock": + from litellm.llms.bedrock.audio_transcription import ( + UnsupportedTranscriptionParams, + map_openai_transcription_params, + ) + + match map_openai_transcription_params( + non_default_params, drop_params=drop_params is True or litellm.drop_params is True + ): + case UnsupportedTranscriptionParams(message=message): + raise UnsupportedParamsError(message=message, llm_provider="bedrock") + case mapped_params: + optional_params = dict(mapped_params) elif provider_config is not None: # custom audio transcription config supported_params = provider_config.get_supported_openai_params(model=model) _check_valid_arg(supported_params=supported_params) @@ -4118,7 +4148,7 @@ def get_optional_params_transcription( optional_params=optional_params, passed_params=passed_params, custom_llm_provider=custom_llm_provider, - openai_params=OPENAI_TRANSCRIPTION_PARAMS, + openai_params=list(default_params) if custom_llm_provider == "bedrock" else OPENAI_TRANSCRIPTION_PARAMS, additional_drop_params=kwargs.get("additional_drop_params", None), ) @@ -5059,8 +5089,10 @@ def get_optional_params( supported_params: List[str] - supported params from the litellm config """ verbose_logger.info("\nLiteLLM completion() model= %s; provider = %s", model, custom_llm_provider) - verbose_logger.debug("\nLiteLLM: Params passed to completion() %s", passed_params) - verbose_logger.debug("\nLiteLLM: Non-Default params passed to completion() %s", non_default_params) + if verbose_logger.isEnabledFor(logging.DEBUG): + verbose_logger.debug( + "\nLiteLLM: Non-Default params passed to completion() %s", _debug_params_repr(non_default_params) + ) unsupported_params: Final = {} for k in non_default_params: if k not in supported_params: @@ -5601,7 +5633,9 @@ def get_optional_params( additional_drop_params=additional_drop_params, ) if _print_verbose_is_active(): - print_verbose(f"Final returned optional params: {redact_credentials_in_payload(optional_params)}") + print_verbose( + f"Final returned optional params: {_debug_params_repr(redact_credentials_in_payload(optional_params))}" + ) optional_params = apply_openai_param_overrides( optional_params=optional_params, non_default_params=non_default_params, @@ -5641,6 +5675,7 @@ def add_provider_specific_params_to_optional_params( "openai", "azure", "text-completion-openai", + "bigmodel", *litellm.openai_compatible_providers, ] or JSONProviderRegistry.exists(custom_llm_provider) if calls_through_openai_sdk: @@ -6610,8 +6645,6 @@ def get_model_info_helper( model=model, custom_llm_provider=custom_llm_provider or declared_authenticating_provider(model) ) - verbose_logger.debug("checking potential_model_names in litellm.model_cost: %s", potential_model_names) - combined_model_name: Final = potential_model_names["combined_model_name"] stripped_model_name: Final = potential_model_names["stripped_model_name"] combined_stripped_model_name: Final = potential_model_names["combined_stripped_model_name"] @@ -6714,6 +6747,7 @@ def get_model_info_helper( key, _model_info = generalization if _model_info is None or key is None: + verbose_logger.debug("model not found in litellm.model_cost, tried: %s", potential_model_names) raise ModelNotMappedError(_model_not_mapped_message(model, custom_llm_provider)) _input_cost_per_token: float | None = _model_info.get("input_cost_per_token") if _input_cost_per_token is None: @@ -7000,6 +7034,8 @@ def get_model_info_helper( supports_xhigh_reasoning_effort=_model_info.get("supports_xhigh_reasoning_effort", None), supports_max_reasoning_effort=_model_info.get("supports_max_reasoning_effort", None), reasoning_effort_levels=_model_info.get("reasoning_effort_levels", None), + reasoning_modes=_model_info.get("reasoning_modes", None), + reasoning_contexts=_model_info.get("reasoning_contexts", None), default_reasoning_effort=_model_info.get("default_reasoning_effort", None), bedrock_output_config_effort_ceiling=_model_info.get("bedrock_output_config_effort_ceiling", None), bedrock_converse_supports_strict_tools=_model_info.get("bedrock_converse_supports_strict_tools", None), @@ -7662,7 +7698,6 @@ def validate_environment( model in litellm.open_ai_chat_completion_models or model in litellm.open_ai_text_completion_models or model in litellm.open_ai_embedding_models - or model in litellm.openai_image_generation_models or model.startswith("gpt-image") ): if "OPENAI_API_KEY" in os.environ: @@ -8532,6 +8567,23 @@ def get_valid_models( return [] # NON-Blocking +_MAX_INLINE_DEBUG_ARG_CHARS: Final = 500 + + +def _debug_arg_repr(value: object) -> str: + """Short form of a call argument, since the outgoing provider request log already prints the request body.""" + rendered: Final = repr(value) + if len(rendered) <= _MAX_INLINE_DEBUG_ARG_CHARS: + return rendered + if isinstance(value, Sized): + return f"<{type(value).__name__} len={len(value)}>" + return f"<{type(value).__name__}>" + + +def _debug_params_repr(params: Mapping[str, object]) -> str: + return "{" + ", ".join(f"{key!r}: {_debug_arg_repr(value)}" for key, value in params.items()) + "}" + + def print_args_passed_to_litellm(original_function, args, kwargs): if not is_debugging_on(): return @@ -8552,9 +8604,9 @@ def print_args_passed_to_litellm(original_function, args, kwargs): ): return - args_str: Final = ", ".join(map(repr, args)) + args_str: Final = ", ".join(map(_debug_arg_repr, args)) redacted_kwargs: Final = redact_credentials_in_payload(kwargs) - kwargs_str: Final = ", ".join(f"{key}={value!r}" for key, value in redacted_kwargs.items()) + kwargs_str: Final = ", ".join(f"{key}={_debug_arg_repr(value)}" for key, value in redacted_kwargs.items()) print_verbose( "\n", ) # new line before @@ -9133,6 +9185,7 @@ class ProviderConfigManager: LlmProviders.DATABRICKS: (lambda: litellm.DatabricksConfig(), False), LlmProviders.XAI: (lambda: litellm.XAIChatConfig(), False), LlmProviders.ZAI: (lambda: litellm.ZAIChatConfig(), False), + LlmProviders.BIGMODEL: (ProviderConfigManager._get_bigmodel_chat_config, False), LlmProviders.OPENCODE_GO: (ProviderConfigManager.get_opencode_go_config, True), LlmProviders.LAMBDA_AI: (lambda: litellm.LambdaAIChatConfig(), False), LlmProviders.INCEPTION: (lambda: litellm.InceptionChatConfig(), False), @@ -9325,6 +9378,12 @@ class ProviderConfigManager: return get_bedrock_chat_config(model=model) + @staticmethod + def _get_bigmodel_chat_config() -> BaseConfig: + from litellm.llms.bigmodel.chat.transformation import BigModelChatConfig + + return BigModelChatConfig() + @staticmethod def get_opencode_go_config(model: str) -> BaseConfig: from litellm.llms.opencode.chat.transformation import go_chat_config @@ -9612,18 +9671,19 @@ class ProviderConfigManager: return litellm.HostedVLLMDecisionsConfig() if provider == LlmProviders.LM_STUDIO: return litellm.LMStudioDecisionsConfig() + if provider in (LlmProviders.OLLAMA, LlmProviders.OLLAMA_CHAT): + return litellm.OllamaDecisionsConfig() if provider == LlmProviders.LAYA: return litellm.LayaDecisionsConfig() if provider == LlmProviders.BESPOKE: return litellm.BespokeDecisionsConfig() - if provider in (LlmProviders.OPENAI, LlmProviders.AZURE): + if provider in (LlmProviders.OPENAI, LlmProviders.AZURE, LlmProviders.AZURE_AI): configs: Final = { LlmProviders.OPENAI: litellm.OpenAIDecisionsConfig, LlmProviders.AZURE: litellm.AzureDecisionsConfig, + LlmProviders.AZURE_AI: litellm.AzureAIDecisionsConfig, } return configs[provider]() - if provider == LlmProviders.AZURE_AI: - return litellm.AzureAIDecisionsConfig() return None @staticmethod @@ -9645,6 +9705,10 @@ class ProviderConfigManager: model: str, provider: LlmProviders, ) -> BaseAnthropicMessagesConfig | None: + if provider == LlmProviders.BIGMODEL: + from litellm.llms.bigmodel.messages.transformation import BigModelMessagesConfig + + return BigModelMessagesConfig() if provider == LlmProviders.OPENCODE_GO: from litellm.llms.opencode.common_utils import go_endpoint from litellm.llms.opencode.messages.transformation import OpenCodeGoMessagesConfig @@ -9876,6 +9940,10 @@ class ProviderConfigManager: if provider is None: return None + if provider == LlmProviders.BIGMODEL: + from litellm.llms.bigmodel.responses.transformation import BigModelResponsesAPIConfig + + return BigModelResponsesAPIConfig() if provider == LlmProviders.OPENCODE_GO: from litellm.llms.opencode.common_utils import go_endpoint from litellm.llms.opencode.responses.transformation import OpenCodeGoResponsesConfig @@ -9897,8 +9965,14 @@ class ProviderConfigManager: elif litellm.LlmProviders.AZURE_AI == provider: from litellm.llms.azure_ai.common_utils import ( azure_ai_supports_native_responses, + is_foundry_project_agent, + ) + from litellm.llms.azure_ai.responses.transformation import ( + AzureAIAgentResponsesAPIConfig, ) + if is_foundry_project_agent(model): + return AzureAIAgentResponsesAPIConfig() if azure_ai_supports_native_responses(model, api_base): return litellm.AzureAIResponsesAPIConfig() return None @@ -10308,11 +10382,9 @@ class ProviderConfigManager: provider: LlmProviders, ) -> BaseImageGenerationConfig | None: if LlmProviders.OPENAI == provider: - from litellm.llms.openai.image_generation import ( - get_openai_image_generation_config, - ) + from litellm.llms.openai.image_generation import GPTImageGenerationConfig - return get_openai_image_generation_config(model) + return GPTImageGenerationConfig() elif LlmProviders.AZURE == provider: from litellm.llms.azure.image_generation import ( get_azure_image_generation_config, @@ -10415,6 +10487,13 @@ class ProviderConfigManager: return get_modelscope_image_generation_config(model) elif LlmProviders.EDENAI == provider: return litellm.EdenAIImageGenerationConfig() + elif LlmProviders.TENCENT == provider: + from litellm.llms.tencent.image_generation.transformation import ( + TencentImageGenerationConfig, + is_tokenhub_image_model, + ) + + return TencentImageGenerationConfig() if is_tokenhub_image_model(model) else None return None @staticmethod @@ -10536,9 +10615,9 @@ class ProviderConfigManager: provider: LlmProviders, ) -> BaseImageEditConfig | None: if LlmProviders.OPENAI == provider: - from litellm.llms.openai.image_edit import get_openai_image_edit_config + from litellm.llms.openai.image_edit import OpenAIImageEditConfig - return get_openai_image_edit_config(model=model) + return OpenAIImageEditConfig() elif LlmProviders.HOSTED_VLLM == provider: from litellm.llms.hosted_vllm.image_edit import get_hosted_vllm_image_edit_config @@ -10603,6 +10682,15 @@ class ProviderConfigManager: ) return get_openrouter_image_edit_config(model) + elif LlmProviders.TENCENT == provider: + from litellm.llms.tencent.image_edit.transformation import ( + TencentImageEditConfig, + ) + from litellm.llms.tencent.image_generation.transformation import ( + is_tokenhub_image_model, + ) + + return TencentImageEditConfig() if is_tokenhub_image_model(model) else None return None @staticmethod diff --git a/litellm/vector_stores/vector_store_registry.py b/litellm/vector_stores/vector_store_registry.py index b93d9874dbc..598b56f4a79 100644 --- a/litellm/vector_stores/vector_store_registry.py +++ b/litellm/vector_stores/vector_store_registry.py @@ -36,7 +36,7 @@ else: _DB_ROW: Final = TypeAdapter(Mapping[str, object], config=ConfigDict(strict=True, hide_input_in_errors=True)) _ITEMS: Final = TypeAdapter(Sequence[object], config=ConfigDict(strict=True)) _TOOL: Final = TypeAdapter(Mapping[str, object], config=ConfigDict(strict=True)) -_STORE_ID_ITEMS: Final = TypeAdapter(list[object], config=ConfigDict(strict=True)) +_STORE_ID_ITEMS: Final = TypeAdapter(list[object] | tuple[object, ...], config=ConfigDict(strict=True)) def _named_store_ids(store_ids: object) -> tuple[str, ...]: @@ -49,7 +49,11 @@ def _named_store_ids(store_ids: object) -> tuple[str, ...]: return tuple(store_id for store_id in items if isinstance(store_id, str)) -def _tool_vector_store_ids(tool: object) -> tuple[str, ...]: +def listed_vector_store_ids(store_ids: object) -> tuple[str, ...]: + return _named_store_ids(store_ids) if isinstance(store_ids, (list, tuple)) else () + + +def vector_store_ids_in_tool(tool: object) -> tuple[str, ...]: try: return _named_store_ids(_TOOL.validate_python(tool).get("vector_store_ids")) except ValidationError: @@ -195,7 +199,7 @@ class VectorStoreRegistry: tools_to_remove: Final[list[int]] = [] for i, tool in enumerate(tools): - tool_vector_store_ids = _tool_vector_store_ids(tool) + tool_vector_store_ids = vector_store_ids_in_tool(tool) if not tool_vector_store_ids: continue @@ -305,7 +309,7 @@ class VectorStoreRegistry: List of vector stores with tool parameters merged into litellm_params """ # Pop vector_store_ids from params - vector_store_ids: Final[list[str]] = non_default_params.pop("vector_store_ids", None) or [] + vector_store_ids: Final = [*listed_vector_store_ids(non_default_params.pop("vector_store_ids", None))] # Extract params from tools and collect IDs params_by_id = self.get_and_pop_recognised_vector_store_tools(tools=tools, vector_store_ids=vector_store_ids) @@ -353,7 +357,7 @@ class VectorStoreRegistry: List of vector stores with tool parameters merged into litellm_params """ # Pop vector_store_ids from params - vector_store_ids: Final[list[str]] = non_default_params.pop("vector_store_ids", None) or [] + vector_store_ids: Final = [*listed_vector_store_ids(non_default_params.pop("vector_store_ids", None))] # Extract params from tools and collect IDs params_by_id = self.get_and_pop_recognised_vector_store_tools(tools=tools, vector_store_ids=vector_store_ids) @@ -423,7 +427,7 @@ class VectorStoreRegistry: validated_tools: Final = _ITEMS.validate_python(tools) except ValidationError: return vector_store_ids - return [*vector_store_ids, *chain.from_iterable(_tool_vector_store_ids(tool) for tool in validated_tools)] + return [*vector_store_ids, *chain.from_iterable(vector_store_ids_in_tool(tool) for tool in validated_tools)] def load_vector_stores_from_config(self, vector_stores_config: list[dict]): """ diff --git a/model_prices_and_context_window.json b/model_prices_and_context_window.json index 5774e699ad7..50b3560f05b 100644 --- a/model_prices_and_context_window.json +++ b/model_prices_and_context_window.json @@ -4039,6 +4039,7 @@ "source": "https://azure.microsoft.com/en-us/pricing/details/cognitive-services/openai-service/" }, "azure_ai/gpt-oss-120b": { + "deprecation_date": "2027-09-15", "input_cost_per_token": 1.5e-07, "output_cost_per_token": 6e-07, "litellm_provider": "azure_ai", @@ -4243,6 +4244,54 @@ "supports_web_search": true, "supports_xhigh_reasoning_effort": true }, + "azure_ai/gpt-6.1-terra": { + "cache_creation_input_token_cost": 1.25e-06, + "cache_creation_input_token_cost_above_272k_tokens": 2.5e-06, + "cache_read_input_token_cost": 5e-08, + "cache_read_input_token_cost_above_272k_tokens": 1e-07, + "input_cost_per_token": 1e-06, + "input_cost_per_token_above_272k_tokens": 2e-06, + "litellm_provider": "azure_ai", + "max_input_tokens": 922000, + "max_output_tokens": 128000, + "mode": "chat", + "output_cost_per_token": 5e-06, + "output_cost_per_token_above_272k_tokens": 7.5e-06, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, + "source": "https://techcommunity.microsoft.com/blog/azure-ai-foundry-blog/gpt-6-1-terra-now-generally-available-in-microsoft-foundry-build-agents-that-see/4567769", + "supported_endpoints": [ + "/v1/chat/completions", + "/v1/responses" + ], + "supported_modalities": [ + "text", + "image" + ], + "supported_output_modalities": [ + "text" + ], + "supports_computer_use": true, + "supports_function_calling": true, + "supports_max_reasoning_effort": true, + "supports_minimal_reasoning_effort": false, + "supports_native_streaming": true, + "supports_none_reasoning_effort": false, + "supports_parallel_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_cache_breakpoint": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_system_messages": true, + "supports_tool_choice": true, + "supports_vision": true, + "supports_web_search": true, + "supports_xhigh_reasoning_effort": true + }, "azure_ai/gpt-5.5": { "deprecation_date": "2027-10-26", "cache_read_input_token_cost": 5e-07, @@ -4904,6 +4953,11 @@ "max_output_tokens": 16384, "mode": "chat", "output_cost_per_token": 6.6e-07, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supports_function_calling": true, "supports_parallel_function_calling": true, @@ -4922,6 +4976,11 @@ "max_output_tokens": 16384, "mode": "chat", "output_cost_per_token": 6.6e-07, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supports_function_calling": true, "supports_parallel_function_calling": true, @@ -5009,6 +5068,11 @@ "output_cost_per_token": 1.1e-05, "output_cost_per_token_batches": 5.5e-06, "output_cost_per_token_priority": 2.2e-05, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ "/v1/chat/completions", @@ -5048,6 +5112,11 @@ "output_cost_per_token": 2.2e-06, "output_cost_per_token_batches": 1.1e-06, "output_cost_per_token_priority": 3.96e-06, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ "/v1/chat/completions", @@ -5113,6 +5182,11 @@ "input_cost_per_token_priority": 2.75e-06, "output_cost_per_token_batches": 5.5e-06, "output_cost_per_token_priority": 2.2e-05, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" }, "azure/eu/gpt-5.1-codex": { @@ -5188,6 +5262,11 @@ "mode": "chat", "output_cost_per_token": 4.4e-07, "output_cost_per_token_batches": 2.2e-07, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ "/v1/chat/completions", @@ -5344,6 +5423,11 @@ "max_output_tokens": 16384, "mode": "chat", "output_cost_per_token": 6e-07, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_response_schema": true, @@ -5428,6 +5512,11 @@ "input_cost_per_token_priority": 2.5e-06, "output_cost_per_token_batches": 5e-06, "output_cost_per_token_priority": 2e-05, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" }, "azure/global/gpt-5.1-codex": { @@ -5680,6 +5769,11 @@ "output_cost_per_token": 8e-06, "output_cost_per_token_batches": 4e-06, "output_cost_per_token_priority": 1.4e-05, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ "/v1/chat/completions", @@ -5717,6 +5811,11 @@ "output_cost_per_token": 8e-06, "output_cost_per_token_batches": 4e-06, "output_cost_per_token_priority": 1.4e-05, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ "/v1/chat/completions", @@ -5754,6 +5853,11 @@ "output_cost_per_token": 1.6e-06, "output_cost_per_token_batches": 8e-07, "output_cost_per_token_priority": 2.8e-06, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ "/v1/chat/completions", @@ -5791,6 +5895,11 @@ "output_cost_per_token": 1.6e-06, "output_cost_per_token_batches": 8e-07, "output_cost_per_token_priority": 2.8e-06, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ "/v1/chat/completions", @@ -5992,6 +6101,7 @@ "text", "audio" ], + "supports_audio_output": true, "supports_function_calling": true, "supports_native_streaming": true, "supports_parallel_function_calling": true, @@ -6024,6 +6134,7 @@ "text", "audio" ], + "supports_audio_output": true, "supports_function_calling": true, "supports_native_streaming": true, "supports_parallel_function_calling": true, @@ -6055,6 +6166,7 @@ "text", "audio" ], + "supports_audio_output": true, "supports_function_calling": true, "supports_native_streaming": true, "supports_parallel_function_calling": true, @@ -6121,6 +6233,7 @@ "text", "audio" ], + "supports_audio_output": true, "supports_function_calling": true, "supports_native_streaming": true, "supports_parallel_function_calling": true, @@ -6184,6 +6297,7 @@ "text", "audio" ], + "supports_audio_output": true, "supports_function_calling": true, "supports_native_streaming": true, "supports_parallel_function_calling": true, @@ -6203,6 +6317,11 @@ "max_output_tokens": 16384, "mode": "chat", "output_cost_per_token": 6e-07, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_prompt_caching": true, @@ -6221,6 +6340,11 @@ "mode": "chat", "output_cost_per_token": 6e-07, "output_cost_per_token_batches": 3e-07, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supports_function_calling": true, "supports_parallel_function_calling": true, @@ -6250,6 +6374,7 @@ "text", "audio" ], + "supports_audio_output": true, "supports_function_calling": true, "supports_native_streaming": true, "supports_parallel_function_calling": true, @@ -6710,6 +6835,11 @@ "default_reasoning_effort": "none", "input_cost_per_token_batches": 6.25e-07, "output_cost_per_token_batches": 5e-06, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supports_minimal_reasoning_effort": true, "cache_read_input_token_cost_batches": 6.25e-08 @@ -6797,6 +6927,11 @@ "output_cost_per_token": 1e-05, "output_cost_per_token_batches": 5e-06, "output_cost_per_token_priority": 2e-05, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ "/v1/chat/completions", @@ -6835,6 +6970,11 @@ "output_cost_per_token": 1e-05, "output_cost_per_token_batches": 5e-06, "output_cost_per_token_priority": 2e-05, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ "/v1/chat/completions", @@ -6906,6 +7046,11 @@ "output_cost_per_token": 2e-06, "output_cost_per_token_batches": 1e-06, "output_cost_per_token_priority": 3.6e-06, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ "/v1/chat/completions", @@ -6944,6 +7089,11 @@ "output_cost_per_token": 2e-06, "output_cost_per_token_batches": 1e-06, "output_cost_per_token_priority": 3.6e-06, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ "/v1/chat/completions", @@ -6981,6 +7131,11 @@ "mode": "chat", "output_cost_per_token": 4e-07, "output_cost_per_token_batches": 2e-07, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ "/v1/chat/completions", @@ -7016,6 +7171,11 @@ "mode": "chat", "output_cost_per_token": 4e-07, "output_cost_per_token_batches": 2e-07, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ "/v1/chat/completions", @@ -7051,6 +7211,11 @@ "mode": "responses", "output_cost_per_token": 0.00012, "output_cost_per_token_batches": 6e-05, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ "/v1/responses" @@ -7112,6 +7277,11 @@ "input_cost_per_token_priority": 2.5e-06, "output_cost_per_token_batches": 5e-06, "output_cost_per_token_priority": 2e-05, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" }, "azure/gpt-5-chat": { @@ -7459,6 +7629,11 @@ "output_cost_per_token": 1.4e-05, "output_cost_per_token_batches": 7e-06, "output_cost_per_token_priority": 2.8e-05, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ "/v1/chat/completions", @@ -7498,6 +7673,11 @@ "output_cost_per_token": 1.4e-05, "output_cost_per_token_batches": 7e-06, "output_cost_per_token_priority": 2.8e-05, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ "/v1/chat/completions", @@ -7567,6 +7747,11 @@ "mode": "responses", "output_cost_per_token": 1.4e-05, "output_cost_per_token_priority": 2.8e-05, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ "/v1/responses" @@ -7599,9 +7784,9 @@ "output_cost_per_token": 0.000168, "output_cost_per_token_batches": 8.4e-05, "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ @@ -7637,9 +7822,9 @@ "output_cost_per_token": 0.000168, "output_cost_per_token_batches": 8.4e-05, "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ @@ -7996,9 +8181,9 @@ "output_cost_per_token_batches": 9e-05, "output_cost_per_token_flex": 9e-05, "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ @@ -8043,9 +8228,9 @@ "output_cost_per_token_batches": 9e-05, "output_cost_per_token_flex": 9e-05, "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ @@ -8095,9 +8280,9 @@ "output_cost_per_token_priority": 4e-05, "output_cost_per_token_above_272k_tokens_priority": 6e-05, "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 }, "supported_endpoints": [ "/v1/chat/completions", @@ -8157,9 +8342,9 @@ "output_cost_per_token_above_272k_tokens_priority": 6e-05, "output_cost_per_token_flex": 1e-05, "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ @@ -8220,9 +8405,9 @@ "output_cost_per_token_above_272k_tokens_priority": 6e-05, "output_cost_per_token_flex": 1e-05, "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ @@ -8283,9 +8468,9 @@ "output_cost_per_token_above_272k_tokens_priority": 3.6e-05, "output_cost_per_token_flex": 6e-06, "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ @@ -8346,9 +8531,9 @@ "output_cost_per_token_above_272k_tokens_priority": 3.6e-05, "output_cost_per_token_flex": 6e-06, "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ @@ -8409,9 +8594,9 @@ "output_cost_per_token_above_272k_tokens_priority": 3.6e-06, "output_cost_per_token_flex": 6e-07, "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ @@ -8472,9 +8657,9 @@ "output_cost_per_token_above_272k_tokens_priority": 3.6e-06, "output_cost_per_token_flex": 6e-07, "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 }, "supported_endpoints": [ "/v1/chat/completions", @@ -8519,9 +8704,9 @@ "output_cost_per_token": 5e-05, "output_cost_per_token_above_272k_tokens": 7.5e-05, "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ @@ -8567,9 +8752,9 @@ "output_cost_per_token": 5e-05, "output_cost_per_token_above_272k_tokens": 7.5e-05, "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ @@ -8615,9 +8800,9 @@ "output_cost_per_token": 5e-07, "output_cost_per_token_above_272k_tokens": 7.5e-07, "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 }, "source": "https://azure.microsoft.com/en-us/blog/gpt-6-astra-sol-and-luna-for-production-agents-in-microsoft-foundry/", "supported_endpoints": [ @@ -8663,9 +8848,9 @@ "output_cost_per_token": 5e-07, "output_cost_per_token_above_272k_tokens": 7.5e-07, "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 }, "source": "https://azure.microsoft.com/en-us/blog/gpt-6-astra-sol-and-luna-for-production-agents-in-microsoft-foundry/", "supported_endpoints": [ @@ -8718,7 +8903,7 @@ "output_cost_per_token_above_272k_tokens": 1.5e-05, "output_cost_per_token_above_272k_tokens_priority": 3e-05, "output_cost_per_token_priority": 2e-05, - "search_context_cost_per_query": {"search_context_size_high":0.01,"search_context_size_low":0.01,"search_context_size_medium":0.01}, + "search_context_cost_per_query": {"search_context_size_high":0.014,"search_context_size_low":0.014,"search_context_size_medium":0.014}, "source": "https://azure.microsoft.com/en-us/blog/gpt-6-astra-sol-and-luna-for-production-agents-in-microsoft-foundry/", "supported_endpoints": [ "/v1/chat/completions", @@ -8770,7 +8955,7 @@ "output_cost_per_token_above_272k_tokens": 1.5e-05, "output_cost_per_token_above_272k_tokens_priority": 3e-05, "output_cost_per_token_priority": 2e-05, - "search_context_cost_per_query": {"search_context_size_high":0.01,"search_context_size_low":0.01,"search_context_size_medium":0.01}, + "search_context_cost_per_query": {"search_context_size_high":0.014,"search_context_size_low":0.014,"search_context_size_medium":0.014}, "source": "https://azure.microsoft.com/en-us/blog/gpt-6-astra-sol-and-luna-for-production-agents-in-microsoft-foundry/", "supported_endpoints": [ "/v1/chat/completions", @@ -8800,6 +8985,53 @@ "supports_web_search": true, "supports_xhigh_reasoning_effort": true }, + "azure/gpt-6.1-terra": { + "cache_creation_input_token_cost": 1.25e-06, + "cache_creation_input_token_cost_above_272k_tokens": 2.5e-06, + "cache_read_input_token_cost": 5e-08, + "cache_read_input_token_cost_above_272k_tokens": 1e-07, + "input_cost_per_token": 1e-06, + "input_cost_per_token_above_272k_tokens": 2e-06, + "litellm_provider": "azure", + "max_input_tokens": 922000, + "max_output_tokens": 128000, + "mode": "chat", + "output_cost_per_token": 5e-06, + "output_cost_per_token_above_272k_tokens": 7.5e-06, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, + "source": "https://techcommunity.microsoft.com/blog/azure-ai-foundry-blog/gpt-6-1-terra-now-generally-available-in-microsoft-foundry-build-agents-that-see/4567769", + "supported_endpoints": [ + "/v1/chat/completions", + "/v1/responses" + ], + "supported_modalities": [ + "text", + "image" + ], + "supported_output_modalities": [ + "text" + ], + "supports_computer_use": true, + "supports_function_calling": true, + "supports_max_reasoning_effort": true, + "supports_minimal_reasoning_effort": false, + "supports_native_streaming": true, + "supports_none_reasoning_effort": false, + "supports_parallel_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_system_messages": true, + "supports_tool_choice": true, + "supports_vision": true, + "supports_web_search": true, + "supports_xhigh_reasoning_effort": true + }, "azure/gpt-6.1-sol": { "cache_creation_input_token_cost": 2.5e-06, "cache_creation_input_token_cost_above_272k_tokens": 5e-06, @@ -8815,9 +9047,9 @@ "output_cost_per_token": 1e-05, "output_cost_per_token_above_272k_tokens": 1.5e-05, "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 }, "source": "https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/models", "supported_endpoints": [ @@ -8863,9 +9095,9 @@ "output_cost_per_token": 1e-05, "output_cost_per_token_above_272k_tokens": 1.5e-05, "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 }, "source": "https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/models", "supported_endpoints": [ @@ -8896,6 +9128,53 @@ "supports_web_search": true, "supports_xhigh_reasoning_effort": true }, + "azure/us/gpt-6.1-terra": { + "cache_creation_input_token_cost": 1.375e-06, + "cache_creation_input_token_cost_above_272k_tokens": 2.75e-06, + "cache_read_input_token_cost": 5.5e-08, + "cache_read_input_token_cost_above_272k_tokens": 1.1e-07, + "input_cost_per_token": 1.1e-06, + "input_cost_per_token_above_272k_tokens": 2.2e-06, + "litellm_provider": "azure", + "max_input_tokens": 922000, + "max_output_tokens": 128000, + "mode": "chat", + "output_cost_per_token": 5.5e-06, + "output_cost_per_token_above_272k_tokens": 8.25e-06, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, + "source": "https://techcommunity.microsoft.com/blog/azure-ai-foundry-blog/gpt-6-1-terra-now-generally-available-in-microsoft-foundry-build-agents-that-see/4567769", + "supported_endpoints": [ + "/v1/chat/completions", + "/v1/responses" + ], + "supported_modalities": [ + "text", + "image" + ], + "supported_output_modalities": [ + "text" + ], + "supports_computer_use": true, + "supports_function_calling": true, + "supports_max_reasoning_effort": true, + "supports_minimal_reasoning_effort": false, + "supports_native_streaming": true, + "supports_none_reasoning_effort": false, + "supports_parallel_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_system_messages": true, + "supports_tool_choice": true, + "supports_vision": true, + "supports_web_search": true, + "supports_xhigh_reasoning_effort": true + }, "azure/us/gpt-6.1-sol": { "cache_creation_input_token_cost": 2.75e-06, "cache_creation_input_token_cost_above_272k_tokens": 5.5e-06, @@ -8911,9 +9190,9 @@ "output_cost_per_token": 1.1e-05, "output_cost_per_token_above_272k_tokens": 1.65e-05, "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 }, "source": "https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/models", "supported_endpoints": [ @@ -8944,6 +9223,53 @@ "supports_web_search": true, "supports_xhigh_reasoning_effort": true }, + "azure/eu/gpt-6.1-terra": { + "cache_creation_input_token_cost": 1.5e-06, + "cache_creation_input_token_cost_above_272k_tokens": 3e-06, + "cache_read_input_token_cost": 6e-08, + "cache_read_input_token_cost_above_272k_tokens": 1.2e-07, + "input_cost_per_token": 1.2e-06, + "input_cost_per_token_above_272k_tokens": 2.4e-06, + "litellm_provider": "azure", + "max_input_tokens": 922000, + "max_output_tokens": 128000, + "mode": "chat", + "output_cost_per_token": 6e-06, + "output_cost_per_token_above_272k_tokens": 9e-06, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, + "source": "https://techcommunity.microsoft.com/blog/azure-ai-foundry-blog/gpt-6-1-terra-now-generally-available-in-microsoft-foundry-build-agents-that-see/4567769", + "supported_endpoints": [ + "/v1/chat/completions", + "/v1/responses" + ], + "supported_modalities": [ + "text", + "image" + ], + "supported_output_modalities": [ + "text" + ], + "supports_computer_use": true, + "supports_function_calling": true, + "supports_max_reasoning_effort": true, + "supports_minimal_reasoning_effort": false, + "supports_native_streaming": true, + "supports_none_reasoning_effort": false, + "supports_parallel_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_system_messages": true, + "supports_tool_choice": true, + "supports_vision": true, + "supports_web_search": true, + "supports_xhigh_reasoning_effort": true + }, "azure/eu/gpt-6.1-sol": { "cache_creation_input_token_cost": 3e-06, "cache_creation_input_token_cost_above_272k_tokens": 6e-06, @@ -8959,9 +9285,9 @@ "output_cost_per_token": 1.2e-05, "output_cost_per_token_above_272k_tokens": 1.8e-05, "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 }, "source": "https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/models", "supported_endpoints": [ @@ -8992,6 +9318,53 @@ "supports_web_search": true, "supports_xhigh_reasoning_effort": true }, + "azure/apac/gpt-6.1-terra": { + "cache_creation_input_token_cost": 1.5e-06, + "cache_creation_input_token_cost_above_272k_tokens": 3e-06, + "cache_read_input_token_cost": 6e-08, + "cache_read_input_token_cost_above_272k_tokens": 1.2e-07, + "input_cost_per_token": 1.2e-06, + "input_cost_per_token_above_272k_tokens": 2.4e-06, + "litellm_provider": "azure", + "max_input_tokens": 922000, + "max_output_tokens": 128000, + "mode": "chat", + "output_cost_per_token": 6e-06, + "output_cost_per_token_above_272k_tokens": 9e-06, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, + "source": "https://techcommunity.microsoft.com/blog/azure-ai-foundry-blog/gpt-6-1-terra-now-generally-available-in-microsoft-foundry-build-agents-that-see/4567769", + "supported_endpoints": [ + "/v1/chat/completions", + "/v1/responses" + ], + "supported_modalities": [ + "text", + "image" + ], + "supported_output_modalities": [ + "text" + ], + "supports_computer_use": true, + "supports_function_calling": true, + "supports_max_reasoning_effort": true, + "supports_minimal_reasoning_effort": false, + "supports_native_streaming": true, + "supports_none_reasoning_effort": false, + "supports_parallel_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_system_messages": true, + "supports_tool_choice": true, + "supports_vision": true, + "supports_web_search": true, + "supports_xhigh_reasoning_effort": true + }, "azure/apac/gpt-6.1-sol": { "cache_creation_input_token_cost": 3e-06, "cache_creation_input_token_cost_above_272k_tokens": 6e-06, @@ -9007,9 +9380,9 @@ "output_cost_per_token": 1.2e-05, "output_cost_per_token_above_272k_tokens": 1.8e-05, "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 }, "source": "https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/models", "supported_endpoints": [ @@ -9134,9 +9507,9 @@ "output_cost_per_token_above_272k_tokens_priority": 6.6e-05, "output_cost_per_token_priority": 4.4e-05, "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 }, "supported_endpoints": [ "/v1/chat/completions", @@ -9188,9 +9561,9 @@ "output_cost_per_token_above_272k_tokens_priority": 6.6e-05, "output_cost_per_token_priority": 4.4e-05, "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ @@ -9243,9 +9616,9 @@ "output_cost_per_token_above_272k_tokens_priority": 3.96e-05, "output_cost_per_token_priority": 2.64e-05, "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ @@ -9298,9 +9671,9 @@ "output_cost_per_token_above_272k_tokens_priority": 3.96e-06, "output_cost_per_token_priority": 2.64e-06, "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ @@ -9345,9 +9718,9 @@ "output_cost_per_token": 5.5e-05, "output_cost_per_token_above_272k_tokens": 8.25e-05, "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ @@ -9393,9 +9766,9 @@ "output_cost_per_token": 5.5e-07, "output_cost_per_token_above_272k_tokens": 8.25e-07, "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 }, "source": "https://azure.microsoft.com/en-us/blog/gpt-6-astra-sol-and-luna-for-production-agents-in-microsoft-foundry/", "supported_endpoints": [ @@ -9448,7 +9821,7 @@ "output_cost_per_token_above_272k_tokens": 1.65e-05, "output_cost_per_token_above_272k_tokens_priority": 3.3e-05, "output_cost_per_token_priority": 2.2e-05, - "search_context_cost_per_query": {"search_context_size_high":0.01,"search_context_size_low":0.01,"search_context_size_medium":0.01}, + "search_context_cost_per_query": {"search_context_size_high":0.014,"search_context_size_low":0.014,"search_context_size_medium":0.014}, "source": "https://azure.microsoft.com/en-us/blog/gpt-6-astra-sol-and-luna-for-production-agents-in-microsoft-foundry/", "supported_endpoints": [ "/v1/chat/completions", @@ -9536,9 +9909,9 @@ "output_cost_per_token_above_272k_tokens_priority": 6.6e-05, "output_cost_per_token_priority": 4.4e-05, "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 }, "supported_endpoints": [ "/v1/chat/completions", @@ -9590,9 +9963,9 @@ "output_cost_per_token_above_272k_tokens_priority": 6.6e-05, "output_cost_per_token_priority": 4.4e-05, "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ @@ -9645,9 +10018,9 @@ "output_cost_per_token_above_272k_tokens_priority": 3.96e-05, "output_cost_per_token_priority": 2.64e-05, "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ @@ -9700,9 +10073,9 @@ "output_cost_per_token_above_272k_tokens_priority": 3.96e-06, "output_cost_per_token_priority": 2.64e-06, "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ @@ -9760,9 +10133,9 @@ "output_cost_per_token_above_272k_tokens_priority": 9e-05, "output_cost_per_token_batches": 1.5e-05, "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ @@ -9814,9 +10187,9 @@ "output_cost_per_token_above_272k_tokens_batches": 2.475e-05, "output_cost_per_token_batches": 1.65e-05, "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ @@ -9868,9 +10241,9 @@ "output_cost_per_token_above_272k_tokens_batches": 2.475e-05, "output_cost_per_token_batches": 1.65e-05, "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ @@ -9921,9 +10294,9 @@ "output_cost_per_token_priority": 7.5e-05, "output_cost_per_token_above_272k_tokens_priority": 9e-05, "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 }, "supported_endpoints": [ "/v1/chat/completions", @@ -9981,9 +10354,9 @@ "output_cost_per_token_priority": 7.5e-05, "output_cost_per_token_above_272k_tokens_priority": 9e-05, "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 }, "supported_endpoints": [ "/v1/chat/completions", @@ -10034,9 +10407,9 @@ "max_output_tokens": 128000, "mode": "chat", "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 }, "supported_endpoints": [ "/v1/chat/completions", @@ -10086,9 +10459,9 @@ "max_output_tokens": 128000, "mode": "chat", "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 }, "supported_endpoints": [ "/v1/chat/completions", @@ -10139,9 +10512,9 @@ "max_output_tokens": 128000, "mode": "chat", "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 }, "supported_endpoints": [ "/v1/chat/completions", @@ -10191,9 +10564,9 @@ "max_output_tokens": 128000, "mode": "chat", "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 }, "supported_endpoints": [ "/v1/chat/completions", @@ -10239,9 +10612,9 @@ "output_cost_per_token": 0.00018, "output_cost_per_token_above_272k_tokens": 0.00027, "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 }, "supported_endpoints": [ "/v1/batch", @@ -10282,9 +10655,9 @@ "output_cost_per_token": 0.00018, "output_cost_per_token_above_272k_tokens": 0.00027, "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 }, "supported_endpoints": [ "/v1/batch", @@ -10322,9 +10695,9 @@ "mode": "chat", "output_cost_per_token": 4.5e-06, "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 }, "supported_endpoints": [ "/v1/chat/completions", @@ -10372,9 +10745,9 @@ "mode": "chat", "output_cost_per_token": 4.5e-06, "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 }, "supported_endpoints": [ "/v1/chat/completions", @@ -10423,9 +10796,9 @@ "mode": "chat", "output_cost_per_token": 1.25e-06, "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 }, "supported_endpoints": [ "/v1/chat/completions", @@ -10470,9 +10843,9 @@ "mode": "chat", "output_cost_per_token": 1.25e-06, "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 }, "supported_endpoints": [ "/v1/chat/completions", @@ -10934,6 +11307,11 @@ "max_output_tokens": 100000, "mode": "chat", "output_cost_per_token": 8e-06, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "supported_endpoints": [ "/v1/chat/completions", "/v1/batch", @@ -10965,6 +11343,11 @@ "mode": "chat", "output_cost_per_token": 8e-06, "output_cost_per_token_batches": 4e-06, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ "/v1/chat/completions", @@ -10996,9 +11379,9 @@ "mode": "responses", "output_cost_per_token": 4e-05, "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ @@ -11065,6 +11448,11 @@ "mode": "responses", "output_cost_per_token": 8e-05, "output_cost_per_token_batches": 4e-05, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ "/v1/batch", @@ -11095,6 +11483,11 @@ "mode": "responses", "output_cost_per_token": 8e-05, "output_cost_per_token_batches": 4e-05, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ "/v1/batch", @@ -11124,6 +11517,11 @@ "max_output_tokens": 100000, "mode": "chat", "output_cost_per_token": 4.4e-06, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "supported_endpoints": [ "/v1/chat/completions", "/v1/batch", @@ -11155,6 +11553,11 @@ "mode": "chat", "output_cost_per_token": 4.4e-06, "output_cost_per_token_batches": 2.2e-06, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supports_function_calling": true, "supports_parallel_function_calling": false, @@ -11268,6 +11671,11 @@ "output_cost_per_token": 8.8e-06, "output_cost_per_token_batches": 4.4e-06, "output_cost_per_token_priority": 1.54e-05, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ "/v1/chat/completions", @@ -11305,6 +11713,11 @@ "output_cost_per_token": 1.76e-06, "output_cost_per_token_batches": 8.8e-07, "output_cost_per_token_priority": 3.08e-06, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ "/v1/chat/completions", @@ -11428,6 +11841,11 @@ "max_output_tokens": 16384, "mode": "chat", "output_cost_per_token": 6.6e-07, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supports_function_calling": true, "supports_parallel_function_calling": true, @@ -11446,6 +11864,11 @@ "max_output_tokens": 16384, "mode": "chat", "output_cost_per_token": 