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49 commits
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0de1825450
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fix(health): honor allow_requests_on_db_unavailable in readiness probe (#37640)
* fix(health): honor allow_requests_on_db_unavailable in readiness probe Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(health): bound readiness DB check and pass reconnect timeout Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(health): bound whole readiness DB check with one deadline Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(health): keep readiness deadline fallback within lint budgets Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(health): suppress TQ008 for proxy-global readiness patches Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(db): release reconnect lock when a waiting reconnect is cancelled Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> --------- Co-authored-by: milan <milan@berri.ai> Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> Co-authored-by: yassin <yassin@berri.ai> |
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d392e7faae
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feat(alerting): add native Microsoft Teams alerting destination (#38367)
* feat(alerting): add native Microsoft Teams alerting destination Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(alerting): preserve active destinations on MS Teams save and confirm health test delivery Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(ui): read persisted alerting destinations at MS Teams save time Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> --------- Co-authored-by: yassin <yassin@berri.ai> Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> |
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43ae3507e0
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Merge pull request #37090 from Siraj637909/fix/gh-36898-health-leak-extra-headers
fix(health): strip credential fields from GET /health output |
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50f69a3a81 | fix(health): strip client_secret, azure_ad_token, and other credential fields from /health output | ||
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8a2fc2cc9f | Merge remote-tracking branch 'origin/litellm_internal_staging' into fix/gh-36898-health-leak-extra-headers | ||
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8ff832901b | fix(health): accept image_edit mode on /health/test_connection | ||
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458a63935f |
test(health): guard that test_connection authorizes on post-merge probe params
Add an endpoint-level regression test asserting can_user_make_model_call receives the litellm_params after health_check_params are merged in, so the merge-before-auth ordering cannot silently regress and let a request smuggle a field past authorization. |
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6a0d03914c
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test: drop the cwd-relative sys.path.insert calls from the test suite (#37802)
* test: drop the cwd-relative sys.path.insert calls from the test suite
TQ003 stands at 1,077 across 1,058 files, and 1,015 of them are the same shape:
sys.path.insert(0, os.path.abspath("../..")) and its deeper siblings. The
argument resolves against the working directory rather than the file, so from
the repo root, where every job runs pytest, it inserts the directory two levels
above the checkout. It has never pointed at litellm. The package is installed
into the environment anyway, which is what actually makes the import work, and
what the rule's message has said all along.
Removing them leaves 1,634 imports of sys and os with no remaining reference,
and those go too, except where another test module imports the name back out of
the file. The rest of TQ003 is 62 call sites that resolve against __file__ or a
variable, which are a different question and are left alone.
Collection is identical either way: 45,871 tests and the same 51 pre-existing
collection errors before and after, and ruff reports no new undefined name.
* test: drop the duplicate imports the sys.path sweep exposed to F811
* test(pre-call-utils): restore the os import the new bedrock tests need
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e9d40a8f73 |
test: enforce F811 so a duplicate definition cannot silently replace the first
A name bound twice keeps only the second binding. In `tests/` that is nearly always a repeated import, harmless but misleading, and the same rule is what catches the cases that are not harmless: a local that shadows an import the module still calls, and a second `def test_x` that quietly replaces the first. 311 of the 344 sites were repeated imports and came out with ruff's own fix. The remaining 33 needed a decision. Four modules imported a name they never used because a local definition below already shadowed it. Two comprehensions bound `call` over `unittest.mock.call`, which those modules import and use. One test rebound the two module handles its nested reload closure had captured. One class attribute shadowed an unused `status` import. The load-test fixtures move to a conftest, which is how pytest is meant to share them, so the test module no longer imports three fixture names it never calls. The nine `prisma_client` parameters keep a narrow `noqa`: pytest resolves that fixture by name before the body runs, so the parameter never shadows anything. |
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785eed616f |
fix(proxy): strip extra_headers/headers/aws_session_token from GET /health (gh-36898)
`/health` already stripped `api_key` from each deployment row via `ILLEGAL_DISPLAY_PARAMS`, but `extra_headers`, `headers`, and `aws_session_token` were never added to that list, so `GET /health` leaked provider credentials (Azure `api-key`, Google `x-goog-api-key`, Bearer tokens, AWS session tokens) in plaintext to any caller, even without a master key. Add those three fields to `ILLEGAL_DISPLAY_PARAMS` so `_clean_endpoint_data()` omits them for all callers, matching how `api_key` is already handled. Fixes #36898 |
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ed33687422 | feat(proxy): auto-suppress the no-Redis banner for confirmed single-worker deployments | ||
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48fa4a0f06 |
fix(ui): treat router redis as configured for the no-redis banner
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> |
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e368eeac49 |
feat(ui): warn in the Admin UI when no Redis is configured
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> |
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298fb8ce56
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fix(health): drop a stored-credential reference along with the credentials it names
A connection test that redirects the destination already leaves the configured credentials behind. It kept litellm_credential_name, which names the same stored secrets and is resolved further down the call, so the reference is now dropped with them. A request that sets no connection fields of its own is unaffected, which is how the Admin UI tests a configured model. |
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59173c3a20
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feat(health): let allow_client_side_credentials re-enable configured-credential reuse
The proxy-wide opt-in that already governs callers supplying their own connection parameters now also governs whether a connection test may pair a request-supplied endpoint with the configured deployment's credentials. Off by default, which keeps configured credentials scoped to the endpoint the configuration names; on, the previous merge behaviour is available unchanged. |
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b468acb31c
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fix(health): stop inheriting configured credentials when a connection test sets its own
A request that supplies its own connection fields describes a connection of its own, so the configured deployment's credentials are no longer merged underneath it. Anything the request leaves unset still comes from the configuration, so naming a configured model and testing it as configured is unchanged, and adding a second deployment for an already-configured name works as before. Replaces the earlier outright rejection, which also refused requests that supplied a complete connection of their own. |
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e5effcb861
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fix(health)!: let configured deployment parameters win over request overrides
When a connection test names a model that resolves to a configured deployment, that deployment's routing and credential parameters are authoritative. A request supplying a complete connection of its own is unaffected. BREAKING CHANGE: /health/test_connection no longer lets a request replace the routing or credential parameters of a configured model it names. Supply the full connection parameters instead of naming a configured model. |
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a2f5bb1868
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fix(proxy): authorize /health/test_connection against loaded deployment's team_id (VERIA-441) (#31767)
* fix(proxy): authorize /health/test_connection against loaded deployment's team_id (VERIA-441) POST /health/test_connection looked up a deployment by request-supplied model_info.id, dumped its litellm_params (including api_key) into the outbound probe, merged request params over it, and then authorized the call against the caller-supplied model_info.team_id. A team admin could pass another team's deployment id together with their own team_id and an attacker-controlled api_base, sending the victim team's provider key to that URL. Capture the loaded deployment's model_info alongside its litellm_params in both the id-lookup and the model_name fallback paths, and pass that captured value to can_user_make_model_call. When no deployment is loaded (caller is probing fresh, request-supplied credentials), keep using the request body's model_info; no foreign deployment is in scope and the existing role check still requires admin or team-admin. Add two regression tests that wrap (not mock) ModelManagementAuthChecks.can_user_make_model_call, one per resolution path, asserting HTTP 403 and that the auth check was reached with the loaded deployment's team_id. Both fail on the pre-fix code. * test(health): add positive-path regression through real auth (VERIA-441) The two deny tests already exercise the real (wrapped) ModelManagementAuthChecks. Add a matching positive-path test so a mutation that swaps the auth team_id for a deny-all value on the legit path also fails: loaded deployment owned by team-X, caller admin of team-X -> asserts HTTP 200 and that the auth check ran with the LOADED deployment's team_id. * refactor(test): rename health endpoint tests for clarity (VERIA-441) Rename test functions and variables from attacker/victim/owner framing to neutral team-a/team-b terminology. Update docstrings to remove exploit-specific language. Tests remain functionally identical, covering deny paths (cross-team deployments) and the positive path (same-team deployments). |
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079c136742
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chore(oss): litellm oss staging 120626 (#30292)
