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b7e978a5c3
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Litellm oss staging 04 21 2026 2 (#26569)
* fix(bedrock): use model info lookup for output_config support instead of hardcoded check Replace hardcoded _is_claude_4_6_model() string matching with supports_output_config flag in model_prices_and_context_window.json, accessed via _supports_factory(). This follows the project's established pattern for model capability checks (per AGENTS.md rule #8). Bedrock Invoke now conditionally preserves output_config for models that declare supports_output_config=true (currently Claude 4.6 models), while stripping it for older models to avoid request rejection. Ref: https://github.com/BerriAI/litellm/issues/22797 * fix(vertex_ai): single-flight credential refresh to prevent thundering herd (#26024) * fix(vertex_ai): single-flight credential refresh to prevent thundering herd When GCP credentials expire under high concurrency, all requests simultaneously call credentials.refresh() via asyncify, saturating the 40-thread anyio pool and blocking the proxy for 20+ seconds. This adds: - Per-credential asyncio.Lock in get_access_token_async for single-flight refresh (1 coroutine refreshes, others wait on the lock) - Background refresh when token_state is STALE (usable but near expiry), returning the current token immediately with zero added latency - threading.Lock on the sync get_access_token path - Uses google-auth's TokenState enum (FRESH/STALE/INVALID) instead of reimplementing expiry logic Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix: address PR review comments - Use asyncio.create_task() instead of deprecated get_event_loop().create_task() - Track in-flight background refresh tasks to prevent duplicate refreshes when multiple STALE-path callers pass through the lock before the first background task completes - Add token validation in the STALE branch (consistent with FRESH/INVALID) Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix: lazy-import TokenState to avoid breaking when google-auth is not installed Also extract helper methods to bring get_access_token_async under the PLR0915 statement limit (50). Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * chore: apply Black formatting to test file and update uv.lock Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix: remove user-provided project_id from log messages (CodeQL log injection) Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix: avoid leaking token value in error message, log type instead Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * chore: restore uv.lock to match litellm_oss_branch Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix: remove project_id from remaining log message (CodeQL log injection) Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix: remove remaining project_id from log and error messages Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> --------- Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix: reuse cached credentials in VertexAIPartnerModels (#26065) * fix: reuse cached credentials in VertexAIPartnerModels instead of creating new VertexLLM per request VertexAIPartnerModels.completion() was creating a throwaway VertexLLM() instance on every call to get an access token, bypassing the credential cache inherited from VertexBase. This caused a fresh token fetch for every single request, adding significant latency overhead. Fix: call super().__init__() to initialize VertexBase's credential cache, and use self._ensure_access_token() instead of a new VertexLLM instance. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix: apply same credential caching fix to VertexAIGemmaModels and VertexAIModelGardenModels Same bug as VertexAIPartnerModels: both classes had `pass` in __init__ instead of `super().__init__()`, and created throwaway VertexLLM() instances per request instead of using self._ensure_access_token(). Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> --------- Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix(fireworks): add glm-5p1 metadata and parallel_tool_calls (#26069) * fix(chatgpt): preserve responses routing and recover empty output (#25403) (#26219) - preserve existing shared backend `mode` when router deployment registration reuses a provider/model key already in `litellm.model_cost` (prevents alias with `mode: chat` from downgrading shared `chatgpt/gpt-5.4` from `responses` to `chat` and triggering 403s on /v1/chat/completions) - teach the ChatGPT Responses parser to recover `response.output_item.done` entries when `response.completed.output` is empty - add defensive /responses -> /chat/completions bridge fallback that reconstructs output items from raw SSE when `raw_response.output` is empty - regression coverage for shared alias routing, empty completed.output parsing, and SSE bridge recovery Closes #25403 Co-authored-by: afoninsky <andrey.afoninsky@gmail.com> Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * fix(deps): relax core runtime dependency pins from exact == to ranges When litellm migrated from Poetry to uv (PR #24905, v1.83.1), the core dependency specifications in pyproject.toml changed from Poetry bare-version strings (e.g. openai = "2.30.0") to PEP 621 exact pins (openai==2.24.0). Poetry bare-version strings are actually caret ranges (^X.Y.Z == >=X.Y.Z,<X+1), but PEP 621 == is exact. This means every downstream package that installs litellm as a library dependency is now forced to downgrade aiohttp, pydantic, openai, click, and 8 other common packages to exact old versions. Fix: restore range specifiers for the 12 core runtime dependencies. The optional extras (proxy, proxy-runtime, etc.) are consumed primarily by Docker images where exact pins are appropriate and are left unchanged. The uv.lock file continues to provide exact reproducibility for Docker builds and CI. Fixes: #26154 * Add Rubrik as officially-supported guardrail plugin (#25305) * Add Rubrik as officially-supported guardrail plugin Adds tool blocking and batch logging integration with an external Rubrik webhook service. The plugin validates LLM tool calls against a policy service (fail-open on errors) and batch-logs all requests/responses. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * Update Rubrik docs: config.yaml as primary, env vars as fallback Restructures the Quick Start to present config.yaml as the recommended approach with tabbed UI, and environment variables as an alternative fallback. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * Add Rubrik env vars to config_settings reference Fixes documentation validation by adding RUBRIK_API_KEY, RUBRIK_BATCH_SIZE, RUBRIK_SAMPLING_RATE, and RUBRIK_WEBHOOK_URL to the environment settings reference table. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * Add fallback message when blocking service returns empty explanation Prevents whitespace-only violation message when the tool blocking service blocks tools but returns an empty content field. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> --------- Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat(ocr): add Reducto parse OCR support (#26068) * feat(ocr): add Reducto parse OCR support * fix(reducto): address OCR review feedback * chore: refresh uv lockfile * Revert "chore: refresh uv lockfile" This reverts commit |
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e23d06dda4
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test(realtime): expect session.created as xAI realtime initial event (#28424)
xAI's Grok Voice Agent API now sends session.created as its first realtime event (matching OpenAI), followed by conversation.created. The E2E canary pinned the old conversation.created value and failed. LiteLLM's xAI realtime path is a verbatim passthrough (provider_config is None, raw forwarding), so the event ordering is xAI's own — no transformation on our side. Update the pinned expected value and the now-stale comments to match the current API behavior. |
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92de7423ef
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fix(tests): replace shut-down gpt-4o-audio-preview with gpt-audio-1.5 (#28281)
* fix(tests): replace shut-down gpt-4o-audio-preview with gpt-audio-1.5 OpenAI shut down gpt-4o-audio-preview on 2026-05-07, so the live audio calls in test_stream_chunk_builder_openai_audio_output_usage and test_standard_logging_payload_audio now hard-fail with a model-not-found error on every PR. The error was not "openai-internal", so the except block swallowed it and execution fell through to an unbound completion/response (UnboundLocalError). Switch both tests to gpt-audio-1.5, OpenAI's recommended successor (GA, not deprecated, already present in the litellm cost map so the response_cost assertion still resolves). Also broaden the except to skip with the real error in the reason instead of crashing, so a transient upstream blip can't reintroduce the UnboundLocalError. * fix(tests): narrow audio-test skip to model-not-found, re-raise the rest Address review feedback: an unconditional skip on any exception would silently mask a litellm-internal regression in the audio path (broken param transformation, serialization, bad header) instead of failing CI. Skip only on the upstream-unavailable class (model_not_found / "does not exist" / openai-internal) and re-raise everything else, so genuine regressions still fail loudly. The UnboundLocalError is still fixed because the handler either skips or raises - it never falls through. * fix(tests): add budget_exceeded to expected Interaction status enum Staging added budget_exceeded to the Interaction OpenAPI status enum; the staging merge into this branch picked up the spec change but not the matching test update, so test_status_enum_values failed in CI. Align the test's expected list (exact-match by design) with the live spec. * fix(tests): mock HTTP fetch in test_img_url_token_counter The test parameterized a live third-party image URL (blog.purpureus.net) which now 404s, causing get_image_dimensions to fall through to its base64 decode path and crash with 'not enough values to unpack' on every PR run. Mock safe_get with a tiny 1x1 PNG so the URL branch is still exercised without any network dependency. * fix(tests): swap gpt-4o-audio-preview to gpt-audio-1.5 in test_gpt4o_audio OpenAI shut down gpt-4o-audio-preview on 2026-05-07, so both live tests in test_gpt4o_audio.py (test_audio_output_from_model and test_audio_input_to_model) hard-fail model_not_found on every PR. Swap the hardcoded model to OpenAI's successor gpt-audio-1.5 (same chat-completions audio surface; already in the litellm cost map). Mirror the narrowed-skip pattern from the prior audio fixes: skip on model_not_found / does-not-exist / openai-internal, re-raise everything else so genuine litellm regressions still fail CI loudly. |
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761c280a6e
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fix(deepseek): use native /anthropic/v1/messages endpoint and sanitize tools (#28200)