6.6e-07, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supports_function_calling": true, "supports_parallel_function_calling": true, @@ -11533,6 +11956,11 @@ "output_cost_per_token": 1.1e-05, "output_cost_per_token_batches": 5.5e-06, "output_cost_per_token_priority": 2.2e-05, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ "/v1/chat/completions", @@ -11572,6 +12000,11 @@ "output_cost_per_token": 2.2e-06, "output_cost_per_token_batches": 1.1e-06, "output_cost_per_token_priority": 3.96e-06, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ "/v1/chat/completions", @@ -11608,6 +12041,11 @@ "mode": "chat", "output_cost_per_token": 4.4e-07, "output_cost_per_token_batches": 2.2e-07, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ "/v1/chat/completions", @@ -11673,6 +12111,11 @@ "input_cost_per_token_priority": 2.75e-06, "output_cost_per_token_batches": 5.5e-06, "output_cost_per_token_priority": 2.2e-05, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" }, "azure/us/gpt-5.1-codex": { @@ -11800,6 +12243,11 @@ "mode": "chat", "output_cost_per_token": 8.8e-06, "output_cost_per_token_batches": 4.4e-06, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ "/v1/chat/completions", @@ -11832,6 +12280,11 @@ "mode": "chat", "output_cost_per_token": 8.8e-06, "output_cost_per_token_batches": 4.4e-06, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ "/v1/chat/completions", @@ -11898,6 +12351,11 @@ "mode": "chat", "output_cost_per_token": 4.84e-06, "output_cost_per_token_batches": 2.42e-06, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supports_function_calling": true, "supports_parallel_function_calling": false, @@ -11918,6 +12376,11 @@ "mode": "chat", "output_cost_per_token": 4.84e-06, "output_cost_per_token_batches": 2.42e-06, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supports_function_calling": true, "supports_parallel_function_calling": false, @@ -11935,6 +12398,7 @@ "output_cost_per_second": 0.0001 }, "azure_ai/Cohere-embed-v3-english": { + "deprecation_date": "2027-02-15", "input_cost_per_token": 1e-07, "litellm_provider": "azure_ai", "max_input_tokens": 512, @@ -11945,6 +12409,7 @@ "supports_embedding_image_input": true }, "azure_ai/Cohere-embed-v3-multilingual": { + "deprecation_date": "2027-02-15", "input_cost_per_token": 1e-07, "litellm_provider": "azure_ai", "max_input_tokens": 512, @@ -11955,6 +12420,7 @@ "supports_embedding_image_input": true }, "azure_ai/Codestral-2501": { + "deprecation_date": "2027-02-15", "input_cost_per_token": 3e-07, "litellm_provider": "azure_ai", "max_input_tokens": 256000, @@ -11974,6 +12440,7 @@ "supports_native_streaming": true }, "azure_ai/FLUX-1.1-pro": { + "deprecation_date": "2027-01-05", "litellm_provider": "azure_ai", "max_input_tokens": 5000, "mode": "image_generation", @@ -11984,6 +12451,7 @@ ] }, "azure_ai/FLUX.1-Kontext-pro": { + "deprecation_date": "2027-01-05", "litellm_provider": "azure_ai", "max_input_tokens": 5000, "mode": "image_generation", @@ -11994,6 +12462,7 @@ ] }, "azure_ai/flux.2-pro": { + "deprecation_date": "2027-01-20", "litellm_provider": "azure_ai", "max_input_tokens": 32000, "mode": "image_generation", @@ -12004,6 +12473,7 @@ ] }, "azure_ai/FLUX.2-flex": { + "deprecation_date": "2027-01-20", "input_cost_per_pixel": 5e-08, "litellm_provider": "azure_ai", "max_input_tokens": 32000, @@ -12368,6 +12838,7 @@ "supports_tool_choice": true }, "azure_ai/Llama-3.3-70B-Instruct": { + "deprecation_date": "2027-01-31", "input_cost_per_token": 7.1e-07, "litellm_provider": "azure_ai", "max_input_tokens": 128000, @@ -12379,6 +12850,7 @@ "supports_tool_choice": true }, "azure_ai/Llama-4-Maverick-17B-128E-Instruct-FP8": { + "deprecation_date": "2026-11-19", "input_cost_per_token": 2.5e-07, "litellm_provider": "azure_ai", "max_input_tokens": 1000000, @@ -12391,6 +12863,7 @@ "supports_vision": true }, "azure_ai/Llama-4-Scout-17B-16E-Instruct": { + "deprecation_date": "2027-01-31", "input_cost_per_token": 2e-07, "litellm_provider": "azure_ai", "max_input_tokens": 10000000, @@ -12624,6 +13097,7 @@ ] }, "azure_ai/cohere-command-a": { + "deprecation_date": "2027-02-15", "input_cost_per_token": 2.5e-06, "litellm_provider": "azure_ai", "max_input_tokens": 131072, @@ -12696,6 +13170,7 @@ "source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/retired-models" }, "azure_ai/cohere-rerank-v4.0-pro": { + "deprecation_date": "2027-09-13", "input_cost_per_query": 0.0025, "input_cost_per_token": 0.0, "litellm_provider": "azure_ai", @@ -12706,6 +13181,7 @@ "source": "https://techcommunity.microsoft.com/blog/azure-ai-foundry-blog/introducing-cohere-rerank-4-0-in-microsoft-foundry/4477076" }, "azure_ai/cohere-rerank-v4.0-fast": { + "deprecation_date": "2027-09-13", "input_cost_per_query": 0.002, "input_cost_per_token": 0.0, "litellm_provider": "azure_ai", @@ -12716,6 +13192,7 @@ "source": "https://techcommunity.microsoft.com/blog/azure-ai-foundry-blog/introducing-cohere-rerank-4-0-in-microsoft-foundry/4477076" }, "azure_ai/deepseek-v3.2": { + "deprecation_date": "2027-11-01", "input_cost_per_token": 5.8e-07, "litellm_provider": "azure_ai", "max_input_tokens": 128000, @@ -12730,6 +13207,7 @@ "supports_tool_choice": true }, "azure_ai/deepseek-v3.2-speciale": { + "deprecation_date": "2027-11-01", "input_cost_per_token": 5.8e-07, "litellm_provider": "azure_ai", "max_input_tokens": 128000, @@ -12800,6 +13278,7 @@ "supports_tool_choice": true }, "azure_ai/embed-v-4-0": { + "deprecation_date": "2027-06-01", "input_cost_per_token": 1.2e-07, "litellm_provider": "azure_ai", "max_input_tokens": 128000, @@ -12818,6 +13297,7 @@ "input_cost_per_image_token": 4.7e-07 }, "azure_ai/grok-4": { + "deprecation_date": "2027-01-31", "input_cost_per_token": 3e-06, "litellm_provider": "azure_ai", "max_input_tokens": 262000, @@ -12906,6 +13386,7 @@ "supports_web_search": true }, "azure_ai/grok-4-1-fast-non-reasoning": { + "deprecation_date": "2027-05-19", "input_cost_per_token": 2e-07, "output_cost_per_token": 5e-07, "litellm_provider": "azure_ai", @@ -12919,6 +13400,7 @@ "supports_web_search": true }, "azure_ai/grok-4-1-fast-reasoning": { + "deprecation_date": "2027-05-19", "input_cost_per_token": 2e-07, "output_cost_per_token": 5e-07, "litellm_provider": "azure_ai", @@ -12933,6 +13415,7 @@ "supports_web_search": true }, "azure_ai/grok-code-fast-1": { + "deprecation_date": "2027-01-31", "input_cost_per_token": 2e-07, "litellm_provider": "azure_ai", "max_input_tokens": 256000, @@ -13100,7 +13583,7 @@ "supports_tool_choice": true }, "azure_ai/mistral-small-2503": { - "deprecation_date": "2026-12-09", + "deprecation_date": "2027-02-15", "input_cost_per_token": 1e-07, "litellm_provider": "azure_ai", "max_input_tokens": 128000, @@ -14619,11 +15102,12 @@ "cache_creation_input_token_cost": 4.5e-06, "cache_creation_input_token_cost_above_1hr": 7.2e-06, "cache_read_input_token_cost": 3.6e-07, + "deprecation_date": "2027-04-08", "input_cost_per_token": 3.6e-06, "litellm_provider": "bedrock", "supports_tool_search": true, "max_input_tokens": 200000, - "max_output_tokens": 8192, + "max_output_tokens": 64000, "mode": "chat", "output_cost_per_token": 1.8e-05, "supports_assistant_prefill": true, @@ -14638,6 +15122,7 @@ "supports_native_structured_output": true, "supports_parallel_tool_use_config": true, "prompt_cache_min_tokens": 1024, + "source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-anthropic-claude-sonnet-4-5.md", "token_count_model": { "model": "anthropic.claude-sonnet-4-5-20250929-v1:0", "litellm_provider": "bedrock" @@ -14647,11 +15132,12 @@ "cache_creation_input_token_cost": 4.5e-06, "cache_creation_input_token_cost_above_1hr": 7.2e-06, "cache_read_input_token_cost": 3.6e-07, + "deprecation_date": "2027-04-08", "input_cost_per_token": 3.6e-06, "litellm_provider": "bedrock", "supports_tool_search": true, "max_input_tokens": 200000, - "max_output_tokens": 8192, + "max_output_tokens": 64000, "mode": "chat", "output_cost_per_token": 1.8e-05, "supports_assistant_prefill": true, @@ -14665,7 +15151,8 @@ "supports_vision": true, "supports_native_structured_output": true, "supports_parallel_tool_use_config": true, - "prompt_cache_min_tokens": 1024 + "prompt_cache_min_tokens": 1024, + "source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-anthropic-claude-sonnet-4-5.md" }, "bedrock/us-gov-east-1/meta.llama3-70b-instruct-v1:0": { "input_cost_per_token": 2.65e-06, @@ -14787,11 +15274,12 @@ "cache_creation_input_token_cost": 4.5e-06, "cache_creation_input_token_cost_above_1hr": 7.2e-06, "cache_read_input_token_cost": 3.6e-07, + "deprecation_date": "2027-04-08", "input_cost_per_token": 3.6e-06, "litellm_provider": "bedrock", "supports_tool_search": true, "max_input_tokens": 200000, - "max_output_tokens": 8192, + "max_output_tokens": 64000, "mode": "chat", "output_cost_per_token": 1.8e-05, "supports_assistant_prefill": true, @@ -14806,6 +15294,7 @@ "supports_native_structured_output": true, "supports_parallel_tool_use_config": true, "prompt_cache_min_tokens": 1024, + "source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-anthropic-claude-sonnet-4-5.md", "token_count_model": { "model": "anthropic.claude-sonnet-4-5-20250929-v1:0", "litellm_provider": "bedrock" @@ -14815,11 +15304,12 @@ "cache_creation_input_token_cost": 4.5e-06, "cache_creation_input_token_cost_above_1hr": 7.2e-06, "cache_read_input_token_cost": 3.6e-07, + "deprecation_date": "2027-04-08", "input_cost_per_token": 3.6e-06, "litellm_provider": "bedrock", "supports_tool_search": true, "max_input_tokens": 200000, - "max_output_tokens": 8192, + "max_output_tokens": 64000, "mode": "chat", "output_cost_per_token": 1.8e-05, "supports_assistant_prefill": true, @@ -14833,7 +15323,8 @@ "supports_vision": true, "supports_native_structured_output": true, "supports_parallel_tool_use_config": true, - "prompt_cache_min_tokens": 1024 + "prompt_cache_min_tokens": 1024, + "source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-anthropic-claude-sonnet-4-5.md" }, "bedrock/us-gov-west-1/meta.llama3-70b-instruct-v1:0": { "input_cost_per_token": 2.65e-06, @@ -15197,6 +15688,7 @@ "supports_tool_choice": true }, "cerebras/llama-3.3-70b": { + "deprecation_date": "2026-02-16", "input_cost_per_token": 8.5e-07, "litellm_provider": "cerebras", "max_input_tokens": 128000, @@ -15207,6 +15699,7 @@ "supports_tool_choice": true }, "cerebras/llama3.1-70b": { + "deprecation_date": "2025-01-17", "input_cost_per_token": 6e-07, "litellm_provider": "cerebras", "max_input_tokens": 128000, @@ -15217,6 +15710,7 @@ "supports_tool_choice": true }, "cerebras/llama3.1-8b": { + "deprecation_date": "2026-05-27", "input_cost_per_token": 1e-07, "litellm_provider": "cerebras", "max_input_tokens": 128000, @@ -15241,6 +15735,7 @@ "supports_tool_choice": true }, "cerebras/qwen-3-32b": { + "deprecation_date": "2026-02-16", "input_cost_per_token": 4e-07, "litellm_provider": "cerebras", "max_input_tokens": 128000, @@ -15552,6 +16047,7 @@ "output_cost_per_token_above_200k_tokens": 2.25e-05, "cache_creation_input_token_cost_above_200k_tokens": 7.5e-06, "cache_read_input_token_cost_above_200k_tokens": 6e-07, + "deprecation_date": "2027-04-08", "litellm_provider": "bedrock", "supports_tool_search": true, "max_input_tokens": 200000, @@ -15570,7 +16066,8 @@ "supports_parallel_tool_use_config": true, "prompt_cache_min_tokens": 1024, "input_cost_per_token_batches": 1.5e-06, - "output_cost_per_token_batches": 7.5e-06 + "output_cost_per_token_batches": 7.5e-06, + "source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-anthropic-claude-sonnet-4-5.md" }, "claude-opus-4-5-20251101": { "supports_web_search": true, @@ -15764,7 +16261,6 @@ "us": 1.1 }, "supports_output_config": true, - "supports_speed": true, "prompt_cache_min_tokens": 2048, "source": "https://platform.claude.com/docs/en/about-claude/pricing" }, @@ -15807,7 +16303,6 @@ "us": 1.1 }, "supports_output_config": true, - "supports_speed": true, "prompt_cache_min_tokens": 2048 }, "claude-fable-5": { @@ -20520,10 +21015,11 @@ "source": "https://www.databricks.com/product/pricing/foundation-model-serving" }, "databricks/databricks-claude-fable-5": { - "cache_creation_input_token_cost": 1.250004e-05, + "cache_creation_input_token_cost": 1.249997e-05, + "cache_creation_input_token_cost_above_1hr": 1.999998e-05, "cache_read_input_token_cost": 1.00002e-06, - "input_cost_per_token": 1.000006e-05, - "input_dbu_cost_per_token": 0.000142858, + "input_cost_per_token": 9.99999e-06, + "input_dbu_cost_per_token": 0.00014286, "litellm_provider": "databricks", "max_input_tokens": 1000000, "max_output_tokens": 128000, @@ -20532,7 +21028,7 @@ }, "mode": "chat", "output_cost_per_token": 5.000002e-05, - "output_dbu_cost_per_token": 0.000714286, + "output_dbu_cost_per_token": 0.00071429, "prompt_cache_min_tokens": 512, "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", "supports_adaptive_thinking": true, @@ -20548,10 +21044,11 @@ "thinking_always_on": true }, "databricks/databricks-claude-fable-5-1": { - "cache_creation_input_token_cost": 1.250004e-05, - "cache_read_input_token_cost": 2.5004e-07, - "input_cost_per_token": 1.000006e-05, - "input_dbu_cost_per_token": 0.000142858, + "cache_creation_input_token_cost": 1.249997e-05, + "cache_creation_input_token_cost_above_1hr": 1.999998e-05, + "cache_read_input_token_cost": 2.4997e-07, + "input_cost_per_token": 9.99999e-06, + "input_dbu_cost_per_token": 0.00014286, "litellm_provider": "databricks", "max_input_tokens": 1000000, "max_output_tokens": 128000, @@ -20560,7 +21057,7 @@ }, "mode": "chat", "output_cost_per_token": 5.000002e-05, - "output_dbu_cost_per_token": 0.000714286, + "output_dbu_cost_per_token": 0.00071429, "prompt_cache_min_tokens": 512, "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", "supports_adaptive_thinking": true, @@ -20578,6 +21075,7 @@ }, "databricks/databricks-claude-haiku-4-5": { "cache_creation_input_token_cost": 1.24999e-06, + "cache_creation_input_token_cost_above_1hr": 1.99997e-06, "cache_read_input_token_cost": 1.0003e-07, "input_cost_per_token": 1.00002e-06, "input_dbu_cost_per_token": 1.4286e-05, @@ -20601,9 +21099,10 @@ }, "databricks/databricks-claude-opus-4": { "cache_creation_input_token_cost": 1.874999e-05, + "cache_creation_input_token_cost_above_1hr": 2.999997e-05, "cache_read_input_token_cost": 1.50003e-06, - "input_cost_per_token": 1.5000020000000002e-05, - "input_dbu_cost_per_token": 0.000214286, + "input_cost_per_token": 1.500002e-05, + "input_dbu_cost_per_token": 0.00021429, "litellm_provider": "databricks", "max_input_tokens": 200000, "max_output_tokens": 32000, @@ -20611,8 +21110,8 @@ "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." }, "mode": "chat", - "output_cost_per_token": 7.500003000000001e-05, - "output_dbu_cost_per_token": 0.001071429, + "output_cost_per_token": 7.50001e-05, + "output_dbu_cost_per_token": 0.0010714, "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", "supports_assistant_prefill": true, "supports_function_calling": true, @@ -20624,9 +21123,10 @@ }, "databricks/databricks-claude-opus-4-1": { "cache_creation_input_token_cost": 1.874999e-05, + "cache_creation_input_token_cost_above_1hr": 2.999997e-05, "cache_read_input_token_cost": 1.50003e-06, - "input_cost_per_token": 1.5000020000000002e-05, - "input_dbu_cost_per_token": 0.000214286, + "input_cost_per_token": 1.500002e-05, + "input_dbu_cost_per_token": 0.00021429, "litellm_provider": "databricks", "max_input_tokens": 200000, "max_output_tokens": 32000, @@ -20634,8 +21134,8 @@ "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." }, "mode": "chat", - "output_cost_per_token": 7.500003000000001e-05, - "output_dbu_cost_per_token": 0.001071429, + "output_cost_per_token": 7.50001e-05, + "output_dbu_cost_per_token": 0.0010714, "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", "supports_assistant_prefill": true, "supports_function_calling": true, @@ -20647,6 +21147,7 @@ }, "databricks/databricks-claude-opus-4-5": { "cache_creation_input_token_cost": 6.25002e-06, + "cache_creation_input_token_cost_above_1hr": 9.99999e-06, "cache_read_input_token_cost": 5.0001e-07, "input_cost_per_token": 5.00003e-06, "input_dbu_cost_per_token": 7.1429e-05, @@ -20657,8 +21158,8 @@ "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." }, "mode": "chat", - "output_cost_per_token": 2.5000010000000002e-05, - "output_dbu_cost_per_token": 0.000357143, + "output_cost_per_token": 2.500001e-05, + "output_dbu_cost_per_token": 0.00035714, "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", "supports_assistant_prefill": true, "supports_function_calling": true, @@ -20671,6 +21172,7 @@ }, "databricks/databricks-claude-opus-4-6": { "cache_creation_input_token_cost": 6.25002e-06, + "cache_creation_input_token_cost_above_1hr": 9.99999e-06, "cache_read_input_token_cost": 5.0001e-07, "input_cost_per_token": 5.00003e-06, "input_dbu_cost_per_token": 7.1429e-05, @@ -20681,8 +21183,8 @@ "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." }, "mode": "chat", - "output_cost_per_token": 2.5000010000000002e-05, - "output_dbu_cost_per_token": 0.000357143, + "output_cost_per_token": 2.500001e-05, + "output_dbu_cost_per_token": 0.00035714, "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", "supports_assistant_prefill": false, "supports_function_calling": true, @@ -20695,6 +21197,7 @@ }, "databricks/databricks-claude-opus-4-7": { "cache_creation_input_token_cost": 6.25002e-06, + "cache_creation_input_token_cost_above_1hr": 9.99999e-06, "cache_read_input_token_cost": 5.0001e-07, "input_cost_per_token": 5.00003e-06, "input_dbu_cost_per_token": 7.1429e-05, @@ -20706,7 +21209,7 @@ }, "mode": "chat", "output_cost_per_token": 2.500001e-05, - "output_dbu_cost_per_token": 0.000357143, + "output_dbu_cost_per_token": 0.00035714, "prompt_cache_min_tokens": 2048, "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", "supports_adaptive_thinking": true, @@ -20721,6 +21224,7 @@ }, "databricks/databricks-claude-opus-4-8": { "cache_creation_input_token_cost": 6.25002e-06, + "cache_creation_input_token_cost_above_1hr": 9.99999e-06, "cache_read_input_token_cost": 5.0001e-07, "input_cost_per_token": 5.00003e-06, "input_dbu_cost_per_token": 7.1429e-05, @@ -20732,7 +21236,7 @@ }, "mode": "chat", "output_cost_per_token": 2.500001e-05, - "output_dbu_cost_per_token": 0.000357143, + "output_dbu_cost_per_token": 0.00035714, "prompt_cache_min_tokens": 1024, "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", "supports_adaptive_thinking": true, @@ -20748,6 +21252,7 @@ }, "databricks/databricks-claude-opus-5": { "cache_creation_input_token_cost": 6.25002e-06, + "cache_creation_input_token_cost_above_1hr": 9.99999e-06, "cache_read_input_token_cost": 5.0001e-07, "input_cost_per_token": 5.00003e-06, "input_dbu_cost_per_token": 7.1429e-05, @@ -20759,7 +21264,7 @@ }, "mode": "chat", "output_cost_per_token": 2.500001e-05, - "output_dbu_cost_per_token": 0.000357143, + "output_dbu_cost_per_token": 0.00035714, "prompt_cache_min_tokens": 512, "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", "supports_adaptive_thinking": true, @@ -20855,8 +21360,9 @@ }, "databricks/databricks-claude-sonnet-4-5": { "cache_creation_input_token_cost": 3.74997e-06, + "cache_creation_input_token_cost_above_1hr": 5.99998e-06, "cache_read_input_token_cost": 3.0002e-07, - "input_cost_per_token": 2.9999900000000002e-06, + "input_cost_per_token": 2.99999e-06, "input_dbu_cost_per_token": 4.2857e-05, "litellm_provider": "databricks", "max_input_tokens": 200000, @@ -20865,8 +21371,8 @@ "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." }, "mode": "chat", - "output_cost_per_token": 1.5000020000000002e-05, - "output_dbu_cost_per_token": 0.000214286, + "output_cost_per_token": 1.500002e-05, + "output_dbu_cost_per_token": 0.00021429, "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", "supports_assistant_prefill": true, "supports_function_calling": true, @@ -20878,8 +21384,9 @@ }, "databricks/databricks-claude-sonnet-4-6": { "cache_creation_input_token_cost": 3.74997e-06, + "cache_creation_input_token_cost_above_1hr": 5.99998e-06, "cache_read_input_token_cost": 3.0002e-07, - "input_cost_per_token": 2.9999900000000002e-06, + "input_cost_per_token": 2.99999e-06, "input_dbu_cost_per_token": 4.2857e-05, "litellm_provider": "databricks", "max_input_tokens": 1000000, @@ -20888,8 +21395,8 @@ "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." }, "mode": "chat", - "output_cost_per_token": 1.5000020000000002e-05, - "output_dbu_cost_per_token": 0.000214286, + "output_cost_per_token": 1.500002e-05, + "output_dbu_cost_per_token": 0.00021429, "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", "supports_assistant_prefill": false, "supports_function_calling": true, @@ -20901,19 +21408,20 @@ "prompt_cache_min_tokens": 1024 }, "databricks/databricks-claude-sonnet-5": { - "cache_creation_input_token_cost": 3.74997e-06, - "cache_read_input_token_cost": 3.0002e-07, - "input_cost_per_token": 2.99999e-06, - "input_dbu_cost_per_token": 4.2857e-05, + "cache_creation_input_token_cost": 2.49998e-06, + "cache_creation_input_token_cost_above_1hr": 4.00001e-06, + "cache_read_input_token_cost": 1.9999e-07, + "input_cost_per_token": 1.99997e-06, + "input_dbu_cost_per_token": 2.8571e-05, "litellm_provider": "databricks", "max_input_tokens": 1000000, "max_output_tokens": 128000, "metadata": { - "notes": "Costs per token are the published Global DBU rates times $0.070 per DBU. The '*_dbu_cost_per_token' fields are provided for reference; cost calculation reads the dollar '*_cost_per_token' fields. Introductory launch rates of 28.571 input / 142.857 output / 35.714 cache write / 2.857 cache read DBU run through 2026-08-31; the standard rates are listed here because entries carry no expiry date." + "notes": "Costs per token are the published Global DBU rates times $0.070 per DBU. The '*_dbu_cost_per_token' fields are provided for reference; cost calculation reads the dollar '*_cost_per_token' fields." }, "mode": "chat", - "output_cost_per_token": 1.500002e-05, - "output_dbu_cost_per_token": 0.000214286, + "output_cost_per_token": 9.99999e-06, + "output_dbu_cost_per_token": 0.00014286, "prompt_cache_min_tokens": 1024, "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", "supports_adaptive_thinking": true, @@ -21057,7 +21565,10 @@ }, "databricks/databricks-gemini-3-1-flash-lite": { "cache_creation_input_token_cost": 3.1248e-07, + "cache_read_input_audio_token_cost": 6.251e-08, "cache_read_input_token_cost": 3.122e-08, + "input_cost_per_audio_token": 6.2503e-07, + "input_cost_per_image_token": 3.1248e-07, "input_cost_per_token": 3.1248e-07, "input_dbu_cost_per_token": 4.464e-06, "litellm_provider": "databricks", @@ -21084,16 +21595,28 @@ ], "supports_vision": true, "supports_audio_input": true, - "supports_video_input": true + "supports_video_input": true, + "input_cost_per_token_priority": 5.6252e-07, + "output_cost_per_token_priority": 3.37498e-06, + "cache_read_input_token_cost_priority": 5.628e-08, + "cache_creation_input_token_cost_priority": 5.6252e-07, + "input_cost_per_audio_token_priority": 1.12497e-06, + "cache_read_input_audio_token_cost_priority": 1.1249e-07 }, "databricks/databricks-gemini-3-1-flash-image": { + "cache_creation_input_token_cost": 6.2503e-07, + "cache_read_input_token_cost": 6.2503e-07, + "input_cost_per_image_token": 6.2503e-07, + "input_cost_per_token": 6.2503e-07, "litellm_provider": "databricks", "max_input_tokens": 131072, "max_output_tokens": 32768, "metadata": { - "notes": "Databricks DBU rates not yet published for this model; endpoint metadata only." + "notes": "Costs per token are the published Global DBU rates times $0.070 per DBU. The '*_dbu_cost_per_token' fields are provided for reference; cost calculation reads the dollar '*_cost_per_token' fields." }, "mode": "chat", + "output_cost_per_image_token": 7.50001e-05, + "output_cost_per_token": 3.74997e-06, "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", "supported_modalities": [ "text", @@ -21107,13 +21630,19 @@ "supports_vision": true }, "databricks/databricks-gemini-3-pro-image": { + "cache_creation_input_token_cost": 2.49998e-06, + "cache_read_input_token_cost": 2.49998e-06, + "input_cost_per_image_token": 2.49998e-06, + "input_cost_per_token": 2.49998e-06, "litellm_provider": "databricks", "max_input_tokens": 65536, "max_output_tokens": 32768, "metadata": { - "notes": "Databricks DBU rates not yet published for this model; endpoint metadata only." + "notes": "Costs per token are the published Global DBU rates times $0.070 per DBU. The '*_dbu_cost_per_token' fields are provided for reference; cost calculation reads the dollar '*_cost_per_token' fields." }, "mode": "chat", + "output_cost_per_image_token": 0.0001500002, + "output_cost_per_token": 1.500002e-05, "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", "supported_modalities": [ "text", @@ -21129,7 +21658,9 @@ "databricks/databricks-gemini-3-1-pro": { "cache_creation_input_token_cost": 2.49998e-06, "cache_read_input_token_cost": 2.4997e-07, + "cache_read_input_token_cost_above_200k_tokens": 5.0001e-07, "input_cost_per_token": 2.49998e-06, + "input_cost_per_token_above_200k_tokens": 5.00003e-06, "input_dbu_cost_per_token": 3.5714e-05, "litellm_provider": "databricks", "max_input_tokens": 1048576, @@ -21139,12 +21670,9 @@ }, "mode": "chat", "output_cost_per_token": 1.5000020000000002e-05, + "output_cost_per_token_above_200k_tokens": 2.25e-05, "output_dbu_cost_per_token": 0.000214286, "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", - "supports_function_calling": true, - "supports_prompt_caching": true, - "supports_tool_choice": true, - "supports_reasoning": true, "supported_modalities": [ "text", "image", @@ -21154,13 +21682,27 @@ "supported_output_modalities": [ "text" ], - "supports_vision": true, "supports_audio_input": true, - "supports_video_input": true + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_tool_choice": true, + "supports_video_input": true, + "supports_vision": true, + "input_cost_per_token_priority": 4.50002e-06, + "output_cost_per_token_priority": 2.699998e-05, + "cache_read_input_token_cost_priority": 4.5003e-07, + "cache_creation_input_token_cost_priority": 4.50002e-06, + "input_cost_per_token_above_200k_tokens_priority": 8.99997e-06, + "output_cost_per_token_above_200k_tokens_priority": 4.049997e-05, + "cache_read_input_token_cost_above_200k_tokens_priority": 8.9999e-07 }, "databricks/databricks-gemini-3-flash": { "cache_creation_input_token_cost": 6.2503e-07, + "cache_read_input_audio_token_cost": 1.2502e-07, "cache_read_input_token_cost": 6.251e-08, + "input_cost_per_audio_token": 1.24999e-06, + "input_cost_per_image_token": 6.2503e-07, "input_cost_per_token": 6.2503e-07, "input_dbu_cost_per_token": 8.929e-06, "litellm_provider": "databricks", @@ -21187,7 +21729,13 @@ ], "supports_vision": true, "supports_audio_input": true, - "supports_video_input": true + "supports_video_input": true, + "input_cost_per_token_priority": 1.12497e-06, + "output_cost_per_token_priority": 6.75003e-06, + "cache_read_input_token_cost_priority": 1.1249e-07, + "cache_creation_input_token_cost_priority": 1.12497e-06, + "input_cost_per_audio_token_priority": 2.25001e-06, + "cache_read_input_audio_token_cost_priority": 2.2498e-07 }, "databricks/databricks-gemini-3-pro": { "cache_creation_input_token_cost": 2.49998e-06, @@ -21209,58 +21757,9 @@ "supports_tool_choice": true }, "databricks/databricks-gemini-3-8-flash": { - "litellm_provider": "databricks", - "max_input_tokens": 1048576, - "max_output_tokens": 65536, - "metadata": { - "notes": "Databricks DBU rates not yet published for this model; endpoint metadata only." - }, - "mode": "chat", - "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", - "supported_modalities": [ - "text", - "image", - "audio", - "video" - ], - "supported_output_modalities": [ - "text" - ], - "supports_function_calling": true, - "supports_reasoning": true, - "supports_sampling_params": false, - "supports_tool_choice": true, - "supports_vision": true - }, - "databricks/databricks-gemini-3-7-flash": { - "litellm_provider": "databricks", - "max_input_tokens": 1048576, - "max_output_tokens": 65536, - "metadata": { - "notes": "Databricks DBU rates not yet published for this model; endpoint metadata only." - }, - "mode": "chat", - "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", - "supported_modalities": [ - "text", - "image", - "audio", - "video" - ], - "supported_output_modalities": [ - "text" - ], - "supports_function_calling": true, - "supports_reasoning": true, - "supports_sampling_params": false, - "supports_tool_choice": true, - "supports_vision": true - }, - "databricks/databricks-gemini-3-6-flash": { - "cache_creation_input_token_cost": 1.87502e-06, - "cache_read_input_token_cost": 1.8753e-07, - "input_cost_per_token": 1.87502e-06, - "input_dbu_cost_per_token": 2.6786e-05, + "cache_creation_input_token_cost": 7.4998e-07, + "cache_read_input_token_cost": 7.497e-08, + "input_cost_per_token": 7.4998e-07, "litellm_provider": "databricks", "max_input_tokens": 1048576, "max_output_tokens": 65536, @@ -21268,8 +21767,73 @@ "notes": "Costs per token are the published Global DBU rates times $0.070 per DBU. The '*_dbu_cost_per_token' fields are provided for reference; cost calculation reads the dollar '*_cost_per_token' fields." }, "mode": "chat", - "output_cost_per_token": 9.37503e-06, - "output_dbu_cost_per_token": 0.000133929, + "output_cost_per_token": 3.74997e-06, + "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", + "supported_modalities": [ + "text", + "image", + "audio", + "video" + ], + "supported_output_modalities": [ + "text" + ], + "supports_function_calling": true, + "supports_reasoning": true, + "supports_sampling_params": false, + "supports_tool_choice": true, + "supports_vision": true, + "input_cost_per_token_priority": 1.35002e-06, + "output_cost_per_token_priority": 6.75003e-06, + "cache_read_input_token_cost_priority": 1.3503e-07, + "cache_creation_input_token_cost_priority": 1.35002e-06 + }, + "databricks/databricks-gemini-3-7-flash": { + "cache_creation_input_token_cost": 7.4998e-07, + "cache_read_input_token_cost": 7.497e-08, + "input_cost_per_token": 7.4998e-07, + "litellm_provider": "databricks", + "max_input_tokens": 1048576, + "max_output_tokens": 65536, + "metadata": { + "notes": "Costs per token are the published Global DBU rates times $0.070 per DBU. The '*_dbu_cost_per_token' fields are provided for reference; cost calculation reads the dollar '*_cost_per_token' fields." + }, + "mode": "chat", + "output_cost_per_token": 3.74997e-06, + "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", + "supported_modalities": [ + "text", + "image", + "audio", + "video" + ], + "supported_output_modalities": [ + "text" + ], + "supports_function_calling": true, + "supports_reasoning": true, + "supports_sampling_params": false, + "supports_tool_choice": true, + "supports_vision": true, + "input_cost_per_token_priority": 1.35002e-06, + "output_cost_per_token_priority": 6.75003e-06, + "cache_read_input_token_cost_priority": 1.3503e-07, + "cache_creation_input_token_cost_priority": 1.35002e-06 + }, + "databricks/databricks-gemini-3-6-flash": { + "cache_creation_input_token_cost": 7.4998e-07, + "cache_read_input_token_cost": 7.497e-08, + "input_cost_per_token": 7.4998e-07, + "input_dbu_cost_per_token": 1.0714e-05, + "litellm_provider": "databricks", + "max_input_tokens": 1048576, + "max_output_tokens": 65536, + "metadata": { + "notes": "Costs per token are the published Global DBU rates times $0.070 per DBU. The '*_dbu_cost_per_token' fields are provided for reference; cost calculation reads the dollar '*_cost_per_token' fields." + }, + "mode": "chat", + "output_cost_per_token": 3.74997e-06, + "output_dbu_cost_per_token": 5.3571e-05, "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", "supported_modalities": [ "text", @@ -21285,7 +21849,11 @@ "supports_reasoning": true, "supports_sampling_params": false, "supports_tool_choice": true, - "supports_vision": true + "supports_vision": true, + "input_cost_per_token_priority": 1.35002e-06, + "output_cost_per_token_priority": 6.75003e-06, + "cache_read_input_token_cost_priority": 1.3503e-07, + "cache_creation_input_token_cost_priority": 1.35002e-06 }, "databricks/databricks-gemini-3-5-flash": { "cache_creation_input_token_cost": 1.87502e-06, @@ -21315,7 +21883,11 @@ "supports_prompt_caching": true, "supports_reasoning": true, "supports_tool_choice": true, - "supports_vision": true + "supports_vision": true, + "input_cost_per_token_priority": 3.37498e-06, + "output_cost_per_token_priority": 2.025002e-05, + "cache_read_input_token_cost_priority": 3.3747e-07, + "cache_creation_input_token_cost_priority": 3.37498e-06 }, "databricks/databricks-gemini-3-5-flash-lite": { "cache_creation_input_token_cost": 3.7499e-07, @@ -21347,7 +21919,11 @@ "supports_response_schema": true, "supports_sampling_params": false, "supports_tool_choice": true, - "supports_vision": true + "supports_vision": true, + "input_cost_per_token_priority": 6.7501e-07, + "output_cost_per_token_priority": 5.62499e-06, + "cache_read_input_token_cost_priority": 6.748e-08, + "cache_creation_input_token_cost_priority": 6.7501e-07 }, "databricks/databricks-gemma-3-12b": { "cache_creation_input_token_cost": 1.5001e-07, @@ -21390,7 +21966,11 @@ "supports_prompt_caching": true, "supports_reasoning": true, "supports_tool_choice": true, - "supports_vision": false + "supports_vision": false, + "input_cost_per_token_priority": 2.45e-06, + "output_cost_per_token_priority": 7.7e-06, + "cache_read_input_token_cost_priority": 4.55e-07, + "cache_creation_input_token_cost_priority": 2.45e-06 }, "databricks/databricks-glm-5-3": { "cache_creation_input_token_cost": 1.4e-06, @@ -21420,7 +22000,11 @@ "supports_response_schema": true, "supports_tool_choice": true, "supports_vision": false, - "thinking_always_on": true + "thinking_always_on": true, + "input_cost_per_token_priority": 2.45e-06, + "output_cost_per_token_priority": 7.7e-06, + "cache_read_input_token_cost_priority": 4.55e-07, + "cache_creation_input_token_cost_priority": 2.45e-06 }, "databricks/databricks-glm-5-3-flash": { "cache_creation_input_token_cost": 1.5001e-07, @@ -21449,7 +22033,11 @@ "supports_reasoning": true, "supports_tool_choice": true, "supports_vision": true, - "thinking_always_on": true + "thinking_always_on": true, + "input_cost_per_token_priority": 2.625e-07, + "output_cost_per_token_priority": 8.75e-07, + "cache_read_input_token_cost_priority": 5.25e-08, + "cache_creation_input_token_cost_priority": 2.625e-07 }, "databricks/databricks-gpt-5": { "cache_creation_input_token_cost": 1.24999e-06, @@ -21468,7 +22056,11 @@ "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", "supports_function_calling": true, "supports_prompt_caching": true, - "supports_tool_choice": true + "supports_tool_choice": true, + "input_cost_per_token_priority": 2.49998e-06, + "output_cost_per_token_priority": 1.999998e-05, + "cache_read_input_token_cost_priority": 2.4997e-07, + "cache_creation_input_token_cost_priority": 2.49998e-06 }, "databricks/databricks-gpt-5-1": { "cache_creation_input_token_cost": 1.24999e-06, @@ -21487,7 +22079,11 @@ "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", "supports_function_calling": true, "supports_prompt_caching": true, - "supports_tool_choice": true + "supports_tool_choice": true, + "input_cost_per_token_priority": 2.49998e-06, + "output_cost_per_token_priority": 1.999998e-05, + "cache_read_input_token_cost_priority": 2.4997e-07, + "cache_creation_input_token_cost_priority": 2.49998e-06 }, "databricks/databricks-gpt-5-2": { "cache_creation_input_token_cost": 1.75e-06, @@ -21506,7 +22102,11 @@ "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", "supports_function_calling": true, "supports_prompt_caching": true, - "supports_tool_choice": true + "supports_tool_choice": true, + "input_cost_per_token_priority": 3.5e-06, + "output_cost_per_token_priority": 2.8e-05, + "cache_read_input_token_cost_priority": 3.5e-07, + "cache_creation_input_token_cost_priority": 3.5e-06 }, "databricks/databricks-gpt-5-3-codex": { "cache_creation_input_token_cost": 1.75e-06, @@ -21525,12 +22125,18 @@ "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", "supports_function_calling": true, "supports_prompt_caching": true, - "supports_tool_choice": true + "supports_tool_choice": true, + "input_cost_per_token_priority": 3.5e-06, + "output_cost_per_token_priority": 2.8e-05, + "cache_read_input_token_cost_priority": 3.5e-07, + "cache_creation_input_token_cost_priority": 3.5e-06 }, "databricks/databricks-gpt-5-4": { "cache_creation_input_token_cost": 2.49998e-06, "cache_read_input_token_cost": 2.4997e-07, + "cache_read_input_token_cost_above_272k_tokens": 5.0001e-07, "input_cost_per_token": 2.49998e-06, + "input_cost_per_token_above_272k_tokens": 5.00003e-06, "input_dbu_cost_per_token": 3.5714e-05, "litellm_provider": "databricks", "max_input_tokens": 922000, @@ -21540,6 +22146,7 @@ }, "mode": "chat", "output_cost_per_token": 1.5000020000000002e-05, + "output_cost_per_token_above_272k_tokens": 2.25e-05, "output_dbu_cost_per_token": 0.000214286, "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", "supported_modalities": [ @@ -21553,7 +22160,14 @@ "supports_prompt_caching": true, "supports_reasoning": true, "supports_tool_choice": true, - "supports_vision": true + "supports_vision": true, + "input_cost_per_token_priority": 5.00003e-06, + "output_cost_per_token_priority": 2.999997e-05, + "cache_read_input_token_cost_priority": 5.0001e-07, + "cache_creation_input_token_cost_priority": 5.00003e-06, + "input_cost_per_token_above_272k_tokens_priority": 5.00003e-06, + "output_cost_per_token_above_272k_tokens_priority": 2.999997e-05, + "cache_read_input_token_cost_above_272k_tokens_priority": 5.0001e-07 }, "databricks/databricks-gpt-5-4-mini": { "cache_creation_input_token_cost": 7.4998e-07, @@ -21581,7 +22195,11 @@ "supports_prompt_caching": true, "supports_reasoning": true, "supports_tool_choice": true, - "supports_vision": true + "supports_vision": true, + "input_cost_per_token_priority": 1.50003e-06, + "output_cost_per_token_priority": 8.99997e-06, + "cache_read_input_token_cost_priority": 1.5001e-07, + "cache_creation_input_token_cost_priority": 1.50003e-06 }, "databricks/databricks-gpt-5-4-nano": { "cache_creation_input_token_cost": 1.9999e-07, @@ -21613,8 +22231,11 @@ }, "databricks/databricks-gpt-5-6-sol": { "cache_creation_input_token_cost": 5.00003e-06, + "cache_creation_input_token_cost_above_272k_tokens": 9.99999e-06, "cache_read_input_token_cost": 3.9998e-07, + "cache_read_input_token_cost_above_272k_tokens": 8.0003e-07, "input_cost_per_token": 4.00001e-06, + "input_cost_per_token_above_272k_tokens": 8.00002e-06, "input_dbu_cost_per_token": 5.7143e-05, "litellm_provider": "databricks", "max_input_tokens": 922000, @@ -21624,6 +22245,7 @@ }, "mode": "chat", "output_cost_per_token": 1.999998e-05, + "output_cost_per_token_above_272k_tokens": 3e-05, "output_dbu_cost_per_token": 0.000285714, "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", "supported_modalities": [ @@ -21637,13 +22259,24 @@ "supports_prompt_caching": true, "supports_reasoning": true, "supports_tool_choice": true, - "supports_vision": true + "supports_vision": true, + "input_cost_per_token_priority": 8.00002e-06, + "output_cost_per_token_priority": 4.000003e-05, + "cache_read_input_token_cost_priority": 8.0003e-07, + "cache_creation_input_token_cost_priority": 9.99999e-06, + "input_cost_per_token_above_272k_tokens_priority": 1.599997e-05, + "output_cost_per_token_above_272k_tokens_priority": 6.000001e-05, + "cache_read_input_token_cost_above_272k_tokens_priority": 1.59999e-06, + "cache_creation_input_token_cost_above_272k_tokens_priority": 1.999998e-05 }, "databricks/databricks-gpt-5-6-terra": { - "cache_creation_input_token_cost": 3.12501e-06, - "cache_read_input_token_cost": 2.4997e-07, - "input_cost_per_token": 2.49998e-06, - "input_dbu_cost_per_token": 3.5714e-05, + "cache_creation_input_token_cost": 2.49998e-06, + "cache_creation_input_token_cost_above_272k_tokens": 5.00003e-06, + "cache_read_input_token_cost": 1.9999e-07, + "cache_read_input_token_cost_above_272k_tokens": 3.9998e-07, + "input_cost_per_token": 1.99997e-06, + "input_cost_per_token_above_272k_tokens": 4.00001e-06, + "input_dbu_cost_per_token": 2.8571e-05, "litellm_provider": "databricks", "max_input_tokens": 922000, "max_output_tokens": 128000, @@ -21651,8 +22284,9 @@ "notes": "Costs per token are the published Global DBU rates times $0.070 per DBU. The '*_dbu_cost_per_token' fields are provided for reference; cost calculation reads the dollar '*_cost_per_token' fields." }, "mode": "chat", - "output_cost_per_token": 1.500002e-05, - "output_dbu_cost_per_token": 0.000214286, + "output_cost_per_token": 1.200003e-05, + "output_cost_per_token_above_272k_tokens": 1.8e-05, + "output_dbu_cost_per_token": 0.000171429, "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", "supported_modalities": [ "text", @@ -21665,13 +22299,24 @@ "supports_prompt_caching": true, "supports_reasoning": true, "supports_tool_choice": true, - "supports_vision": true + "supports_vision": true, + "input_cost_per_token_priority": 4.00001e-06, + "output_cost_per_token_priority": 2.399999e-05, + "cache_read_input_token_cost_priority": 3.9998e-07, + "cache_creation_input_token_cost_priority": 5.00003e-06, + "input_cost_per_token_above_272k_tokens_priority": 8.00002e-06, + "output_cost_per_token_above_272k_tokens_priority": 3.600002e-05, + "cache_read_input_token_cost_above_272k_tokens_priority": 8.0003e-07, + "cache_creation_input_token_cost_above_272k_tokens_priority": 9.99999e-06 }, "databricks/databricks-gpt-5-6-luna": { - "cache_creation_input_token_cost": 1.24999e-06, - "cache_read_input_token_cost": 1.0003e-07, - "input_cost_per_token": 1.00002e-06, - "input_dbu_cost_per_token": 1.4286e-05, + "cache_creation_input_token_cost": 2.4997e-07, + "cache_creation_input_token_cost_above_272k_tokens": 5.0001e-07, + "cache_read_input_token_cost": 2.002e-08, + "cache_read_input_token_cost_above_272k_tokens": 3.997e-08, + "input_cost_per_token": 1.9999e-07, + "input_cost_per_token_above_272k_tokens": 3.9998e-07, + "input_dbu_cost_per_token": 2.857e-06, "litellm_provider": "databricks", "max_input_tokens": 922000, "max_output_tokens": 128000, @@ -21679,8 +22324,9 @@ "notes": "Costs per token are the published Global DBU rates times $0.070 per DBU. The '*_dbu_cost_per_token' fields are provided for reference; cost calculation reads the dollar '*_cost_per_token' fields." }, "mode": "chat", - "output_cost_per_token": 5.99998e-06, - "output_dbu_cost_per_token": 8.5714e-05, + "output_cost_per_token": 1.20001e-06, + "output_cost_per_token_above_272k_tokens": 1.79998e-06, + "output_dbu_cost_per_token": 1.7143e-05, "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", "supported_modalities": [ "text", @@ -21693,12 +22339,22 @@ "supports_prompt_caching": true, "supports_reasoning": true, "supports_tool_choice": true, - "supports_vision": true + "supports_vision": true, + "input_cost_per_token_priority": 3.9998e-07, + "output_cost_per_token_priority": 2.40002e-06, + "cache_read_input_token_cost_priority": 3.997e-08, + "cache_creation_input_token_cost_priority": 5.0001e-07, + "input_cost_per_token_above_272k_tokens_priority": 8.0003e-07, + "output_cost_per_token_above_272k_tokens_priority": 3.60003e-06, + "cache_read_input_token_cost_above_272k_tokens_priority": 8.001e-08, + "cache_creation_input_token_cost_above_272k_tokens_priority": 1.00002e-06 }, "databricks/databricks-gpt-5-5": { "cache_creation_input_token_cost": 5.00003e-06, "cache_read_input_token_cost": 5.0001e-07, + "cache_read_input_token_cost_above_272k_tokens": 1.00002e-06, "input_cost_per_token": 5.00003e-06, + "input_cost_per_token_above_272k_tokens": 9.99999e-06, "input_dbu_cost_per_token": 7.1429e-05, "litellm_provider": "databricks", "max_input_tokens": 922000, @@ -21708,6 +22364,7 @@ }, "mode": "responses", "output_cost_per_token": 2.999997e-05, + "output_cost_per_token_above_272k_tokens": 4.5e-05, "output_dbu_cost_per_token": 0.000428571, "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", "supported_modalities": [ @@ -21721,13 +22378,21 @@ "supports_prompt_caching": true, "supports_reasoning": true, "supports_tool_choice": true, - "supports_vision": true + "supports_vision": true, + "input_cost_per_token_priority": 1.249997e-05, + "output_cost_per_token_priority": 7.50001e-05, + "cache_read_input_token_cost_priority": 1.24999e-06, + "cache_creation_input_token_cost_priority": 1.249997e-05, + "input_cost_per_token_above_272k_tokens_priority": 1.249997e-05, + "output_cost_per_token_above_272k_tokens_priority": 7.50001e-05, + "cache_read_input_token_cost_above_272k_tokens_priority": 1.24999e-06 }, "databricks/databricks-gpt-5-5-pro": { "cache_creation_input_token_cost": 2.999997e-05, "cache_read_input_token_cost": 2.999997e-05, "input_cost_per_token": 2.999997e-05, - "input_dbu_cost_per_token": 0.000428571, + "input_cost_per_token_above_272k_tokens": 6e-05, + "input_dbu_cost_per_token": 0.00042857, "litellm_provider": "databricks", "max_input_tokens": 922000, "max_output_tokens": 128000, @@ -21735,8 +22400,9 @@ "notes": "Costs per token are the published Global DBU rates times $0.070 per DBU. The '*_dbu_cost_per_token' fields are provided for reference; cost calculation reads the dollar '*_cost_per_token' fields." }, "mode": "responses", - "output_cost_per_token": 0.00018000003, - "output_dbu_cost_per_token": 0.002571429, + "output_cost_per_token": 0.0001800001, + "output_cost_per_token_above_272k_tokens": 0.00027, + "output_dbu_cost_per_token": 0.0025714, "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", "supported_modalities": [ "text", @@ -21768,7 +22434,11 @@ "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", "supports_function_calling": true, "supports_prompt_caching": true, - "supports_tool_choice": true + "supports_tool_choice": true, + "input_cost_per_token_priority": 4.5003e-07, + "output_cost_per_token_priority": 3.60003e-06, + "cache_read_input_token_cost_priority": 4.501e-08, + "cache_creation_input_token_cost_priority": 4.5003e-07 }, "databricks/databricks-gpt-5-nano": { "cache_creation_input_token_cost": 4.998e-08, @@ -21918,7 +22588,11 @@ "supports_prompt_caching": true, "supports_reasoning": true, "supports_tool_choice": true, - "supports_vision": true + "supports_vision": true, + "input_cost_per_token_priority": 5.25e-06, + "output_cost_per_token_priority": 2.625e-05, + "cache_read_input_token_cost_priority": 5.25e-07, + "cache_creation_input_token_cost_priority": 5.25e-06 }, "databricks/system.ai.kimi-k3": { "litellm_provider": "databricks", @@ -22000,7 +22674,11 @@ "supports_reasoning": true, "supports_tool_choice": true, "supports_vision": false, - "thinking_always_on": true + "thinking_always_on": true, + "input_cost_per_token_priority": 3.85e-07, + "output_cost_per_token_priority": 3.85e-06, + "cache_read_input_token_cost_priority": 3.85e-07, + "cache_creation_input_token_cost_priority": 3.85e-07 }, "databricks/databricks-qwen3-next-80b-a3b-instruct": { "cache_creation_input_token_cost": 1.5001e-07, @@ -22055,6 +22733,25 @@ "output_dbu_cost_per_token": 0.0, "source": "https://docs.databricks.com/aws/en/machine-learning/foundation-model-apis/supported-models" }, + "databricks/databricks-typesafeai-jev-1-14-0": { + "cache_creation_input_token_cost": 4.2e-08, + "cache_read_input_token_cost": 4.2e-08, + "input_cost_per_token": 4.2e-08, + "input_dbu_cost_per_token": 6e-07, + "litellm_provider": "databricks", + "metadata": { + "notes": "TypeSafe AI Jev 1.14.0, provider-hosted by TypeSafe AI and served through Unity Gateway, queried through the System One API. The proprietary pricing page lists 'Jev 1.14' at 0.600 DBU per 1M input tokens; input_cost_per_token is that times $0.070 per DBU. Output is free. No cache rates are published, so cache tokens bill at the input rate." + }, + "mode": "evaluation", + "output_cost_per_token": 0.0, + "output_dbu_cost_per_token": 0.0, + "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", + "supported_modalities": [ + "text", + "image" + ], + "supports_vision": true + }, "databricks/ai_decide": { "cache_creation_input_token_cost": 0.0, "cache_read_input_token_cost": 0.0, @@ -27374,7 +28071,7 @@ "supports_reasoning": true, "supports_response_schema": true, "supports_tool_choice": true, - "supports_vision": false + "supports_vision": true }, "fireworks_ai/accounts/fireworks/models/mixtral-8x22b-instruct-hf": { "input_cost_per_token": 1.2e-06, @@ -27648,7 +28345,7 @@ "supports_reasoning": true, "supports_response_schema": true, "supports_tool_choice": true, - "supports_vision": false + "supports_vision": true }, "fireworks_ai/qwen3p7-plus": { "cache_read_input_token_cost": 8e-08, @@ -28162,6 +28859,7 @@ "mode": "image_generation", "output_cost_per_image": 0.039, "output_cost_per_image_token": 3e-05, + "output_cost_per_image_token_batches": 1.5e-05, "output_cost_per_reasoning_token": 2.5e-06, "output_cost_per_token": 2.5e-06, "output_cost_per_token_batches": 1.25e-06, @@ -28219,6 +28917,7 @@ "mode": "image_generation", "output_cost_per_image": 0.134, "output_cost_per_image_token": 0.00012, + "output_cost_per_image_token_batches": 6e-05, "output_cost_per_token": 1.2e-05, "output_cost_per_token_above_200k_tokens": 1.8e-05, "output_cost_per_token_above_200k_tokens_priority": 3.24e-05, @@ -28272,12 +28971,13 @@ "mode": "image_generation", "output_cost_per_image": 0.134, "output_cost_per_image_token": 0.00012, + "output_cost_per_image_token_batches": 6e-05, "output_cost_per_token": 1.2e-05, "output_cost_per_token_priority": 2.16e-05, "output_cost_per_token_above_200k_tokens": 1.8e-05, "output_cost_per_token_above_200k_tokens_priority": 3.24e-05, "output_cost_per_token_batches": 6e-06, - "source": "https://ai.google.dev/gemini-api/docs/pricing", + "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", "supported_endpoints": [ "/v1/chat/completions", "/v1/images/generations", @@ -28323,6 +29023,7 @@ "mode": "image_generation", "output_cost_per_image": 0.0672, "output_cost_per_image_token": 6e-05, + "output_cost_per_image_token_batches": 3e-05, "output_cost_per_token": 3e-06, "output_cost_per_token_batches": 1.5e-06, "output_cost_per_token_flex": 1.5e-06, @@ -28368,9 +29069,10 @@ "mode": "image_generation", "output_cost_per_image": 0.0672, "output_cost_per_image_token": 6e-05, + "output_cost_per_image_token_batches": 3e-05, "output_cost_per_token": 3e-06, "output_cost_per_token_batches": 1.5e-06, - "source": "https://cloud.google.com/vertex-ai/generative-ai/pricing#gemini-models", + "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", "supported_endpoints": [ "/v1/chat/completions", "/v1/images/generations", @@ -28415,6 +29117,7 @@ "mode": "image_generation", "output_cost_per_image": 0.0336, "output_cost_per_image_token": 3e-05, + "output_cost_per_image_token_batches": 1.5e-05, "output_cost_per_token": 1.5e-06, "output_cost_per_token_batches": 7.5e-07, "output_cost_per_token_flex": 7.5e-07, @@ -28981,10 +29684,12 @@ }, "search_free_requests": {"count": 10000, "period": "day", "shared_group": "gemini-2.5-pro"}, "google_maps_grounding_cost_per_query": 0.025, + "input_cost_per_token_above_200k_tokens_batches": 1.25e-06, "input_cost_per_token_above_200k_tokens_priority": 4.5e-06, "input_cost_per_token_batches": 6.25e-07, "input_cost_per_token_flex": 6.25e-07, "input_cost_per_token_priority": 2.25e-06, + "output_cost_per_token_above_200k_tokens_batches": 7.5e-06, "output_cost_per_token_above_200k_tokens_priority": 2.7e-05, "output_cost_per_token_batches": 5e-06, "output_cost_per_token_flex": 5e-06, @@ -28999,6 +29704,7 @@ "google_maps_grounding_cost_per_query": 0.014, "input_cost_per_token": 2e-06, "input_cost_per_token_above_200k_tokens": 4e-06, + "input_cost_per_token_above_200k_tokens_batches": 2e-06, "input_cost_per_token_above_200k_tokens_priority": 7.2e-06, "input_cost_per_token_batches": 1e-06, "input_cost_per_token_flex": 1e-06, @@ -29010,6 +29716,7 @@ "output_cost_per_image": 0.00012, "output_cost_per_token": 1.2e-05, "output_cost_per_token_above_200k_tokens": 1.8e-05, + "output_cost_per_token_above_200k_tokens_batches": 9e-06, "output_cost_per_token_above_200k_tokens_priority": 3.24e-05, "output_cost_per_token_batches": 6e-06, "output_cost_per_token_flex": 6e-06, @@ -29538,6 +30245,7 @@ "google_maps_grounding_cost_per_query": 0.014, "input_cost_per_token": 2e-06, "input_cost_per_token_above_200k_tokens": 4e-06, + "input_cost_per_token_above_200k_tokens_batches": 2e-06, "input_cost_per_token_above_200k_tokens_priority": 7.2e-06, "input_cost_per_token_batches": 1e-06, "input_cost_per_token_flex": 1e-06, @@ -29549,6 +30257,7 @@ "output_cost_per_image": 0.00012, "output_cost_per_token": 1.2e-05, "output_cost_per_token_above_200k_tokens": 1.8e-05, + "output_cost_per_token_above_200k_tokens_batches": 9e-06, "output_cost_per_token_above_200k_tokens_priority": 3.24e-05, "output_cost_per_token_batches": 6e-06, "output_cost_per_token_flex": 6e-06, @@ -34478,6 +35187,7 @@ "source": "https://developers.openai.com/api/docs/pricing" }, "gpt-4o-mini-tts": { + "deprecation_date": "2027-01-06", "input_cost_per_token": 6e-07, "litellm_provider": "openai", "mode": "audio_speech", @@ -35095,6 +35805,7 @@ "cache_read_input_token_cost_batches": 6.25e-08, "cache_read_input_token_cost_flex": 6.25e-08, "cache_read_input_token_cost_priority": 2.5e-07, + "deprecation_date": "2026-12-11", "input_cost_per_token": 1.25e-06, "input_cost_per_token_batches": 6.25e-07, "input_cost_per_token_flex": 6.25e-07, @@ -35107,6 +35818,13 @@ "output_cost_per_token_batches": 5e-06, "output_cost_per_token_flex": 5e-06, "output_cost_per_token_priority": 2e-05, + "reasoning_contexts": [ + "auto", + "current_turn" + ], + "reasoning_modes": [ + "standard" + ], "search_context_cost_per_query": { "search_context_size_high": 0.01, "search_context_size_low": 0.01, @@ -35184,6 +35902,13 @@ "mode": "chat", "output_cost_per_token": 1e-05, "output_cost_per_token_priority": 2e-05, + "reasoning_contexts": [ + "auto", + "current_turn" + ], + "reasoning_modes": [ + "standard" + ], "search_context_cost_per_query": { "search_context_size_high": 0.01, "search_context_size_low": 0.01, @@ -35351,6 +36076,7 @@ "cache_read_input_token_cost_batches": 6.25e-08, "cache_read_input_token_cost_flex": 6.25e-08, "cache_read_input_token_cost_priority": 2.5e-07, + "deprecation_date": "2027-04-01", "input_cost_per_token": 1.25e-06, "input_cost_per_token_priority": 2.5e-06, "litellm_provider": "openai", @@ -35359,6 +36085,13 @@ "mode": "chat", "output_cost_per_token": 1e-05, "output_cost_per_token_priority": 2e-05, + "reasoning_contexts": [ + "auto", + "current_turn" + ], + "reasoning_modes": [ + "standard" + ], "search_context_cost_per_query": { "search_context_size_high": 0.01, "search_context_size_low": 0.01, @@ -35410,6 +36143,13 @@ "mode": "chat", "output_cost_per_token": 1.4e-05, "output_cost_per_token_priority": 2.8e-05, + "reasoning_contexts": [ + "auto", + "current_turn" + ], + "reasoning_modes": [ + "standard" + ], "search_context_cost_per_query": { "search_context_size_high": 0.01, "search_context_size_low": 0.01, @@ -35525,6 +36265,13 @@ "mode": "chat", "output_cost_per_token": 1.4e-05, "output_cost_per_token_priority": 2.8e-05, + "reasoning_contexts": [ + "auto", + "current_turn" + ], + "reasoning_modes": [ + "standard" + ], "search_context_cost_per_query": { "search_context_size_high": 0.01, "search_context_size_low": 0.01, @@ -35574,6 +36321,13 @@ "mode": "responses", "output_cost_per_token": 0.000168, "output_cost_per_token_batches": 8.4e-05, + "reasoning_contexts": [ + "auto", + "current_turn" + ], + "reasoning_modes": [ + "pro" + ], "search_context_cost_per_query": { "search_context_size_high": 0.01, "search_context_size_low": 0.01, @@ -35615,6 +36369,13 @@ "mode": "responses", "output_cost_per_token": 0.000168, "output_cost_per_token_batches": 8.4e-05, + "reasoning_contexts": [ + "auto", + "current_turn" + ], + "reasoning_modes": [ + "pro" + ], "search_context_cost_per_query": { "search_context_size_high": 0.01, "search_context_size_low": 0.01, @@ -35650,15 +36411,15 @@ "gpt-6-astra": { "cache_creation_input_token_cost": 1.25e-05, "cache_creation_input_token_cost_above_12hr": 2.5e-05, + "cache_creation_input_token_cost_above_12hr_ultrafast": 0.00015, + "cache_creation_input_token_cost_above_12hr_batches": 1.25e-05, "cache_creation_input_token_cost_above_12hr_above_272k_tokens": 5e-05, "cache_creation_input_token_cost_above_12hr_above_272k_tokens_batches": 2.5e-05, "cache_creation_input_token_cost_above_12hr_above_272k_tokens_flex": 2.5e-05, "cache_creation_input_token_cost_above_12hr_above_272k_tokens_priority": 0.0001, "cache_creation_input_token_cost_above_12hr_above_272k_tokens_ultrafast": 0.0003, - "cache_creation_input_token_cost_above_12hr_batches": 1.25e-05, "cache_creation_input_token_cost_above_12hr_flex": 1.25e-05, "cache_creation_input_token_cost_above_12hr_priority": 5e-05, - "cache_creation_input_token_cost_above_12hr_ultrafast": 0.00015, "cache_creation_input_token_cost_above_272k_tokens": 2.5e-05, "cache_creation_input_token_cost_above_272k_tokens_flex": 1.25e-05, "cache_creation_input_token_cost_above_272k_tokens_priority": 5e-05, @@ -35702,6 +36463,15 @@ "output_cost_per_token_flex": 2.5e-05, "output_cost_per_token_priority": 0.0001, "output_cost_per_token_ultrafast": 0.0003, + "reasoning_contexts": [ + "auto", + "current_turn", + "all_turns" + ], + "reasoning_modes": [ + "standard", + "pro" + ], "regional_processing_uplift_multiplier_eu": 1.1, "regional_processing_uplift_multiplier_us": 1.1, "search_context_cost_per_query": { @@ -35786,6 +36556,15 @@ "output_cost_per_token_above_272k_tokens_batches": 7.5e-06, "output_cost_per_token_flex": 5e-06, "output_cost_per_token_priority": 2e-05, + "reasoning_contexts": [ + "auto", + "current_turn", + "all_turns" + ], + "reasoning_modes": [ + "standard", + "pro" + ], "regional_processing_uplift_multiplier_eu": 1.1, "regional_processing_uplift_multiplier_us": 1.1, "search_context_cost_per_query": { @@ -35828,11 +36607,11 @@ "gpt-6-luna": { "cache_creation_input_token_cost": 1.25e-07, "cache_creation_input_token_cost_above_12hr": 2.5e-07, + "cache_creation_input_token_cost_above_12hr_batches": 1.25e-07, "cache_creation_input_token_cost_above_12hr_above_272k_tokens": 5e-07, "cache_creation_input_token_cost_above_12hr_above_272k_tokens_batches": 2.5e-07, "cache_creation_input_token_cost_above_12hr_above_272k_tokens_flex": 2.5e-07, "cache_creation_input_token_cost_above_12hr_above_272k_tokens_priority": 1e-06, - "cache_creation_input_token_cost_above_12hr_batches": 1.25e-07, "cache_creation_input_token_cost_above_12hr_flex": 1.25e-07, "cache_creation_input_token_cost_above_12hr_priority": 5e-07, "cache_creation_input_token_cost_decisions": 1.25e-07, @@ -35878,6 +36657,15 @@ "output_cost_per_token_above_272k_tokens_batches": 3.75e-07, "output_cost_per_token_flex": 2.5e-07, "output_cost_per_token_priority": 1e-06, + "reasoning_contexts": [ + "auto", + "current_turn", + "all_turns" + ], + "reasoning_modes": [ + "standard", + "pro" + ], "regional_processing_uplift_multiplier_eu": 1.1, "regional_processing_uplift_multiplier_us": 1.1, "search_context_cost_per_query": { @@ -35961,6 +36749,15 @@ "output_cost_per_token_above_272k_tokens_batches": 1.5e-05, "output_cost_per_token_flex": 1e-05, "output_cost_per_token_priority": 4e-05, + "reasoning_contexts": [ + "auto", + "current_turn", + "all_turns" + ], + "reasoning_modes": [ + "standard", + "pro" + ], "regional_processing_uplift_multiplier_eu": 1.1, "regional_processing_uplift_multiplier_us": 1.1, "search_context_cost_per_query": { @@ -36042,6 +36839,15 @@ "output_cost_per_token_above_272k_tokens_batches": 1.5e-05, "output_cost_per_token_flex": 1e-05, "output_cost_per_token_priority": 4e-05, + "reasoning_contexts": [ + "auto", + "current_turn", + "all_turns" + ], + "reasoning_modes": [ + "standard", + "pro" + ], "regional_processing_uplift_multiplier_eu": 1.1, "regional_processing_uplift_multiplier_us": 1.1, "search_context_cost_per_query": { @@ -36125,6 +36931,15 @@ "output_cost_per_token_above_272k_tokens_batches": 9e-06, "output_cost_per_token_flex": 6e-06, "output_cost_per_token_priority": 2.4e-05, + "reasoning_contexts": [ + "auto", + "current_turn", + "all_turns" + ], + "reasoning_modes": [ + "standard", + "pro" + ], "regional_processing_uplift_multiplier_eu": 1.1, "regional_processing_uplift_multiplier_us": 1.1, "search_context_cost_per_query": { @@ -36207,6 +37022,15 @@ "output_cost_per_token_above_272k_tokens_batches": 9e-07, "output_cost_per_token_flex": 6e-07, "output_cost_per_token_priority": 2.4e-06, + "reasoning_contexts": [ + "auto", + "current_turn", + "all_turns" + ], + "reasoning_modes": [ + "standard", + "pro" + ], "regional_processing_uplift_multiplier_eu": 1.1, "regional_processing_uplift_multiplier_us": 1.1, "search_context_cost_per_query": { @@ -36444,6 +37268,14 @@ "reasoning_effort_levels": [ "medium" ], + "reasoning_contexts": [ + "auto", + "current_turn", + "all_turns" + ], + "reasoning_modes": [ + "standard" + ], "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/chat/completions", @@ -36491,6 +37323,14 @@ "output_cost_per_token_batches": 1.5e-05, "output_cost_per_token_above_272k_tokens_batches": 2.25e-05, "output_cost_per_token_priority": 7.5e-05, + "reasoning_contexts": [ + "auto", + "current_turn", + "all_turns" + ], + "reasoning_modes": [ + "standard" + ], "regional_processing_uplift_multiplier_eu": 1.1, "regional_processing_uplift_multiplier_us": 1.1, "search_context_cost_per_query": { @@ -36553,6 +37393,14 @@ "output_cost_per_token_batches": 1.5e-05, "output_cost_per_token_above_272k_tokens_batches": 2.25e-05, "output_cost_per_token_priority": 7.5e-05, + "reasoning_contexts": [ + "auto", + "current_turn", + "all_turns" + ], + "reasoning_modes": [ + "standard" + ], "regional_processing_uplift_multiplier_eu": 1.1, "regional_processing_uplift_multiplier_us": 1.1, "search_context_cost_per_query": { @@ -36607,6 +37455,14 @@ "output_cost_per_token_flex": 9e-05, "output_cost_per_token_batches": 9e-05, "output_cost_per_token_above_272k_tokens_batches": 0.000135, + "reasoning_contexts": [ + "auto", + "current_turn", + "all_turns" + ], + "reasoning_modes": [ + "pro" + ], "regional_processing_uplift_multiplier_eu": 1.1, "regional_processing_uplift_multiplier_us": 1.1, "search_context_cost_per_query": { @@ -36658,6 +37514,14 @@ "output_cost_per_token_flex": 9e-05, "output_cost_per_token_batches": 9e-05, "output_cost_per_token_above_272k_tokens_batches": 0.000135, + "reasoning_contexts": [ + "auto", + "current_turn", + "all_turns" + ], + "reasoning_modes": [ + "pro" + ], "regional_processing_uplift_multiplier_eu": 1.1, "regional_processing_uplift_multiplier_us": 1.1, "search_context_cost_per_query": { @@ -36717,6 +37581,14 @@ "output_cost_per_token_batches": 7.5e-06, "output_cost_per_token_above_272k_tokens_batches": 1.125e-05, "output_cost_per_token_priority": 3e-05, + "reasoning_contexts": [ + "auto", + "current_turn", + "all_turns" + ], + "reasoning_modes": [ + "standard" + ], "regional_processing_uplift_multiplier_eu": 1.1, "regional_processing_uplift_multiplier_us": 1.1, "supported_endpoints": [ @@ -36774,6 +37646,14 @@ "output_cost_per_token_batches": 7.5e-06, "output_cost_per_token_above_272k_tokens_batches": 1.125e-05, "output_cost_per_token_priority": 3e-05, + "reasoning_contexts": [ + "auto", + "current_turn", + "all_turns" + ], + "reasoning_modes": [ + "standard" + ], "regional_processing_uplift_multiplier_eu": 1.1, "regional_processing_uplift_multiplier_us": 1.1, "supported_endpoints": [ @@ -36823,6 +37703,14 @@ "output_cost_per_token_flex": 9e-05, "output_cost_per_token_batches": 9e-05, "output_cost_per_token_above_272k_tokens_batches": 0.000135, + "reasoning_contexts": [ + "auto", + "current_turn", + "all_turns" + ], + "reasoning_modes": [ + "pro" + ], "regional_processing_uplift_multiplier_eu": 1.1, "regional_processing_uplift_multiplier_us": 1.1, "search_context_cost_per_query": { @@ -36875,6 +37763,14 @@ "output_cost_per_token_flex": 9e-05, "output_cost_per_token_batches": 9e-05, "output_cost_per_token_above_272k_tokens_batches": 0.000135, + "reasoning_contexts": [ + "auto", + "current_turn", + "all_turns" + ], + "reasoning_modes": [ + "pro" + ], "regional_processing_uplift_multiplier_eu": 1.1, "regional_processing_uplift_multiplier_us": 1.1, "search_context_cost_per_query": { @@ -36929,6 +37825,14 @@ "output_cost_per_token_flex": 2.25e-06, "output_cost_per_token_batches": 2.25e-06, "output_cost_per_token_priority": 9e-06, + "reasoning_contexts": [ + "auto", + "current_turn", + "all_turns" + ], + "reasoning_modes": [ + "standard" + ], "regional_processing_uplift_multiplier_eu": 1.1, "regional_processing_uplift_multiplier_us": 1.1, "search_context_cost_per_query": { @@ -36983,6 +37887,14 @@ "output_cost_per_token_flex": 2.25e-06, "output_cost_per_token_batches": 2.25e-06, "output_cost_per_token_priority": 9e-06, + "reasoning_contexts": [ + "auto", + "current_turn", + "all_turns" + ], + "reasoning_modes": [ + "standard" + ], "regional_processing_uplift_multiplier_eu": 1.1, "regional_processing_uplift_multiplier_us": 1.1, "search_context_cost_per_query": { @@ -37034,6 +37946,14 @@ "output_cost_per_token": 1.25e-06, "output_cost_per_token_flex": 6.25e-07, "output_cost_per_token_batches": 6.25e-07, + "reasoning_contexts": [ + "auto", + "current_turn", + "all_turns" + ], + "reasoning_modes": [ + "standard" + ], "regional_processing_uplift_multiplier_eu": 1.1, "regional_processing_uplift_multiplier_us": 1.1, "search_context_cost_per_query": { @@ -37075,6 +37995,7 @@ "cache_read_input_token_cost": 2e-08, "cache_read_input_token_cost_batches": 1e-08, "cache_read_input_token_cost_flex": 1e-08, + "deprecation_date": "2027-04-01", "input_cost_per_token": 2e-07, "input_cost_per_token_flex": 1e-07, "input_cost_per_token_batches": 1e-07, @@ -37085,6 +38006,14 @@ "output_cost_per_token": 1.25e-06, "output_cost_per_token_flex": 6.25e-07, "output_cost_per_token_batches": 6.25e-07, + "reasoning_contexts": [ + "auto", + "current_turn", + "all_turns" + ], + "reasoning_modes": [ + "standard" + ], "regional_processing_uplift_multiplier_eu": 1.1, "regional_processing_uplift_multiplier_us": 1.1, "search_context_cost_per_query": { @@ -37122,6 +38051,7 @@ "supports_minimal_reasoning_effort": false }, "gpt-5-pro": { + "deprecation_date": "2026-12-11", "input_cost_per_token": 1.5e-05, "input_cost_per_token_batches": 7.5e-06, "litellm_provider": "openai", @@ -37130,6 +38060,13 @@ "mode": "responses", "output_cost_per_token": 0.00012, "output_cost_per_token_batches": 6e-05, + "reasoning_contexts": [ + "auto", + "current_turn" + ], + "reasoning_modes": [ + "pro" + ], "search_context_cost_per_query": { "search_context_size_high": 0.01, "search_context_size_low": 0.01, @@ -37172,6 +38109,13 @@ "mode": "responses", "output_cost_per_token": 0.00012, "output_cost_per_token_batches": 6e-05, + "reasoning_contexts": [ + "auto", + "current_turn" + ], + "reasoning_modes": [ + "pro" + ], "search_context_cost_per_query": { "search_context_size_high": 0.01, "search_context_size_low": 0.01, @@ -37222,6 +38166,13 @@ "output_cost_per_token_batches": 5e-06, "output_cost_per_token_flex": 5e-06, "output_cost_per_token_priority": 2e-05, + "reasoning_contexts": [ + "auto", + "current_turn" + ], + "reasoning_modes": [ + "standard" + ], "search_context_cost_per_query": { "search_context_size_high": 0.01, "search_context_size_low": 0.01, @@ -37332,6 +38283,13 @@ "mode": "responses", "output_cost_per_token": 1.4e-05, "output_cost_per_token_priority": 2.8e-05, + "reasoning_contexts": [ + "auto", + "current_turn" + ], + "reasoning_modes": [ + "standard" + ], "search_context_cost_per_query": { "search_context_size_high": 0.01, "search_context_size_low": 0.01, @@ -37401,6 +38359,7 @@ "cache_read_input_token_cost_batches": 1.25e-08, "cache_read_input_token_cost_flex": 1.25e-08, "cache_read_input_token_cost_priority": 4.5e-08, + "deprecation_date": "2026-12-11", "input_cost_per_token": 2.5e-07, "input_cost_per_token_batches": 1.25e-07, "input_cost_per_token_flex": 1.25e-07, @@ -37413,6 +38372,13 @@ "output_cost_per_token_batches": 1e-06, "output_cost_per_token_flex": 1e-06, "output_cost_per_token_priority": 3.6e-06, + "reasoning_contexts": [ + "auto", + "current_turn" + ], + "reasoning_modes": [ + "standard" + ], "search_context_cost_per_query": { "search_context_size_high": 0.01, "search_context_size_low": 0.01, @@ -37464,6 +38430,13 @@ "output_cost_per_token_batches": 1e-06, "output_cost_per_token_flex": 1e-06, "output_cost_per_token_priority": 3.6e-06, + "reasoning_contexts": [ + "auto", + "current_turn" + ], + "reasoning_modes": [ + "standard" + ], "search_context_cost_per_query": { "search_context_size_high": 0.01, "search_context_size_low": 0.01, @@ -37501,10 +38474,10 @@ "cache_read_input_token_cost": 5e-09, "cache_read_input_token_cost_batches": 2.5e-09, "cache_read_input_token_cost_flex": 2.5e-09, + "deprecation_date": "2026-12-11", "input_cost_per_token": 5e-08, "input_cost_per_token_batches": 2.5e-08, "input_cost_per_token_flex": 2.5e-08, - "input_cost_per_token_priority": 2.5e-06, "litellm_provider": "openai", "max_input_tokens": 272000, "max_output_tokens": 128000, @@ -37512,6 +38485,13 @@ "output_cost_per_token": 4e-07, "output_cost_per_token_batches": 2e-07, "output_cost_per_token_flex": 2e-07, + "reasoning_contexts": [ + "auto", + "current_turn" + ], + "reasoning_modes": [ + "standard" + ], "search_context_cost_per_query": { "search_context_size_high": 0.01, "search_context_size_low": 0.01, @@ -37552,7 +38532,6 @@ "deprecation_date": "2026-12-11", "input_cost_per_token": 5e-08, "input_cost_per_token_batches": 2.5e-08, - "input_cost_per_token_priority": 2.5e-06, "input_cost_per_token_flex": 2.5e-08, "litellm_provider": "openai", "max_input_tokens": 272000, @@ -37561,6 +38540,13 @@ "output_cost_per_token": 4e-07, "output_cost_per_token_batches": 2e-07, "output_cost_per_token_flex": 2e-07, + "reasoning_contexts": [ + "auto", + "current_turn" + ], + "reasoning_modes": [ + "standard" + ], "search_context_cost_per_query": { "search_context_size_high": 0.01, "search_context_size_low": 0.01, @@ -38212,6 +39198,7 @@ }, "supports_function_calling": true, "supports_parallel_function_calling": true, + "supports_prompt_caching": true, "supports_reasoning": true, "supports_response_schema": true, "supports_tool_choice": true, @@ -38232,6 +39219,7 @@ }, "supports_function_calling": true, "supports_parallel_function_calling": true, + "supports_prompt_caching": true, "supports_reasoning": true, "supports_response_schema": true, "supports_tool_choice": true, @@ -38251,6 +39239,7 @@ "search_context_size_medium": 0.005 }, "supports_function_calling": true, + "supports_prompt_caching": true, "supports_reasoning": true, "supports_response_schema": true, "supports_tool_choice": true, @@ -40950,6 +41939,120 @@ "supports_system_messages": true, "supports_native_structured_output": true }, + "bedrock/ap-southeast-2/mistral.voxtral-mini-3b-2507": { + "deprecation_date": "2027-03-30", + "input_cost_per_token": 4.12e-08, + "input_cost_per_token_batches": 2.06e-08, + "input_cost_per_token_flex": 2.06e-08, + "input_cost_per_token_priority": 7.21e-08, + "litellm_provider": "bedrock", + "max_input_tokens": 32768, + "max_output_tokens": 8192, + "mode": "chat", + "output_cost_per_token": 4.12e-08, + "output_cost_per_token_batches": 2.06e-08, + "output_cost_per_token_flex": 2.06e-08, + "output_cost_per_token_priority": 7.21e-08, + "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrock/current/ap-southeast-2/index.json", + "supports_audio_input": true, + "supports_system_messages": true, + "supports_native_structured_output": true + }, + "bedrock/ap-southeast-2/mistral.voxtral-small-24b-2507": { + "deprecation_date": "2027-03-30", + "input_cost_per_token": 1.03e-07, + "input_cost_per_token_batches": 5.15e-08, + "input_cost_per_token_flex": 5.15e-08, + "input_cost_per_token_priority": 1.8025e-07, + "litellm_provider": "bedrock", + "max_input_tokens": 32768, + "max_output_tokens": 8192, + "mode": "chat", + "output_cost_per_token": 3.09e-07, + "output_cost_per_token_batches": 1.545e-07, + "output_cost_per_token_flex": 1.545e-07, + "output_cost_per_token_priority": 5.4075e-07, + "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrock/current/ap-southeast-2/index.json", + "supports_audio_input": true, + "supports_system_messages": true, + "supports_native_structured_output": true + }, + "bedrock/ap-northeast-1/mistral.voxtral-mini-3b-2507": { + "deprecation_date": "2027-03-30", + "input_cost_per_token": 5e-08, + "input_cost_per_token_batches": 3e-08, + "input_cost_per_token_flex": 3e-08, + "input_cost_per_token_priority": 9e-08, + "litellm_provider": "bedrock", + "max_input_tokens": 32768, + "max_output_tokens": 8192, + "mode": "chat", + "output_cost_per_token": 5e-08, + "output_cost_per_token_batches": 3e-08, + "output_cost_per_token_flex": 3e-08, + "output_cost_per_token_priority": 9e-08, + "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrock/current/ap-northeast-1/index.json", + "supports_audio_input": true, + "supports_system_messages": true, + "supports_native_structured_output": true + }, + "bedrock/ap-northeast-1/mistral.voxtral-small-24b-2507": { + "deprecation_date": "2027-03-30", + "input_cost_per_token": 1.2e-07, + "input_cost_per_token_batches": 6e-08, + "input_cost_per_token_flex": 6e-08, + "input_cost_per_token_priority": 2.1e-07, + "litellm_provider": "bedrock", + "max_input_tokens": 32768, + "max_output_tokens": 8192, + "mode": "chat", + "output_cost_per_token": 3.6e-07, + "output_cost_per_token_batches": 1.8e-07, + "output_cost_per_token_flex": 1.8e-07, + "output_cost_per_token_priority": 6.3e-07, + "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrock/current/ap-northeast-1/index.json", + "supports_audio_input": true, + "supports_system_messages": true, + "supports_native_structured_output": true + }, + "bedrock/eu-west-2/mistral.voxtral-mini-3b-2507": { + "deprecation_date": "2027-03-30", + "input_cost_per_token": 6e-08, + "input_cost_per_token_batches": 3e-08, + "input_cost_per_token_flex": 3e-08, + "input_cost_per_token_priority": 1.1e-07, + "litellm_provider": "bedrock", + "max_input_tokens": 32768, + "max_output_tokens": 8192, + "mode": "chat", + "output_cost_per_token": 6e-08, + "output_cost_per_token_batches": 3e-08, + "output_cost_per_token_flex": 3e-08, + "output_cost_per_token_priority": 1.1e-07, + "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrock/current/eu-west-2/index.json", + "supports_audio_input": true, + "supports_system_messages": true, + "supports_native_structured_output": true + }, + "bedrock/eu-west-2/mistral.voxtral-small-24b-2507": { + "deprecation_date": "2027-03-30", + "input_cost_per_token": 1.6e-07, + "input_cost_per_token_batches": 8e-08, + "input_cost_per_token_flex": 8e-08, + "input_cost_per_token_priority": 2.8e-07, + "litellm_provider": "bedrock", + "max_input_tokens": 32768, + "max_output_tokens": 8192, + "mode": "chat", + "output_cost_per_token": 4.7e-07, + "output_cost_per_token_batches": 2.3e-07, + "output_cost_per_token_flex": 2.3e-07, + "output_cost_per_token_priority": 8.2e-07, + "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrock/current/eu-west-2/index.json", + "supports_audio_input": true, + "supports_system_messages": true, + "supports_native_structured_output": true + }, "mistral/codestral-2508": { "cache_read_input_token_cost": 3e-08, "input_cost_per_token": 3e-07, @@ -40998,9 +42101,14 @@ "max_output_tokens": 256000, "mode": "chat", "output_cost_per_token": 3e-07, + "reasoning_effort_levels": [ + "none", + "high" + ], "source": "https://docs.mistral.ai/models/devstral-small-2-25-12", "supports_assistant_prefill": true, "supports_function_calling": true, + "supports_reasoning": true, "supports_response_schema": true, "supports_tool_choice": true }, @@ -41012,9 +42120,14 @@ "max_output_tokens": 256000, "mode": "chat", "output_cost_per_token": 2e-06, + "reasoning_effort_levels": [ + "none", + "high" + ], "source": "https://mistral.ai/news/devstral-2-vibe-cli", "supports_assistant_prefill": true, "supports_function_calling": true, + "supports_reasoning": true, "supports_response_schema": true, "supports_tool_choice": true }, @@ -41026,9 +42139,14 @@ "max_output_tokens": 256000, "mode": "chat", "output_cost_per_token": 2e-06, + "reasoning_effort_levels": [ + "none", + "high" + ], "source": "https://mistral.ai/news/devstral-2-vibe-cli", "supports_assistant_prefill": true, "supports_function_calling": true, + "supports_reasoning": true, "supports_response_schema": true, "supports_tool_choice": true }, @@ -41333,6 +42451,22 @@ "supports_response_schema": true, "supports_tool_choice": true }, + "mistral/deepseek-v4-1-flash-1017": { + "cache_read_input_token_cost": 7e-09, + "input_cost_per_token": 3e-07, + "litellm_provider": "mistral", + "max_input_tokens": 1048576, + "max_output_tokens": 131072, + "mode": "chat", + "output_cost_per_token": 1.2e-06, + "source": "https://docs.mistral.ai/models/deepseek-v4-flash-1017", + "supports_assistant_prefill": true, + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_tool_choice": true + }, "mistral/zai-glm-5-3": { "cache_read_input_token_cost": 1.4e-07, "input_cost_per_token": 1.4e-06, @@ -41549,13 +42683,13 @@ "mode": "embedding" }, "mistral/mistral-large-4": { - "cache_read_input_token_cost": 6.8e-08, - "input_cost_per_token": 6.8e-07, + "cache_read_input_token_cost": 1.4e-07, + "input_cost_per_token": 1.36e-06, "litellm_provider": "mistral", "max_input_tokens": 1048576, "max_output_tokens": 1048576, "mode": "chat", - "output_cost_per_token": 2.09e-06, + "output_cost_per_token": 4.18e-06, "reasoning_effort_levels": [ "none", "high" @@ -41570,13 +42704,13 @@ "supports_vision": true }, "mistral/mistral-large-4-0": { - "cache_read_input_token_cost": 6.8e-08, - "input_cost_per_token": 6.8e-07, + "cache_read_input_token_cost": 1.4e-07, + "input_cost_per_token": 1.36e-06, "litellm_provider": "mistral", "max_input_tokens": 1048576, "max_output_tokens": 1048576, "mode": "chat", - "output_cost_per_token": 2.09e-06, + "output_cost_per_token": 4.18e-06, "reasoning_effort_levels": [ "none", "high" @@ -41723,8 +42857,13 @@ "max_output_tokens": 8191, "mode": "chat", "output_cost_per_token": 3e-07, + "reasoning_effort_levels": [ + "none", + "high" + ], "supports_assistant_prefill": true, "supports_function_calling": true, + "supports_reasoning": true, "supports_response_schema": true, "supports_tool_choice": true }, @@ -41923,6 +43062,7 @@ }, "moonshot/kimi-k2.5": { "cache_read_input_token_cost": 1e-07, + "deprecation_date": "2026-08-31", "input_cost_per_token": 6e-07, "litellm_provider": "moonshot", "max_input_tokens": 262144, @@ -41953,7 +43093,31 @@ "supports_video_input": true, "supports_vision": true }, + "moonshot/kimi-k3.1-pro": { + "cache_creation_input_token_cost": 2e-06, + "cache_creation_input_token_cost_above_1hr": 4e-06, + "cache_read_input_token_cost": 2e-07, + "input_cost_per_token": 2e-06, + "litellm_provider": "moonshot", + "max_input_tokens": 1048576, + "max_output_tokens": 1048576, + "mode": "chat", + "output_cost_per_token": 1e-05, + "reasoning_effort_levels": [ + "low", + "high", + "max" + ], + "source": "https://platform.kimi.ai/docs/pricing/chat", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_vision": true + }, "moonshot/kimi-k3": { + "cache_creation_input_token_cost": 3e-06, + "cache_creation_input_token_cost_above_1hr": 6e-06, "cache_read_input_token_cost": 3e-07, "input_cost_per_token": 3e-06, "litellm_provider": "moonshot", @@ -41968,6 +43132,7 @@ ], "source": "https://platform.kimi.ai/docs/pricing/chat-k3", "supports_function_calling": true, + "supports_prompt_caching": true, "supports_reasoning": true, "supports_response_schema": true, "supports_tool_choice": true, @@ -41975,6 +43140,7 @@ "supports_vision": true }, "moonshot/moonshot-v1-128k": { + "deprecation_date": "2026-08-31", "input_cost_per_token": 2e-06, "litellm_provider": "moonshot", "max_input_tokens": 131072, @@ -41987,6 +43153,7 @@ "supports_tool_choice": true }, "moonshot/moonshot-v1-128k-vision-preview": { + "deprecation_date": "2026-08-31", "input_cost_per_token": 2e-06, "litellm_provider": "moonshot", "max_input_tokens": 131072, @@ -42000,6 +43167,7 @@ "supports_vision": true }, "moonshot/moonshot-v1-32k": { + "deprecation_date": "2026-08-31", "input_cost_per_token": 1e-06, "litellm_provider": "moonshot", "max_input_tokens": 32768, @@ -42012,6 +43180,7 @@ "supports_tool_choice": true }, "moonshot/moonshot-v1-32k-vision-preview": { + "deprecation_date": "2026-08-31", "input_cost_per_token": 1e-06, "litellm_provider": "moonshot", "max_input_tokens": 32768, @@ -42025,6 +43194,7 @@ "supports_vision": true }, "moonshot/moonshot-v1-8k": { + "deprecation_date": "2026-08-31", "input_cost_per_token": 2e-07, "litellm_provider": "moonshot", "max_input_tokens": 8192, @@ -42037,6 +43207,7 @@ "supports_tool_choice": true }, "moonshot/moonshot-v1-8k-vision-preview": { + "deprecation_date": "2026-08-31", "input_cost_per_token": 2e-07, "litellm_provider": "moonshot", "max_input_tokens": 8192, @@ -42050,6 +43221,7 @@ "supports_vision": true }, "moonshot/moonshot-v1-auto": { + "deprecation_date": "2026-08-31", "input_cost_per_token": 2e-06, "litellm_provider": "moonshot", "max_input_tokens": 131072, @@ -43242,6 +44414,7 @@ "cache_read_input_token_cost": 5e-07, "cache_read_input_token_cost_flex": 2.5e-07, "cache_read_input_token_cost_priority": 8.75e-07, + "deprecation_date": "2026-12-11", "input_cost_per_token": 2e-06, "input_cost_per_token_batches": 1e-06, "input_cost_per_token_flex": 1e-06, @@ -43254,6 +44427,13 @@ "output_cost_per_token_batches": 4e-06, "output_cost_per_token_flex": 4e-06, "output_cost_per_token_priority": 1.4e-05, + "reasoning_contexts": [ + "auto", + "current_turn" + ], + "reasoning_modes": [ + "standard" + ], "search_context_cost_per_query": { "search_context_size_high": 0.01, "search_context_size_low": 0.01, @@ -43362,6 +44542,13 @@ "output_cost_per_token_batches": 4e-06, "output_cost_per_token_flex": 4e-06, "output_cost_per_token_priority": 1.4e-05, + "reasoning_contexts": [ + "auto", + "current_turn" + ], + "reasoning_modes": [ + "standard" + ], "search_context_cost_per_query": { "search_context_size_high": 0.01, "search_context_size_low": 0.01, @@ -43432,6 +44619,7 @@ "supports_vision": false }, "o3-pro": { + "deprecation_date": "2026-12-11", "input_cost_per_token": 2e-05, "input_cost_per_token_batches": 1e-05, "litellm_provider": "openai", @@ -43440,6 +44628,13 @@ "mode": "responses", "output_cost_per_token": 8e-05, "output_cost_per_token_batches": 4e-05, + "reasoning_contexts": [ + "auto", + "current_turn" + ], + "reasoning_modes": [ + "pro" + ], "search_context_cost_per_query": { "search_context_size_high": 0.01, "search_context_size_low": 0.01, @@ -43477,6 +44672,13 @@ "mode": "responses", "output_cost_per_token": 8e-05, "output_cost_per_token_batches": 4e-05, + "reasoning_contexts": [ + "auto", + "current_turn" + ], + "reasoning_modes": [ + "pro" + ], "search_context_cost_per_query": { "search_context_size_high": 0.01, "search_context_size_low": 0.01, @@ -47292,13 +48494,13 @@ "supports_reasoning": true }, "together_ai/Qwen/Qwen3.7-Max": { - "cache_read_input_token_cost": 3e-07, - "input_cost_per_token": 1.5e-06, + "cache_read_input_token_cost": 5e-07, + "input_cost_per_token": 2.5e-06, "litellm_provider": "together_ai", "max_input_tokens": 1000000, "max_output_tokens": 1000000, "mode": "chat", - "output_cost_per_token": 4.5e-06, + "output_cost_per_token": 7.5e-06, "source": "https://www.together.ai/pricing", "supports_prompt_caching": true }, @@ -47808,6 +49010,7 @@ "cache_creation_input_token_cost_above_200k_tokens": 9e-06, "cache_creation_input_token_cost_above_1hr_above_200k_tokens": 1.44e-05, "cache_read_input_token_cost_above_200k_tokens": 7.2e-07, + "deprecation_date": "2027-04-08", "litellm_provider": "bedrock_converse", "supports_tool_search": true, "max_input_tokens": 200000, @@ -47826,7 +49029,7 @@ "supports_native_structured_output": true, "supports_parallel_tool_use_config": true, "prompt_cache_min_tokens": 1024, - "source": "https://aws.amazon.com/bedrock/pricing/", + "source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-anthropic-claude-sonnet-4-5.md", "token_count_model": { "model": "anthropic.claude-sonnet-4-5-20250929-v1:0", "litellm_provider": "bedrock" @@ -50839,6 +52042,7 @@ "mode": "image_generation", "output_cost_per_image": 0.039, "output_cost_per_image_token": 3e-05, + "output_cost_per_image_token_batches": 1.5e-05, "output_cost_per_reasoning_token": 2.5e-06, "output_cost_per_token": 2.5e-06, "output_cost_per_token_batches": 1.25e-06, @@ -50897,6 +52101,7 @@ "mode": "image_generation", "output_cost_per_image": 0.134, "output_cost_per_image_token": 0.00012, + "output_cost_per_image_token_batches": 6e-05, "output_cost_per_token": 1.2e-05, "output_cost_per_token_above_200k_tokens": 1.8e-05, "output_cost_per_token_above_200k_tokens_priority": 3.24e-05, @@ -50931,13 +52136,14 @@ "mode": "image_generation", "output_cost_per_image": 0.134, "output_cost_per_image_token": 0.00012, + "output_cost_per_image_token_batches": 6e-05, "output_cost_per_token": 1.2e-05, "output_cost_per_token_priority": 2.16e-05, "output_cost_per_token_above_200k_tokens": 1.8e-05, "output_cost_per_token_above_200k_tokens_priority": 3.24e-05, "output_cost_per_token_batches": 6e-06, "supports_reasoning": false, - "source": "https://docs.cloud.google.com/vertex-ai/generative-ai/docs/models/gemini/3-pro-image", + "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", "supported_endpoints": [ "/v1/chat/completions", "/v1/images/generations", @@ -50963,6 +52169,7 @@ "mode": "image_generation", "output_cost_per_image": 0.0672, "output_cost_per_image_token": 6e-05, + "output_cost_per_image_token_batches": 3e-05, "output_cost_per_token": 3e-06, "output_cost_per_token_batches": 1.5e-06, "output_cost_per_token_flex": 1.5e-06, @@ -50990,10 +52197,11 @@ "mode": "image_generation", "output_cost_per_image": 0.0672, "output_cost_per_image_token": 6e-05, + "output_cost_per_image_token_batches": 3e-05, "output_cost_per_token": 3e-06, "output_cost_per_token_batches": 1.5e-06, "supports_reasoning": false, - "source": "https://cloud.google.com/vertex-ai/generative-ai/pricing#gemini-models", + "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", "supported_endpoints": [ "/v1/chat/completions", "/v1/images/generations", @@ -51018,6 +52226,7 @@ "mode": "image_generation", "output_cost_per_image": 0.0336, "output_cost_per_image_token": 3e-05, + "output_cost_per_image_token_batches": 1.5e-05, "output_cost_per_token": 1.5e-06, "output_cost_per_token_batches": 7.5e-07, "output_cost_per_token_flex": 7.5e-07, @@ -52903,15 +54112,21 @@ "xai/grok-4.7": { "cache_read_input_token_cost": 5e-07, "cache_read_input_token_cost_above_200k_tokens": 1e-06, + "cache_read_input_token_cost_above_200k_tokens_batches": 8e-07, + "cache_read_input_token_cost_batches": 4e-07, "input_cost_per_image_token": 2e-06, "input_cost_per_token": 2e-06, "input_cost_per_token_above_200k_tokens": 4e-06, + "input_cost_per_token_above_200k_tokens_batches": 3.2e-06, + "input_cost_per_token_batches": 1.6e-06, "litellm_provider": "xai", "max_input_tokens": 500000, "max_output_tokens": 500000, "mode": "chat", "output_cost_per_token": 6e-06, "output_cost_per_token_above_200k_tokens": 1.2e-05, + "output_cost_per_token_above_200k_tokens_batches": 9.6e-06, + "output_cost_per_token_batches": 4.8e-06, "source": "https://api.x.ai/v1/language-models", "supports_function_calling": true, "supports_prompt_caching": true, @@ -56992,6 +58207,7 @@ ] }, 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"max_output_tokens": 64000, + "mode": "chat", + "output_cost_per_token": 2.25e-06, + "supports_function_calling": true, + "supports_vision": true, + "supports_reasoning": false, + "source": "https://www.streamlake.ai/document/DOC/mgrnm4xm362hvp5wyce" + }, + "streamlake/qwen3.8-2.4t-a95b": { + "cache_read_input_token_cost": 2.5e-07, + "input_cost_per_token": 2e-06, + "litellm_provider": "streamlake", + "max_input_tokens": 983616, + "max_output_tokens": 128000, + "mode": "chat", + "output_cost_per_token": 6e-06, + "supports_function_calling": true, + "supports_reasoning": true, + "supports_vision": true, + "cache_creation_input_token_cost": 2.5e-06, + "explicit_cache_read_input_token_cost": 1.7e-07, + "supports_prompt_caching": true, + "source": "https://www.streamlake.ai/document/DOC/mgrnm4xm362hvp5wyce" + }, + "streamlake/qwen3.8-27b": { + "cache_read_input_token_cost": 1e-07, + "input_cost_per_token": 5e-07, + "litellm_provider": "streamlake", + "max_input_tokens": 983616, + "max_output_tokens": 128000, + "mode": "chat", + "output_cost_per_token": 3e-06, + "supports_function_calling": true, + "supports_reasoning": true, + "supports_vision": true, + "cache_creation_input_token_cost": 6.25e-07, + "explicit_cache_read_input_token_cost": 5e-08, + "supports_prompt_caching": true, + "source": "https://www.streamlake.ai/document/DOC/mgrnm4xm362hvp5wyce" + }, "deepseek-v4-flash": { "cache_creation_input_token_cost": 0.0, "cache_read_input_token_cost": 6e-09, @@ -60908,6 +62477,39 @@ "supports_reasoning": true, "supports_vision": false }, + "tencent/seedream-image-v5.0-flash": { + "litellm_provider": "tencent", + "mode": "image_generation", + "output_cost_per_image": 0.018, + "output_cost_per_image_token": 1.6e-06, + "source": "https://cloud.tencent.com/document/product/1823/130055", + "supported_endpoints": [ + "/v1/images/generations", + "/v1/images/edits" + ] + }, + "tencent/seedream-image-v5.0-lite": { + "litellm_provider": "tencent", + "mode": "image_generation", + "output_cost_per_image": 0.035, + "output_cost_per_image_token": 1.6e-06, + "source": "https://www.tencentcloud.com/document/product/1300/78937", + "supported_endpoints": [ + "/v1/images/generations", + "/v1/images/edits" + ] + }, + "tencent/seedream-image-v5.0-pro": { + "litellm_provider": "tencent", + "mode": "image_generation", + "output_cost_per_image": 0.09, + "output_cost_per_image_token": 1.6e-06, + "source": "https://www.tencentcloud.com/document/product/1300/78937", + "supported_endpoints": [ + "/v1/images/generations", + "/v1/images/edits" + ] + }, "cognition/swe-1.6": { "input_cost_per_token": 5e-07, "output_cost_per_token": 2.5e-06, @@ -61455,6 +63057,14 @@ "litellm_provider": "anthropic" } }, + { + "name": "typesafe-jev-ids", + "pattern": "^jev-(?:latest|preview|1\\.13\\.0|1\\.14\\.0)$", + "description": "A bare Jev id that has a typesafe/ price entry (jev-latest, jev-preview, jev-1.13.0, jev-1.14.0), the name the /typesafe pass-through forwards to TypeSafe. Listed by name, matched case-insensitively like every rule here, so foo/jev-latest or a model group named like a Jev id TypeSafe does not serve, such as jev-1.0 or jev-internal-router, never resolves to typesafe. A new Jev version goes here together with its price entry. Provider inference feeds the proxy's provider/* wildcard access checks, so this rule is what lets typesafe/* on a key, team or project allowlist cover a jev-latest request.", + "model_info": { + "litellm_provider": "typesafe" + } + }, { "name": "claude-family-baseline", "pattern": "claude-[a-z]+-\\d+(?:[-.]\\d+)?(?:-\\d{8})?", @@ -64529,6 +66139,7 @@ ] }, "xai/grok-imagine-image-pro": { + "deprecation_date": "2026-05-15", "input_cost_per_image": 0.05, "litellm_provider": "xai", "mode": "image_generation", @@ -64935,9 +66546,14 @@ "max_output_tokens": 256000, "mode": "chat", "output_cost_per_token": 2e-06, + "reasoning_effort_levels": [ + "none", + "high" + ], "source": "https://mistral.ai/news/devstral-2-vibe-cli", "supports_assistant_prefill": true, "supports_function_calling": true, + "supports_reasoning": true, "supports_response_schema": true, "supports_tool_choice": true }, @@ -65281,6 +66897,180 @@ "supports_reasoning": true, "supports_tool_choice": true }, + "zerogpu/deepseek-v4.1-flash": { + "cache_read_input_token_cost": 3e-09, + "input_cost_per_token": 3e-07, + "litellm_provider": "zerogpu", + "max_input_tokens": 1048576, + "max_output_tokens": 65536, + "mode": "chat", + "output_cost_per_token": 1.2e-06, + "source": "https://docs.zerogpu.ai/docs/model-catalog", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_tool_choice": true + }, + "zerogpu/glm-5.3-flash": { + "cache_read_input_token_cost": 1.5e-08, + "input_cost_per_token": 1e-07, + "litellm_provider": "zerogpu", + "max_input_tokens": 1048576, + "max_output_tokens": 32768, + "mode": "chat", + "output_cost_per_token": 3.5e-07, + "source": "https://docs.zerogpu.ai/docs/model-catalog", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_tool_choice": true + }, + "zerogpu/gpt-4.1-mini": { + "cache_read_input_token_cost": 1e-07, + "input_cost_per_token": 4e-07, + "litellm_provider": "zerogpu", + "max_input_tokens": 1047576, + "max_output_tokens": 32768, + "mode": "chat", + "output_cost_per_token": 1.6e-06, + "source": "https://docs.zerogpu.ai/docs/model-catalog", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_response_schema": true, + "supports_tool_choice": true + }, + "zerogpu/gpt-5.4-nano": { + "cache_read_input_token_cost": 2e-08, + "input_cost_per_token": 2e-07, + "litellm_provider": "zerogpu", + "max_input_tokens": 272000, + "max_output_tokens": 128000, + "mode": "chat", + "output_cost_per_token": 1.25e-06, + "source": "https://docs.zerogpu.ai/docs/model-catalog", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_tool_choice": true + }, + "zerogpu/gpt-5.6-luna": { + "cache_read_input_token_cost": 2e-07, + "input_cost_per_token": 2e-07, + "litellm_provider": "zerogpu", + "max_input_tokens": 272000, + "max_output_tokens": 128000, + "mode": "chat", + "output_cost_per_token": 1.2e-06, + "source": "https://docs.zerogpu.ai/docs/model-catalog", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_tool_choice": true + }, + "zerogpu/gpt-6-luna": { + "cache_read_input_token_cost": 1e-08, + "input_cost_per_token": 1e-07, + "litellm_provider": "zerogpu", + "max_input_tokens": 272000, + "max_output_tokens": 128000, + "mode": "chat", + "output_cost_per_token": 5e-07, + "source": "https://docs.zerogpu.ai/docs/model-catalog", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_tool_choice": true, + "supports_vision": true + }, + "zerogpu/gpt-oss-120b": { + "cache_read_input_token_cost": 3e-08, + "input_cost_per_token": 1.5e-07, + "litellm_provider": "zerogpu", + "max_input_tokens": 128000, + "max_output_tokens": 32768, + "mode": "chat", + "output_cost_per_token": 6e-07, + "source": "https://docs.zerogpu.ai/docs/model-catalog", + "supports_function_calling": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_tool_choice": true + }, + "zerogpu/LFM2.5-1.2B-Instruct": { + "input_cost_per_token": 2e-08, + "litellm_provider": "zerogpu", + "max_input_tokens": 32768, + "max_output_tokens": 8192, + "mode": "chat", + "output_cost_per_token": 5e-08, + "source": "https://docs.zerogpu.ai/docs/model-catalog" + }, + "zerogpu/LFM2.5-1.2B-Thinking": { + "input_cost_per_token": 2e-08, + "litellm_provider": "zerogpu", + "max_input_tokens": 32768, + "max_output_tokens": 8192, + "mode": "chat", + "output_cost_per_token": 5e-08, + "source": "https://docs.zerogpu.ai/docs/model-catalog" + }, + "zerogpu/llama-3.1-8b-instruct-fast": { + "cache_read_input_token_cost": 2.5e-08, + "input_cost_per_token": 1.5e-07, + "litellm_provider": "zerogpu", + "max_input_tokens": 131072, + "max_output_tokens": 8192, + "mode": "chat", + "output_cost_per_token": 2.8e-07, + "source": "https://docs.zerogpu.ai/docs/model-catalog", + "supports_function_calling": true, + "supports_response_schema": true, + "supports_tool_choice": true + }, + "zerogpu/llama-3.2-3b-instruct-fast": { + "cache_read_input_token_cost": 2.5e-08, + "input_cost_per_token": 5e-08, + "litellm_provider": "zerogpu", + "max_input_tokens": 131072, + "max_output_tokens": 8192, + "mode": "chat", + "output_cost_per_token": 3e-07, + "source": "https://docs.zerogpu.ai/docs/model-catalog" + }, + "zerogpu/qwen3-30b-a3b-fp8": { + "cache_read_input_token_cost": 5e-08, + "input_cost_per_token": 1e-07, + "litellm_provider": "zerogpu", + "max_input_tokens": 32768, + "max_output_tokens": 16384, + "mode": "chat", + "output_cost_per_token": 4.5e-07, + "source": "https://docs.zerogpu.ai/docs/model-catalog", + "supports_function_calling": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_tool_choice": true + }, + "zerogpu/qwen3.6-35b-a3b": { + "cache_read_input_token_cost": 2e-07, + "input_cost_per_token": 2e-07, + "litellm_provider": "zerogpu", + "max_input_tokens": 262144, + "max_output_tokens": 16384, + "mode": "chat", + "output_cost_per_token": 1.5e-06, + "source": "https://docs.zerogpu.ai/docs/model-catalog", + "supports_function_calling": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_tool_choice": true, + "supports_vision": true + }, "together_ai/Qwen/Qwen3.8-Flash": { "input_cost_per_token": 1.5e-07, "litellm_provider": "together_ai", @@ -65366,6 +67156,7 @@ ] }, "scaleway/glm-5.2": { + "deprecation_date": "2026-11-16", "input_cost_per_token": 1.8e-06, "litellm_provider": "scaleway", "max_input_tokens": 256000, @@ -67924,6 +69715,11 @@ "output_cost_per_token": 8.8e-06, "output_cost_per_token_batches": 4.4e-06, "output_cost_per_token_priority": 1.54e-05, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" }, "azure/eu/gpt-4.1-mini": { @@ -67938,6 +69734,11 @@ "output_cost_per_token": 1.76e-06, "output_cost_per_token_batches": 8.8e-07, "output_cost_per_token_priority": 3.08e-06, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" }, "azure/eu/gpt-4.1-nano": { @@ -67976,6 +69777,11 @@ "output_cost_per_token": 1.1e-05, "output_cost_per_token_batches": 5.5e-06, "output_cost_per_token_priority": 2.2e-05, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" }, "azure/eu/gpt-5-codex": { @@ -68000,6 +69806,11 @@ "output_cost_per_token": 2.2e-06, "output_cost_per_token_batches": 1.1e-06, "output_cost_per_token_priority": 3.96e-06, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" }, "azure/eu/gpt-5-nano": { @@ -68012,6 +69823,11 @@ "mode": "chat", "output_cost_per_token": 4.4e-07, "output_cost_per_token_batches": 2.2e-07, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" }, "azure/eu/gpt-5-pro": { @@ -68022,6 +69838,11 @@ "mode": "responses", "output_cost_per_token": 0.000132, "output_cost_per_token_batches": 6.6e-05, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" }, "azure/eu/gpt-5.1-codex-max": { @@ -68046,6 +69867,11 @@ "output_cost_per_token": 1.54e-05, "output_cost_per_token_batches": 7.7e-06, "output_cost_per_token_priority": 3.08e-05, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" }, "azure/eu/gpt-5.2-codex": { @@ -68064,6 +69890,11 @@ "mode": "responses", "output_cost_per_token": 0.0001848, "output_cost_per_token_batches": 9.24e-05, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" }, "azure/eu/gpt-5.3-codex": { @@ -68076,6 +69907,11 @@ "mode": "responses", "output_cost_per_token": 1.54e-05, "output_cost_per_token_priority": 3.08e-05, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" }, "azure/eu/gpt-5.4-mini": { @@ -68091,6 +69927,11 @@ "output_cost_per_token": 4.95e-06, "output_cost_per_token_batches": 2.475e-06, "output_cost_per_token_priority": 9.9e-06, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" }, "azure/eu/gpt-5.4-nano": { @@ -68103,6 +69944,11 @@ "mode": "chat", "output_cost_per_token": 1.375e-06, "output_cost_per_token_batches": 6.875e-07, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" }, "azure/eu/gpt-5.4-pro": { @@ -68117,6 +69963,11 @@ "output_cost_per_token_above_272k_tokens": 0.000297, "output_cost_per_token_above_272k_tokens_batches": 0.0001485, "output_cost_per_token_batches": 9.9e-05, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" }, "azure/eu/gpt-6-astra": { @@ -68133,6 +69984,11 @@ "mode": "chat", "output_cost_per_token": 6e-05, "output_cost_per_token_above_272k_tokens": 9e-05, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://learn.microsoft.com/en-us/azure/foundry/foundry-models/concepts/models-sold-directly-by-azure", "supported_endpoints": [ "/v1/chat/completions", @@ -68177,9 +70033,9 @@ "output_cost_per_token": 6e-07, "output_cost_per_token_above_272k_tokens": 9e-07, "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 }, "source": "https://azure.microsoft.com/en-us/blog/gpt-6-astra-sol-and-luna-for-production-agents-in-microsoft-foundry/", "supported_endpoints": [ @@ -68225,9 +70081,9 @@ "output_cost_per_token": 1.2e-05, "output_cost_per_token_above_272k_tokens": 1.8e-05, "search_context_cost_per_query": { - "search_context_size_high": 0.01, - "search_context_size_low": 0.01, - "search_context_size_medium": 0.01 + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 }, "source": "https://azure.microsoft.com/en-us/blog/gpt-6-astra-sol-and-luna-for-production-agents-in-microsoft-foundry/", "supported_endpoints": [ @@ -68279,6 +70135,11 @@ "mode": "chat", "output_cost_per_token": 8.8e-06, "output_cost_per_token_batches": 4.4e-06, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" }, "azure/eu/o3-2025-04-16": { @@ -68292,6 +70153,11 @@ "mode": "chat", "output_cost_per_token": 8.8e-06, "output_cost_per_token_batches": 4.4e-06, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" }, "azure/eu/o3-deep-research": { @@ -68314,6 +70180,11 @@ "mode": "chat", "output_cost_per_token": 4.84e-06, "output_cost_per_token_batches": 2.42e-06, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" }, "azure/eu/o4-mini-2025-04-16": { @@ -68327,6 +70198,11 @@ "mode": "chat", "output_cost_per_token": 4.84e-06, "output_cost_per_token_batches": 2.42e-06, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" }, "azure/eu/text-embedding-3-large": { @@ -68420,6 +70296,11 @@ "output_cost_per_token": 8.8e-06, "output_cost_per_token_batches": 4.4e-06, "output_cost_per_token_priority": 1.54e-05, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" }, "azure/us/gpt-4.1-mini": { @@ -68434,6 +70315,11 @@ "output_cost_per_token": 1.76e-06, "output_cost_per_token_batches": 8.8e-07, "output_cost_per_token_priority": 3.08e-06, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" }, "azure/us/gpt-4.1-nano": { @@ -68472,6 +70358,11 @@ "output_cost_per_token": 1.1e-05, "output_cost_per_token_batches": 5.5e-06, "output_cost_per_token_priority": 2.2e-05, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" }, "azure/us/gpt-5-codex": { @@ -68496,6 +70387,11 @@ "output_cost_per_token": 2.2e-06, "output_cost_per_token_batches": 1.1e-06, "output_cost_per_token_priority": 3.96e-06, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" }, "azure/us/gpt-5-nano": { @@ -68508,6 +70404,11 @@ "mode": "chat", "output_cost_per_token": 4.4e-07, "output_cost_per_token_batches": 2.2e-07, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" }, "azure/us/gpt-5-pro": { @@ -68518,6 +70419,11 @@ "mode": "responses", "output_cost_per_token": 0.000132, "output_cost_per_token_batches": 6.6e-05, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" }, "azure/us/gpt-5.1-codex-max": { @@ -68542,6 +70448,11 @@ "output_cost_per_token": 1.54e-05, "output_cost_per_token_batches": 7.7e-06, "output_cost_per_token_priority": 3.08e-05, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" }, "azure/us/gpt-5.2-codex": { @@ -68560,6 +70471,11 @@ "mode": "responses", "output_cost_per_token": 0.0001848, "output_cost_per_token_batches": 9.24e-05, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" }, "azure/us/gpt-5.3-codex": { @@ -68572,6 +70488,11 @@ "mode": "responses", "output_cost_per_token": 1.54e-05, "output_cost_per_token_priority": 3.08e-05, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" }, "azure/us/gpt-5.4-mini": { @@ -68587,6 +70508,11 @@ "output_cost_per_token": 4.95e-06, "output_cost_per_token_batches": 2.475e-06, "output_cost_per_token_priority": 9.9e-06, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" }, "azure/us/gpt-5.4-nano": { @@ -68599,6 +70525,11 @@ "mode": "chat", "output_cost_per_token": 1.375e-06, "output_cost_per_token_batches": 6.875e-07, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" }, "azure/us/gpt-5.4-pro": { @@ -68613,6 +70544,11 @@ "output_cost_per_token_above_272k_tokens": 0.000297, "output_cost_per_token_above_272k_tokens_batches": 0.0001485, "output_cost_per_token_batches": 9.9e-05, + "search_context_cost_per_query": { + "search_context_size_high": 0.014, + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" }, "azure/us/o1-mini": { @@ -68659,7 +70595,7 @@ "cache_creation_input_audio_token_cost": 4e-07, "cache_read_input_audio_token_cost": 4e-07, "cache_read_input_token_cost": 4e-07, - "deprecation_date": "2026-10-31", + "deprecation_date": "2027-01-20", "input_cost_per_audio_token": 3.2e-05, "input_cost_per_image_token": 5e-06, "input_cost_per_token": 4e-06, @@ -69827,6 +71763,201 @@ "supports_reasoning": true, "supports_vision": true }, + "aiand/deepseek-ai/deepseek-v4-flash": { + "cache_read_input_token_cost": 8e-08, + "input_cost_per_token": 1.5e-07, + "litellm_provider": "aiand", + "max_input_tokens": 1048576, + "max_output_tokens": 384000, + "mode": "chat", + "output_cost_per_token": 2.5e-07, + "source": "https://api.aiand.com/v1/models", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_tool_choice": true, + "supports_vision": false + }, + "aiand/deepseek-ai/deepseek-v4-pro": { + "cache_read_input_token_cost": 2.5e-07, + "input_cost_per_token": 1e-06, + "litellm_provider": "aiand", + "max_input_tokens": 1048576, + "max_output_tokens": 384000, + "mode": "chat", + "output_cost_per_token": 2.5e-06, + "source": "https://api.aiand.com/v1/models", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_tool_choice": true, + "supports_vision": false + }, + "aiand/deepseek-ai/deepseek-v4.1-flash": { + "cache_read_input_token_cost": 2e-08, + "input_cost_per_token": 3e-07, + "litellm_provider": "aiand", + "max_input_tokens": 1048576, + "max_output_tokens": 384000, + "mode": "chat", + "output_cost_per_token": 6e-07, + "source": "https://api.aiand.com/v1/models", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_tool_choice": true, + "supports_vision": true + }, + "aiand/google/gemma-4-31b-it": { + "cache_read_input_token_cost": 5e-08, + "input_cost_per_token": 2e-07, + "litellm_provider": "aiand", + "max_input_tokens": 262144, + "max_output_tokens": 32768, + "mode": "chat", + "output_cost_per_token": 5e-07, + "source": "https://api.aiand.com/v1/models", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_tool_choice": true, + "supports_vision": true + }, + "aiand/moonshotai/kimi-k2.7-code": { + "cache_read_input_token_cost": 2e-07, + "input_cost_per_token": 7.5e-07, + "litellm_provider": "aiand", + "max_input_tokens": 262144, + "max_output_tokens": 262144, + "mode": "chat", + "output_cost_per_token": 3.5e-06, + "source": "https://api.aiand.com/v1/models", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_tool_choice": true, + "supports_vision": true + }, + "aiand/moonshotai/kimi-k3": { + "cache_read_input_token_cost": 5e-07, + "input_cost_per_token": 3e-06, + "litellm_provider": "aiand", + "max_input_tokens": 1048576, + "max_output_tokens": 131072, + "mode": "chat", + "output_cost_per_token": 1.25e-05, + "source": "https://api.aiand.com/v1/models", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_tool_choice": true, + "supports_vision": true + }, + "aiand/motif-technologies/motif-3": { + "cache_read_input_token_cost": 2e-07, + "input_cost_per_token": 5e-07, + "litellm_provider": "aiand", + "max_input_tokens": 262144, + "max_output_tokens": 262144, + "mode": "chat", + "output_cost_per_token": 2e-06, + "source": "https://api.aiand.com/v1/models", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_tool_choice": true, + "supports_vision": false + }, + "aiand/openai/gpt-oss-120b": { + "cache_read_input_token_cost": 8e-08, + "input_cost_per_token": 1.5e-07, + "litellm_provider": "aiand", + "max_input_tokens": 131072, + "max_output_tokens": 32768, + "mode": "chat", + "output_cost_per_token": 6e-07, + "source": "https://api.aiand.com/v1/models", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_tool_choice": true, + "supports_vision": false + }, + "aiand/qwen/qwen3.6-27b": { + "cache_read_input_token_cost": 2e-07, + "input_cost_per_token": 3.2e-07, + "litellm_provider": "aiand", + "max_input_tokens": 262144, + "max_output_tokens": 65536, + "mode": "chat", + "output_cost_per_token": 3.2e-06, + "source": "https://api.aiand.com/v1/models", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_tool_choice": true, + "supports_vision": true + }, + "aiand/qwen/qwen3.8-27b": { + "cache_read_input_token_cost": 2e-07, + "input_cost_per_token": 4e-07, + "litellm_provider": "aiand", + "max_input_tokens": 262144, + "max_output_tokens": 32768, + "mode": "chat", + "output_cost_per_token": 3e-06, + "source": "https://api.aiand.com/v1/models", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_tool_choice": true, + "supports_vision": true + }, + "aiand/zai-org/glm-5.2": { + "cache_read_input_token_cost": 3e-07, + "input_cost_per_token": 1e-06, + "litellm_provider": "aiand", + "max_input_tokens": 1048576, + "max_output_tokens": 131072, + "mode": "chat", + "output_cost_per_token": 4e-06, + "source": "https://api.aiand.com/v1/models", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_tool_choice": true, + "supports_vision": false + }, + "aiand/zai-org/glm-5.3": { + "cache_read_input_token_cost": 3e-07, + "input_cost_per_token": 1e-06, + "litellm_provider": "aiand", + "max_input_tokens": 1048576, + "max_output_tokens": 131072, + "mode": "chat", + "output_cost_per_token": 4e-06, + "source": "https://api.aiand.com/v1/models", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_tool_choice": true, + "supports_vision": false + }, + "aiand/zai-org/glm-5.3-flash": { + "cache_read_input_token_cost": 3e-08, + "input_cost_per_token": 1.5e-07, + "litellm_provider": "aiand", + "max_input_tokens": 1048550, + "max_output_tokens": 131072, + "mode": "chat", + "output_cost_per_token": 5e-07, + "source": "https://api.aiand.com/v1/models", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_tool_choice": true, + "supports_vision": true + }, "bespoke/nimble-latest": { "input_cost_per_token": 0.0, "litellm_provider": "bespoke", @@ -70809,6 +72940,7 @@ "xai/grok-code-fast-1": { "cache_read_input_token_cost": 2e-07, "cache_read_input_token_cost_above_200k_tokens": 4e-07, + "deprecation_date": "2026-05-15", "input_cost_per_image_token": 1e-06, "input_cost_per_token": 1e-06, "input_cost_per_token_above_200k_tokens": 2e-06, @@ -71705,7 +73837,7 @@ "supports_mid_conversation_system": true, "cache_creation_input_token_cost": 2.5e-06, "cache_creation_input_token_cost_above_1hr": 4e-06, - "cache_read_input_token_cost": 2e-07, + "cache_read_input_token_cost": 1e-07, "deprecation_date": "2027-09-29", "input_cost_per_token": 2e-06, "litellm_provider": "azure_ai", @@ -72312,15 +74444,15 @@ "gpt-6.1-sol": { "cache_creation_input_token_cost": 2.5e-06, "cache_creation_input_token_cost_above_12hr": 5e-06, + "cache_creation_input_token_cost_above_12hr_ultrafast": 3e-05, + "cache_creation_input_token_cost_above_12hr_batches": 2.5e-06, "cache_creation_input_token_cost_above_12hr_above_272k_tokens": 1e-05, "cache_creation_input_token_cost_above_12hr_above_272k_tokens_batches": 5e-06, "cache_creation_input_token_cost_above_12hr_above_272k_tokens_flex": 5e-06, "cache_creation_input_token_cost_above_12hr_above_272k_tokens_priority": 2e-05, "cache_creation_input_token_cost_above_12hr_above_272k_tokens_ultrafast": 6e-05, - "cache_creation_input_token_cost_above_12hr_batches": 2.5e-06, "cache_creation_input_token_cost_above_12hr_flex": 2.5e-06, "cache_creation_input_token_cost_above_12hr_priority": 1e-05, - "cache_creation_input_token_cost_above_12hr_ultrafast": 3e-05, "cache_creation_input_token_cost_above_272k_tokens": 5e-06, "cache_creation_input_token_cost_above_272k_tokens_batches": 2.5e-06, "cache_creation_input_token_cost_above_272k_tokens_flex": 2.5e-06, @@ -72364,6 +74496,15 @@ "output_cost_per_token_flex": 5e-06, "output_cost_per_token_priority": 2e-05, "output_cost_per_token_ultrafast": 6e-05, + "reasoning_contexts": [ + "auto", + "current_turn", + "all_turns" + ], + "reasoning_modes": [ + "standard", + "pro" + ], "regional_processing_uplift_multiplier_eu": 1.1, "regional_processing_uplift_multiplier_us": 1.1, "search_context_cost_per_query": { @@ -72758,6 +74899,7 @@ "mode": "image_generation", "output_cost_per_image": 0.0336, "output_cost_per_image_token": 3e-05, + "output_cost_per_image_token_batches": 1.5e-05, "output_cost_per_token": 7.5e-06, "output_cost_per_token_batches": 3.75e-06, "output_cost_per_token_priority": 1.35e-05, @@ -72803,6 +74945,7 @@ "mode": "image_generation", "output_cost_per_image": 0.0336, "output_cost_per_image_token": 3e-05, + "output_cost_per_image_token_batches": 1.5e-05, "output_cost_per_token": 7.5e-06, "output_cost_per_token_batches": 3.75e-06, "output_cost_per_token_priority": 1.35e-05, @@ -74281,14 +76424,14 @@ "supports_vision": true }, "wandb/nvidia/NVIDIA-Nemotron-3.5-Super-VL-120B-A12B": { - "cache_read_input_token_cost": 2e-08, - "input_cost_per_token": 1.5e-07, + "cache_read_input_token_cost": 5e-08, + "input_cost_per_token": 2.5e-07, "litellm_provider": "wandb", "max_input_tokens": 1049000, "max_output_tokens": 943718, "mode": "chat", - "output_cost_per_token": 7.5e-07, - "source": "https://openrouter.ai/api/v1/models/nvidia/nemotron-3.5-super-vl/endpoints", + "output_cost_per_token": 1.5e-06, + "source": "https://www.coreweave.com/products/coreweave-forge/serverless-inference", "supports_function_calling": true, "supports_prompt_caching": true, "supports_reasoning": true, @@ -75863,6 +78006,15 @@ "output_cost_per_token_batches": 2.5e-06, "output_cost_per_token_flex": 2.5e-06, "output_cost_per_token_priority": 1e-05, + "reasoning_contexts": [ + "auto", + "current_turn", + "all_turns" + ], + "reasoning_modes": [ + "standard", + "pro" + ], "regional_processing_uplift_multiplier_eu": 1.1, "regional_processing_uplift_multiplier_us": 1.1, "search_context_cost_per_query": {"search_context_size_high":0.01,"search_context_size_low":0.01,"search_context_size_medium":0.01}, @@ -75995,7 +78147,7 @@ "supports_xhigh_reasoning_effort": true }, "baseten/decision-models/baseten-elephant-9b-latest": { - "input_cost_per_token": 0.0, + "input_cost_per_token": 3.5e-08, "litellm_provider": "baseten", "max_input_tokens": 16384, "mode": "decisions", @@ -76004,7 +78156,7 @@ "supports_vision": true }, "baseten/decision-models/baseten-mammoth-27b-latest": { - "input_cost_per_token": 0.0, + "input_cost_per_token": 1e-07, "litellm_provider": "baseten", "max_input_tokens": 16384, "mode": "decisions", @@ -76036,13 +78188,13 @@ "supports_vision": true }, "refuseless/glm-5.3-abliterated": { - "cache_read_input_token_cost": 2.5e-07, - "input_cost_per_token": 1.25e-06, + "cache_read_input_token_cost": 1.5e-07, + "input_cost_per_token": 1e-06, "litellm_provider": "refuseless", "max_input_tokens": 1048576, "max_output_tokens": 131072, "mode": "chat", - "output_cost_per_token": 2.25e-06, + "output_cost_per_token": 2e-06, "source": "https://refuseless.com/pricing", "supports_function_calling": true, "supports_prompt_caching": true, @@ -76057,13 +78209,13 @@ ] }, "refuseless/glm-5.3-flash-abliterated": { - "cache_read_input_token_cost": 1.5e-07, - "input_cost_per_token": 2.5e-07, + "cache_read_input_token_cost": 4e-08, + "input_cost_per_token": 1.2e-07, "litellm_provider": "refuseless", "max_input_tokens": 1048576, "max_output_tokens": 131072, "mode": "chat", - "output_cost_per_token": 8e-07, + "output_cost_per_token": 5e-07, "source": "https://refuseless.com/pricing", "supports_function_calling": true, "supports_prompt_caching": true, @@ -76078,13 +78230,13 @@ ] }, "refuseless/deepseek-v4.1-flash-abliterated": { - "cache_read_input_token_cost": 4.5e-08, - "input_cost_per_token": 2.2e-07, + "cache_read_input_token_cost": 3.5e-08, + "input_cost_per_token": 1.4e-07, "litellm_provider": "refuseless", "max_input_tokens": 1048576, "max_output_tokens": 130000, "mode": "chat", - "output_cost_per_token": 7.5e-07, + "output_cost_per_token": 5e-07, "source": "https://refuseless.com/pricing", "supports_function_calling": true, "supports_prompt_caching": true, @@ -76140,6 +78292,15 @@ "max" ] }, + "fireworks_ai/accounts/fireworks/models/rune": { + "cache_read_input_token_cost": 8.4e-09, + "input_cost_per_token": 4.2e-08, + "litellm_provider": "fireworks_ai", + "max_input_tokens": 262144, + "mode": "decisions", + "output_cost_per_token": 0.0, + "source": "https://api.fireworks.ai/v1/serverless/models?format=nested" + }, "bedrock_mantle/openai.gpt-6.1-terra": { "cache_creation_input_token_cost": 1.375e-06, "cache_creation_input_token_cost_above_272k_tokens": 2.75e-06, @@ -76177,5 +78338,738 @@ "supports_vision": true, "supports_xhigh_reasoning_effort": true, "use_openai_responses_path": true + }, + "databricks/databricks-claude-haiku-5-5": { + "cache_creation_input_token_cost": 1.2502e-07, + "cache_creation_input_token_cost_above_100k_tokens": 6.2503e-07, + "cache_creation_input_token_cost_above_1hr": 1.9999e-07, + "cache_creation_input_token_cost_above_1hr_above_100k_tokens": 1.00002e-06, + "cache_read_input_token_cost": 1.001e-08, + "cache_read_input_token_cost_above_100k_tokens": 4.998e-08, + "input_cost_per_token": 1.0003e-07, + "input_cost_per_token_above_100k_tokens": 5.0001e-07, + "input_dbu_cost_per_token": 1.429e-06, + "litellm_provider": "databricks", + "max_input_tokens": 1000000, + "max_output_tokens": 128000, + "metadata": { + "notes": "Costs per token are the published Global DBU rates times $0.070 per DBU. The '*_dbu_cost_per_token' fields are provided for reference; cost calculation reads the dollar '*_cost_per_token' fields." + }, + "mode": "chat", + "output_cost_per_token": 5.0001e-07, + "output_cost_per_token_above_100k_tokens": 2.49998e-06, + "output_dbu_cost_per_token": 7.143e-06, + "prompt_cache_min_tokens": 512.0, + "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", + "supports_adaptive_thinking": true, + "supports_anthropic_thinking_payload": true, + "supports_assistant_prefill": false, + "supports_function_calling": true, + "supports_mid_conversation_system": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_sampling_params": false, + "supports_tool_choice": true, + "supports_vision": true, + "thinking_always_on": false + }, + "databricks/databricks-claude-sonnet-5-5": { + "cache_creation_input_token_cost": 2.49998e-06, + "cache_creation_input_token_cost_above_1hr": 4.00001e-06, + "cache_read_input_token_cost": 1.0003e-07, + "input_cost_per_token": 1.99997e-06, + "input_dbu_cost_per_token": 2.8571e-05, + "litellm_provider": "databricks", + "max_input_tokens": 1000000, + "max_output_tokens": 128000, + "metadata": { + "notes": "Costs per token are the published Global DBU rates times $0.070 per DBU. The '*_dbu_cost_per_token' fields are provided for reference; cost calculation reads the dollar '*_cost_per_token' fields." + }, + "mode": "chat", + "output_cost_per_token": 9.99999e-06, + "output_dbu_cost_per_token": 0.00014286, + "prompt_cache_min_tokens": 512.0, + "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", + "supports_adaptive_thinking": true, + "supports_anthropic_thinking_payload": true, + "supports_assistant_prefill": false, + "supports_function_calling": true, + "supports_mid_conversation_system": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_sampling_params": false, + "supports_tool_choice": true, + "supports_vision": false, + "thinking_always_on": true + }, + "databricks/databricks-deepseek-v4-1-flash": { + "cache_creation_input_token_cost": 3.0002e-07, + "cache_read_input_token_cost": 3.003e-08, + "deprecation_date": "2026-11-19", + "input_cost_per_token": 3.0002e-07, + "input_dbu_cost_per_token": 4.286e-06, + "litellm_provider": "databricks", + "max_input_tokens": 1000000, + "max_output_tokens": 384000, + "metadata": { + "notes": "Costs per token are the published Global DBU rates times $0.070 per DBU. The '*_dbu_cost_per_token' fields are provided for reference; cost calculation reads the dollar '*_cost_per_token' fields. The docs list only databricks-deepseek-v4-1-flash (retiring 2026-11-19) and databricks-deepseek-v4-1-flash-1017, so the pricing page's 'DeepSeek V4.1 Flash (0910)' row prices the unsuffixed endpoint." + }, + "mode": "chat", + "output_cost_per_token": 1.20001e-06, + "output_dbu_cost_per_token": 1.7143e-05, + "source": "https://docs.databricks.com/aws/en/machine-learning/foundation-model-apis/supported-models", + "supported_modalities": [ + "text", + "image" + ], + "supported_output_modalities": [ + "text" + ], + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_tool_choice": true, + "supports_vision": true, + "input_cost_per_token_priority": 5.25e-07, + "output_cost_per_token_priority": 2.1e-06, + "cache_read_input_token_cost_priority": 5.25e-08, + "cache_creation_input_token_cost_priority": 5.25e-07 + }, + "databricks/databricks-deepseek-v4-1-flash-1017": { + "cache_creation_input_token_cost": 3.0002e-07, + "cache_read_input_token_cost": 7e-09, + "input_cost_per_token": 3.0002e-07, + "input_dbu_cost_per_token": 4.286e-06, + "litellm_provider": "databricks", + "max_input_tokens": 1000000, + "max_output_tokens": 384000, + "metadata": { + "notes": "Costs per token are the published Global DBU rates times $0.070 per DBU. The '*_dbu_cost_per_token' fields are provided for reference; cost calculation reads the dollar '*_cost_per_token' fields." + }, + "mode": "chat", + "output_cost_per_token": 1.20001e-06, + "output_dbu_cost_per_token": 1.7143e-05, + "source": "https://www.databricks.com/product/pricing/foundation-model-serving", + "supported_modalities": [ + "text", + "image" + ], + "supported_output_modalities": [ + "text" + ], + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_tool_choice": true, + "supports_vision": true + }, + "databricks/databricks-gemini-2-5-flash-lite": { + "cache_creation_input_token_cost": 1.2502e-07, + "cache_read_input_audio_token_cost": 3.752e-08, + "cache_read_input_token_cost": 1.253e-08, + "input_cost_per_audio_token": 3.7499e-07, + "input_cost_per_image_token": 1.2502e-07, + "input_cost_per_token": 1.2502e-07, + "input_dbu_cost_per_token": 1.786e-06, + "litellm_provider": "databricks", + "max_input_tokens": 1048576, + "max_output_tokens": 65536, + "metadata": { + "notes": "Costs per token are the published Global DBU rates times $0.070 per DBU. The '*_dbu_cost_per_token' fields are provided for reference; cost calculation reads the dollar '*_cost_per_token' fields." + }, + "mode": "chat", + "output_cost_per_token": 5.0001e-07, + "output_dbu_cost_per_token": 7.143e-06, + "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", + "supported_modalities": [ + "text", + "image", + "audio", + "video" + ], + "supported_output_modalities": [ + "text" + ], + "supports_audio_input": true, + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_tool_choice": true, + "supports_video_input": true, + "supports_vision": true + }, + "databricks/databricks-gemini-3-1-flash-lite-image": { + "cache_creation_input_token_cost": 3.1248e-07, + "cache_read_input_token_cost": 3.1248e-07, + "input_cost_per_image_token": 3.1248e-07, + "input_cost_per_token": 3.1248e-07, + "input_dbu_cost_per_token": 4.464e-06, + "litellm_provider": "databricks", + "max_input_tokens": 65536, + "max_output_tokens": 4096, + "metadata": { + "notes": "Costs per token are the published Global DBU rates times $0.070 per DBU. The '*_dbu_cost_per_token' fields are provided for reference; cost calculation reads the dollar '*_cost_per_token' fields." + }, + "mode": "chat", + "output_cost_per_image_token": 3.749998e-05, + "output_cost_per_token": 1.87502e-06, + "output_dbu_cost_per_token": 2.6786e-05, + "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", + "supported_modalities": [ + "text", + "image" + ], + "supported_output_modalities": [ + "text", + "image" + ], + "supports_function_calling": false, + "supports_vision": true + }, + "databricks/databricks-gemini-4-argon": { + "cache_creation_input_token_cost": 2.49998e-06, + "cache_read_input_token_cost": 1.2502e-07, + "input_cost_per_token": 2.49998e-06, + "input_dbu_cost_per_token": 3.5714e-05, + "litellm_provider": "databricks", + "max_input_tokens": 1048576, + "max_output_tokens": 1048576, + "metadata": { + "notes": "Costs per token are the published Global DBU rates times $0.070 per DBU. The '*_dbu_cost_per_token' fields are provided for reference; cost calculation reads the dollar '*_cost_per_token' fields." + }, + "mode": "chat", + "output_cost_per_token": 1.249997e-05, + "output_dbu_cost_per_token": 0.00017857, + "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", + "supported_modalities": [ + "text", + "image", + "audio", + "video" + ], + "supported_output_modalities": [ + "text" + ], + "supports_audio_input": true, + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_tool_choice": true, + "supports_video_input": true, + "supports_vision": true, + "input_cost_per_token_priority": 4.50002e-06, + "output_cost_per_token_priority": 2.250003e-05, + "cache_read_input_token_cost_priority": 2.2498e-07, + "cache_creation_input_token_cost_priority": 4.50002e-06 + }, + "databricks/databricks-gpt-5-4-pro": { + "cache_creation_input_token_cost": 2.999997e-05, + "cache_read_input_token_cost": 2.999997e-05, + "input_cost_per_token": 2.999997e-05, + "input_cost_per_token_above_272k_tokens": 6e-05, + "input_dbu_cost_per_token": 0.00042857, + "litellm_provider": "databricks", + "max_input_tokens": 922000, + "max_output_tokens": 128000, + "metadata": { + "notes": "Costs per token are the published Global DBU rates times $0.070 per DBU. The '*_dbu_cost_per_token' fields are provided for reference; cost calculation reads the dollar '*_cost_per_token' fields." + }, + "mode": "responses", + "output_cost_per_token": 0.0001800001, + "output_cost_per_token_above_272k_tokens": 0.00027, + "output_dbu_cost_per_token": 0.0025714, + "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", + "supported_modalities": [ + "text", + "image" + ], + "supported_output_modalities": [ + "text" + ], + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_tool_choice": true, + "supports_vision": true + }, + "databricks/databricks-gpt-6-1-sol": { + "cache_creation_input_token_cost": 2.49998e-06, + "cache_creation_input_token_cost_above_272k_tokens": 5.00003e-06, + "cache_read_input_token_cost": 1.0003e-07, + "cache_read_input_token_cost_above_272k_tokens": 1.9999e-07, + "input_cost_per_token": 1.99997e-06, + "input_cost_per_token_above_272k_tokens": 4.00001e-06, + "input_dbu_cost_per_token": 2.8571e-05, + "litellm_provider": "databricks", + "max_input_tokens": 922000, + "max_output_tokens": 128000, + "metadata": { + "notes": "Costs per token are the published Global DBU rates times $0.070 per DBU. The '*_dbu_cost_per_token' fields are provided for reference; cost calculation reads the dollar '*_cost_per_token' fields." + }, + "mode": "responses", + "output_cost_per_token": 