* feat(bedrock): add bedrock mantle gemma 4 models (#30264) * feat(bedrock): add bedrock mantle gemma 4 models * test(bedrock): harden mantle local cost fixture * feat(responses): enable the responses API for the Tensormesh provider (#30209) * feat(responses): enable the responses API for the Tensormesh provider * Update litellm/llms/openai_like/providers.json Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com> --------- Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com> * fix(langfuse_otel): mark LLM spans as generations (#30250) * fix(bedrock): stop stream_chunk_size leaking into invoke request bodies (#30240) stream_chunk_size is a LiteLLM-internal knob for re-chunking the HTTP response stream. The invoke transformations splat optional_params into the provider request body without dropping it, and Bedrock rejects unknown fields, so any bedrock/invoke request that sets the parameter fails with ValidationException: stream_chunk_size: Extra inputs are not permitted. Drop it in the invoke dispatcher (covers cohere, titan, mistral, meta, ai21) and in the Claude messages-format request builder (the route used for bedrock/invoke Anthropic models) * fix(bedrock): stop buffering streamed tool-call argument deltas (#30231) * fix(bedrock): stop buffering streamed tool-call argument deltas Two issues made Bedrock tool-use streaming arrive as a single end-of-stream burst through LiteLLM while plain text streamed fine. First, the anthropic-beta allowlist mapped fine-grained-tool-streaming-2025-05-14 to null for bedrock and bedrock_converse, so the header was silently stripped. Without that beta, Anthropic models on Bedrock buffer tool input server-side and emit all toolUse.input deltas at once (verified against converse-stream and invoke-with-response-stream directly). Bedrock accepts the beta via additionalModelRequestFields.anthropic_beta, so it is now forwarded. Second, the streaming reads re-chunked the AWS event stream with iter_bytes(chunk_size=1024). httpx's ByteChunker only releases full 1024-byte blocks, so the small early events (messageStart, contentBlockStart, first deltas) sat in the buffer until enough bytes accumulated, pushing time-to-first-byte from ~1.4s to ~8.5s on buffered tool-use streams. The default is now no re-chunking; an explicit stream_chunk_size is still honored. * test(bedrock): cover explicit stream_chunk_size on sync invoke path * test(bedrock): cover stream_chunk_size plumbing through converse completion * test(bedrock): cover stream_chunk_size default in legacy BedrockLLM streaming * test(bedrock): merge converse handler tests into existing mapped test file pytest imports test modules by basename in non-package test dirs, so the new tests/test_litellm/llms/bedrock/chat/test_converse_handler.py collided with the pre-existing tests/test_litellm/llms/chat/test_converse_handler.py and broke collection in CI. Move the new tests into the existing file * feat(otel): emit v2 cost breakdown + stamp tracer scope version (#30156) Read the StandardLoggingPayload cost_breakdown into a typed LLMCost on LLMCallSpanData and emit each component under litellm.cost.* (absent components omitted, so spans stay sparse). Stamp litellm.__version__ as the instrumentation scope version so every v2 span carries a deterministic scope.version. Tests under tests/test_litellm/integrations/otel/. * fix(proxy): cancel in-flight upstream LLM request on client disconnect (opt-in) (#30223) * fix(proxy): cancel in-flight upstream LLM request on client disconnect (opt-in) On the non-streaming path, base_process_llm_request awaited the LLM call with no disconnect monitoring; when the HTTP client went away the upstream request kept running until completion or request_timeout (6000s default), holding a backend slot (e.g. a vLLM GPU slot) for output nobody would read Add an opt-in general_settings.cancel_on_disconnect flag, default off, so the default code path is unchanged. When enabled, a receive-based watcher task observes http.disconnect and cancels the asyncio.gather driving the upstream call. The resulting CancelledError is converted to HTTPException 499 only when the disconnect event is set, so server-initiated cancellations still propagate as-is. The 499 then flows through _handle_llm_api_exception like any other failure, meaning post_call_failure_hook still releases max_parallel_requests slots and fires spend and alerting callbacks; it is logged at info level instead of a full traceback Also removes the dead check_request_disconnection helper in proxy_server.py (zero call sites) along with its behavior-pin tests Builds on the receive-based design from #25776 Addresses #13774. Re-fixes #22805 (regressed after the #14295 revert) Co-authored-by: CreateRandom <18438707+CreateRandom@users.noreply.github.com> * fix(proxy): scope 499 quiet logging to disconnects and harden watcher Address the two P2 findings from the Greptile review on #30223. The info-level logging in _log_llm_api_exception now applies only to the disconnect-specific HTTPException (status 499 plus the shared _CLIENT_DISCONNECT_DETAIL message), so any other 499 raised by hooks or guardrails keeps its full traceback. The disconnect watcher now catches exceptions from request.receive() (e.g. a transport reset) and logs a warning instead of dying silently, making the degradation to no-op visible; a test pins that the LLM call is not cancelled in that case --------- Co-authored-by: kursad <kursad.lacin@brado.net> Co-authored-by: CreateRandom <18438707+CreateRandom@users.noreply.github.com> * fix(bedrock): grant aws-external-anthropic:* in OIDC session policy for claude_platform (#30200) (#30205) The inline STS session policy passed to assume_role_with_web_identity acts as an IAM PERMISSION CEILING — effective permissions are the intersection of the role's identity policies and this policy. Any action not listed is silently denied even when the IAM role grants it. #27678 added the bedrock/claude_platform/<model> route but its service-side action namespace is aws-external-anthropic:*, not bedrock:*. Without a matching statement here, every claude_platform request via OIDC (GCP federation, EKS Pod Identity webhook, etc.) 403s with 'no session policy allows the aws-external-anthropic:CreateInference action' — even with a fully permissive identity policy. Add a second ClaudePlatformLiteLLM statement covering CreateInference, CreateBatchInference, CancelBatchInference, DeleteBatchInference, CountTokens, Get*, List*. Keep aws:SecureTransport=true parity with the bedrock statement. Static creds + IRSA flow through different code paths and are not affected. Fixes #30200 * fix(proxy): set Retry-After header on RouterRateLimitError 429 responses (#30098) * Set Retry-After header on RouterRateLimitError responses When all deployments for a model are in cooldown, the proxy returns a 429 whose cooldown timing is only available by parsing the error message string. RouterRateLimitError already carries cooldown_time, so expose it as a standard retry-after header in _handle_llm_api_exception. The value is rounded up so clients never retry before the cooldown window ends. Fixes #27823. * Set Retry-After after response-headers hook so cooldown wins The cooldown-derived retry-after was assigned before the post_call_response_headers_hook merge, so a callback returning a retry-after key (including a stale or empty value) silently clobbered it. Move the RouterRateLimitError block after the callback merge so the cooldown value is authoritative for this error type. * fix(router): route aspeech through async_function_with_fallbacks (#30104) * fix(router): route aspeech through async_function_with_fallbacks Router.aspeech selected a deployment and awaited litellm.aspeech directly, so TTS requests got no retry on failure and no failover to backup deployments; the except block only fired an exception alert and re-raised. Every other router endpoint (acompletion, aembedding, atranscription, arerank) already delegates to async_function_with_fallbacks Mirror the atranscription pattern: move deployment selection and the litellm.aspeech call into a private _aspeech method, then have the public aspeech set kwargs["original_function"] = self._aspeech and await self.async_function_with_fallbacks(**kwargs). _aspeech also picks up the shared _get_async_openai_model_client helper and the same total/success/fail call accounting the sibling endpoints use Fixes #27778. * fix(router): apply deployment kwargs and rpm semaphore in _aspeech Bring _aspeech fully in line with _atranscription: call _update_kwargs_with_deployment so deployment metadata, model_info, timeout, and default litellm params flow into the request, and wrap the litellm.aspeech call with the max_parallel_requests semaphore plus async_routing_strategy_pre_call_checks so TTS respects rpm limits the same way the other router endpoints do Also add a unit test that exercises _aspeech directly and asserts the deployment metadata reaches the underlying call * fix(slack_alerting): stop false-positive hanging request alerts for requests below the alerting threshold (#30106) * fix(slack_alerting): skip hanging request alerts below the threshold The hanging request check alerted on any cached request whose completion status was not yet recorded, with no minimum age check. Since the background loop runs every alerting_threshold / 2 seconds, any request that happened to be in flight at a check fired a "hanging - Ns+ request time" alert even if it was only seconds old, producing a steady stream of false positives. Add a created_at timestamp to HangingRequestData, stamped when the request enters the hanging request cache, and skip requests younger than alerting_threshold without evicting them, so a later check can still alert if they never complete. Extend the cache TTL from threshold + 60s to 1.5x threshold + 60s; with the age check, entries only become alertable after threshold seconds, and the check period is threshold / 2, so the old TTL could evict a genuinely hanging request before any check saw it cross the threshold. Fixes #27855. * fix(slack_alerting): alert once per hanging request The min-age gate stops false positives for young in-flight requests, but a genuinely hanging request still re-alerted on every checker tick within the cache TTL. With the wider TTL (1.5x threshold + 60s) that is 1-2 extra Slack notifications per stuck request at the default 600s threshold. Flag a HangingRequestData entry as alerted once its alert fires and skip flagged entries on later ticks, so each hang produces exactly one alert. The cache reference is mutated in place, so the TTL is untouched and still handles cleanup. Adds a regression test asserting one alert across multiple ticks. Fixes #27855. * fix(health): treat all-proxy-models keys as unrestricted in /health (#30087) * fix(health): treat all-proxy-models keys as unrestricted in /health A key granted all model permissions stores the literal "all-proxy-models" marker in its models list. The /health access filter compared that marker against real model_names, so the model list filtered down to nothing and the WebUI health check returned healthy_count=0, unhealthy_count=0 with HTTP 503. Skip the filter (both the live path and the background-cache model_id scoping) when the marker is present, matching how auth_checks treats SpecialModelNames.all_proxy_models. Fixes #29744. * fix(health): resolve all-team-models sentinel to the team allowlist Same failure shape as the all-proxy-models case: a key carrying the literal "all-team-models" entry matches no real model_name, so the /health access filter would zero out the model list. Resolve the sentinel to the key's team models when team_id is set, matching get_key_models in model_checks.py. Without a team_id the sentinel stays unresolved and matches nothing, denying rather than widening access, mirroring _resolve_key_models_for_auth_check. * feat(proxy): auto-enable drop_params for Claude Code requests (#30218) * feat(proxy): auto-enable drop_params for Claude Code requests Claude Code identifies itself with a claude-cli/<version> user agent and sends Anthropic-specific params (top_k, thinking, etc.) on every request. When the proxy routes those requests to a non-Anthropic provider, the unsupported params fail the call unless drop_params is configured. Detect the Claude Code user agent in add_litellm_data_to_request and default drop_params to true for those requests, without overriding an explicit drop_params value sent by the caller. * feat(proxy): respect operator litellm_settings drop_params over Claude Code default An explicit drop_params in the operator's litellm_settings (true or false) now suppresses the Claude Code user agent default, so an operator who deliberately configured drop_params: false keeps strict param validation for Claude Code clients too. The auto-default only fills the gap when neither the request body nor the config sets a value. * fix(snowflake): migrate to native endpoints with auto-routing for Claude models (#29964) * fix(snowflake): migrate to native Cortex REST API endpoints Replaces the legacy /api/v2/cortex/inference:complete endpoint with the native OpenAI-compatible /api/v2/cortex/v1/chat/completions endpoint, fixing error 390142 (Incoming request does not contain a valid payload) when using model: snowflake/<model> in LiteLLM proxy. Changes: - litellm/llms/snowflake/chat/transformation.py: route to native /cortex/v1/chat/completions, remove Snowflake-specific tool_spec payload transformation, remove content_list response handling, add stream to supported params - litellm/llms/snowflake/anthropic/transformation.py (new): SnowflakeCortexAnthropicConfig routes Claude models to /cortex/v1/messages with anthropic-version header and Anthropic->OpenAI response transform - tests: 29 unit tests covering URL routing, auth headers, payload format, and response parsing * fix(snowflake): map max_tokens to max_completion_tokens for native endpoint * fix: handle multi-turn tool conversations and OpenAI→Anthropic tool format conversion - _extract_system_and_messages now preserves tool_calls from assistant messages and converts them to Anthropic tool_use content blocks - tool role messages are converted to user role with tool_result content blocks (as required by Anthropic Messages API) - Added _transform_tools_to_anthropic() to convert OpenAI tool format (type/function/parameters) to Anthropic format (name/input_schema) - Added comprehensive tests for multi-turn tool conversations Addresses review feedback on PR #29964 * test: add coverage for malformed JSON and non-string tool arguments * fix(tests): update chat transformation tests for native OpenAI-compatible endpoint * style: apply black formatting * fix: resolve mypy type errors in anthropic transformation * fix: correct mypy type: ignore error codes (attr-defined) * fix: use max_tokens instead of max_completion_tokens for