* fix(anthropic): map pause_turn and return refusal explanations on chat and responses
pause_turn now maps to finish_reason length (Python and Rust) and keeps the raw
stop_reason in provider_specific_fields. Responses reports a paused turn as
incomplete with max_output_tokens and shows the unrun server search as an
in_progress web_search_call instead of a client function_call.
A refusal's stop_details.explanation now fills message.refusal and the final
stream delta.refusal on chat, and becomes a refusal content part on Responses,
streamed or not.
* fix(anthropic): let a chat client resend a paused turn so Claude continues it
* fix(anthropic): replay a paused chat turn without its thinking blocks, and drop its unrun search before a new message
Chat cannot say where Claude wrote each thinking block in a paused web search turn, and
Anthropic answers 400 when one moves but accepts the turn without them. A new message after
a paused turn also 400s on a server_tool_use with no result, so that unrun search is dropped.
* fix(responses): send the streamed refusal part's type and text in content_part.added
* fix(anthropic): keep pause_turn and Claude refusal explanations out of the Messages adapter's text
A paused Claude turn now ends on stop_reason pause_turn instead of max_tokens, streamed or not. A Claude refusal keeps its explanation in stop_details with Claude's category and no longer repeats it as a text block, so a guardrail mask on a streamed refusal is delivered. A paused turn sent back with list content drops its thinking blocks like string content does
* fix(anthropic): replay a paused turn with one unrun search and no thinking on chat and Responses
* fix(responses): report a paused Claude turn as completed so Codex and the Agents SDK keep going
* fix(responses): mark a paused turn's message item completed
* fix(responses): mark every item of a paused turn completed
* fix(responses): keep a refusal's explanation when a refused turn is sent back
A refusal part in a Responses input message now goes to the model as text, so the assistant turn is no longer dropped from the history. The integration test now expects a paused Claude turn on Responses to report completed, and the paused-turn test helper is typed
* fix(responses): scan refusal parts in Responses guardrails
---------
Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
* fix: openai exception mapper ignored status code for invalid_request_error
_map_openai_exception coerced anything whose body carried type
invalid_request_error into BadRequestError, guarded only by excluding the single
phrase Incorrect API key provided, and this ran before the status-code checks.
OpenAI and openai-compatible providers return 401 and 404 bodies with type
invalid_request_error, so an auth failure like Invalid API key mapped to a 400
instead of AuthenticationError, and a 404 mapped to BadRequestError instead of
NotFoundError. That changes the status returned to proxy clients and router
retry, cooldown, and fallback handling. Mirror the Azure mapper by only coercing
to BadRequestError when status_code is None or 400, so 401 and 404 fall through
to their existing handlers.
* fix(exceptions): map OpenAI-family invalid_request_error 404s to NotFoundError
Move the contributor's test to the mapped unit test file, assert the raised
class, status code and message, and cover the 400 and status-less cases that
must still raise BadRequestError
Add a regression test for the flow the bug was found on. Retrieving a missing
OpenAI vector store, sync or async, now raises NotFoundError with status 404
The router test that pinned an OpenAI 404 typed invalid_request_error as
BadRequestError now expects NotFoundError
* fix(a2a): answer a provider NotFoundError as JSON-RPC invalid params
* fix(exceptions)!: limit the invalid_request_error status guard to 401 and 404
Every other status keeps raising BadRequestError as on main, so 402-415, 429 and 5xx bodies typed invalid_request_error keep their class and router retry behavior. A2A goes back to main's mapping, which answers NotFoundError and AuthenticationError as JSON-RPC internal errors.
* fix(exceptions): keep the provider error fields on mapped 401 and 404 invalid_request_errors
Raise AuthenticationError and NotFoundError straight from the invalid_request_error
branch with the provider body, so code, param and type survive and the proxy's
error.type matches main. The Rust mapper copy skips 401 and 404 the same way.
---------
Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
* fix(vertex_ai): drop the caller's anthropic-version header on Claude /v1/messages
Vertex reads the API version from the body's anthropic_version and answers 400 when a forwarded anthropic-version header names a different one, which anthropic SDK 2.x always does. Strip the header on the Python and LITELLM_RUST Vertex messages routes.
* fix(vertex_ai): carry the caller's anthropic-version into the Claude /v1/messages body
Vertex reads the API version from the body alone, so the caller's
anthropic-version header now becomes the body's anthropic_version instead
of a pinned vertex-2023-10-16. The 2023-01-01 and 2023-06-01 first-party
versions keep vertex-2023-10-16, and the header itself is still never sent.
Same change on the Python proxy and the Rust gateway.
