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10183 commits
| Author | SHA1 | Message | Date | |
|---|---|---|---|---|
Sameer Kankute
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0290c7bc00
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fix(proxy): decode bytes and pass-through SSE for Google-native streamGenerateContent (#27444) (#28213)
* fix(proxy): decode bytes and pass-through SSE for Google-native streamGenerateContent (#27444) * fix(proxy): address Greptile review on Google-native SSE bytes path Remove unreachable try/except around SSE pass-through yield and add a unit test covering pre-formatted SSE bytes, terminator padding, and non-SSE byte fallback wrapping. Co-authored-by: Cursor <cursoragent@cursor.com> --------- Co-authored-by: Tai An <antai12232931@outlook.com> Co-authored-by: Cursor <cursoragent@cursor.com> |
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Sameer Kankute
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581882879d
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feat(ui): add Interactions API endpoint to playground with SSE streaming (#28156)
* feat(ui): add Interactions API support to playground with streaming
Adds /v1beta/interactions as a selectable endpoint in the UI playground.
Uses SSE streaming (stream=true) and parses content.delta events for real-time output.
Co-authored-by: Cursor <cursoragent@cursor.com>
* fix(interactions): remove forced gemini provider so all providers work via interactions API
Proxy endpoint was hardcoding custom_llm_provider="gemini" before routing,
preventing non-Gemini models from using the litellm_responses bridge.
Also reverts the UI Gemini-only model filter.
Co-authored-by: Cursor <cursoragent@cursor.com>
* fix(interactions): fix streaming for non-gemini providers via bridge
Two bugs in LiteLLMResponsesInteractionsStreamingIterator:
1. content.delta was emitted without "type":"text" in delta dict, so the
UI type-check always failed and no tokens were displayed
2. First OutputTextDeltaEvent was silently dropped (used to emit content.start
with empty text); fixed by handling ResponsePartAddedEvent for content.start
so text deltas go directly to content.delta
Co-authored-by: Cursor <cursoragent@cursor.com>
* undo unrelated changes
* fix(ui): extract model from top-level field in interactions bridge events
Co-authored-by: Yassin Kortam <yassin@berri.ai>
* test(interactions): remove tautological gemini-provider assertion
The test_no_forced_gemini_provider_in_request_data check only asserted
against dict literals it had just constructed, so it always passed and
did not exercise the create_interaction endpoint. The endpoint
deliberately defaults custom_llm_provider to gemini, so the assertion
was also factually incorrect. Drop the misleading test.
Co-authored-by: Yassin Kortam <yassin@berri.ai>
* fix(interactions): use ContentPartAddedEvent and guard interaction.start ordering
- ResponsePartAddedEvent corresponds to reasoning summary parts, not text
content parts. Use ContentPartAddedEvent which is the event emitted before
text output deltas (type response.content_part.added).
- Mirror the OutputTextDeltaEvent ordering guard: if interaction.start has
not been sent yet, emit it first before content.start to honor the
documented event ordering contract.
Co-authored-by: Yassin Kortam <yassin@berri.ai>
* test(interactions): cover ContentPartAddedEvent ordering and no-op paths
* fix(tests): treat corrupt VCR cassette payloads as cache miss + use gpt-realtime in OpenAI realtime guardrails test
VCR redis persister was raising UnicodeDecodeError on cached payloads that
fail to UTF-8 decode (e.g. legacy entries written by another version of
the persister), failing tests at fixture setup instead of degrading to a
cache miss. Wrap decode+deserialize in a try/except so corrupt cache
entries are treated as CassetteNotFoundError, surfacing the failure via
the existing _record_cache_failure / VCRCassetteCacheWarning path.
OpenAI shut down gpt-4o-realtime-preview-2024-12-17 (and the entire
gpt-4o-realtime-preview family) on 2026-05-07. The live realtime
guardrails integration test now fails with model_not_found instead of
receiving session.created. Point OPENAI_REALTIME_URL at the current GA
model gpt-realtime, and relax the assertion in
test_text_message_blocked_by_guardrail_no_ai_response to also accept the
model's refusal-to-repeat the block message (gpt-realtime declines
verbatim-repeat instructions, which is still a safe outcome since the
original user message was blocked before reaching OpenAI). The
BLOCKED_PHRASE leak check is preserved as a hard invariant.
* fix(tests): migrate realtime + nvidia_nim rerank tests off shut-down upstream models
OpenAI shut down the entire gpt-4o-realtime-preview family (including the
undated alias) on 2026-05-07. The live realtime tests still connected
with that dead alias and failed with messages_received=1 (an error event
'The model gpt-4o-realtime-preview does not exist' instead of
session.created). Point the live OpenAI realtime tests at gpt-realtime,
the current GA realtime model:
- test_openai_realtime_simple.py: get_model() -> gpt-realtime
- test_openai_realtime.py: test_openai_realtime_direct_call_no_intent and
test_openai_realtime_direct_call_with_intent -> openai/gpt-realtime
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.
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.
* test(callbacks): harden flaky proxy callback-leak detector
The proxy callback-leak detector (test_check_num_callbacks_on_lowest_latency)
was failing on this PR with 'abs(85 - 95) <= 4' — a bounded one-time
registration jump caused by switching to latency-based-routing
(+LowestLatencyLoggingHandler, +SlackAlerting). The count then plateaus
under load, so this is pollution from the test's own config update, not a
leak.
Replace the brittle two-sample diff threshold with a sampler that settles
past the deliberate config switch and only flags sustained monotonic
per-type growth, with a terminal-burst confirmation pass for leaks that
would otherwise escape the >=2-interval guard. Normalizes instance
addresses so identical callbacks at different memory locations collapse,
and names the leaking type on failure.
* fix(interactions): preserve first text token when both start events are missing
When OutputTextDeltaEvent arrived before any ResponseCreatedEvent or
ContentPartAddedEvent, the double-fallback path emitted interaction.start
and silently dropped the first delta's text — the second delta's
content.start carried only that chunk's delta, and the first token never
made it to any content.delta event consumed by the UI.
Queue a content.start that carries the first delta's text alongside the
interaction.start emission, and drain pending events before pulling the
next upstream chunk.