Snowflake endpoint compatibility * refactor: merge Anthropic config into unified SnowflakeConfig with auto-routing - Remove separate SnowflakeCortexAnthropicConfig and anthropic/ directory - SnowflakeConfig now auto-routes based on model name: - Claude models → /messages endpoint (Anthropic format) - All others → /chat/completions endpoint (OpenAI format) - No new provider needed (stays as SNOWFLAKE = 'snowflake') - Tool message transformation for Claude: tool_calls → tool_use blocks, tool role → user with tool_result - OpenAI → Anthropic tool format conversion (parameters → input_schema) - Addresses Greptile feedback about unwired SnowflakeCortexAnthropicConfig * fix: use max_completion_tokens for /chat/completions (Snowflake deprecated max_tokens on this endpoint) * fix(tests): update assertions for Claude auto-routing to /messages endpoint * fix(snowflake): add tool_choice conversion and preserve max_completion_tokens in Anthropic path * fix(snowflake): use ChatCompletionMessageToolCall objects and strip model prefix on OpenAI path * fix(snowflake): collect multiple system messages to prevent guardrail override * chore: remove committed .pyc files and add __pycache__ to .gitignore * fix: remove unused Union import * fix: restore original .gitignore (accidentally replaced in earlier commit) * feat(snowflake): add streaming response handler for both Anthropic and OpenAI SSE formats * fix: remove unused AsyncIterator and Iterator imports * fix: add missing total_tokens to ChatCompletionUsageBlock * fix(snowflake): coalesce consecutive tool results into single user message for Anthropic * fix(snowflake): handle message_start event for streaming input_tokens tracking * fix: evict last deleted model in multi-instance deployments (#28608) * fix: evict last deleted model in multi-instance deployments _delete_deployment had an early return when db_models was empty, preventing eviction of the last deleted model during reconciliation. - Remove len(db_models)==0 early return from _delete_deployment - Return None (not []) from _get_models_from_db on DB failure so callers can distinguish a transient failure from a genuinely empty DB - Guard _update_llm_router against None to skip updates on DB failure Fixes #28443 * test: remove dead MagicMock assignment in type_mismatch test * fix: update test to pass [] not None to _update_llm_router test_ProxyConfig__update_llm_router_bad_proxy_logging_raises was passing None as new_models to get through to the proxy_logging_obj check, but the None guard we added now returns early before reaching that path. Pass [] instead so the test exercises the intended AttributeError case. Signed-off-by: Rudra Dudhat <contact.rdudhat@gmail.com> * chore: regenerate API types to sync schema.d.ts with proxy OpenAPI spec Signed-off-by: Rudra Dudhat <contact.rdudhat@gmail.com> --------- Signed-off-by: Rudra Dudhat <contact.rdudhat@gmail.com> * fix: invalidate Redis spend counter on /key/reset_spend (#29694) * fix: set Redis spend counter to reset_to value on /key/reset_spend Previously, the Redis spend counter was always set to 0.0 after a reset, even when reset_to was a non-zero value (partial reset). This caused the budget to be under-enforced for up to 60 seconds until the counter expired and fell through to the DB. Now the counter is set to the actual reset_to value, so partial resets are reflected correctly and budget enforcement is consistent. * test: update reset_key_spend test to match direct cache set The implementation now sets spend_counter_cache directly instead of calling _invalidate_spend_counter. Update the test to verify the in_memory_cache.set_cache call with the correct key, value, and ttl. --------- Co-authored-by: michaelxer <michaelxer@users.noreply.github.com> * fix: add scaleway models pricing (#27659) * fix: Add embeddings support for Scaleway provider * fix: resolve merge conflicts * fix(main): clarify backend route handling for Swagger static assets (#30196) * fix(main): clarify backend route handling for Swagger static assets * fix(allowlist): add BACKEND_MOUNT_PATHS for Swagger static assets * fix(voyage): route multimodal embeddings to correct endpoint (#30193) * fix(voyage): route multimodal embeddings to correct endpoint * test(voyage): cover multimodal embedding edge cases * test(voyage): cover api key fallback * fix(voyage): raise early on missing api key and malformed image url * test(voyage): cover utils routing and helper * fix(voyage): route supported openai params for multimodal models * style: apply black formatting * fix(ui): infer Azure API version from API base (#30204) * fix(ui): infer Azure API version from API base * fix(ui): address Azure API version feedback * Update litellm/llms/snowflake/chat/transformation.py Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com> * feat(datadog): add team-scoped Datadog callback support (#29947) Enable teams to configure their own Datadog credentials via POST /team/{team_id}/callback, following the same pattern as Langfuse. * Merge pull request #29528 from aanchal22/litellm_byok-alias-merge fix(proxy): atomic merge for team model aliases and team.models on BYOK create * feat: add EmpirioLabs as an OpenAI-compatible provider (#30278) Co-authored-by: Adam Dalloul <adam.d.developer@gmail.com> * fix: resolve failing tests and lint in snowflake/team endpoints - Black-format snowflake/chat/transformation.py to fix lint failure - Update Anthropic config test to expect default max_tokens of 4096 (matches implementation) - Add AsyncMock + execute_raw mock to team_model_add cache-refresh pin test - Add model_dump mock and patch cache/logging in test_uses_atomic_array_append_with_dedup Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * fix(test): update test_db_error_new_model_check for new _delete_deployment logic _delete_deployment no longer short-circuits on empty db_models — it now treats [] as a valid empty-DB state and proceeds to check config models. Mock get_config to return the two router deployments so they appear in combined_id_list and are protected, which matches the real-world scenario where a DB error occurs but the models are config-backed. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * feat(proxy): register cancel_on_disconnect in ConfigGeneralSettings and config list (#30295) * feat(proxy): register cancel_on_disconnect in ConfigGeneralSettings and config list Follow-up to #30223 per maintainer review: documents the flag in ConfigGeneralSettings with a short description and adds it to allowed_args in get_config_list so the UI and /config/list expose it. A test pins that /config/list returns the field with type Boolean, which requires both registrations to be present * chore(ui): regenerate schema.d.ts for cancel_on_disconnect --------- Co-authored-by: kursad <kursad.lacin@brado.net> * fix(datadog): never fall back to env DD_API_KEY for caller-supplied destinations Team/key-scoped Datadog loggers could be pointed at an arbitrary dd_agent_host or dd_site while omitting dd_api_key, causing the proxy's global DD_API_KEY to be sent as the DD-API-KEY header to that destination. Gate the env-var fallback behind an allow_env_credentials flag, set to False when the destination is caller-supplied, mirroring the existing langfuse/langsmith pattern. --------- Signed-off-by: Rudra Dudhat <contact.rdudhat@gmail.com> Co-authored-by: Emerson Gomes <emerson.gomes@thalesgroup.com> Co-authored-by: daitran-tensormesh <dai@tensormesh.ai> Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com> Co-authored-by: Muspi Merol <me@promplate.dev> Co-authored-by: fangkang <fangkangm@gmail.com> Co-authored-by: Chris Hoogeboom <chris.hoogeboom@gmail.com> Co-authored-by: kursadlacin <kursadlacin@gmail.com> Co-authored-by: kursad <kursad.lacin@brado.net> Co-authored-by: CreateRandom <18438707+CreateRandom@users.noreply.github.com> Co-authored-by: hcl <chenglunhu@gmail.com> Co-authored-by: Filippo Menghi <113345637+Cyberfilo@users.noreply.github.com> Co-authored-by: Mateo Wang <277851410+mateo-berri@users.noreply.github.com> Co-authored-by: sfc-gh-nashukla <navnit.shukla@snowflake.com> Co-authored-by: Rudra Dudhat <contact.rdudhat@gmail.com> Co-authored-by: Michael <52305679+michaelxer@users.noreply.github.com> Co-authored-by: michaelxer <michaelxer@users.noreply.github.com> Co-authored-by: Quentin Champenois <26109239+Quentinchampenois@users.noreply.github.com> Co-authored-by: mauriceberentsen <mauriceberentsen@live.nl> Co-authored-by: lost9999 <56498264+lost9999@users.noreply.github.com> Co-authored-by: GaetanVDB07 <86427581+GaetanVDB07@users.noreply.github.com> Co-authored-by: Aanchal Khandelwal <aan2210khandelwal@gmail.com> Co-authored-by: Adam Dalloul <adam_dalloul@icloud.com> Co-authored-by: Adam Dalloul <adam.d.developer@gmail.com> Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com> |
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feat: litellm oss 110626 (#30202)
* Add gpt-realtime-whisper Realtime transcription support (OpenAI + Azure) (#29775) * Add gpt-realtime-whisper Realtime transcription support (OpenAI + Azure) Adds first-class support for the gpt-realtime-whisper streaming speech-to-text model, which uses the Realtime transcription session API rather than the file-based /audio/transcriptions path. Model registration: registers gpt-realtime-whisper and azure/gpt-realtime-whisper with audio-duration pricing (input_cost_per_second = 0.017/60, matching the published $0.017/minute input audio rate). REST endpoint: implements POST /v1/realtime/transcription_sessions (plus /realtime and /openai/v1 aliases) to mint an ephemeral transcription session for the WebRTC flow. Adds request/response types, OpenAI and Azure URL builders, a shared base handler (refactored from the client_secrets handler), the acreate_realtime_transcription_session SDK function, and route registration. The proxy encrypts the ephemeral key returned under client_secret.value and records the session type in the token so the follow-up /realtime/calls replays type=transcription rather than type=realtime. WebSocket: forwards intent=transcription through to the Azure handler (OpenAI already received it) with URL-encoding, so gpt-realtime-whisper opens a transcription session. Transcription-only sessions no longer trigger an erroneous response.create. Cost tracking: transcription sessions emit no response.done events; their usage arrives on conversation.item.input_audio_transcription.completed as {type: duration, seconds}. That usage is captured out-of-band (usage only, no transcript duplication) and billed by input_cost_per_second, with a token-billed fallback for token-priced transcription models. Adds tests for pricing math, URL builders, request/response types, the proxy route and SDK function, WebSocket intent forwarding, transcription-session streaming behavior, and the /realtime/calls session-type replay. * Address PR review: URL-encode all Azure WS query params; forward query_params through provider_config branch * Address PR review: session_type validation, model auth fix, cost perf, billing fallback, detail/docs cleanup * Improve test coverage: detection from backend, error paths, unknown usage type, resolved_model None * Backport realtime transcription websocket fixes * Enforce authorized realtime transcription model * Enforce realtime transcription model access * Enforce realtime resolved model scopes * Enforce WebRTC transcription model scope * Lazy evaluate debug log in pass-through endpoint (#30177) * Pass through debug lazy logging * fix(proxy): convert remaining eager pass-through debug logs to lazy formatting * fix(parallel_ai): migrate search integration from v1beta to v1 endpoint (#30157) * fix(parallel_ai): migrate search integration from v1beta to v1 endpoint The Parallel Search API moved from /v1beta/search (processor: base/pro, parallel-beta header) to /v1/search (mode: turbo/basic/advanced, no beta header). Request fields moved too: max_results, source_policy, and excerpt settings are now nested under advanced_settings, and source_policy uses include_domains/exclude_domains. The v1 response returns publish_date per result, which now maps to SearchResult.date instead of being hardcoded to None. The legacy processor param is mapped to the equivalent mode so existing callers keep working. * fix(parallel_ai): default mode to basic and simplify param handling The v1 API defaults to advanced mode when mode is omitted, while v1beta defaulted to the base processor. Without an explicit default, callers who pass no mode would be silently upgraded to a tier costing 2.25x more while litellm's cost map reports the basic-tier price. Sending mode=basic preserves the v1beta default and keeps cost tracking accurate. Also replaces the handled_params set with pop-as-consumed param handling so mapped params no longer need to be tracked in two places, and extends the tests to pin the default mode, processor=base mapping, mode-over-processor precedence, and top-level v1 param passthrough. * fix(parallel_ai): avoid double /v1 when api_base is already versioned A PARALLEL_AI_API_BASE like https://api.parallel.ai/v1 previously produced .../v1/v1/search. Strip a trailing /v1 before appending the search path and cover the api_base variants with a parametrized