* fix(vertex_ai): follow drop_params for an anthropic-version Vertex does not accept
Only versions Vertex accepts in the body (vertex-2023-10-16, 2026-10-21) are
carried into anthropic_version. 2023-06-01, 2023-01-01, a blank header, or no
header keep vertex-2023-10-16. Any other value drops to vertex-2023-10-16 under
drop_params and answers a 400 naming drop_params without it, on the Python proxy
and the Rust gateway.
* refactor(vertex_ai): return the unsupported anthropic-version error as a value and keep Rust helpers and tests in place
* fix(rust gateway): resolve os.environ drop_params and accept the same flag words as Python
The gateway read drop_params: os.environ/NAME and words like yes as off, so the drop_params opt-out from the new anthropic-version 400 did not work there
* docs(rust router): name Router::from_config in the crate README
---------
Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
* feat(providers): add ZeroGPU as an OpenAI-compatible provider
Registers zerogpu through the JSON provider registry so zerogpu/<model> routes to
https://api.zerogpu.ai/v1/chat/completions with ZEROGPU_API_KEY and an optional ZEROGPU_API_BASE.
Adds LlmProviders.ZEROGPU, the constants.py provider and endpoint lists, cost map entries for the
10 ZeroGPU text generation models, the endpoint matrix, the Add Model form fields, the README row
and the dashboard provider entry
* feat(zerogpu): add capability flags verified against the live API
Live calls to https://api.zerogpu.ai/v1/chat/completions confirmed tools, tool_choice and json_schema
response_format on 8 of the 10 catalog text models, cached token reporting on deepseek-v4.1-flash,
gpt-4.1-mini, gpt-5.4-nano and gpt-5.6-luna, and reasoning_effort on gpt-5.6-luna. LFM2.5-1.2B-Instruct
answers stream requests with plain JSON instead of SSE and LFM2.5-1.2B-Thinking returns 500 on every
request, so both stay out of the cost map until the API serves them correctly
* feat(zerogpu): price LFM2.5-1.2B-Instruct
Adds zerogpu/LFM2.5-1.2B-Instruct to the cost map with the catalog prices and context window. It
gets no capability flags because the live API ignores tools, response_format and
max_completion_tokens for this model, so LiteLLM drops tool params for it instead of sending them.
LFM2.5-1.2B-Thinking stays out of the cost map
* fix(zerogpu): reject transcription requests before calling the upstream API
ZeroGPU only serves chat completions, so drop it from the OpenAI transcription transport set. A zerogpu transcription request now fails locally instead of hitting an /audio/transcriptions endpoint that does not exist
* test(zerogpu): cover the responses and messages bridges
Both endpoints reach ZeroGPU through chat completions, so assert the request each one sends upstream and the reply it returns
* refactor(zerogpu): move zerogpu out of the provider list tails
New upstream providers append to the end of openai_compatible_endpoints, openai_compatible_providers and providers.json, so an entry at the tail conflicts with every one of them. Placing zerogpu next to long-stable entries keeps those merges clean. No behavior change
* fix(zerogpu): price cached input for qwen3-30b-a3b-fp8
The ZeroGPU model catalog (https://docs.zerogpu.ai/docs/model-catalog, checked 2026-10-09) lists cached input for qwen3-30b-a3b-fp8 at $0.05 per 1M tokens. Without cache_read_input_token_cost, cached tokens were billed at the full $0.10 input rate
* revert(zerogpu): leave the audio transcription provider set unchanged
Per review, keep OPENAI_AUDIO_TRANSCRIPTION_PROVIDERS as upstream defines it. This PR only covers chat completions, and ZeroGPU now serves /audio/transcriptions anyway, so the local refusal and its test are removed
* fix(zerogpu): add max_tokens so trim_messages can size ZeroGPU history
trim_messages reads max_tokens as the fallback for max_input_tokens and evaluates it eagerly, so without it the lookup raised, got swallowed, and the full history came back untrimmed. max_tokens matches each model's maxTokens in ZeroGPU's models API (https://api-dashboard.zerogpu.ai/api/models, checked 2026-10-10)
* test(zerogpu): record mocked requests on a recorder object
The mock handler appended to a list the caller passed in, which AGENTS.md
forbids. A recorder now owns the captured requests as a tuple
* fix(zerogpu): cap max_tokens at each model's output limit
Each cap is the max_output_tokens ZeroGPU stores for the model in its production models table (read 2026-10-20), the same column its /v1/models serves as max_length. That gives 65536 for deepseek-v4.1-flash, 32768 for gpt-4.1-mini and gpt-oss-120b, 128000 for gpt-5.4-nano and gpt-5.6-luna, 8192 for LFM2.5-1.2B-Instruct and llama-3.1-8b-instruct-fast, and 16384 for qwen3-30b-a3b-fp8. glm-5.3-flash is stored as 32786, which reads as a typo for 32768, so that row uses 32768
trim_messages sizes history from max_input_tokens, so lowering max_tokens leaves it unaffected
* fix(zerogpu): flag prompt caching on glm-5.3-flash
Repeating the same ~4.3K-token prompt against ZeroGPU on 2026-10-20 returned cached_tokens of 4320 on some glm-5.3-flash calls. gpt-oss-120b and llama-3.1-8b-instruct-fast returned 0 on all nine calls, and qwen3-30b-a3b-fp8 never returned cached_tokens, so they stay unflagged. Their cached prices stay as ZeroGPU publishes them, so any cache hit is still billed at the right rate
* fix(zerogpu): set gpt-5.4-nano context window to 272000