* chore(ui): remove unused InteractionOutput/InteractionResponse interfaces
Co-authored-by: Yassin Kortam <yassin@berri.ai>
---------
Co-authored-by: Cursor <cursoragent@cursor.com>
Co-authored-by: Yassin Kortam <yassin@berri.ai>
Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
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Mateo Wang
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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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Mateo Wang
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761ab19209
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fix(bedrock): sanitize batch metadata to prevent Pydantic ValidationError (#28202)
* fix(bedrock): sanitize batch metadata to prevent Pydantic ValidationError Proxy guardrail hooks (Model Armor, OpenAI Moderations) and internal processing inject non-string values (dicts, floats) into the request metadata. When the Bedrock batch handler passes this metadata directly to LiteLLMBatch (which inherits OpenAI's Batch Pydantic model with metadata: Dict[str, str]), Pydantic raises a ValidationError. This causes the router retry loop to re-submit the same Bedrock job multiple times before ultimately failing. Add _get_openai_compatible_batch_metadata() that serializes non-string values to JSON strings via safe_dumps, skips None values and internal logging keys, ensuring the response object always validates. * test(bedrock): add tests for batch metadata sanitization Covers _get_openai_compatible_batch_metadata: string passthrough, dict/float serialization, None/internal key exclusion, and LiteLLMBatch compatibility. --------- Co-authored-by: Noah Nistler <60981020+noahnistler@users.noreply.github.com> |
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yuneng-jiang
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a7f3dbcbe3
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test(callbacks): harden flaky proxy callback-leak detector (#28195)
* test(callbacks): TEMP diagnostic probe for callback-leak flake Hardened leak detector (sample N, flag sustained monotonic per-type growth, normalize instance addresses) + a temporary always-fail probe on test_check_num_callbacks_on_lowest_latency that dumps the per-type series and raw reprs via the JUnit failure message, to settle real-leak vs bounded-pollution on CCI. Diagnostic block is clearly marked and will be reverted before the PR. * test(callbacks): harden proxy callback-leak detector, drop diagnostic CCI diagnostic confirmed the 85->95 jump is a bounded one-time registration from the test's own switch to latency-based-routing (+LowestLatencyLoggingHandler, +SlackAlerting), flat at 95 for 2.5 min under load — not a leak. Final detector: settle past the deliberate config/update, sample N times, flag only sustained monotonic per-type growth, normalize instance addresses, name the leaking type on failure. Removes the temporary always-fail probe. * test(callbacks): address review - drop redundant settle, close terminal-burst blind spot - test_check_num_callbacks: remove leftover sleep(30) before sleep(SETTLE_SECONDS) (60s -> 30s dead wait). - Add _terminal_suspects + _detect_leaks_confirmed: when monotonic net growth is confined to the final interval (escapes the >=2-interval guard), take one confirmation sample. A real ongoing leak keeps climbing and is flagged; a one-time terminal registration plateaus and is ignored. |
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Sameer Kankute
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73e32a31bf
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feat(prometheus): add user_email and user_alias to user budget metrics (#28155)
* feat(prometheus): add user_email and user_alias to user budget metrics User budget Prometheus gauges now expose human-readable labels alongside user_id, matching team and API key budget metrics for Grafana filtering. Co-authored-by: Cursor <cursoragent@cursor.com> * fix(prometheus): gate user budget email/alias labels behind opt-in flag Address greptile review: adding labels to existing metrics is a breaking cardinality change. Gate behind prometheus_user_budget_label_include_email_alias=True (default: False) so existing dashboards and recording rules are unaffected. Co-authored-by: Cursor <cursoragent@cursor.com> --------- Co-authored-by: Cursor <cursoragent@cursor.com> |
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Sameer Kankute
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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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Sameer Kankute
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477b63c5ea
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fix(caching): replay openai/responses bridge cache hits as chat streams (#28158)
* fix(caching): replay openai/responses bridge cache hits as chat streams
When chat completions route through openai/responses, cached ModelResponse
payloads under aresponses keys were deserialized as ResponsesAPIResponse
(500) or re-translated as responses events (empty streaming deltas). Deserialize
chat-shaped cache entries as acompletion and bypass the responses stream iterator
for cached CustomStreamWrapper replay.
Co-authored-by: Cursor <cursoragent@cursor.com>
* fix(caching): map responses bridge call_type for sync vs async stream replay
Co-authored-by: Yassin Kortam <yassin@berri.ai>
* fix: handle ModelResponse cache return in responses bridge and drop dead acompletion check
Co-authored-by: Yassin Kortam <yassin@berri.ai>
* fix(caching): detect chat cache hits via object field before choices fallback
Prefer chat.completion object type over the broad choices-key heuristic so
Responses API cached payloads are not misclassified if their schema changes.
Co-authored-by: Cursor <cursoragent@cursor.com>
* test(caching): cover responses bridge cache-hit paths in CI-tracked test suite
The new bridge cache replay logic in caching_handler.py and the
preformatted-stream guard in litellm_responses_transformation/handler.py
were exercised only by tests under tests/local_testing/, which the
responses-caching-types and misc shards do not run. Codecov flagged the
patch as 29.72% covered.
Add equivalent unit tests under tests/test_litellm/ so the responses,
caching, types, and misc shards execute them and ship their coverage
data to Codecov:
- _is_chat_completion_cached_dict happy/sad paths
- aresponses streaming bridge cache hit -> CustomStreamWrapper
- responses non-streaming bridge cache hit -> ModelResponse
- legacy ResponsesAPIResponse stream + non-stream replay
- _is_preformatted_cached_chat_stream true/false
- completion/acompletion early return on cached ModelResponse
- completion/acompletion skip rewrap on preformatted cached stream
* fix: add negative guard on object field in _is_chat_completion_cached_dict
Co-authored-by: Yassin Kortam <yassin@berri.ai>
* fix(vcr): treat corrupt cassette payloads as cache miss
* test: bump EOL'd NVIDIA rerank and OpenAI realtime models in CI
The NVIDIA hosted rerank endpoint for nvidia/llama-3_2-nv-rerankqa-1b-v2
reached end-of-life on 2026-05-18 and now returns HTTP 410 Gone, breaking
TestNvidiaNim::test_basic_rerank. Switch to nvidia/nv-rerankqa-mistral-4b-v3,
which is still hosted on the NVIDIA API catalog and is already listed in
model_prices_and_context_window.json.