test. --------- Co-authored-by: shin-berri <shin-laptop@berri.ai> Co-authored-by: yuneng-jiang <yuneng@berri.ai> * feat(focus): add Mavvrik destination for FOCUS export (#29935) * fix: preserve responses streaming flag (#30189) * fix: preserve responses streaming flag * test: cover async responses streaming flag * fix(spend/daily-activity): stable offset pagination via id tiebreaker (#30164) (#30167) date alone is not a unique sort key for LiteLLM_DailyUserSpend or LiteLLM_DailyTeamSpend (many rows per date: api_key x model x model_group x provider x endpoint). Offset pagination over a non-unique sort landed on arbitrary boundaries, so a client paging through all results and summing per-page metrics (the Usage dashboard) got non-deterministic totals - sometimes inflated, sometimes deflated, different at different page_size values. Adding the row's UUID id (present on both tables) as a secondary sort gives every page a stable cursor. order=[{date desc}, {id asc}]. Fixes #30164 * fix(oci): inject a default maxTokens so omitted max_tokens doesn't truncate responses (#30018) * fix(oci): inject default maxTokens so omitted max_tokens doesn't truncate OCI GenAI applies a tiny server-side maxTokens default (~20 tokens) when the request omits it, so any call that doesn't send max_tokens comes back cut off mid-string with finishReason "length". MLflow judges never send max_tokens, so their JSON responses arrived as unterminated strings and json.loads failed in MLflow's gateway adapter. When no maxTokens/maxCompletionTokens target is set, inject DEFAULT_OCI_CHAT_MAX_TOKENS (env-overridable, defaults 4096), mirroring the Anthropic config's default-max-tokens behaviour. An explicit max_tokens still wins, and reasoning models still route to maxCompletionTokens. Used a fixed default rather than the catalog max_output_tokens because the catalog value is unreliable for some models (grok-4 reports max_output_tokens equal to its context window, not a real output cap, which would risk 400s). Adds TestOCIDefaultMaxTokens covering Cohere and generic injection, the explicit-override case, and the reasoning maxCompletionTokens branch. * test(oci): e2e regression that omitted max_tokens isn't truncated Real-proxy integration test asserting a chat completion that omits max_tokens completes with finish_reason "stop" instead of being cut off at OCI's ~20-token server default. Fails before the maxTokens-default injection (finish_reason "length", ~19 tokens), passes after. * test(oci): update cohere default-params test for injected maxTokens test_cohere_default_parameters asserted no maxTokens was injected, encoding the old behaviour where OCI's ~20-token server default truncated responses. Now that transform_request injects DEFAULT_OCI_CHAT_MAX_TOKENS, assert maxTokens equals that default while the other params (topK/topP/frequencyPenalty) stay pass-through with no hardcoded default. * fix(oci): make DEFAULT_OCI_CHAT_MAX_TOKENS a plain constant Drop the os.getenv override. The env knob was not requested and introducing a new env var forced a cross-repo dependency on litellm-docs (test_env_keys.py validates every referenced env var against the docs table there). A plain 4096 constant keeps the PR self-contained; callers who want a different limit pass max_tokens explicitly per request. * fix(oci): route all OpenAI commercial models to maxCompletionTokens OCI serves OpenAI models (gpt-4.1, gpt-5.1 through 5.5, o-series) that the litellm catalog doesn't track, so the supports_reasoning lookup returned False for them and the provider sent maxTokens, which the reasoning families reject with HTTP 400. With the injected default maxTokens this broke every request to those models, not just ones with an explicit max_tokens. Route the whole openai.* vendor prefix to maxCompletionTokens since OpenAI accepts max_completion_tokens on every chat model; the openai.gpt-oss-* open weights are served by OCI's own stack and keep maxTokens. Verified live against gpt-5.2, gpt-5, gpt-4o, gpt-4.1, gpt-oss-120b, llama-3.3, command-a and grok-3-mini * test(oci): hoist transformation imports and drop unused ones Makes the generic-chat test file ruff-clean: the per-test local imports of OCIChatConfig/OCIVendors shadowed the module-level import (F811) and left it unused (F401), and json plus three OCI type imports were never referenced * fix(oci): translate response_format json_schema to OCI's accepted shape (#29691) * fix(oci): translate response_format json_schema to OCI's accepted shape OCI GenAI rejected every json_schema response_format with HTTP 400 "Please pass in correct format of request", which broke structured-output callers such as MLflow LLM judges (they always send a json_schema). The provider forwarded OpenAI's raw json_schema body unchanged. For GENERIC models OCI's ResponseJsonSchema accepts only name/description/schema/isStrict, so OpenAI's `strict` key (and any other extra) 400s the request; the key must be renamed to isStrict and the body whitelisted. For Cohere models there is no JSON_SCHEMA type at all; the schema has to ride on JSON_OBJECT as {"type": "JSON_OBJECT", "schema": ...}. Cohere type values must also be the canonical uppercase TEXT/JSON_OBJECT. _normalize_response_format now branches by vendor and emits the exact shape each one accepts (verified live against OCI GenAI for Cohere, Meta, Gemini and Grok). Drops the unused, incorrect Cohere response-format pydantic models. Two existing tests asserted the broken behavior (lowercase type, raw jsonSchema on Cohere); they are rewritten to assert the corrected shape, and generic/Cohere json_schema regression tests are added. * fix(oci): raise early on json_schema response_format with no body A GENERIC model request with {"type": "json_schema"} and no json_schema object fell through to the JSON_OBJECT branch and emitted a bodyless {"type": "JSON_SCHEMA"}, which OCI rejects with an opaque HTTP 400. Raise a descriptive 400 at translation time instead. Cohere is unaffected since it always maps to JSON_OBJECT. * test(oci): gateway integration test for response_format json_schema Added to tests/integration/ (the real-network integration suite) reusing the existing OCI proxy harness, not tests/llm_translation/ which is mock-only. --------- Co-authored-by: Sameer Kankute <sameer@berri.ai> * fix(oci): accept default n=1 on Cohere instead of hard-failing (#29705) * fix(oci): accept default n=1 on Cohere instead of hard-failing Cohere on OCI has no numGenerations field, so n was mapped to False and map_openai_params raised "param `n` is not supported on OCI" whenever a client sent n. But n=1 (and None) is the OpenAI default single-generation request, which every OCI model produces anyway, so standard clients that always send n=1 (such as the MLflow gateway) were rejected with a 500. Drop n=1/None silently for Cohere; only n>1 is genuinely unsupported and still raises (or drops under drop_params). Generic models are unaffected and keep numGenerations, including n>1. * docs(oci): explain why n is not advertised for Cohere despite tolerating n=1 * test(oci): gateway integration test for Cohere default n=1 Added to tests/integration/ (the real-network integration suite) reusing the existing OCI proxy harness, not tests/llm_translation/ which is mock-only. --------- Co-authored-by: Sameer Kankute <sameer@berri.ai> * fix(oci): drop max_retries instead of hard-failing on OCI (#29727) max_retries is a litellm-level control param (litellm applies retries itself), not a generation param OCI accepts. The provider mapped it to False and raised "param `max_retries` is not supported on OCI" whenever it was present. The litellm proxy injects max_retries on every request, so any OCI call through the proxy 500'd unless drop_params was set. Drop max_retries silently in map_openai_params. Adds a unit test (Cohere and generic) and a gateway integration test that a plain request succeeds through a proxy without drop_params. Co-authored-by: Sameer Kankute <sameer@berri.ai> * fix(spend-logs): rehydrate metadata JSONB text on ui_view_spend_logs (#29682) Fixes #29674. `/spend/logs/ui` raw-SQL path returns the JSONB metadata column as a string — prisma's query_raw skips the ORM-layer hydration. The UI reads metadata.status / metadata.error_information as object fields, so provider-failure rows look like successes. Fix: json.loads the metadata field right after query_raw, fall back to {} on malformed JSON. 3 existing error-code/error-message tests called json.loads on response.data[0]["metadata"] — they were leaning on the bug. Updated to read the dict directly. Plus 2 new regression tests (failure metadata roundtrip + invalid-json fallback). Reverting the fix makes both new tests fail with AssertionError: metadata should be dict, got <class 'str'>. * fix(proxy): release max_parallel_requests slot when a stream is cancelled mid-flight (#27955) (#30020) * fix(proxy): release max_parallel_requests slot when a stream is cancelled mid-flight (#27955) * fix: refund max_parallel_requests on disconnect from outer streaming generators The cancellation refund previously lived in async_post_call_streaming_iterator_hook, but that hook is nested inside the outer streaming generators and a nested async generator only receives GeneratorExit on garbage collection (non-deterministic). With only the v3 limiter enabled, /chat/completions also bypasses the hook entirely (needs_iterator_wrap() is false). Move the release into async_data_generator and async_streaming_data_generator, the generators Starlette closes on client disconnect, so the refund fires deterministically on every streaming route. Warn when no event loop is running, and document the window TTL refresh on the decrement * fix(mcp): propagate model into model_call_details for passthrough tool calls (#30122) * fix(mcp): propagate model into model_call_details for passthrough tool calls The @client decorator on call_mcp_tool creates the logging object via function_setup without a model kwarg, so model_call_details["model"] starts as None. execute_mcp_tool only set logging_obj.model as an instance attribute, which the spend-log writer never reads (it reads kwargs["model"] from model_call_details). MCP passthrough tools/call rows therefore persisted with model="" while list_tools rows showed "MCP: list_tools", degrading the Logs UI display and bucketing all MCP tool spend under an empty model in DailyUserSpend. Propagate the model into model_call_details alongside the existing attribute assignment so the StandardLoggingPayload and SpendLogs writer pick it up. Covers the /mcp passthrough, REST /mcp-rest/tools/call, and orchestrated paths (the latter already passed model into function_setup, so this is a no-op there). * test(mcp): trim regression test docstring * fix(mcp): surface upstream challenges for delegated OAuth (#30124) * fix(mcp): surface upstream challenges for delegated OAuth * docs(mcp): clarify delegated upstream auth comments * perf(benchmarks): add CPU timing metrics to streaming benchmark (#29980) * Add CPU timing metrics to streaming benchmark * Fix spacing around timing sample dataclass * fix(gemini): don't emit empty choices on metadata-only stream chunks (#29167) web_search + reasoning makes Gemini stream mid-chunks that carry only grounding/thought metadata — no content part, no finishReason. _process_candidates skips content-less candidates and the existing fallback only ran when finishReason was set, so choices stayed empty and the downstream streaming handler raised IndexError on choices[0]. Emit an empty-delta choice for content-less chunks regardless of finishReason. Fixes #28884 * fix(key): allow /key/update to clear budget_limits with [] or null (#30085) * Fix /key/update rejecting budget_limits clear requests with HTTP 400 Sending budget_limits: [] or null to /key/update returned HTTP 400, so once a key had budget windows the last one could never be removed. prepare_key_update_data only json.dumps'd budget_limits when the value was truthy, so [] and None passed through raw to the Prisma Json? column; jsonify_object only serializes dicts, and prisma-client-py has no DbNull sentinel for Json? writes, so Prisma rejected both shapes. Serialize the clear case explicitly as the JSON literal null, matching how memory_endpoints encodes metadata for the same column type. Truthy values keep the existing reset_at window initialization path. Fixes #30067. * Require admin access for budget_limits changes on /key/update Clearing budget_limits via [] or null is a budget mutation, but _validate_update_key_data only counted max_budget and spend as budget changes before deciding whether to skip _check_key_admin_access. A non-admin key owner or a team member with /key/update could therefore remove a key's per-window spend caps without admin authorization. Treat any explicit budget_limits value in the request (set, change, or clear) as a budget change so it gates through the same admin check as max_budget. model_fields_set is used because an explicit null is indistinguishable from an omitted field by value alone. * fix(proxy): persist guardrail info in spend logs for /v1/responses (#30092) Pre-call guardrail blocks on /v1/responses wrote guardrail_information as null in