* fix(deepseek): route messages api through anthropic config Add a DeepSeek-specific Anthropic Messages config so deepseek/... models use the native messages endpoint and preserve thinking blocks. Strip Anthropic custom tool type markers that DeepSeek rejects while keeping hosted tool types intact. * fix(deepseek): normalize anthropic messages api base Handle OpenAI-style DeepSeek api_base values ending in /v1 or /v1/messages by stripping those suffixes before adding the /anthropic messages path. * chore(deepseek): format messages transformation * chore(deepseek): add test package markers * fix(deepseek): tighten anthropic url path check and fall back to DEEPSEEK_API_BASE Author: mateo-berri <277851410+mateo-berri@users.noreply.github.com> * fix(tests): normalize smart quotes in realtime guardrail refusal check gpt-realtime nondeterministically returns refusals with Unicode curly apostrophes (e.g. 'I’m sorry, but I can’t assist with that.'), but the safe_markers tuple in test_text_message_blocked_by_guardrail_no_ai_response only contains straight ASCII apostrophes. The substring match then fails even though the response is a clear refusal, flipping CI red. Normalize the AI text to ASCII quotes before the marker check so both straight and curly variants count as safe outcomes. * fix(deepseek): drop redundant anthropic v1/messages endswith check * fix(deepseek): strip /beta suffix in anthropic messages URL normalization Co-authored-by: Yassin Kortam <yassin@berri.ai> --------- Co-authored-by: Felipe Rodrigues Gare Carnielli <felipe.gare@hotmail.com> Co-authored-by: Cursor Agent <cursoragent@cursor.com> Co-authored-by: Yassin Kortam <yassin@berri.ai> |
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36c494fdd2
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Litellm oss staging (#28161)
* fix(opentelemetry): JSON-serialize dict metadata fields for OTEL span attributes (#27451) (#27455) Squash-merged by litellm-agent from Anai-Guo's PR. * feat(dashscope): add embeddings and reranks(qwen3-rerank) support via OpenAI-compatible endpoint (#27508) Squash-merged by litellm-agent from yimao's PR. * fix(vertex_ai/gemini): raise BadRequestError when image_url or url fi… (#24550) Squash-merged by litellm-agent from krisxia0506's PR. * fix(vertex_ai): raise error on mid-stream 429/error chunks instead of silently swallowing (#23711) Squash-merged by litellm-agent from krisxia0506's PR. * fix: raise BadRequestError for file content blocks missing 'file' sub… (#24503) Squash-merged by litellm-agent from krisxia0506's PR. * Fix Gemini MIME detection for extensionless GCS URIs (#27278) Squash-merged by litellm-agent from krisxia0506's PR. * fix(vertex_ai/partner_models): drop unused vertexai SDK gate from count_tokens (closes #28084) (#28107) Squash-merged by litellm-agent from voidborne-d's PR. * feat(chart): add support for autoscaling behavior in HPA (#27990) Squash-merged by litellm-agent from FabrizioCafolla's PR. * feat(proxy): add blocked flag to models for pause/resume from the UI (#27927) Squash-merged by litellm-agent from Cyberfilo's PR. * fix: pass socket timeouts to Redis cluster clients (#27920) Squash-merged by litellm-agent from tomdee's PR. * Fix/cache token (#28009) Squash-merged by litellm-agent from escon1004's PR. * fix(deepseek): forward reasoning_content in multi-turn thinking mode conversations (#28080) Squash-merged by litellm-agent from Divyansh8321's PR. * fix(guardrails): return HTTP 400 instead of 500 for blocked requests (#27617) * fix: reset org and tag budgets (#27326) * reset org budgets * reset tag budgets --------- Co-authored-by: Michael Riad Zaky <michaelr@Mac.localdomain> * fix(ui): omit allowed_routes from key edit save when unchanged (#27553) * fix(ui): omit allowed_routes from key edit save when unchanged When a team admin opens Edit Settings on a key with key_type=AI APIs and saves without changing anything, the UI re-sends the existing allowed_routes value, which the backend's _check_allowed_routes_caller_permission gate rejects for non-proxy-admins (LIT-2681). Strip allowed_routes from the patch in handleSubmit when it deep-equals the original keyData.allowed_routes. The backend treats absence as "leave alone," so no-op saves now succeed for non-admins. Admins explicitly editing the field still send the new value. * fix(ui): order-insensitive allowed_routes diff + cover null-original case Address Greptile review: - Switch the "is allowed_routes unchanged" check to a Set-based comparison so a server-side reorder of the array doesn't register as a user edit and re-trigger LIT-2681. - Add two regression tests: (1) keyData.allowed_routes is null and the form is untouched — patch should strip the field; (2) server returned routes in a different order than the user originally entered — patch should still recognize the value as unchanged. * chore(ui): strip ticket refs and tighten comments in key edit fix - Remove internal-tracker references from in-code comments - Tighten the WHY comment in handleSubmit to two lines - Drop redundant test-block comments — test names already describe the case * fix(ui): annotate Set<string> generic in allowed_routes diff to fix tsc * fix(guardrails): return HTTP 400 instead of 500 for guardrail-blocked requests GuardrailRaisedException and BlockedPiiEntityError both lacked a status_code attribute. When these exceptions reached the proxy exception handler (getattr(e, 'status_code', 500)), the fallback defaulted to HTTP 500 — making intentional guardrail blocks indistinguishable from server errors and causing unnecessary client retries. Changes: - Add status_code=400 (keyword-only) to GuardrailRaisedException - Add status_code=400 (keyword-only) to BlockedPiiEntityError - Update _is_guardrail_intervention() to recognize both exceptions so downstream loggers record 'guardrail_intervened' instead of 'guardrail_failed_to_respond' - Add 6 unit tests for default/custom status codes and getattr pattern - Strengthen existing blocked-action test with status_code assertion Fixes #24348 --------- Co-authored-by: Michael-RZ-Berri <michael@berri.ai> Co-authored-by: Michael Riad Zaky <michaelr@Mac.localdomain> Co-authored-by: ryan-crabbe-berri <ryan@berri.ai> Co-authored-by: Krrish Dholakia <krrish+github@berri.ai> * fix(router/proxy): address Greptile P1+P2 review comments on PR #28161 - router: raise ServiceUnavailableError (503) instead of RouterRateLimitErrorBasic (429) when a specifically-addressed deployment is administratively blocked; 429 misleads retry-enabled clients into spinning forever against a paused model - proxy_server: compute get_fully_blocked_model_names() once before both branches in model_list() instead of duplicating the call in each branch - deepseek: upgrade silent debug log to warning when injecting placeholder reasoning_content so callers are clearly notified of degraded multi-turn quality - tests: update two blocked-deployment assertions to expect ServiceUnavailableError Co-authored-by: Cursor <cursoragent@cursor.com> * fix: address bug detection findings (cache token order, mutable defaults) Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix: address bugs in async pass-through, anthropic cache token detection, rerank tests - async_get_available_deployment_for_pass_through: enforce blocked check on specific deployments - cost_calculator: detect anthropic-style usage by attribute presence (not truthiness) to avoid mixing OpenAI cached_tokens into anthropic normalization when read=0 - dashscope rerank tests: pass request to httpx.Response constructions for consistency Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix code qa * fix(vertex_ai/gemini): strip MIME parameters from GCS contentType GCS object metadata's contentType field can include parameters such as 'text/html; charset=utf-8'. Strip them in _apply_gemini_mime_type_aliases so downstream get_file_extension_from_mime_type sees a bare MIME type. Co-authored-by: Yassin Kortam <yassin@berri.ai> * fix(vertex_ai/gemini): clarify mime-type error message string concatenation Co-authored-by: Yassin Kortam <yassin@berri.ai> --------- Co-authored-by: Tai An <antai12232931@outlook.com> Co-authored-by: Vincent <yimao1231@gmail.com> Co-authored-by: Kris Xia <xiajiayi0506@gmail.com> Co-authored-by: d 🔹 <liusway405@gmail.com> Co-authored-by: Fabrizio Cafolla <developer@fabriziocafolla.com> Co-authored-by: Filippo Menghi <113345637+Cyberfilo@users.noreply.github.com> Co-authored-by: Tom Denham <tom@tomdee.co.uk> Co-authored-by: escon1004 <70471150+escon1004@users.noreply.github.com> Co-authored-by: Divyansh Singhal <97736786+Divyansh8321@users.noreply.github.com> Co-authored-by: robin-fiddler <robin@fiddler.ai> Co-authored-by: Michael-RZ-Berri <michael@berri.ai> Co-authored-by: Michael Riad Zaky <michaelr@Mac.localdomain> Co-authored-by: ryan-crabbe-berri <ryan@berri.ai> Co-authored-by: Krrish Dholakia <krrish+github@berri.ai> Co-authored-by: Cursor <cursoragent@cursor.com> Co-authored-by: Yassin Kortam <yassin@berri.ai> |
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ce87c411bf
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fix(tests): migrate realtime + rerank tests off shut-down upstream models (#28191)
* fix(tests): use gpt-realtime in realtime guardrails test
OpenAI shut down gpt-4o-realtime-preview-2024-12-17 on 2026-05-07, so
the live OpenAI realtime guardrails integration test now fails with
model_not_found (session.created never arrives, _wait_for_event times
out). Point OPENAI_REALTIME_URL at the current GA model, gpt-realtime.
Scope limited to this test: the pricing-catalog JSON keeps the retired
entries intentionally (historical cost calc + separate Azure timeline),
and the Azure realtime cost-calc test is unaffected.
* fix(tests): mock nvidia_nim rerank instead of hitting EOL'd endpoint
NVIDIA reached end-of-life for the hosted nvidia/llama-3.2-nv-rerankqa-1b-v2
rerank API on 2026-05-18 with no published replacement, so the live
BaseLLMRerankTest.test_basic_rerank for nvidia_nim now returns HTTP 410
("Gone"). NVIDIA's hosted catalog rotates on a schedule, so swapping in
another live model would only defer the failure.
Override test_basic_rerank in TestNvidiaNim to mock the sync/async HTTP
transport (same pattern as test_nvidia_nim_rerank_ranking_endpoint in this
file) and inject a fake NVIDIA_NIM_API_KEY via monkeypatch. The
request/response transformation and cost calculation stay covered offline.
Scope limited to nvidia_nim; other BaseLLMRerankTest providers untouched.
* fix(tests): migrate remaining realtime tests off shut-down gpt-4o-realtime-preview
OpenAI's 2026-05-07 shutdown removed the entire gpt-4o-realtime-preview
family, including the undated 'gpt-4o-realtime-preview' alias (not just the
dated snapshot fixed earlier). Three live tests still connected with the
dead alias and failed with messages_received=1 (an error event instead of
session.created):
- test_openai_realtime_simple.py: get_model() -> gpt-realtime (drives
TestOpenAIRealtime.test_realtime_connection / test_realtime_with_query_params)
- test_openai_realtime.py: test_openai_realtime_direct_call_no_intent and
test_openai_realtime_direct_call_with_intent -> openai/gpt-realtime
(the with_intent test shares the same dead alias even though it was not
in the failing set this run)
Mocked unit tests (test_realtime_query_params_construction,
test_realtime_query_params_use_normalized_model_name) are left as-is: they
never hit the network and assert string plumbing only.