OpenAI also retired the gpt-4o-realtime-preview-2024-12-17 model used by
test_realtime_guardrails_openai (now returns model_not_found). Switch the
realtime test URL to the GA gpt-realtime alias.
Unrelated to the responses-bridge cache fix in this PR, but committing
here to unblock CI per maintainer guidance.
Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>
* test(realtime): switch retired gpt-4o-realtime-preview to gpt-realtime
OpenAI removed gpt-4o-realtime-preview and all its date snapshots on
2026-05-18 (every variant now returns model_not_found), breaking the
live-WebSocket OpenAI realtime tests in CI:
- test_openai_realtime_direct_call_no_intent
- test_openai_realtime_direct_call_with_intent
- TestOpenAIRealtime.test_realtime_connection
- TestOpenAIRealtime.test_realtime_with_query_params
Point each of those to the current GA alias gpt-realtime (verified live).
Pure unit/mock tests that just assert the string value (e.g. in
test_realtime_query_params_construction and the
test_realtime_query_params_use_normalized_model_name mock) are left
alone since they do not depend on model availability.
Also relax the AI-response assertion in
test_text_message_blocked_by_guardrail_no_ai_response: gpt-realtime
occasionally produces a polite refusal ("I'm sorry, but I can't say
that") when the cancel arrives after the model has already started
generating, which is the expected outcome (no real AI content) but does
not contain the words 'blocked' or 'guardrail'. The primary guardrail
behaviour (guardrail_violation error event + transcript_delta block
message) is still asserted unchanged.
Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>
* test(nvidia_nim): mock rerank live API 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 (returns HTTP 410 Gone), and the proposed
replacement nv-rerankqa-mistral-4b-v3 returns HTTP 404 for the CI account,
breaking TestNvidiaNim::test_basic_rerank.
Override test_basic_rerank to mock the HTTP transport (same pattern as
test_nvidia_nim_rerank_ranking_endpoint above) so the request/response
transformation and cost calculation stay covered without depending on
NVIDIA's hosted catalog rotation. The model identifier reverts to the
original llama-3.2-nv-rerankqa-1b-v2 since the request never leaves
the test process.
---------
Co-authored-by: Cursor <cursoragent@cursor.com>
Co-authored-by: Yassin Kortam <yassin@berri.ai>
Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>
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yuneng-jiang
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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.
|
||
|
ishaan-berri
|
8c6625216b
|
fix(bedrock/cohere): send embedding_types as JSON array, not string (#28172)
* fix(bedrock/cohere): wrap embedding_types as list in map_openai_params Bedrock Cohere expects embedding_types as a JSON array but encoding_format was passed through as a raw string, causing: Malformed input request: #/embedding_types: expected type: JSONArray, found: String * test(bedrock/cohere): assert embedding_types is sent as JSON array --------- Co-authored-by: Ishaan Jaffer <ishaanjaffer0324@gmail.com> |
||
|
Mateo Wang
|
bb448b0031
|
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
|
||
|
ryan-crabbe-berri
|
fe63650ebd
|
fix(proxy): gate team allowed_passthrough_routes to proxy admins (#28097)
* fix(proxy): gate team allowed_passthrough_routes to proxy admins allowed_passthrough_routes short-circuits the role-based route gate, so the keys endpoints already restrict it to proxy admins. The team writers (/team/new, /team/update) had no equivalent check, letting an org admin (a non-proxy-admin who clears the route gate and _verify_team_access) self-grant pass-through routes on their team. Lift the keys check into a shared helper and apply it to both team endpoints. Resolves LIT-3019 * docs(proxy): note view-only admins are intentionally excluded from passthrough gate Clarifies the proxy-admin guard per review feedback; no behavior change. Refs LIT-3019 |
||
|
Mateo Wang
|
1b0ae3af83
|
fix(mcp-oauth): PROXY_BASE_URL escape hatch + diagnostic logging for {"detail":"invalid_request"} (#28086)
* fix(mcp-oauth): add PROXY_BASE_URL escape hatch + diagnostic logging for invalid_request
Customers hitting "{"detail":"invalid_request"}" on the MCP /authorize
endpoint had no way to recover when their ingress mangles X-Forwarded-*
headers (the same-origin check in validate_trusted_redirect_uri compares
the browser-supplied redirect_uri against get_request_base_url, which is
reconstructed from those headers).
Two contained changes:
1. get_request_base_url now honours PROXY_BASE_URL as the canonical
public origin when set, bypassing the X-Forwarded-* trust gate
entirely. Operators who know their public URL can set it once
instead of debugging ingress header rewrites.
2. The rejection path in validate_trusted_redirect_uri emits a WARN
log carrying the redirect_uri, computed proxy base, and the
X-Forwarded-* / Host headers seen. A bare 400 was undiagnosable;
this turns it into a one-line root-cause.
* test(mcp-oauth): capture warnings from correct logger ("LiteLLM")
Co-authored-by: Yassin Kortam <yassin@berri.ai>
* fix(mcp-oauth): reject malformed PROXY_BASE_URL with one-shot diagnostic
A scheme-less PROXY_BASE_URL (e.g. "litellm.example.com" instead of
"https://litellm.example.com") would sail through urlparse with empty
scheme + netloc, silently breaking every same-origin compare in
validate_trusted_redirect_uri and leaving the operator staring at the
same opaque 400 the env var was meant to fix.
Validate it once at read time: only honour values that parse as
http(s) URLs with a non-empty netloc; otherwise log a one-shot WARN
naming the bad value and fall through to the request-derived origin
so the proxy still serves traffic.
* fix(mcp/oauth): normalize PROXY_BASE_URL to strip query/fragment
Match the X-Forwarded-* path's normalization so a configured
PROXY_BASE_URL containing a query string or fragment does not break
downstream f-string concatenation like f"{base_url}/callback".
Co-authored-by: Yassin Kortam <yassin@berri.ai>
* refactor(mcp-oauth): drop non-essential comments from PROXY_BASE_URL changes
Strip narrative comments and verbose docstrings added in this PR; the
code is intuitive enough on its own and the log messages already carry
their own diagnostic context. Pre-existing comments are left untouched.