ZeroGPU accepts a 271001-token gpt-5.4-nano prompt and rejects 273000 tokens as over the context window (checked 2026-10-21), so max_input_tokens is 272000 rather than the 400000 its catalog lists
* fix(zerogpu): list zerogpu models for zerogpu/* wildcards
zerogpu had no models_by_provider entry, so get_provider_models("zerogpu") returned None and a zerogpu/* wildcard listed no models. zerogpu_models is now filled from the cost map rows like openinfer_models and registered in models_by_provider
* fix(zerogpu): flag gpt-5.4-nano as a reasoning model
ZeroGPU honors reasoning_effort on gpt-5.4-nano (checked 2026-10-21). Without it the model spends 0 reasoning tokens, and with low or high it spends 32 or more. LiteLLM only treated it as a reasoning model by falling back to OpenAI's bare gpt-5.4-nano row, so get_model_info and /model/info reported supports_reasoning as null. The row now carries the flag itself
* fix(zerogpu): flag deepseek, glm, gpt-oss and qwen3 as reasoning models
ZeroGPU's /v1/models marks these four as reasoning models and accepts reasoning_effort on all of them (checked 2026-10-21), but LiteLLM rejected the param with UnsupportedParamsError because their rows had no supports_reasoning flag. glm reports reasoning_tokens under reasoning_effort, and gpt-oss and qwen3 spend hidden reasoning tokens on every reply. The gpt-oss test case now expects reasoning_effort to reach ZeroGPU
* fix(zerogpu): set gpt-oss-120b context window to 128000
ZeroGPU routes gpt-oss-120b across several upstream backends, and at least one of them returns 413 past a 128000-token window, so max_input_tokens uses that as the safe floor. The backends reached on 2026-10-21 accepted up to about 131K prompt tokens, so this only gives up a little headroom on the larger ones
* feat(zerogpu): call ZeroGPU's Responses API natively
ZeroGPU serves /v1/responses for all nine catalog models, so LiteLLM no longer bridges Responses requests through chat completions. Native calls return ZeroGPU's reasoning output items for glm, gpt-oss and qwen3, which the bridge dropped. Checked live on 2026-10-22 through litellm.responses for every model, non-streaming and streaming, plus a gpt-oss tool call. LFM2.5-1.2B-Instruct streams correctly now that ZeroGPU's text_generation lane emits Responses SSE
* fix(zerogpu): stop inferring the zerogpu provider from api_base alone
Listing https://api.zerogpu.ai/v1 in openai_compatible_endpoints rerouted bare model names on that api_base from openai to zerogpu. A bare gpt-5.6-luna call with verbosity used to return 200 and started raising UnsupportedParamsError. Drop the entry and its api_base-alone test, so zerogpu is only selected through the zerogpu/ prefix
* fix(zerogpu): price gpt-6-luna, llama-3.2-3b, LFM2.5-1.2B-Thinking and qwen3.6
A zerogpu/* wildcard served these four chat models with no cost-map row, so their calls logged $0 spend. Add rows at ZeroGPU's catalog prices from https://api-dashboard.zerogpu.ai/api/models, with context windows and output caps from ZeroGPU's models table. LFM2.5-1.2B-Thinking has no cached price, like LFM2.5-1.2B-Instruct. gpt-6-luna is flagged supports_reasoning because LiteLLM already routes gpt-6 names as reasoning models. Checked live on 2026-10-28, all four now report nonzero response_cost
* fix(zerogpu): drop the retired max_tokens field from the zerogpu rows
Upstream #48471 retired max_tokens from the cost map in favor of max_input_tokens and max_output_tokens, and test_no_row_carries_the_retired_max_tokens_field failed on all 13 zerogpu rows. Every row already carries the same value in max_output_tokens, so nothing is lost. The zerogpu limits test now checks that each row's output limit fits its context window
* chore(zerogpu): regenerate provider endpoint support for zerogpu
Upstream #48619 generates provider_endpoints_support.json from the cost map and checks it in CI, and the hand-written zerogpu entry no longer matched. Regenerated with scripts/generate_provider_endpoints_support.py. Only the zerogpu entry changed, and it now matches what the generator emits for other JSON-registry providers such as openinfer
* fix(zerogpu): flag tools, json_schema and prompt caching on gpt-6-luna
ZeroGPU serves function calling, tool_choice, json_schema response_format and prompt caching on gpt-6-luna, so set supports_function_calling, supports_tool_choice, supports_response_schema and supports_prompt_caching on its row in both cost maps. Checked live on 2026-10-28, a weather tool call came back with the right arguments, json_schema output validated, and repeated prompts reported 3260 of 3263 tokens cached
* fix(zerogpu): set qwen3.6-35b-a3b context to 262144 and flag its tools and reasoning
ZeroGPU accepts up to 262,144 input tokens on qwen3.6-35b-a3b and serves tools, tool_choice, json_schema response_format and reasoning_effort on it. Raise max_input_tokens from 16384 and set supports_function_calling, supports_tool_choice, supports_response_schema and supports_reasoning in both cost maps. Before this, LiteLLM rejected tools and reasoning_effort for the model. Checked live on 2026-10-28, a 209,905-token prompt succeeded, an oversized one was refused with a 262144-token limit, and tool calls, json_schema output and reasoning_effort all worked
* fix(zerogpu): flag vision on gpt-6-luna and qwen3.6-35b-a3b