9.99999e-06, + "output_cost_per_token_above_272k_tokens": 1.5e-05, + "output_dbu_cost_per_token": 0.00014286, + "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", + "supported_modalities": [ + "text", + "image" + ], + "supported_output_modalities": [ + "text" + ], + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_tool_choice": true, + "supports_vision": true, + "input_cost_per_token_priority": 4.00001e-06, + "output_cost_per_token_priority": 1.99997e-05, + "cache_read_input_token_cost_priority": 1.9999e-07, + "cache_creation_input_token_cost_priority": 5.00003e-06, + "input_cost_per_token_above_272k_tokens_priority": 8.00002e-06, + "output_cost_per_token_above_272k_tokens_priority": 2.99999e-05, + "cache_read_input_token_cost_above_272k_tokens_priority": 3.9998e-07, + "cache_creation_input_token_cost_above_272k_tokens_priority": 9.99999e-06 + }, + "databricks/databricks-gpt-6-1-terra": { + "cache_creation_input_token_cost": 1.24999e-06, + "cache_creation_input_token_cost_above_272k_tokens": 2.49998e-06, + "cache_read_input_token_cost": 4.998e-08, + "cache_read_input_token_cost_above_272k_tokens": 1.0003e-07, + "input_cost_per_token": 1.00002e-06, + "input_cost_per_token_above_272k_tokens": 1.99997e-06, + "input_dbu_cost_per_token": 1.4286e-05, + "litellm_provider": "databricks", + "max_input_tokens": 922000, + "max_output_tokens": 128000, + "metadata": { + "notes": "Costs per token are the published Global DBU rates times $0.070 per DBU. The '*_dbu_cost_per_token' fields are provided for reference; cost calculation reads the dollar '*_cost_per_token' fields." + }, + "mode": "chat", + "output_cost_per_token": 5.00003e-06, + "output_cost_per_token_above_272k_tokens": 7.50001e-06, + "output_dbu_cost_per_token": 7.1429e-05, + "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", + "supported_modalities": [ + "text", + "image" + ], + "supported_output_modalities": [ + "text" + ], + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_tool_choice": true, + "supports_vision": true, + "input_cost_per_token_priority": 1.99997e-06, + "output_cost_per_token_priority": 9.99999e-06, + "cache_read_input_token_cost_priority": 1.0003e-07, + "cache_creation_input_token_cost_priority": 2.49998e-06, + "input_cost_per_token_above_272k_tokens_priority": 4.00001e-06, + "output_cost_per_token_above_272k_tokens_priority": 1.500002e-05, + "cache_read_input_token_cost_above_272k_tokens_priority": 1.9999e-07, + "cache_creation_input_token_cost_above_272k_tokens_priority": 5.00003e-06 + }, + "databricks/databricks-gpt-6-astra": { + "cache_creation_input_token_cost": 1.249997e-05, + "cache_creation_input_token_cost_above_272k_tokens": 2.5e-05, + "cache_read_input_token_cost": 1.00002e-06, + "cache_read_input_token_cost_above_272k_tokens": 1.99997e-06, + "input_cost_per_token": 9.99999e-06, + "input_cost_per_token_above_272k_tokens": 2e-05, + "input_dbu_cost_per_token": 0.00014286, + "litellm_provider": "databricks", + "max_input_tokens": 922000, + "max_output_tokens": 128000, + "metadata": { + "notes": "Costs per token are the published Global DBU rates times $0.070 per DBU. The '*_dbu_cost_per_token' fields are provided for reference; cost calculation reads the dollar '*_cost_per_token' fields." + }, + "mode": "chat", + "output_cost_per_token": 5.000002e-05, + "output_cost_per_token_above_272k_tokens": 7.50001e-05, + "output_dbu_cost_per_token": 0.00071429, + "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", + "supported_modalities": [ + "text", + "image" + ], + "supported_output_modalities": [ + "text" + ], + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_tool_choice": true, + "supports_vision": true, + "input_cost_per_token_priority": 1.999998e-05, + "output_cost_per_token_priority": 9.99999e-05, + "cache_read_input_token_cost_priority": 1.99997e-06, + "cache_creation_input_token_cost_priority": 2.500001e-05, + "input_cost_per_token_above_272k_tokens_priority": 4.000003e-05, + "output_cost_per_token_above_272k_tokens_priority": 0.0001500002, + "cache_read_input_token_cost_above_272k_tokens_priority": 4.00001e-06, + "cache_creation_input_token_cost_above_272k_tokens_priority": 5.000002e-05 + }, + "databricks/databricks-gpt-6-luna": { + "cache_creation_input_token_cost": 1.2502e-07, + "cache_creation_input_token_cost_above_272k_tokens": 2.4997e-07, + "cache_read_input_token_cost": 1.001e-08, + "cache_read_input_token_cost_above_272k_tokens": 2.002e-08, + "input_cost_per_token": 1.0003e-07, + "input_cost_per_token_above_272k_tokens": 1.9999e-07, + "input_dbu_cost_per_token": 1.429e-06, + "litellm_provider": "databricks", + "max_input_tokens": 922000, + "max_output_tokens": 128000, + "metadata": { + "notes": "Costs per token are the published Global DBU rates times $0.070 per DBU. The '*_dbu_cost_per_token' fields are provided for reference; cost calculation reads the dollar '*_cost_per_token' fields." + }, + "mode": "responses", + "output_cost_per_token": 5.0001e-07, + "output_cost_per_token_above_272k_tokens": 7.497e-07, + "output_dbu_cost_per_token": 7.143e-06, + "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", + "supported_modalities": [ + "text", + "image" + ], + "supported_output_modalities": [ + "text" + ], + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_tool_choice": true, + "supports_vision": true, + "input_cost_per_token_priority": 1.9999e-07, + "output_cost_per_token_priority": 1.0003e-06, + "cache_read_input_token_cost_priority": 2.002e-08, + "cache_creation_input_token_cost_priority": 2.4997e-07, + "input_cost_per_token_above_272k_tokens_priority": 3.9998e-07, + "output_cost_per_token_above_272k_tokens_priority": 1.5001e-06, + "cache_read_input_token_cost_above_272k_tokens_priority": 3.997e-08, + "cache_creation_input_token_cost_above_272k_tokens_priority": 5.0001e-07 + }, + "databricks/databricks-gpt-6-sol": { + "cache_creation_input_token_cost": 2.49998e-06, + "cache_creation_input_token_cost_above_272k_tokens": 5.00003e-06, + "cache_read_input_token_cost": 1.9999e-07, + "cache_read_input_token_cost_above_272k_tokens": 3.9998e-07, + "input_cost_per_token": 1.99997e-06, + "input_cost_per_token_above_272k_tokens": 4.00001e-06, + "input_dbu_cost_per_token": 2.8571e-05, + "litellm_provider": "databricks", + "max_input_tokens": 922000, + "max_output_tokens": 128000, + "metadata": { + "notes": "Costs per token are the published Global DBU rates times $0.070 per DBU. The '*_dbu_cost_per_token' fields are provided for reference; cost calculation reads the dollar '*_cost_per_token' fields." + }, + "mode": "responses", + "output_cost_per_token": 9.99999e-06, + "output_cost_per_token_above_272k_tokens": 1.50003e-05, + "output_dbu_cost_per_token": 0.00014286, + "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", + "supported_modalities": [ + "text", + "image" + ], + "supported_output_modalities": [ + "text" + ], + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_tool_choice": true, + "supports_vision": true, + "input_cost_per_token_priority": 4.00001e-06, + "output_cost_per_token_priority": 1.99997e-05, + "cache_read_input_token_cost_priority": 3.9998e-07, + "cache_creation_input_token_cost_priority": 5.00003e-06, + "input_cost_per_token_above_272k_tokens_priority": 8.00002e-06, + "output_cost_per_token_above_272k_tokens_priority": 2.99999e-05, + "cache_read_input_token_cost_above_272k_tokens_priority": 8.0003e-07, + "cache_creation_input_token_cost_above_272k_tokens_priority": 9.99999e-06 + }, + "databricks/databricks-gpt-image-1": { + "cache_creation_input_token_cost": 5.00003e-06, + "cache_read_input_token_cost": 1.24999e-06, + "input_cost_per_image_token": 9.99999e-06, + "input_cost_per_token": 5.00003e-06, + "input_dbu_cost_per_token": 7.1429e-05, + "litellm_provider": "databricks", + "metadata": { + "notes": "Costs per token are the published Global DBU rates times $0.070 per DBU. The '*_dbu_cost_per_token' fields are provided for reference; cost calculation reads the dollar '*_cost_per_token' fields." + }, + "mode": "image_generation", + "output_cost_per_image_token": 4.000003e-05, + "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving" + }, + "databricks/databricks-gpt-image-1-5": { + "cache_creation_input_token_cost": 5.00003e-06, + "cache_read_input_token_cost": 1.24999e-06, + "input_cost_per_image_token": 8.00002e-06, + "input_cost_per_token": 5.00003e-06, + "input_dbu_cost_per_token": 7.1429e-05, + "litellm_provider": "databricks", + "metadata": { + "notes": "Costs per token are the published Global DBU rates times $0.070 per DBU. The '*_dbu_cost_per_token' fields are provided for reference; cost calculation reads the dollar '*_cost_per_token' fields." + }, + "mode": "image_generation", + "output_cost_per_image_token": 3.200001e-05, + "output_cost_per_token": 9.99999e-06, + "output_dbu_cost_per_token": 0.00014286, + "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", + "supports_pdf_input": true, + "supports_vision": true + }, + "databricks/databricks-gpt-image-1-mini": { + "cache_creation_input_token_cost": 1.99997e-06, + "cache_read_input_token_cost": 1.9999e-07, + "input_cost_per_image_token": 2.49998e-06, + "input_cost_per_token": 1.99997e-06, + "input_dbu_cost_per_token": 2.8571e-05, + "litellm_provider": "databricks", + "metadata": { + "notes": "Costs per token are the published Global DBU rates times $0.070 per DBU. The '*_dbu_cost_per_token' fields are provided for reference; cost calculation reads the dollar '*_cost_per_token' fields." + }, + "mode": "image_generation", + "output_cost_per_image_token": 8.00002e-06, + "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving" + }, + "databricks/databricks-gpt-image-2": { + "cache_creation_input_token_cost": 5.00003e-06, + "cache_read_input_token_cost": 1.24999e-06, + "input_cost_per_image_token": 8.00002e-06, + "input_cost_per_token": 5.00003e-06, + "input_dbu_cost_per_token": 7.1429e-05, + "litellm_provider": "databricks", + "metadata": { + "notes": "Costs per token are the published Global DBU rates times $0.070 per DBU. The '*_dbu_cost_per_token' fields are provided for reference; cost calculation reads the dollar '*_cost_per_token' fields." + }, + "mode": "image_generation", + "output_cost_per_image_token": 2.999997e-05, + "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", + "supports_pdf_input": true, + "supports_vision": true + }, + "databricks/databricks-grok-4-7": { + "cache_creation_input_token_cost": 2.49998e-06, + "cache_read_input_token_cost": 6.2503e-07, + "input_cost_per_token": 2.49998e-06, + "input_dbu_cost_per_token": 3.5714e-05, + "litellm_provider": "databricks", + "max_input_tokens": 500000, + "max_output_tokens": 500000, + "metadata": { + "notes": "Costs per token are the published Global DBU rates times $0.070 per DBU. The '*_dbu_cost_per_token' fields are provided for reference; cost calculation reads the dollar '*_cost_per_token' fields." + }, + "mode": "chat", + "output_cost_per_token": 7.50001e-06, + "output_dbu_cost_per_token": 0.00010714, + "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", + "supported_modalities": [ + "text", + "image" + ], + "supported_output_modalities": [ + "text" + ], + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_tool_choice": true, + "supports_vision": true + }, + "databricks/databricks-kimi-k2-7": { + "cache_creation_input_token_cost": 9.4997e-07, + "cache_read_input_token_cost": 1.8998e-07, + "input_cost_per_token": 9.4997e-07, + "input_dbu_cost_per_token": 1.3571e-05, + "litellm_provider": "databricks", + "max_input_tokens": 262144, + "max_output_tokens": 262144, + "metadata": { + "notes": "Costs per token are the published Global DBU rates times $0.070 per DBU. The '*_dbu_cost_per_token' fields are provided for reference; cost calculation reads the dollar '*_cost_per_token' fields." + }, + "mode": "chat", + "output_cost_per_token": 4.00001e-06, + "output_dbu_cost_per_token": 5.7143e-05, + "source": "https://www.databricks.com/product/pricing/foundation-model-serving", + "supported_modalities": [ + "text", + "image" + ], + "supported_output_modalities": [ + "text" + ], + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_tool_choice": true, + "supports_vision": true + }, + "fireworks_ai/accounts/fireworks/routers/spot-deepseek-v4-flash": { + "cache_read_input_token_cost": 2.1e-08, + "deprecation_date": "2026-08-14", + "input_cost_per_token": 1.05e-07, + "litellm_provider": "fireworks_ai", + "max_input_tokens": 1048576, + "max_output_tokens": 384000, + "mode": "chat", + "output_cost_per_token": 2.1e-07, + "source": "https://api.fireworks.ai/v1/serverless/models", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_tool_choice": true, + "supports_vision": false + }, + "fireworks_ai/accounts/fireworks/routers/kimi-k3-spot": { + "cache_read_input_token_cost": 2.1e-07, + "input_cost_per_token": 2.1e-06, + "litellm_provider": "fireworks_ai", + "max_input_tokens": 1048576, + "max_output_tokens": 131072, + "mode": "chat", + "output_cost_per_token": 1.05e-05, + "reasoning_effort_levels": [ + "low", + "high", + "max" + ], + "source": "https://api.fireworks.ai/v1/serverless/models", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_tool_choice": true, + "supports_vision": true + }, + "fireworks_ai/accounts/fireworks/routers/glm-5p3-spot": { + "cache_read_input_token_cost": 1.82e-07, + "input_cost_per_token": 9.8e-07, + "litellm_provider": "fireworks_ai", + "max_input_tokens": 1048576, + "max_output_tokens": 128000, + "mode": "chat", + "output_cost_per_token": 3.08e-06, + "source": "https://api.fireworks.ai/v1/serverless/models", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_tool_choice": true, + "supports_vision": false + }, + "fireworks_ai/accounts/fireworks/routers/deepseek-v4p1-flash-spot": { + "cache_read_input_token_cost": 4.2e-09, + "input_cost_per_token": 2.1e-07, + "litellm_provider": "fireworks_ai", + "max_input_tokens": 1048576, + "max_output_tokens": 393216, + "mode": "chat", + "output_cost_per_token": 8.4e-07, + "source": "https://api.fireworks.ai/v1/serverless/models", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_tool_choice": true, + "supports_vision": true + }, + "fireworks_ai/accounts/fireworks/routers/deepseek-v4p1-flash-1017-spot": { + "cache_read_input_token_cost": 4.2e-09, + "input_cost_per_token": 2.1e-07, + "litellm_provider": "fireworks_ai", + "max_input_tokens": 1048576, + "max_output_tokens": 393216, + "mode": "chat", + "output_cost_per_token": 8.4e-07, + "source": "https://api.fireworks.ai/v1/serverless/models", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_tool_choice": true, + "supports_vision": true + }, + "bigmodel/glm-5.3": { + "input_cost_per_token": 1.1428571428571428e-06, + "output_cost_per_token": 4e-06, + "cache_read_input_token_cost": 2.857142857142857e-07, + "litellm_provider": "bigmodel", + "max_input_tokens": 1000000, + "max_output_tokens": 128000, + "mode": "chat", + "source": "https://docs.bigmodel.cn/cn/guide/start/pricing", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_tool_choice": true, + "thinking_always_on": true, + "metadata": { + "comment": "Official API list price checked 2026-10-27: input 8, output 28, cached input 2 CNY per million tokens; converted at 7.0 CNY/USD. Cache storage is temporarily free and is not encoded." + }, + "supported_endpoints": [ + "/v1/chat/completions", + "/v1/responses", + "/v1/messages" + ], + "supports_native_streaming": true + }, + "bigmodel/glm-5.3-flash": { + "input_cost_per_token": 1.142857142857143e-07, + "output_cost_per_token": 4e-07, + "cache_read_input_token_cost": 3.2857142857142855e-08, + "litellm_provider": "bigmodel", + "max_input_tokens": 1000000, + "max_output_tokens": 128000, + "mode": "chat", + "source": "https://docs.bigmodel.cn/cn/guide/start/pricing", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_tool_choice": true, + "thinking_always_on": true, + "supports_vision": true, + "supports_video_input": true, + "metadata": { + "comment": "Official API list price checked 2026-10-27: input 0.8, output 2.8, cached input 0.23 CNY per million tokens; converted at 7.0 CNY/USD. Cache storage is temporarily free and is not encoded." + }, + "supported_endpoints": [ + "/v1/chat/completions", + "/v1/responses", + "/v1/messages" + ], + "supports_native_streaming": true + }, + "bigmodel/glm-5.3-flashx": { + "input_cost_per_token": 2.857142857142857e-07, + "output_cost_per_token": 1e-06, + "cache_read_input_token_cost": 8.142857142857142e-08, + "litellm_provider": "bigmodel", + "max_input_tokens": 1000000, + "max_output_tokens": 128000, + "mode": "chat", + "source": "https://docs.bigmodel.cn/cn/guide/start/pricing", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_tool_choice": true, + "thinking_always_on": true, + "supports_vision": true, + "supports_video_input": true, + "metadata": { + "comment": "Official API list price checked 2026-10-27: input 2, output 7, cached input 0.57 CNY per million tokens; converted at 7.0 CNY/USD. Cache storage is temporarily free and is not encoded." + }, + "supported_endpoints": [ + "/v1/chat/completions", + "/v1/responses", + "/v1/messages" + ], + "supports_native_streaming": true } } diff --git a/osv-scanner.toml b/osv-scanner.toml index 33e2f614edc..32a4f65fdf9 100644 --- a/osv-scanner.toml +++ b/osv-scanner.toml @@ -1,27 +1,102 @@ -[[IgnoredVulns]] -id = "GHSA-w8v5-vhqr-4h9v" -ignoreUntil = 2026-11-01 -reason = "diskcache has no fixed release published; remove this entry once one exists" - [[IgnoredVulns]] id = "GHSA-v4x8-3wr5-3wq8" ignoreUntil = 2026-11-20 -reason = "the only fixed filelock is 4.2.1, a new major that requires Python >= 3.11 while litellm still supports 3.10, and the advisory is in ReadWriteLock, which litellm never uses (only FileLock); bump filelock and remove this entry once 3.10 is dropped or a 3.x fix ships" +reason = "filelock ReadWriteLock advisory, which no package in the lock takes (litellm and huggingface_hub, filelock's only dependents, use just FileLock and SoftFileLock); fixed only in 4.2.1, and filelock 4.1.1+ needs Python >= 3.11; litellm's own filelock<4.0 cap keeps every Python on 3.32.7 until it is lifted for 3.11+ (#48635, #48802); remove once that lands and 3.10 is dropped" [[IgnoredVulns]] -id = "GHSA-vfj7-8cjw-p6xm" -ignoreUntil = 2026-11-03 -reason = "braces has no fixed release published (3.0.3, 2024-05-21, is latest and last_affected); dev-only via knip > fast-glob > micromatch; remove this entry once one exists" +id = "GHSA-567q-5qvw-pf92" +ignoreUntil = 2026-11-20 +reason = "Windows-only local DoS (CVSS 2.5) in filelock soft locks; litellm never takes SoftFileLock, but huggingface_hub falls back to it in the Hugging Face cache when the filesystem has no flock, which litellm reaches only to download the Kimi K3 tokenizer for Bedrock token counting, and the attack needs another local user who can write that cache; fixed only in 4.2.1, and filelock 4.1.1+ needs Python >= 3.11; litellm's own filelock<4.0 cap keeps every Python on 3.32.7 until it is lifted for 3.11+ (#48635, #48802); remove once that lands and 3.10 is dropped" [[IgnoredVulns]] -id = "GHSA-6q48-6c7w-9gw2" -ignoreUntil = 2026-10-23 -reason = "certifi 2026.10.19 (published 2026-10-20) is inside the 3-day uv exclude-newer window until 2026-10-23 02:24 UTC; bump certifi and remove this entry once it clears" +id = "GHSA-9vhv-jxww-xfm5" +ignoreUntil = 2026-11-20 +reason = "Windows-only local DoS (CVSS 3.3) in filelock ReadWriteLock, which no package in the lock takes (litellm and huggingface_hub, filelock's only dependents, use just FileLock and SoftFileLock); fixed only in 4.2.1, and filelock 4.1.1+ needs Python >= 3.11; litellm's own filelock<4.0 cap keeps every Python on 3.32.7 until it is lifted for 3.11+ (#48635, #48802); remove once that lands and 3.10 is dropped" + +[[IgnoredVulns]] +id = "GHSA-6627-m3xw-93mp" +ignoreUntil = 2026-11-20 +reason = "filelock StrictSoftFileLock claim directories ignore the lock mode, which no package in the lock takes (litellm and huggingface_hub, filelock's only dependents, use just FileLock and SoftFileLock); fixed only in 4.2.1, and filelock 4.1.1+ needs Python >= 3.11; litellm's own filelock<4.0 cap keeps every Python on 3.32.7 until it is lifted for 3.11+ (#48635, #48802); remove once that lands and 3.10 is dropped" + +[[IgnoredVulns]] +id = "GHSA-69hj-f68j-2879" +ignoreUntil = 2026-11-20 +reason = "filelock UnixFileLock truncates and chmods a file another user renames or hard-links in at the lock path; litellm's CLI takes FileLock only inside ~/.litellm, which it creates owner-only, and huggingface_hub takes it in the Hugging Face cache, which litellm reaches only to download the Kimi K3 tokenizer for Bedrock token counting; the attack needs another local user who can rename or link files in that cache; fixed only in 4.2.1, and filelock 4.1.1+ needs Python >= 3.11; litellm's own filelock<4.0 cap keeps every Python on 3.32.7 until it is lifted for 3.11+ (#48635, #48802); remove once that lands and 3.10 is dropped" + +[[IgnoredVulns]] +id = "GHSA-8mx5-7m5m-r77g" +ignoreUntil = 2026-11-20 +reason = "filelock WindowsFileLock ignores mode; the proxy image is Linux, so only Windows installs run it; there litellm's CLI takes FileLock only inside the owner-only ~/.litellm, whose lock file holds no data, and huggingface_hub takes it in the Hugging Face cache, which litellm reaches only to download the Kimi K3 tokenizer for Bedrock token counting; fixed only in 4.2.1, and filelock 4.1.1+ needs Python >= 3.11; litellm's own filelock<4.0 cap keeps every Python on 3.32.7 until it is lifted for 3.11+ (#48635, #48802); remove once that lands and 3.10 is dropped" + +[[IgnoredVulns]] +id = "GHSA-9c4x-gm8v-wgc4" +ignoreUntil = 2026-11-20 +reason = "filelock StrictSoftFileLock and SoftReadWriteLock adopt another user's protocol directory, which no package in the lock takes (litellm and huggingface_hub, filelock's only dependents, use just FileLock and SoftFileLock); fixed only in 4.2.1, and filelock 4.1.1+ needs Python >= 3.11; litellm's own filelock<4.0 cap keeps every Python on 3.32.7 until it is lifted for 3.11+ (#48635, #48802); remove once that lands and 3.10 is dropped" + +[[IgnoredVulns]] +id = "GHSA-9j6q-wvj5-jgjg" +ignoreUntil = 2026-11-20 +reason = "filelock SoftFileLock symlink swap leaks whether a path exists; litellm never takes SoftFileLock, but huggingface_hub falls back to it in the Hugging Face cache when the filesystem has no flock, which litellm reaches only to download the Kimi K3 tokenizer for Bedrock token counting, and the attack needs another local user who can write that cache; fixed only in 4.2.1, and filelock 4.1.1+ needs Python >= 3.11; litellm's own filelock<4.0 cap keeps every Python on 3.32.7 until it is lifted for 3.11+ (#48635, #48802); remove once that lands and 3.10 is dropped" + +[[IgnoredVulns]] +id = "GHSA-cwqr-hh33-gh44" +ignoreUntil = 2026-11-20 +reason = "filelock ReadWriteLock stalls on a crafted lock database, which no package in the lock takes (litellm and huggingface_hub, filelock's only dependents, use just FileLock and SoftFileLock); fixed only in 4.2.1, and filelock 4.1.1+ needs Python >= 3.11; litellm's own filelock<4.0 cap keeps every Python on 3.32.7 until it is lifted for 3.11+ (#48635, #48802); remove once that lands and 3.10 is dropped" + +[[IgnoredVulns]] +id = "GHSA-fq56-3cx3-fjxp" +ignoreUntil = 2026-11-20 +reason = "filelock SoftFileLock stale-lock break removes a live lock on a reused inode; litellm never takes SoftFileLock, but huggingface_hub falls back to it in the Hugging Face cache when the filesystem has no flock, which litellm reaches only to download the Kimi K3 tokenizer for Bedrock token counting, and the attack needs another local user who can write that cache; fixed only in 4.2.1, and filelock 4.1.1+ needs Python >= 3.11; litellm's own filelock<4.0 cap keeps every Python on 3.32.7 until it is lifted for 3.11+ (#48635, #48802); remove once that lands and 3.10 is dropped" + +[[IgnoredVulns]] +id = "GHSA-j8f7-rjxc-mr56" +ignoreUntil = 2026-11-20 +reason = "filelock ReadWriteLock follows a symlink into SQLite, which no package in the lock takes (litellm and huggingface_hub, filelock's only dependents, use just FileLock and SoftFileLock); fixed in 4.0.9, which litellm's own filelock<4.0 cap blocks on every Python until it is lifted (#48635, #48802); remove once that lands" + +[[IgnoredVulns]] +id = "GHSA-m462-7rxw-wvpg" +ignoreUntil = 2026-11-20 +reason = "filelock StrictSoftFileLock follows a symlink swapped in at .filelock, which no package in the lock takes (litellm and huggingface_hub, filelock's only dependents, use just FileLock and SoftFileLock); fixed only in 4.2.1, and filelock 4.1.1+ needs Python >= 3.11; litellm's own filelock<4.0 cap keeps every Python on 3.32.7 until it is lifted for 3.11+ (#48635, #48802); remove once that lands and 3.10 is dropped" + +[[IgnoredVulns]] +id = "GHSA-rfpc-qcw5-3pc4" +ignoreUntil = 2026-11-20 +reason = "filelock SoftFileLock removes a live holder's marker when another user forges its PID; litellm never takes SoftFileLock, but huggingface_hub falls back to it in the Hugging Face cache when the filesystem has no flock, which litellm reaches only to download the Kimi K3 tokenizer for Bedrock token counting, and the attack needs another local user who can write that cache; fixed only in 4.2.1, and filelock 4.1.1+ needs Python >= 3.11; litellm's own filelock<4.0 cap keeps every Python on 3.32.7 until it is lifted for 3.11+ (#48635, #48802); remove once that lands and 3.10 is dropped" + +[[IgnoredVulns]] +id = "GHSA-pcg2-g6cj-q92c" +ignoreUntil = 2026-11-27 +reason = "tornado 6.6 (published 2026-10-21) is the only fix and requires Python >= 3.11, so the Python 3.10 resolution stays on 6.5.10 while 3.11+ locks 6.6; litellm starts no tornado server or client, since semantic-router and aurelio-sdk only declare it and tenacity and sentry-sdk import it only to wrap tornado code when it is present, so tornado's HTTP header parsing is never reached; remove this entry once 3.10 is dropped" + +[[IgnoredVulns]] +id = "GHSA-pw9p-v7r6-gx4p" +ignoreUntil = 2026-11-27 +reason = "tornado 6.6 (published 2026-10-21) is the only fix and requires Python >= 3.11, so the Python 3.10 resolution stays on 6.5.10 while 3.11+ locks 6.6; litellm starts no tornado server or client, since semantic-router and aurelio-sdk only declare it and tenacity and sentry-sdk import it only to wrap tornado code when it is present, so tornado's RedirectHandler is never reached; remove this entry once 3.10 is dropped" + +[[IgnoredVulns]] +id = "GHSA-r4j5-9xpp-3985" +ignoreUntil = 2026-11-27 +reason = "tornado 6.6 (published 2026-10-21) is the only fix and requires Python >= 3.11, so the Python 3.10 resolution stays on 6.5.10 while 3.11+ locks 6.6; litellm starts no tornado server or client, since semantic-router and aurelio-sdk only declare it and tenacity and sentry-sdk import it only to wrap tornado code when it is present, so tornado's chunked body reading is never reached; remove this entry once 3.10 is dropped" + +[[IgnoredVulns]] +id = "GHSA-w8v5-vhqr-4h9v" +ignoreUntil = 2026-11-27 +reason = "diskcache still has no fixed release published (checked 2026-10-28), and it is reached only through the optional caching extra; remove this entry once one exists" + +[[IgnoredVulns]] +id = "GHSA-45c3-73f7-pv4m" +ignoreUntil = 2026-11-27 +reason = "dnspython 2.9.0 (published 2026-10-09) is the only fix and requires Python >= 3.11, so the Python 3.10 resolution stays on 2.8.0 while 3.11+ locks 2.9.0; the advisory is CPU use in dns.name.from_wire_parser and litellm only reaches dnspython through pydantic EmailStr, which never does DNS lookups; remove this entry once 3.10 is dropped or a 3.10-compatible fix ships" + +[[IgnoredVulns]] +id = "GHSA-xcx6-jx8p-x3h5" +ignoreUntil = 2026-11-24 +reason = "@azure/msal-node is fixed only in 7.1.0 (published 2026-10-13), but it is dev-only in vscode-extension via @vscode/vsce > @azure/identity, and the latest @azure/identity (4.14.0) still requires msal-node ^6.0.0, so the lock cannot move without forcing a major override; the advisory is in the auth_code flow, which extension packaging does not run; bump and remove this entry once @azure/identity accepts msal-node >= 7.1.0" [[PackageOverrides]] name = "pillow" version = "12.3.0" ecosystem = "PyPI" vulnerability.ignore = true -effectiveUntil = 2026-10-27 -reason = "pillow 13.0.0 requires Python >= 3.11, so the Python 3.10 resolution of the ci and dev groups stays on 12.3.0; 3.11+ is on 13.0.0" +effectiveUntil = 2026-11-27 +reason = "pillow 13.0.0 requires Python >= 3.11, so the Python 3.10 resolution of the ci and dev groups and of the mlflow extra stays on 12.3.0; 3.11+ is on 13.0.0; pillow has never shipped an older-major release after the next major (no 10.x after 11.0.0, no 11.x after 12.0.0), so 13.x is the only fix line; extended to 2026-11-27 with maintainer approval, same date as the dnspython 3.10 entry; remove once 3.10 is dropped" diff --git a/provider_endpoints_support.json b/provider_endpoints_support.json index 9ba6ed342ea..7b0234e28d7 100644 --- a/provider_endpoints_support.json +++ b/provider_endpoints_support.json @@ -189,6 +189,32 @@ "generateContent": false } }, + "aiand": { + "display_name": "ai& (`aiand`)", + "url": "https://docs.aiand.com/api/chat-completions/", + "endpoints": { + "chat_completions": true, + "responses": true, + "text_completion": true, + "embeddings": false, + "image_generations": false, + "image_edits": false, + "audio_transcriptions": false, + "audio_speech": false, + "rerank": false, + "ocr": false, + "search": false, + "moderations": false, + "realtime": false, + "video_generations": false, + "batches": false, + "messages": true, + "interactions": true, + "systemone": false, + "a2a": true, + "generateContent": true + } + }, "amazon_nova": { "display_name": "Amazon Nova (`amazon_nova`)", "url": "https://docs.litellm.ai/docs/providers/amazon_nova", @@ -1199,7 +1225,7 @@ "responses": true, "text_completion": true, "embeddings": true, - "image_generations": false, + "image_generations": true, "image_edits": false, "audio_transcriptions": false, "audio_speech": false, @@ -3759,6 +3785,32 @@ "generateContent": true } }, + "streamlake": { + "display_name": "StreamLake (`streamlake`)", + "url": "https://docs.litellm.ai/docs/providers/openai_compatible", + "endpoints": { + "chat_completions": true, + "responses": true, + "text_completion": true, + "embeddings": false, + "image_generations": false, + "image_edits": false, + "audio_transcriptions": false, + "audio_speech": false, + "rerank": false, + "ocr": false, + "search": false, + "moderations": false, + "realtime": false, + "video_generations": false, + "batches": false, + "messages": true, + "interactions": true, + "systemone": false, + "a2a": true, + "generateContent": true + } + }, "tencent": { "display_name": "Tencent TokenHub (`tencent`)", "url": "https://docs.litellm.ai/docs/providers/tencent", @@ -3767,8 +3819,8 @@ "responses": true, "text_completion": true, "embeddings": false, - "image_generations": false, - "image_edits": false, + "image_generations": true, + "image_edits": true, "audio_transcriptions": false, "audio_speech": false, "rerank": false, @@ -4411,6 +4463,32 @@ "generateContent": true } }, + "zerogpu": { + "display_name": "ZeroGPU (`zerogpu`)", + "url": "https://docs.litellm.ai/docs/providers/zerogpu", + "endpoints": { + "chat_completions": true, + "responses": true, + "text_completion": true, + "embeddings": false, + "image_generations": false, + "image_edits": false, + "audio_transcriptions": false, + "audio_speech": false, + "rerank": false, + "ocr": false, + "search": false, + "moderations": false, + "realtime": false, + "video_generations": false, + "batches": false, + "messages": true, + "interactions": true, + "systemone": false, + "a2a": true, + "generateContent": true + } + }, "ragflow": { "display_name": "RAGFlow (`ragflow`)", "url": "https://docs.litellm.ai/docs/providers/ragflow", @@ -5248,6 +5326,32 @@ "a2a": false, "generateContent": false } + }, + "bigmodel": { + "display_name": "BigModel (Zhipu AI) (`bigmodel`)", + "url": "https://docs.bigmodel.cn/cn/guide/develop/responses/introduction", + "endpoints": { + "chat_completions": true, + "responses": true, + "text_completion": true, + "embeddings": false, + "image_generations": false, + "image_edits": false, + "audio_transcriptions": false, + "audio_speech": false, + "rerank": false, + "ocr": false, + "search": false, + "moderations": false, + "realtime": false, + "video_generations": false, + "batches": false, + "messages": true, + "interactions": true, + "systemone": false, + "a2a": true, + "generateContent": true + } } }, "endpoints": { diff --git a/pyproject.toml b/pyproject.toml index 0b3480cab23..200bb463313 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -296,7 +296,7 @@ ci = [ "anthropic==0.84.0", "blockbuster==1.5.26", "beautifulsoup4==4.14.3", - "pylint==4.0.5", + "pylint==4.0.9", "langchain-openai==1.1.14", "langgraph>=1.2.4,<1.3.0", "langgraph-prebuilt>=1.1.0,<1.3.0", @@ -360,11 +360,13 @@ cache-keys = [ ] constraint-dependencies = [ "tornado>=6.5.8", + "tornado>=6.6; python_version >= '3.11'", "aiohttp>=3.14.2,<4.0", "packaging>=24.0", "soupsieve>=2.8.4", "httplib2>=0.32.0", "setuptools>=84.1.0", + "dnspython>=2.9.0; python_version >= '3.11'", ] override-dependencies = [ # a2a-sdk 1.x requires packaging>=24.0; lunary 1.4.x still caps at <24.0. @@ -401,7 +403,7 @@ markers = [ "asyncio: mark test as an asyncio test", "limit_leaks: mark test with memory limit for leak detection (e.g., '40 MB')", "no_parallel: mark test to run sequentially (not in parallel) - typically for memory measurement tests", - "requires_rust_extension: public Python contract requiring an enabled, compiled Rust extension", + "requires_rust_extension: public Python contract tests that run against the release-built wheel", ] filterwarnings = [ # Suppress Pydantic serializer warnings from mock server responses (non-critical for memory tests) diff --git a/schema.prisma b/schema.prisma index 83a0e6f9e05..2965174114b 100644 --- a/schema.prisma +++ b/schema.prisma @@ -1163,6 +1163,7 @@ model LiteLLM_ManagedFileTable { @@index([unified_file_id]) @@index([flat_model_file_ids], type: Gin) @@index([team_id, created_at(sort: Desc)]) + @@index([created_by, created_at(sort: Desc)]) } model LiteLLM_ManagedObjectTable { // for batches or finetuning jobs which use the @@ -2060,3 +2061,73 @@ model LiteLLM_TelemetryReport { @@index([window_end]) @@index([created_at]) } + +enum AccountingEventKind { + inbound_usage + outbound_usage + cost +} + +enum AccountingDeliveryState { + pending + applied + parked +} + +enum AccountingDeliveryTarget { + LiteLLM_VerificationToken + LiteLLM_UserTable + LiteLLM_TeamTable + LiteLLM_TeamMembership + LiteLLM_OrganizationTable + LiteLLM_OrganizationMembership + LiteLLM_EndUserTable + LiteLLM_AgentsTable + LiteLLM_TagTable + LiteLLM_ProjectTable + LiteLLM_ModelAccessGroupBudgetTable + LiteLLM_BudgetTable + LiteLLM_BudgetWindowSpend + LiteLLM_DailyUserSpend + LiteLLM_DailyTeamSpend + LiteLLM_DailyOrganizationSpend + LiteLLM_DailyEndUserSpend + LiteLLM_DailyAgentSpend + LiteLLM_DailyTagSpend + LiteLLM_DailyModelUsage + LiteLLM_DailyToolSpend + LiteLLM_AutoRouterDailySpend +} + +// Durable accounting ledger. One row per usage or cost event; payload holds the +// private event envelope versioned by schema_version. Usage rows retain request-scoped +// pricing context; cost rows include resolved rates and the finalized pricing snapshot. +model LiteLLM_AccountingEvent { + event_id String @id + kind AccountingEventKind + source_event_id String? + schema_version Int + payload_hash String + occurred_at DateTime + recorded_at DateTime @default(now()) + payload Json + + @@index([recorded_at]) + @@index([kind, source_event_id]) +} + +// One row per (event, target table, version): pending work for the projector and, +// once applied in the same transaction as the target write, the receipt that stops a retry. +model LiteLLM_AccountingDelivery { + event_id String + target AccountingDeliveryTarget + version Int + state AccountingDeliveryState @default(pending) + attempts Int @default(0) + next_attempt_at DateTime @default(now()) + applied_at DateTime? + last_error String? + + @@id([event_id, target, version]) + @@index([target, state, next_attempt_at]) +} diff --git a/skills/litellm-setup/SKILL.md b/skills/litellm-setup/SKILL.md new file mode 100644 index 00000000000..7c824751d6f --- /dev/null +++ b/skills/litellm-setup/SKILL.md @@ -0,0 +1,205 @@ +--- +name: litellm-setup +description: Set up a self-hosted LiteLLM proxy, the OpenAI-compatible LLM gateway, on this machine, from install through provider keys, config.yaml, a master key, optional Postgres and Admin UI, and a verified chat completion. Use when the user asks to set up LiteLLM, install the LiteLLM proxy, self-host an LLM gateway, or put one endpoint in front of OpenAI, Anthropic, Gemini, Azure, Bedrock, Ollama, or other providers. Not for using the LiteLLM Python SDK inside an app +--- + +# Set up a LiteLLM proxy + +Take the user from nothing to a running LiteLLM proxy that has answered one chat completion. Run every command yourself unless a step says the user does it + +Never print a secret. Provider keys, the master key, the salt key, the database URL, and virtual keys live only in `.env`, and `config.yaml` reads them through `os.environ/NAME`. Check that a value is there with `grep -c '^NAME=.' .env`, never with `cat .env` or `echo "$NAME"`. Load `.env` into a shell with this line, which exports each line as it is, so a `&` or `$` in a value stays literal, and first drops any database settings the shell already had and sets `LITELLM_MODE=PRODUCTION`, which stops `litellm` from also loading a `.env` it finds above its install folder, such as `~/.env`, so only this `.env` picks the database. The steps that need it start with it: + +```bash +unset DATABASE_URL DIRECT_URL DATABASE_HOST; export LITELLM_MODE=PRODUCTION; while IFS= read -r line || [ -n "$line" ]; do case "$line" in [A-Za-z_]*=*) export "$line" ;; esac; done < .env +``` + +## 1. Ask once + +Ask everything in one message, with defaults the user can accept by saying "go": + +- Providers and models. Default is OpenAI with its newest flagship model, using the `OPENAI_API_KEY` in your environment when `[ -n "$OPENAI_API_KEY" ] && echo set` says it is there. Run that check before asking, and say in the question that the default uses that variable, naming it but never its value, since a key in your environment can belong to another account +- Whether they want virtual keys, teams, spend tracking, or the Admin UI. Those need Postgres, plain routing does not. Default is no +- uv (default) or Docker. With Postgres, Docker runs the repo's quickstart, which brings its own database, and uv needs a Postgres server they already have, with a new, empty database for LiteLLM, so someone with their own Postgres server picks uv +- Folder and port. Defaults are `./litellm-proxy` (`./litellm-gateway` for the quickstart) and 4000 + +Then follow the steps for their answers. Plain routing skips steps 3 and 6. The quickstart is steps 2, 3, 8, and 9. uv with their own Postgres skips step 3 + +In the same message, say that someone who picks uv and would rather answer prompts can run `litellm --setup` in a separate terminal window once LiteLLM is installed, not through Claude Code. Never run it yourself, since it needs a real terminal and without one prints "Setup cancelled." and writes nothing. Give them the command as `LITELLM_MODE=PRODUCTION /litellm --setup`, with `` replaced by the folder `uv tool dir --bin` prints, to run from the folder they want the config in. It writes `litellm_config.yaml` there with the provider keys and master key in plain text and offers to start the proxy, which then listens on every network interface and stops with Ctrl+C in that window. When the user is done, run this in that folder. It makes the file readable only by them, keeps it out of git (the wizard does neither), and prints only the model names. Never print that file or run `grep`, `sed`, or `cat` on it: + +```bash +chmod 600 litellm_config.yaml; grep -qx 'litellm_config.yaml' .gitignore 2>/dev/null || echo 'litellm_config.yaml' >> .gitignore +"$(uv tool dir)/litellm/bin/python" -I -c 'import yaml; print(*(m["model_name"] for m in yaml.safe_load(open("litellm_config.yaml"))["model_list"]), sep="\n")' +``` + +Then skip to step 8 and run it against their proxy, starting that shell command with this line instead of the loader line, which reads the master key without printing it: + +```bash +export LITELLM_MASTER_KEY="$("$(uv tool dir)/litellm/bin/python" -I -c 'import yaml; print(yaml.safe_load(open("litellm_config.yaml"))["general_settings"]["master_key"])')" +``` + +## 2. Check prerequisites + +```bash +uv --version; docker info --format '{{.ServerVersion}}'; docker compose version; curl --version | head -1; openssl version; command -v python3 +``` + +On native Windows, ask the user to run Claude Code inside WSL, since every command here is POSIX shell. Every path needs curl, openssl, and python3, so ask the user to install any that is missing. The uv path needs uv, which downloads a supported Python (LiteLLM supports 3.10 to 3.14) when the `--python` range in step 4 rules out the one on the machine. If uv is missing, offer to install it, and only after the user says yes run `curl -LsSf https://astral.sh/uv/install.sh | env UV_NO_MODIFY_PATH=1 sh`, which leaves their shell profile alone (https://docs.astral.sh/uv/getting-started/installation/). It puts uv in `~/.local/bin`, so start every later command that runs `uv` or `litellm` with `export PATH="$HOME/.local/bin:$PATH";`. The Docker path needs a running Docker daemon, and the quickstart also needs Docker Compose v2. If `docker info` says `permission denied`, the user's account cannot use Docker without sudo. Offer the uv path, or ask them to add themselves to the `docker` group the way https://docs.docker.com/engine/install/linux-postinstall/ shows and start a new login session before you check again + +Check the port is free with `curl -s -o /dev/null --max-time 2 http://127.0.0.1:4000; echo $?