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79 commits
| Author | SHA1 | Message | Date | |
|---|---|---|---|---|
Devin AI
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4fd69b25e1 | Merge remote-tracking branch 'origin/main' into litellm_registry_audit_2026_09_14 | ||
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kerry
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ba6bcd747f |
chore: merge origin/main into test cleanup
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> |
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yassin
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b13cf21fd1 |
fix(vertex_ai): bill Gemini Omni Interactions usage and Veo sampleCount on passthrough
Route Vertex and Gemini /interactions create responses through the shared Interactions usage transformation so SpendLogs carry per-modality tokens and cost instead of zeros, and carry parameters.sampleCount into Veo usage as video_count so duration-based video cost is multiplied by the number of generated videos Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> |
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kerry
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62aa21e810 |
test: drop remaining tests that pin cost-map vendor facts
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> |
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Devin AI
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65a2e4f503 |
test(cost): derive Nova cache expectations from registry and cite Gemini alias targets
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> |
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Devin AI
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ae5451b07d |
Merge remote-tracking branch 'origin/main' into litellm_registry_audit_2026_09_14
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> # Conflicts: # tests/test_litellm/llms/gemini/test_cost_calculator.py |
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Devin AI
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da7853c20a |
test: drop tests that pin vendor facts and add the CLAUDE.md rule
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> |
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Devin AI
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631ba7f9e3 |
fix(models): dedupe merged keys, price gemini *-latest aliases at live targets, add Nova cache read prices and Fireworks deprecation dates
Absorbs #41148 and #41152 into the rolling registry PR. Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> |
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Marty Sullivan
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228d87db63 |
test(gemini-live): assert grounding counters on the emitted response.done event
Replaces a patch.object spy on a static method with a read of the public return value, which also covers the usage bridge the spy ran ahead of. |
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Marty Sullivan
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b1262b05f4 |
fix(gemini-live): count grounding requests so Live sessions carry their query fee
Live reports grounding in the server frames and never in usageMetadata, so nothing set the counter the cost path reads and the per-query charge was missing from every grounded session. Google bills a grounded Live prompt on top of its tokens, and that fee dwarfs the token cost, so a non-zero spend check could never catch it. Both Live surfaces now read serverContent.groundingMetadata where they build usage, and reuse the chat path's own classifier so web search and Maps keep their separate SKUs rather than being counted together. Separately, a client sending turn_detection: null reached a membership test against None and took the session down with no traceback, while the branch immediately above already guards for it. Live emits grounding and usage on the same frame, verified against Vertex directly, so the realtime counter is set where usage is built. (cherry picked from commit c997436be34beb2e84f8468286b8016c195eca92) (cherry picked from commit 26c8d4822fc1c5c44fe8f72f4f57473a2ce1acbf) |
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mateo
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5cfe20a68d |
test: collapse blank lines left by removed tests
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> |
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mateo
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3023497590 |
test: drop static cost-map value assertions
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> |
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mateo-berri
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05e4d2f946 | fix(guardrails): scan generateContent systemInstruction text and drop fastapi import from handler tests | ||
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mateo-berri
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a099be02fd |
fix(guardrails): resolve generateContent routes and async-first passthrough call types
API_ROUTE_TO_CALL_TYPES listed the sync llm_passthrough_route first, so every
call_types[0] consumer resolved /llm_passthrough to a call type with no
guardrail translation handler, and the {model}:generateContent patterns never
matched a concrete route because the placeholder segment carries a literal
suffix the matcher treated as an exact segment. Reorder the passthrough
entries async-first, teach the matcher placeholder-with-suffix segments plus
suffixed multi-segment tails (mirroring FastAPI's {model_name:path}), add the
missing /v1beta generateContent entries, and register a Google GenAI
guardrail translation handler so guardrails actually scan generateContent
requests, responses, and streams.
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mateo-berri
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2bd7b58640 |
fix(registry): correct xai retired slug pricing, bedrock grok caching, and unsourced entries
Reprice ten more retired xAI slugs (grok-3 and grok-3-mini families, grok-4-1-fast) to the grok-4.3 rates they now bill at, with family-correct deprecation dates. Restore cache_read_input_token_cost on the Bedrock Grok 4.6 entries so implicit cache hits bill at the cache-read rate while explicit cachePoint stays unsupported. Drop the unsourced 1080p video rate and the gemini/ live native-audio entry the Gemini API 404s on. Add Groq qwen3.8-27b tool-use flags per Groq docs. Extend the xai and gemini tests to lock all of this in |
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Devin AI
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9df3a4fc1c |
fix(model_prices): registry audit - add groq qwen3.8-27b, gemini live native audio (from #38573), anthropic sources
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> |
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Mateo Wang
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0c0a1f4eb1
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Merge pull request #38457 from BerriAI/litellm_realtime_audio_output_tokens
fix(realtime): bill Gemini Live native-audio output tokens at the audio rate |
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Mateo Wang
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e5b2f5bec2
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Merge pull request #38561 from BerriAI/litellm_transcription_srt_vtt_synthesis
fix(transcription): synthesize srt/vtt output for adapters without native subtitle formats |
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mateo-berri
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c860d511db | Merge remote-tracking branch 'origin/litellm_internal_staging' into litellm_realtime_audio_output_tokens | ||
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mateo-berri
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f2e64d9818 | fix(gemini): ignore non-string response_format when deciding on word timestamps | ||
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mateo-berri
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c251703e8b | fix(realtime): bill trailing audio when a Gemini transcribe Live session closes | ||
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mateo-berri
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5b80fb0fc0 |
fix(transcription): synthesize srt/vtt output for adapters without native subtitle formats
Extract the Soniox SRT/VTT cue grouping and rendering into a shared litellm_core_utils/audio_utils/subtitle_utils module, have Gemini transcription request word timestamps whenever response_format is srt or vtt, and let the http handler rewrite the response text into the synthesized subtitle document (dropping the internally requested words array) for any provider config that opts in via supports_subtitle_synthesis |
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mateo-berri
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462942de65 |
fix(gemini): bill transcribe-live sessions from streamed audio duration
Gemini Live sends no usageMetadata and no turnComplete for gemini-3.5-transcribe-live sessions, so realtime spend logged as 0.0. Attach estimated usage to the input_audio_transcription.completed event using Google's published billing estimate (25 audio tokens/sec of input, 175 text tokens/min of output) derived from the streamed pcm16 audio duration, gated to audio_transcription-mode models so conversational Live models keep billing through usageMetadata. Also capture that usage in the provider_config backend path so realtime cost calculation sees it. |
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mateo-berri
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e44e2fe242 | fix(gemini): keep transcription-only Live turn usage when generationComplete arrives without a delta | ||
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mateo-berri
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ef4c84dc36 |
feat(gemini): day-0 support for gemini-3.5-transcribe and transcribe-live
Adds a Gemini audio transcription config that maps /v1/audio/transcriptions onto the Interactions API (speaker attribution and word timestamps land on the OpenAI verbose_json shape), registers both models with published pricing, routes text-only Live sessions to TEXT responseModalities so gemini-3.5-transcribe-live sessions survive, and makes the token-priced transcription cost path provider-aware instead of hardcoding OpenAI. |
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mateo-berri
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449c091391 | fix(realtime): carry audio output tokens into response.done usage so Gemini Live native audio bills at the audio rate | ||
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mateo-berri
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815fa0ff08 |
fix(anthropic_adapter): carry web search usage into /v1/messages cost breakdown
For non-Anthropic models served over /v1/messages, the outer wrapper recomputes cost over the adapter-translated Anthropic response dict. That dict dropped every web search usage signal, so the recompute overwrote the correct cost breakdown with a token-only one: x-litellm-response-cost-tool-usage read 0.0 and x-litellm-response-cost-original excluded the search cost, while the total kept it. The adapter now maps web search request counts (from Usage.server_tool_use or Gemini's prompt_tokens_details) into usage.server_tool_use.web_search_requests, matching the Anthropic API shape, and the Gemini web search cost calculator falls back to server_tool_use when prompt_tokens_details carries no count. The shared get_web_search_requests helper is now public since five modules consume it. Resolves LIT-6288 |
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mateo-berri
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901bea41e7 |
Merge branch 'litellm_internal_staging' of https://github.com/BerriAI/litellm into litellm_gemini_latest_cache_read_rates
# Conflicts: # tests/test_litellm/llms/gemini/test_cost_calculator.py |
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mateo-berri
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1e1c231076 | fix(model_prices): bill gemini -latest/preview alias cache reads at 10% of input | ||
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Mateo Wang
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40005cf7f8
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Merge pull request #37724 from bisma-nawaz/fix-37647-staging
fix: map Gemini ON_DEMAND_FLEX traffic type to flex service tier |
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mateo-berri
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885d95d71b |
Merge remote-tracking branch 'origin/litellm_internal_staging' into pr37724
# Conflicts: # tests/test_litellm/test_cost_calculator.py |
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mateo-berri
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dca5144dba |
Merge branch 'litellm_internal_staging' of https://github.com/BerriAI/litellm into litellm_gemini_maps_grounding_cost