---------
Co-authored-by: Cursor Agent <cursoragent@cursor.com>
Co-authored-by: Yassin Kortam <yassin@berri.ai>
|
||
|
Shivam Rawat
|
fbe0ee81f1
|
fix(proxy): sort BYOK models by their displayed name in /v2/model/info (#28079)
* fix(proxy): sort BYOK models by team_public_model_name in /v2/model/info
Team BYOK rows persist an internal `model_name` like
`model_name_{team_id}_{uuid}` and expose the user-facing name via
`model_info.team_public_model_name`. The UI's `getDisplayModelName`
and the search filter already fall back to that field, but
`_sort_models` was keying off the raw `model_name` — so BYOK rows
ranked by their opaque IDs and clumped at the end of the alphabetized
list instead of interleaving with non-BYOK rows.
Match the UI/search behavior: prefer `team_public_model_name` when
present, fall back to `model_name` otherwise.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* fix(proxy): case-insensitive DB-side search for BYOK models
`_apply_search_filter_to_models` used Prisma's JSON path
`string_contains` to match the BYOK `team_public_model_name` field, but
that operator is case-sensitive in Postgres (no `mode: insensitive`
flag like column-level string filters have). So a search for "claude"
missed a stored "Claude Sonnet" via the DB branch even though the
router-side path matched it case-insensitively.
Widen the JSON branch to "row has a team_public_model_name set" and
filter case-insensitively in Python so DB-only BYOK rows match the
same terms users see in the UI. This also drops the now-unused
DB-level page-size optimization and `sort_by` knob — the in-Python
filter is the source of truth for `db_models_total_count` now.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* fix(proxy): scope BYOK search results to caller's accessible teams
`_apply_search_filter_to_models` was widened to fetch every row with a
`team_public_model_name` set so case-insensitive search could match
mixed-case stored names. `/v2/model/info` is reachable by non-admin
keys though, and the helper ran before `include_team_models` / `teamId`
filtering — so a non-admin caller could search a common substring like
"claude" and see BYOK rows belonging to teams they're not a member of.
Resolve the caller's team membership once (admin → no scoping, else
their `user_row.teams`) and drop BYOK rows (those with
`model_info.team_id` set) outside that scope on both the router-side
matches and the over-broad DB query, before display-name matching.
Non-team rows are unaffected and remain gated by the existing
`include_team_models` / `direct_access` paths.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* fix(proxy): search by team_public_model_name and scope teamId queries
- /v2/model/info search now matches both `model_name` and
`model_info.team_public_model_name`, so team BYOK rows (which persist
an internal `model_name_{team_id}_{uuid}`) are findable by the public
name shown in the UI. DB query OR-includes a JSON-path match on
`team_public_model_name` for rows that exist only in the DB.
- `_filter_models_by_team_id` no longer short-circuits on the viewer's
`direct_access` flag — that describes the admin viewer's own
permissions and would leak every public model into a team-scoped view.
Models are kept only when they belong to the team (own BYOK, in
access_via_team_ids, or reachable via team.models / access groups).
- Added `_authorize_team_id_query`: the untrusted `teamId` query
parameter now requires the caller to be a proxy admin or a member of
the requested team, otherwise returns 403. Without this, any
authenticated user could enumerate another team's BYOK metadata by
guessing the team id.
- `_get_caller_byok_team_scope` now treats `PROXY_ADMIN_VIEW_ONLY` the
same as `PROXY_ADMIN` (both are admin roles); previously VIEW_ONLY
admins fell through to a user-id team lookup and saw only their own
teams' BYOK rows.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* fix(proxy): bound BYOK search DB fetch in /v2/model/info
Previously the DB-side search OR'd a JSON-path predicate
`{model_info: {path: [team_public_model_name], string_contains: ""}}`
to compensate for Prisma's case-sensitive JSON `string_contains` on
Postgres. That predicate matches every row that has any
`team_public_model_name` set, so any authenticated caller could force a
full BYOK-table read with `/v2/model/info?search=x` regardless of page
size.
Drop the JSON-path branch. The DB query now does a bounded
`model_name contains <search>` lookup. BYOK rows that are loaded into
the router are still searchable by their `team_public_model_name` via
the router-side filter; only the rare edge case of a BYOK row that
exists only in the DB (router sync failed) loses display-name search,
which is an acceptable trade-off given the DoS surface.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* fix(proxy): bound DB find_many in /v2/model/info search
The previous bounding patch dropped the page-aware `take=N` on
`find_many`, so a broad `?search=model` would load and decrypt every
matching DB row on each request even though the response only returns
one page.
Restore bounded fetches in `_apply_search_filter_to_models`:
* Unsorted searches use `take = max(0, page * size - router_count)`,
i.e. exactly one page worth of remaining DB rows.
* Sorted searches need ordering across the full match set, so they cap
at `_SORTED_SEARCH_DB_FETCH_CAP = 500` instead of fetching everything.
* Total count comes from a cheap `count(...)` query so pagination stays
accurate without materializing every row.
Wired `page`, `size`, and `sortBy` through from the endpoint and added
a regression test covering both `take` values.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* refactor(proxy): extract DB-fetch helper to satisfy PLR0915
_apply_search_filter_to_models tripped Ruff's "too many statements"
(51 > 50) after the bounded-fetch fix. Move the DB-side block into
`_fetch_db_models_for_search`, which keeps the same behavior:
* Bounded `take` via page math (unsorted) or `_SORTED_SEARCH_DB_FETCH_CAP`
(sorted)
* Cheap `count(...)` for accurate pagination totals
* Caller-team scope applied to fetched rows before decrypt
Pure refactor; no behavior change. All 8 BYOK/team tests still pass.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* style: apply black formatting to _fetch_db_models_for_search
CI's "Check Black formatting" step flagged one line in the helper added
in
|
||
|
ryan-crabbe-berri
|
86f73e5e8a
|
feat(otel): set http.response.status_code on the success SERVER span (#28090)
The proxy SERVER span ("Received Proxy Server Request") only carried
http.response.status_code on failures (set in _record_exception_on_span),
so success traces had no 2xx bucket — error-ratio and status-breakdown
dashboards were missing their denominator and the span violated the HTTP
semconv (the attribute is required whenever a response is sent). Add a
set_response_status_code_attribute helper and call it from
async_post_call_success_hook with 200, symmetric with the failure path
and the existing route/preprocessing-duration SERVER-span attributes.
|
||
|
ryan-crabbe-berri
|
0300333753
|
feat(otel): OTel-standard attributes on the proxy SERVER span (status code, route/path, preprocessing latency) (#28040)
* feat(otel): expose http.response.status_code on failure spans
Set the OTel-standard http.response.status_code (integer) on failure
spans alongside the existing OpenInference error.code (kept for
back-compat). error.type is already emitted via ERROR_TYPE.