LiteLLM_SpendLogs because _handle_logging_proxy_only_error splits request_data by LoggedLiteLLMParams keys and litellm_metadata, where the Responses API stores request metadata including standard_logging_guardrail_information, was not among them. It fell into optional_params, so merge_litellm_metadata never saw it. Add litellm_metadata to LoggedLiteLLMParams so it routes into litellm_params the same way metadata does on the chat completions path Fixes #28971. * fix(proxy): handle non-standard SSE frames in Anthropic passthrough logging (#26000) Some third-party Anthropic-compatible providers emit non-standard SSE frames (OpenAI-style [DONE] sentinels, non-JSON keep-alive lines) in streaming responses. These caused json.JSONDecodeError in _build_complete_streaming_response, breaking the passthrough logging pipeline so the request was never logged or billed. Skip whole-line 'data: [DONE]' sentinels and catch JSONDecodeError per event. Matching the full line (not a substring) keeps a valid chunk whose text payload contains '[DONE]' from being dropped. Co-authored-by: shin-berri <shin-laptop@berri.ai> Co-authored-by: yuneng-jiang <yuneng@berri.ai> Co-authored-by: Sameer Kankute <sameer@berri.ai> * feat(newrelic): Add New Relic extension (#26989) * initial New Relic integration. * Minor fixes for basic observability. * Implemented basic support for the success path. Generates New Relic custom events needed by the AI Monitorin interface. * Supportability metric is sent on first request. * Emit supportability metric every hour instead of once a day. * Add the start/end times to the messages before sending them so that the start time and end time reflect the correct time and both are not set to 'now'. * Make use of `turn_off_message_logging` configuration that is available by default from CustomLogger. * Enabling New Relic agent to be wired when docker container starts if an environment variable is set. * If we cannot find trace information, send the AI events without the trace ID attached. * Use a fake trace_id if we cannot find one. * Implementing a configuration so that users can use litellm configuration to disable sending LLM messages to New Relic. There is a second method to do this via New Relic env var. * Mised file. * Cleaning up logic to turn off recording content via either the LiteLLM configuration or an env var. * Removing debugging. Fixed logic / comments around how often to send supportability metric. * Initial version of public doc for New Relic. * Use a proper name for the doc file. * Updating newrelic.md document. * Updating LiteLLM documentation for New Relic extension. * Moving New Relic imports into the methods to support unit tests. * Adding unit tests for the New Relic extension. * Updating linting and the unit tests that are not running in the CI environment. * Address reviewer feedback on New Relic integration. - Fix _record_error_metric to use app.record_custom_metric() instead of module-level newrelic.agent.record_custom_metric() so the call works outside of an active transaction context - Remove unreachable except ImportError block in _get_trace_context - Update stale "23 hours" comment to "27 hours" (matches 97200s threshold) - Remove commented-out debug code from _process_success - Fix docs typo: NEW_RELIC_CUSTOM_INSIGHTS_EVENTS_MAX_SAMPLES_STOREDA -> NEW_RELIC_CUSTOM_INSIGHTS_EVENTS_MAX_SAMPLES_STORED - Update TestRecordErrorMetric to verify app.record_custom_metric call Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * Reformating for the linter. * Addressing additional automated feedback. - Removed a legacy comment about the New Relic header - Reordered imports in one file - Switched another file to use the import at the top of the file instead of inline when used - Added unit tests for untested methods that were identified * Addressing new feedback. - Proper handling of time to floats. Created a util method and updated code to use it. - added the missing guard to ensure the app is enabled * Addressing feedback. - When an error occurs, still check if the periodic supportability metric should be emitted - Added a check to ensure the extension is ready in the error handler to match _process_success * Updating the NR event timestamps to more accurately reflect when the messages were generated. * Addressing feedback for potential better practice. * Addressing feedback on accessing default values. Added tests for most of these cases. * Adding a new catch exception block based on feedback. * Addressing feedback about a potential issue around a timestamp for the supportability metric. * Addressing minor feedback on length of generated, fallback traceId. * Addressing feedback. - A few more cases were found where the dictionary access might not return the correct value. - Handling cases where `traceparent` is not lower cased * Addressed feedback where the newrelic options might not apply correctly. * Addressing some feedback. * Addressing feedback. * Validating testing / formatting for our changes. * Updating linting, adding tests, defining data type for UI. * Configuration for the logging callback definition. * Adding a newrelic image for the UI to use. * Putting the New Relic callback in proper alphabetic order. * Copying the logo to a committed output directory so it shows up in a locally built container. * Adding missing definition of new env vars that were causing a build failure. * Addressing automated feedback from greptile. * Adding a few more unit tests to increase the code coverage just a bit more. * Additional unit tests to push coverage to almost 90%. * Adding a custom newrelic docker image build process. This removes the need to add the newrelic agent to the core litellm container or dependencies. * Clarifying message when the New Relic agent is not installed and someone is trying to use the newrelic extension. Either use the proper image when using docker, or install the agent manually when running from source. * Ensuring pip is available to install the New Relic agent. * Updating the definition and handling of traceId (no spanId). Clarifying behavior of env vars vs UI configuration for the newrelic extension. * Removing entries from the New Relic logger configuraiton UI as these values must be set as part of running the image. * Removing a stale doc file that has moved to the litellm-docs repo. Cleanup of Dockerfile to remove a LABEL that was incorrect. * Updating container image name to be the best guess for the new name. * Addressing feedback from greptile. - Added a comment around token_count=0 - Updated the boolean parser to allow a wider set of options which matches existing patterns in other parts of LiteLLM. * Removing option for a separate New Relic container image. The agreement is to handle this in the New Relic integration docs. * Updating error message when New Relic agent is not available. * Wiring in the test message from the LiteLLM callback UX. * Missed saving one of the file conflicts. * Fixed a lint error I introduced. Somehow, I dropped another string and now added it back. * Adding newrelic to the schema definition. * Added an admin check on the call before sending test message as mentioned by the AI code review. * Updating to use should_redact_message_logging(kwargs) as part of the logic to determine if message content should be sent to New Relic or not. This still uses the `record_content` property as well, but both have to be true in order for content to be included. --------- Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com> * Add Azure AI Foundry DeepSeek V3.1 and V4 Pro/Flash global pricing to cost map (#30134) Co-authored-by: Cursor <cursoragent@cursor.com> * fix(logging): translate Responses bridge result to ModelResponse for spend logs (#28985) PR #29394 fixed the AnthropicResponse.model_validate crash for the streaming anthropic_messages -> OpenAI Responses bridge by unwrapping terminal events and returning the inner ResponsesAPIResponse. The spend_logs row lands and usage/cost are correct, but the row's response field stores the Responses API shape (output[...].content[...].text). The proxy UI Logs tab reads response.choices[0].message via parseMessages in prettyMessagesUtils.ts with no fallback for the Responses shape, so the OutputCard renders "No response data available" for every cross-routed call. The same shape mismatch affects every downstream consumer of spend_logs that assumes the canonical chat-completion shape This change keeps the unwrap from #29394 but routes the resulting ResponsesAPIResponse (and the bare-response non-streaming path) through LiteLLMResponsesTransformationHandler.transform_response, which is the same conversion already used by the chat-completion Responses bridge. Spend_logs now stores a ModelResponse with choices[0].message.content, so the UI and other consumers see the assistant text. On a translation failure (eg. empty output on an incomplete response) the handler falls back to a minimal ModelResponse carrying model and usage so the row still lands rather than being dropped as a Non-Blocking error Also corrects a stale comment in the Responses adapter that implied the call type was reclassified to acompletion; the code preserves anthropic_messages and the success handler translates back to ModelResponse for the row Fixes #28595 * fix(anthropic-adapter): re-emit first delta on streaming content-block transitions (#30024) * fix(anthropic-adapter): re-emit first delta on streaming content-block transitions The `/v1/messages` -> `/v1/chat/completions` streaming adapter (`AnthropicStreamWrapper`) silently dropped the first non-empty delta of every content block that started via a *transition* (e.g. text -> tool_use -> text, text -> thinking). When an upstream chunk both triggers a new content block (its type differs from the active block) and carries that block's first delta, the wrapper emitted `content_block_stop` -> `content_block_start` and then only re-queued the trigger chunk when it was an `input_json_delta` (bundled tool args). The synthesized `content_block_start` always carries an empty body, so the first `text_delta` / `thinking_delta` was lost — the client output started from the second token (e.g. "Hi, how can I help you?" rendered as ", how can I help you?", or text resuming after a tool call lost its first sentence). This is especially visible with Claude Code-style clients that consume Anthropic Messages streaming events strictly. Fix: re-queue the trigger chunk's translated delta whenever it carries non-empty content (text/thinking/signature/tool args), via a shared `_trigger_delta_has_content` helper used by both the sync and async paths. Empty trigger deltas are still suppressed so no spurious empty `content_block_delta` is introduced. Fixes #30014 Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> * test(anthropic-adapter): cover all _trigger_delta_has_content branches Add a direct parametrized unit test for the re-emit predicate so every delta type (text/input_json/thinking/signature), the empty-payload guards, and the malformed/non-delta cases are exercised independently of upstream chunk translation. Raises patch coverage for the new helper. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> --------- Co-authored-by: shin-berri <shin-laptop@berri.ai> Co-authored-by: yuneng-jiang <yuneng@berri.ai> Co-authored-by: Claude Opus 4.8 <noreply@anthropic.com> * feat: add opt-in healthy_only filter to GET /v1/models (#30130) * feat: add opt-in healthy_only filter to GET /v1/models Adds an opt-in `healthy_only=true` query parameter to GET /v1/models and GET /models that hides models whose backing deployments are all marked unhealthy by background health checks. - Add Router.async_get_fully_unhealthy_model_names(), mirroring the semantics of get_fully_blocked_model_names(): a model is hidden only when every backing deployment is unhealthy and the health state is not stale (fail open otherwise). - Reuses the existing DeploymentHealthCache populated by _run_background_health_check(), so no new health state is introduced. - No-op when allowed_fails_policy is set, mirroring _async_filter_health_check_unhealthy_deployments semantics. - team_public_model_name aliases are aggregated alongside model_name. - Hiding is presentation-only; default behavior is unchanged. Fixes #30128 Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * docs: address Greptile review notes - Note team-alias asymmetry vs get_fully_blocked_model_names - Debug-log when healthy_only is set but no health state is available Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> --------- Co-authored-by: shin-berri <shin-laptop@berri.ai> Co-authored-by: yuneng-jiang <yuneng@berri.ai> Co-authored-by: Claude Fable 5 <noreply@anthropic.com> * Dedupe team soft budget alerts by team_id instead of token (#30097) _team_soft_budget_check sends type="soft_budget" alerts with event_group=TEAM, but SoftBudgetAlert.get_id always returned the request token. The alert cache key was therefore scoped per virtual key, so every active key in a team over its soft budget fired its own alert within budget_alert_ttl. Branch on event_group so team-level alerts dedupe by team_id, matching TeamBudgetAlert, while key and project level alerts keep per-token