# Conflicts: # litellm/llms/vertex_ai/gemini/vertex_and_google_ai_studio_gemini.py |
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mateo-berri
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b9a790899a |
fix(gemini): bill Google Maps grounding as its own SKU
Gemini API Maps-grounded prompts were billed as web search and Vertex AI Maps-grounded prompts were not billed at all. Classify grounding metadata per candidate into web search vs Maps requests, carry a distinct google_maps_grounding_requests usage counter through non-streaming and streaming paths, and price it via the new google_maps_grounding_cost_per_query cost map key with per-query and per-prompt defaults keyed off web_search_billing_unit. Fixes #35906 |
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mateo-berri
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aabbc3204b |
fix(gemini-realtime): drop the native-audio speechConfig strip on Google AI Studio too
Live probes against every gemini_native_audio model on both providers show setup accepts a valid prebuilt voice and 1007s only unknown voice names, so the strip predicate rested on a false premise and silently discarded the client's voice on AI Studio native-audio sessions |
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Yucheng Zhu
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27207659f8 | fix(gemini-realtime): drop OpenAI stock voice names instead of pairing them to Gemini voices | ||
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Yucheng Zhu
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8e1dcf02ea | style(gemini-realtime): wrap overlong docstrings to the 120 char limit | ||
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Yucheng Zhu
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002407af90 | fix(gemini-realtime): map OpenAI stock voice names to Gemini prebuilt voices | ||
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yuneng-jiang
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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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yuneng-jiang
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693797420d
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test: unwind environment writes in tests/test_litellm with monkeypatch (#37806)
* test: use monkeypatch.setenv for env writes in tests/test_litellm `os.environ["X"] = v` inside a test leaks the value into every test that runs after it in the same worker, so ordering decides the result. 262 of those writes across 40 files now go through pytest's `monkeypatch` fixture, which restores the previous value at teardown. The rewrite skips any test that a mock.patch-family decorator wraps, any test with defaulted positional parameters, any test whose own name is called directly elsewhere, and rebinds nothing inside nested defs, because in each of those cases appending a fixture parameter changes what pytest or mock binds. Ratchets the TQ004 ceiling from 768 to 506. * fix(test): delete the key through monkeypatch instead of popping it first Five tests popped a key straight out of `os.environ`, ran, then restored it with `monkeypatch.setenv`. By the time monkeypatch saw the name it was already gone, so it recorded "absent" as the value to go back to and deleted the key at teardown. On a worker that inherited a real `RESEND_API_KEY`, `SENDGRID_API_KEY`, `UI_PASSWORD`, `LITELLM_SALT_KEY` or `OPENAI_API_KEY`, every test after the first one ran without it. `monkeypatch.delenv(..., raising=False)` removes the key and restores whatever was there, so the try/finally the manual restore needed goes with it. * chore(test): leave the two cost-calc files to the PR that rewrites them fully Both files are also in #37815, which converts the module-global writes as well as the env writes and folds them into one fixture. Two PRs rewriting the same lines differently is a conflict nobody benefits from resolving, so this one drops back to staging on those two and keeps the other 39. TQ004 clears 200 here instead of 275; the rest moves with #37815. |
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ryan-crabbe-berri
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b76def0e5d
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test: require a match= on broad pytest.raises, and drop duplicate parametrize cases (#37769)
`pytest.raises(Exception)` with no `match=` passes on any error that broad. A TypeError from a refactor, a botched fixture, an import that moved: all of them read as the rejection the test claims to police, so the test goes green for the wrong reason and stays green after the behaviour it guards is gone. PT011 closes that gap for the 317 sites B017 could not reach, because B017 only fires on a single-statement body with no `as e` binding. Each pattern here is the message the code actually raised, recorded by running the sites under a plugin that logged the concrete type and text per call site, so the assertions describe observed behaviour rather than a guess. Where a site raises more than one message across its parametrize cases, the pattern is an alternation of what was seen; where the exception carries an empty `str()` and puts the text on `.message`, the site keeps a narrow `noqa` with the reason. PT014 removes four parametrize cases that were listed twice. The duplicate re-runs an assertion that already passed, and it usually marks a case someone meant to vary and forgot to edit. |
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Bisma Nawaz
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909ab23b89 | test: annotate parametrized traffic-type test inputs | ||
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Bisma Nawaz
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d317c5621f | fix: map Gemini ON_DEMAND_FLEX traffic type to flex service tier | ||
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mubashir1osmani
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ef5d05f137
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fix(realtime): stop second Gemini Live setup, retry hung handshake, close guardrail bypass (#31519)
* fix(realtime): stop sending a second Gemini Live setup on follow-up session.update Gemini Live (BidiGenerateContent) accepts setup as the first-and-only client message; a second setup closes the socket with 1007 Request contains an invalid argument. The AI Studio Gemini path forwarded every client session.update after the first as a follow-up setup, and GA clients (pipecat) send several while configuring the session, so the second one tore the session down before the first turn. Callers saw silence after the first response, exponential per-turn latency from reconnect/retry churn, and intermittent 1011 errors. Drop subsequent session.updates instead of resending setup, matching what the Vertex subclass already does. Tools and instructions must ride on the first session.update before any conversation content. Adds regression tests covering the plain follow-up, a follow-up that adds tools (the case the previous identical-only dedup still forwarded), and the guardrail create_response=False warning path. * fix(realtime): retry the backend open handshake instead of failing with 1011 The upstream Live API open handshake (e.g. Gemini Live) intermittently hangs; waiting longer never recovers a hung attempt, but a fresh attempt almost always connects in ~1s. The proxy opened the backend websocket once with the default open_timeout and no retry, so a single slow handshake surfaced to the caller as a fatal 1011 internal error and dropped the call. Bound each open attempt with a short open_timeout and retry; a bounded attempt that already timed out spaces out the next try, so no backoff is needed. Deterministic handshake-status rejections (auth/4xx) are not retried, and the retry only ever wraps the open, never a live session. Adds tests for retry-then-succeed, raise-after-max-attempts, and no-retry-on-auth-failure. * fix(realtime): close guardrail bypass + surface handshake status; drop obsolete tests Three review fixes on the Gemini Live realtime path. Transcription-guardrail bypass: Gemini Live rejects a second setup (1007), so once the initial setup is sent the guardrail's automaticActivityDetection.disabled=true can no longer be delivered as a follow-up session.update. With that follow-up now dropped, the model's auto-response stayed enabled and a realtime_input_transcription guardrail was bypassed (the model answered before the proxy could gate the turn). Fold the disable into the one-and-only setup instead: the handler injects it into the auto-sent setup (gemini_live_defer_setup false) and _send_to_backend injects it into the deferred first setup. OpenAI sessions accept follow-up updates and are left untouched. Backend handshake status: the open-retry treated only InvalidStatusCode as deterministic; websockets>=15 raises InvalidStatus for a rejected client handshake, so a 401/403 fell into the broad WebSocketException branch and was retried before the caller closed the client with 1011 instead of the upstream status. Treat both as non-retryable. Obsolete tests: the four tests asserting a follow-up session.update is merged and re-sent as a second setup asserted behavior that crashes Gemini Live with 1007 (verified directly against the API). Removed; the drop is covered by new regression tests. * style(realtime): reformat changed files to ruff line-length 120 Post-merge with litellm_internal_staging, which unified ruff format width to 120 (#31518). The realtime change set was formatted at 88, so the changed lines tripped the whole-file ruff format check. Reformat with ruff 0.15.3 at the repo's 120 width; no logic changes. |
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Sameer Kankute
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4476923ac4
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test: add realtime proxy e2e suite across providers (#30960)
* tests: add e2e tests for spend, budgets and llms * style: make chained comparison of status_code clearer Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com> * remove e2e_tests folder * test: add spend tracking tests * test: multi-window budgets coverage * fix: p0 issues, added types and shared functions for each test suite * chore: add config.yml * test: passthrough endpoints stream/non-stream e2e * style: carry clearer status_code comparison into renamed e2e dir * fix: rename cost breakdown function * fix: pydantic validation for budget info, dont allow explicit type cast * refactor: migrate to gateway client * test: add custom pricing tests * chore: change master key * test(e2e): address greptile review feedback Remove the duplicate cache/cache_params block in the gateway config so the two can't silently diverge under future edits. Reorder the soft-budget test to assert the call isn't a budget block before require_successful_call, since that helper hard-fails any non-2xx and left the budget-block check unreachable; the misleading "skip" comment is corrected. Add a deferred delete in test_budget_delete_removes_it so a failed delete doesn't leak a budget on the shared proxy. Scope the spend_tracking sys.path insertion in pytest_sessionfinish to just the cleanup import so a broader "pytest tests/" run isn't left with a mutated path. * test(e2e): drop misleading skip comment on require_successful_call require_successful_call fails hard, it does not skip; the trailing comment was factually wrong. The function name already states intent, so the comment is removed in both per-model and tag budget helpers. * test(e2e): assert budget-isolation invariant before success check On the should-still-succeed path of the per-model and tag isolation tests, check is_budget_block before require_successful_call. If the isolation bug fires the unaffected model/tag is blocked, so asserting the specific 'blocked by X' invariant first yields the diagnostic message instead of a generic upstream-failure. Matches the ordering in test_soft_budget_e2e.py. * fix(e2e): guard spend-log truncate on skip and stop returning unrelated priced rows * fix(e2e): run case init() inside try so partial-init failures tear down run_case called case.init() outside the try/finally that runs teardown(), so a case that registers cleanups progressively (create team, then user, then key) and then fails partway through init() would leak the already-created entities on the long-lived shared proxy. Move init() inside the try so teardown always runs. Add a regression test that registers a cleanup then raises mid-init and asserts the resource is still released. * test(e2e): mark known pricing-leak isolation test xfail(strict) test_custom_pricing_is_isolated_from_sibling_deployment documents a real proxy gap (a deployment's custom per-token pricing leaks into the shared cost map for sibling deployments of the same underlying model) and was left unconditionally failing, which pollutes the suite's pass/fail signal. Mark it xfail(strict=True) so the suite stays green while the leak persists and turns into a failure the moment isolation is fixed, prompting the marker's removal. * refactor(e2e): make suite pass its shipped strict basedpyright config The suite ships tests/pyrightconfig.json (strict, no Any), but basedpyright --project tests reported four errors in it: three reportAny on the parametrize ids=lambda c: c.