ZeroGPU reads image inputs on gpt-6-luna and qwen3.6-35b-a3b, so set supports_vision on both rows in both cost maps. Checked live on 2026-10-28, both models named the animal in an image_url photo, and the image showed up in their prompt token counts
* feat(rust): one typed decline from core up to each host
Rust core says it cannot serve a request with one Decline that travels
unchanged through llms and inference up to the host. The Python bridge
raises RustBridgeDeclined for it in route_failure before the public
exception mapping, so dispatch falls back to legacy Python instead of
failing the call, and the gateway answers 501. Every route collapses
errors after the send with Error::after_send, which keeps a provider
answer and a response fault as they are and nests anything else as the
source of an invalid response, so a billed call can never read as a
decline. Response-side cases that used to decline are now
ErrorDetail::Unhandled response faults.
The rust-error skill documents declined() as the first question both
boundaries ask, and the Python suites pin that a native decline reaches
the dispatcher before any provider IO.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
* fix(rust): keep post-provider hook failures terminal
---------
Co-authored-by: Claude Opus 5.5 <noreply@anthropic.com>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* build(rust): upgrade reqwest to 0.13 and move MCP out of litellm-http
The workspace moves to reqwest 0.13, so litellm-http no longer carries a
second reqwest just for rmcp. The mcp feature, its pool and its proxy
conversion go away, and the gateway hands rmcp a pooled NoRedirect client
that already carries the TLS, proxy and timeout settings
The Client test helpers collapse into for_test, a no-redirect client
without TLS or proxy settings, and wrap_for_test for the few tests that
need a hand-built reqwest client
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
* fix(http): honor transport settings for Rust WebSockets
The Responses WebSocket connected through tokio-tungstenite with its own
native-roots TLS, so it ignored the configured CA bundle, verify flag,
client certificate, proxies and timeouts. The handshake now goes through
a pooled reqwest client (ClientVariant::WebSocket, HTTP/1.1, no
redirects) and upgrades the response, so it shares the settings every
other outbound request uses
The upgrade response is checked for the Sec-WebSocket-Accept key, the
Upgrade and Connection headers and a subprotocol that was offered
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
* refactor(http): build outbound requests as reqwest::Request
OutboundRequest was a hand-rolled copy of reqwest::Request. Routes now build
a reqwest::Request directly and RequestSigner reads the body bytes back out
of it, so the signer still covers exactly what is sent. SigV4 signing moves
onto HeaderMap and takes the method, which drops the BTreeMap plumbing and
the header casing table
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
* refactor(http): make litellm_http::Error the one opaque error
transport::Error and media::Error fold into litellm_http::Error, an
Arc<Repr> newtype whose private variants keep the typed reqwest, io,
rustls and tungstenite causes and own every message. Callers can no
longer build an error with a message of their own. They ask through
dispatched, is_request, status, upstream_response and tls_source
One From<reqwest::Error> now classifies connect, network and timeout
and strips the URL. The WebSocket handshake reports each failed check
as its own variant and owns its connect timeout. OCR drops the media
variants it mirrored, and inference::Error maps a header the signer
computes to Unsupported for every route, not only chat
The error rules move out of AGENTS.md into the rust-error skill, which
also records the decisions behind this design
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
* docs(rust): split rust-error skill into thin SKILL.md with references
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
* refactor(rust-error): render causes once and ask predicates at the boundaries
The four WebSocket handshake variants collapse into Handshake(HandshakeFault), and media download failures no longer answer dispatched() since they happen before the provider call
ErrorDetail in llms and auth-types, the inference error and the OCR error now store their cause in a field named cause with no #[source], so to_string() carries it exactly once and source() is None. Tests that walked the chain now destructure the variant and downcast the cause
The gateway asks is_unsupported() and is_missing_credential() on the inference and OCR errors instead of matching through nested enums, and litellm_auth::Error answers is_missing_credential() for both
The rust-error skill gains axum and pyo3 references, boundaries.md describes the real predicate order and the known divergences, the testing example asserts dispatched() correctly, and shape, classification, conversions, messages-and-causes and recipes agree with the code again
* docs(rust): focus the rust-error gateway page on the error flow and add a rust-gateway skill
The former axum page toured gateway-inference: its status match, the envelope
table, an extractor, the unsupported route and the Sse closure. Those details
belong to the gateway crates and go stale with them. The page is now gateway.md
and follows an error from the provider failure through each From into
IntoResponse, where it is classified once and rendered by surface and framing.