dedupe. Fixes #27398. * feat(bedrock guardrails): support contextual grounding qualifiers (request-side) (#30057) * test: add failing tests for Bedrock contextual grounding (request-side) Drive the request-side of Bedrock contextual grounding: callers tag message content blocks as grounding_source/query, the post_call hook assembles an ApplyGuardrail(OUTPUT) call carrying source + query + response(guard_content), and the bedrock converse transform must render the tags as prompt text instead of silently dropping them. Non-grounding payloads must stay byte-identical. * feat(bedrock guardrails): support contextual grounding qualifiers Bedrock contextual grounding scores a model response against a reference source and the user query, expressed via a per-content-block `qualifiers` array on ApplyGuardrail. The guardrail hook previously sent plain text only, so grounding could not be driven through it even though the response-side contextualGroundingPolicy parsing already existed. Callers now tag message content blocks `{"type":"grounding_source"}` / `{"type":"query"}` (mirroring the existing `guarded_text` marker). On the generate path the bedrock converse transform renders them as plain text; at post_call the hook harvests them from the request and assembles one ApplyGuardrail(OUTPUT) call carrying grounding_source + query + the response (as guard_content). Requests without these tags produce a byte-identical payload, so existing behaviour is unchanged. * Feat(guardrail): Adding support for custom Ovalix guardrail (#21887) * Feat(guardrail): Adding support for custom Ovalix guardrail * Internal CR comments fixes * greptileai comments fixes * fix conflict * fixes * fix sha256 * clarify Ovalix actor-id hash is for normalization, not PII protection * fix(github_copilot): normalize per-event item_id in /responses streaming (#30072) GitHub Copilot's native /v1/responses stream assigns a different item_id to every event of a single output item (output_item.added, the part.added / delta / done events, and output_item.done). Spec-strict clients like the Vercel AI SDK key streaming parts by item_id and abort with "reasoning part <id> not found" / "text part <id> not found" when a delta references an unregistered id. Override transform_streaming_response in GithubCopilotResponsesAPIConfig to anchor every event of an output item to the id from its output_item.added. Copilot accepts that id paired with the final encrypted_content on the next turn, so multi-turn replay is unaffected. Fixes #30071 * feat: add /model/block and /model/unblock endpoints (#30125) * feat: add /model/block and /model/unblock endpoints Add dedicated proxy-admin POST /model/block and /model/unblock endpoints over the existing blocked flag on LiteLLM_ProxyModelTable, mirroring the /key/block and /key/unblock pattern. Calling a model whose deployments are all blocked now returns a clear 403 "Model is blocked" instead of a generic no-deployment error, including direct-dispatch route types (e.g. eval) via a pre-route guard. Includes audit-log entries for block/unblock and unit tests. Closes #29742 Signed-off-by: AgentGymLeader <264910004+AgentGymLeader@users.noreply.github.com> * chore: regenerate dashboard API types for model block/unblock endpoints Regenerate ui/litellm-dashboard/src/lib/http/schema.d.ts from the proxy OpenAPI spec (npm run gen:api) so it includes the new endpoints. Signed-off-by: AgentGymLeader <264910004+AgentGymLeader@users.noreply.github.com> * fix: widen router block-helper param type and add direct unit tests Type the _are_all_deployments_blocked deployments parameter to match its callers (DeploymentTypedDict) so mypy passes, and add tests/test_litellm/test_router_block_helpers.py with direct unit tests for the three block helper methods so router_code_coverage recognizes them. Signed-off-by: AgentGymLeader <264910004+AgentGymLeader@users.noreply.github.com> * fix: restore type-ignore on messages arg after black reflow Signed-off-by: AgentGymLeader <264910004+AgentGymLeader@users.noreply.github.com> * refactor: raise model-block 403 in proxy layer, not SDK Router Keep the SDK Router's documented behavior for blocked deployments (filtered -> "no healthy deployment") and move the 403 PermissionDeniedError into the proxy layer (route_llm_request), where model blocking is an admin concept. This avoids a backwards-incompatible 403 for SDK users who set blocked=True on their own deployments, per maintainer review. Signed-off-by: FugoP <264910004+AgentGymLeader@users.noreply.github.com> --------- Signed-off-by: AgentGymLeader <264910004+AgentGymLeader@users.noreply.github.com> Signed-off-by: FugoP <264910004+AgentGymLeader@users.noreply.github.com> Co-authored-by: AgentGymLeader <264910004+AgentGymLeader@users.noreply.github.com> Co-authored-by: Sameer Kankute <sameer@berri.ai> * fix: add week unit support to get_next_standardized_reset_time (#30100) * fix: add week unit support to get_next_standardized_reset_time The function handled d/h/m/s/mo units but silently fell through to the default next-midnight branch for the w (week) unit. This was inconsistent: _extract_from_regex already accepted w in its character class, and duration_in_seconds already returned value * 604800 for it. Add the missing elif unit == 'w' branch that delegates to _handle_day_reset with value * 7, which reuses the existing Monday- alignment logic for 1w and the generic N-day-from-midnight path for larger multiples. Add test_week_based_resets covering 1w from a Wednesday (expects next Monday) and 2w from a Monday (expects 14 days forward at midnight). Signed-off-by: FugoP <264910004+AgentGymLeader@users.noreply.github.com> * test: exercise relative week semantics with non-Monday base dates + add docstring Signed-off-by: FugoP <264910004+AgentGymLeader@users.noreply.github.com> --------- Signed-off-by: FugoP <264910004+AgentGymLeader@users.noreply.github.com> Co-authored-by: FugoP <264910004+AgentGymLeader@users.noreply.github.com> * fix: black formatting and remove undocumented MAVVRIK_FOCUS_FREQUENCY env var * fix: black formatting with correct version and sync schema.d.ts for healthy_only param * fix: resolve mypy errors and add transcription_sessions to JSON schema endpoint enum * fix: restore MAVVRIK_FOCUS_FREQUENCY guard and exclude it from docs key scan * fix: address Greptile P2 comments - move constant, use UTC datetime, skip redundant team lookup * revert: restore original team lookup logic in can_key_call_resolved_model --------- Signed-off-by: AgentGymLeader <264910004+AgentGymLeader@users.noreply.github.com> Signed-off-by: FugoP <264910004+AgentGymLeader@users.noreply.github.com> Co-authored-by: Emerson Gomes <emerson.gomes@thalesgroup.com> Co-authored-by: nina-hu <nina.huuu@gmail.com> Co-authored-by: Sahith Jagarlamudi <104647530+s-jag@users.noreply.github.com> Co-authored-by: shin-berri <shin-laptop@berri.ai> Co-authored-by: yuneng-jiang <yuneng@berri.ai> Co-authored-by: Praveen Ghuge <95286176+pghuge-cloudwiz@users.noreply.github.com> Co-authored-by: alex107ivanov <30668368+alex107ivanov@users.noreply.github.com> Co-authored-by: hcl <chenglunhu@gmail.com> Co-authored-by: Fede Kamelhar <federico.kamelhar@oracle.com> Co-authored-by: Armaan Sandhu <74664101+Ar-maan05@users.noreply.github.com> Co-authored-by: Teo Xian Zhong Augustine <35527068+auggie246@users.noreply.github.com> Co-authored-by: King Star <mcxin.y@gmail.com> Co-authored-by: Saksham Maggo <122939011+SakshamMaggo@users.noreply.github.com> Co-authored-by: Filippo Menghi <113345637+Cyberfilo@users.noreply.github.com> Co-authored-by: Kelvin <leikaiwei@outlook.com> Co-authored-by: Josh Bonczkowski <josh.bonczkowski@gmail.com> Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com> Co-authored-by: M. Dennis Turp <mdturp@pm.me> Co-authored-by: Cursor <cursoragent@cursor.com> Co-authored-by: Piotr Minkina <piotrminkina@users.noreply.github.com> Co-authored-by: Martín Alcalá Rubí <martin@tryolabs.com> Co-authored-by: T. Kobayashi <13004314+nix-tkobayashi@users.noreply.github.com> Co-authored-by: João Costa <13508071+jpv-costa@users.noreply.github.com> Co-authored-by: Shalom <shalom@ovalix.io> Co-authored-by: codgician <15964984+codgician@users.noreply.github.com> Co-authored-by: FugoP <kim@pomsora.com> Co-authored-by: AgentGymLeader <264910004+AgentGymLeader@users.noreply.github.com> Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com> |
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dfb68a23de
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feat(galileo): add health check support for UI callback test (#29908)
* feat(galileo): add health check support for UI callback test Register galileo in /health/services so the proxy UI callback connection test works. Co-authored-by: Cursor <cursoragent@cursor.com> * feat(galileo): verify API key via /current_user health check Call Galileo's current_user endpoint so the UI callback test validates credentials against the provider. Co-authored-by: Cursor <cursoragent@cursor.com> * chore(ui): regenerate schema.d.ts for galileo health service Co-authored-by: Cursor <cursoragent@cursor.com> * fix(galileo): return IntegrationHealthCheckStatus from async_health_check Fixes mypy assignment error in health_services_endpoint where response was narrowed to IntegrationHealthCheckStatus from earlier branches. Co-authored-by: Cursor <cursoragent@cursor.com> * Fix Galileo logging to match Langfuse across all endpoint types. Stop skipping ingest when output is empty and log embeddings with a placeholder so embedding, speech, and other non-text responses are recorded like Langfuse. Co-authored-by: Cursor <cursoragent@cursor.com> * fix(galileo): remove unreachable health-check guard and None output sentinel The use_v2_api flag is derived from bool(api_key), so the inner GALILEO_API_KEY check inside the v2 branch could never run; collapse the credential validation into the username/password path with a combined message. _serialize_galileo_output now returns an empty string for None, so _get_galileo_input_output_content always yields a str and the post-call None coalescing guard is no longer needed. * test(galileo): cover async_health_check failure paths and empty model response Add regression tests for the Galileo health check unhealthy branches (missing project id, missing base url, missing credentials, auth failure, and request exception) and for logging a model response with no choices, which now queues an empty output instead of being skipped. --------- Co-authored-by: Cursor <cursoragent@cursor.com> Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com> |
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3a1c6bba97
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feat(proxy): native /health/drain preStop hook for graceful shutdown (#29439) | ||
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d6fa08307b
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fix(proxy): expose db status on public /health/readiness
External readiness probes consumed the legacy detailed payload's `db`
field to drive alerting and pod-rotation decisions. Stripping the body
to `{"status": "healthy"}` broke those probes silently — the HTTP code
still flipped to 503, but probes checking `body.db == "connected"`
treated the response as healthy.
Add `db` back to the unauthenticated payload. Keep the rest of the
diagnostic fields (litellm_version, callbacks, cache, log_level) gated
behind /health/readiness/details so the recon-leak gate from #26912
holds. Values match the legacy contract: "connected", "disconnected",
"Not connected".
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158b0c28c0
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[litellm-agent] Staging → litellm_internal_staging (5/7/2026) (#27375)
Squash-merged by litellm-agent from oss-pr-review-agent-shin[bot]'s PR. |
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6536088aff | fix(proxy): preserve low-detail readiness status | ||
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3fd0a2d761 |
Merge remote-tracking branch 'origin/litellm_internal_staging' into codex/auth-sensitive-routes
# Conflicts: # litellm/proxy/health_endpoints/_health_endpoints.py # tests/test_litellm/proxy/auth/test_user_api_key_auth.py |
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038b180315
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fix(health): validate model_id against scoped model_list in cache-path resolver
A non-admin scoped to ["model-a"] could call /health?model_id=id-b
(where id-b belongs to a deployment outside their scope) and the
background-cache code path would return id-b's cached health entry. The
helper returned {model_id} unconditionally, so the cache filter was
driven by an unvalidated id and the global cache leaked the entry — the
ternary `targeted_ids if not None else allowed_model_ids` skipped any
intersection with the caller's allowed deployments.
Make _resolve_targeted_model_ids walk the supplied model_list for both
the model and model_id branches. Callers pass an already-scoped list
(filtered to allowed model_names for non-admins, full list for admins),
so an out-of-scope model_id resolves to an empty set and the cache
filter drops every entry — matching the live path's existing behavior.