__name__, and one reportUnusedFunction on the underscore-prefixed autouse fixture _require_live_proxy. Replace the untyped lambda with a typed _case_id(case_cls: Type[_BudgetCase]) -> str so the ids are no longer Any, and rename the fixture to require_live_proxy so basedpyright no longer treats it as an unused private function (it is referenced only by pytest's autouse machinery). basedpyright --project tests now reports zero errors. * fix(tests/e2e): gate spend-log truncate on e2e marker, not test directory * test(e2e): run harness unit tests without a live proxy The autouse session fixture skipped the whole tests/e2e session when no proxy answered, which also skipped test_lifecycle.py, a pure unit test of run_case that never touches the proxy. A regression test that silently skips gives no signal, so the skip now lives in pytest_runtest_setup gated on the same e2e marker the spend-log truncate guard already uses: live tests skip when no proxy is up while harness unit coverage always runs. The liveness probe is cached with lru_cache so it still runs once per session * test(e2e): clean up gateway config comment debris Fix the typo on the header comment and drop the orphaned namespace/ttl comment remnants left indented under cache_params; the active values are already set above. Flagged by greptile review. * fix: add new tests, split gateway * test(e2e): type the redis spend-counter probe for strict basedpyright The new cold-counter reseed test drove its redis client untyped, so the strict tests/pyrightconfig.json (reportUnknown*, reportAny) flagged ten errors once the file landed: scan_iter/get came back unknown and the pool.map lambda had an untyped parameter. Annotate the client as redis.Redis[str] via a TYPE_CHECKING import (the runtime import stays lazy so the suite still skips, not errors, when redis is absent), which resolves scan_iter to Iterator[str] and get to str | None, and replace the lambda with a typed inner function mirroring _burst. basedpyright --project tests is back to zero errors. * test(e2e): xfail the known team multi-window failure and isolate member teardown Greptile flagged two issues in the mirrored split-gateway commit. The team multi-window budget test documents a real /team/new write bug (budget_limits go straight to the Json? column and Prisma 500s, unlike the json.dumps'd key and /team/update paths) and was left as an unconditional hard failure, which would turn any live-proxy CI run red; mark it xfail(strict=True) like the custom-pricing isolation test so the suite stays green while the bug persists and flips to a failure the moment the write is fixed and the marker should go. The class-scoped member fixture in test_team_member_budget_e2e.py tore down its key, user, and team sequentially with no exception isolation, so a failed delete_key would strand the user and team on the long-lived shared proxy. Route cleanup through a ResourceManager: register each delete progressively and run them LIFO best-effort in a finally, so a partial-setup failure still releases what came before and one failed delete never blocks the rest. * test: add realtime proxy e2e suite across providers Add tests/realtime_e2e covering the proxy realtime websocket endpoint end to end against live providers (openai, azure, gemini, vertex_ai, bedrock, xai). Two layers: a raw-websocket suite asserting the normalized OpenAI GA event sequence, delta/transcript consistency, usage, and a full tool-call round-trip; and a pipecat smoke driving the proxy through the GA OpenAIRealtimeLLMService. Tests carry a new realtime_e2e marker and skip cleanly when the proxy or provider creds are absent, so they stay out of the default unit run. * test: move realtime e2e suite into tests/e2e harness Replace the standalone tests/realtime_e2e with a tests/e2e/realtime suite that follows the existing e2e conventions: a session-scoped client fixture, a frozen-dataclass RealtimeClient wrapping the shared Gateway, pydantic models for every sent and received event, and the e2e marker with the parent harness's liveness skip. The suite opens the proxy realtime websocket (websockets.sync to stay synchronous like the rest of the harness) and asserts the normalized OpenAI GA event sequence for a text conversation plus a full tool-call round-trip, parametrized across providers. A provider whose realtime alias is not configured on the proxy skips via /model/info. Adds a gemini realtime model to the gateway config and fixes the openai realtime model id. * test: add pipecat realism layer to realtime e2e suite Add test_realtime_pipecat_e2e driving the same providers through pipecat's GA OpenAIRealtimeLLMService with base_url pointed at the proxy, as a coarse realism check on top of the raw-websocket suite. Each test stays synchronous and runs the async pipecat pipeline via asyncio.run, and the module skips unless pipecat-ai is installed. Lift the shared provider matrix, ws-url helper, and skip helper into realtime_client so both suites use them. * fix(e2e): parse GA realtime transcript events in e2e client The realtime e2e client speaks the GA protocol, but transcript() only aggregated beta delta event names. Handle GA deltas, fall back to response.done output, and accept nested usage details on response.done. Co-authored-by: Cursor <cursoragent@cursor.com> * fix(e2e): address realtime code-review findings - Use the real openai/gpt-4o-realtime-preview model ID in the gateway config (gpt-realtime-2 does not exist and would fail every live test) - Pass a bare base_url to pipecat's OpenAIRealtimeLLMService so pipecat can append ?model= itself; the previous realtime_ws_url already contained ?model= causing a malformed duplicated query parameter - Wrap connection.recv() in a try/except TimeoutError in collect_until so a deadline expiry inside recv preserves the collected-events diagnostic instead of raising a bare, message-free exception Co-authored-by: Cursor <cursoragent@cursor.com> * fix(e2e): filter configured_models to mode:realtime entries only ModelInfoEntry.model_info used CustomPricing (extra="ignore") so the mode field from /model/info was silently dropped, making it impossible to distinguish realtime from non-realtime deployments. Add an optional mode field to CustomPricing and filter configured_models() to entries whose model_info.mode == "realtime" so skip_if_unconfigured never accidentally skips a realtime test due to a naming-pattern collision with a non-realtime deployment. Co-authored-by: Cursor <cursoragent@cursor.com> * Update litellm-config.yml * fix(e2e): use TypeVar instead of PEP 695 generic in realtime parse_last PEP 695 type-parameter syntax (def f[T: Bound](...)) is only parseable on Python 3.12+, but the project declares requires-python >=3.10. Importing the realtime e2e client on 3.10/3.11 raised a SyntaxError before any test could run. Switch parse_last to the backport-safe TypeVar idiom so the suite imports across the full supported range. * fix(e2e/realtime): use GA openai/gpt-realtime model id The realtime gateway config used openai/gpt-realtime-2, which is not a real OpenAI model id and would 404 once live OpenAI realtime credentials are wired in. The GA speech-to-speech model is openai/gpt-realtime (snapshot gpt-realtime-2025-08-28); switch the openai-realtime alias to it. * fix(realtime): harden Gemini/Vertex Live for audio-native e2e Coerce TEXT responseModalities to AUDIO on native-audio and flash-live models, suppress the orphan turnComplete response.done that arrives immediately after tool results, omit function_response.id on Vertex, stop appending client query params to Gemini/Vertex WSS URLs, and add regression tests for these paths. Co-authored-by: Cursor <cursoragent@cursor.com> * Add xai full compatibility * Add working vertex ai realtime tests * Add audio + server vad e2e tests * Add config for e2e testing models * Add fix xai server vad * fix: use correct OpenAI realtime model ID in e2e gateway config openai/gpt-realtime is not a valid model; replace with the correct openai/gpt-4o-realtime-preview model ID to prevent model-not-found errors when running the openai-realtime e2e tests. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * revert: restore openai/gpt-realtime model ID gpt-realtime is a valid model; reverting the unnecessary change. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * fix: resolve UP006 violations, mock test failures, and stale spec field - Guard gemini setup-without-tools deferral with litellm.gemini_live_defer_setup flag so the default (False) path sends setup immediately, fixing two failing mock tests: test_client_ack_caches_setup_to_prevent_duplicate_session_update_setup and test_deferred_setup_sends_session_update_before_buffered_audio - Replace deprecated typing generics (Dict, List, Tuple, Optional) with builtin equivalents in xai/realtime/transformation.py, gemini/realtime/transformation.py, and realtime_streaming.py to satisfy the UP006 ruff-strict ceiling - Remove 'role' from OpenAPI compliance test expected fields; Google removed it from the Interaction schema in their live spec Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * fix: use Optional[dict] in xai normalizer to preserve Black line-split dict[str, Any] | None is shorter than Optional[Dict[str, Any]] by enough that Black collapses the _normalize_usage signature to a single line (86 chars), conflicting with the existing multiline format. Using Optional[dict[str, Any]] keeps the line at 90 chars (> 88 limit) so Black preserves the multiline shape, while still satisfying UP006 by replacing Dict with dict. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * fix: remove proxy-level setup-tools deferral, delegate to transformer The _gemini_setup_deferred / _gemini_pre_setup_buffer block in _send_to_backend was double-deferring: GeminiRealtimeConfig already handles the session.update-to-setup mapping internally and always returns a ready-to-send setup on the first session.update call (session_configuration_request=None). The proxy layer was incorrectly holding back that setup waiting for tools that the transformer had already incorporated. Removing the block fixes two failing tests: test_client_ack_caches_setup_to_prevent_duplicate_session_update_setup test_deferred_setup_sends_session_update_before_buffered_audio Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * refactor: abstract Gemini protocol keys out of core and use cost map for live model detection Move Gemini-specific message key knowledge (setup, realtimeInput, clientContent, toolResponse) out of the core RealTimeStreaming module into provider-level methods. BaseRealtimeConfig gains is_setup_message and is_content_message (both default False); GeminiRealtimeConfig overrides them with the actual Gemini key checks. Add gemini_native_audio and gemini_audio_only_live capability flags to the 10 affected model entries in the cost map. _is_audio_only_live_model and _is_native_audio_model now read from the cost map first and fall back to the existing string markers for models not in the map. * fix: apply black formatting and register gemini capability fields in schema * refactor: drop string-marker fallback; resolve audio-only live models via cost map only * fix: use registered cost-map model name in vertex realtime tests * fix: patch cost map in tests so they don't depend on remote main branch state * fix: align gateway config vertex-realtime model ID with cost-map registered name * fix: patch gemini-2.5-flash-native-audio in cost map fixture for CI * fix(e2e): use correct OpenAI realtime model id in gateway config Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * fix(e2e): add budget rescheduler short intervals to gateway config Without proxy_budget_rescheduler_min/max_time set, the rescheduler defaults to ~600s, causing all budget-reset e2e tests to timeout before the reset fires. Set to 5–10s so tests complete within 90s. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * chore(e2e): strip non-realtime files from PR scope Restore budget, spend-tracking, and custom-pricing test files to their litellm_internal_staging state. Keep the mode field addition to CustomPricing in models.py (needed by realtime configured_models filter). Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * fix(tests): restore async_realtime regression test and add missing fixture - Restore the end-to-end async_realtime regression test for Vertex query-param forwarding; the previous unit-only version did not exercise the code path where the original bug lived - Add patch_gemini_audio_cost_map_entries fixture to test_gemini_audio_only_live_models_drop_text_from_text_audio_combo so it does not depend on the cost map having gemini_audio_only_live set in CI Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * fix(lint): resolve ANN401 violations in realtime streaming code Define RealtimeEventNormalizer Protocol and replace bare Any annotations with typed alternatives (object for event/value params, the Protocol for the normalizer) to stay within the strict-rule budget. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * style: black format realtime_streaming.py * fix(tests): add gemini_native_audio and gemini_audio_only_live to model prices schema * fix(lint): fix I001 import sort order in realtime_streaming.py * fix(lint): restore import litellm to correct position before from-litellm imports * undo budget removal * test(e2e): pin explicit credentials for gemini and vertex realtime models * test(e2e): share keepalive-safe LiteLLMRealtimeLLMService across pipecat suites The pipecat smoke test drove the proxy through the stock OpenAIRealtimeLLMService, which sends websocket keepalive pings at its default interval. The proxy does not answer them, so the connection is closed with a 1011 before the run completes. Move the proxy-aware LiteLLMRealtimeLLMService (keepalive disabled) into a shared pipecat_service module and use it from both the smoke and audio suites. * test(e2e): document that LiteLLMRealtimeLLMService._connect keeps the ?model= param The proxy routes realtime websockets on the ?model= query param, and pipecat's OpenAIRealtimeLLMService.__init__ bakes it into self.base_url before _connect runs. Passing self.base_url through preserves it; spell that out so the override is not misread as dropping the param. * fix(realtime): set _content_sent_after_setup only after the backend send succeeds A failed content send used to flip _content_sent_after_setup to True before the send was confirmed, mirroring the correct-on-failure ordering the adjacent session-config cache already follows. If the send raised, the flag stayed True and a later session.update that produced a setup frame was silently dropped even though the backend never received any content. Set the flag after the send succeeds and add a regression test that fails if the ordering is reverted. * fix: normalize realtime passthrough events * refactor(realtime): declare patch_outgoing_session on normalizer Protocol; fix wav chunk return type The RealtimeEventNormalizer Protocol only declared should_drop and normalize, so the outgoing session.update patch went through a getattr(..., None) lookup even though should_drop/normalize are called directly. The sole implementer (XAIRealtimeNormalizer) already provides patch_outgoing_session, so declare it on the Protocol and call it directly for consistent, fully-typed dispatch. Also correct _load_wav_chunks' return annotation from list[bytes] to tuple[list[bytes], int]; it returns (chunks, sample_rate) and the caller unpacks both. --------- Co-authored-by: mubashir1osmani <mubashir.osmani777@gmail.com> Co-authored-by: Mateo Wang <277851410+mateo-berri@users.noreply.github.com> Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com> Co-authored-by: Cursor Agent <cursoragent@cursor.com> Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com> |
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|
Sameer Kankute
|
87cf67ec30
|
feat(gemini): forward web search tools in image generation (#30119)
* feat(gemini): forward web search tools in image generation Map tools and web_search_options to googleSearch on Gemini image generateContent requests for Google AI Studio and Vertex AI. Co-authored-by: Cursor <cursoragent@cursor.com> * fix(gemini): dedupe image search tools and return mapped params Skip web_search_options when tools already include search, dedupe search tool entries, and assign the return value from map_gemini_image_tools_params. Co-authored-by: Cursor <cursoragent@cursor.com> * fix(gemini): preserve toolConfig side-effects in image tool mapping * fix(gemini): forward toolConfig in image generation request body * fix(gemini): track web search grounding cost on image generation Forwarding Google Search grounding to Gemini and Vertex image generation previously incurred billable grounding charges that never reached LiteLLM spend tracking, because the image cost path returns through the Gemini/Vertex image calculators before built-in tool spend is added. Carry the grounding request count from the response onto the image usage object and bill it with the same per-request web search accounting used for chat completions. --------- Co-authored-by: Cursor <cursoragent@cursor.com> Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com> |
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|
Sameer Kankute
|
c30297e98a
|
fix(gemini-live): forward audio buffer commit and correct Vertex PCM rate (#29946)
* fix(gemini-live): forward audio buffer commit and correct Vertex PCM rate Map input_audio_buffer.commit/end to Gemini audioStreamEnd (or activityEnd for manual VAD) so burst user audio triggers server_vad after response.done. Use 24kHz PCM MIME for Vertex native-audio sessions. Co-authored-by: Cursor <cursoragent@cursor.com> * fix(gemini-live): honor input_audio_buffer.clear during deferred setup replay Apply clear semantics when buffering and flushing pre-setup audio frames so cleared appends are not forwarded to Gemini Live after setup completes. Co-authored-by: Cursor <cursoragent@cursor.com> * style: black-format realtime_streaming.py for py312 CI Co-authored-by: Cursor <cursoragent@cursor.com> * Fix realtime working with gaurdrails * fix(realtime): remove unused GuardrailEventHooks import Co-authored-by: Cursor <cursoragent@cursor.com> --------- Co-authored-by: Cursor <cursoragent@cursor.com> |
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Sameer Kankute
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32c88ca74f
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Litellm oss staging 080626 (#29932)
* feat(bedrock_mantle): add SigV4/IAM auth to Responses API route (fixes #29665) (#29788) * feat(responses): add default no-op sign_request to BaseResponsesAPIConfig * feat(responses): call sign_request after body is final, send signed bytes when signed * feat(bedrock_mantle): add SigV4 sign_request via composed BaseAWSLLM (bearer path) * test(bedrock_mantle): cover SigV4 access-key, AssumeRole, body bytes, region/auth consistency * feat(bedrock_mantle): defer auth to sign_request; validate_environment no longer requires bearer * docs(bedrock_mantle): document SigV4 + Bearer auth on Responses route * test(responses): cover fake-stream signing order and mantle bearer arg/env precedence * fix(bedrock_mantle): wrap all botocore credential errors with both-paths guidance * fix(bedrock_mantle): catch specific credential errors, not all BotoCoreError, so STS transport failures are not masked * fix(bedrock_mantle): sign the compact Responses route too, not just create * fix(github-copilot): route per-model on /v1/responses based on model info (#29747) * feat(focus): add GCS destination for FOCUS export (#29751) * test: add failing tests for FocusGCSDestination * feat: add FocusGCSDestination reusing GCSBucketBase auth * feat: register FocusGCSDestination in factory; export from __init__ * fix(focus): preserve GCS_PATH_SERVICE_ACCOUNT when service_account_json not in config * style: apply Black formatting to gcs_destination and tests * style: apply Black formatting to factory.py * fix(bedrock): omit empty additionalModelRequestFields and system from Converse API payload (#29565) Amazon Nova Pro (and other strict Bedrock models) return 400 Malformed input request when additionalModelRequestFields: {} or system: [] are present in the payload. Both fields are optional in CommonRequestObject (total=False) and must be omitted rather than sent as empty structures. Co-authored-by: shin-berri <shin-laptop@berri.ai> Co-authored-by: yuneng-jiang <yuneng@berri.ai> Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com> * fix(proxy): recognize *.cognitiveservices.azure.com as OpenAI-compatible in pass-through cost tracking (#29730) * fix(proxy): recognize *.cognitiveservices.azure.com as OpenAI-compatible Azure OpenAI resources created via the newer "Azure AI Foundry" / Cognitive Services pathway live on `*.cognitiveservices.azure.com` subdomains, not the older `openai.azure.com`. Both are valid Azure OpenAI surfaces in production today. The OpenAI pass-through cost-tracking handler hard-codes only the older hostname in five places (four `is_openai_*_route` methods on OpenAIPassthroughLoggingHandler, plus is_openai_route on PassThroughEndpointLogging). As a result, calls from newer Azure deployments are silently classified as "not an OpenAI route", the dispatch into the cost-tracking handler is skipped, and tokens/cost never get extracted into LiteLLM_SpendLogs — the row gets written with prompt_tokens=0, completion_tokens=0, spend=0, model='unknown'. Reproduced 2026-06-04 against a real Azure OpenAI deployment on `*.cognitiveservices.azure.com` proxied through LiteLLM v1.88.0. Fix: factor the hostname check into a single helper `_is_openai_compatible_host` listing all three recognized surfaces (api.openai.com, openai.azure.com, cognitiveservices.azure.com), and have all five call sites delegate to it. Purely additive — never weakens recognition for the originally-supported hostnames. Adds a test `test_is_openai_route_recognizes_cognitiveservices_azure_com` that exercises all four `is_openai_*_route` static methods against `*.cognitiveservices.azure.com` URLs (positive cases per route + a small cross-route negative to confirm route-specific path matching still works on the new hostname). Out of scope for this PR (separate followup): - `openai_passthrough_handler` calls chat/completions `transform_response` on Responses API payloads (`output:` not `choices:`), which throws inside the dispatch and drops the SpendLogs row entirely. Recognized + tracked separately. * ci: trigger fresh run Empty commit to re-run checks. The previous auth-and-jwt failure was a transient HuggingFace Hub 429 rate-limit hitting tokenizer downloads in tests/proxy_unit_tests/test_custom_tokenizer_bug.py — unrelated to this PR's scope (hostname recognition in pass-through cost tracking). No code change. --------- Co-authored-by: shin-berri <shin-laptop@berri.ai> Co-authored-by: yuneng-jiang <yuneng@berri.ai> * fix(responses): preserve forced-function tool_choice name in Responses to Chat transform (#29812) The Responses API forces a specific function with a top-level name ({"type": "function", "name": "X"}), but _transform_tool_choice only handled the nested Chat Completions shape and fell through to returning "required" for the flat form, silently dropping the function name and degrading a forced function call to force-any-tool. Map the flat Responses shape to the nested Chat shape, keeping the "required" fallback when no name is present. * Preserve x-anthropic-billing-header system blocks for first-party Anthropic (#29584) * Preserve x-anthropic-billing-header system blocks for first-party Anthropic PR #20951 strips system blocks beginning with "x-anthropic-billing-header:" for every Anthropic target. That block is how the first-party Anthropic API recognizes Claude Code subscription (OAuth) traffic, so dropping it makes requests that carry only that block, such as the auto-mode tool-safety classifier, fail with a misleading 429 rate_limit_error; normal turns still work because they also carry the "You are Claude Code" identity block. Gate the strip behind should_strip_billing_metadata(), defaulting to False on the first-party AnthropicConfig and AnthropicMessagesConfig so the block is kept, and overridden to True on the providers that reach these transforms and reject the block (Bedrock platform, Vertex, Azure for the chat path; Minimax, Azure, DeepSeek for the messages path). Behavior for those providers is unchanged. * Strip billing header on Bedrock invoke and Vertex messages pass-through Two more subclasses reach the gated strip but inherited keep-by-default. AmazonAnthropicClaudeConfig (Bedrock invoke) calls AnthropicConfig.transform_request, which calls translate_system_message, and VertexAIPartnerModelsAnthropicMessagesConfig (Vertex messages pass-through) calls super().transform_anthropic_messages_request. Override should_strip_billing_metadata() to True on both. Add a parametrized test asserting the flag for every first-party base (False) and provider subclass (True), covering all overrides, plus a translate_system_message regression test for the Bedrock invoke path. * fix(cache): log hashed cache keys (#29890) * fix(ui): save routing groups as list (#29889) * Revert "fix(ui): save routing groups as list (#29889)" (#29928) This reverts commit |
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Sameer Kankute
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cb041966bf
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Litellm oss staging 040626 (#29671)
* fix(azure): apply api_version fallback chain to image edit URL
`AzureImageEditConfig.get_complete_url` only read `api_version` from
`litellm_params`. When callers configured it via `litellm.api_version`
or `AZURE_API_VERSION`, the constructed URL had no `?api-version=` and
Azure responded `404 Resource not found`.