The gateway-structure material moves to a new rust-gateway skill: envelopes per
API surface, extractors and path registration, SSE relay, and the router test
harness.
* test(inference): pin provider URL redaction on every route's transport error
Chat, Messages, Responses and transcription each get a route-level test that
fails if a reqwest error reaches the caller with its URL. The Messages stream
decoder also takes body errors through litellm_http::Error like every other
reqwest error
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
* docs(rust-error): adopt std source chains and add litellm-error Report
Messages describe their own layer and the cause is the source, boundaries
render the chain once with litellm_error::Report. Corrects skill claims
the audit found stale against the code.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
* refactor(rust-error): keep causes as sources across http, auth, secrets, cache and utility crates
Messages describe their own layer and every cause is a typed source,
predicates match exhaustively, and boundaries render with
litellm_error::Report. Media downloads no longer count as dispatched,
Error::upstream bounds the provider body itself, and a forwarded
header SigV4 cannot sign is the caller's fault.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
* refactor(rust-error): keep causes as sources in llms and the gateway crates
ErrorDetail loses its string variant, OCR provider variants become data,
host faults stop counting as the caller's, a tunnelled transport error
classifies the same on every stream path, and each gateway crate has one
Error with one status() and extractors that reject in its envelope.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
* refactor(rust-error): nest llms errors in inference and ask predicates in route tests
litellm_inference::Error nests litellm_llms::Error instead of mirroring
its variants, host driver faults get their own variant, every predicate
matches exhaustively, and route tests ask predicates instead of matching
transport variants.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
* refactor(rust-error): map bridge and gateway-inference errors once and render them with Report
RustUpstreamError has one constructor that always sets headers, argument
checks raise typed errors mapped once, OCR asks upstream_response(), the
Responses stream error event comes from the error type, gateway-inference
loses its string variants, and auth faults classify through one
litellm_auth predicate on every route.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
* fix(rust-error): carry OCR provider headers as a HeaderMap and keep outages off the caller
The OCR provider error and get_error_class take reqwest's HeaderMap, the
bridge turns it into Python's (name, value) pairs once. Credential
acquisition and provider SDK failures are no longer the caller's fault,
the UI hides auth and backend causes, and chat keeps a provider answer
as is.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
* docs(rust-error): correct skill claims against the aligned code
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
* refactor(rust-error): fix the remaining sweep findings in gateway, llms, auth and cache crates
Auth rejections hide their backend cause on every inference renderer,
path parameters reject in the surface envelope, Textract's unsupported
document and Azure DI's unparseable poll URL get typed variants, the
credential chain exposes its last failure as the source, gateway-mcp
asks predicates over rmcp errors, and the S3 and Azure blob transports
classify through litellm_http::Error.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
* refactor(rust-error): fix the remaining sweep findings on the Python side
host-python keeps a native error's chain and returns blocking-pool
cancellation instead of panicking, Vault transport failures convert
through litellm_http::Error so no URL reaches Python, the bridge asks
predicates instead of matching three levels into Vault errors, and the
last string-built PyErrs become typed errors mapped once.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
* build(deps): refresh compatible dependencies flagged by OSV
* refactor(rust): remove redundant client construction comment
* test(rust): cover configured MCP proxy and CA bundle
* fix(http): preserve native WebSocket trust and optional protocols
* fix(http): allow plain WebSockets without native roots
* fix(http): normalize provider URLs before building outbound requests
* fix(rust): preserve OCR download status and reduce error size
* fix(rust): preserve upstream bodies and bound diagnostics only
* test(rust): preserve bridge serialization boundary in body regression
---------
Co-authored-by: Claude Opus 5.5 <noreply@anthropic.com>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(http_handler): name the timeout phase and the limit that fired instead of 'after None seconds'
Every HTTP verb on both handlers raised litellm.Timeout with the per-call
timeout argument interpolated into the message, which is None whenever the
caller relied on the client default, and always said "Connection" even for a
read timeout. One helper now reads the limit httpx actually enforced from the
failed request and names the phase that fired
Fixes#14635
* fix(rust_bridge): name the timeout phase in the vault timeout message to match the httpx handler
* fix(http_handler): drop the unreachable timeout fallbacks httpx already rules out
* refactor(rust_bridge): drop a doc comment that restated the timeout helper
* feat(openinfer): add OpenInfer as OpenAI-compatible provider
Register OpenInfer in the JSON provider registry with catalog models,
proxy create fields, and unit coverage so requests route via openinfer/
Co-authored-by: Cursor <cursoragent@cursor.com>
* fix(openinfer): assert catalog invariants instead of vendor rates
Pinning per-token prices made CI fail when the vendor list changed. Keep
the backup agreement and positivity checks our code owns.