Crucially, also record structured error attributes on the proxy SERVER
span ('Received Proxy Server Request') from async_post_call_failure_hook
- the only place the SERVER span is in hand. _handle_failure records on
the litellm_request child span (the parent span is not propagated into
its kwargs), so prior to this change the SERVER span that dashboards
query carried only span status, never error.code/error.type. Reuses
_record_exception_on_span + StandardLoggingPayloadSetup.get_error_information
so values match the child span.
Tests: recorder unit coverage + a hook-driven test asserting the SERVER
span is stamped (the gap recorder-only tests missed). Full
test_opentelemetry.py suite: 197 passed.
* feat(otel): set http.route + url.path on the proxy SERVER span
Add the OTel-standard http.route (low-cardinality route template, e.g.
/v1/threads/{thread_id}/runs) and url.path (literal path) to the SERVER
span ('Received Proxy Server Request') so dashboards can group traffic
by endpoint instead of seeing every path param as a unique value.
Same architectural gap as the status-code commit: the success/failure
logging handlers write the litellm_request CHILD span, and
_handle_success explicitly refuses to copy to the SERVER span. Verified
with a console-exporter run that the SERVER span was bare on success.
Unlike error info, route/path are known at request time, so set them
directly on the freshly-created SERVER span in user_api_key_auth (one
edit point, works for success and failure, no hook-ordering risk):
- http.route from the matched FastAPI route (scope['route'].path),
empirically confirmed populated at auth-dependency time.
- url.path from the existing literal-path variable.
New get_request_route_template helper + set_proxy_request_route_attributes
(no-op on None span, so the Langfuse override stays safe).
Tests: route-attribute setter + route-template helper edges. Full
test_opentelemetry.py and test_auth_utils.py green.
* feat(otel): set litellm.preprocessing.duration_ms on the proxy SERVER span
Expose the total time LiteLLM spends before the upstream provider
request begins (auth + parsing + pre-call hooks) as a single number on
the SERVER span ('Received Proxy Server Request'). Window:
proxy-receive -> FIRST provider handoff.
Retry semantics: first attempt only (pure preprocessing, excludes
retry loops + backoff). api_call_start_time is overwritten on every
attempt, so a set-once first_api_call_start_time pins the first handoff.
Same architectural gap as the prior two commits: the success/failure
logging handlers write the litellm_request CHILD span, not the SERVER
span. Set it instead from the post-call hooks on
user_api_key_dict.parent_otel_span.
Failure-path subtlety: request_data.pop('litellm_logging_obj') runs
before the failure-hook loop, so the failure hook can't read the
logging object. litellm_received_at is propagated via the existing
request->metadata channel, and first_api_call_start_time is mirrored
onto litellm_params.metadata, so both anchors survive into request_data
and the OTel helper reads them uniformly for success and failure.
Edits: user_api_key_auth (stash receive instant), litellm_pre_call_utils
(propagate it), litellm_logging (set-once first handoff + metadata
mirror), opentelemetry (constant + set_preprocessing_duration_attribute,
called from both post-call hooks).
Tests: duration helper (both container shapes, missing/negative/None
edges) + set-once invariant (retry doesn't overwrite, metadata mirror).
test_opentelemetry.py + test_auth_utils.py + test_litellm_logging.py:
447 passed. Verified live: SERVER span carries the attribute on success
and failure, coexisting with the status-code and route attributes.
* fix(otel): MyPy type-narrowing for status-code + preprocessing-duration
No behavior change. MyPy (CI lint) flagged:
- error_information["error_code"] is str|None: narrow via a None-checked
local before int().
- _to_timestamp returns Optional[float]: resolve both anchors and return
early if either is None instead of subtracting possibly-None floats.
* fix(otel): stop polluting user request metadata with first_api_call_start_time
The PR3 set-once preprocessing anchor was mirrored into
litellm_params["metadata"] from core litellm_logging.py. That dict is
the caller's request metadata, mutated in place and shared across every
call path including pure SDK (litellm.acreate_batch). It got echoed into
LiteLLMBatch(metadata=...), which the OpenAI batch schema types as
Dict[str, str] -> pydantic ValidationError on a datetime value.
- litellm_logging.py: set first_api_call_start_time only on
model_call_details (success path reads it there directly).
- proxy/utils.py: post_call_failure_hook lifts it off the logging object
into request_data (internal top-level key, same convention as the
other proxy-internal request_data keys) right before the existing
litellm_logging_obj pop. Never touches user metadata.
- opentelemetry.py: read the anchor from the container top level
(model_call_details on success, request_data on failure).
- Tests updated; add TestPostCallFailureHookLiftsFirstApiCallStartTime.
Fixes the batches_testing regression introduced on this branch.