Apply the same fallback chain the Azure chat path already uses in
`common_utils.py`:
litellm_params > litellm.api_version > AZURE_API_VERSION env >
litellm.AZURE_DEFAULT_API_VERSION
Adds 5 unit tests pinning each layer of the chain plus a regression
guard for `api_base` that already carries `?api-version=`.
* feat(mcp): core sampling and elicitation flow with security hardening
- Add sampling_handler.py: full MCP sampling/createMessage flow with
model selection (hint-based + priority-based), auth enforcement,
budget checks, route restriction gates, and tag policy pre-auth
- Add elicitation_handler.py: MCP elicitation/create relay with
downstream client capability detection
- Wire sampling/elicitation callbacks in mcp_server_manager.py
gated behind allow_sampling/allow_elicitation config flags
- Add allow_sampling/allow_elicitation fields to MCPServer type
- Fix session lock deadlock: skip lock for JSON-RPC response POSTs
(elicitation/sampling replies) with truncated-body heuristic
- Extend client.py with sampling_callback and elicitation_callback
- Security: RouteChecks gate, tag-budget bypass fix, x-forwarded-for
spoofing fix, Latin-1 header encoding guard
- Add 4 new test modules (model access, priority selection, request
builder, tool conversion) + update existing MCP tests
* fix(security): run pre-call guardrails before MCP sampling acompletion
Without this, an upstream MCP server with allow_sampling enabled could
send prompts that bypass every guardrail (content filtering, PII
redaction, prompt-injection detection) configured on /chat/completions.
- Call proxy_logging_obj.pre_call_hook(call_type='acompletion') before
llm_router.acompletion so guardrails fire for sampling sub-calls
- Add HTTPException to the re-raise list so guardrail rejections
propagate correctly instead of being swallowed as generic errors
* feat(bedrock_mantle): add Responses API support (/openai/v1/responses) (#29490)
* feat(bedrock_mantle): add Responses API transformation config
* test(bedrock_mantle): cover trailing-slash api_base normalization
* feat(bedrock_mantle): export BedrockMantleResponsesAPIConfig
* feat(bedrock_mantle): register gpt-5.x Responses config (gpt-oss unchanged)
* feat(bedrock_mantle): add gpt-5.5/gpt-5.4 Responses price-map entries
* refactor(bedrock_mantle): exclude gpt-oss instead of allow-listing gpt-5 for Responses routing
Frontier OpenAI models on Bedrock Mantle are Responses-only on /openai/v1/responses;
gpt-oss is the legacy family that also speaks chat-completions. Gate by excluding
gpt-oss (which keeps its chat-completions emulation) and defaulting everything else
to the native Responses config, so future frontier models (gpt-6, etc.) route
correctly without a code change. Verified against the live us-east-2 Mantle endpoint:
gpt-oss 400s on /openai/v1/responses while gpt-5.5 400s on both standard paths.
* test(bedrock_mantle): cover supports_native_websocket opt-out
Closes the one uncovered line flagged by codecov on the Responses config.
The assertion documents that Mantle Responses has no realtime/websocket
transport, so realtime routing must not attempt a socket it cannot serve.
* fix(bedrock_mantle): route file_search through emulation instead of forwarding to Mantle
BedrockMantleResponsesAPIConfig inherited supports_native_file_search()
-> True from OpenAIResponsesAPIConfig but never overrode it. Mantle has no
OpenAI vector stores, so a forwarded file_search tool is rejected with a
400 (verified upstream: Tool type 'file_search' is not supported). Opting
out, like the existing supports_native_websocket override, routes the tool
through LiteLLM's file_search emulation instead.
* fix(bedrock_mantle): only route openai.gpt frontier models to Responses
The previous gate excluded gpt-oss and routed every other model to the
native Responses config. But on Mantle only the OpenAI gpt frontier models
(gpt-5.x) are served on /openai/v1/responses; gpt-oss and the non-OpenAI
families (nvidia, mistral, google, zai, ...) are chat-completions only and
400 on that path. Allow-list the openai.gpt- family (excluding gpt-oss)
instead, so chat-only models fall through to the chat-completions emulation.
Verified against the live us-east-2 endpoint: nvidia.nemotron-nano-9b-v2
returns 400 on /openai/v1/responses and 200 on /v1/chat/completions.
* feat(custom_llm): allow streaming/astreaming to yield ModelResponseStream (#27580)
* fix(custom_llm): allow streaming/astreaming to yield ModelResponseStream directly
* fix(streaming): enhance ModelResponseStream handling for custom LLM providers
* fix(streaming): strip finish_reason from content chunks and ensure tool_calls are preserved
* fix(streaming): add type ignore for finish_reason assignment in CustomStreamWrapper
* fix(proxy): strip stack trace from HTTP 503 responses (CWE-209) (#28330)
* fix(proxy/cwe-209): strip Python traceback from HTTP 503 error responses
The /cache/ping endpoint included a full Python traceback in its 503 error
response body (inside the ProxyException message), leaking internal file
paths, line numbers, and call stacks to any caller. Two MCP route handlers
in proxy_server.py similarly interpolated str(e) into "Internal server
error" detail strings.
Fix: log the traceback server-side via verbose_proxy_logger.exception()
and omit it from the ProxyException payload / HTTPException detail returned
to clients. Tests updated to assert no "traceback" keyword or frame paths
appear in the 503 body, with a new dedicated regression test.
CWE-209: Generation of Error Message Containing Sensitive Information.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
* fix(proxy/cwe-209): apply Greptile P2 fixes and add MCP exception-path tests
Greptile 4/5 review identified two remaining gaps and Codecov reported
0% coverage on the two MCP handler exception branches:
1. caching_routes.py — str(e) in "Service Unhealthy ({str(e)})" could
still leak Redis hostnames/IPs; replaced with static "Service Unhealthy".
HTTPException is now re-raised before the generic handler so the
"cache not initialized" 503 still reaches callers with its detail.
Removed the redundant str(e) arg from verbose_proxy_logger.exception()
(exception() already appends the traceback automatically).
2. tests — two new unit tests cover the exception paths in
dynamic_mcp_route and toolset_mcp_route that were previously at 0%:
- test_dynamic_mcp_route_unexpected_exception_returns_500_without_traceback
- test_toolset_mcp_route_unexpected_exception_returns_500_without_traceback
All 25 tests pass (9 caching + 16 MCP).
CWE-209: Generation of Error Message Containing Sensitive Information.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
* test(caching_routes): restore precise assertion in test_cache_ping_no_cache_initialized
The assertion was weakened to `"Cache not initialized" in str(data)`, which
matches the raw string of the entire response dict and would pass even if the
error moved to an unexpected field or changed structure.
Restore a targeted check on the parsed response: assert the exact string in
the correct field `data["detail"]`, matching FastAPI's HTTPException
serialisation format {"detail": "<message>"}.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
* test(caching_routes): restore precise assertion and add CWE-209 no-cache path test
The assertion in test_cache_ping_no_cache_initialized was weakened to
`"Cache not initialized" in str(data)`, which matched against the raw string
representation of the entire response dict. This would pass silently even if
the error message moved to an unexpected field or the structure changed.
Restore a targeted assertion on the parsed field:
assert data["detail"] == "Cache not initialized. litellm.cache is None"
matching FastAPI's HTTPException serialisation format exactly.
Add test_cache_ping_no_cache_does_not_expose_internals to show the code path
is still working correctly after the CWE-209 fix: verifies that the HTTPException
is re-raised as-is (no traceback, no source paths), and asserts the complete
response structure is exactly {"detail": "Cache not initialized. litellm.cache is None"}.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
* fix(caching_routes): restore ProxyException envelope for null-cache 503
The except HTTPException: raise guard (added in the CWE-209 fix) caused
the null-cache HTTPException to escape as FastAPI's {"detail": "..."} shape
instead of the {"error": {...}} ProxyException envelope that callers expect.
Move the null-cache guard before the try block and raise ProxyException
directly so the response structure is consistent with all other /cache/ping
503s, and the except HTTPException: raise guard is only reachable by
unexpected downstream HTTPExceptions.
Update the two no-cache tests to assert the correct ProxyException envelope.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
---------
Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>
* Update utils.py (#26609)
* feat(pricing): add Snowflake Cortex REST API model pricing (#26612)
* feat(pricing): add Snowflake Cortex REST API model pricing
## Summary
Adds pricing and context window information for 20+ Snowflake Cortex REST API models to `model_prices_and_context_window.json`.
## What's included
- **7 Claude models** (sonnet-4-5, sonnet-4-6, 4-sonnet, 4-opus, haiku-4-5, 3-7-sonnet, 3-5-sonnet) — with prompt caching rates
- **4 OpenAI models** (gpt-4.1, gpt-5, gpt-5-mini, gpt-5-nano) — with prompt caching rates
- **5 Llama models** (3.1-8b, 3.1-70b, 3.1-405b, 3.3-70b, 4-maverick)
- **1 DeepSeek model** (deepseek-r1)
- **1 Mistral model** (mistral-large2)
- **1 Snowflake model** (snowflake-llama-3.3-70b)
- **2 Embedding models** (arctic-embed-l-v2.0, arctic-embed-m-v2.0)
Each entry includes `input_cost_per_token`, `output_cost_per_token`, `cache_read_input_token_cost` (where applicable), `max_input_tokens`, `max_output_tokens`, and capability flags (`supports_function_calling`, `supports_vision`, `supports_prompt_caching`, `supports_reasoning`).
## Pricing source
All prices are in USD per token, sourced from the official [Snowflake Service Consumption Table](https://www.snowflake.com/legal-files/CreditConsumptionTable.pdf) — Tables 6(b) (REST API with Prompt Caching) and 6(c) (REST API).