`, which prints `7` (could not connect) only when nothing listens there. Don't use `lsof` for this, since it misses ports that root or Docker hold. If it is taken, pick another port and use it everywhere below, because a proxy asked for a busy 4000 silently moves to a random port + +## 3. Postgres with Docker: run the quickstart + +The repo's quickstart starts the gateway, Postgres, and the Admin UI in Docker, listening on this machine only, and puts a `litellm-gateway` command in that folder that stops, starts, updates, or removes them. It asks nothing when it has no terminal. It writes the master key, salt key, and database password to its own `.env` and never prints them. Download it, then run it with the folder and port from step 1. It returns once the gateway is ready: + +```bash +curl -fsSL https://raw.githubusercontent.com/BerriAI/litellm/main/scripts/quickstart.sh -o quickstart.sh +LITELLM_DIR="$PWD/litellm-gateway" LITELLM_PORT=4000 sh quickstart.sh --yes +cd litellm-gateway +``` + +Models live in the database here, so add each one through the API instead of a `config.yaml`, naming it the way step 5 says. Pipe the request body in, so the provider key never shows up in output or on a command line. Unless the user agreed to the key in your environment, as step 5 says, ask them to add the line `OPENAI_API_KEY=` to this `.env` themselves. Run the loader line first: + +```bash +python3 -c 'import json, os, sys; json.dump({"model_name": "gpt-6.1-sol", "litellm_params": {"model": "openai/gpt-6.1-sol", "api_key": os.environ["OPENAI_API_KEY"]}}, sys.stdout)' \ + | curl -sS -o /dev/null -w '%{http_code}\n' http://127.0.0.1:4000/model/new \ + -H "Authorization: Bearer $LITELLM_MASTER_KEY" -H "Content-Type: application/json" -d @- +``` + +Run that in one shell command that starts with the loader line, since the master key is in `.env`. `200` means the model was added. Then go to step 8 + +## 4. Install + +uv: + +```bash +uv tool install --python '>=3.10,<3.15' 'litellm[proxy]' +export PATH="$(uv tool dir --bin):$PATH"; litellm --version +``` + +With their own Postgres, install `'litellm[proxy,extra_proxy]'` instead, with the same `--python` range, which adds the Prisma client the proxy uses for the database. Running `uv tool install` again with the new extras replaces the old install. Start every later command that runs `litellm` with `export PATH="$(uv tool dir --bin):$PATH";`, so this install runs even when the shell has no `litellm` or an older one from a venv or `pip install litellm`. `uv tool update-shell` puts it on the PATH of new shells by editing the user's shell profile, so run it only after the user says yes + +Docker: + +```bash +docker pull docker.litellm.ai/berriai/litellm:main-stable +``` + +## 5. Write `.env` and `config.yaml` + +Run every command from here on in the folder from step 1. Create `.env` readable only by the user, keep it out of git, and add a master key unless it already has one. The proxy refuses to start without one, and `sk-` is the format of every key it issues: + +```bash +mkdir -p litellm-proxy && cd litellm-proxy +touch .env && chmod 600 .env; grep -qx '.env' .gitignore 2>/dev/null || echo '.env' >> .gitignore +grep -q '^LITELLM_MASTER_KEY=.' .env || printf 'LITELLM_MASTER_KEY=sk-%s\n' "$(openssl rand -hex 32)" >> .env +``` + +Copy a provider key that is already in your environment only after the user agreed to that variable, in their step 1 answer or when you ask now, and copy it without printing it, as in `printf 'OPENAI_API_KEY=%s\n' "$OPENAI_API_KEY" >> .env`. Otherwise ask the user to add the line `OPENAI_API_KEY=` to `.env` themselves and tell you when it is there. If they paste a key into the chat anyway, write it to `.env` and never repeat it. Keep one `NAME=value` per line with no quotes, so `docker --env-file` and the loader line read the same value + +Confirm each model's current LiteLLM name in the cost map instead of trusting memory, since model names go stale fast. This prints the chat models of the provider named last (`openai`, `anthropic`, `gemini`, `azure`, `bedrock`, `vertex_ai`, and so on) the way `config.yaml` takes them, with the provider in front. It matches by prefix, so `bedrock` also lists the newer Bedrock models and `vertex_ai` lists every Vertex family. For Ollama, use a model from `ollama list` instead: + +```bash +curl -fsSL https://raw.githubusercontent.com/BerriAI/litellm/main/model_prices_and_context_window.json | python3 -c ' +import json, sys +for name, row in json.load(sys.stdin).items(): + provider = str(row.get("litellm_provider", "")) if isinstance(row, dict) else "" + if provider.startswith(sys.argv[1]) and row.get("mode") == "chat": + prefix = "bedrock" if provider == "bedrock_converse" else "vertex_ai" if provider.startswith("vertex_ai") else provider + print(name if name.startswith(prefix + "/") else prefix + "/" + name) +' openai +``` + +In `config.yaml`, `model` is a name from that list, as in `openai/gpt-6.1-sol` or `bedrock/us.anthropic.`, and `model_name` is what clients will send. If the folder already has a `config.yaml`, show the user its `model_name` lines and ask before replacing it. This example uses the newest GPT model in the cost map when this skill was written, so replace it with what the user picked: + +```yaml +model_list: + - model_name: gpt-6.1-sol + litellm_params: + model: openai/gpt-6.1-sol + api_key: os.environ/OPENAI_API_KEY + +general_settings: + master_key: os.environ/LITELLM_MASTER_KEY +``` + +Add one entry per model. On Azure, ask the user for each deployment's name and the model it runs. Use `azure/` as `model`, since Azure routes by deployment and a name from the lookup works only when the deployment has that same name, and add `model_info:` with `base_model: azure/` to the entry, since LiteLLM prices each call by that name. Providers that need more than a key, like Azure or Bedrock, list their `litellm_params` on their page under https://docs.litellm.ai/docs/providers. Point every secret at `.env` through `os.environ/NAME` the same way + +## 6. Their own Postgres, on the uv path + +Ask the user to create a new, empty database for LiteLLM on their server (`CREATE DATABASE litellm;`) and add `DATABASE_URL=postgresql://...` for it to `.env` themselves. The proxy creates its tables there on first start and stops on a database that already holds other tables. If that URL goes through a transaction pooler such as PgBouncer, they also add `DIRECT_URL` for the same database without the pooler, which the migrations use. Then add a salt key. It encrypts the provider credentials the proxy stores in the database and falls back to the master key when unset, so set it once and never change it: + +```bash +grep -q '^LITELLM_SALT_KEY=.' .env || printf 'LITELLM_SALT_KEY=sk-%s\n' "$(openssl rand -hex 32)" >> .env +``` + +Generate the Prisma client once inside the tool's environment. A pip or uv install doesn't ship it generated (Docker images do): + +```bash +tool="$(uv tool dir)/litellm" +schema=$("$tool/bin/python" -I -c 'import importlib.util, os; print(os.path.join(importlib.util.find_spec("litellm").submodule_search_locations[0], "proxy", "schema.prisma"))') +PATH="$tool/bin:$PATH" prisma generate --schema "$schema" +``` + +## 7. Start the proxy + +Bind to `127.0.0.1` unless the user wants other machines to reach it + +uv, in one shell command that starts with the loader line, since the installed `litellm` does not read `.env` by itself: + +```bash +export PATH="$HOME/.local/bin:$PATH"; export PATH="$(uv tool dir --bin):$PATH" +nohup litellm --config config.yaml --host 127.0.0.1 --port 4000 > litellm.log 2>&1 & +echo $! > litellm.pid +``` + +Docker: + +```bash +docker run -d --name litellm --env-file .env -v "$PWD/config.yaml:/app/config.yaml:ro" -p 127.0.0.1:4000:4000 \ + docker.litellm.ai/berriai/litellm:main-stable --config /app/config.yaml --port 4000 +``` + +Wait on the health route, stopping early if the proxy exits. The first start with Postgres applies the database migrations and takes longer. Define `alive` for the path you took, `alive() { kill -0 "$(cat litellm.pid)" 2>/dev/null; }` for uv or `alive() { [ "$(docker inspect -f '{{.State.Running}}' litellm 2>/dev/null)" = true ]; }` for Docker, in the same shell command as the loop: + +```bash +for i in $(seq 1 180); do curl -fsS http://127.0.0.1:4000/health/liveliness >/dev/null 2>&1 && break; alive || break; sleep 1; done +curl -sS http://127.0.0.1:4000/health/readiness +``` + +Readiness reports `"db":"connected"` with Postgres and `"db":"Not connected"` without it. If the proxy never comes up, read the end of `litellm.log` (or `docker logs litellm`) and check the troubleshooting list + +## 8. Verify with a chat completion + +Use a `model_name` from `config.yaml` (or step 3), in one shell command that starts with the loader line: + +```bash +curl -sS http://127.0.0.1:4000/v1/chat/completions \ + -H "Authorization: Bearer $LITELLM_MASTER_KEY" -H "Content-Type: application/json" \ + -d '{"model": "gpt-6.1-sol", "messages": [{"role": "user", "content": "Say hello in five words."}]}' +``` + +Show the user the reply in `choices[0].message.content`. An error here means the setup is not done, so fix it before handing off + +## 9. Hand off + +Tell the user, without printing any secret: + +- The base URL is `http://127.0.0.1:4000`. Any OpenAI-compatible client works with it as the base URL and the master key or a virtual key as the API key +- The master key is `LITELLM_MASTER_KEY` in the folder's `.env`, or `general_settings.master_key` in `litellm_config.yaml` when they used `litellm --setup` +- To stop it, `kill "$(cat litellm.pid)"` (uv), `docker stop litellm` (Docker), `/litellm-gateway stop` (quickstart), or Ctrl+C in its window (`litellm --setup`). To start it again, `docker start litellm`, `/litellm-gateway start`, on uv the whole step 7 command as you ran it, loader line and PATH export included, wrapped in `( ... )` so their shell keeps its own settings, shown as a code block and never paraphrased, since a new shell has neither, or for `litellm --setup` `LITELLM_MODE=PRODUCTION /litellm --config litellm_config.yaml --host 127.0.0.1 --port ` in a terminal window in that folder, with `` and `` filled in, since running the wizard again writes a new config with a new master key. `update` and `uninstall` update or remove a quickstart install. Give the quickstart commands with the folder's full path, since a bare `litellm-gateway` is on PATH only when `~/.local/bin` is, and can belong to an earlier install +- With Postgres, the Admin UI is at `http://127.0.0.1:4000/ui` (user `admin`, password the master key), and `POST /key/generate` with the master key creates virtual keys with their own budgets and model lists. Without Postgres, both need step 3 or 6 first +- The Admin UI warns that the master-key login is a shared secret, which is fine while only this machine reaches the proxy. Before anyone else can reach it, invite an admin with their own password on the Internal Users page, then set `general_settings.disable_env_credential_login: true` in the proxy config +- To manage the running proxy from a coding agent (keys, teams, users, models, MCP servers), install `npx skills add BerriAI/litellm-skills -g` + +## Troubleshooting + +- `refused to start: no master key is set` means the loader line did not run in the shell command that started `litellm`, or `--env-file .env` is missing from `docker run` +- `a database URL is set but the prisma CLI is neither on PATH nor importable` means the install lacks `extra_proxy`, so rerun step 4 with it, or, on plain routing, that the command that started `litellm` did not start with the loader line +- `The Client hasn't been generated yet` or `Unable to find Prisma binaries` means the Prisma generate command in step 6 has not run +- `Incorrect API key provided` or another provider `AuthenticationError` means a provider key is wrong. Fix it in `.env` and restart, since the proxy reads the environment only at startup. On uv, stop it and rerun step 7. On Docker, `docker rm -f litellm` and rerun step 7, since `docker restart` keeps the environment the container was created with. On the quickstart the key is saved with the model, so delete the model and add it again: `GET /model/info` lists each model's `model_info.id`, and `POST /model/delete` with `{"id": ""}` deletes it +- `Cannot automatically baseline this database` means `DATABASE_URL` points at a database that already holds tables LiteLLM did not create. Point it at a new, empty database +- `LLM Provider NOT provided` means a `model` in `config.yaml` (or step 3) lacks its provider in front. Use the name as the step 5 lookup prints it +- `Invalid model name passed in model=...` means the request's `model` is not a `model_name` in `config.yaml` or step 3. `GET /v1/models` lists the ones the key can use +- `No connected db.` on a proxy without Postgres means the bearer token is not the master key +- `Conflict. The container name "/litellm" is already in use` means an earlier run left a container. `docker start litellm` reuses it, or with the user's OK `docker rm -f litellm` and rerun step 7 +- Inside Docker, `localhost` in `config.yaml` (an Ollama `api_base`, say) is the container itself. Use `host.docker.internal`, and on Linux also pass `--add-host=host.docker.internal:host-gateway` diff --git a/tests/base_sdk_tests/check_base_sdk_install.py b/tests/base_sdk_tests/check_base_sdk_install.py index e546549d25f..e37593adb4b 100644 --- a/tests/base_sdk_tests/check_base_sdk_install.py +++ b/tests/base_sdk_tests/check_base_sdk_install.py @@ -8,6 +8,8 @@ the very class of undeclared-dependency bug this guards against. import argparse import importlib.util +from importlib.machinery import EXTENSION_SUFFIXES +from pathlib import Path import re import sys import traceback @@ -89,6 +91,18 @@ def check_import() -> str: return f"imported {distribution} {sdk_version}" +def check_native_extension() -> str: + import litellm + from litellm.rust_bridge import _native + + native_path: Final = Path(_native.__file__).resolve() + package_path: Final = Path(litellm.__file__).resolve().parent + _require(native_path.parent == package_path / "rust_bridge", "native extension is outside the SDK package") + _require(any(str(native_path).endswith(suffix) for suffix in EXTENSION_SUFFIXES), "native module is not compiled") + _require(_native.trace_encode_error("ping") == b"\x12\x04ping", "native OTLP error encoding failed") + return f"loaded and exercised {native_path}" + + def check_completion() -> str: import litellm @@ -230,6 +244,7 @@ def check_bedrock_credential_resolution() -> str: CHECKS: tuple[tuple[str, Callable[[], str]], ...] = ( ("environment is base-only", check_environment_is_base_only), ("import litellm", check_import), + ("native extension", check_native_extension), ("optional MCP installation guidance", check_mcp_install_guidance), ("chat completion", check_completion), ("chat completion with a function tool", check_completion_with_function_tool), @@ -250,8 +265,11 @@ def _run(check: Callable[[], str]) -> tuple[bool, str]: def main() -> int: parser = argparse.ArgumentParser(description=__doc__) - parser.add_argument("--profile", choices=("legacy", "core", "dependencies"), default="legacy") + parser.add_argument("--profile", choices=("legacy", "core", "dependencies", "native"), default="legacy") profile = parser.parse_args().profile + if profile == "native": + print(check_native_extension()) + return 0 for module in ("boto3", "botocore", "tokenizers", "huggingface_hub"): present = importlib.util.find_spec(module) is not None _require(present == (profile != "core"), f"{profile}: unexpected presence of {module}: {present}") diff --git a/tests/benchmarks/test_json_fragment_accumulator_benchmarks.py b/tests/benchmarks/test_json_fragment_accumulator_benchmarks.py new file mode 100644 index 00000000000..807dd8ff236 --- /dev/null +++ b/tests/benchmarks/test_json_fragment_accumulator_benchmarks.py @@ -0,0 +1,26 @@ +from collections.abc import Iterator +from typing import Final + +import pytest + +from litellm.litellm_core_utils.json_fragment_accumulator import JSONFragmentAccumulator + +CONCATENATED_VALUES: Final = 20_000 + + +def _popped_values(accumulator: JSONFragmentAccumulator) -> Iterator[object]: + while True: + found, value = accumulator.pop_next_value() + if not found: + return + yield value + + +@pytest.mark.benchmark +def test_draining_many_concatenated_values() -> None: + accumulator: Final = JSONFragmentAccumulator() + accumulator.append('{"a": 1}' * CONCATENATED_VALUES) + + drained: Final = sum(1 for _ in _popped_values(accumulator)) + + assert drained == CONCATENATED_VALUES diff --git a/tests/benchmarks/test_sse_lines_benchmarks.py b/tests/benchmarks/test_sse_lines_benchmarks.py new file mode 100644 index 00000000000..1320fae49a6 --- /dev/null +++ b/tests/benchmarks/test_sse_lines_benchmarks.py @@ -0,0 +1,27 @@ +from collections.abc import Sequence +from typing import Final + +import pytest + +from litellm.llms.custom_httpx.sse_lines import iter_sse_lines + +EVENT: Final = 'data: {"choices":[{"delta":{"content":"hello world"}}]}' + + +def _chunks(line_break: str) -> Sequence[str]: + body: Final = "".join(f"{EVENT}{line_break}{line_break}" for _ in range(2000)) + return tuple(body[i : i + 512] for i in range(0, len(body), 512)) + + +LF_CHUNKS: Final = _chunks("\n") +CRLF_CHUNKS: Final = _chunks("\r\n") + + +@pytest.mark.benchmark +def test_iter_sse_lines_lf_stream() -> None: + assert sum(1 for _ in iter_sse_lines(LF_CHUNKS)) == 4000 + + +@pytest.mark.benchmark +def test_iter_sse_lines_crlf_stream() -> None: + assert sum(1 for _ in iter_sse_lines(CRLF_CHUNKS)) == 4000 diff --git a/tests/code_coverage_tests/router_code_coverage.py b/tests/code_coverage_tests/router_code_coverage.py index 853b10ad97b..c7781819ae4 100644 --- a/tests/code_coverage_tests/router_code_coverage.py +++ b/tests/code_coverage_tests/router_code_coverage.py @@ -95,6 +95,7 @@ ignored_function_names = [ "arm_routing_read_prefetch", # Tested in tests/unit/caching/test_request_redis_batch_pre_call.py (file lacks "router" in name) "_deployment_params_base_model", # Tested through log_retry in test_router_helper_utils.py "_configured_model_info", # Tested through get_configured_service_tiers in test_router.py + "_every_deployment_refused", # Tested through the unsupported transcription retry tests in test_router.py "_routable_deployments", # Tested through get_configured_service_tiers and get_routable_upstream_model in test_router.py "_async_get_available_deployment", # Body of the `route {model}` phase wrapper, exercised through async_get_available_deployment in test_router.py "_async_get_available_deployment_for_pass_through", # Same, through async_get_available_deployment_for_pass_through in test_router.py @@ -106,6 +107,7 @@ ignored_function_names = [ "_deployment_num_retries", # Tested through the deployment num_retries mid-stream budget test in test_router.py "_request_fallback_list", # Tested through every mid-stream retry test in test_router.py "_request_model_group", # Tested through test_anthropic_messages_retry_budget_precedence_direct_call + "_search_tool_support", # Tested through the test_get_search_tool_support_* tests "_mid_stream_retry_trigger", # Tested through the retry policy mid-stream budget test in test_router.py "_anthropic_messages_group_retry_policy", # Tested through the retry budget precedence test in test_router.py "_anthropic_messages_resolved_retry_policy", # Tested through the malformed retry policy tests in test_router.py @@ -171,20 +173,29 @@ ignored_function_names = [ "_deployment_field", # Read by is_batch_capable, tested through the mixed-group tests in test_router.py "_deployment_provider", # Read by without_deployments_that_cannot_batch, tested through the mixed-group tests in test_router.py "_cannot_run_batches", # Tested through the Azure and OpenAI mixed-group acreate_batch tests in test_router.py + "_responses_continuation", # Tested through the Responses mid-stream fallback tests in tests/unit/llms/base_llm/responses/test_transformation.py + "_responses_continuation_ceilings", # Tested through the Responses mid-stream fallback tests in tests/unit/llms/base_llm/responses/test_transformation.py "_team_deployments_named", # Tested through the team lookups in the concurrent delete tests in test_router.py + "_served_openai_models", # Cached as served_openai_models, tested through the pre-call check token count tests in test_router.py + "priority_header_update", # Tested through the priority header tests in test_common_request_processing.py + "_drops_params", # Read by split_request_priority and priority_header_update, tested through both + "_responses_event_announces_background_run", # Tested through the background Responses stream tests in test_router.py + "_aresponses_background_stream_can_release", # Tested through the background Responses stream tests in test_router.py + "_raise_released_stream_error", # Tested through the background Responses stream content-policy tests in test_router.py + "_mid_stream_error_before_output", # Tested through the Responses mid-stream fallback and background stream tests ] def main(): router_file = [ "./litellm/router.py", - "./litellm/router_utils/batch_utils.py", + "./litellm/litellm_core_utils/batch_utils.py", "./litellm/router_utils/pattern_match_deployments.py", ] # router_file = [ # "../../litellm/router.py", # "../../litellm/router_utils/pattern_match_deployments.py", - # "../../litellm/router_utils/batch_utils.py", + # "../../litellm/litellm_core_utils/batch_utils.py", # ] ## LOCAL TESTING tests_dir = "./tests/" # Update this path if your tests directory is located elsewhere # tests_dir = "../../tests/" # LOCAL TESTING diff --git a/tests/code_coverage_tests/router_surface_allowlist.json b/tests/code_coverage_tests/router_surface_allowlist.json new file mode 100644 index 00000000000..52e5bb43625 --- /dev/null +++ b/tests/code_coverage_tests/router_surface_allowlist.json @@ -0,0 +1,212 @@ +{ + "_doc": "Router members and litellm.router_utils modules used outside the router. Shrink-only: see tests/code_coverage_tests/router_surface_check.py.", + "members_outside": [ + "_get_client", + "_zero_cost_cache", + "a_add_message", + "aadapter_completion", + "aanthropic_messages", + "abatch_completion", + "abatch_completion_fastest_response", + "acancel_batch", + "acancel_fine_tuning_job", + "acompletion", + "acreate_assistants", + "acreate_batch", + "acreate_file", + "acreate_fine_tuning_job", + "acreate_thread", + "adaptive_routers", + "adecisions", + "adelete_assistant", + "aembedding", + "afile_content", + "afile_delete", + "aget_assistants", + "aget_messages", + "aget_responses", + "aget_thread", + "alist_batches", + "alist_fine_tuning_jobs", + "allm_passthrough_route", + "amoderation", + "aocr", + "are_all_deployments_blocked", + "arefresh_model_info", + "aretrieve_batch", + "aretrieve_fine_tuning_job", + "arm_routing_read_prefetch", + "arun_thread", + "async_get_available_deployment", + "async_get_fully_unhealthy_model_names", + "async_get_healthy_deployments", + "async_pre_routing_hook", + "auto_routers", + "avector_store_create", + "avector_store_search", + "background_health_check_model_groups", + "bind_to_request_logging", + "cache", + "cache_responses", + "cached_deployment_model_info", + "cached_model_group_info", + "completion", + "complexity_routers", + "config_deployments", + "content_policy_fallbacks", + "context_window_fallbacks", + "cooldown_time", + "default_deployment", + "default_litellm_params", + "delete_deployment", + "deployment_latency_map", + "deployment_names", + "deployment_usable_by_team", + "deployments_for_request", + "deployments_named", + "discard", + "embedding", + "enable_health_check_routing", + "fallbacks", + "generate_model_id", + "get_all_deployments", + "get_available_deployment_for_pass_through", + "get_available_guardrail", + "get_candidate_model_ids_for_route", + "get_configured_display_name", + "get_configured_mode", + "get_configured_service_tiers", + "get_configured_token_limits", + "get_credential_deployment", + "get_deployment", + "get_deployment_by_model_group_name", + "get_deployment_credentials", + "get_deployment_credentials_with_provider", + "get_deployment_model_info", + "get_discovered_model_info", + "get_fully_blocked_model_names", + "get_model_access_groups", + "get_model_from_alias", + "get_model_group_info", + "get_model_group_usage", + "get_model_ids", + "get_model_info", + "get_model_list", + "get_model_list_from_model_alias", + "get_model_list_from_routing_groups", + "get_model_list_of_routed_group", + "get_model_listing_info", + "get_model_names", + "get_remaining_model_group_usage", + "get_routable_deployments", + "get_routable_upstream_model", + "get_router_deployment_budget_limiter", + "get_routing_group", + "get_search_tool_support", + "get_settings", + "get_valid_args", + "guardrail_list", + "has_model_id", + "health_check_ignore_transient_errors", + "health_state_cache", + "is_deployment_blocked", + "is_model_access_group_for_wildcard_route", + "is_recognized_model", + "kubernetes_pod_discovery", + "map_team_model", + "model_group_alias", + "model_list", + "model_name_to_deployment_indices", + "model_names", + "pattern_router", + "priority_header_update", + "prompt_caching_pin_cache", + "provider_budget_config", + "quality_routers", + "resolve_model_name_from_model_id", + "resolve_served_model_name", + "resolved_litellm_models", + "routable_model_group", + "router_general_settings", + "routing_groups", + "routing_plugins", + "schedule_acompletion", + "search_tools", + "serve_through_request_logging", + "should_include_deployment", + "split_request_priority", + "team_model_to_deployment_indices", + "team_pattern_routers", + "team_ptu_ceiling", + "team_public_model_names", + "team_public_model_names_of", + "update_redis_cache", + "update_settings", + "upsert_deployment", + "wildcard_route_deployments", + "wildcard_routed_models" + ], + "members_router_family": [ + "_count_pre_call_check_tokens", + "_pre_call_checks", + "_update_kwargs_before_fallbacks", + "acompletion", + "adecisions", + "aembedding", + "allowed_fails", + "allowed_fails_policy", + "aresponses", + "async_function_with_fallbacks", + "async_get_healthy_deployments", + "cache", + "cached_deployment_model_info", + "cooldown_cache", + "cooldown_time", + "default_max_parallel_requests", + "deployments_named", + "disable_cooldowns", + "embedding", + "enable_pre_call_checks", + "enable_tag_filtering", + "explicit_allowed_fails", + "fallback_access_check", + "fallback_budget_check", + "fallbacks", + "get_all_deployments", + "get_allowed_fails_from_policy", + "get_deployment", + "get_model_group", + "get_model_ids", + "get_model_info", + "get_model_list", + "get_router_model_info", + "log_retry", + "model_list", + "provider_default_deployment_ids", + "routing_group_has_alternatives", + "routing_strategy", + "search_tools", + "set_custom_routing_strategy", + "slack_alerting_logger", + "tag_filtering_match_any", + "tag_routing_prefix", + "team_model_has_alternatives" + ], + "router_utils_imports_outside": [ + "litellm.router_utils.access_windows", + "litellm.router_utils.add_retry_fallback_headers", + "litellm.router_utils.clientside_credential_handler", + "litellm.router_utils.common_utils", + "litellm.router_utils.cooldown_handlers", + "litellm.router_utils.deployment_pricing", + "litellm.router_utils.fallback_event_handlers", + "litellm.router_utils.get_retry_from_policy", + "litellm.router_utils.health_state_cache", + "litellm.router_utils.pattern_match_deployments", + "litellm.router_utils.ptu_shares", + "litellm.router_utils.reasoning_effort_capability", + "litellm.router_utils.router_callbacks.track_deployment_metrics", + "litellm.router_utils.routing_groups", + "litellm.router_utils.search_api_router" + ] +} diff --git a/tests/code_coverage_tests/router_surface_check.py b/tests/code_coverage_tests/router_surface_check.py new file mode 100644 index 00000000000..0b35bac5240 --- /dev/null +++ b/tests/code_coverage_tests/router_surface_check.py @@ -0,0 +1,235 @@ +""" +Fence for the Router's public surface. + +Code outside the router may use only the Router members listed in +router_surface_allowlist.json, and may import only the litellm.router_utils +modules listed there. The lists hold what is used today and may only shrink: + +- a member or module used outside the router that is not listed fails the + check (use an existing entry point instead, or discuss widening the surface); +- a listed member or module that nothing outside the router uses any more + also fails, so the entry is removed in the same change. + +"Outside" means every non-test file under litellm/ and enterprise/ except +litellm/router.py and the router's own modules. Uses from the router family +(litellm/router_utils, litellm/router_strategy) are listed separately, because +those modules become private parts of the router core in a later step. + +Member uses are found the same way the boundary survey found them: attribute +access on a receiver whose name looks like a router (llm_router, +litellm_router_instance, router, ...) or on the Router class, plus +getattr/setattr/hasattr with a constant name on such a receiver. Members +include the container file endpoints Router.__init__ registers by name. + +Run: python tests/code_coverage_tests/router_surface_check.py [--write] +--write regenerates the allowlist from the current tree (for shrinking it). +""" + +import ast +import json +import os +import re +import sys +from typing import Dict, List, Set + +ROOT = os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "..")) +ALLOWLIST = os.path.join(os.path.dirname(__file__), "router_surface_allowlist.json") + +ROUTER_FILES = { + "litellm/router.py", +} +ROUTER_CLASS_FILES = ["litellm/router.py"] +ROUTER_CLASS_NAMES = {"Router"} + +SCAN_ROOTS = ["litellm", "enterprise"] +SKIP_DIRS = { + ".git", + "node_modules", + ".venv", + "__pycache__", + "litellm-rust", + "ui", + "docs", + "cookbook", + "tests", + "test", +} + +RECEIVER = re.compile( + r"(^|[._])(llm_router|router|litellm_router|litellm_router_instance|router_instance" + r"|_router|proxy_router|llm_router_instance|router_obj|mock_router|Router)$" +) +# Router.__init__ registers these with setattr(self, name, ...), so they never appear as self.. +CONTAINER_FILE_ENDPOINTS = "litellm/containers/endpoints.json" +DYNAMIC_FUNCS = {"getattr", "setattr", "hasattr"} + + +def _area(rel: str) -> str: + if rel.startswith(("litellm/router_utils/", "litellm/router_strategy/")): + return "router_family" + return "outside" + + +def _is_test(rel: str) -> bool: + name = os.path.basename(rel) + return "/tests/" in rel or name.startswith("test_") or name.endswith("_test.py") + + +def router_members() -> Set[str]: + members: Set[str] = set() + for rel in ROUTER_CLASS_FILES: + with open(os.path.join(ROOT, rel), encoding="utf-8") as f: + tree = ast.parse(f.read()) + for cls in tree.body: + if not isinstance(cls, ast.ClassDef) or cls.name not in ROUTER_CLASS_NAMES: + continue + for node in cls.body: + if isinstance(node, (ast.FunctionDef, ast.AsyncFunctionDef)): + members.add(node.name) + elif isinstance(node, ast.AnnAssign) and isinstance(node.target, ast.Name): + members.add(node.target.id) + elif isinstance(node, ast.Assign): + members.update(t.id for t in node.targets if isinstance(t, ast.Name)) + for node in ast.walk(cls): + if ( + isinstance(node, ast.Attribute) + and isinstance(node.value, ast.Name) + and node.value.id == "self" + and isinstance(node.ctx, ast.Store) + ): + members.add(node.attr) + with open(os.path.join(ROOT, CONTAINER_FILE_ENDPOINTS), encoding="utf-8") as f: + for endpoint in json.load(f)["endpoints"]: + members.update((endpoint["name"], endpoint["async_name"])) + return {m for m in members if not (m.startswith("__") and m.endswith("__"))} + + +def _python_files(): + for top in SCAN_ROOTS: + base = os.path.join(ROOT, top) + for dirpath, dirnames, filenames in os.walk(base): + dirnames[:] = [d for d in dirnames if d not in SKIP_DIRS] + for fn in filenames: + if fn.endswith(".py"): + path = os.path.join(dirpath, fn) + yield os.path.relpath(path, ROOT).replace(os.sep, "/"), path + + +def scan() -> Dict[str, Dict[str, Set[str]]]: + """Return {"members": {area: {member: files}}, "router_utils_imports": {module: files}}.""" + members = router_members() + uses: Dict[str, Dict[str, Set[str]]] = {"outside": {}, "router_family": {}} + imports: Dict[str, Set[str]] = {} + for rel, path in _python_files(): + if rel in ROUTER_FILES or _is_test(rel): + continue + with open(path, encoding="utf-8") as f: + src = f.read() + has_router = "router" in src.lower() + if not has_router: + continue + try: + tree = ast.parse(src) + except SyntaxError: + continue + area = _area(rel) + for name in member_uses(tree, members): + uses[area].setdefault(name, set()).add(rel) + if area == "outside": + for node in ast.walk(tree): + for mod in _router_utils_modules(node): + imports.setdefault(mod, set()).add(rel) + return {"members": uses, "router_utils_imports": imports} + + +def member_uses(tree: ast.AST, members: Set[str]) -> Set[str]: + """The Router members a module uses, on an instance or on the Router class itself.""" + used: Set[str] = set() + for node in ast.walk(tree): + if isinstance(node, ast.Attribute) and node.attr in members: + if RECEIVER.search(ast.unparse(node.value)): + used.add(node.attr) + elif ( + isinstance(node, ast.Call) + and isinstance(node.func, ast.Name) + and node.func.id in DYNAMIC_FUNCS + and len(node.args) >= 2 + and isinstance(node.args[1], ast.Constant) + and node.args[1].value in members + and RECEIVER.search(ast.unparse(node.args[0])) + ): + used.add(node.args[1].value) + return used + + +def _router_utils_modules(node: ast.AST) -> List[str]: + if isinstance(node, ast.ImportFrom) and node.module: + if node.module == "litellm.router_utils": + return ["litellm.router_utils." + a.name for a in node.names] + if node.module.startswith("litellm.router_utils."): + return [node.module] + if isinstance(node, ast.Import): + return [a.name for a in node.names if a.name.startswith("litellm.router_utils.")] + return [] + + +def build_allowlist(found) -> dict: + return { + "_doc": ( + "Router members and litellm.router_utils modules used outside the router. " + "Shrink-only: see tests/code_coverage_tests/router_surface_check.py." + ), + "members_outside": sorted(found["members"]["outside"]), + "members_router_family": sorted(found["members"]["router_family"]), + "router_utils_imports_outside": sorted(found["router_utils_imports"]), + } + + +def compare(allow: dict, found) -> List[str]: + errors: List[str] = [] + sections = [ + ("members_outside", found["members"]["outside"], "Router member"), + ("members_router_family", found["members"]["router_family"], "Router member (router family)"), + ("router_utils_imports_outside", found["router_utils_imports"], "litellm.router_utils import"), + ] + for key, used, what in sections: + listed = set(allow.get(key, [])) + for name in sorted(set(used) - listed): + files = ", ".join(sorted(used[name])) + errors.append( + f"new {what} outside the router: {name!r} in {files}. The router surface may only " + f"shrink: use an entry point instead." + ) + for name in sorted(listed - set(used)): + errors.append( + f"{what} {name!r} is listed in {os.path.basename(ALLOWLIST)} [{key}] but nothing uses it " + f"any more: remove it from the list." + ) + return errors + + +def main(argv: List[str]) -> int: + found = scan() + if "--write" in argv: + with open(ALLOWLIST, "w", encoding="utf-8") as f: + json.dump(build_allowlist(found), f, indent=2) + f.write("\n") + print(f"wrote {ALLOWLIST}") + return 0 + with open(ALLOWLIST, encoding="utf-8") as f: + allow = json.load(f) + errors = compare(allow, found) + for e in errors: + print(e) + if errors: + return 1 + print( + f"router surface ok: {len(allow['members_outside'])} members outside, " + f"{len(allow['members_router_family'])} from the router family, " + f"{len(allow['router_utils_imports_outside'])} router_utils modules imported outside" + ) + return 0 + + +if __name__ == "__main__": + sys.exit(main(sys.argv[1:])) diff --git a/tests/code_coverage_tests/unbounded_in_baseline.txt b/tests/code_coverage_tests/unbounded_in_baseline.txt index 1da964681a9..d8c6e2241f4 100644 --- a/tests/code_coverage_tests/unbounded_in_baseline.txt +++ b/tests/code_coverage_tests/unbounded_in_baseline.txt @@ -129,4 +129,4 @@ litellm/proxy/utils.py prefetch_config_params prisma param_name.in `param_names` litellm/repositories/daily_activity_repository.py DailyActivityRepository.daily_rows prisma [scope.entity_id_field].in `list(scope.entity_ids)` 0 litellm/repositories/daily_activity_repository.py DailyActivityRepository.daily_rows prisma api_key.in `list(scope.api_keys)` 0 litellm/repositories/daily_activity_repository.py DailyActivityRepository.daily_rows prisma not.in `list(scope.exclude_entity_ids)` 0 -litellm/router_utils/auto_router_model_naming.py raw-sql classifier_type.IN `IN ({_LLM_CLASSIFIER_TYPES_SQL})` 0 +litellm/router_strategy/auto_router/auto_router_model_naming.py raw-sql classifier_type.IN `IN ({_LLM_CLASSIFIER_TYPES_SQL})` 0 diff --git a/tests/e2e/coverage_registry/llm_conversational.yaml b/tests/e2e/coverage_registry/llm_conversational.yaml index c3c5330c440..0e450b08ebe 100644 --- a/tests/e2e/coverage_registry/llm_conversational.yaml +++ b/tests/e2e/coverage_registry/llm_conversational.yaml @@ -155,3 +155,4 @@ - {id: llm.responses.anthropic.basic.stream.works, module: llm, tier: P1, subject_endpoint: responses, route: anthropic, capability: basic, streaming: stream, assertions: [works], source: "llm_translation/test_conversational_matrix_e2e.py", rationale: "Anthropic over /v1/responses streams Responses events"} - {id: llm.responses.anthropic.basic.nonstream.cost_logged, module: llm, tier: P1, subject_endpoint: responses, route: anthropic, capability: basic, streaming: nonstream, assertions: [works, cost_logged], source: "llm_translation/test_conversational_matrix_e2e.py", rationale: "Anthropic over /v1/responses: cost header and spend row agree"} - {id: llm.responses.anthropic.multi_turn.nonstream.works, module: llm, tier: P1, subject_endpoint: responses, route: anthropic, capability: multi_turn, streaming: nonstream, assertions: [works], source: "llm_translation/test_conversational_matrix_e2e.py", rationale: "Anthropic function_call_output round trip over /v1/responses"} +- {id: llm.responses.anthropic.tool_search.nonstream.works, module: llm, tier: P1, subject_endpoint: responses, route: anthropic, capability: tool_search, streaming: nonstream, assertions: [works], source: "llm_translation/test_responses_codex_tool_search_e2e.py", rationale: "Codex client tool_search over /v1/responses finds and loads a deferred tool on Claude"} diff --git a/tests/e2e/llm_translation/test_responses_codex_tool_search_e2e.py b/tests/e2e/llm_translation/test_responses_codex_tool_search_e2e.py new file mode 100644 index 00000000000..79fd61e247a --- /dev/null +++ b/tests/e2e/llm_translation/test_responses_codex_tool_search_e2e.py @@ -0,0 +1,205 @@ +"""Live e2e: Codex's client tool_search over /v1/responses on Claude. + +Codex holds MCP tools back behind its client-executed `tool_search` tool when the model catalog says +`supports_search_tool`. Over the completion bridge the proxy offers that search to Claude as a plain function, +hands Claude's call back as a `tool_search_call` Codex runs itself, and loads the tools Codex returns in +`tool_search_output` so Claude can call them on the next turn +""" + +from __future__ import annotations + +from typing import Final + +import pytest +from e2e_config import unique_marker +from e2e_metadata import Capability, Domain, Mode, Provider, Route, Subject, meta +from lifecycle import ResourceManager +from models import LiteLLMParamsBody +from openai.types.responses import ( + FunctionToolParam, + Response, + ResponseFunctionToolCall, + ResponseInputParam, + ResponseToolSearchCall, + ToolParam, + ToolSearchToolParam, +) +from proxy_client import ProxyClient +from pydantic import BaseModel, ConfigDict +from sdk_clients import NO_PROXY_CACHE, SdkClients + +pytestmark = pytest.mark.e2e + +ANTHROPIC_BACKEND: Final = "anthropic/claude-haiku-5-5" +DEFERRED_TOOL_COUNT: Final = 50 +CALENDAR_TOOL_NAME: Final = "mcp__codex_apps__calendar_create_event" + +CODEX_TOOL_SEARCH: Final[ToolSearchToolParam] = { + "type": "tool_search", + "execution": "client", + "description": ( + "# Tool discovery\n\nSearches over deferred tool metadata with BM25 and exposes matching tools for the next " + "model call. Some of the tools may not have been provided to you upfront, and you should use this tool " + "(`tool_search`) to search for the required tools." + ), + "parameters": { + "type": "object", + "properties": { + "query": {"type": "string", "description": "Search query for deferred tools."}, + "limit": {"type": "number", "description": "Maximum number of tools to return. Defaults to 8."