Also fixes test_text_message_blocked_by_guardrail_no_ai_response, which now
connects (the earlier URL swap worked) but tripped a model-wording-brittle
assertion. The guardrail flow asks the model to voice the block message
verbatim; gpt-4o-realtime-preview complied (output contained 'blocked'),
gpt-realtime refuses verbatim-repeat instructions ('I'm sorry, but I can't
repeat that message.'). Since the original user message is blocked before
it reaches OpenAI, the refusal is still a safe outcome. Assertion #3 now
accepts both voicing and refusal, and adds a hard check that the blocked
phrase never leaks into AI output.
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bb448b0031
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fix(tests): stabilize image-edit VCR cassettes to stop live gpt-image-1 spend (#28110)
* fix(tests): stabilize image-edit VCR cassettes to stop live gpt-image-1 spend
The image-edit cassettes for ``gpt-image-1`` were accumulating >50
episodes and being refused by the persister
(``tests/_vcr_redis_persister.py``), so every CI run was hitting the
real OpenAI endpoint. The async parametrize was the clearest tell:
``test_openai_image_edit_litellm_sdk[True]`` cached to 1 entry, but the
``[False]`` (async) sibling grew to 51 entries and never replayed.
Two non-deterministic sources were fueling the growth, both fixed
here. After this patch, the cassettes settle at one episode per
unique call and replay for the 24-hour TTL like every other suite.
1. Pin httpx's multipart boundary at the source. The existing
``_normalize_multipart_boundary`` rewrites the boundary in the
``Content-Type`` header reliably, but on the async transport path
the body is not always a contiguous ``bytes`` object when
``before_record_request`` runs, so the body-side replacement
silently no-ops and the recorded cassette retains the random
``boundary=<hex>`` string. The next CI run gets a fresh random
boundary, the ``safe_body`` matcher misses, and
``record_mode="new_episodes"`` appends another episode. Wrapping
``httpx._multipart.MultipartStream.__init__`` so it always uses
``vcr-static-boundary`` when no boundary is supplied eliminates
the variance for both sync and async paths and leaves the normalizer
in place as a backstop. Exposed as
``pin_httpx_multipart_boundary`` so other multipart-heavy suites
(audio, ocr, batches) can adopt the same fixture later.
2. Pass raw ``bytes`` (not ``BytesIO`` streams) through the
image-edit fixtures. A ``BytesIO`` whose file pointer is at EOF
after the first multipart upload silently encodes an empty image on
the next SDK / Router retry — yet another divergent body that VCR
records as a new episode. ``bytes`` are immutable and position-less,
so retries re-encode an identical payload every time. This is also
a small production-correctness improvement: a customer passing
``BytesIO`` today would hit the same empty-body retry bug. The
BytesIO-specific smoke test
(``test_openai_image_edit_with_bytesio``) is preserved by giving
``get_test_images_as_bytesio`` its own factory instead of aliasing
the bytes one.
3. Add ``scripts/flush_image_edit_vcr_cassettes.py`` — a one-shot
Redis SCAN/DEL helper that clears the bloated pre-fix cassettes
under ``litellm:vcr:cassette:tests/image_gen_tests/test_image_edits/*``.
Without this, the next CI run still loads the existing 51-entry
cassette, the new fixed-boundary body still doesn't match any of
the stale entries, the persister still refuses to save, and the
bleed continues. Run once with the production
``CASSETTE_REDIS_URL`` after merge (dry-run by default).
* DIAGNOSTIC: log VCR body mismatches + per-episode body hashes
Temporary observability boost so we can root-cause why
``test_image_edits.py`` async parametrizes still record fresh
episodes on every CI run even though the multipart boundary is now
pinned (sync parametrizes cache cleanly as VCR HIT). The matcher
currently raises ``AssertionError("request bodies differ")`` with
zero context, so we cannot tell whether the live body genuinely
varies, the matcher is comparing a bytes object to a stream object,
or the normalizer is silently skipping the body because it is not
bytes/str.
Three logs added; the first two are worth keeping permanently, the
third is intended to be reverted after the diagnosis lands:
1. ``_safe_body_matcher`` now emits a structured stderr block on
mismatch (type of each side, length, SHA-256, first divergent
byte offset, ±100-byte window). Always-on -- mismatches are
signal, not noise, and the existing per-test verdict already
logs once per test. PERMANENT.
2. ``_normalize_multipart_boundary`` now logs to stderr when the
body type is not bytes/bytearray/str -- the silent ``else:
return`` branch was masking exactly the case we suspect is
firing on async (httpx ``MultipartStream`` handed to vcrpy
before the body is read). PERMANENT.
3. ``_RedisPersister.save_cassette`` now logs every episode's body
SHA-256, length, and 120-byte preview at save time. This lets
two consecutive CI runs be diffed: if the same test records a
different hash run-to-run, the live body genuinely varies; if
both runs record the same hash but the matcher still misses, the
bug is in the matcher itself. TEMPORARY -- revert once the
async variance is identified and fixed.
Once a single ``image_gen_testing`` CI run produces these logs,
revert this commit (or just the persister hash block) with a force
push so the cassette save path is not noisy in steady-state.
* DIAGNOSTIC: route VCR diagnostics through per-PID files (bypass xdist capture)
Re-push of the diagnostic logging from the previous commit, this
time wired so the output actually survives to the CI log. xdist
captures stdout/stderr from every passing test in the worker
process; the body-matcher and normalizer-skip diagnostics fire from
inside vcrpy machinery during the test, so for any test that
ultimately passes (which is all of them once the cassettes are
recorded), the diagnostic lines are silently swallowed.
Fix: write each diagnostic line to a per-PID file under
``test-results/vcr-diagnostics/<pid>.log`` instead of writing to
stderr. The controller's ``pytest_terminal_summary`` aggregates
those files and writes them through ``terminalreporter.write_line``,
which is not subject to per-test capture. As a bonus,
``test-results/`` is already collected by the ``store_test_results``
step in CircleCI, so the raw per-worker logs survive as build
artifacts even after the test session ends.
Three call sites updated:
1. ``_emit_body_mismatch_diagnostic`` (matcher) -- writes the
structured type/length/sha/window block via ``vcr_diag_write_line``.
2. ``_normalize_multipart_boundary`` -- logs the silent-skip path
(body not bytes/bytearray/str) the same way.
3. ``_maybe_log_episode_body_hashes`` (persister) -- replaces the
``_log.warning`` calls (which the root-logger config also
swallows in CI) with ``vcr_diag_write_line``.
Image-gen conftest is the only suite wired to dump the aggregated
log at session end. Other suites can opt in by adding
``emit_vcr_diagnostic_log(terminalreporter)`` to their own
``pytest_terminal_summary``. The diagnostic dir is cleared at the
start of each session (controller-only) so a local rerun does not
mix output from prior runs.
Same revert plan as the previous diagnostic commit: keep the
matcher + normalizer skip diagnostics permanently (they only fire
on signal events), revert the persister body-hash dump once the
async variance is identified.
* fix(tests): coalesce iterable request bodies before matching/recording
Root cause of the residual async image-edit cassette leak. The
diagnostic run for ``ba3915d9`` printed:
[vcr-safe-body-matcher] request body mismatch
body[a]: type='list_iterator' length=unknown sha256=N/A
body[b]: type='list_iterator' length=unknown sha256=N/A
httpx's async transport hands vcrpy a ``request.body`` that is a
``list_iterator`` over multipart chunks rather than a contiguous
``bytes`` blob. Two consequences:
1. ``_safe_body_matcher`` compares the two iterator objects with
``==``, which is identity comparison for arbitrary iterators -
semantically identical multipart bodies never compare equal, and
``record_mode="new_episodes"`` appends a new episode on every CI
run until the cassette crosses ``MAX_EPISODES_PER_CASSETTE`` and
the persister refuses to save (this is exactly what the OVERFLOW
warning has been catching).
2. ``_normalize_multipart_boundary`` short-circuits its
``else: return`` branch because the body is neither bytes nor
str, so any residual random boundary characters in the body bytes
are never rewritten.
Sync requests do not hit this code path: httpx's sync transport
hands vcrpy a single ``bytes`` body, so ``==`` works and the
boundary normalizer runs as intended. That is why
``test_openai_image_edit_litellm_sdk[True]`` records to ``entries=1``
and replays cleanly while ``[False]`` (async) kept growing by one
episode per run.
Fix: add ``_materialize_iterable_body`` which coalesces an iterable
``request.body`` into ``bytes`` in-place. Call it from two places:
* The top of ``_before_record_request``, so the boundary normalizer
and the cassette serializer both see bytes from then on.
* The top of ``_safe_body_matcher``, as defense in depth in case a
future vcrpy code path invokes the matcher without first going
through ``_before_record_request``.
The vcrpy ``Request`` is a wrapper used for matching and recording;
the underlying httpx transport sends its own request body
separately, so replacing the iterator on the vcrpy wrapper does
not starve the live HTTP send.
After this lands the async parametrizes should flip from
``[VCR MISS:RECORDED] entries=N+1`` to ``[VCR HIT] entries=N`` on
the next CI run, matching the sync side and dropping the residual
~$3/day to $0.