## Context
The existing `snowflake/` provider has zero model entries in the pricing JSON, which means LiteLLM cannot track costs for Snowflake Cortex calls. This PR fills that gap.
## Related
- Existing provider: `litellm/llms/snowflake/`
- Cortex REST API docs: https://docs.snowflake.com/en/user-guide/snowflake-cortex/cortex-rest-api
* Update model_prices_and_context_window.json
Fix the JSON parsing error
* Update model_prices_and_context_window.json
Removed the duplicate entry
* fix(utils): copy extra_body before adding unknown params to prevent model config mutation (#29620)
Fixes #29615. In add_provider_specific_params_to_optional_params, the line:
extra_body = passed_params.pop("extra_body", None) or {}
returns the original dict reference when extra_body is non-empty (truthy).
Subsequent writes like extra_body[k] = passed_params[k] then mutate the
shared model config object held by the router, poisoning /model/info and
all subsequent requests for that deployment.
The or {} short-circuit creates a new dict only when extra_body is falsy
(None or {}), which is why the bug does not reproduce with extra_body: {}.
Fix: wrap in dict() so we always work on a fresh shallow copy.
* fix(vertex_ai): Bake tool_choice into Gemini CachedContent body to prevent silent drop (#29097)
* fix(vertex_ai): bake tool_choice into Gemini CachedContent body to prevent silent drop
* address greptile feedback on tool_choice cache test
* adds test that uses ToolConfig(functionCallingConfig=FunctionCallingConfig(mode=ANY)) instead of a dict literal, mirroring what map_tool_choice_values actually produce
* fix(gemini/veo): move image from parameters into instances[0] (#29501)
* fix(gemini/veo): move image from parameters into instances[0]
Veo's predictLongRunning schema puts image (and prompt) on the
instances element; parameters is for aspectRatio/durationSeconds/etc.
The Gemini path was leaving image in params_copy, so it ended up
nested under parameters and the API silently ignored it.
The Vertex path already builds the instance dict explicitly, so this
just aligns the Gemini path with it.
Fixes #29498
* address greptile: unconditional pop + BytesIO test
- Pop `image` from params_copy unconditionally so it never reaches
GeminiVideoGenerationParameters even when None, removing implicit
reliance on Pydantic's extra-field-ignore.
- Add test_transform_video_create_request_image_filelike_goes_to_instance
covering the BytesIO path (_convert_image_to_gemini_format) — round-trips
the base64 to confirm encoding.
- Add test_transform_video_create_request_image_none_is_dropped covering
the new None branch.
* fix(huggingface): handle special token text in embedding usage (#29660)
* fix(guardrails): recompile ToolPermissionGuardrail rules on update_in_memory_litellm_params (#29655)
* fix(guardrails): recompile ToolPermissionGuardrail rules on update_in_memory_litellm_params
ToolPermissionGuardrail builds self.rules and the compiled target/pattern
maps only in __init__. The base update_in_memory_litellm_params re-sets raw
attributes via setattr but never rebuilds those maps, so a guardrail updated
in place (PUT /guardrails, or the immediate in-memory sync) keeps enforcing
the construction-time rules until it is reinitialized (PATCH path, periodic
DB poll, or restart).
Extract the compile step into _load_rules and override
update_in_memory_litellm_params to rebuild from it (dict- and model-safe),
re-normalizing default_action / on_disallowed_action. Mirrors the existing
PresidioGuardrail override of the same method. Adds regression tests.
Fixes #29592.
* fix(guardrails): handle dict params in ToolPermissionGuardrail in-memory update
Delegate to super() only for LitellmParams input (the base setattr loop is
model-only); apply the raw-dict case inline. Fixes the mypy arg-type error
and makes the recompile work when the proxy passes the raw DB dict.
* fix(guardrails): preserve tool-permission rules on a partial in-memory update
A partial update (e.g. a LitellmParams whose rules field is None) ran through
the generic setattr, which set self.rules to None, and the recompile was
skipped, leaving the guardrail with no rules. Snapshot the previous rules and
restore them when the update carries no rules; an explicit empty list still
clears them. Adds a regression test for the rules-absent case.
Addresses the Greptile review note on #29655.
* fix(bedrock): stop base_model label from stripping tools/tool_choice (#29621)
* fix(bedrock): stop base_model label from stripping tools/tool_choice
A Router/proxy Bedrock deployment whose model_info.base_model is a friendly
label (e.g. claude-haiku-4-5) silently lost tools/tool_choice: the outgoing
Converse request was built without toolConfig, so the model behaved as if no
tools were provided. Worked in v1.84.0, regressed in v1.85.0, and with
drop_params=true it failed silently.
Two changes compound into the bug. completion() passed model_info.base_model
as the model argument to get_optional_params, so the real Bedrock model id
never reached supported-param resolution; and get_supported_openai_params
resolved the provider config's params from base_model or model, letting the
label fully replace the real model. For Bedrock the label resolves to no tool
support, so tools/tool_choice were dropped before transformation.
completion() now keeps model as the real deployment model and threads the
resolved base_model (kwarg or model_info) through separately, and
get_supported_openai_params treats base_model as additive: it returns the
union of the params supported by model and by base_model. A hint can only add
capabilities, never strip ones the real model already exposes, which also
preserves the original base_model behavior from #27717 and Azure's base_model
driven model-type detection.
Fixes #29618
* test(main): make base_model param test robust to new parametrize cases
Restore an explicit per-case expected_model_param literal instead of
hardcoding the gemini id, so a future case with a different model can't
produce a misleading assertion failure.
* fix(fireworks_ai): pass response_format json_schema through unchanged (#29606)
FireworksAIConfig.map_openai_params was rewriting the OpenAI strict
`{type: json_schema, json_schema: {name, strict, schema}}` shape into
`{type: json_object, schema: ...}` before sending to Fireworks, dropping
`strict` and `name` and changing the `type`. Per Fireworks' docs json_object
means "force any valid JSON output (no specific schema)", so the schema
constraint was effectively dropped and grammar-guided decoding never ran;
model output silently violated the schema.
The rewrite landed in #7085 (Dec 2024) when Fireworks did not yet accept
native json_schema. Fireworks accepts the OpenAI strict shape natively now,
so the rewrite has become a regression.
Removes the rewrite. Passes response_format through unchanged. Updates the
existing test_map_response_format to assert pass-through. Adds focused
regression tests in tests/test_litellm/ covering preservation of type,
strict, name, and schema body, plus that json_object alone still works.
* fix(types): import Required from typing_extensions in gemini types
* style: reformat sampling_handler.py for py312 black compat
* refactor(mcp-sampling): extract helpers to fix PLR0915 too-many-statements in handle_sampling_create_message
* fix(proxy-server): add explicit ProxyLogging type annotation to proxy_logging_obj to fix mypy inference
* fix(mcp-sampling): suppress mypy assignment error on ImportError fallback for proxy_logging_obj
* fix(test): use .value when comparing LlmProviders enum against string in test_default_api_base
* fix(test): iterate LlmProviders enum in test_default_api_base to avoid str pollution from custom provider registration
litellm.provider_list is a mutable global initialized to list(LlmProviders) but custom_llm_setup() appends plain provider strings to it. When a test_custom_llm.py test runs first in the same xdist worker, provider_list contains a str and calling .value on it raises AttributeError. Iterate the immutable LlmProviders enum instead, which is deterministic and what the check intends.
* fix(mcp): depth-aware JSON-RPC response detection and neutral speed-priority fallback
Replace the flat substring check in the truncated-body routing path with a
top-level-key scan so a JSON-RPC response whose result payload nests a
"method" field is still detected as a response and skips the session lock,
removing a deadlock against the in-flight tool call awaiting it.
Drop the inverse max_output_tokens speed proxy when no model exposes
output_tokens_per_second; context-window size does not track latency, so a
neutral score avoids biasing speedPriority toward the smallest-context model.
* fix(guardrails): make ToolPermission rule reload atomic on invalid regex
_load_rules appended each rule to self.rules before compiling its regex, so an
invalid pattern raised mid-loop after the bad rule was already live but without
a _compiled_rule_targets entry. _matches_regex reads a missing compiled target
as a None pattern and returns True, turning the bad rule into a match-all that
silently applies its decision to every tool. Via update_in_memory_litellm_params
(PUT /guardrails) this corrupted the live guardrail.
Build the parsed rules and compiled maps into locals and swap them in only after
every regex compiles, and restore the previous ruleset if a live update is
rejected, so an invalid regex now fails the update without leaving the guardrail
enforcing a broken policy.
* test(mcp): cover sampling conversion, model resolution, and elicitation relay paths
The MCP sampling and elicitation handlers shipped with partial test
coverage, leaving the response-to-MCP conversion, the model resolution
fallback chain, completion-kwargs assembly, guardrail routing, and the
entire elicitation relay untested. That pulled the PR's diff (patch)
coverage below the codecov threshold even though overall project
coverage rose.