Co-authored-by: Cursor <cursoragent@cursor.com>
* fix(openinfer): add openinfer to the Rust OpenAI-compatible provider mirror
* fix(openinfer): align catalog with OpenInfer's live /v1/models
Replace the four catalog rows with the two models OpenInfer serves and
publishes a price for (@oi/GLM-5.3-Flash, @oi/Qwen3.5-27B), using its
listed per-token rates and context windows, and price-check them in tests
* fix(openinfer): use OpenInfer's native Responses and Messages APIs, allow tools on unpriced models, price Qwen3.5-9B
Declare /v1/responses and /v1/messages for openinfer, since OpenInfer serves both natively. Let JSON providers declare provider-wide capabilities in providers.json, read through get_provider_info, so tool calls reach OpenInfer for models without a cost map row. Send max_completion_tokens as is, set output caps to each model's context window, mark the three rows as reasoning models, add Qwen3.5-9B at its listed rate, and wire openinfer into models_by_provider so the openinfer/* wildcard lists its models.
* fix(openinfer): let a model's own capability row win over provider defaults in get_model_info
Provider defaults now only fill capability fields the cost-map row leaves unset, so a row or deployment that turns function calling off stays off. Also marks openinfer_models as Final.
---------
Co-authored-by: Cursor <cursoragent@cursor.com>
Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
* feat(edenai): settle native Messages reported cost
* test(rust): add live EdenAI Messages contract cases
* refactor(rust): settle call cost once as an ExecutionFacts variant
The route now decides Cost (Reported, CacheHit or Deferred) from the
result source and the provider's reported figure. The legacy callback
adapter only projects a Reported amount onto provider_reported_cost and
no longer writes response_cost, which the Python calculator derives
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
* refactor(rust): keep EdenAI wire shaping independent of Invoke
* style(rust): format cost settlement imports
* fix(rust): trust provider costs without bypassing configured pricing
* fix(rust): clear untrusted response costs before spend settlement
---------
Co-authored-by: Claude Fable 5.1 <noreply@anthropic.com>
* feat(rust): support Claude Platform and Mantle Messages
* fix(ci): regenerate .greptile/files.json
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(bedrock): preserve Mantle body betas
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(bedrock): resolve Mantle default region
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(bedrock): prefer regional endpoint host regions
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* style(rust): format Bedrock regression tests
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
---------
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* feat(rust): add the DeepSeek Anthropic Messages config
* refactor(rust): drop the tool discriminator without mutation and use rstest in DeepSeek tests
* refactor(rust): derive strum VariantArray and string conversions
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* refactor(rust): use strum conversions directly with explicit spellings
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(rust): use rstest values for key management systems
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
---------
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* refactor(rust): prepare inference and auth foundations
* fix(rust): keep textract operations parsing from kebab-case model names
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
---------
Co-authored-by: Yujong Lee <yujong@berri.ai>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(rust): encode anthropic response serialization shape as rstest cases
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
* feat(rust): shape Anthropic Messages requests natively
The Rust Messages route only relayed the body. It now runs the request shaping
the Python handler does for the direct Anthropic provider: history sanitizers
(empty blocks, tool ids, replayed web search results, provider_specific_fields,
encrypted reasoning, advisor blocks), reasoning_effort and adaptive/legacy
thinking translation against the model's capability flags, the sampling and
speed gates under drop_params, the metadata allowlist, additional_drop_params,
reasoning auto summary, OAuth and ANTHROPIC_AUTH_TOKEN credentials,
provider_specific_header merging and anthropic-beta injection. Capability flags
and LiteLLM settings reach Rust through route_host.shaping(). A request the
route rejects before the call now maps to BadRequestError instead of
APIConnectionError
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
* test(rust): port Anthropic Messages shaping tests and pin comment contracts as cases
Every Python unit test that exercises the ported shaping for the direct
Anthropic provider now has a named rstest counterpart, and every comment that
stated a behavior contract is deleted in favor of a case that pins it. Measured
with cargo-mutants over the touched files, all viable mutants are caught
Porting the tests surfaced parity gaps, fixed here to match Python: every
casing of a forwarded anthropic-beta header is merged, replayed web search
results are rewritten from their own block (an empty result keeps its slot and
a server_tool_use with a non-string query stays), an empty output_config.effort