}, + }, + "required": ["query"], + "additionalProperties": False, + }, +} + +SHELL_TOOL: Final[FunctionToolParam] = { + "type": "function", + "name": "shell", + "description": "Runs a shell command.", + "parameters": {"type": "object", "properties": {"cmd": {"type": "string"}}, "required": ["cmd"]}, + "strict": False, +} + +CALENDAR_TOOL: Final[FunctionToolParam] = { + "type": "function", + "name": CALENDAR_TOOL_NAME, + "description": "Create a calendar event.", + "parameters": { + "type": "object", + "properties": {"title": {"type": "string"}}, + "required": ["title"], + "additionalProperties": False, + }, + "strict": False, + "defer_loading": True, +} + +PROMPT: Final = "Create a calendar event titled Standup. Find the calendar tool with tool_search first, then call it." + + +class _CalendarArguments(BaseModel): + model_config = ConfigDict(frozen=True) + + title: str + + +def _filler_tool(index: int) -> FunctionToolParam: + return { + "type": "function", + "name": f"mcp__codex_apps__records_{index:02d}", + "description": f"List, inspect, update and archive records of family {index} in the connected workspace.", + "parameters": { + "type": "object", + "properties": { + "title": {"type": "string", "description": "Title of the record to act on"}, + "notes": {"type": "string", "description": "Free-form notes and context for the operation"}, + "tags": {"type": "array", "items": {"type": "string"}}, + "priority": {"type": "integer", "minimum": 0, "maximum": 5}, + }, + "required": ["title"], + "additionalProperties": False, + }, + "strict": False, + "defer_loading": True, + } + + +DEFERRED_TOOLS: Final[tuple[FunctionToolParam, ...]] = ( + *(_filler_tool(index) for index in range(DEFERRED_TOOL_COUNT - 1)), + CALENDAR_TOOL, +) + + +def _eager(tool: FunctionToolParam) -> ToolParam: + return FunctionToolParam( + type="function", + name=tool["name"], + description=tool.get("description"), + parameters=tool.get("parameters"), + strict=False, + ) + + +def _input_tokens(response: Response) -> int: + assert response.usage is not None, f"response carried no usage: {response.id}" + return response.usage.input_tokens + + +def _search_call(response: Response) -> ResponseToolSearchCall: + calls: Final = tuple(item for item in response.output if isinstance(item, ResponseToolSearchCall)) + assert len(calls) == 1, f"expected one tool_search_call, got {response.output!r}" + return calls[0] + + +class TestResponsesCodexToolSearchOverAnthropic: + @pytest.mark.covers("llm.responses.anthropic.tool_search.nonstream.works") + @meta( + Subject( + domain=Domain.LLM_TRANSLATION, + route=Route.RESPONSES, + providers=(Provider.ANTHROPIC,), + models=(ANTHROPIC_BACKEND,), + capabilities=(Capability.TOOL_SEARCH, Capability.FUNCTION_CALLING), + mode=Mode.NONSTREAM, + ) + ) + def test_claude_finds_a_deferred_tool_through_codex_tool_search_and_calls_it( + self, proxy: ProxyClient, resources: ResourceManager, sdk: SdkClients + ) -> None: + model: Final = f"e2e-codex-tool-search-{unique_marker()}" + model_id: Final = proxy.create_model( + model, LiteLLMParamsBody(model=ANTHROPIC_BACKEND, api_key="os.environ/ANTHROPIC_API_KEY") + ) + resources.defer(lambda: proxy.delete_model(model_id)) + client: Final = sdk.openai(resources.key()) + searchable_tools: Final[list[ToolParam]] = [SHELL_TOOL, CODEX_TOOL_SEARCH] + + eager: Final = client.responses.create( + model=model, + input=PROMPT, + tools=[SHELL_TOOL, *(_eager(tool) for tool in DEFERRED_TOOLS)], + extra_body=NO_PROXY_CACHE, + ) + first: Final = client.responses.create( + model=model, input=PROMPT, tools=searchable_tools, extra_body=NO_PROXY_CACHE + ) + + search: Final = _search_call(first) + assert search.execution == "client", f"tool_search ran on the wrong side: {search!r}" + assert search.call_id, f"tool_search_call had no call_id: {search!r}" + assert not any(isinstance(item, ResponseFunctionToolCall) for item in first.output), first.output + assert _input_tokens(first) * 4 < _input_tokens(eager), ( + f"deferred first turn used {_input_tokens(first)} input tokens against {_input_tokens(eager)} eager" + ) + + follow_up: Final[ResponseInputParam] = [ + {"role": "user", "content": PROMPT}, + { + "type": "tool_search_call", + "call_id": search.call_id, + "execution": "client", + "arguments": search.arguments, + }, + { + "type": "tool_search_output", + "call_id": search.call_id, + "status": "completed", + "execution": "client", + "tools": [CALENDAR_TOOL], + }, + ] + second: Final = client.responses.create( + model=model, input=follow_up, tools=searchable_tools, extra_body=NO_PROXY_CACHE + ) + + calendar_call: Final = next( + ( + item + for item in second.output + if isinstance(item, ResponseFunctionToolCall) and item.name == CALENDAR_TOOL_NAME + ), + None, + ) + assert calendar_call is not None, f"Claude did not call the loaded tool: {second.output!r}" + assert "standup" in _CalendarArguments.model_validate_json(calendar_call.arguments).title.lower() diff --git a/tests/e2e/llm_translation/test_responses_e2e.py b/tests/e2e/llm_translation/test_responses_e2e.py index bb75569ad99..a0f185c4077 100644 --- a/tests/e2e/llm_translation/test_responses_e2e.py +++ b/tests/e2e/llm_translation/test_responses_e2e.py @@ -183,6 +183,48 @@ class TestResponses: ) assert response.output_text.strip(), f"/responses returned no output text: {response.output!r}" + @pytest.mark.covers("llm.responses.openai.basic.nonstream.works") + @meta( + Subject( + domain=Domain.LLM_TRANSLATION, + route=Route.RESPONSES, + providers=(Provider.OPENAI,), + models=(OPENAI_RESPONSES_BACKEND,), + mode=Mode.NONSTREAM, + ) + ) + def test_responses_forwards_moderation( + self, proxy: ProxyClient, resources: ResourceManager, sdk: SdkClients + ) -> None: + model: Final = _register(proxy, resources, _openai_responses_params()) + client: Final = sdk.openai(resources.key()) + + response: Final = client.responses.create( + model=model, + input="hi", + extra_body={**NO_PROXY_CACHE, "moderation": {"model": "omni-moderation-latest"}}, + ) + response_body: Final = TypeAdapter(dict[str, object]).validate_python(cast(object, response.model_dump())) + moderation_value: Final = response_body.get("moderation") + assert moderation_value is not None, f"response had no moderation results: {response_body!r}" + moderation: Final = TypeAdapter(dict[str, object]).validate_python(moderation_value) + moderation_input: Final = TypeAdapter(dict[str, object]).validate_python(moderation["input"]) + moderation_output: Final = TypeAdapter(dict[str, object]).validate_python(moderation["output"]) + assert moderation_input.get("type") == "moderation_result", ( + f"unexpected input moderation: {moderation_input!r}" + ) + assert ( + moderation_output.get("type") == "moderation_result" + ), f"unexpected output moderation: {moderation_output!r}" + + with pytest.raises(openai.BadRequestError) as exc_info: + client.responses.create( + model=model, + input="hi", + extra_body={**NO_PROXY_CACHE, "moderation": {"model": "does-not-exist"}}, + ) + assert exc_info.value.status_code == 400 + @pytest.mark.covers("llm.responses.openai.basic.stream.works") @meta( Subject( diff --git a/tests/integration/AGENTS.md b/tests/integration/AGENTS.md index a727b20596c..5bdc538b2d9 100644 --- a/tests/integration/AGENTS.md +++ b/tests/integration/AGENTS.md @@ -37,3 +37,14 @@ together with its dedicated job, and list a new dedicated GitHub workflow with t `DEDICATED_INTEGRATION_WORKFLOWS` in `.github/scripts/assert_ci_coverage.py`. The `ci-coverage` check fails a file here that a GitHub workflow runs unless it is in `GITHUB_FILES` and that workflow owns its directory (#46780) + +## Fixtures that boot a proxy + +Scope them to the module or class, or pin a session one to a single worker with an `xdist_group` mark +as `_llm_gateway` in `mcp/test_mcp_llm_endpoints.py` does, and request them as arguments, never through +`request.getfixturevalue`. The harness puts tests that request the same set of module or class fixtures +on one xdist worker, so the proxy they share boots there once and stops when that worker moves to another +file. A test that requests one more of those fixtures than its neighbors gets its own group and can boot +the proxy again on another worker, so keep that set the same across the tests that share a proxy. An +unpinned session fixture boots a copy on every worker that runs one of its tests and keeps them all until +the node ends, and those copies ran CircleCI integration-extensions nodes out of memory diff --git a/tests/integration/_support/device_login.py b/tests/integration/_support/device_login.py index 9b990fd2167..55519678f40 100644 --- a/tests/integration/_support/device_login.py +++ b/tests/integration/_support/device_login.py @@ -73,6 +73,7 @@ COPILOT_USER_CODE: Final = "COPI-LEAK" COPILOT_ACCESS: Final = "device-login-github-access" COPILOT_REJECTED_ACCESS: Final = "device-login-github-access-rejected" COPILOT_FIRST_LOGIN_ACCESS: Final = "device-login-github-access-first-login" +COPILOT_UNSAVED_KEY_ACCESS: Final = "device-login-github-access-unsaved-key" COPILOT_STORED_KEY: Final = "tid=device-login;stored" COPILOT_MINTED_KEY: Final = "tid=device-login;minted" COPILOT_REJECTED_KEY: Final = "tid=device-login;rejected" @@ -132,7 +133,11 @@ def _oauth_token(request: Request, grant: threading.Event) -> Reply: def _copilot_api_key(request: Request, api_url: str) -> Reply: - if request.headers.get("authorization") not in (f"token {COPILOT_ACCESS}", f"token {COPILOT_FIRST_LOGIN_ACCESS}"): + if request.headers.get("authorization") not in ( + f"token {COPILOT_ACCESS}", + f"token {COPILOT_FIRST_LOGIN_ACCESS}", + f"token {COPILOT_UNSAVED_KEY_ACCESS}", + ): return _json(401, {"message": "Bad credentials"}) return _json( 200, @@ -380,4 +385,7 @@ def write_copilot_access(directory: Path, access_token: str) -> None: def clear_tokens(*directories: Path) -> None: for directory in directories: for path in directory.iterdir(): - path.unlink() + if path.is_dir(): + path.rmdir() + else: + path.unlink() diff --git a/tests/integration/_support/responses_replay.py b/tests/integration/_support/responses_replay.py new file mode 100644 index 00000000000..c4e73ffbf2b --- /dev/null +++ b/tests/integration/_support/responses_replay.py @@ -0,0 +1,214 @@ +import json +import uuid +from collections.abc import Callable, Sequence +from itertools import chain +from typing import Final + +from integration._support.client import list_value, object_value +from integration._support.wire import Reply, Request, Wire +from pydantic import JsonValue + +MODEL: Final = "gpt-6.1-sol" +PLAN: Final = "I am starting by choosing which city to check." +PICK: Final = "My pick is Tokyo, so I will check its weather." +PATCH_NOTE: Final = "I will create hello.txt containing hi." +ANSWER: Final = "It is raining in Tokyo." + +WEATHER_TOOL: Final[dict[str, JsonValue]] = { + "type": "function", + "function": { + "name": "get_weather", + "description": "Get the weather for a city.", + "parameters": {"type": "object", "properties": {"city": {"type": "string"}}, "required": ["city"]}, + }, +} +PATCH_TOOL: Final[dict[str, JsonValue]] = { + "type": "custom", + "custom": {"name": "apply_patch", "description": "Apply a V4A patch to the workspace"}, +} + + +def _message(item_id: str, text: str, phase: str) -> dict[str, JsonValue]: + return { + "type": "message", + "id": item_id, + "status": "completed", + "role": "assistant", + "phase": phase, + "content": [{"type": "output_text", "text": text, "annotations": []}], + } + + +def _reasoning(item_id: str, summary: str) -> dict[str, JsonValue]: + return { + "type": "reasoning", + "id": item_id, + "summary": [{"type": "summary_text", "text": summary}], + "encrypted_content": f"enc_{item_id}", + } + + +_WEATHER_CALL: Final[dict[str, JsonValue]] = { + "type": "function_call", + "id": "fc_weather", + "call_id": "call_weather", + "name": "get_weather", + "arguments": '{"city":"Tokyo"}', + "status": "completed", +} +WEATHER_TURN: Final[tuple[dict[str, JsonValue], ...]] = ( + _message("msg_plan", PLAN, "commentary"), + _reasoning("rs_pick", "Tokyo is often rainy this time of year."), + _message("msg_pick", PICK, "commentary"), + _WEATHER_CALL, +) +TWO_THOUGHTS_TURN: Final[tuple[dict[str, JsonValue], ...]] = ( + _reasoning("rs_scan", "Paris and Tokyo are the two candidates."), + _reasoning("rs_pick", "Tokyo is often rainy this time of year."), + _message("msg_pick", PICK, "commentary"), + _WEATHER_CALL, +) +CALL_ONLY_TURN: Final[tuple[dict[str, JsonValue], ...]] = (_WEATHER_CALL,) +PATCH_TURN: Final[tuple[dict[str, JsonValue], ...]] = ( + _message("msg_patch", PATCH_NOTE, "commentary"), + { + "type": "custom_tool_call", + "id": "ctc_patch", + "call_id": "call_patch", + "name": "apply_patch", + "input": "*** Begin Patch\n*** Add File: hello.txt\n+hi\n*** End Patch", + "status": "completed", + }, +) +WEATHER_REPLAY: Final = ( + ("message", "assistant", "commentary", PLAN), + ("reasoning", "rs_pick"), + ("message", "assistant", "commentary", PICK), + ("function_call", "call_weather", "get_weather"), + ("function_call_output", "call_weather"), +) +TWO_THOUGHTS_REPLAY: Final = ( + ("reasoning", "rs_scan"), + ("reasoning", "rs_pick"), + ("message", "assistant", "commentary", PICK), + ("function_call", "call_weather", "get_weather"), + ("function_call_output", "call_weather"), +) + + +def _response(identity: str, output: Sequence[dict[str, JsonValue]]) -> dict[str, JsonValue]: + return { + "id": f"resp_{identity}", + "object": "response", + "created_at": 1789788253, + "status": "completed", + "model": MODEL, + "output": list(output), + "usage": {"input_tokens": 10, "output_tokens": 5, "total_tokens": 15}, + } + + +def _event(payload: dict[str, JsonValue]) -> bytes: + return f"event: {payload['type']}\ndata: {json.dumps(payload)}\n\n".encode() + + +def _opened(item: dict[str, JsonValue]) -> dict[str, JsonValue]: + match item["type"]: + case "message": + return {**item, "status": "in_progress", "content": []} + case "function_call": + return {**item, "status": "in_progress", "arguments": ""} + case _: + return item + + +def _deltas(index: int, item: dict[str, JsonValue]) -> tuple[dict[str, JsonValue], ...]: + match item["type"]: + case "message": + text: Final = object_value(list_value(item["content"])[0])["text"] + return ( + { + "type": "response.output_text.delta", + "item_id": item["id"], + "output_index": index, + "content_index": 0, + "delta": text, + }, + ) + case "function_call": + return ( + { + "type": "response.function_call_arguments.delta", + "item_id": item["id"], + "output_index": index, + "delta": item["arguments"], + }, + ) + case _: + return () + + +def _item_events(index: int, item: dict[str, JsonValue]) -> tuple[bytes, ...]: + return ( + _event({"type": "response.output_item.added", "output_index": index, "item": _opened(item)}), + *(_event(delta) for delta in _deltas(index, item)), + _event({"type": "response.output_item.done", "output_index": index, "item": item}), + ) + + +def _stream(identity: str, output: Sequence[dict[str, JsonValue]]) -> tuple[bytes, ...]: + response: Final = _response(identity, output) + return ( + _event({"type": "response.created", "response": {**response, "status": "in_progress", "output": []}}), + *chain.from_iterable(_item_events(index, item) for index, item in enumerate(output)), + _event({"type": "response.completed", "response": response}), + ) + + +def _answered(body: dict[str, JsonValue]) -> bool: + return any( + object_value(item).get("type") in {"function_call_output", "custom_tool_call_output"} + for item in list_value(body["input"]) + ) + + +def responses_upstream(turn_one: Sequence[dict[str, JsonValue]]) -> Callable[[Request], Reply]: + def respond(request: Request) -> Reply: + if request.method == "GET": + return Reply(body=b'{"object":"list","data":[]}') + assert request.target == "/responses", request.target + body: Final = object_value(json.loads(request.body)) + identity: Final = uuid.uuid4().hex + output: Final = (_message("msg_answer", ANSWER, "final_answer"),) if _answered(body) else turn_one + if body.get("stream"): + return Reply(content_type="text/event-stream", chunks=_stream(identity, output)) + return Reply(body=json.dumps(_response(identity, output)).encode()) + + return respond + + +def _text(content: JsonValue) -> JsonValue: + if isinstance(content, str): + return content + return "".join(str(object_value(part).get("text")) for part in list_value(content)) + + +def _shape(item: JsonValue) -> tuple[JsonValue, ...]: + fields: Final = object_value(item) + match fields.get("type"): + case "message": + return ("message", fields.get("role"), fields.get("phase"), _text(fields.get("content"))) + case "reasoning": + return ("reasoning", fields.get("id")) + case "function_call" | "custom_tool_call" as kind: + return (kind, fields.get("call_id"), fields.get("name")) + case kind: + return (kind, fields.get("call_id")) + + +def posted_inputs(wire: Wire) -> tuple[tuple[tuple[JsonValue, ...], ...], ...]: + return tuple( + tuple(_shape(item) for item in list_value(object_value(json.loads(request.body))["input"])) + for request in wire.drain() + if request.method == "POST" + ) diff --git a/tests/integration/_support/riva.py b/tests/integration/_support/riva.py new file mode 100644 index 00000000000..8552bc2197d --- /dev/null +++ b/tests/integration/_support/riva.py @@ -0,0 +1,143 @@ +from __future__ import annotations + +import io +import threading +import wave +from array import array +from collections.abc import Iterable, Iterator +from concurrent import futures +from contextlib import contextmanager +from dataclasses import dataclass +from enum import Enum +from queue import SimpleQueue +from typing import Final + +import grpc +from riva.client.proto import riva_asr_pb2, riva_asr_pb2_grpc + +SAMPLE_RATE_HZ: Final = 16000 +OFFLINE_ONLY_REFUSAL: Final = ( + "Error: Unavailable model requested given these parameters: language_code=en-US; sample_rate=16000; type=online;" +) +_STALL_LIMIT_SECONDS: Final = 120 + + +class Rpc(Enum): + RECOGNIZE = "Recognize" + STREAMING = "StreamingRecognize" + + +@dataclass(frozen=True, slots=True) +class Word: + word: str + start_ms: int + end_ms: int + + +@dataclass(frozen=True, slots=True) +class RivaCall: + rpc: Rpc + audio: bytes + cancelled: bool + + +@dataclass(frozen=True, slots=True) +class RivaServer: + address: str + calls: SimpleQueue[RivaCall] + + def drain(self) -> tuple[RivaCall, ...]: + return tuple(self.calls.get_nowait() for _ in range(self.calls.qsize())) + + +def _clip_samples(seconds: float) -> array[int]: + return array("h", (((index * 37) % 2001 - 1000) * 16 for index in range(int(seconds * SAMPLE_RATE_HZ)))) + + +def pcm_wav(seconds: float) -> bytes: + buffer: Final = io.BytesIO() + with wave.open(buffer, "wb") as writer: + writer.setnchannels(1) + writer.setsampwidth(2) + writer.setframerate(SAMPLE_RATE_HZ) + writer.writeframes(_clip_samples(seconds).tobytes()) + return buffer.getvalue() + + +def pcm_bytes(seconds: float) -> int: + return int(seconds * SAMPLE_RATE_HZ) * 2 + + +def carries_clip(audio: bytes, seconds: float) -> bool: + sent: Final = _clip_samples(seconds) + if len(audio) != len(sent) * 2: + return False + received: Final = array("h", audio) + return all(abs(left - right) <= 1 for left, right in zip(sent, received, strict=True)) + + +class _Asr(riva_asr_pb2_grpc.RivaSpeechRecognitionServicer): + def __init__(self, words: tuple[Word, ...], offline_only: bool, stall: bool, calls: SimpleQueue[RivaCall]) -> None: + self._words: Final = words + self._offline_only: Final = offline_only + self._stall: Final = stall + self._calls: Final = calls + + def _alternative(self, config: riva_asr_pb2.RecognitionConfig) -> riva_asr_pb2.SpeechRecognitionAlternative: + timed: Final = self._words if config.enable_word_time_offsets else () + return riva_asr_pb2.SpeechRecognitionAlternative( + transcript=" ".join(word.word for word in self._words), + confidence=0.9, + words=[ + riva_asr_pb2.WordInfo(word=word.word, start_time=word.start_ms, end_time=word.end_ms) for word in timed + ], + ) + + def Recognize( + self, request: riva_asr_pb2.RecognizeRequest, context: grpc.ServicerContext + ) -> riva_asr_pb2.RecognizeResponse: + if self._stall: + released: Final = threading.Event() + context.add_callback(released.set) + released.wait(timeout=_STALL_LIMIT_SECONDS) + self._calls.put(RivaCall(Rpc.RECOGNIZE, request.audio, cancelled=not context.is_active())) + return riva_asr_pb2.RecognizeResponse() + self._calls.put(RivaCall(Rpc.RECOGNIZE, request.audio, cancelled=False)) + return riva_asr_pb2.RecognizeResponse( + results=[riva_asr_pb2.SpeechRecognitionResult(alternatives=[self._alternative(request.config)])] + ) + + def StreamingRecognize( + self, request_iterator: Iterable[riva_asr_pb2.StreamingRecognizeRequest], context: grpc.ServicerContext + ) -> Iterator[riva_asr_pb2.StreamingRecognizeResponse]: + if self._offline_only: + self._calls.put(RivaCall(Rpc.STREAMING, b"", cancelled=False)) + context.abort(grpc.StatusCode.INVALID_ARGUMENT, OFFLINE_ONLY_REFUSAL) + requests: Final = tuple(request_iterator) + config: Final = requests[0].streaming_config.config if requests else riva_asr_pb2.RecognitionConfig() + self._calls.put( + RivaCall(Rpc.STREAMING, b"".join(request.audio_content for request in requests), cancelled=False) + ) + yield riva_asr_pb2.StreamingRecognizeResponse( + results=[riva_asr_pb2.StreamingRecognitionResult(alternatives=[self._alternative(config)], is_final=True)] + ) + + +@contextmanager +def riva_server( + words: tuple[Word, ...], + *, + offline_only: bool = False, + stall: bool = False, + max_receive_bytes: int | None = None, +) -> Iterator[RivaServer]: + calls: Final[SimpleQueue[RivaCall]] = SimpleQueue() + options: Final = () if max_receive_bytes is None else (("grpc.max_receive_message_length", max_receive_bytes),) + server: Final = grpc.server(futures.ThreadPoolExecutor(max_workers=8), options=options) + riva_asr_pb2_grpc.add_RivaSpeechRecognitionServicer_to_server(_Asr(words, offline_only, stall, calls), server) + port: Final = server.add_insecure_port("127.0.0.1:0") + server.start() + try: + yield RivaServer(f"127.0.0.1:{port}", calls) + finally: + server.stop(grace=None).wait() diff --git a/tests/integration/_support/wire.py b/tests/integration/_support/wire.py index df6036ff8d7..e278a796146 100644 --- a/tests/integration/_support/wire.py +++ b/tests/integration/_support/wire.py @@ -19,6 +19,7 @@ class Request: target: str headers: Mapping[str, str] body: bytes + header_lines: tuple[tuple[str, str], ...] = () class AbortedBody(Exception): @@ -136,7 +137,7 @@ def wire_server( self.close_connection = True disconnected.put(self.path) return - request: Final = Request(self.command, self.path, headers, body) + request: Final = Request(self.command, self.path, headers, body, tuple(self.headers.items())) received.put(request) try: reply = respond(request) diff --git a/tests/integration/authorization/test_agent_least_privilege.py b/tests/integration/authorization/test_agent_least_privilege.py index 498a53c3ca9..d993920a32e 100644 --- a/tests/integration/authorization/test_agent_least_privilege.py +++ b/tests/integration/authorization/test_agent_least_privilege.py @@ -313,7 +313,7 @@ def test_agent_access_default_deny_toggles_at_runtime_through_config_api( for field in config_fields.json() if object_value(field)["field_name"] == "agent_access_default_deny" ) - assert setting["field_type"] == "Boolean" and setting["field_value"] == "true", setting + assert setting["field_type"] == "Boolean" and setting["field_value"] is True, setting eventually( lambda: tuple(_card(candidate, agent_id, ungranted_key) for _ in range(8)), lambda responses: all(response.status_code == 403 for response in responses), diff --git a/tests/integration/authorization/test_claude_code_gateway_oauth.py b/tests/integration/authorization/test_claude_code_gateway_oauth.py index a80eeacad46..4dedbdcd8e4 100644 --- a/tests/integration/authorization/test_claude_code_gateway_oauth.py +++ b/tests/integration/authorization/test_claude_code_gateway_oauth.py @@ -545,3 +545,94 @@ def test_device_authorization_polls_complete_sso_and_mints_a_model_restricted_be assert set(token_form) == {"code", "code_verifier", "grant_type", "redirect_uri"}, token_form assert userinfo_request.method == "GET" and urlsplit(userinfo_request.target).path == "/userinfo" assert user_id == _USER_ID + + +_TEAM_OPTION: Final = re.compile(r'
setServerSearch(e.target.value)} + placeholder="Search tools or servers..." + aria-label="Search tools or servers" + value={search} + onChange={(e) => setSearch(e.target.value)} /> - {serverSearch && ( + {search && ( - setServerSearch("")}> + setSearch("")}> )} + {searchActive && ( +
+

+ {matchingTools.length} matching {matchingTools.length === 1 ? "tool" : "tools"} + {pendingServerCount > 0 && + ` · loading ${pendingServerCount} ${pendingServerCount === 1 ? "server" : "servers"}…`} +

+
+ + +
+
+ )}
- {filteredServers.length === 0 ? ( + {serverViews.length === 0 ? (

- {mcpServers.length === 0 ? "No MCP servers configured" : "No servers match your search"} + {mcpServers.length === 0 ? "No MCP servers configured" : "No tools or servers match your search"}

) : ( - filteredServers.map((server) => ( - ( + handleToggleExpanded(server.server_id)} + onToggleTool={handleToggleTool} + onSetToolsSelected={handleSetToolsSelected} /> )) )} @@ -266,41 +412,60 @@ function CreateToolsetModal({ open, onClose, onSave, accessToken, initialToolset {/* Right panel: Your Toolset */}
-

- Your Toolset{" "} - ({selectedTools.length} tools) -

+
+

+ Your Toolset{" "} + ({selectedTools.length} tools) +

+ +
{selectedTools.length === 0 ? (

No tools added yet

) : ( - selectedTools.map((tool, idx) => ( -
- - ✕ - - - )) + + ); + }) )}
-
- ↵ Open + ↵ Open - ↑↓ Navigate + ↑↓ Navigate - esc Close + esc Close
diff --git a/ui/litellm-dashboard/src/components/CommandPalette/CommandPaletteHint.tsx b/ui/litellm-dashboard/src/components/CommandPalette/CommandPaletteHint.tsx index 0a4c3fcda18..6fa362f4509 100644 --- a/ui/litellm-dashboard/src/components/CommandPalette/CommandPaletteHint.tsx +++ b/ui/litellm-dashboard/src/components/CommandPalette/CommandPaletteHint.tsx @@ -2,6 +2,7 @@ import { Search, X } from "lucide-react"; import { z } from "zod"; +import { Kbd } from "@/components/ui/kbd"; import { storageKey } from "@/lib/storage"; import type { PaletteScope } from "./utils"; import { useCommandPalette } from "./CommandPaletteProvider"; @@ -26,9 +27,7 @@ export function CommandPaletteHint({ scope, onDismiss }: CommandPaletteHintProps ); } diff --git a/ui/litellm-dashboard/src/components/add_model/ComplexityRouterConfig.tsx b/ui/litellm-dashboard/src/components/add_model/ComplexityRouterConfig.tsx index b59aa051e38..ac13af14a6b 100644 --- a/ui/litellm-dashboard/src/components/add_model/ComplexityRouterConfig.tsx +++ b/ui/litellm-dashboard/src/components/add_model/ComplexityRouterConfig.tsx @@ -37,6 +37,7 @@ import { } from "./tier_rows"; import React from "react"; import { ModelGroup } from "@/components/llm_calls/fetch_models"; +import { routingModelGroups } from "./auto_setup"; import ClassificationMethodConfig, { InactiveHeuristicV2Threshold } from "./ClassificationMethodConfig"; import ComplexityRouterAdvancedSections from "./ComplexityRouterAdvancedSections"; import { type TierSetAction, applyTierSetAction, setFallbackTier } from "./tier_set_actions"; @@ -657,13 +658,10 @@ const ComplexityRouterConfig: React.FC = ({ ); const classifierEffortOptionsByModel = classifierEffortOptionsForModels(modelInfo); - // Embedding models can't serve a chat-completion role, so they're excluded here. - const modelOptions = modelInfo - .filter((model) => model.mode !== "embedding") - .map((model) => ({ - value: model.model_group, - label: model.model_group, - })); + const modelOptions = routingModelGroups(modelInfo).map((model) => ({ + value: model.model_group, + label: model.model_group, + })); const handleTierModelParamChange = (tier: string, model: string, change: TierModelParamChange) => onChange({ diff --git a/ui/litellm-dashboard/src/components/add_model/add_auto_router_tab.integration.test.tsx b/ui/litellm-dashboard/src/components/add_model/add_auto_router_tab.integration.test.tsx index 52c4e9093a4..78782e755ac 100644 --- a/ui/litellm-dashboard/src/components/add_model/add_auto_router_tab.integration.test.tsx +++ b/ui/litellm-dashboard/src/components/add_model/add_auto_router_tab.integration.test.tsx @@ -319,6 +319,27 @@ describe("AddAutoRouterTab", () => { }, ); + it("carries Responses model choices from simple setup into Advanced tiers", async () => { + const models = ["gpt-6-luna", "gpt-6-astra"]; + mockFetchAvailableModels.mockResolvedValue(models.map((model_group) => ({ model_group, mode: "responses" }))); + mockFetchAllModelDeployments.mockResolvedValue( + models.map((model_name) => ({ + model_name, + litellm_params: { model: `chatgpt/${model_name}` }, + model_info: { mode: "responses" }, + })), + ); + renderWithProviders(); + await waitFor(() => + expect(screen.getByRole("combobox", { name: "Everyday model" })).toHaveTextContent("gpt-6-luna"), + ); + expect(screen.getByRole("combobox", { name: "Hard tasks model" })).toHaveTextContent("gpt-6-astra"); + expect(screen.queryByText(/Two deployed models are needed/)).not.toBeInTheDocument(); + fireEvent.click(screen.getByRole("button", { name: "Advanced configuration", exact: true })); + expectTierModel("Simple", "gpt-6-luna"); + expectTierModel("Reasoning", "gpt-6-astra"); + }); + it("keeps manual solver choices on goal changes and carries them into Advanced", async () => { mockFetchAvailableModels.mockResolvedValue( ["claude-haiku-5-5", "custom-fast", "claude-opus-5-5"].map((model_group) => ({ diff --git a/ui/litellm-dashboard/src/components/add_model/auto_setup.test.ts b/ui/litellm-dashboard/src/components/add_model/auto_setup.test.ts index 4097afc17fe..c0d4931873f 100644 --- a/ui/litellm-dashboard/src/components/add_model/auto_setup.test.ts +++ b/ui/litellm-dashboard/src/components/add_model/auto_setup.test.ts @@ -7,6 +7,7 @@ import { solverPairConfig, nextRouterName, simpleSetupError, + routingModelGroups, } from "./auto_setup"; const deployment = (name: string, model: string, extra: Partial = {}): AutoRouterDeployment => ({ @@ -76,7 +77,7 @@ describe("deployedRouterModels", () => { ]); }); - it("uses only caller-visible chat models and excludes blocked and recursive targets", () => { + it("matches Advanced choices while keeping blocked and recursive targets out of suggestions", () => { const rows = [ deployment("hidden", "anthropic/claude-opus-6"), deployment("blocked", "anthropic/claude-opus-5", { model_info: { blocked: true } }), @@ -94,9 +95,40 @@ describe("deployedRouterModels", () => { ], rows, ).map((model) => model.name), - ).toEqual(["ready"]); + ).toEqual(["blocked", "ready", "recursive"]); + expect( + recommendSolverPair( + deployedRouterModels( + rows + .filter((row) => row.model_name !== "hidden" && row.model_name !== "embedding") + .map((row) => ({ model_group: row.model_name! })), + rows, + ), + "balanced", + "auto", + ), + ).toBeNull(); }); + it.each(["chat", "responses", "completion", "unknown", undefined])( + "offers the same routing choices as Advanced for mode %s", + (mode) => { + const groups = [ + { model_group: "everyday", mode }, + { model_group: "hard", mode }, + { model_group: "embedding", mode: "embedding" }, + ]; + const rows = [ + deployment("everyday", "chatgpt/gpt-6-luna", { model_info: { mode } }), + deployment("hard", "chatgpt/gpt-6-astra", { model_info: { mode } }), + ]; + const models = deployedRouterModels(groups, rows); + expect(models.map((model) => model.name)).toEqual(routingModelGroups(groups).map((group) => group.model_group)); + expect(models.map((model) => model.name)).toEqual(["everyday", "hard"]); + expect(names(recommendSolverPair(models, "balanced", "openai"))).toEqual(["everyday", "hard"]); + }, + ); + it("does not claim a mixed-version or unknown model group is a known version", () => { const rows = [ deployment("mixed", "anthropic/claude-opus-5"), @@ -112,7 +144,7 @@ describe("deployedRouterModels", () => { ], rows, ); - expect(models.map((model) => model.name)).toEqual(["claude-sonnet-5", "mixed"]); + expect(models.map((model) => model.name)).toEqual(["claude-sonnet-5", "mixed", "wildcard"]); expect(models.every((model) => model.family === undefined)).toBe(true); expect(recommendSolverPair(models, "balanced", "auto")).toBeNull(); }); diff --git a/ui/litellm-dashboard/src/components/add_model/auto_setup.ts b/ui/litellm-dashboard/src/components/add_model/auto_setup.ts index 39476470928..eb21e17c265 100644 --- a/ui/litellm-dashboard/src/components/add_model/auto_setup.ts +++ b/ui/litellm-dashboard/src/components/add_model/auto_setup.ts @@ -146,24 +146,21 @@ const compareVersion = (left: readonly number[], right: readonly number[]): numb const compareRelease = (left: ModelIdentity, right: ModelIdentity): number => compareVersion(left.version, right.version) || left.snapshot - right.snapshot; +export const routingModelGroups = (groups: readonly ModelGroup[]): ModelGroup[] => + groups.filter((group) => group.mode !== "embedding"); + export const deployedRouterModels = ( groups: readonly ModelGroup[], deployments: readonly AutoRouterDeployment[], ): SolverModel[] => - groups - .flatMap((group) => { - if (group.mode && group.mode !== "chat") return []; + routingModelGroups(groups) + .map((group) => { const rows = deployments.filter((row) => row.model_name === group.model_group); - if ( - rows.some(isAutoRouterDeployment) || - group.model_group.includes("*") || - group.model_group.startsWith("auto_router/") - ) - return []; const active = rows.filter((row) => !row.model_info?.blocked); - if (rows.length > 0 && active.length === 0) return []; - if (active.some((row) => row.model_info?.mode && row.model_info.mode !== "chat")) return []; - if (active.some((row) => row.litellm_params?.model?.includes("*"))) return []; + const isRouter = rows.some(isAutoRouterDeployment) || group.model_group.startsWith("auto_router/"); + const hasWildcard = + group.model_group.includes("*") || active.some((row) => row.litellm_params?.model?.includes("*")); + const manualOnly = isRouter || hasWildcard || (rows.length > 0 && active.length === 0); const identities = active.length > 0 ? active.map(identityOf) : [parseModel(group.model_group)]; const first = identities[0]; const homogeneous = @@ -173,19 +170,17 @@ export const deployedRouterModels = ( const sameLine = identity.family === first.family && identity.line === first.line; return sameLine && compareRelease(identity, first) === 0; }); - const identity = homogeneous ? first : undefined; + const identity = homogeneous && !manualOnly ? first : undefined; const providers = active.length > 0 ? active.map((row) => providerOf(row, group, identity?.family)) : [providerOf({}, group, identity?.family)]; - return [ - { - ...identity, - name: group.model_group, - model: identity?.model ?? group.model_group, - provider: [...new Set(providers)].toSorted().join(", "), - }, - ]; + return { + ...identity, + name: group.model_group, + model: identity?.model ?? group.model_group, + provider: [...new Set(providers)].toSorted().join(", "), + }; }) .toSorted((a, b) => a.name.localeCompare(b.name)); diff --git a/ui/litellm-dashboard/src/components/key_team_helpers/ModelMaxBudgetEditor.integration.test.tsx b/ui/litellm-dashboard/src/components/key_team_helpers/ModelMaxBudgetEditor.integration.test.tsx index 33f09092cca..955b911ca97 100644 --- a/ui/litellm-dashboard/src/components/key_team_helpers/ModelMaxBudgetEditor.integration.test.tsx +++ b/ui/litellm-dashboard/src/components/key_team_helpers/ModelMaxBudgetEditor.integration.test.tsx @@ -1,5 +1,6 @@ +import userEvent from "@testing-library/user-event"; import { describe, expect, it, vi } from "vitest"; -import { renderWithProviders, screen } from "../../../tests/test-utils"; +import { fireEvent, renderWithProviders, screen } from "../../../tests/test-utils"; import { MODEL_MAX_BUDGET_PREMIUM_HINT, ModelMaxBudgetEditor, type ModelMaxBudget } from "./ModelMaxBudgetEditor"; const STORED: ModelMaxBudget = { "gpt-4o": { budget_limit: 5, time_period: "30d" } }; @@ -67,3 +68,65 @@ describe("ModelMaxBudgetEditor with an enterprise license", () => { expect(addButton()).toBeEnabled(); }); }); + +describe("ModelMaxBudgetEditor model families", () => { + it("stores a typed pattern that matches no listed model as one budget entry", async () => { + const user = userEvent.setup(); + const onChange = vi.fn(); + renderWithProviders( + , + ); + + await user.click(addButton()); + const modelField = screen.getByPlaceholderText("Select model"); + await user.type(modelField, "claude-opus*"); + await user.click(await screen.findByRole("option", { name: /claude-opus\*/ })); + fireEvent.change(screen.getByPlaceholderText("Max spend ($)"), { target: { value: "10" } }); + + expect(onChange).toHaveBeenLastCalledWith({ "claude-opus*": { budget_limit: 10, time_period: "30d" } }); + }); + + it("does not offer a typed pattern that another row already budgets", async () => { + const user = userEvent.setup(); + renderWithProviders( + , + ); + + await user.click(addButton()); + const [, newRowModelField] = screen.getAllByPlaceholderText("Select model"); + await user.type(newRowModelField, "claude-opus*"); + + expect(screen.queryByRole("option", { name: /claude-opus\*/ })).not.toBeInTheDocument(); + await user.clear(newRowModelField); + await user.type(newRowModelField, "claude-sonnet*"); + expect(await screen.findByRole("option", { name: /claude-sonnet\*/ })).toBeInTheDocument(); + }); + + it("does not offer a typed name that is neither listed nor a pattern", async () => { + const user = userEvent.setup(); + renderWithProviders( + , + ); + + await user.click(addButton()); + await user.type(screen.getByPlaceholderText("Select model"), "claude-opsu-4-8"); + + expect(screen.queryByRole("option", { name: /claude-opsu-4-8/ })).not.toBeInTheDocument(); + expect(screen.getByText("No models found")).toBeInTheDocument(); + }); +}); diff --git a/ui/litellm-dashboard/src/components/key_team_helpers/ModelMaxBudgetEditor.tsx b/ui/litellm-dashboard/src/components/key_team_helpers/ModelMaxBudgetEditor.tsx index a6e72068463..02fc022e881 100644 --- a/ui/litellm-dashboard/src/components/key_team_helpers/ModelMaxBudgetEditor.tsx +++ b/ui/litellm-dashboard/src/components/key_team_helpers/ModelMaxBudgetEditor.tsx @@ -50,6 +50,8 @@ export const MODEL_BUDGET_PERIOD_OPTIONS = [ const DEFAULT_PERIOD = "30d"; +const MODEL_PATTERN_VALUE = { hint: "Model pattern", accepts: (typed: string) => typed.includes("*") }; + export const entriesToModelMaxBudget = (entries: readonly ModelBudgetEntry[]): ModelMaxBudget => Object.fromEntries( entries @@ -121,7 +123,7 @@ export function ModelMaxBudgetEditor({ const blurb = (
{premiumUser - ? "Cap spend per model over its own window. A budget set on the bare model name also covers the provider-prefixed spelling of that model." + ? "Cap spend per model over its own window. A budget set on the bare model name also covers the provider-prefixed spelling of that model. Pick an access group, or type a pattern like claude-opus*, to share one budget across every model it covers." : MODEL_MAX_BUDGET_PREMIUM_HINT}