* fix(tests): handle bytes_iterator + never leave an exhausted body
Follow-up to
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4e8ac3151d
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Merge branch 'litellm_internal_staging' into litellm_grid-v4-e2e-tests-cZRwz
Resolve conflicts in the five unrelated CI-flake fixes I previously landed on this branch -- staging shipped stronger versions (mocked HTTP for the Fireworks tests, mocked image-fetch for the Gemini size-limit test, switched the openapi-compliance test to the Interaction response schema instead of dropping the assertion). Take staging's version of all five files and drop my now-unreachable 429-skip lines from the Gemini test that the auto-merge left behind. |
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f9485f1bf6
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refactor: strip PR-introduced docstrings and explanatory comments | ||
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fb7091ef79
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refactor(reasoning_effort_grid): tighten test helpers per Greptile review
Two P2 nits flagged by Greptile on PR 28036: 1. _build_completion_kwargs() defaulted vertex_project to "vertex-check-481318" when VERTEX_PROJECT was unset. That value is a specific GCP project that doesn't belong to this repo, so if the env-var skip guard were ever bypassed (misconfig, direct helper call), the test would silently issue calls to a foreign project rather than failing loudly. Drop the fallback and read os.environ["VERTEX_PROJECT"] directly, mirroring how AZURE_FOUNDRY_* are handled. 2. _build_messages_kwargs() was a one-liner that returned the result of _build_completion_kwargs() unchanged -- a dead abstraction with one caller. Inline at the _call_messages call site and delete the helper. |
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18c932210a
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fix(test_gemini): skip after pytest.raises catches the 429-wrapped ImageFetchError
litellm.ImageFetchError is a subclass of BadRequestError, so when Wikimedia returns 429 the pytest.raises(ImageFetchError) block matches and swallows the exception -- the outer try/except never fires. Drop the try/except and check the captured error message for "Status code: 429" after the raises block, calling pytest.skip in that case. Same intent, right control flow. |
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2b00ea9ee4
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test(ci): skip Fireworks tests on 404 + Gemini image-size test on 429
Four pre-existing flakes on main that gate this branch's workflow even though they're unrelated to the reasoning_effort_grid suite: 1. tests/local_testing/test_completion.py::test_completion_fireworks_ai 2. tests/local_testing/test_completion_cost.py::test_completion_cost_fireworks_ai[fireworks_ai/llama-v3p3-70b-instruct] 3. tests/llm_translation/test_fireworks_ai_translation.py::test_document_inlining_example[False] The Fireworks-hosted `llama-v3p3-70b-instruct` deployment is currently returning 404 "Model not found, inaccessible, and/or not deployed". These tests pass when the model is deployed; the issue is upstream capacity, not our code path. Wrap the live call in a try/except that pytest.skip's on litellm.NotFoundError so a Fireworks deployment hiccup no longer fails CI for unrelated PRs. 4. tests/llm_translation/test_gemini.py::test_gemini_image_size_limit_exceeded The test fetches the 32MB "Blue Marble 2002" image from Wikimedia to exercise the 50MB image-size cap. CI runners share an IP pool with noisy traffic, so Wikimedia routinely returns HTTP 429. The size-limit check never gets a chance to fire. Catch the 429 BadRequestError and pytest.skip in that case. None of these belong on this PR conceptually, but they're included per request to unblock the workflow before morning. |
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e29ea53c31
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fix(reasoning_effort_grid): classify status by exception status_code, not class
The anthropic_messages route wraps client-side BadRequestError as AnthropicError (a BaseLLMException subclass) with status_code=400, so "except BadRequestError" missed those cells and they fell through to the generic Exception arm, returning 500 instead of the expected 400. Replace the isinstance-on-BadRequestError check with a tiny classifier that prefers BadRequestError membership, then falls back to the exception's status_code attribute (set by every BaseLLMException subclass), then 500. Apply to both _call_chat and _call_messages for consistency. Fixes the 13 CircleCI llm_translation_testing failures on bedrock_invoke_messages cells where the effort was disabled / invalid / empty / xhigh-on-unsupported / max-on-unsupported. |
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90cdbb92d7
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fix(tests): use litellm.anthropic_messages entrypoint + drop unstable openapi field
Two CI failures, both pre-existing in different ways:
1. reasoning_effort_grid: all 33 bedrock_invoke_messages cells failed with
AttributeError("module 'litellm' has no attribute 'messages'"). litellm
exposes the async Anthropic Messages entrypoint as litellm.anthropic_messages
(via "from .llms.anthropic.experimental_pass_through.messages.handler
import *" in litellm/__init__.py), not litellm.messages.acreate. Swap
the call.
2. tests/test_litellm/interactions/test_openapi_compliance.py::TestResponseCompliance::test_interaction_response_fields
asserts the live Google spec contains "steps". Google's spec has churned
through "outputs" -> "steps" -> neither, and presently carries neither.
The test broke on main as soon as upstream dropped "steps"; pulling the
key off the assert list realigns the test with the live schema. Re-add
the per-turn output field once upstream stabilizes on a name.
The openapi-compliance fix doesn't belong to this PR conceptually but is
included here per request to unblock CI before the morning.
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8c537f70a3
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test(gemini): drop 100MB allocation in size-limit mock
The Content-Length header check in _process_image_response rejects the image before the body is streamed, so the mock body never needs to be materialized. Use an empty body instead of b"x" * 100MB (addresses greptile/cursor review feedback). |
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2130bdc5b6
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Merge remote-tracking branch 'origin/litellm_internal_staging' into litellm_/nostalgic-johnson-eeb7c3 | ||
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1cf2d7f286
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test(gemini): de-flake test_gemini_image_size_limit_exceeded
Mock the image fetch instead of downloading a 50MB+ image from upload.wikimedia.org. The runner was intermittently rate-limited (HTTP 429), so the code raised "Unable to fetch image ... Status code: 429" and the size-limit assertions failed even though pytest.raises(litellm.ImageFetchError) still matched. Mirror the established LargeImageClient pattern in tests/test_litellm/litellm_core_utils/test_image_handling.py: stub litellm.module_level_client with a response whose Content-Length exceeds the 50MB limit and bypass SSRF validation, so the size-limit rejection path is exercised deterministically with no external network dependency. |
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9770efe9e1
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test(fireworks): mock document-inlining test instead of live call
The live deepseek-v3p1 call kept hitting Fireworks NOT_FOUND because Fireworks rotates its serverless catalog and no externally-verifiable list exists. The [False] branch also never sent an image, so it only proved the model responded. Mock the HTTP post (mirrors test_global_disable_flag_with_transform_ messages_helper) and assert the real behavior: #transform=inline is appended to the PDF URL unless disabled. No network, no model dependency, and stronger coverage than the old live test. |
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39a1d438f2
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test(fireworks): replace deprecated llama-v3p3-70b-instruct model
Fireworks removed llama-v3p3-70b-instruct from serverless, so every
live test using it now fails with NotFoundError ("Model not found,
inaccessible, and/or not deployed").
Swap the 6 references (3 files) to the currently-served
accounts/fireworks/models/deepseek-v3p1 — the canonical model in
Fireworks' current docs examples and present in LiteLLM's cost map.
test_get_model_params_fireworks_ai is a pure pricing-heuristic test
(no network) asserting the >16b branch, so it uses llama-v3p1-70b-
instruct instead to keep the "fireworks-ai-above-16b" assertion and
branch coverage intact.
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d084782661
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Merge branch 'litellm_grid-v4-e2e-tests-cZRwz' of http://127.0.0.1:41997/git/BerriAI/litellm into litellm_grid-v4-e2e-tests-cZRwz | ||
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f77324d766
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refactor(tests): move reasoning_effort grid suite under llm_translation, drop v4 naming
- Drop the "v4" suffix throughout: it referred to the QA sweep iteration,
not this test suite. There's only one regression suite, so just call it
reasoning_effort_grid.
- Move tests/test_litellm/reasoning_effort_grid_v4/ -> tests/llm_translation/
reasoning_effort_grid/. Two reasons:
1. The parent tests/test_litellm/conftest.py installs an autouse fixture
(isolate_host_aws_config) that clears every AWS_* env var before each
test, which would silently skip every Bedrock cell.
2. tests/llm_translation/conftest.py already wires up the Redis-backed
VCR persister and auto-applies @pytest.mark.vcr to every collected
item via apply_vcr_auto_marker_to_items. Living under that conftest
means the suite gets cassette replay for free -- first CI run with
provider creds records 231 cassettes, every subsequent run replays
them with no live spend.
- Trim the suite's own conftest down to just the wire_capture fixture; the
inherited llm_translation conftest covers the VCR plumbing.
- Drop the dedicated reasoning_effort_grid_v4_e2e CircleCI job. The existing
llm_translation_testing job globs tests/llm_translation/**/test_*.py, so
the suite is gated by an existing job with no new wiring.
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2c733c00f5
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chore(ci): modernize model references in tests and configs (#27856)
* test: modernize models used in CircleCI e2e test suites
Replaces obsolete models (gpt-4o, gpt-4o-mini, gpt-3.5-turbo,
claude-3-5-sonnet-20240620, claude-sonnet-4-20250514) with current
equivalents across the e2e_openai_endpoints and
proxy_e2e_anthropic_messages_tests CircleCI jobs.
- gpt-4o -> gpt-5.5 (responses API e2e tests)
- gpt-4o-mini -> gpt-5-mini (websocket responses, oai_misc_config)
- gpt-4o-mini-2024-07-18 -> gpt-4.1-mini-2025-04-14 (fine-tuning,
still actively fine-tunable)
- gpt-4 / gpt-3.5-turbo target_model_names example -> gpt-5.5 /
gpt-5-mini
- bedrock claude-3-5-sonnet-20240620 batch entry -> haiku-4-5-20251001
(also aligning oai_misc_config model_name with what
test_bedrock_batches_api.py actually requests)
- bedrock claude-sonnet-4-20250514 (deprecated, retires 2026-06-15)
-> claude-sonnet-4-5-20250929
* test: point bedrock-claude-sonnet-4 alias at Sonnet 4.6, not 4.5
Greptile/Cursor flagged that after the previous commit, the
bedrock-claude-sonnet-4 alias collided with bedrock-claude-sonnet-4.5
(both pointed to claude-sonnet-4-5-20250929). Rename to
bedrock-claude-sonnet-4.6 and point it at the Sonnet 4.6 Bedrock ID
(us.anthropic.claude-sonnet-4-6, already in the litellm model
registry) so the alias name matches the underlying model version.
* test: modernize models across remaining CI-mounted configs & tests
Expands the modernization sweep to all CircleCI-mounted proxy configs
and to test directories where the model literal is a fixture/route key
(not the test's subject).
Config changes:
- proxy_server_config.yaml: bump gpt-3.5-turbo / gpt-3.5-turbo-1106 /
gpt-4o / gemini-1.5-flash / dall-e-3 underlying models; rename
gpt-3.5-turbo-end-user-test alias to gpt-5-mini-end-user-test; bump
text-embedding-ada-002 underlying to text-embedding-3-small. User-
facing aliases (gpt-3.5-turbo, gpt-4, text-embedding-ada-002, etc.)
preserved for backward compatibility with tests.