Add focused unit tests for _convert_openai_response_to_mcp_result,
_convert_mcp_tools_to_openai, _convert_mcp_tool_choice_to_openai, image
and audio content conversion, the hint-matching and fallback branches of
_resolve_model_from_preferences, _build_completion_kwargs, the router and
guardrail-rejection paths of _run_guardrails_and_call_llm, the
handle_sampling_create_message success and error-propagation flows, the
marker-hoisting fallback for tool content on unexpected roles, and the
elicitation form/url/generic relay together with its decline paths
---------
Co-authored-by: shin-berri <shin-laptop@berri.ai>
Co-authored-by: yuneng-jiang <yuneng@berri.ai>
Co-authored-by: lengkejun <lengkejun@xd.com>
Co-authored-by: Yug <yugborana000@gmail.com>
Co-authored-by: Kent <72616338+kingdoooo@users.noreply.github.com>
Co-authored-by: tanmay958 <53569547+tanmay958@users.noreply.github.com>
Co-authored-by: DrishnaTrivedi <142084770+DrishnaTrivedi@users.noreply.github.com>
Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>
Co-authored-by: Navnit Shukla <Navnit.shukla25@gmail.com>
Co-authored-by: PRABHU KIRAN VANDRANKI <72809214+VANDRANKI@users.noreply.github.com>
Co-authored-by: Adrian Lopez <109683617+adriangomez24@users.noreply.github.com>
Co-authored-by: hcl <chenglunhu@gmail.com>
Co-authored-by: JooHo Lee <96564470+BWAAEEEK@users.noreply.github.com>
Co-authored-by: Dinesh Girbide <85330597+Dinesh-Girbide@users.noreply.github.com>
Co-authored-by: cloudwiz <22098246+andrey-dubnik@users.noreply.github.com>
Co-authored-by: Ahmad Khan <ahmadkhan2508@gmail.com>
Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
|
||
|
Sameer Kankute
|
ed073d382d
|
fix(gemini-realtime): use GA event names for Pipecat 1.3.x compatibility (#29662)
* fix(gemini-realtime): use GA event names for Pipecat 1.3.x compatibility Pipecat v1.3.0 adopted the OpenAI Realtime API GA event naming: response.audio.delta -> response.output_audio.delta response.text.delta -> response.output_text.delta response.audio.done -> response.output_audio.done response.text.done -> response.output_text.done The proxy was still emitting the old beta names; Pipecat's `parse_server_event` raises "Unimplemented server event type" for any unknown type, which killed the receive task handler and broke audio playback and tool-call delivery. Also: - conversation.item.created -> conversation.item.added (already handled) - client audio is buffered until backend setupComplete in deferred mode - call_id fallback UUID when Gemini returns empty id - status_details / token detail fields added to Pydantic-strict events The _GA_TO_BETA_EVENT_TYPES map in RealTimeStreaming already translates GA names back to beta for clients that opt in with the openai-beta header, so legacy clients are unaffected. Co-authored-by: Cursor <cursoragent@cursor.com> * fix(gemini-realtime): address greptile review comments - emit outputTranscription as response.output_audio_transcript.delta instead of suppressing it; GA_TO_BETA map handles translation for legacy clients - cap pre-setup audio buffer at 200 frames to prevent memory exhaustion; log a warning when the limit is hit and additional frames are dropped - log remaining dropped message count on flush error Co-authored-by: Cursor <cursoragent@cursor.com> * fix(gemini-realtime): address veria review comments - remove unused OpenAIRealtimeConversationItemCreated import - fix guardrail bypass: semantic_vad early-return now preserves create_response when set so a guardrail-injected create_response:false is not silently dropped - add per-connection 10 MB byte cap alongside the 200-frame count cap for the pre-setup audio buffer to prevent memory exhaustion Co-authored-by: Cursor <cursoragent@cursor.com> * fix(gemini-realtime): fix mypy arg-type on _finalize_gemini_live_setup setup parameter typed as BidiGenerateContentSetup to match the TypedDict passed at both call sites; was dict which mypy rejected. Co-authored-by: Cursor <cursoragent@cursor.com> * fix(gemini-realtime): widen _finalize_gemini_live_setup to Dict[str, Any] BidiGenerateContentSetup (TypedDict) is a subtype of Dict[str,Any] so both call sites (one passing a plain dict, one passing the TypedDict) satisfy mypy. Co-authored-by: Cursor <cursoragent@cursor.com> * fix(gemini-realtime): cast BidiGenerateContentSetup to Dict at _finalize call site mypy rejects TypedDict as dict[str, Any] argument; cast at the call site where follow_up_setup is BidiGenerateContentSetup to satisfy the checker. Co-authored-by: Cursor <cursoragent@cursor.com> * Fix Gemini realtime beta compatibility * Fix deferred Gemini setup audio ordering * fix: preserve Gemini audio transcript ids * fix(realtime): cap pre-setup client buffer on all append paths Route every append to the deferred-setup pending buffer through the per-connection message/byte caps. Previously only the audio-buffer fast path enforced the caps; once one frame was buffered, a client that withheld session.update could stream arbitrary frames into _pending_messages_until_setup unbounded and exhaust proxy memory. * style(gemini-realtime): apply black formatting to transformation.py * fix(gemini-realtime): log beta-translation fallback and name native-audio marker Surface the previously swallowed exception in _send_event_to_client so a failed GA->beta translation is observable instead of silently forwarding the untranslated event. Extract the native-audio model substring used by _finalize_gemini_live_setup into a named constant documenting why speechConfig is dropped on those setups. --------- Co-authored-by: Cursor <cursoragent@cursor.com> Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com> |
||
|
Sameer Kankute
|
c7ab9adde5
|
Litellm oss staging 030626 (#29578)
* Fix incorrect agent API request example payload structure (#29556) * fix(otel): add litellm_metadata fallback in _get_span_context and _end_proxy_span_from_kwargs (#29427) * fix(otel): add litellm_metadata fallback in _get_span_context and _end_proxy_span_from_kwargs On /v1/messages and other LITELLM_METADATA_ROUTES, the parent OTel span is stored in litellm_params['litellm_metadata'] instead of litellm_params['metadata']. When the request body contains a native 'metadata' field (e.g. Anthropic's {"user_id": "..."}), litellm_params['metadata'] gets overwritten and the parent span is lost, producing orphan root spans with a different trace_id. Add fallback checks to litellm_metadata in: - _get_span_context(): so child spans find the correct parent - _end_proxy_span_from_kwargs(): so the proxy span gets closed Fixes: https://github.com/BerriAI/litellm/issues/27934 * test(otel): tighten assertions per Greptile review - test_span_context_metadata_takes_priority: assert litellm_metadata span is never accessed, proving metadata takes priority - test_span_context_no_parent_when_neither_has_span: assert both ctx and detected_span are None --------- Co-authored-by: shin-berri <shin-laptop@berri.ai> Co-authored-by: yuneng-jiang <yuneng@berri.ai> Co-authored-by: Aneesh-Fiddler <aneeshfiddler@gmail.com> Co-authored-by: Sameer Kankute <sameer@berri.ai> * fix: remove premature end-user budget check from get_end_user_object (#29420) * fix(proxy): remove premature end-user budget check from get_end_user_object Problem: - `_check_end_user_budget()` was called inside `get_end_user_object()` - This caused budget checks to run BEFORE `skip_budget_checks` could be evaluated - Zero-cost models (e.g., local vLLM) were incorrectly blocked when end-users exceeded their budget, even though they should bypass budget checks Solution: - Remove `_check_end_user_budget()` calls from `get_end_user_object()` - Budget enforcement now happens exclusively in `common_checks()` where `skip_budget_checks` context is available - `get_end_user_object()` keeps `route` as optional in function parameter for backwards compatibility and future implementation. * refactor(tests): update budget enforcement tests to reflect changes in get_end_user_object - test_get_end_user_object() verifies data fetching - test_check_end_user_budget() verifies enforcement - test_budget_enforcement_blocks_over_budget_users() integrates _check_end_user_budget() - test_resolve_end_user_reraises_budget_exceeded() is now test_resolve_end_user since no budget exceeded is thrown in get_end_user_object() * Gemini /images/generate and /images/edits billing fixes + add support for size and aspect ratio params (#29534) * Fix Gemini image config mapping * Address Gemini image config review * Format Gemini image generation transform * Fix Gemini image token usage logging * Share Gemini image request helpers * Fix Gemini Imagen model routing * Fixes as per self code review * Fixes per internal code review * Stop gating Imagen imageSize forwarding * Document Gemini image size mapping source * chore: retrigger lint * Clarify Gemini candidate count precedence * Add Inception provider (#29522) * add inception as provider (chat, fim) * linting * seperate test suite for chat and fim * fix test coverage * fix: model hub custom pricing model info (#29293) * Opik user auth key metadata extractors (#28397) * fix: enhance Opik metadata extraction to include user API key auth context fixed after refactoring to extractor logic * test: add unit tests for OPik metadata extraction logic * fix: enhance extract_opik_metadata function to prioritize metadata sources for improved accuracy * fix(ci): clarified comments and edited unit tests * test: add unit tests for OPik metadata extraction with auth and requester overrides * fix(ui): replace fixed favicon.ico with current api get /get_favicon (#29532) Signed-off-by: José Luis Di Biase <josx@interorganic.com.ar> * fix(vertex/gemini): keep tool_call reference when a text-only assistant message follows (#29561) `_gemini_convert_messages_with_history` tracks `last_message_with_tool_calls` so a following tool result can be matched back to its tool call. The assignment was inside a branch guarded by `assistant_msg.get("tool_calls", []) is not None`, which is also True for a text-only assistant message (an empty list is not None). As a result, an assistant message with no tool calls that appears between a tool call and its tool result overwrote the reference, and conversion failed with: Exception: Missing corresponding tool call for tool response message. This shape is common: a model emits a short narration/assistant message after a tool call before the tool result is appended. Only update `last_message_with_tool_calls` when the assistant message actually carries tool_calls (or a function_call). Adds a regression test. 