); @@ -165,6 +167,8 @@ export function ModelMaxBudgetEditor({ onValueChange={(model) => updateEntry(entry.id, { model })} placeholder="Select model" emptyText="No models found" + customValue={MODEL_PATTERN_VALUE} + reservedValues={entries.flatMap((other) => (other.id !== entry.id && other.model ? [other.model] : []))} disabled={!premiumUser} /> diff --git a/ui/litellm-dashboard/src/components/liteadmin/AriaAvatar.test.tsx b/ui/litellm-dashboard/src/components/liteadmin/AriaAvatar.test.tsx new file mode 100644 index 00000000000..5c9cf27470e --- /dev/null +++ b/ui/litellm-dashboard/src/components/liteadmin/AriaAvatar.test.tsx @@ -0,0 +1,21 @@ +import { render, screen } from "@testing-library/react"; +import { afterEach, describe, expect, it } from "vitest"; +import { setServerRootPath } from "@/lib/serverRootPath"; +import { AriaAvatar } from "./AriaAvatar"; + +describe("AriaAvatar", () => { + afterEach(() => { + setServerRootPath("/"); + }); + + it.each(["/", "/litellm"])("loads the bundled image when the server root is %s", (root) => { + setServerRootPath(root); + + render(); + + expect(screen.getByRole("presentation", { hidden: true })).toHaveAttribute( + "src", + "/_next/static/media/aria-agent.png", + ); + }); +}); diff --git a/ui/litellm-dashboard/src/components/liteadmin/AriaAvatar.tsx b/ui/litellm-dashboard/src/components/liteadmin/AriaAvatar.tsx index 8c78908d3a9..e0f014624fe 100644 --- a/ui/litellm-dashboard/src/components/liteadmin/AriaAvatar.tsx +++ b/ui/litellm-dashboard/src/components/liteadmin/AriaAvatar.tsx @@ -1,10 +1,10 @@ -import { resolveLogoSrc } from "@/lib/assetPaths"; +import ariaAgentImage from "../../../public/assets/aria-agent.png"; import { cn } from "@/lib/cva.config"; export function AriaAvatar({ size = 28, className }: { size?: number; className?: string }) { return ( {ARIA_AGENT_LABEL} - ⌘J + ⌘J ); } diff --git a/ui/litellm-dashboard/src/components/llm_calls/responses_api.test.tsx b/ui/litellm-dashboard/src/components/llm_calls/responses_api.test.tsx index 47a1e3608c5..f9c5e3b0181 100644 --- a/ui/litellm-dashboard/src/components/llm_calls/responses_api.test.tsx +++ b/ui/litellm-dashboard/src/components/llm_calls/responses_api.test.tsx @@ -490,6 +490,137 @@ describe("responses_api", () => { }); }); +describe("responses_api reasoning", () => { + type Run = { reasoning: string; answer: string; timeToFirstToken: number[]; reasoningBeforeFirstToken: string }; + + const run = async (streamingEnabled: boolean): Promise => { + const reasoningChunks: string[] = []; + const answerChunks: string[] = []; + const timeToFirstToken: number[] = []; + const reasoningAtFirstToken: string[] = []; + await makeOpenAIResponsesRequest( + [{ role: "user", content: "What is 3+4?" }], + (_role, delta) => answerChunks.push(delta), + "qwen3", + "test-token", + undefined, + undefined, + (content) => reasoningChunks.push(content), + (ttft) => { + timeToFirstToken.push(ttft); + reasoningAtFirstToken.push(reasoningChunks.join("") + "|" + answerChunks.join("")); + }, + undefined, + undefined, + undefined, + undefined, + undefined, + undefined, + undefined, + undefined, + undefined, + undefined, + undefined, + undefined, + undefined, + undefined, + undefined, + streamingEnabled, + ); + return { + reasoning: reasoningChunks.join(""), + answer: answerChunks.join(""), + timeToFirstToken, + reasoningBeforeFirstToken: reasoningAtFirstToken[0] ?? "", + }; + }; + + const streamOf = (events: Record[]) => { + async function* mockStream() { + for (const event of events) { + yield event; + } + yield { type: "response.completed", response: { id: "resp_reasoning" } }; + } + mockResponsesCreate.mockResolvedValue(mockStream()); + }; + + afterEach(() => { + vi.clearAllMocks(); + }); + + it("shows streamed reasoning_text deltas and starts the first-token timer on them", async () => { + streamOf([ + { type: "response.reasoning_text.delta", item_id: "rs_1", content_index: 0, delta: "Add " }, + { type: "response.reasoning_text.delta", item_id: "rs_1", content_index: 0, delta: "them" }, + { type: "response.output_text.delta", delta: "7" }, + ]); + + const result = await run(true); + + expect(result.reasoning).toBe("Add them"); + expect(result.answer).toBe("7"); + expect(result.timeToFirstToken).toHaveLength(1); + expect(result.reasoningBeforeFirstToken).toBe("Add |"); + }); + + it("separates streamed reasoning summary parts and items with a blank line", async () => { + streamOf([ + { type: "response.reasoning_summary_text.delta", item_id: "rs_1", summary_index: 0, delta: "First" }, + { type: "response.reasoning_summary_text.delta", item_id: "rs_1", summary_index: 0, delta: " part" }, + { type: "response.reasoning_summary_text.delta", item_id: "rs_1", summary_index: 1, delta: "Second" }, + { type: "response.reasoning_summary_text.delta", item_id: "rs_2", summary_index: 0, delta: "Third" }, + ]); + + await expect(run(true)).resolves.toMatchObject({ reasoning: "First part\n\nSecond\n\nThird" }); + }); + + it("still shows the legacy reasoning.delta event", async () => { + streamOf([{ type: "response.reasoning.delta", delta: "Legacy thought" }]); + + await expect(run(true)).resolves.toMatchObject({ reasoning: "Legacy thought" }); + }); + + it("shows non-streamed reasoning content when the summary is empty", async () => { + mockResponsesCreate.mockReturnValueOnce( + nonStreamingResponse({ + id: "resp_content", + output: [ + { + type: "reasoning", + summary: [], + content: [ + { type: "reasoning_text", text: "Add" }, + { type: "reasoning_text", text: "them" }, + ], + }, + { type: "message", content: [{ type: "output_text", text: "7" }] }, + ], + }), + ); + + await expect(run(false)).resolves.toMatchObject({ reasoning: "Add\n\nthem", answer: "7" }); + }); + + it("prefers the non-streamed reasoning summary over its content", async () => { + mockResponsesCreate.mockReturnValueOnce( + nonStreamingResponse({ + id: "resp_summary", + output: [ + { + type: "reasoning", + summary: [{ type: "summary_text", text: "Short summary" }], + content: [{ type: "reasoning_text", text: "Raw chain" }], + }, + { type: "reasoning", content: [{ type: "output_text", text: "Second item" }] }, + ], + }), + ); + + await expect(run(false)).resolves.toMatchObject({ reasoning: "Short summary\n\nSecond item" }); + }); +}); + describe("responses_api prompt cache usage", () => { const captureUsage = async (usage: Record): Promise => { async function* mockStream() { diff --git a/ui/litellm-dashboard/src/components/llm_calls/responses_api.tsx b/ui/litellm-dashboard/src/components/llm_calls/responses_api.tsx index 426abd4e172..ce1a8aab0c5 100644 --- a/ui/litellm-dashboard/src/components/llm_calls/responses_api.tsx +++ b/ui/litellm-dashboard/src/components/llm_calls/responses_api.tsx @@ -44,6 +44,22 @@ type SynthesizedResponseEvent = | { type: "response.output_text.delta"; delta: string } | { type: "response.completed"; response: NonStreamedResponse }; +const REASONING_PART_SEPARATOR = "\n\n"; + +const REASONING_DELTA_EVENT_TYPES: ReadonlySet = new Set([ + "response.reasoning_text.delta", + "response.reasoning_summary_text.delta", + "response.reasoning.delta", +]); + +const nonEmptyTexts = (parts: ResponseOutputPart[] | undefined): string[] => + (parts ?? []).map((part) => part.text ?? "").filter((text) => text.length > 0); + +const reasoningItemText = (item: ResponseOutputItem): string => { + const summary = nonEmptyTexts(item.summary); + return (summary.length > 0 ? summary : nonEmptyTexts(item.content)).join(REASONING_PART_SEPARATOR); +}; + const responseAsEvents = (response: NonStreamedResponse): SynthesizedResponseEvent[] => { const outputItems = response.output ?? []; const outputText = outputItems @@ -54,9 +70,9 @@ const responseAsEvents = (response: NonStreamedResponse): SynthesizedResponseEve .join(""); const reasoningText = outputItems .filter((item) => item.type === "reasoning") - .flatMap((item) => item.summary ?? []) - .map((part) => part.text ?? "") - .join(""); + .map(reasoningItemText) + .filter((text) => text.length > 0) + .join(REASONING_PART_SEPARATOR); return [ ...outputItems.map((item) => ({ type: "response.output_item.done" as const, item })), @@ -124,6 +140,7 @@ export async function makeOpenAIResponsesRequest( try { const startTime = Date.now(); let firstTokenReceived = false; + let reasoningPartKey: string | null = null; let servedFromResponseCache = false; const formattedInput = messages.flatMap((message) => { @@ -298,10 +315,16 @@ export async function makeOpenAIResponsesRequest( } // Handle reasoning content - if (event.type === "response.reasoning.delta" && "delta" in event) { - const delta = event.delta; - if (typeof delta === "string" && onReasoningContent) { - onReasoningContent(delta); + if (REASONING_DELTA_EVENT_TYPES.has(event.type) && typeof event.delta === "string" && event.delta.length > 0) { + const partKey = `${event.item_id ?? ""}:${event.summary_index ?? event.content_index ?? 0}`; + const separator = reasoningPartKey !== null && reasoningPartKey !== partKey ? REASONING_PART_SEPARATOR : ""; + reasoningPartKey = partKey; + onReasoningContent?.(separator + event.delta); + + const isFirstToken = !firstTokenReceived; + firstTokenReceived = true; + if (isFirstToken && onTimingData && streamingEnabled) { + onTimingData(Date.now() - startTime); } } diff --git a/ui/litellm-dashboard/src/components/model_add/CredentialModal.integration.test.tsx b/ui/litellm-dashboard/src/components/model_add/CredentialModal.integration.test.tsx index c7d939333ec..252724412fb 100644 --- a/ui/litellm-dashboard/src/components/model_add/CredentialModal.integration.test.tsx +++ b/ui/litellm-dashboard/src/components/model_add/CredentialModal.integration.test.tsx @@ -9,9 +9,18 @@ import CredentialModal from "./CredentialModal"; vi.mock("../networking", async () => { const actual = await vi.importActual("../networking"); + const { readFileSync } = await import("node:fs"); + const { resolve } = await import("node:path"); + const metadata = JSON.parse( + readFileSync( + resolve(__dirname, "../../../../../litellm/proxy/public_endpoints/provider_create_fields.json"), + "utf8", + ), + ) as { provider: string }[]; return { ...actual, getProviderCreateMetadata: vi.fn().mockResolvedValue([ + ...metadata.filter((provider) => provider.provider === "BIGMODEL"), { provider: "OpenAI", provider_display_name: Providers.OpenAI, @@ -157,6 +166,39 @@ const chooseProvider = async (user: ReturnType, provider await user.click(options.find((option) => option.textContent === provider) ?? options[0]); }; +describe("CredentialModal with BigModel metadata", () => { + it("requires a masked API key and shows the default base", async () => { + const user = userEvent.setup(); + const onSubmit = renderModal(); + await chooseProvider(user, Providers.BIGMODEL); + expect(await screen.findByLabelText("API Base")).toHaveValue("https://open.bigmodel.cn"); + expect(screen.getByLabelText("BigModel (Zhipu AI) API Key")).toHaveAttribute("type", "password"); + fill("Credential Name:", "bigmodel-key"); + await user.click(screen.getByRole("button", { name: "Add Credential" })); + expect(await screen.findByText("Required")).toBeInTheDocument(); + expect(onSubmit).not.toHaveBeenCalled(); + }); + + it("saves the key and an explicit base for BigModel", async () => { + const user = userEvent.setup(); + const onSubmit = renderModal(); + await chooseProvider(user, Providers.BIGMODEL); + await screen.findByLabelText("BigModel (Zhipu AI) API Key"); + fill("Credential Name:", "bigmodel-key"); + fill("BigModel (Zhipu AI) API Key", "synthetic-bigmodel-key"); + fill("API Base", "https://bigmodel-proxy.example"); + await user.click(screen.getByRole("button", { name: "Add Credential" })); + expect(onSubmit).toHaveBeenCalledWith( + { + credential_name: "bigmodel-key", + custom_llm_provider: "BIGMODEL", + credential_values: { api_key: "synthetic-bigmodel-key", api_base: "https://bigmodel-proxy.example" }, + }, + [], + ); + }); +}); + describe("CredentialModal with Anthropic workload identity federation", () => { it("deletes stored exchange fields when switching to a static token", async () => { const user = userEvent.setup(); diff --git a/ui/litellm-dashboard/src/components/provider_info_helpers.test.tsx b/ui/litellm-dashboard/src/components/provider_info_helpers.test.tsx index 0ebd2cdff17..810b010f25e 100644 --- a/ui/litellm-dashboard/src/components/provider_info_helpers.test.tsx +++ b/ui/litellm-dashboard/src/components/provider_info_helpers.test.tsx @@ -20,6 +20,18 @@ const BUNDLED_MODEL_MAP: Record = JSON.pa ); describe("provider_info_helpers", () => { + it("resolves BigModel metadata, name, logo and model placeholder", () => { + const metadata = PROVIDER_CREATE_FIELDS.find((provider) => provider.provider === "BIGMODEL"); + expect(provider_map.BIGMODEL).toBe(metadata?.litellm_provider); + expect(getProviderLogoAndName("bigmodel")).toEqual({ + displayName: "BigModel (Zhipu AI)", + logo: providerLogoMap[Providers.BIGMODEL], + }); + expect(getProviderLogoAndName("BIGMODEL")).toEqual(getProviderLogoAndName("bigmodel")); + expect(providerLogoMap[Providers.BIGMODEL]).toContain("bigmodel"); + expect(getPlaceholder(Providers.BIGMODEL)).toMatch(/^bigmodel\//); + }); + it("maps Microsoft 365 Copilot to its chat model provider and placeholder", () => { expect(provider_map.MICROSOFT_365_COPILOT).toBe("microsoft_365_copilot"); expect(getPlaceholder(Providers.MICROSOFT_365_COPILOT)).toBe("microsoft_365_copilot/chat"); @@ -222,8 +234,10 @@ describe("provider_info_helpers", () => { Providers.PG_VECTOR, Providers.PREDIBASE, Providers.Sail, + Providers.StreamLake, Providers.WANDB, Providers.ZAI, + Providers.ZeroGPU, ]; const logolessProviders = Object.values(Providers).filter((provider) => !providerLogoMap[provider]); expect([...logolessProviders].sort()).toEqual([...knownLogolessProviders].sort()); @@ -357,6 +371,10 @@ describe("provider_info_helpers", () => { expect(getPlaceholder(Providers.Cognition)).toBe("cognition/swe-1.7"); }); + it("should return zerogpu/gpt-oss-120b placeholder for ZeroGPU provider", () => { + expect(getPlaceholder("ZeroGPU")).toBe("zerogpu/gpt-oss-120b"); + }); + it("should return a chatgpt/ placeholder for the CHATGPT dropdown key", () => { expect(getPlaceholder("CHATGPT")).toBe("chatgpt/gpt-5.4"); }); @@ -457,6 +475,19 @@ describe("provider_info_helpers", () => { expect(result).toEqual(["gpt-3.5-turbo", "gpt-4"]); }); + it("should return StreamLake models and exclude models from other providers", () => { + const modelMap = { + "streamlake/GLM-5.3": { litellm_provider: "streamlake" }, + "streamlake/DeepSeek-V3": { litellm_provider: "streamlake" }, + "gpt-4o": { litellm_provider: "openai" }, + }; + const result = getProviderModels(Providers.StreamLake, modelMap); + + expect(provider_map.StreamLake).toBe("streamlake"); + expect(result).toEqual(["streamlake/GLM-5.3", "streamlake/DeepSeek-V3"]); + expect(result).not.toContain("gpt-4o"); + }); + it("should return models whose litellm_provider is a prefix-anchored variant of the provider", () => { const modelMap = { "anthropic-text-model": { litellm_provider: "anthropic_text" }, diff --git a/ui/litellm-dashboard/src/components/provider_info_helpers.tsx b/ui/litellm-dashboard/src/components/provider_info_helpers.tsx index 2541aa45050..1ed32c160e6 100644 --- a/ui/litellm-dashboard/src/components/provider_info_helpers.tsx +++ b/ui/litellm-dashboard/src/components/provider_info_helpers.tsx @@ -6,6 +6,7 @@ import anthropicLogo from "../../public/assets/logos/anthropic.svg"; import assemblyaiSmallLogo from "../../public/assets/logos/assemblyai_small.png"; import basetenLogo from "../../public/assets/logos/baseten.svg"; import bedrockLogo from "../../public/assets/logos/bedrock.svg"; +import bigmodelLogo from "../../public/assets/logos/bigmodel.png"; import cerebrasLogo from "../../public/assets/logos/cerebras.svg"; import cloudflareLogo from "../../public/assets/logos/cloudflare.svg"; import cohereLogo from "../../public/assets/logos/cohere.svg"; @@ -177,6 +178,7 @@ export enum Providers { Snowflake = "Snowflake", Soniox = "Soniox", StrandsDecider = "Strands Decider", + StreamLake = "StreamLake", TEXT_COMPLETION_CODESTRAL = "Text-Completion-Codestral", Tencent = "Tencent", TogetherAI = "TogetherAI", @@ -197,6 +199,8 @@ export enum Providers { xAI = "xAI", XINFERENCE = "Xinference", ZAI = "Z.AI (Zhipu AI)", + BIGMODEL = "BigModel (Zhipu AI)", + ZeroGPU = "ZeroGPU", } export const provider_map: Record = { @@ -305,6 +309,7 @@ export const provider_map: Record = { Snowflake: "snowflake", Soniox: "soniox", StrandsDecider: "strands_decider", + StreamLake: "streamlake", TEXT_COMPLETION_CODESTRAL: "text-completion-codestral", Tencent: "tencent", TogetherAI: "together_ai", @@ -325,6 +330,8 @@ export const provider_map: Record = { xAI: "xai", XINFERENCE: "xinference", ZAI: "zai", + BIGMODEL: "bigmodel", + ZeroGPU: "zerogpu", }; const standaloneSubproviderSlugs = new Set(["bedrock_mantle"]); @@ -333,6 +340,7 @@ export const resolveLitellmProviderSlug = (provider: string): string => provider_map[provider] ?? provider.toLowerCase(); export const providerLogoMap: Partial> = { + [Providers.BIGMODEL]: bigmodelLogo.src, [Providers.A2A_Agent]: a2aAgentLogo.src, [Providers.AI21]: ai21Logo.src, [Providers.AI21_CHAT]: ai21Logo.src, @@ -492,11 +500,14 @@ const providerPlaceholderMap: Partial> = { [Providers.Tencent]: "tencent/deepseek-v4-pro", [Providers.TypeSafe]: "typesafe/jev-latest", [Providers.Nace]: "nace/drex-latest", + [Providers.StreamLake]: "streamlake/", [Providers.Vertex_AI]: "gemini-pro", [Providers.VolcEngine]: "volcengine/", [Providers.Voyage]: "voyage/", [Providers.WATSONX]: "watsonx/ibm/granite-3-3-8b-instruct", [Providers.ZAI]: "zai/glm-4.5", + [Providers.BIGMODEL]: "bigmodel/glm-5.3", + [Providers.ZeroGPU]: "zerogpu/gpt-oss-120b", }; export const getPlaceholder = (selectedProvider: string): string => { diff --git a/ui/litellm-dashboard/src/components/shared/SearchSelect.integration.test.tsx b/ui/litellm-dashboard/src/components/shared/SearchSelect.integration.test.tsx index 9f320049b09..ecb8dd161f3 100644 --- a/ui/litellm-dashboard/src/components/shared/SearchSelect.integration.test.tsx +++ b/ui/litellm-dashboard/src/components/shared/SearchSelect.integration.test.tsx @@ -63,6 +63,24 @@ describe("SearchSelect", () => { expect(onValueChange).toHaveBeenLastCalledWith("team-3"); }); + it("offers the typed text as a value only when the caller accepts it", async () => { + const user = userEvent.setup(); + const onValueChange = vi.fn(); + const customValue = { hint: "Custom value", accepts: (typed: string) => typed.endsWith("*") }; + const { rerender } = render(); + const input = screen.getByRole("combobox"); + await user.click(input); + fireEvent.change(input, { target: { value: "team-*" } }); + expect(screen.queryByRole("option", { name: /team-\*/ })).not.toBeInTheDocument(); + + rerender(); + fireEvent.change(input, { target: { value: "team-4" } }); + expect(screen.queryByRole("option", { name: /team-4/ })).not.toBeInTheDocument(); + fireEvent.change(input, { target: { value: "team-*" } }); + await user.click(await screen.findByRole("option", { name: /team-\*/ })); + expect(onValueChange).toHaveBeenLastCalledWith("team-*"); + }); + it("filters the options client-side as you type", async () => { const user = userEvent.setup(); render(); diff --git a/ui/litellm-dashboard/src/components/shared/SearchSelect.tsx b/ui/litellm-dashboard/src/components/shared/SearchSelect.tsx index 3649114826d..e139720a2ed 100644 --- a/ui/litellm-dashboard/src/components/shared/SearchSelect.tsx +++ b/ui/litellm-dashboard/src/components/shared/SearchSelect.tsx @@ -1,6 +1,6 @@ "use client"; -import React from "react"; +import React, { useState } from "react"; import { Combobox, ComboboxContent, @@ -19,6 +19,11 @@ export interface SearchSelectOption { icon?: React.ReactNode; } +interface CustomValue { + hint: string; + accepts: (typed: string) => boolean; +} + interface SearchSelectProps { options: SearchSelectOption[]; value?: string | null; @@ -29,6 +34,8 @@ interface SearchSelectProps { className?: string; inputId?: string; allowClear?: boolean; + customValue?: CustomValue; + reservedValues?: readonly string[]; "aria-label"?: string; id?: string; } @@ -49,13 +56,22 @@ export function SearchSelect({ className, inputId, allowClear = true, + customValue, + reservedValues = [], "aria-label": ariaLabel, id, }: SearchSelectProps) { + const [query, setQuery] = useState(""); const selected = value == null || value === "" ? null : options.find((option) => option.value === value) ?? { label: value, value }; - const items = + const known = selected !== null && !options.some((option) => option.value === selected.value) ? [selected, ...options] : options; + const typed = query.trim(); + const isNewValue = typed !== "" && !reservedValues.includes(typed) && !known.some((option) => option.value === typed); + const items = + customValue !== undefined && isNewValue && customValue.accepts(typed) + ? [...known, { label: typed, value: typed, sublabel: customValue.hint }] + : known; return ( a.value === b.value} itemToStringLabel={(item: SearchSelectOption) => item.label} filter={matchesQuery} + onInputValueChange={setQuery} disabled={disabled} > ["hotkeys"][number]; @@ -59,14 +60,6 @@ export function shortcutHints(shortcuts: readonly BoundShortcut[]): readonly Sho >((hints, [key, shortcut]) => mergeAdjacent(hints, key, shortcut.description ?? ""), []); } -function Kbd({ children }: { children: ReactNode }) { - return ( - - {children} - - ); -} - /** The shortcuts active right now, read from what is bound rather than typed by hand. */ export function ShortcutHints({ className }: { className?: string }) { const { hotkeys } = useHotkeysContext(); diff --git a/ui/litellm-dashboard/src/components/shared/search/SearchBox.tsx b/ui/litellm-dashboard/src/components/shared/search/SearchBox.tsx index 4e45f8902f0..ae6d5a6ec09 100644 --- a/ui/litellm-dashboard/src/components/shared/search/SearchBox.tsx +++ b/ui/litellm-dashboard/src/components/shared/search/SearchBox.tsx @@ -8,9 +8,10 @@ import { Check, Copy, CornerDownLeft, Loader2, type LucideIcon, Search } from "l import { Schema } from "prosemirror-model"; import { EditorState, Plugin, TextSelection, type Transaction } from "prosemirror-state"; import { Decoration, DecorationSet, type EditorView } from "prosemirror-view"; -import { type ComponentProps, createContext, type ReactNode, useContext, useId, useMemo, useState } from "react"; +import { type ComponentProps, createContext, useContext, useId, useMemo, useState } from "react"; import { Button } from "@/components/ui/button"; +import { Kbd } from "@/components/ui/kbd"; import { cn } from "@/lib/cva.config"; import { type FilterOp, languageOps, parseQuery, type QueryClause, type QueryLanguage } from "./language"; @@ -326,7 +327,7 @@ function Suggestions({ className, children, ...props }: SearchBoxSuggestionsProp - + Select @@ -392,12 +393,4 @@ function OperatorHints({ ops }: { ops: readonly FilterOp[] }) { ); } -function Kbd({ children }: { children: ReactNode }) { - return ( - - {children} - - ); -} - export const SearchBox = { Root, Input, Suggestions, CopyCommand } as const; diff --git a/ui/litellm-dashboard/src/lib/http/schema.d.ts b/ui/litellm-dashboard/src/lib/http/schema.d.ts index 8af76e4d16f..2147afc4931 100644 --- a/ui/litellm-dashboard/src/lib/http/schema.d.ts +++ b/ui/litellm-dashboard/src/lib/http/schema.d.ts @@ -8475,7 +8475,7 @@ export interface paths { * - throttle_on_budget_exceeded: Optional[bool] - When the key exceeds its max_budget, throttle its tpm/rpm to the global budget_exceeded_throttle_percentage instead of blocking the key entirely. * - enable_prompt_caching: Optional[bool] - Auto-inject prompt caching breakpoints (Anthropic cache_control markers) on requests made with this key. Supported Claude models on Anthropic, Bedrock, Vertex AI, and Azure AI only. * - permissions: Optional[dict] - key-specific permissions. Currently just used for turning off pii masking (if connected). Example - {"pii": false} - * - model_max_budget: Optional[Dict[str, BudgetConfig]] - Model-specific budgets {"gpt-4": {"budget_limit": 0.0005, "time_period": "30d"}}}. IF null or {} then no model specific budget. + * - model_max_budget: Optional[Dict[str, BudgetConfig]] - Model-specific budgets keyed by model name, `*` pattern like "claude-opus*", or model access group, e.g. {"gpt-4": {"budget_limit": 0.0005, "time_period": "30d"}}}. IF null or {} then no model specific budget. * - budget_fallbacks: Optional[Dict[str, List[str]]] - Per-model fallback chain tried in order when that model's own `model_max_budget` is exceeded, e.g. {"gpt-4o": ["gpt-4o-mini"]}. * - model_rpm_limit: Optional[dict] - key-specific model rpm limit. Example - {"text-davinci-002": 1000, "gpt-3.5-turbo": 1000}. IF null or {} then no model specific rpm limit. * - model_tpm_limit: Optional[dict] - key-specific model tpm limit. Example - {"text-davinci-002": 1000, "gpt-3.5-turbo": 1000}. IF null or {} then no model specific tpm limit. @@ -8721,7 +8721,7 @@ export interface paths { * - tags: Optional[List[str]] - Tags for organizing keys (Enterprise only) * - spend: Optional[float] - Amount spent by key * - max_budget: Optional[float] - Max budget for key - * - model_max_budget: Optional[Dict[str, BudgetConfig]] - Model-specific budgets {"gpt-4": {"budget_limit": 0.0005, "time_period": "30d"}} + * - model_max_budget: Optional[Dict[str, BudgetConfig]] - Model-specific budgets keyed by model name, `*` pattern like "claude-opus*", or model access group, e.g. {"gpt-4": {"budget_limit": 0.0005, "time_period": "30d"}} * - budget_fallbacks: Optional[Dict[str, List[str]]] - Per-model fallback chain tried in order when that model's own `model_max_budget` is exceeded, e.g. {"gpt-4o": ["gpt-4o-mini"]}. * - budget_duration: Optional[str] - Budget reset period ("30d", "1h", etc.) * - soft_budget: Optional[float] - Soft budget limit (warning vs. hard stop). Will trigger a slack alert when this soft budget is reached. @@ -8798,7 +8798,7 @@ export interface paths { * - metadata: Optional[dict] - Metadata for key, store information for key. Example metadata = {"team": "core-infra", "app": "app2", "email": "ishaan@berri.ai" } * - guardrails: Optional[List[str]] - List of active guardrails for the key * - permissions: Optional[dict] - key-specific permissions. Currently just used for turning off pii masking (if connected). Example - {"pii": false} - * - model_max_budget: Optional[Dict[str, BudgetConfig]] - Model-specific budgets {"gpt-4": {"budget_limit": 0.0005, "time_period": "30d"}}}. IF null or {} then no model specific budget. + * - model_max_budget: Optional[Dict[str, BudgetConfig]] - Model-specific budgets keyed by model name, `*` pattern like "claude-opus*", or model access group, e.g. {"gpt-4": {"budget_limit": 0.0005, "time_period": "30d"}}}. IF null or {} then no model specific budget. * - budget_fallbacks: Optional[Dict[str, List[str]]] - Per-model fallback chain tried in order when that model's own `model_max_budget` is exceeded, e.g. {"gpt-4o": ["gpt-4o-mini"]}. * - model_rpm_limit: Optional[dict] - key-specific model rpm limit. Example - {"text-davinci-002": 1000, "gpt-3.5-turbo": 1000}. IF null or {} then no model specific rpm limit. * - model_tpm_limit: Optional[dict] - key-specific model tpm limit. Example - {"text-davinci-002": 1000, "gpt-3.5-turbo": 1000}. IF null or {} then no model specific tpm limit. @@ -8931,7 +8931,7 @@ export interface paths { * - enforced_params: Optional[List[str]] - List of enforced params for the key (Enterprise only). [Docs](https://docs.litellm.ai/docs/proxy/enterprise#enforce-required-params-for-llm-requests) * - spend: Optional[float] - Amount spent by key * - max_budget: Optional[float] - Max budget for key - * - model_max_budget: Optional[Dict[str, BudgetConfig]] - Model-specific budgets {"gpt-4": {"budget_limit": 0.0005, "time_period": "30d"}} + * - model_max_budget: Optional[Dict[str, BudgetConfig]] - Model-specific budgets keyed by model name, `*` pattern like "claude-opus*", or model access group, e.g. {"gpt-4": {"budget_limit": 0.0005, "time_period": "30d"}} * - budget_fallbacks: Optional[Dict[str, List[str]]] - Per-model fallback chain tried in order when that model's own `model_max_budget` is exceeded, e.g. {"gpt-4o": ["gpt-4o-mini"]}. * - budget_duration: Optional[str] - Budget reset period ("30d", "1h", etc.) * - soft_budget: Optional[float] - Soft budget limit (warning vs. hard stop). Will trigger a slack alert when this soft budget is reached. Set to null to remove the soft budget. @@ -9020,7 +9020,7 @@ export interface paths { * - tags: Optional[List[str]] - Tags for organizing keys (Enterprise only) * - spend: Optional[float] - Amount spent by key * - max_budget: Optional[float] - Max budget for key - * - model_max_budget: Optional[Dict[str, BudgetConfig]] - Model-specific budgets {"gpt-4": {"budget_limit": 0.0005, "time_period": "30d"}} + * - model_max_budget: Optional[Dict[str, BudgetConfig]] - Model-specific budgets keyed by model name, `*` pattern like "claude-opus*", or model access group, e.g. {"gpt-4": {"budget_limit": 0.0005, "time_period": "30d"}} * - budget_fallbacks: Optional[Dict[str, List[str]]] - Per-model fallback chain tried in order when that model's own `model_max_budget` is exceeded, e.g. {"gpt-4o": ["gpt-4o-mini"]}. * - budget_duration: Optional[str] - Budget reset period ("30d", "1h", etc.) * - soft_budget: Optional[float] - Soft budget limit (warning vs. hard stop). Will trigger a slack alert when this soft budget is reached. @@ -11211,6 +11211,9 @@ export interface paths { * * # Get provider response * curl -X GET http://localhost:4000/v1/responses/resp_abc123 -H "Authorization: Bearer $LITELLM_MASTER_KEY" + * + * # Resume a background response's event stream after sequence number 7 + * curl -N "http://localhost:4000/v1/responses/resp_abc123?stream=true&starting_after=7" -H "Authorization: Bearer $LITELLM_MASTER_KEY" * ``` */ get: operations["get_response_openai_v1_responses__response_id__get"]; @@ -14269,6 +14272,9 @@ export interface paths { * * # Get provider response * curl -X GET http://localhost:4000/v1/responses/resp_abc123 -H "Authorization: Bearer $LITELLM_MASTER_KEY" + * + * # Resume a background response's event stream after sequence number 7 + * curl -N "http://localhost:4000/v1/responses/resp_abc123?stream=true&starting_after=7" -H "Authorization: Bearer $LITELLM_MASTER_KEY" * ``` */ get: operations["get_response_responses__response_id__get"]; @@ -17098,7 +17104,7 @@ export interface paths { * - prompts: Optional[List[str]] - List of prompts that the team is allowed to use. * - organization_id: Optional[str] - The organization id of the team. Default is None. Create via `/organization/new`. * - model_aliases: Optional[dict] - Model aliases for the team. [Docs](https://docs.litellm.ai/docs/proxy/team_based_routing#create-team-with-model-alias) - * - model_max_budget: Optional[dict] - Per-model max budget every key on the team inherits unless the key sets its own for that model. Example: {"gpt-4o": {"max_budget": 10, "budget_duration": "1d"}} + * - model_max_budget: Optional[dict] - Per-model max budget every key on the team inherits unless the key sets its own for that model, keyed by model name, `*` pattern, or model access group. Example: {"gpt-4o": {"max_budget": 10, "budget_duration": "1d"}} * - guardrails: Optional[List[str]] - Guardrails for the team. [Docs](https://docs.litellm.ai/docs/proxy/guardrails) * - policies: Optional[List[str]] - Policies for the team. [Docs](https://docs.litellm.ai/docs/proxy/guardrails/guardrail_policies) * - disable_global_guardrails: Optional[bool] - Whether to disable global guardrails for the team. Proxy admin only. @@ -17328,7 +17334,7 @@ export interface paths { * - tags: Optional[List[str]] - Tags for [tracking spend](https://litellm.vercel.app/docs/proxy/enterprise#tracking-spend-for-custom-tags) and/or doing [tag-based routing](https://litellm.vercel.app/docs/proxy/tag_routing). * - organization_id: Optional[str] - The organization id of the team. Default is None. Create via `/organization/new`. * - model_aliases: Optional[dict] - Model aliases for the team. [Docs](https://docs.litellm.ai/docs/proxy/team_based_routing#create-team-with-model-alias) - * - model_max_budget: Optional[dict] - Per-model max budget every key on the team inherits unless the key sets its own for that model. Example: {"gpt-4o": {"max_budget": 10, "budget_duration": "1d"}} + * - model_max_budget: Optional[dict] - Per-model max budget every key on the team inherits unless the key sets its own for that model, keyed by model name, `*` pattern, or model access group. Example: {"gpt-4o": {"max_budget": 10, "budget_duration": "1d"}} * - guardrails: Optional[List[str]] - Guardrails for the team. [Docs](https://docs.litellm.ai/docs/proxy/guardrails) * - policies: Optional[List[str]] - Policies for the team. [Docs](https://docs.litellm.ai/docs/proxy/guardrails/guardrail_policies) * - disable_global_guardrails: Optional[bool] - Whether to disable global guardrails for the team. Proxy admin only. @@ -18778,7 +18784,7 @@ export interface paths { * - permissions: Optional[dict] - [Not Implemented Yet] User-specific permissions, eg. turning off pii masking. * - metadata: Optional[dict] - Metadata for user, store information for user. Example metadata = {"team": "core-infra", "app": "app2", "email": "ishaan@berri.ai" } * - max_parallel_requests: Optional[int] - Rate limit a user based on the number of parallel requests. Raises 429 error, if user's parallel requests > x. - * - model_max_budget: Optional[dict] - Model-specific max budget for user. [Docs](https://docs.litellm.ai/docs/proxy/users#add-model-specific-budgets-to-keys) + * - model_max_budget: Optional[dict] - Model-specific max budget for user, keyed by model name, `*` pattern, or model access group. [Docs](https://docs.litellm.ai/docs/proxy/users#add-model-specific-budgets-to-keys) * - budget_fallbacks: Optional[Dict[str, List[str]]] - Per-model fallback chain tried in order when that model's own `model_max_budget` is exceeded, e.g. {"gpt-4o": ["gpt-4o-mini"]}. * - model_rpm_limit: Optional[float] - Model-specific rpm limit for user. [Docs](https://docs.litellm.ai/docs/proxy/users#add-model-specific-limits-to-keys) * - mcp_rpm_limit: Optional[dict] - Per-MCP-server rpm limit, keyed by MCP server name {"github": 100, "slack": 200}. Enforced for keys and teams only; values set on a user are stored but not enforced per user. @@ -18917,7 +18923,7 @@ export interface paths { * - permissions: Optional[dict] - [Not Implemented Yet] User-specific permissions, eg. turning off pii masking. * - metadata: Optional[dict] - Metadata for user, store information for user. Example metadata = {"team": "core-infra", "app": "app2", "email": "ishaan@berri.ai" } * - max_parallel_requests: Optional[int] - Rate limit a user based on the number of parallel requests. Raises 429 error, if user's parallel requests > x. - * - model_max_budget: Optional[dict] - Model-specific max budget for user. [Docs](https://docs.litellm.ai/docs/proxy/users#add-model-specific-budgets-to-keys) + * - model_max_budget: Optional[dict] - Model-specific max budget for user, keyed by model name, `*` pattern, or model access group. [Docs](https://docs.litellm.ai/docs/proxy/users#add-model-specific-budgets-to-keys) * - budget_fallbacks: Optional[Dict[str, List[str]]] - Per-model fallback chain tried in order when that model's own `model_max_budget` is exceeded, e.g. {"gpt-4o": ["gpt-4o-mini"]}. * - model_rpm_limit: Optional[float] - Model-specific rpm limit for user. [Docs](https://docs.litellm.ai/docs/proxy/users#add-model-specific-limits-to-keys) * - mcp_rpm_limit: Optional[dict] - Per-MCP-server rpm limit, keyed by MCP server name {"github": 100, "slack": 200}. Enforced for keys and teams only; values set on a user are stored but not enforced per user. @@ -19058,6 +19064,7 @@ export interface paths { * @description Args: * request: TokenCountRequest * call_endpoint: bool - When set to "True" it will call the token counting endpoint - e.g Anthropic or Google AI Studio Token Counting APIs. + * litellm_call_id: the x-litellm-call-id header, logged with the count so it joins the inference call's logs * * Returns: * TokenCountResponse @@ -21890,6 +21897,9 @@ export interface paths { * * # Get provider response * curl -X GET http://localhost:4000/v1/responses/resp_abc123 -H "Authorization: Bearer $LITELLM_MASTER_KEY" + * + * # Resume a background response's event stream after sequence number 7 + * curl -N "http://localhost:4000/v1/responses/resp_abc123?stream=true&starting_after=7" -H "Authorization: Bearer $LITELLM_MASTER_KEY" * ``` */ get: operations["get_response_v1_responses__response_id__get"]; @@ -23365,9 +23375,10 @@ export interface paths { * -H "Authorization: Bearer sk-..." \ * -H "Content-Type: application/json" \ * -d '{ - * "name": "my-custom-slides-agent", - * "base_agent": "waverunner", - * "instructions": "You are a helpful assistant that creates slides.", + * "id": "my-custom-slides-agent", + * "base_agent": "antigravity-preview-09-2026", + * "system_instruction": "You are a helpful assistant that creates slides.", + * "agent_config": {"type": "antigravity", "model": "gemini-3.8-flash"}, * "base_environment": { * "type": "remote", * "sources": [ @@ -27719,6 +27730,10 @@ export interface components { entities?: { [key: string]: components["schemas"]["MetricWithMetadata"]; }; + /** Guardrails */ + guardrails?: { + [key: string]: components["schemas"]["GuardrailMetric"]; + }; /** Mcp Servers */ mcp_servers?: { [key: string]: components["schemas"]["MetricWithMetadata"]; @@ -33234,6 +33249,38 @@ export interface components { /** Updated At */ updated_at?: string | null; }; + /** GuardrailKeyMetric */ + GuardrailKeyMetric: { + metadata: components["schemas"]["KeyMetadata"]; + metrics: components["schemas"]["GuardrailSpendMetrics"]; + }; + /** GuardrailMetadata */ + GuardrailMetadata: { + /** Guardrail Name */ + guardrail_name: string; + }; + /** GuardrailMetric */ + GuardrailMetric: { + /** Api Key Breakdown */ + api_key_breakdown?: { + [key: string]: components["schemas"]["GuardrailKeyMetric"]; + }; + metadata: components["schemas"]["GuardrailMetadata"]; + metrics: components["schemas"]["GuardrailSpendMetrics"]; + }; + /** GuardrailSpendMetrics */ + GuardrailSpendMetrics: { + /** + * Spend + * @default 0 + */ + spend: number; + /** + * Untracked Units + * @default 0 + */ + untracked_units: number; + }; /** GuardrailSubmissionItem */ GuardrailSubmissionItem: { /** Created At */ @@ -35359,6 +35406,8 @@ export interface components { cost_per_second?: number | null; /** Custom Llm Provider */ custom_llm_provider?: string | null; + /** Daily Reset Time */ + daily_reset_time?: string | null; /** Default Api Key Rpm Limit */ default_api_key_rpm_limit?: number | null; /** Default Api Key Tpm Limit */ @@ -35609,6 +35658,8 @@ export interface components { regional_processing_uplift_multiplier_us?: number | null; /** Responses Api Version */ responses_api_version?: string | null; + /** Rpd */ + rpd?: number | null; /** Rpm */ rpm?: number | null; /** S3 Access Key Id */ @@ -35661,6 +35712,8 @@ export interface components { token_exchange_profile?: string | null; /** Token Exchange Scope */ token_exchange_scope?: string | null; + /** Tpd */ + tpd?: number | null; /** Tpm */ tpm?: number | null; /** Use Chat Completions Api */ @@ -44163,6 +44216,11 @@ export interface components { */ type: "tool_search_output"; }; + /** ResponsesAPIModeration */ + ResponsesAPIModeration: { + /** Model */ + model: string; + }; /** * ResponsesAPIRequestParams * @description TypedDict for request parameters supported by the responses API. @@ -44188,6 +44246,7 @@ export interface components { } | null; /** Model */ model: string; + moderation?: components["schemas"]["ResponsesAPIModeration"] | null; /** Parallel Tool Calls */ parallel_tool_calls?: boolean | null; /** Partial Images */ @@ -50745,6 +50804,8 @@ export interface components { cost_per_second?: number | null; /** Custom Llm Provider */ custom_llm_provider?: string | null; + /** Daily Reset Time */ + daily_reset_time?: string | null; /** Default Api Key Rpm Limit */ default_api_key_rpm_limit?: number | null; /** Default Api Key Tpm Limit */ @@ -50995,6 +51056,8 @@ export interface components { regional_processing_uplift_multiplier_us?: number | null; /** Responses Api Version */ responses_api_version?: string | null; + /** Rpd */ + rpd?: number | null; /** Rpm */ rpm?: number | null; /** S3 Access Key Id */ @@ -51047,6 +51110,8 @@ export interface components { token_exchange_profile?: string | null; /** Token Exchange Scope */ token_exchange_scope?: string | null; + /** Tpd */ + tpd?: number | null; /** Tpm */ tpm?: number | null; /** Use Chat Completions Api */ @@ -59849,6 +59914,8 @@ export interface operations { purpose?: string | null; limit?: number | null; after?: string | null; + after_id?: string | null; + before_id?: string | null; }; header?: never; path?: never; @@ -66975,6 +67042,7 @@ export interface operations { } | null; /** Model */ model: string; + moderation?: components["schemas"]["ResponsesAPIModeration"] | null; /** Parallel Tool Calls */ parallel_tool_calls?: boolean | null; /** Partial Images */ @@ -67070,7 +67138,16 @@ export interface operations { }; get_response_openai_v1_responses__response_id__get: { parameters: { - query?: never; + query?: { + /** @description Replay the response's events as server-sent events (OpenAI, Azure, and Azure AI Foundry) */ + stream?: boolean; + /** @description With stream=true, replay only the events after this sequence number */ + starting_after?: number; + /** @description Additional output data to include, forwarded to the provider */ + include?: string[]; + /** @description With stream=true, whether delta events carry obfuscation padding */ + include_obfuscation?: boolean; + }; header?: never; path: { response_id: string; @@ -67086,6 +67163,7 @@ export interface operations { }; content: { "application/json": components["schemas"]["ResponsesAPIResponse"]; + "text/event-stream": string; }; }; /** @description Validation Error */ @@ -70439,6 +70517,7 @@ export interface operations { } | null; /** Model */ model: string; + moderation?: components["schemas"]["ResponsesAPIModeration"] | null; /** Parallel Tool Calls */ parallel_tool_calls?: boolean | null; /** Partial Images */ @@ -70534,7 +70613,16 @@ export interface operations { }; get_response_responses__response_id__get: { parameters: { - query?: never; + query?: { + /** @description Replay the response's events as server-sent events (OpenAI, Azure, and Azure AI Foundry) */ + stream?: boolean; + /** @description With stream=true, replay only the events after this sequence number */ + starting_after?: number; + /** @description Additional output data to include, forwarded to the provider */ + include?: string[]; + /** @description With stream=true, whether delta events carry obfuscation padding */ + include_obfuscation?: boolean; + }; header?: never; path: { response_id: string; @@ -70550,6 +70638,7 @@ export interface operations { }; content: { "application/json": components["schemas"]["ResponsesAPIResponse"]; + "text/event-stream": string; }; }; /** @description Validation Error */ @@ -76765,7 +76854,9 @@ export interface operations { query?: { call_endpoint?: boolean; }; - header?: never; + header?: { + "x-litellm-call-id"?: string | null; + }; path?: never; cookie?: never; }; @@ -79041,6 +79132,8 @@ export interface operations { purpose?: string | null; limit?: number | null; after?: string | null; + after_id?: string | null; + before_id?: string | null; }; header?: never; path?: never; @@ -81237,6 +81330,7 @@ export interface operations { } | null; /** Model */ model: string; + moderation?: components["schemas"]["ResponsesAPIModeration"] | null; /** Parallel Tool Calls */ parallel_tool_calls?: boolean | null; /** Partial Images */ @@ -81332,7 +81426,16 @@ export interface operations { }; get_response_v1_responses__response_id__get: { parameters: { - query?: never; + query?: { + /** @description Replay the response's events as server-sent events (OpenAI, Azure, and Azure AI Foundry) */ + stream?: boolean; + /** @description With stream=true, replay only the events after this sequence number */ + starting_after?: number; + /** @description Additional output data to include, forwarded to the provider */ + include?: string[]; + /** @description With stream=true, whether delta events carry obfuscation padding */ + include_obfuscation?: boolean; + }; header?: never; path: { response_id: string; @@ -81348,6 +81451,7 @@ export interface operations { }; content: { "application/json": components["schemas"]["ResponsesAPIResponse"]; + "text/event-stream": string; }; }; /** @description Validation Error */ @@ -86375,6 +86479,8 @@ export interface operations { purpose?: string | null; limit?: number | null; after?: string | null; + after_id?: string | null; + before_id?: string | null; }; header?: never; path: { diff --git a/uv.lock b/uv.lock index d38e96882d0..5be97af9ed2 100644 --- a/uv.lock +++ b/uv.lock @@ -25,11 +25,13 @@ members = [ ] constraints = [ { name = "aiohttp", specifier = ">=3.14.2,<4.0" }, + { name = "dnspython", marker = "python_full_version >= '3.11'", specifier = ">=2.9.0" }, { name = "httplib2", specifier = ">=0.32.0" }, { name = "packaging", specifier = ">=24.0" }, { name = "setuptools", specifier = ">=84.1.0" }, { name = "soupsieve", specifier = ">=2.8.4" }, { name = "tornado", specifier = ">=6.5.8" }, + { name = "tornado", marker = "python_full_version >= '3.11'", specifier = ">=6.6" }, ] overrides = [ { name = "cryptography", specifier = ">=50.0.0,<51.0" }, @@ -579,7 +581,8 @@ dependencies = [ { name = "python-dotenv" }, { name = "requests" }, { name = "requests-toolbelt" }, - { name = "tornado" }, + { name = "tornado", version = "6.5.10", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.11' or python_full_version >= '3.14'" }, + { name = "tornado", version = "6.6", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.11' and python_full_version < '3.14'" }, ] sdist = { url = "https://files.pythonhosted.org/packages/27/0e/c2e369ad173fb3d76448e46d10beb3dcc53388318933ddf8169a3f21a810/aurelio_sdk-0.0.19.tar.gz", hash = "sha256:14107e7440ff2efd0b4a08c52fb595e7680bd4bc973a0ddfb3b64157c6666b91", size = 15258, upload-time = "2025-03-24T14:37:32.203Z" } wheels = [ @@ -1077,11 +1080,30 @@ wheels = [ name = "bytecode" version = "0.17.0" source = { registry = "https://pypi.org/simple" } +resolution-markers = [ + "python_full_version == '3.14.*'", + "python_full_version == '3.13.*'", + "python_full_version == 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