- compute image_generation cost from usage token metadata for vertex/gemini\n- map ImageUsage to Usage and reuse generic_cost_per_token\n- fallback to output_cost_per_image when usage metadata missing\n- add tests for token-based path and fallback path
- add gemini-3.1-flash-image-preview + vertex_ai alias entries\n- set pricing to Gemini 3.1 Flash Image Preview rates\n- mirror updates in packaged backup model map\n- update llm cost calc regression test to cover new model
Add new /public/endpoints endpoint that returns which providers support each LiteLLM
endpoint (e.g., chat_completions, embeddings). The endpoint reads from a local backup
JSON file bundled with the package, caches the result in-process, and transforms the
raw provider-centric data into an endpoint-centric response format.
Changes:
- Add litellm/provider_endpoints_support_backup.json (copy of root source file)
- Add Pydantic response models (EndpointProvider, SupportedEndpoint, SupportedEndpointsResponse)
- Add /public/endpoints route with transformation and caching logic
- Add 16 comprehensive tests covering HTTP layer and transformation functions
Co-Authored-By: Claude Haiku 4.5 <noreply@anthropic.com>
- Updated MidStreamFallbackError to retrieve and maintain the original status code from the wrapped exception.
- Ensured that message, request, and response fields remain consistent after calling the parent constructor.
- Added unit tests to verify the correct propagation of status codes and attributes in various scenarios.
Same bug as team budget: _assemble_user_object fetched user info from DB
but only used budget_reset_at, discarding max_budget. When the key cache
has a stale None for user_max_budget, _safe_get_remaining_budget returns
+Inf. Now falls back to DB max_budget when metadata value is None.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
* fix(gemini): enable inputAudioTranscription and handle transcription events for realtime guardrails
Gemini sends inputTranscription/outputTranscription inside serverContent separately from modelTurn/turnComplete. This adds handling to convert them into OpenAI-compatible events so the guardrail pipeline can inspect voice input, and enables inputAudioTranscription in the session setup config.
Made-with: Cursor
* fix(vertex_ai): enable inputAudioTranscription in realtime session config
Add inputAudioTranscription to the Vertex AI realtime setup so the backend returns transcripts of user speech, allowing guardrails to inspect voice input.
Made-with: Cursor
* fix(realtime): pass user_api_key_dict and guardrail metadata through async_realtime handler
The base LLM HTTP handler's async_realtime method was not accepting or forwarding user_api_key_dict and litellm_metadata to RealTimeStreaming. This meant guardrails configured with default_on=false were silently skipped for all provider_config-based realtime connections (Gemini, Vertex AI, etc). Also fixes wss:// connections when SSL_VERIFY=False by overriding ssl=False for secure WebSocket URLs.
Made-with: Cursor
* fix(realtime): forward guardrail metadata for generic provider_config and vertex_ai paths
The _arealtime function was not passing user_api_key_dict or litellm_metadata to base_llm_http_handler.async_realtime() for the generic provider_config path and the vertex_ai-specific path. This broke guardrail resolution since RealTimeStreaming.request_data was empty, causing should_run_guardrail to return False.
Made-with: Cursor
* fix(realtime): voice guardrail responses and block duplicate response.create on text input
When a guardrail blocks voice input, send a conversation.item.create + response.create to the backend so the LLM voices the guardrail message as audio instead of only returning text. Also adds pending_guardrail_message tracking to suppress the automatic response.create the client sends after a blocked text message, and broadens _has_audio_transcription_guardrails to match pre_call/post_call modes.
Made-with: Cursor
* test(realtime): update guardrail tests for broadened audio transcription check and add integration tests
Update existing tests to reflect that pre_call guardrails now correctly trigger the audio/VAD session.update injection. Add integration test file for live OpenAI realtime guardrail testing.
Made-with: Cursor
* fix(realtime): instruct LLM to say exact guardrail message verbatim
The previous prompt gave the LLM creative freedom to paraphrase the guardrail violation message. Now it instructs the LLM to repeat the exact configured message word for word.
Made-with: Cursor
* fix(realtime): preserve wss ssl semantics and move live guardrail test
Keep TLS enabled for wss realtime sessions while honoring SSL_VERIFY=False via a no-verify SSLContext, move the OpenAI live guardrail test into llm_translation, and dedupe duplicated guardrail-detection helpers to prevent drift.
Made-with: Cursor
The file was at the repo root and excluded from pip distributions. Moving it to litellm/proxy/public_endpoints/ alongside the other provider JSON files ensures it is packaged correctly. Updates all references in the endpoint handler, coverage tests, and release notes instructions.