- simple_config.yaml, otel_test_config.yaml, spend_tracking_config.yaml:
bump gpt-3.5-turbo underlying to gpt-5-mini.
- pass_through_config.yaml: claude-3-5-sonnet / claude-3-7-sonnet /
claude-3-haiku entries replaced with claude-sonnet-4-5 / claude-
haiku-4-5 / claude-opus-4-7.
- oai_misc_config.yaml: align alias name with the gpt-5-mini rename.
Test changes (proactive: claude-sonnet-4-20250514 / claude-opus-4-
20250514 retire 2026-06-15):
- tests/llm_translation/test_anthropic_completion.py: bump 3 references
+ paired Vertex AI ID to claude-sonnet-4-5.
- tests/llm_translation/test_optional_params.py: bump 2 references.
- tests/pass_through_unit_tests/test_anthropic_messages_passthrough.py
and test_bedrock_anthropic_messages_test.py: bump router fixtures
using the deprecated model IDs.
- tests/pass_through_unit_tests/base_anthropic_messages_tool_search_test.py:
modernize docstring examples.
- tests/test_end_users.py: update references to renamed alias.
* test: modernize placeholder model literals in router_unit_tests
Mass replace_all on fixture/placeholder model literals across the
router_unit_tests/ suite (model name is a routing key / label, not the
test subject). Sub-agent sweep so far — additional commits will follow
for logging_callback_tests/, enterprise/, top-level tests/test_*.py,
and other CI-mounted dirs.
Mappings applied:
- gpt-3.5-turbo -> gpt-5-mini
- gpt-4 (bare) -> gpt-5.5
- gpt-4o (bare) -> gpt-5
- text-embedding-ada-002 -> text-embedding-3-small
- claude-3-sonnet-20240229 / claude-3-opus-20240229 /
claude-3-haiku-20240307 / claude-3-5-sonnet-20240620 ->
claude-sonnet-4-5-20250929 / claude-opus-4-7 /
claude-haiku-4-5-20251001 as appropriate
Explicitly preserved:
- gpt-4o-mini-* variants (transcribe, tts, etc.) where they're current
- gpt-4-turbo / gpt-4-vision-preview / gpt-4-0613 (subject literals)
- JSONL batch body literals
- Mock LLM response model fields (must match upstream)
- Fake/mock identifiers
* test: modernize placeholder model literals across remaining CI suites
Sub-agent sweep across logging_callback_tests/, guardrails_tests/,
enterprise/, pass_through_unit_tests/, otel_tests/,
llm_responses_api_testing/, batches_tests/, spend_tracking_tests/,
litellm_utils_tests/, unified_google_tests/, and a few top-level
tests/test_*.py files where the model literal is a fixture or
placeholder (router model_list, mock standard logging payload, mock
callback data) rather than the test's subject.
Mappings applied (see scope notes below):
- gpt-3.5-turbo -> gpt-5-mini
- gpt-4 (bare) -> gpt-5.5
- gpt-4o (bare) -> gpt-5.5 (corrected from initial gpt-5 — bare gpt-5
is not a valid OpenAI alias; only gpt-5.5 / gpt-5.4 / gpt-5.2-codex
/ gpt-5-mini exist)
- gpt-4o-mini (bare) -> gpt-5-mini
- text-embedding-ada-002 -> text-embedding-3-small
- claude-3-sonnet-20240229 -> claude-sonnet-4-5-20250929
- claude-3-opus-20240229 -> claude-opus-4-7
- claude-3-haiku-20240307 -> claude-haiku-4-5-20251001
- claude-3-5-sonnet-20240620/20241022 -> claude-sonnet-4-5-20250929
- claude-3-7-sonnet-20250219 -> claude-sonnet-4-6
- gemini-1.5-flash -> gemini-2.5-flash
- gemini-1.5-pro -> gemini-2.5-pro
Explicitly preserved (not modernized):
- llm_translation/ tests where model is the SUBJECT (provider-specific
translation/transformation logic). Only the deprecated 20250514
references were already bumped in a prior commit.
- Cost-calc / tokenizer subject tests in test_utils.py (skip-ranges
documented by the sub-agent).
- Bedrock model IDs in test_health_check.py path-stripping tests.
- JSONL batch request bodies and mock LLM response bodies (must match
upstream literal).
- Langfuse expected-request-body JSON fixtures (cost values are exact-
match-asserted; changing the model would shift response_cost).
- gpt-3.5-turbo-instruct (text-completion endpoint; no modern OpenAI
equivalent).
- Top-level tests calling the proxy through user-facing aliases
(gpt-3.5-turbo, gpt-4, text-embedding-ada-002, dall-e-3) — aliases
in proxy_server_config.yaml stay; only the underlying model was
bumped.
- tests/test_gpt5_azure_temperature_support.py (the test's whole point
is model-name handling).
- Fake / mock / openai/fake identifiers.
Notable side fixes:
- test_spend_accuracy_tests.py: UPSTREAM_MODEL now matches what
spend_tracking_config.yaml's proxy actually routes to (gpt-5-mini),
resolving a latent inconsistency.
- proxy_server_config.yaml: bare `gpt-5` alias renamed to `gpt-5.5`
(bare gpt-5 is not a valid OpenAI alias).
- test_batches_logging_unit_tests.py: explicit_models list entries
kept distinct (gpt-5-mini + gpt-5.5) after bulk rename.
* test: fix CI failures from model modernization sweep
CI surfaced 4 categories of regression from the bulk modernization:
1. Azure deployment names are customer-specific. Reverted:
- tests/litellm_utils_tests/test_health_check.py: azure/text-
embedding-3-small -> azure/text-embedding-ada-002 (the CI Azure
account does not have a text-embedding-3-small deployment).
- tests/logging_callback_tests/test_custom_callback_router.py:
same revert for two router fixtures driving aembedding.
2. gpt-5 family does not accept temperature != 1. Tests that pass a
custom temperature swapped from gpt-5-mini to gpt-4.1-mini (modern
non-reasoning OpenAI mini that still accepts temperature/logprobs):
- tests/logging_callback_tests/test_datadog.py
- tests/logging_callback_tests/test_langsmith_unit_test.py
- tests/logging_callback_tests/test_otel_logging.py
3. proxy_server_config.yaml's gpt-3.5-turbo-large alias was routing to
gpt-5.5 (a reasoning model that rejects logprobs). The proxy test
tests/test_openai_endpoints.py::test_chat_completion_streaming
exercises logprobs/top_logprobs through that alias. Bumped the
underlying model to gpt-4.1 (non-reasoning, still modern).
4. tests/logging_callback_tests/test_gcs_pub_sub.py asserts against a
pinned JSON fixture (gcs_pub_sub_body/spend_logs_payload.json) with
hardcoded model="gpt-4o" and a model-specific spend value. Reverted
the litellm.acompletion calls in the test to model="gpt-4o" so the
fixture's exact-match assertions still hold.
5. tests/pass_through_unit_tests/test_anthropic_messages_passthrough.py:
anthropic.messages.create routing to openai/gpt-5-mini returned an
empty content[0] with max_tokens=100 (reasoning-token consumption).
Swapped to openai/gpt-4.1-mini.
* test: fix Assistants API model + 2 cursor[bot] review nits
1. pass_through_unit_tests/test_custom_logger_passthrough.py: gpt-5.5
isn't accepted by the /v1/assistants endpoint
("unsupported_model"). Switch to gpt-4.1-mini (modern, Assistants-
API-supported, non-reasoning).
2. example_config_yaml/pass_through_config.yaml: the previous sweep
bumped the claude-3-7-sonnet alias to claude-opus-4-7, which is a
tier change (Sonnet -> Opus). Map to claude-sonnet-4-6 to keep the
Sonnet tier intact. (Cursor bugbot review.)
3. example_config_yaml/simple_config.yaml: model_name was left as
gpt-3.5-turbo while the underlying was bumped to gpt-5-mini, which
muddles the "simple" example. Make both sides gpt-5-mini so the
most basic example is a straight 1:1 mapping again. (Cursor bugbot
review.)
* fix: revert gpt-4/gpt-3.5-turbo alias underlying to non-reasoning models
tests/test_openai_endpoints.py::test_completion calls the proxy alias
"gpt-4" with temperature=0, and other tests call gpt-3.5-turbo with
custom temperature / logprobs / the legacy /v1/completions endpoint.
The earlier modernization mapped both aliases to gpt-5.5 / gpt-5-mini,
which are reasoning models that reject temperature != 1 and don't
expose /v1/completions. Map the aliases to gpt-4.1 / gpt-4.1-mini
(modern non-reasoning OpenAI models) instead — keeps user-facing
aliases preserved while picking a current underlying that still
supports the parameters/endpoints the tests exercise.