* chore(otel): trim verbose comments to concise rationale
Collapse multi-line why-blocks to one or two lines and drop process/plan references (PR-numbering, "the plan") from test comments. No behavior change.
|
||
|
yuneng-jiang
|
57e5e4a3b7
|
Merge pull request #28036 from BerriAI/litellm_grid-v4-e2e-tests-cZRwz
test(ci): add reasoning_effort grid e2e regression suite |
||
|
Yassin Kortam
|
014cb8fa9d
|
feat: add componentized proxy deployment with gateway, backend, ui, and migrations (#27557)
Split the monolithic LiteLLM proxy into independently scalable Kubernetes components to allow separate horizontal scaling of the LLM data plane and management API surfaces - Add DatabaseURLSettings pydantic-settings model that assembles DATABASE_URL (and optional DATABASE_URL_READ_REPLICA) from discrete DATABASE_* env vars before Prisma initializes, supporting both IAM token auth (minting short-lived RDS tokens) and password auth; replaces the CLI-only path that componentized entrypoints bypass - Add gateway component (port 4000) that trims the proxy route table to the LLM data-plane surface (chat, embeddings, completions, audio, realtime, provider passthroughs, health/metrics) via an allowlist applied inside the lifespan context so plugin-registered routes are captured - Add backend component (port 4001) that exposes the management/admin surface (keys, users, teams, orgs, spend analytics, model management, SSO, audit logs) with a complementary allowlist - Add ui component — Next.js static export served by nginx (port 3000) with RSC payload routing, asset prefix aliasing, and SPA fallback for dashboard routes - Add migrations component with dedicated Dockerfile that runs prisma migrate deploy via a Helm pre-install/pre-upgrade Job, eliminating per-pod schema contention on the Prisma advisory lock - Add Helm chart (helm/litellm) with separate Deployments, Services, HPAs, and ConfigMap for each component; shared _helpers.tpl emits DATABASE_*, IAM_TOKEN_DB_AUTH, REDIS_*, and DISABLE_SCHEMA_UPDATE env vars from chart values; ingress template routes traffic to the correct component by path prefix - Add comprehensive tests for DatabaseURLSettings covering IAM auth, password auth, read replica fallbacks, operator-pinned URL preservation, and percent-encoding; add coverage test asserting gateway + backend allowlist union equals the full proxy route set - Add pydantic-settings>=2.14.1 as a proxy extra dependency and update liccheck allowlist Co-authored-by: Yassin Kortam <yassinkortam@g.ucla.edu> |
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Mateo Wang
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4e8ac3151d
|
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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Mateo Wang
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f9485f1bf6
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refactor: strip PR-introduced docstrings and explanatory comments | ||
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Mateo Wang
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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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Mateo Wang
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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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Mateo Wang
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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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Mateo Wang
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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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Mateo Wang
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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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Yuneng Jiang
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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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Yuneng Jiang
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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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Yuneng Jiang
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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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Yuneng Jiang
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b5db7ed37d
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test(fireworks): mock remaining live smoke tests
test_completion_fireworks_ai and test_completion_cost_fireworks_ai made real Fireworks calls and broke whenever Fireworks rotated its serverless catalog (no externally-verifiable model list exists). They also asserted nothing — just printed. Mock the HTTP post and assert real behavior instead: the request is built with the right model/messages and the OpenAI-compatible response parses back; the cost path yields a non-zero cost against the local cost map. No network, no model dependency, stronger than the old smoke checks. |
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Yuneng Jiang
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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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Yuneng Jiang
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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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Yuneng Jiang
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11393f86f5
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test(interactions): validate response fields against Interaction schema
Google restructured the live spec at ai.google.dev/static/api/ interactions.openapi.json: the output-only fields (notably the `steps` array, formerly `outputs`) moved off the request schema `CreateModelInteractionParams` onto a dedicated `Interaction` response schema. The response-side tests still read from the request schema, so `test_interaction_response_fields` failed with "Output field 'steps' not in spec". Point `test_interaction_response_fields` and `test_status_enum_values` at the `Interaction` schema (the semantic response object; all output fields incl. `steps` present there). Request-side tests keep using `CreateModelInteractionParams` (all request fields verified still present). 13/13 pass against the current live spec. |
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yuneng-jiang
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c706184444
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Merge pull request #28029 from BerriAI/litellm_/determined-yalow-811fee
test(proxy): isolate run_server CLI tests from prisma DB-setup path |
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Mateo Wang
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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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Mateo Wang
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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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Cursor Agent
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51dff1ff79
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fix(reasoning_effort_grid_v4): grant sonnet-4-6 entries the max-effort cap
The runtime _validate_effort_for_model allows effort='max' for any Claude 4.6 model (opus or sonnet), and model_prices_and_context_window sets supports_max_reasoning_effort: true for claude-sonnet-4-6. The grid spec previously gave sonnet-4-6 entries _CAPS_NONE, so expected() returned status=400 for effort='max', which mismatched the runtime's status=200 and caused 6 cells (one per route) to fail. Rename _CAPS_OPUS_4_6 to _CAPS_4_6 (since the cap set is shared by opus and sonnet 4.6) and assign it to all sonnet-4-6 entries. Co-authored-by: Yassin Kortam <yassin@berri.ai> |
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Cursor Agent
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432742778a
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fix(reasoning_effort_grid_v4): cleanup unused fixture, parse converse body, guard budget tokens
- Remove unused vertex_credentials_path fixture (and now-unused os import) from conftest.py. - Parse Bedrock Converse complete_input_dict (logged as a JSON string by converse_handler.py) before passing to _assert_cell, so dict accessors work uniformly across routes. - Extend _BUDGET_TOKENS with xhigh and max entries so the budget-mode branch in expected() cannot KeyError if a future budget model gains the matching cap. Co-authored-by: Yassin Kortam <yassin@berri.ai> |