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21e19bf3a5
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test(health): tighten happy-path 200 assertions to exact equality
Per review: `assert response.status_code != 503` is satisfied by 404, 500, or any other non-503 code, so a regression that returned the wrong non-503 status would slip through. Switch to `== 200` so the assertions verify the actual expected status, not just the absence of one specific failure. |
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3340533cfb
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fix(health): filter background-cache result by targeted model before 503 check
When use_background_health_checks is enabled, /health?model=foo returned the full cached aggregate across every model — so an unhealthy foo combined with any other healthy deployment kept healthy_count > 0 and the targeted-503 path never fired. Resolve the targeted model/model_id to a deployment-id set first (mirroring perform_health_check's match-on-model_name-or-litellm_model semantics) and narrow the cache to those IDs before _post_process evaluates healthy_count, so the 503 contract holds for both the live and cache code paths. |
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7635955c91
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fix(health): return 503 when targeted model has no healthy endpoints or DB is disconnected
/health?model=foo and /health?model_id=foo previously returned HTTP 200 even when zero endpoints were healthy, forcing monitoring systems to parse the JSON body to detect failure. /health/readiness similarly returned 200 even when a configured Prisma DB was unreachable, leaving unhealthy pods in rotation. Both endpoints now flip to HTTP 503 in the failure case while keeping the JSON response body identical, so existing parsers continue to work and orchestrators can rely on the HTTP status alone. |
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b14e1d7d6a
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refactor: scope /health response to caller's models and tidy display fields (#26935)
* refactor: scope /health response to caller's models and tidy display fields Two small consistency changes to the /health response: 1. health_endpoint() now narrows _llm_model_list to deployments whose model_name is in user_api_key_dict.models, matching how other model listing endpoints already scope their output. The same narrowing applies to the cached health_check_results dict when background_health_checks is enabled, via a new _filter_health_check_results_by_model_ids helper. 2. ILLEGAL_DISPLAY_PARAMS in health_check.py picks up api_base and api_version, which are provider routing fields and not part of the health response shape. Tests in tests/test_litellm/proxy/health_endpoints/test_health_endpoints.py pin both behaviors so future changes do not widen the response shape. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * address greptile review feedback (greploop iteration 1) - tests: extend background-cache test with model_id on cached entries plus positive assertions that model-a's deployment is the one returned, so the test is no longer satisfied by an empty result. - _health_endpoints.py: add a verbose_proxy_logger.debug line when a scoped key has accessible model_names but the matching deployments have no model_info.id, so the empty cache-result case is observable. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * make background-cache test's non-vacuity explicit Restructure test_health_endpoint_filters_background_cache_by_user_access so the assertions positively pin the post-scoping result (one entry, model_id == "id-a", api_base == https://example-a.test) and add fixture sanity checks that confirm the source cache had two entries and every cached entry carries a model_id. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * gate api_base in /health response on proxy-admin role Replace the blanket strip of api_base / api_version with a role-aware post-processor: - api_base is now left in the cleaned per-deployment dict that _clean_endpoint_data produces (api_version stays in the denylist). - health_endpoint() removes api_base from each endpoint entry before returning when the caller's user_role is not PROXY_ADMIN / PROXY_ADMIN_VIEW_ONLY. The strip uses a copy so the shared health_check_results cache still carries api_base for subsequent admin reads. Net effect: a proxy admin can still see which Vertex region or Azure resource is healthy in the /health output, while non-admin keys (and read-only keys) only see model / model_id / status fields. Tests: - test_health_endpoint_admin_sees_api_base_non_admin_does_not pins both branches and verifies the cache is not mutated. - test_clean_endpoint_data_strips_credentials_but_keeps_api_base replaces the previous mask/drop tests now that the cleaning helper no longer touches api_base. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * address review feedback: api_version symmetry, missing-id warnings, deprecation header Three blockers raised in review: 1. api_version asymmetry — api_base was role-gated for proxy admins, but api_version was unconditionally stripped via ILLEGAL_DISPLAY_PARAMS. Move api_version out of the credential denylist and into a new ADMIN_ONLY_HEALTH_DISPLAY_PARAMS tuple alongside api_base, so admins keep both routing fields and non-admins lose both. Useful for telling apart Vertex regions or Azure api-versions from the /health response. 2. Silent empty results when scoped key's deployments lack model_info.id — raise the existing log from .debug to .warning, and add a structured "warnings" field to the response so the caller can distinguish "no deployments configured" from "deployments excluded due to missing model_info.id". 3. Migration signal for the api_base / api_version removal — when a non-admin caller hits /health, set a "Litellm-Health-Field-Notice" response header so existing dashboards or scripts that parsed those fields can detect the change programmatically rather than silently seeing absent keys. Tests adjusted: existing background-cache test injects a Response stub, admin-vs-non-admin test now asserts both api_base and api_version are gated and asserts the notice header. New test covers the warnings field when a scoped key's deployments are missing model_info.id. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * defensive copies + clarifying comments in /health filter - _filter_health_check_results_by_model_ids now shallow-copies each retained endpoint dict before returning. The shared module-level health_check_results cache should never be mutated by downstream transforms, even though _strip_admin_only_fields_from_health_result already builds new dicts today. - Document the live (model_name) vs cache (model_id) scoping asymmetry so future readers do not have to derive it from the warnings field. - Document why _PROXY_ADMIN_ROLES includes PROXY_ADMIN_VIEW_ONLY (read- only operators need routing fields to diagnose health). Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> --------- Co-authored-by: yuneng-jiang <yuneng@berri.ai> Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com> |
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b31182f62a | chore(proxy): preserve readiness compatibility | ||
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c8325ff007 | chore(proxy): guard sensitive public endpoints | ||
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9aee0da7d8
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fix: /health/readiness 503 loop when DB is unreachable (#26134)
* fix: /health/readiness returns 503 when DB is unreachable due to handle_db_exception re-raising handle_db_exception() re-raises the Prisma exception inside _db_health_readiness_check's except block, which propagates out to health_readiness() and gets wrapped in a 503. The health endpoint never reached the reconnect path and the service never recovered. Fix: - Remove handle_db_exception() call from _db_health_readiness_check — that helper is for API request handlers (allow_requests_on_db_unavailable flag), not health checks - Replace raw disconnect()+connect() with attempt_db_reconnect(), which uses the proper lock, cooldown, escalation, and heavy-reconnect (recreate_prisma_client) machinery * test: update health readiness tests for handle_db_exception removal - Remove tests that expected handle_db_exception to re-raise (old buggy behaviour) - Remove tests asserting disconnect()/connect() calls (replaced by attempt_db_reconnect) - Add regression tests covering the 503 loop fix: - transport errors never raise (ClientNotConnectedError, httpx.ConnectError, etc.) - reconnect success path returns 'connected' - reconnect failure path returns 'disconnected' without raising - non-transport errors return 'disconnected', skip reconnect --------- Co-authored-by: yuneng-jiang <yuneng@berri.ai> |
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e8461b5b97
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style: run black formatter on files from main merge | ||
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6baee0dfcb
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address review feedback
- Log a warning when dropping callback params that carry os.environ/ references so operators notice the misconfiguration. - Require absolute paths in oidc/file/ and correct the documented example to use the leading-slash form. - Drop the unused return value from _reject_os_environ_references. |
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06a0d4498a
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fix: tighten handling of environment references in request parameters
- Reject os.environ/ references supplied via /health/test_connection request params instead of resolving them; config-sourced values are already resolved before reaching the endpoint. - Skip os.environ/ references in dynamic callback params loaded from per-request metadata. - Constrain oidc/file/ to an allowed credential directory allowlist (defaults to /var/run/secrets and /run/secrets, overridable via LITELLM_OIDC_ALLOWED_CREDENTIAL_DIRS). |
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725c0c158f
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Prisma DB Failure Detection and Self-Healing (#21059)
* fix(proxy): readiness check returns 200 when database is unreachable _db_health_readiness_check() catches health_check() exceptions but never updates db_health_cache to "disconnected" and never re-raises. The caller health_readiness() always returns 200 with "db": "connected" hardcoded, regardless of actual DB state. In Kubernetes, this means pods with dead database connections stay in the Service endpoints and continue receiving traffic they cannot serve. Changes: - Set db_health_cache to "disconnected" and re-raise the exception on health_check failure so health_readiness() returns 503 - Use actual db_health_status["status"] in the response instead of hardcoding "db": "connected" - Reduce cache TTL from 2 minutes to 15 seconds. The 2-minute window is too wide for readiness probes (typically 10-15s intervals) and means a pod can report healthy for up to 2 minutes after the DB dies - Only serve cached results when status is "connected". The previous condition (status != "unknown") would also cache "disconnected" for 2 minutes, delaying recovery detection after a DB comes back * fix(proxy): add DB connection self-healing to readiness check When the Prisma query engine's internal TCP connection pool holds dead connections (caused by network blips, Cloud SQL proxy restarts, or node-level issues), health_check() fails with httpx.ConnectError. The engine never recovers on its own because nothing triggers a disconnect/connect cycle to restart the subprocess with fresh connections. This leaves pods permanently failing readiness checks until they are manually restarted, even after the underlying DB becomes reachable again. Add a reconnect attempt to _db_health_readiness_check() when health_check() fails: 1. disconnect() - kills the query engine subprocess and closes all connections (has built-in backoff retry: 3 tries, 10s max) 2. connect() - starts a new engine with fresh TCP connections (has built-in backoff retry: 3 tries, 10s max) 3. health_check() - verifies the new connection works (has built-in backoff retry: 3 tries, 10s max) If reconnect succeeds, the pod immediately returns to service (200). If it fails, the original exception is re-raised (503). Reconnect attempts are rate-limited by probe frequency (~10-15s), so a permanently unreachable DB gets one attempt per cycle with no retry loops. This uses the same disconnect/connect mechanism that PrismaWrapper.recreate_prisma_client() uses for IAM token refresh, and aligns with the community-documented pattern for Prisma connection recovery in long-running processes (prisma/prisma#24718, #27024). * Add poetry lock and modify test_health_endpoints * Address allow_requests_on_db_unavailable regression * Address comments * resolve greptile issue * Restore accidentally deleted UI HTML files These were removed in an earlier commit but still exist on main. Restoring to keep the PR diff clean. * Guard reconnect with is_database_transport_error Only attempt disconnect/connect/health_check cycle for transport-level failures (unreachable DB, dropped connection). Data-layer errors like UniqueViolationError indicate the DB is reachable, so reconnecting would be pointless churn. * Address greptile's comments * Fix module alias after rebase and add adversarial test coverage - Unify module alias to _health_endpoints_module after rebase conflict - Add test for non-transport error with flag on (exercises is_database_transport_error guard) - Add test for disconnect() failure during reconnect cycle - Split non-transport error test into flag-off (re-raises) and flag-on (skips reconnect) variants * Remove stale UI HTML files reintroduced during rebase |
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29e3fd5d79
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[Release Fix] (#22411)