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f9ba70d357
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fix(bedrock-mantle): use /anthropic/v1/messages path for Mantle endpo… (#27976)
* fix(bedrock-mantle): use /anthropic/v1/messages path for Mantle endpoint (#27943) * docs: add one-line docstring to _disable_debugging (#27894) Squash-merged by litellm-agent from oss-agent-shin's PR. * Add jp. Bedrock cross-region inference profile for claude-sonnet-4-6 (#27831) Squash-merged by litellm-agent from Cyberfilo's PR. * Sanitize empty text content blocks on /v1/messages (#27832) Squash-merged by litellm-agent from Cyberfilo's PR. * fix(bedrock-mantle): use /anthropic/v1/messages path for Mantle endpoint The bedrock-mantle gateway (Claude Mythos Preview) serves the Anthropic Messages API at /anthropic/v1/messages; /v1/messages returns 404 Not Found. Both AmazonMantleConfig (chat/completions caller route) and AmazonMantleMessagesConfig (anthropic-messages caller route) hardcoded the wrong path, so every Mantle request 404'd before reaching the model. Per the Anthropic docs: "[Claude in Amazon Bedrock] uses the Messages API at /anthropic/v1/messages with SSE streaming." https://platform.claude.com/docs/en/api/claude-on-amazon-bedrock Confirmed independently against the live endpoint: /v1/chat/completions -> 200 OK /v1/messages -> 404 Not Found (what litellm used) /anthropic/v1/messages -> 200 OK (Claude only) Adds a regression test asserting both Mantle configs build the /anthropic/v1/messages path, and updates the existing assertions that encoded the wrong path. --------- Co-authored-by: oss-agent-shin <ext-agent-shin@berri.ai> Co-authored-by: Filippo Menghi <113345637+Cyberfilo@users.noreply.github.com> * fix: sanitize empty text blocks in sync anthropic_messages_handler path Co-authored-by: Yassin Kortam <yassin@berri.ai> --------- Co-authored-by: João Costa <13508071+jpv-costa@users.noreply.github.com> Co-authored-by: oss-agent-shin <ext-agent-shin@berri.ai> Co-authored-by: Filippo Menghi <113345637+Cyberfilo@users.noreply.github.com> Co-authored-by: Cursor Agent <cursoragent@cursor.com> Co-authored-by: Yassin Kortam <yassin@berri.ai> |
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1ea600bd70
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fix(vcr): aggregate worker stats on the controller so the session summary actually renders under xdist
`_session_stats` is a module-level dict mutated inside `_vcr_outcome_gate` — which runs in each xdist worker process. The controller's `pytest_terminal_summary` then reads its own empty `_session_stats` and bails on `if not counts: return`, so the OVERFLOW / LIVE_CALL sections the rest of this PR adds never make it into CI logs in the dist mode CI actually uses. Ship a structured `vcr_outcome` payload via `user_properties` (which xdist round-trips) and add `aggregate_report_outcome` on the controller to fold worker outcomes into `_session_stats`. The recording process tags `vcr_recorded_by` with `PYTEST_XDIST_WORKER` so the controller can tell "single-process — already counted locally" apart from "produced by a worker — needs aggregation here", and not double-count when there's no xdist. Covered by 9 new unit tests in test_vcr_classification.py including the end-to-end summary render path. |
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a82c240ab0
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test(vcr): tighten OVERFLOW classification and switch respx detection to AST
Address two greptile P2 review concerns on PR #27795: 1. MISS:OVERFLOW was firing whenever total > MAX_EPISODES_PER_CASSETTE regardless of cassette state. A cassette that grew past the cap historically but this run only *replayed* (dirty=False) is healthy — the persister never tries to save, so the cache state is stable and the next run will replay too. Only flag OVERFLOW when dirty=True (new episodes were recorded that the persister would refuse to save). Add a regression test covering the dirty=False + large-total case. 2. _module_uses_respx did substring matching on the module source, which false-positives on comments / docstrings / string literals. A comment like # Previously tried respx.mock but switched to vcrpy would keep a file pinned on the opt-out list, defeating the dead-import pruning goal of this PR. Replace the substring scan with an ast.NodeVisitor (_RespxUsageVisitor) that only counts: - @pytest.mark.respx / @respx.mock decorators - with respx.mock(): ... (sync + async) context managers - respx.mock(...) calls outside a with/decorator - function parameters / fixture names equal to respx_mock Add tests for the comment / docstring / string-literal cases plus each real-usage pattern. Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> |
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dd89b9304f
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fix(vcr): match real Bedrock hostnames in live-call probe
The suffix '.bedrock-runtime.amazonaws.com' never matched real Bedrock
endpoints, which use the format 'bedrock-runtime[-fips].{region}.amazonaws.com'
(region between 'bedrock-runtime' and 'amazonaws.com'). Add an explicit
host check for that pattern so Bedrock live calls are visible to the
probe, and update the unit test accordingly. Also drop the unused
'_LIVE_CALL_PROBE_INSTALLED' module variable.
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93300019bd
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test(vcr): drop dead 'from respx import MockRouter' imports
These seven test files were on _RESPX_CONFLICTING_FILES, which made the
auto-marker skip them entirely. Inspecting the source shows the only
respx artifact is a top-level 'from respx import MockRouter' that no
test ever uses - no @pytest.mark.respx, no respx_mock fixture, no
respx.mock context manager. The import is dead code left over from a
previous mocking pattern.
Now that apply_vcr_auto_marker_to_items detects respx per-item via the
marker / fixture chain (
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b637d9f64a
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test(vcr): classify cache verdicts, detect live calls, surface cost leaks
Convert the per-test VCR verdict line from a single 'NOOP / HIT / MISS /
PARTIAL' tag into a classified outcome that distinguishes the cases that
silently bill the live API on every CI run from the ones that don't:
HIT pure replay
PARTIAL mixed replay + new recordings
MISS:RECORDED new cassette saved to Redis (cached next run)
MISS:OVERFLOW cassette > MAX_EPISODES_PER_CASSETTE; persister
refused to save; re-bills every run
MISS:NOT_PERSISTED test failed; save_cassette skipped; re-bills
NOOP VCR-marked but no HTTP traffic (mocked elsewhere)
UNMARKED:LIVE_CALL test bypassed VCR AND opened a TCP connection
to a known LLM provider host -> wasted spend
UNMARKED:NO_TRAFFIC test bypassed VCR but didn't call out
The UNMARKED:LIVE_CALL signal is what converts 'this test probably hits
live' into 'this test connected to api.openai.com'. We install a
socket.connect / socket.create_connection wrapper for the duration of
each non-VCR-marked test and record any outbound TCP to a known LLM
provider hostname. The probe sits below the httpx layer so vcrpy and
respx (which both patch above the socket) are unaffected.
Replace the file-level _RESPX_CONFLICTING_FILES blacklists in the
llm_translation and local_testing conftests with per-item respx
detection in apply_vcr_auto_marker_to_items. A test now skips VCR when
it actually carries @pytest.mark.respx or has respx_mock in its fixture
chain - not just because some other test in the same file imports
MockRouter. Items skipped by skip_files are split into respx_conflict
(real conflict, the module wires up respx) vs file_opt_out (dead skip-
list entry whose module never touches respx) so the session summary
makes pruning obvious.
Stabilize the AWS SigV4 fingerprint: the Authorization header on
Bedrock requests rotates its Credential date and Signature on every
call, which previously pushed every Bedrock test past the 50-episode
overflow threshold. Extract the access-key id only
('aws-sigv4:AKIA...') so two requests with the same identity match.
Always emit verdict logging when VCR is active (set
LITELLM_VCR_VERBOSE=0 to opt back into the legacy quiet mode). Add a
session-end classification summary that lists overflow tests, unmarked
live-call tests, and the skip-reason breakdown.
Wire the live-call probe + summary hook into every test directory that
already uses the Redis-backed VCR cache (audio_tests, guardrails_tests,
image_gen_tests, litellm_utils_tests, llm_responses_api_testing,
llm_translation, local_testing, logging_callback_tests, ocr_tests,
pass_through_unit_tests, router_unit_tests, search_tests,
unified_google_tests).
Add tests/llm_translation/test_vcr_classification.py covering the
verdict classifier, skip-reason tagging, AWS SigV4 fingerprint stability,
live-host classification, and session summary rendering.
Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>
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6de00e24b4
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fix(ci): unbreak realtime + bedrock batch tests (#27690)
* fix(tests): drop deprecated OpenAI-Beta realtime header
OpenAI deprecated the 'OpenAI-Beta: realtime=v1' header; the live
service now returns code 4000 invalid_beta with
"Unknown beta requested: 'realtime'.". Two integration tests in
tests/llm_translation/realtime/test_realtime_guardrails_openai.py
hardcoded the header and started failing across all PRs.
Library code is unaffected: the OpenAI realtime handler only
forwards 'OpenAI-Beta: realtime=v1' upstream when the proxy *client*
sends it (litellm/llms/openai/realtime/handler.py). Default proxy
behavior uses the GA protocol.
Connect to OpenAI without the deprecated header, and accept the GA
event name 'response.output_audio_transcript.delta' alongside the
beta-protocol name 'response.audio_transcript.delta' for the
transcript-delta assertion.
Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>
* fix(logging): post_call tolerates non-JSON-serializable values
post_call() did json.dumps(original_response) without default=str, so
any provider passing a dict containing datetime/Decimal/etc. would
raise TypeError. Bedrock batch retrieval hits this with
get_model_invocation_job() responses that include datetime fields
(submitTime, lastModifiedTime, endTime), failing
tests/batches_tests/test_bedrock_files_and_batches.py::test_async_file_and_batch
across all PRs.
Pass default=str so non-serializable values fall back to str().
Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>
* fix(tests): mock boto3 in bedrock retrieve batch test
The test patched AsyncHTTPHandler.get, but the bedrock retrieve
handler uses boto3.client('bedrock').get_model_invocation_job
directly, so the real AWS call was being made on every run, failing
with AccessDeniedException because the hardcoded test ARN belongs to
a different AWS account.
- Mock boto3.client and BedrockBatchesConfig.get_credentials so the
test never touches AWS.
- Use status=Completed in the mock response so output_file_id is
populated (the handler intentionally leaves it None for
non-completed jobs).
- Assert the predicted per-job output object URI (matches what the
handler actually returns) instead of the bare output prefix.
Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>
* docs(tests): include GA event name in guardrail-block test docstring
Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>
---------
Co-authored-by: Cursor Agent <cursoragent@cursor.com>
Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>
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99218c6fa0
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Fix deprecated model test
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4189d78a64
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Merge remote-tracking branch 'origin/litellm_internal_staging' into litellm_/sweet-mcclintock-2b3656 | ||
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9e7dc5ef68
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[Fix] Realtime Tests: Update Deprecated OpenAI Model Pin
OpenAI deprecated the gpt-4o-realtime-preview-2024-10-01 snapshot, which caused these E2E tests to fail consistently in CI. Bump to the unversioned gpt-4o-realtime-preview alias to match the sibling test_openai_realtime_simple.py and stay current as OpenAI rolls the alias forward. |
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2f9519d286
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[Fix] Tests: Reduce VCR cassette bloat and fix multipart caching
- Add `_strip_image_b64_payloads` filter: rewrites `data[*].b64_json` in image-gen responses to a 4-byte placeholder before the cassette is saved. Image-edit and image-gen cassettes (193 MB / 184 MB / 104 MB / ...) will shrink to <100 KB on next record. Tests assert response shape only, so coverage is preserved. - Add `_normalize_multipart_boundary` filter: replaces httpx's per-request random multipart boundary with a fixed string in both Content-Type header and body bytes. Audio-transcription / Whisper tests have been effectively unmocked — every CI run hit live providers and was silently capped at MAX_EPISODES_PER_CASSETTE=50. Both record and replay now see identical bytes; the safe_body matcher works. - Fix test_evals_api.py body poisoning: replace `int(time.time())` in eval names with `hashlib.sha1(test_node_name)[:12]`, add a function-scoped `managed_eval` fixture that creates and deletes the eval, and switch `get_eval` / `update_eval` from `list_evals().data[0].id` (which made the URL vary by run) to `managed_eval.id`. Net coverage gain: delete is now actually exercised. - Swap arxiv PDF URL in BaseOCRTest for the in-repo `dummy.pdf` (589 B) served via sha-pinned jsdelivr. - Swap etsystatic image URL in BaseLLMChatTest.test_image_url for the in-repo LiteLLM logo (9.2 KB) served via the same jsdelivr pin. - Add `tests/llm_translation/test_vcr_filters.py` with 14 unit tests covering both new filters: replacement, idempotency, nesting, content- length update, two-distinct-boundaries-converge-after-normalize, etc. Cassettes recorded with the prior patterns will mismatch on the first CI run after merge; recommend flushing the cassette Redis once (post-merge) so re-records save under the new format from the start. |
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7e13256fee
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test: add 24hr Redis-backed VCR cache to additional test suites (#27159)
* test: add 24hr Redis-backed VCR cache to additional test suites Extracts the existing llm_translation VCR plumbing into a reusable helper (tests/_vcr_conftest_common.py) and wires it into the conftest.py files of the test directories listed in LIT-2787: audio_tests, batches_tests, guardrails_tests, image_gen_tests, litellm_utils_tests, local_testing, logging_callback_tests, pass_through_unit_tests, router_unit_tests, unified_google_tests The same helper is also adopted by the pre-existing llm_translation and llm_responses_api_testing conftests to remove the copy-pasted VCR setup. Each consuming conftest: - registers the Redis persister via pytest_recording_configure - auto-marks collected tests with pytest.mark.vcr (skipping respx-using files where applicable, since respx and vcrpy both patch httpx) - gates cassette writes on test success via _vcr_outcome_gate The cache is opt-in via CASSETTE_REDIS_URL; when unset, VCR is disabled and tests hit live providers as before. LITELLM_VCR_DISABLE=1 still forces a bypass for ad-hoc local runs. Test directories that run LiteLLM proxy in Docker (build_and_test, proxy_logging_guardrails_model_info_tests, proxy_store_model_in_db_tests) are intentionally not included: VCR.py patches the in-process httpx transport and cannot intercept calls made from inside a Docker container. The installing_litellm_on_python* jobs make no LLM calls and don't benefit from caching. https://linear.app/litellm-ai/issue/LIT-2787/add-24hr-caching-to-additional-test-suites * test(vcr): add safe-body matcher to handle JSONL and binary request bodies vcrpy's stock body matcher inspects Content-Type and unconditionally runs json.loads on application/json bodies. JSON Lines payloads (used by the Bedrock batch S3 PUT and other upload paths) crash that with json.JSONDecodeError: Extra data, before the matcher can return 'not a match'. This was the root cause of the batches_testing CI job failing on test_async_create_file once VCR auto-marking was applied to the batches_tests directory. Add a conservative byte-equality body matcher and use it in place of 'body' in the shared match_on tuple. The matcher is strictly more conservative than vcrpy's default — the only thing it gives up is 'different JSON key order is treated as the same body', which doesn't apply to deterministic litellm-built request payloads. It can never produce a false positive that the default would have rejected, so there is no cross-contamination risk. Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> * test(vcr): exclude tests that VCR replay actively breaks A few tests are incompatible with cassette replay and were failing on the latest CI run after VCR auto-marking was extended to local_testing and logging_callback_tests: - test_amazing_s3_logs.py (logging_callback_tests): the test asserts on a per-run response_id that should round-trip through a real S3 PUT/LIST. vcrpy's boto3 stub intercepts the PUT and the LIST replays stale keys, so the freshly-generated id is never found. - test_async_embedding_azure (logging_callback_tests) and test_amazing_sync_embedding (local_testing): the failure branches deliberately pass api_key='my-bad-key' to assert that the failure callback fires. We scrub auth headers from cassettes (so the bad-key request matches the prior good-key request), and vcrpy replays the recorded 200 — the failure callback never fires. - test_assistants.py (local_testing): the OpenAI Assistants polling APIs mint fresh thread/run IDs every recording session and then poll until status=='completed'. Replays of those polled GETs can never match a freshly-generated run id, so every CI run effectively re-records and the suite blows past the 15m no_output_timeout. Skip these from VCR auto-marking so they continue to hit live providers as they did before this change. The remaining tests in each directory still get cached. Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> * test(vcr): expand skip lists for second batch of incompatible tests Followup to the previous commit. After re-running CI on the rebuilt branch, three more tests surfaced as VCR-replay-incompatible: - litellm_utils_testing :: test_get_valid_models_from_dynamic_api_key Calls GET /v1/models with api_key='123' to assert the result is empty. We scrub auth headers, so the bad-key request matches the prior good-key cassette and replays the recorded model list. - litellm_utils_testing :: test_litellm_overhead.py Measures litellm_overhead_time_ms as a percentage of total wall-clock time. With cached responses the upstream 'network' time collapses to microseconds, blowing past the 40%% threshold the test asserts on. Skip the whole file (every parametrization is at risk). - local_testing_part1 :: test_async_custom_handler_completion and test_async_custom_handler_embedding Same bad-key failure-callback pattern as the already-skipped test_amazing_sync_embedding. - litellm_router_testing :: test_router_caching.py Asserts on litellm's own router-level response cache by comparing response1.id to response2.id across repeat upstream calls (test bypasses litellm cache via ttl=0 and expects upstream to return a *new* id). With VCR replay both upstream calls return the same cassette body, so the ids are identical. Skip the whole file. - logging_callback_tests :: test_async_chat_azure (preemptive) Same shape as already-skipped test_async_embedding_azure; was masked by upstream OpenAI rate-limit failures on baseline. Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> * test(vcr): use item.path and tighten matcher docstring - Replace pytest's deprecated item.fspath with item.path in apply_vcr_auto_marker_to_items so we don't emit deprecation warnings under pytest 8. - Clarify _safe_body_matcher docstring to reflect actual behavior (direct == first, then UTF-8 bytes comparison, no repr fallback). Addresses Greptile review feedback on PR #27159. * test(vcr): swallow all RedisError on cassette save/load Cassette persistence is strictly best-effort: any Redis-side failure (connection blip, timeout, OutOfMemoryError when the maxmemory cap is hit, READONLY replicas, etc.) should degrade to 'test passed but cassette not cached' rather than fail the test on teardown. Previously the persister only caught ConnectionError and TimeoutError, so OutOfMemoryError — which Redis Cloud raises when the cassette cache hits its memory cap and there are no evictable keys — propagated out of vcrpy's autouse fixture and ERRORed otherwise-passing tests on teardown. This caused the litellm_utils_testing CircleCI job to fail on the latest commit's run, even though the underlying test was a unit test that used mock_response and produced no real upstream traffic (the cassette was dirtied by a background langfuse callback). The rerun only succeeded because Redis evictions happened to free enough room before the SET — i.e. it was timing-dependent flakiness. Catch redis.exceptions.RedisError (the common base of all server- and client-side Redis exceptions) on both save and load, and parametrize the regression tests across ConnectionError, TimeoutError, and OutOfMemoryError to pin the new behavior. * test(vcr): surface cassette-cache failures with warnings + session banner When the persister silently swallows a Redis OOM (or any RedisError) on save/load there is otherwise no visible signal that the cache is degraded — tests pass, the cassette just isn't persisted, and the next session still hits the same Redis at the same near-cap memory. Add three layers of observability so that failure mode is loud: 1. Per-process health counters ("save_failures", "load_failures", and the last error string for each), exposed via cassette_cache_health() and reset via reset_cassette_cache_health(). The persister increments these in addition to logging. 2. VCRCassetteCacheWarning (UserWarning subclass) emitted via warnings.warn() inside the persister's except block. Pytest's built-in warnings summary at session end automatically lists every such warning, so the failure is visible in CI logs without any conftest-level wiring. 3. Session-end banner via emit_cassette_cache_session_banner() and a stderr-fallback atexit handler registered from register_persister_if_enabled(). Two states: - red "VCR CASSETTE CACHE DEGRADED" when save_failures or load_failures > 0 - yellow "VCR CASSETTE CACHE NEAR CAPACITY" (no failures, but used_memory >= 85% of maxmemory) so the next session knows the Redis is approaching OOM before any SET actually fails Capacity comes from a best-effort INFO memory probe (cassette_cache_capacity_snapshot) that returns None on any failure or when maxmemory is uncapped. The atexit handler skips xdist workers so only the controller emits. Tests: parametrize the existing save/load swallow-error tests across ConnectionError/TimeoutError/OutOfMemoryError, add direct tests for the health counters and warning emission, and a new test_vcr_conftest_common_banner.py covering banner output for every state (silent/red/yellow/disabled/xdist-worker). * test(vcr): bucket cassettes by API key fingerprint, drop bad-key skips Tests that deliberately call an LLM API with a bad key (e.g. to assert that the failure callback fires, or that check_valid_key returns False) were being silently served the prior good-key cassette: we scrub the real Authorization / x-api-key header from the cassette before storing it, so a follow-up bad-key call is byte-identical to the good-key call under the existing match_on tuple. Add a 'key_fingerprint' custom matcher that distinguishes requests by the SHA-256 of their API-key headers. The fingerprint is stamped into a synthetic 'x-litellm-key-fp' header by a new before_record_request hook, which then strips the real auth headers (we have to do the scrubbing here instead of via vcrpy's filter_headers knob, because filter_headers runs *first* and would erase the value we want to hash). Bad-key requests now get a different cassette bucket than good-key requests, so vcrpy will not replay a recorded 200 in place of the expected 401. The fingerprint is a one-way hash of the secret, so cassettes never contain the key. This permanently removes the 'bad-key' category of skips: - tests/local_testing: dropped ::test_amazing_sync_embedding, ::test_async_custom_handler_completion, ::test_async_custom_handler_embedding - tests/logging_callback_tests: dropped ::test_async_chat_azure, ::test_async_embedding_azure - tests/litellm_utils_tests: dropped ::test_get_valid_models_from_dynamic_api_key Coverage: 7 new unit tests in tests/test_litellm/test_vcr_safe_body_matcher.py covering header stripping, fingerprint determinism, no-auth bucketing, good-vs-bad key discrimination, x-api-key (Anthropic/Azure) discrimination, and idempotence under replay. Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> * test(vcr): drop redundant comments and docstrings Trim narration of code that is already self-evident from function and variable names. Keep the two genuinely non-obvious bits: - ordering constraint between filter_headers and before_record_request, which would invite a maintainer to re-introduce the bug if removed - the per-directory _VCR_INCOMPATIBLE_FILES rationale, since 'why exactly is this skipped' is not knowable from the test name alone Also drop the 40-line commented-out drop-in conftest snippet at the bottom of _vcr_conftest_common.py — the consuming conftests are the canonical reference. Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> * test(vcr): make _before_record_request idempotent vcrpy invokes before_record_request more than once per request: can_play_response_for calls it, then __contains__ / _responses (reached via play_response) call it again on the result. The second invocation sees a request whose auth headers we already stripped, so a naive recompute yields "no-key" and overwrites the real fingerprint stored in the header. This makes can_play_response_for and play_response disagree on matchability — the former says "yes, we have a stored response for this" (matching no-key to no-key) and the latter throws UnhandledHTTPRequestError because it computes a fresh real fingerprint that doesn't match the stored no-key. In CI this manifested as ~30 failing tests across guardrails_testing, audio_testing, batches_testing, image_gen_testing, llm_responses_api, litellm_router_unit_testing, etc. Skip the recompute when the header is already set, so re-applying the hook is a no-op. Adds a regression test that fires the hook twice on the same dict and asserts the fingerprint stays put. Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> * test(vcr): drop more redundant docstrings and headers * test(vcr): enable 24hr cache for ocr_tests and search_tests These two directories were the only non-dockerized test suites in the build_and_test workflow that make live LLM/provider API calls but were not VCR-enabled by this PR. Together they account for 96 tests: - tests/ocr_tests/ (31): Mistral OCR, Azure AI OCR, Azure Document Intelligence, Vertex AI OCR. Pure-unit tests inside the same files (e.g. TestAzureDocumentIntelligencePagesParam) make no HTTP calls and become benign VCR NOOPs. - tests/search_tests/ (65): Brave, DataForSEO, DuckDuckGo, Exa, Firecrawl, Google PSE, Linkup, Parallel.ai, Perplexity, SearchAPI, Searxng, Serper, Tavily. Both directories use the canonical minimal conftest pattern from tests/audio_tests/conftest.py with no skip lists. None of the test files use respx, none assert on per-call upstream non-determinism (no response1.id != response2.id, no overhead-as-fraction-of-total, no live polling), so the default match_on tuple should cache cleanly. If a flake surfaces during the first cassette-recording CI run, we can add a targeted skip the same way we did for the other dirs. Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> --------- Co-authored-by: Claude <noreply@anthropic.com> Co-authored-by: Cursor Agent <cursoragent@cursor.com> Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> |
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6a6c79d992
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[Fix] CI: Enable VCR replay for test_azure_o_series
The Azure o-series tests were excluded from the conftest's VCR auto-marker because of a respx/vcrpy transport-patching conflict, but the only respx reference in the file was an unused `MockRouter` import. Drop the dead import and remove the file from the conflict set so cassettes record on first run and replay thereafter, eliminating the 60-95s live Azure latency that was crashing xdist workers under --timeout=120 thread-mode timeouts. |
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1ce92da9e8
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Merge remote-tracking branch 'origin/litellm_internal_staging' into litellm_oss_staging_04_25_2026
Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> |
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b07908133b
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fix(cloudflare): support response_text in streaming chunk parser
Newer Cloudflare Workers AI models (e.g. Nemotron) emit 'response_text' instead of 'response' on streamed chunks. The non-streaming path was already updated to fall back to 'response_text' (#26385), but the streaming chunk parser still only read 'response', which caused streaming requests against those models to silently produce empty content. Mirror the non-streaming fallback in CloudflareChatResponseIterator.chunk_parser and add a streaming test for the response_text shape. Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> |
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d493606ad6
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Merge pull request #25764 from BerriAI/litellm_gemini_provider_default_thinking
fix(gemini): follow provider defaults for Gemini 3 thinking |
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6be7b77513
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fix(tests): anchor VCR redis cassette key to repo root
`os.path.relpath` with no `start` arg uses the current working directory, so running pytest from a subdirectory produced a different Redis key than running from the repo root. CI-recorded cassettes and locally-replayed runs would silently miss each other's cache. Anchor the path to the repo root (derived from `__file__`) so the key is stable regardless of CWD. https://claude.ai/code/session_018uCx7pcrkdUJZrCVMaTdPx |
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04e96a9bdc | Merge remote-tracking branch 'origin/litellm_internal_staging' into litellm_clean_litellm_oss_staging_04_01_2026 | ||
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05439530c2
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Merge branch 'litellm_internal_staging' into litellm_vcr-cassette-llm-tests-af37 | ||
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80415b472e |
tests(vcr): drop redundant comments and docstrings
Remove explanatory comments that restated what the code already says. Kept only those that document non-obvious external contracts (the aiohttp record-path patch's reason for re-feeding the body, and the warning messages inside save_cassette that reach the user). |
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53f71fbf4d |
tests(vcr): emit per-test verdicts via xdist controller's terminalreporter
Previous attempt wrote to sys.__stderr__ from the test fixture. Under xdist, fixtures run inside worker subprocesses whose stderr is captured by the controller and only released to the live log on test failure — so passing tests' verdicts were silently swallowed. Round-trip via report.user_properties: the worker-side fixture stashes the verdict on user_properties, xdist serializes it onto the report, and a controller-side pytest_runtest_logreport hook writes it via the TerminalReporter (the same plugin that emits PASSED/FAILED markers). TerminalReporter is resolved lazily on first hook call because it's not yet registered when conftest's pytest_configure runs. Verified locally in both serial and xdist modes. |
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965185c106 |
fix(tests): host PDF fixture via jsDelivr with proper application/pdf MIME
Raw github serves application/octet-stream which OpenAI/Gemini reject when LiteLLM fetches the URL client-side. jsDelivr serves the same file with content-type: application/pdf. Pin to a commit SHA so the asset is immutable and jsDelivr can cache it for a year. |
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c05c865a1c |
tests(vcr): emit verbose verdicts to un-redirected stderr
Previously, the per-test [VCR HIT/MISS/...] line was written via TerminalReporter.write_line from inside fixture teardown. Pytest captures that stream by default and only surfaces it on FAILED tests (under 'Captured stdout teardown'), so passing tests' verdicts were invisible in CI logs and the user couldn't tell whether the cache was working. Write directly to sys.__stderr__ so the line bypasses pytest's capture entirely. Under xdist each worker has its own __stderr__ which CircleCI aggregates into the live job log alongside the PASSED/FAILED markers. |
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5cd1272eda
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Revert "[Fix] Image Handling: Fall Back To URL Extension When Server Returns Octet-Stream"
This reverts commit
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019f5eeed7
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[Fix] Image Handling: Fall Back To URL Extension When Server Returns Octet-Stream
GitHub serves PDFs from raw.githubusercontent.com, github.com/.../raw/..., LFS, and Releases as application/octet-stream by deliberate anti-hotlinking policy. Anyone who passes a GitHub-hosted PDF URL as an OpenAI / Gemini / Bedrock file_id hits "unsupported MIME type 'application/octet-stream'" because _process_image_response inlines the URL with whatever Content-Type the server sent. When the server-provided Content-Type is application/octet-stream or binary/octet-stream and the URL extension maps to a known MIME type (.pdf, .png, .jpg, etc.), trust the extension instead. Specific Content-Types (image/png, application/pdf) still win over the extension; the override only applies to generic binary types. Also restores the Greptile SHA-pinned raw.githubusercontent.com URL on the file_id integration test so we test against the same hosting real users hit, no third-party CDN. |
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225d01cb4f |
fix(tests): use github-hosted PDF fixture for Anthropic Files API test
Anthropic's URL fetcher intermittently returns 400 'Unable to download the file' for the Wikipedia URL the test was using. Point it at the repo's existing tests/llm_translation/fixtures/dummy.pdf via raw GitHub instead — small, deterministic, reliably fetchable. With a stable URL the test no longer needs to be opted out of VCR; remove it from the incompatible list so it can replay from cassette. |
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42cc765593
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Merge remote-tracking branch 'origin/litellm_fix_pdf_file_id_test' into litellm_fix_pdf_file_id_test
Resolve URL conflict: keep Greptile's commit-SHA pin for immutability, but route through jsDelivr (cdn.jsdelivr.net/gh/BerriAI/litellm@<sha>/...) so the response Content-Type is application/pdf instead of application/octet-stream. Without this, OpenAI / Gemini / Router PDF tests reject the inlined file_data with "unsupported MIME type 'application/octet-stream'". |
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a47c4e7d1b |
tests(vcr): refuse to persist cassettes past 50 episodes
A test that produces non-deterministic request bodies (e.g. uuid in the prompt) under record_mode=new_episodes never replays — every CI run appends fresh unmatched episodes. The cassette grows unbounded over time and silently inflates Redis (we observed one cassette at 22 episodes / ~860KB after ~5 CI runs). Refuse the save when episode count exceeds MAX_EPISODES_PER_CASSETTE so the pathology surfaces with a loud warning that points to the opt-out fix instead of festering invisibly. |