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Mateo Wang
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fec4ae69e0
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test(ci): add reasoning_effort grid v4 e2e regression suite
Encode the 231-cell QA sweep (21 provider x model combos x 11 effort values) from #27039 / #27074 as an automated CircleCI-gated regression suite. Each cell hits the real provider endpoint, captures the outgoing wire body via a pre-call CustomLogger, and asserts: - thinking.type, output_config.effort, thinking.budget_tokens, max_tokens in the captured request body (regression signal for silent drops/strips in any provider transformation) - HTTP status (200 vs BadRequestError -> 400) returned by litellm (regression signal for clean-error vs leaked-500 mappings) The matrix is encoded as a small rule set keyed by (model_mode, effort) plus per-model xhigh/max capability overrides, then expanded across the five chat-completion routes (Anthropic direct, Azure AI Foundry, Vertex AI, Bedrock Converse, Bedrock Invoke /chat) and the Bedrock Invoke /v1/messages route. Cells skip at runtime when the route's provider env vars are absent, so PR builds without credentials no-op gracefully. Wired into CircleCI as the reasoning_effort_grid_v4_e2e job behind the existing main / litellm_* branch filter. |
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Michael-RZ-Berri
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c459646162
|
feat: add OTEL GenAI latest-experimental semantic convention support (#27418)
- Introduce `OTEL_SEMCONV_STABILITY_OPT_IN=gen_ai_latest_experimental` opt-in that switches OTEL traces to conform with the OpenTelemetry GenAI semantic conventions specification
- Extract all semconv behavior into a new `OTELGenAISemconvMixin` class in `gen_ai_semconv.py`, mixed into `OpenTelemetry` to keep concerns separated
- In semconv mode, span name follows `{operation} {model}` pattern (e.g. `chat gpt-4`) and span kind is set to `CLIENT` instead of legacy `litellm_request`
- Replace `gen_ai.system` with `gen_ai.provider.name` and drop `llm.is_streaming` in semconv mode; add `gen_ai.request.{frequency_penalty,presence_penalty,top_k,seed,stop_sequences,stream,choice.count}` and `gen_ai.usage.cache_{creation,read}.input_tokens` attributes
- Replace per-message `gen_ai.content.prompt` / per-choice `gen_ai.content.completion` log events with a single consolidated `gen_ai.client.inference.operation.details` event; omit `gen_ai.input/output.messages` when content capture is disabled
- Suppress the non-standard `raw_gen_ai_request` child span entirely in semconv mode
- Support both programmatic (`OpenTelemetryConfig.semconv_stability_opt_in` field) and environment variable activation; the two sources are unioned so either or both can enable the opt-in
- Extract OTEL SDK `LogRecord` / `SeverityNumber` version-compatibility shim into a reusable `_otel_log_types()` static method to deduplicate the `< 1.39.0` / `>= 1.39.0` import branching
- Add 30+ unit tests covering opt-in gating, span naming, attribute emission/omission rules, stop sequence normalization, cache token attributes, and the consolidated event lifecycle
Co-authored-by: Yassin Kortam <yassinkortam@g.ucla.edu>
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Yuneng Jiang
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ed8a8a634b
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Merge remote-tracking branch 'origin/litellm_internal_staging' into litellm_/determined-yalow-811fee | ||
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Yuneng Jiang
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953a8b1b85
|
test(proxy): isolate run_server CLI tests from prisma DB-setup path
test_keepalive_timeout_flag and test_timeout_worker_healthcheck_flag were the only run_server tests in test_proxy_cli.py that neither stripped DATABASE_URL/DIRECT_URL nor mocked the prisma DB path. When a DATABASE_URL is present (CI/env leak), run_server --local enters the DB block and blocks in the un-timeout'd subprocess.run(["prisma"]) at proxy_cli.py:987 plus the ProxyExtrasDBManager migrate-deploy retry loops, ~370s per test on the CI runner. --dist=loadscope pins both to one xdist worker, so the proxy-infra job appears stuck at 99% and hits the 20-min timeout. Apply the same isolation every other run_server test in this file already uses: mock PrismaManager.setup_database + should_update_prisma_schema and strip DATABASE_URL/DIRECT_URL. Full module drops from 31.7s to 2.9s locally; both tests fall off the slow list. |
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yuneng-jiang
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361a84ccb0
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Merge pull request #28022 from BerriAI/litellm_/hardcore-albattani-e592b4
fix(proxy): make /config/update env-var encryption idempotent |
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Mateo Wang
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2c733c00f5
|
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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Yuneng Jiang
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a4a1726d99
|
test(proxy): add endpoint-level regression for /config/update double-encryption
Adds test_update_config_env_var_round_trip_not_double_encrypted, which drives the real /config/update handler: first write plaintext, then re-POST the stored ciphertext (the Admin UI round-trip) and assert the value is not stacked with a second encryption layer and untouched keys stay byte-identical. Verified to fail against the pre-fix handler and pass after. Also tightens the unit test to exactly three ciphertext re-feeds. |
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Yuneng Jiang
|
0d8c9137fb
|
fix(proxy): make /config/update env-var encryption idempotent
A single decrypt-then-encrypt chokepoint (_encrypt_env_variables_for_db) now backs both update_config and save_config. Re-submitting a value the Admin UI read back from /get/config/callbacks as ciphertext no longer stacks a second encryption layer, which previously decrypted to garbage and silently broke the callback. The chokepoint decrypts with the pure _decrypt_db_variables (no os.environ mutation on the write path) and encrypts exactly once; update_config merges only the sent keys so untouched env vars keep their stored ciphertext byte-for-byte. |
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ishaan-berri
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f9ba70d357
|
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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Sameer Kankute
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50df072d95
|
feat: add weighted-routing failover (#27980)
* Feat: Add Weighted-Routing Failover
* test(router): cover weighted failover helper functions
Co-authored-by: Cursor <cursoragent@cursor.com>
* fix(router): align weighted failover deployment list type with mypy
Co-authored-by: Cursor <cursoragent@cursor.com>
* fix(router): address greptile review on weighted failover
- Narrow exception swallowing in `_maybe_run_weighted_failover` to
`openai.APIError` so model failures defer to the regular fallback
while programming bugs (AttributeError/KeyError/TypeError) surface.
- Note async-only limitation of `enable_weighted_failover` in the
Router constructor docstring.
- Make the weighted distribution test less flaky (1000 iterations,
looser bound) and make the non-simple-shuffle test deterministic by
failing both deployments instead of relying on the latency strategy's
first pick.
Co-authored-by: Cursor <cursoragent@cursor.com>
* fix(router): ensure weighted failover metadata persists in kwargs
The previous `kwargs.setdefault(metadata_variable_name, {}) or {}` returned
a brand-new dict whenever the existing metadata was falsy (empty dict or
None), so writes to `_failover_excluded_ids` never made it back into
`kwargs`. Multi-hop weighted failover then re-selected previously failed
deployments and exhausted `max_fallbacks` prematurely.
Explicitly assign a fresh dict into kwargs when metadata is missing so
mutations are visible to subsequent failover hops.
Co-authored-by: Yassin Kortam <yassin@berri.ai>
* test(router): regression for weighted failover metadata persistence
Asserts kwargs["metadata"]["_failover_excluded_ids"] is populated after
_maybe_run_weighted_failover, proving the metadata dict written by the
helper is the same object that lives in kwargs (no disconnected copy).
Pairs with the prior fix that replaced `setdefault(..., {}) or {}` with
an explicit get/assign so writes survive across hops.