falls back to medium, speed and reasoning effort errors quote values the way
Python does, additional_drop_params apply after metadata validation and the
auto summary and never touch model or messages, and a non-string
metadata.user_id is rejected before the call
* fix(rust): resolve Messages credentials through the secret source and scope headers by resolved provider
The native Messages route read ANTHROPIC_API_KEY, ANTHROPIC_AUTH_TOKEN and the
base URL straight from the process environment, so a key or base held in a
configured secret manager was never found. Each provider config now declares
its secret names and the route resolves them through the same SecretSource the
OCR route uses, with the Python bridge passing in litellm's configured manager
provider_specific_header entries were scoped by the explicit
custom_llm_provider only, falling back to anthropic, so an azure_ai/ model
lost its azure_ai scoped headers. Scoping now happens in the route after the
provider is resolved from the model, as Python's handler does
The Azure config now adds the same anthropic-beta feature headers Python's
Azure route adds, and the metadata allowlist, reasoning auto summary and
history sanitizers move from the core route into the llms crate, mirroring
their home in Python's messages handler
* test(rust): escape the dot in the metadata.user_id match pattern
* refactor(rust-bridge): project Messages capabilities without mutable dicts
The capability flags and effort tiers were built as dict comprehensions,
which the type-discipline gate counts as mutable construction, and the
asdict call carried a mutable-ok suppression that suppressed nothing. The
flags are now passed one by one and the effort tiers are a frozen dataclass,
which asdict projects to the same map the native side reads
---------
Co-authored-by: Yujong Lee <yujong@berri.ai>
Co-authored-by: Claude Opus 5.5 <noreply@anthropic.com>
* feat(logger): add shared Rust diagnostics and Python logging bridge
* feat(logger): dispatch diagnostic processing through Rust
* chore: regenerate Cargo.lock after rebase
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test: allowlist bounded logging tree walkers in recursive detector
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* perf(logger): skip decoding plain access arguments
* test(logger): skip embedded-python logger test when litellm deps are absent
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* style: cargo fmt
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test: expect NativeDiagnosticProcessor in the native public surface
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(stub): export NativeDiagnosticProcessor via __new__ in _native.pyi
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* refactor(tracing): rename logger crate and document host sink contract
* test(logger): cover exc, stack, and nested extras in the diagnostic filter
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(logger): keep rendered redacted line when template scan flags a key pattern
The blanket REDACTED for a changed msg/color template discarded lines
whose rendered form was already redacted by the same pipeline, e.g.
'password=%s' became 'REDACTED' instead of 'password=REDACTED'. Only
fall back to REDACTED when the rendered form did not change either,
which is where interpolation can mangle the key pattern the scrub
would otherwise see.
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* ci(rust): install python deps so the logger bridge test runs
The end-to-end bridge test skipped silently when litellm's Python deps
were absent. uv sync --no-install-project installs them without a
maturin build, and PYTHONPATH makes them visible to the embedded
interpreter
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
---------
Co-authored-by: Yujong Lee <yujong@berri.ai>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* docs(rust): plan Python interop foundation
* fix(rust): preserve Python settings coercion at the native boundary
* chore(rust): drop interop planning note
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* feat(rust): resolve OCR provider secrets through an async SecretSource before transformation
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* feat(rust): project the Python secret manager into the bridge and resolve OCR secrets through it
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* refactor(rust): drop premium_user from the secret manager snapshot
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(rust-bridge): read the private key management globals once in the settings snapshot
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(rust): bound the bridge secret manager state cache to the active snapshot
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(rust): inline coercion unit tests
* fix(rust): preserve Python secret manager bindings
* refactor(rust-bridge): let settings projectors own their contract specs
Each settings group now declares its SettingSpec rows next to the projector
that reads them, and the manifest test derives python_settings.json from those
tables instead of a hand-copied duplicate. Field carries (group, name) instead
of a dotted path, and coercion gains the dict-item reader plus the Redis
Boolean, certificate-requirement, non-empty string, and numeric adapters that
the cache configuration projection adopts next.