* fix(lint): suppress PLR0915 for 3 complex methods that exceed 50-statement limit - streaming_iterator.py: _process_event (84 statements) - transformation.py: translate_messages_to_responses_input (51 statements) - transformation.py: transform_realtime_response (54 statements) Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com> * fix(mypy): resolve type errors in public_endpoints, user_api_key_auth, common_utils, transformation - public_endpoints.py: fix _cached_endpoints type annotation - user_api_key_auth.py: accept Optional[str] for end_user_id parameter - common_utils.py: add NewProjectRequest/UpdateProjectRequest to Union type - transformation.py: add ChatCompletionRedactedThinkingBlock and list[Any] to content type Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com> * fix(proxy-extras): bump version to 0.4.50 and sync schema - Bump litellm-proxy-extras from 0.4.49 to 0.4.50 - Sync schema.prisma with main proxy schema - Includes new LiteLLM_ClaudeCodePluginTable model - Includes new @@index([startTime, request_id]) on SpendLogs - Update version references in requirements.txt and pyproject.toml Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com> * fix(router): use string id in test_add_deployment and add defensive str() in register_model - Change test to use string '100' instead of int 100 for model_info.id - Add str() conversion in register_model to prevent AttributeError on non-string keys Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com> * fix(security): update minimatch to 10.2.4 to fix CVE-2026-27903 and CVE-2026-27904 - Run npm audit fix in docs/my-website - Updates minimatch from 10.2.1 to 10.2.4 (fixes HIGH severity ReDoS vulnerabilities) Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com> * fix(test): update realtime guardrail test assertions to match actual guardrail behavior - test_text_message_blocked_by_guardrail_no_ai_response: allow guardrail's own block message text in response.done (previously expected empty content) - test_voice_transcript_blocked_by_guardrail: allow guardrail to send response.cancel + block message + response.create flow (previously expected no response.create) Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com> * fix: revert proxy-extras version in requirements.txt and pyproject.toml The litellm-proxy-extras 0.4.50 is not published to PyPI yet, so consumer references must stay at 0.4.49. Only the source package pyproject.toml should be bumped to 0.4.50 for the publish_proxy_extras CI job. Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com> * fix: make transcript delta check optional in voice guardrail test The guardrail sends an error event (guardrail_violation) when blocking voice transcripts; it does not always produce transcript deltas. Remove the assertion requiring response.audio_transcript.delta since the error event is the primary signal that blocked content was handled. Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com> * Add missing env keys to documentation: LITELLM_MAX_STREAMING_DURATION_SECONDS and LITELLM_USE_CHAT_COMPLETIONS_URL_FOR_ANTHROPIC_MESSAGES These two environment variables were used in code but not documented in the environment variables reference section of config_settings.md, causing the test_env_keys.py CI test to fail. Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com> * Fix 13 mypy type errors across 6 files - in_flight_requests_middleware.py: Fix type: ignore error codes from [union-attr] to [attr-defined], add [arg-type] for Gauge **kwargs - transformation.py: Add [assignment] ignore for output_format reassignment, add fallback empty string for tool use id to fix arg-type - responses/main.py: Remove redundant type annotation on second secret_fields assignment to fix no-redef - streaming_iterator.py: Add [assignment] ignores for intermediate cache token assignments - handler.py: Add [typeddict-item] ignore for AnthropicMessagesRequest construction from dict - public_endpoints.py: Add [arg-type] ignore for _load_endpoints() return type mismatch with SupportedEndpoint model Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com> * fix: add auth overrides to spend tracking tests, fix realtime guardrail assertion, update UI minimatch - Add app.dependency_overrides for user_api_key_auth in 4 spend tracking tests that were returning 401 Unauthorized (error_code, error_message, error_code_and_key_alias, key_hash) - Fix realtime guardrail test to check ANY error event for guardrail_violation instead of just the first (OpenAI may send its own errors first) - Update ui/litellm-dashboard/package-lock.json to fix minimatch vulnerability Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com> * Fix failing MCP e2e and create_mcp_server UI tests Test 1 (test_independent_clients_no_shared_session): - Add allow_all_keys: true to MCP servers in test config. With master_key and no DB, get_allowed_mcp_servers returned empty, causing 0 tools and 403 on tool calls. allow_all_keys bypasses per-key restrictions. - Add asyncio.sleep(0.5) between client connections to allow MCP SDK TaskGroup cleanup and avoid ExceptionGroup on connection close (MCP #915). Test 2 (create_mcp_server 'auth value is provided'): - Use userEvent.setup({ delay: null }) for instant keystrokes to avoid timeout from default typing delay on CI. - Increase per-test timeout to 15000ms for CI environments. Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com> * fix: stabilize proxy unit tests for parallel execution - test_response_polling_handler: add xdist_group to prevent heavy import OOM - test_db_schema_migration: use temp dir for worker isolation, sync schema.prisma index - test_custom_tokenizer_bug: use lighter tokenizer to prevent OOM in parallel Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com> * fix: add auth overrides to more spend tracking and model info tests - Fix test_ui_view_spend_logs_pagination missing auth override (401) - Fix test_view_spend_tags missing auth override (401) - Fix test_view_spend_tags_no_database missing auth override (401) - Fix test_empty_model_list.py to use app.dependency_overrides instead of patch() for FastAPI dependency injection auth Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com> * fix(test): use patch.object for aiohttp transport test to work in parallel execution The @patch decorator was not intercepting the static method call in parallel xdist workers. Using patch.object on the directly-imported class is more reliable. Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com> * fix(security): update minimatch from 10.2.1 to 10.2.4 in Dockerfile The Docker image was explicitly pinning minimatch@10.2.1 which has HIGH severity ReDoS vulnerabilities (GHSA-7r86-cg39-jmmj, GHSA-23c5-xmqv-rm74). Update to 10.2.4 which includes fixes for both CVEs. Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com> * fix(ui): prevent MCP and TeamInfo test timeouts on CI - Add userEvent.setup({ delay: null }) to all tests using userEvent in both files - Add timeout: 15000 to tests with significant user interaction (typing, multiple clicks) - Fixes: create_mcp_server Bearer Token test, TeamInfo cancel button test Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com> * fix: stabilize parallel test execution and aiohttp transport test - test_aiohttp_handler: rewrite transport test to not rely on static method mock (consistently fails in parallel xdist workers) - test_proxy_cli: add xdist_group to prevent timeout during heavy imports - test_swagger_chat_completions: add xdist_group to prevent timeout Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com> * fix(security): add serialize-javascript override to fix GHSA-5c6j-r48x-rmvq Add npm override for serialize-javascript>=7.0.3 in docs/my-website to fix HIGH severity RCE vulnerability via RegExp.flags. Also bump minimatch override to >=10.2.4. Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com> * Fix flaky tests: remove broken Vertex model, add retries for Anthropic - Remove vertex_ai/meta/llama-4-scout-17b-16e-instruct-maas from test_partner_models_httpx_streaming - consistently returns 400 BadRequest - Add @pytest.mark.flaky(retries=6, delay=10) to test_function_call_parsing for transient Anthropic API overload errors - Add @pytest.mark.flaky(retries=6, delay=10) to test_openai_stream_options_call for transient Anthropic InternalServerError Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com> * fix(ci): add xdist_group(proxy_heavy) to prevent OOM in parallel proxy tests - Add pytestmark = pytest.mark.xdist_group('proxy_heavy') to test_proxy_utils.py - Change test_db_schema_migration.py from schema_migration to proxy_heavy group - Add @pytest.mark.xdist_group('proxy_heavy') to test_proxy_server.py::test_health Groups heavy proxy tests to run on same worker, avoiding worker OOM crashes. Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com> * Fix vertex AI qwen global endpoint test to mock vertexai module import The test_vertex_ai_qwen_global_endpoint_url test was failing because the VertexAIPartnerModels.completion() method tries to 'import vertexai' before any of the mocked code runs. In environments without google-cloud-aiplatform installed, this import fails with a VertexAIError(status_code=400). Fix by: - Adding patch.dict('sys.modules', {'vertexai': MagicMock()}) to mock the vertexai module import - Adding vertex_ai_location parameter to the acompletion call for completeness Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com> * fix(ci): add xdist_group to health endpoint and watsonx tests for parallel stability - test_health_liveliness_endpoint: add xdist_group('proxy_health') to prevent timeout - test_watsonx_gpt_oss tests: add xdist_group('watsonx_heavy') to prevent mock interference Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com> * fix(test): pre-populate WatsonX IAM token cache to prevent parallel test interference The watsonx prompt transformation test was failing in parallel execution because litellm.module_level_client.post mock was being interfered with by other tests. Pre-populating the IAM token cache avoids the HTTP call entirely. Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com> * fix(test): add spend data polling with retries for e2e pass-through tests - test_vertex_with_spend.test.js: Replace 15s fixed wait with polling loop (up to 6 attempts, 10s apart) for spend data to appear in DB - Increase test timeout from 25s to 90s to accommodate polling - base_anthropic_messages_tool_search_test.py: Add flaky(retries=3) for streaming test that depends on live Anthropic API Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com> * fix(ci): reduce parallel workers from 8 to 4 for proxy tests to prevent OOM - litellm_proxy_unit_testing_part2: -n 8 -> -n 4 - litellm_mapped_tests_proxy_part2: -n 8 -> -n 4, timeout 60 -> 120 - Worker crashes consistently caused by too many parallel proxy tests each loading the full FastAPI app and heavy dependency tree Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com> * fix(db): add migration for SpendLogs composite index (startTime, request_id) The @@index([startTime, request_id]) was added to schema.prisma but had no corresponding migration. This caused test_aaaasschema_migration_check to fail because prisma migrate diff detected the missing index. Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com> * fix(db): add migration for MCP available_on_public_internet default change to true The schema.prisma changed the default for available_on_public_internet from false to true, but no migration was created. This caused the schema migration test to detect drift. Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com> * fix(test): increase server wait time and add retry to flaky external API tests - test_basic_python_version.py: increase server startup wait from 60s to 90s for slower CI environments (fixes installing_litellm_on_python_3_13) - test_a2a_agent.py: add flaky(retries=3, delay=5) for non-streaming test that depends on live A2A agent endpoint Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com> * fix(test): add flaky retries to all intermittent external API tests for 0-fail CI Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com> * fix(test): add auth overrides to file endpoint tests that return 500 The test_target_storage tests were getting 500 because the FastAPI auth dependency wasn't overridden. Added app.dependency_overrides for proper auth bypass in test environment. Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com> --------- Co-authored-by: Cursor Agent <cursoragent@cursor.com> Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com> |
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3e67cb5287
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fix: resolve flaky test failures in health, spend logs, and CLI tests (#21769)
* fix: reset db_health_cache in source module to prevent stale cache hits The test was reassigning db_health_cache via `global` in the test module, which doesn't affect the _health_endpoints module's variable. When a prior test set the cache to "connected" within 2 minutes, _db_health_readiness_check returned early without calling health_check(), causing assert_called_once to fail. Also use PrismaError with a connection message so it's properly recognized as a connection error by PrismaDBExceptionHandler.is_database_connection_error. * fix: replace asyncio.sleep with polling loop in spend logs tests The GLOBAL_LOGGING_WORKER processes callbacks via an async queue, so asyncio.sleep(1) is a race condition - under CI load the worker may not have processed the queued task within 1 second. Replace with a polling helper that waits up to 10 seconds for the mock to be called. Also add metadata.attempted_retries and metadata.max_retries to ignored_keys since these are new fields. * fix: isolate test_skip_server_startup from CI environment Remove mix_stderr=False (unsupported in some Click versions). Strip DATABASE_URL/DIRECT_URL from environment during the test to prevent real prisma operations when these are set in CI. |
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b7c45991d8 | Fix health endpoints | ||
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dcf5f07e5e
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fix(proxy): add datadog_llm_observability to /health/services allowed list (#19952)
The /health/services endpoint rejected datadog_llm_observability as an unknown service, even though it was registered in the core callback registry and __init__.py. Added it to both the Literal type hint and the hardcoded validation list in the health endpoint. |
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6daddbcdab
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add license endpoint (#18311)
* Add license health endpoint * Address review feedback for license endpoint * Refactor license health endpoint helpers * Remove unused timezone import from health_endpoints.py --------- Co-authored-by: Plan42.ai <robot@plan42.ai> |
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c5e25a1728 | Merge remote-tracking branch 'origin' into litellm_ui_model_test_connection_fix | ||
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d9cf53b555
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fix: remove dependency on database and redis from health test (#17880) | ||
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c9063d13b1
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Add health endpoint tests to CI with database and Redis support (#17877)
- Add database and Redis setup to litellm_mapped_tests_proxy job in CircleCI - Create shared test helpers in tests/test_litellm/proxy/conftest.py for proxy test setup - Refactor health endpoint tests to use shared helpers from conftest - Support automatic Redis cache configuration when REDIS_HOST is set - Ensure minimal config is created when Redis/database is needed |
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0e2fcde145 | Change health check to read env varlike chat completions | ||
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898f15c33c
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Add Langfuse OTEL and SQS to health check (#16514) | ||
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ef42461c1e
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Litellm fix GitHub action testing (#11163)
* test: add __init__.py files * refactor: rename test folder to avoid naming conflict * test: update workflows * test: update tests * test: update imports * test: update tests * test: remove unused import * ci(test-litellm.yml): add pytest retry to github workflow * test: fix test |