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> * Add 1-hour cache write pricing for EU/AU/JP Bedrock Anthropic models (#28572) * fix(thinking): handle None thinking param in is_thinking_enabled (#28598) Squash-merged by litellm-agent from Terrajlz's PR. * feat(helm): support tpl rendering in podAnnotations (#28609) Squash-merged by litellm-agent from devauxbr's PR. * Forward custom_llm_provider through the Responses API bridge (Fixes #28505) (#28575) * Forward custom_llm_provider through the Responses API bridge (Fixes #28505) When a Chat Completions request to a GPT-5.4+ model contains both `tools` and `reasoning_effort`, `completion()` auto-routes through `responses_api_bridge`. The bridge handler called `litellm.responses()` / `litellm.aresponses()` without forwarding the already-resolved `custom_llm_provider`, so the downstream call re-invoked `get_llm_provider()` with `custom_llm_provider=None` and stripped a second provider prefix from a `provider/provider/model` deployment string. For a deployment configured as `openai/openai/openai/gpt-5.5`, the bridge flow sent `openai/gpt-5.5` to the upstream API instead of the correct `openai/openai/gpt-5.5`. Upstream APIs that enforce model-name allow-lists rejected this as `key_model_access_denied`. Fix: pass the locally-resolved `custom_llm_provider` into both the sync `responses()` and async `aresponses()` calls so the downstream `_resolve_model_provider_for_responses` sees an explicit provider and skips the second prefix-strip. New regression test `tests/test_litellm/completion_extras/test_responses_bridge_provider_propagation.py` pins both call sites: each must forward `custom_llm_provider`. * fix(28505): set custom_llm_provider on request_data instead of as duplicate kwarg Greptile flagged that the previous patch passed custom_llm_provider as an explicit kwarg to responses()/aresponses() while request_data already carried it via the spread of sanitized_litellm_params, which would raise TypeError: got multiple values for keyword argument on every real bridge call. Switches to assigning request_data['custom_llm_provider'] before the call so the resolved provider wins over whatever sanitized_litellm_params spread in, without duplicating the kwarg. Updates the regression test to seed request_data with a sentinel custom_llm_provider so it actually exercises the overwrite path (the previous test mocked transform_request with a minimal dict and never hit the conflict). * chore: trigger shin-agent re-eval on retargeted staging base * chore: trigger shin-agent re-eval against updated Greptile state * Add 1-hour cache write pricing for EU/AU/JP Bedrock Anthropic models The 1-hour prompt-cache write tier (`cache_creation_input_token_cost_above_1hr`) was added to the us./global. variants of the Claude 4.5/4.6/4.7 family on Bedrock, but the eu./au./jp. cross-region inference profiles were left without it. AWS Bedrock pricing applies the same +10% regional premium across all geo profiles, so eu./au./jp. should carry the same 1-hour rates as us. (1.6x the 5-minute regional rate). Without these fields, cost tracking on EU/AU/JP Bedrock 1-hour-TTL prompt caching falls back to the 5-minute write rate and undercounts spend by ~60% for European, Australian, and Japanese tenants. Adds the 1-hour tier (and Sonnet 4.5's long-context >200K tier where AWS publishes one) to 14 regional Bedrock entries in both `model_prices_and_context_window.json` and the bundled `model_prices_and_context_window_backup.json`: - eu./au. Opus 4.6 ($11.00 / MTok) - eu./au. Opus 4.7 ($11.00 / MTok) - eu./au./jp. Sonnet 4.6 ($6.60 / MTok) - eu./au./jp. Sonnet 4.5 ($6.60 / MTok regular, $13.20 / MTok LC) - eu./au./jp. Haiku 4.5 ($2.20 / MTok) Also extends `tests/test_litellm/test_bedrock_anthropic_1hr_cache_pricing.py` with a `REGIONAL_EXPECTED` parametrized block covering all 13 new entries plus the existing 1.6x ratio invariant. Note: `eu.anthropic.claude-opus-4-5-20251101-v1:0` carries the wrong 5m rate today (base 6.25e-06 instead of regional 6.875e-06), which would break the 1.6x ratio check. It is intentionally left out of this PR so the scope stays "1-hour cache tier addition" — a separate follow-up should correct the EU 5m rates for Opus 4.5. --------- Co-authored-by: Terrajlz <info@jouleselectrictech.com> Co-authored-by: Bruno Devaux <devaux.br@gmail.com> Co-authored-by: Sameer Kankute <sameer@berri.ai> * Add 1-hour cache write pricing tier for Vertex AI Anthropic models (#28569) * fix(thinking): handle None thinking param in is_thinking_enabled (#28598) Squash-merged by litellm-agent from Terrajlz's PR. * feat(helm): support tpl rendering in podAnnotations (#28609) Squash-merged by litellm-agent from devauxbr's PR. * Forward custom_llm_provider through the Responses API bridge (Fixes #28505) (#28575) * Forward custom_llm_provider through the Responses API bridge (Fixes #28505) When a Chat Completions request to a GPT-5.4+ model contains both `tools` and `reasoning_effort`, `completion()` auto-routes through `responses_api_bridge`. The bridge handler called `litellm.responses()` / `litellm.aresponses()` without forwarding the already-resolved `custom_llm_provider`, so the downstream call re-invoked `get_llm_provider()` with `custom_llm_provider=None` and stripped a second provider prefix from a `provider/provider/model` deployment string. For a deployment configured as `openai/openai/openai/gpt-5.5`, the bridge flow sent `openai/gpt-5.5` to the upstream API instead of the correct `openai/openai/gpt-5.5`. Upstream APIs that enforce model-name allow-lists rejected this as `key_model_access_denied`. Fix: pass the locally-resolved `custom_llm_provider` into both the sync `responses()` and async `aresponses()` calls so the downstream `_resolve_model_provider_for_responses` sees an explicit provider and skips the second prefix-strip. New regression test `tests/test_litellm/completion_extras/test_responses_bridge_provider_propagation.py` pins both call sites: each must forward `custom_llm_provider`. * fix(28505): set custom_llm_provider on request_data instead of as duplicate kwarg Greptile flagged that the previous patch passed custom_llm_provider as an explicit kwarg to responses()/aresponses() while request_data already carried it via the spread of sanitized_litellm_params, which would raise TypeError: got multiple values for keyword argument on every real bridge call. Switches to assigning request_data['custom_llm_provider'] before the call so the resolved provider wins over whatever sanitized_litellm_params spread in, without duplicating the kwarg. Updates the regression test to seed request_data with a sentinel custom_llm_provider so it actually exercises the overwrite path (the previous test mocked transform_request with a minimal dict and never hit the conflict). * chore: trigger shin-agent re-eval on retargeted staging base * chore: trigger shin-agent re-eval against updated Greptile state * Add 1-hour cache write pricing tier for Vertex AI Anthropic models GCP Vertex AI publishes a separate 1-hour cache write column for the Claude family (1.6x the 5-minute write rate, matching the documented Bedrock ratio). LiteLLM's Vertex AI Anthropic entries only carry the 5-minute tier, so any request that uses `cache_control: {"ttl": "1h"}` on Vertex AI Claude is undercounted in cost tracking by ~60%. The runtime side already supports the 1-hour tier — `VertexAIAnthropicConfig` extends `AnthropicConfig`, populating `ephemeral_1h_input_tokens`, and `_calculate_cache_creation_cost` reads `cache_creation_input_token_cost_above_1hr`. Only the price registry was missing data. Adds the field to 19 vertex_ai/claude-* entries across both `model_prices_and_context_window.json` and the bundled `model_prices_and_context_window_backup.json`: - Haiku 4.5 ($1.25 -> $2.00 / MTok) - Sonnet 3.7 / 4 / 4.5 / 4.6 ($3.75 -> $6.00 / MTok) - Opus 4.5 / 4.6 / 4.7 ($6.25 -> $10.00 / MTok) - Opus 4 / 4.1 ($18.75 -> $30.00 / MTok) Adds `tests/test_litellm/test_vertex_anthropic_1hr_cache_pricing.py` mirroring the Bedrock equivalent — pins each (5m, 1h) pair per model and asserts the 1.6x ratio across the family. Fixes #27781. --------- Co-authored-by: Terrajlz <info@jouleselectrictech.com> Co-authored-by: Bruno Devaux <devaux.br@gmail.com> Co-authored-by: Sameer Kankute <sameer@berri.ai> * Fix Gemini multimodal function responses (#29325) Co-authored-by: shin-berri <shin-laptop@berri.ai> Co-authored-by: yuneng-jiang <yuneng@berri.ai> * address greptile review: add _transform_image_usage method and model-map supports_image_size flag - Add _transform_image_usage instance method to GoogleImageGenConfig that delegates to transform_gemini_image_usage, fixing the regression test - Replace hardcoded "2.5-flash" string check in supports_gemini_image_size with a get_model_info lookup on supports_image_size (default true) - Add supports_image_size: false to all gemini-2.5-flash model entries in model_prices_and_context_window.json so capability is controlled via the model map rather than embedded in code * fix test failures: schema validation, mypy type, model info plumbing, pricing test - Add supports_image_size to ModelInfoBase TypedDict so get_model_info surfaces it - Pass supports_image_size through _get_model_info_helper constructor call - Fix supports_gemini_image_size to use value is not False (None means unset, defaults to True) - Add supports_image_size to JSON schema in test_aaamodel_prices_and_context_window_json_is_valid - Correct gemini-3.1-flash-lite pricing assertions in test to match JSON values * Add Azure AI Kimi K2.6 metadata (#27052) * Add Azure AI Kimi K2.6 metadata * Scope Kimi metadata test cost map setup * fall back to substring check for models not in model_prices_and_context_window.json Models like gemini-2.5-flash-image-preview are not in the pricing JSON, so get_model_info raises. Fall back to "2.5-flash" not in model when the JSON has no explicit supports_image_size entry for the model. * fix(inception): don't forward global litellm.api_key to Inception FIM Match the Inception chat config: resolve only an Inception-specific key (param, litellm.inception_key, or INCEPTION_API_KEY) for the text-completion FIM path. The global litellm.api_key (often an OpenAI key) was both leaking to api.inceptionlabs.ai and taking precedence over the configured Inception key when set. * fix(auth): enforce end-user budget on custom-auth path that skips common_checks get_end_user_object() no longer raises BudgetExceededError, so custom-auth deployments with custom_auth_run_common_checks unset (which skip the centralized common_checks gate) stopped enforcing the end-user budget, letting an over-budget end user keep making requests. Re-enforce the budget in _run_post_custom_auth_checks on that path. --------- Signed-off-by: José Luis Di Biase <josx@interorganic.com.ar> Co-authored-by: Isha <72744901+IshaMeera@users.noreply.github.com> Co-authored-by: aneeshsangvikar <aneeshsangvikar@fiddler.ai> Co-authored-by: shin-berri <shin-laptop@berri.ai> Co-authored-by: yuneng-jiang <yuneng@berri.ai> Co-authored-by: Aneesh-Fiddler <aneeshfiddler@gmail.com> Co-authored-by: Suleiman Elkhoury <108065141+suleimanelkhoury@users.noreply.github.com> Co-authored-by: Dmitriy Alergant <93501479+DmitriyAlergant@users.noreply.github.com> Co-authored-by: Yanis Miraoui <yanis.miraoui19@imperial.ac.uk> Co-authored-by: Lovro Seder <vrovro@gmail.com> Co-authored-by: Thomas Mildner <12685945+Thomas-Mildner@users.noreply.github.com> Co-authored-by: José Luis Di Biase <josx@interorganic.com.ar> Co-authored-by: Lai Quang Huy <64073540+1qh@users.noreply.github.com> Co-authored-by: Claude Opus 4.8 <noreply@anthropic.com> Co-authored-by: Filippo Menghi <113345637+Cyberfilo@users.noreply.github.com> Co-authored-by: Terrajlz <info@jouleselectrictech.com> Co-authored-by: Bruno Devaux <devaux.br@gmail.com> Co-authored-by: ZHONG Ziwen <67355585+zzw-math@users.noreply.github.com> Co-authored-by: Emerson Gomes <emerson.gomes@thalesgroup.com> Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com> |