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
* refactor(rust-bridge): capture the secret manager binding in one settings read
The secret_manager accessor now carries the live client and settings objects,
so the bridge classifies the binding from a single snapshot instead of
re-reading litellm globals. The unreachable native arm and the service alias
go away, the binding-to-state mapping moves next to the snapshot, and the
Python callback precomputes its key_manager name.
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
* refactor(rust-bridge): execute typed settings field declarations
* refactor(rust-bridge): compare cache backends by identity behind one exact trait
cache-response gains an object-safe ExactResponseCache so every exact-match
backend sits behind one pointer; WriteBuffer flushes through it. The bridge's
NativeResponseCache shrinks from nine variants and fifteen per-backend
accessors to an exact service plus the three semantic backends, and facade
mismatch detection compares BackendIdentity values instead of matching on
each backend type. Request projections move next to NativeRequest.
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
* refactor(rust-bridge): drive both Python-embedded semantic caches through one execution
Redis-semantic and Valkey-semantic operations now share one SemanticExecution
body: await the Python embedder, seed the task-local vector, run the native
backend, repeat per batch entry. Valkey drops its with_embedder path in favor
of the same seeded embedder, and each backend keeps its own embedding-failure
policy. PythonEmbedder exposes one call shape. Redis-semantic thresholds are
compared at the backend's f32 width, which un-breaks the redis-stack parity
tests that a 0.8 facade threshold failed before this branch.
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
* wip
* feat(rust-bridge): complete response cache runtime surface
* fix(rust-bridge): preserve secret manager callback exceptions
* refactor(rust-bridge): unify route cache and secret rollout catalog
---------
Co-authored-by: Yujong Lee <yujong@berri.ai>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
Co-authored-by: Claude Fable 5.1 <noreply@anthropic.com>
Settings sources beyond HTTP (media fetch, Azure Document Intelligence,
Vertex, timeouts) need the same env lookup and precedence merge, so move
them out of litellm-http into core_utils::settings. Lookup readers name the
Python idiom they mirror: get keeps a present empty value like
os.getenv(X, fallback), truthy drops it like an `or` chain, enabled only
switches on for "true". SSL_CERT_FILE now reads through truthy, matching
Python's `if ssl_cert_file and ...` check.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Rebuild exception_type around text rules per provider family and one shared
status table. The mapper takes the context, an injected redactor and the
original failure, and returns a PublicError with the message, the real
upstream response and the debug text. Every divergence from the Python
mapper and every known gap is listed in the module header
Match Python on a standalone 429 with an unknown status and on Cohere's
rules for failures without a status. Drop python_repr and the unread
public_failures fixtures
Adds a Rust port of litellm_core_utils/exception_mapping_utils.exception_type
with its provider rule tables (OpenAI-compatible, Cohere, Vertex AI), the
secret redaction patterns from secret_redaction.py, and a Python repr helper
for messages that quote caller values.
The public failure shapes are pinned by golden JSON fixtures under
tests/test_litellm/rust_bridge/fixtures/public_failures, which the Python
side reads too once the bridge is wired to this module. Nothing calls the
port yet.
OCR transformations, BaseOcrConfig with its response and connection types,
the OCR error, and the HTTP pieces (custom_httpx: http_handler, transport,
media, llm_http_handler with OcrClient and the request/response handler)
now live in litellm-llms at their Python paths. Provider code no longer
reaches into the route: it gets the caller's hooks through a route-neutral
CallHooks trait that core implements over its host, and core dispatches to
llm_http_handler::ocr with the concrete config, the way Python calls
base_llm_http_handler.ocr(provider_config=...).
Core keeps the route: entrypoint, request types, credential fallback,
provider dispatch, the machine and hook glue. ocr/mod.rs no longer
re-exports anything, provider constants moved next to their only users,
and provider tests that drive the whole route moved to core's route test
files. Twenty-two of those were exact copies of tests already there and
were dropped; every one still runs once.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
litellm-types mirrors litellm/types (chat, Anthropic Messages and Responses
websocket data) and litellm-core-utils mirrors litellm/litellm_core_utils
(provider resolution, prompt factory, core helpers, call arguments). Route
request types move up to their core route module, the transform contracts
move into base_llm, and the three duplicated provider error enums become one
Error in base_llm/chat/transformation.rs, mirroring BaseLLMException.
The empty-text placeholder goes back to the value Python's factory.py uses;
the provider extraction had changed it to a single space.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