Co-authored-by: Cursor <cursoragent@cursor.com>
* fix(router): harden weighted failover error/state handling
- Catch RouterRateLimitError (ValueError) alongside openai.APIError in
_maybe_run_weighted_failover so an exhausted intra-group retry falls
through to the regular cross-group fallback path instead of bubbling
out and bypassing configured fallbacks.
- Stop mutating the shared input_kwargs dict; build a local copy with
the weighted-failover keys so the entry (with _excluded_deployment_ids)
cannot leak into later fallback paths reading the same dict.
- _get_excluded_filtered_deployments now returns an empty list when the
exclusion filter removes every healthy deployment, instead of falling
back to the original list. The original-list behavior risked re-picking
the just-failed deployment; callers already handle the empty case by
raising their no-deployments error, which weighted failover now catches
and converts into a normal cross-group fallback.
Co-authored-by: Yassin Kortam <yassin@berri.ai>
* fix(router): fall through to rpm/tpm when total weight is zero
When the weight metric's total is zero (e.g. after weighted-failover
exclusion leaves only zero-weight backups), continue to the next metric
(rpm/tpm) instead of returning a uniform random pick immediately. This
lets rpm/tpm still drive routing when present, and only falls back to
the uniform random pick at the end if no metric provides a positive
total weight.
Co-authored-by: Yassin Kortam <yassin@berri.ai>
* fix(router): skip weighted failover when remaining deployments are all in cooldown
_maybe_run_weighted_failover was computing 'remaining' from all_deployments
(every deployment in the model group, including those in cooldown). This meant
that when all non-excluded deployments were in cooldown the method still invoked
run_async_fallback unnecessarily, which propagated into async_get_healthy_deployments,
found no eligible deployments, and raised RouterRateLimitError — only safely
caught thanks to the earlier exception-broadening fix.
The fix: before computing 'remaining', fetch the current cooldown set via
_async_get_cooldown_deployments and subtract it from all_ids. This allows
_maybe_run_weighted_failover to return None immediately (skipping the
run_async_fallback call entirely) when every non-failed deployment is in cooldown,
letting the caller fall through to the correct cross-group fallback path without
the wasteful extra round-trip.
Tests added:
- unit: _maybe_run_weighted_failover returns None without calling run_async_fallback
when all remaining deployments are in cooldown
- unit: _maybe_run_weighted_failover still calls run_async_fallback when at least
one healthy (non-cooldown) deployment is available
- integration: end-to-end fallthrough to cross-group fallback when remaining
deployments are in cooldown
Co-authored-by: Sameer Kankute <Sameerlite@users.noreply.github.com>
---------
Co-authored-by: Cursor <cursoragent@cursor.com>
Co-authored-by: Yassin Kortam <yassin@berri.ai>
Co-authored-by: Sameer Kankute <Sameerlite@users.noreply.github.com>
|
||
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Sameer Kankute
|
106b2f2da8
|
Merge pull request #27977 from BerriAI/litellm_mcp_internal_delegate_pkce
fix(mcp): delegate PKCE bypass for internal MCP servers |
||
|
Sameer Kankute
|
c2efe9e422
|
fix(vertex-ai): fix zero cost/usage on completed Vertex AI batch jobs (#27912)
* fix(vertex-ai): fix zero cost/usage on completed Vertex AI batch jobs Vertex batch jobs recorded 0 spend and 0 tokens after PR #25627 added automatic transformation of GCS predictions.jsonl to OpenAI format. Two bugs fixed: 1. batch_utils.py: the Vertex-specific cost/usage reader (calculate_vertex_ai_batch_cost_and_usage) was always invoked and reads raw usageMetadata fields that no longer exist in the OpenAI-shaped output. Now the reader is only used when disable_vertex_batch_output_transformation=True; otherwise the generic path handles the already-transformed OpenAI-shaped content. 2. cost_calculator.py: batch_cost_calculator skipped the global litellm.get_model_info() lookup when a model_info dict was passed in, even when that dict had no pricing fields (e.g. deployment metadata with only id/db_model). It now falls back to the global pricing table when the provided model_info has no pricing data. Co-authored-by: Cursor <cursoragent@cursor.com> * Update litellm/cost_calculator.py Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com> * fix(cost-calculator): use not-any guard for pricing fallback in batch_cost_calculator Co-authored-by: Cursor <cursoragent@cursor.com> * fix(cost-calculator): treat explicit zero batch pricing as set in model_info The fallback to litellm.get_model_info() used truthy checks on pricing fields, so 0.0 was treated as missing and replaced by global rates. Use `is not None` like elsewhere in cost calculation. Add regression test. Co-authored-by: Sameer Kankute <Sameerlite@users.noreply.github.com> --------- Co-authored-by: Cursor <cursoragent@cursor.com> Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com> Co-authored-by: Sameer Kankute <Sameerlite@users.noreply.github.com> |
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|
Sameer Kankute
|
cbdc70d544
|
fix(managed_batches): convert raw output_file_id to managed ID in CheckBatchCost poller (#27984)
* fix(managed_batches): convert raw output_file_id to managed ID in CheckBatchCost poller
CheckBatchCost bypasses async_post_call_success_hook, causing raw provider
output_file_ids to be persisted in LiteLLM_ManagedObjectTable. This fix converts
output_file_id and error_file_id to managed base64 IDs before the DB write.
Co-authored-by: Cursor <cursoragent@cursor.com>
* fix(check_batch_cost): persist managed file before mutating response and propagate team_id
- Move setattr after store_unified_file_id so the response only receives the
managed ID once the DB record is successfully written. Avoids serializing
an orphaned managed ID into file_object when the store call fails.
- Populate team_id on the minimal UserAPIKeyAuth from job.team_id so the
managed file record is created with the correct team ownership, allowing
other team members to access the batch output file via /files/{id}/content.
Co-authored-by: Yassin Kortam <yassin@berri.ai>
* test(managed_batches): extend test to cover error_file_id conversion
Co-authored-by: Cursor <cursoragent@cursor.com>
* fix managed file test
---------
Co-authored-by: Cursor <cursoragent@cursor.com>
Co-authored-by: Yassin Kortam <yassin@berri.ai>
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