Co-Authored-By: Claude Haiku 4.5 <noreply@anthropic.com>
Return all supported endpoints and which providers support them. Includes endpoint display names, URL paths, and per-provider support lists. Results are cached for the process lifetime.
Also adds comprehensive test coverage for the new endpoint.
Co-Authored-By: Claude Haiku 4.5 <noreply@anthropic.com>
Phase 2 (per-worker mark_process_dead on shutdown) only ever fired
when all workers shut down together, making it redundant — Phase 1
wipes everything on next startup anyway. This aligns with the
prometheus_client docs: just wipe the directory between runs.
Adds cleanup utilities for PROMETHEUS_MULTIPROC_DIR to prevent
unbounded RAM/disk growth from stale .db files in multi-worker setups.
Three-part lifecycle aligned with upstream prometheus_client docs:
1. Startup: wipe entire directory before workers fork (clean slate)
2. Shutdown: mark_process_dead() for own PID (removes gauge_live* only)
3. Periodic (hourly): scan for dead PIDs and call mark_process_dead()
Counter/histogram files are never individually deleted at runtime to
avoid partial counter resets that cause false spikes in rate()/increase().
Also auto-creates PROMETHEUS_MULTIPROC_DIR when prometheus callback is
configured with multiple workers and the env var is not already set.
Replace Prisma ORM count/find_many calls with two query_raw calls that
only project the key_alias column. The Prisma client wrapper does not
support SELECT projection via find_many, so raw SQL is used to keep
memory usage proportional to the page size rather than total key count.
Update tests to mock query_raw instead of count/find_many.
Co-Authored-By: Claude Haiku 4.5 <noreply@anthropic.com>
LiteLLM_VerificationTokenActions.find_many() does not support the
select keyword argument. Remove it and drop the corresponding test.
Co-Authored-By: Claude Haiku 4.5 <noreply@anthropic.com>
Add select={"key_alias": True} to the find_many call so only the alias
column is fetched from the database instead of full token rows. Add
five unit tests in test_key_management_endpoints.py covering response
shape, pagination skip/take computation, search filter injection,
absence of contains filter when no search term is given, and the
select-only-alias optimization.
Co-Authored-By: Claude Haiku 4.5 <noreply@anthropic.com>
The /key/aliases endpoint previously fetched all key aliases from the database without limit, causing OOM crashes with large key sets. Added page, size, and search query parameters with database-level filtering to enable paginated and searchable key alias retrieval. Updated the response to include pagination metadata (total_count, current_page, total_pages, size) matching the /v2/model/info pattern.
Co-Authored-By: Claude Haiku 4.5 <noreply@anthropic.com>
Adds TestProxyMcpStatelessBehavior to test_proxy_mcp_e2e.py with a test
that verifies two independent MCP clients can connect, initialize, and
call tools without sharing session state. This catches the regression
from PR #19809 where stateless=False broke clients that don't manage
mcp-session-id headers.
Regression test for #20242
When extended thinking is enabled, the websearch interception agentic loop
builds a follow-up assistant message with only tool_use blocks. Anthropic's
API requires assistant messages to start with thinking/redacted_thinking
blocks when thinking is enabled, causing a 400 Bad Request.
Extract thinking blocks from the model's initial response, thread them
through the agentic loop, and prepend them to the follow-up assistant
message — matching the pattern used by anthropic_messages_pt in factory.py.
Fixes the error: "Expected 'thinking' or 'redacted_thinking', but found
'tool_use'"
The tests were mocking `filter_server_ids_by_ip` but the production
code in server.py now calls `filter_server_ids_by_ip_with_info` which
returns a (server_ids, blocked_count) tuple. Update all 8 mock sites
to use the correct method name and return signature.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
When calling non-text-embedding-3 models routed through the openai provider
(e.g. nvidia/llama-3.2-nv-embedqa-1b-v2), passing `dimensions` previously
raised an UnsupportedParamsError unconditionally. This fix threads
`allowed_openai_params` through the embedding call stack so that providers
can opt-in to passing `dimensions` by including it in the list.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
The old test assumed ArizePhoenixLogger reused the global TracerProvider.
With the nested traces fix, Phoenix now creates its own dedicated provider
and produces litellm_proxy_request + litellm_request + raw_gen_ai_request
spans independently.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
- ArizePhoenixLogger now creates spans on its own dedicated TracerProvider
instead of trying to reuse parent spans from the global otel TracerProvider
(which were invisible in Phoenix since they go to a different exporter)
- Auto-initialize ArizePhoenixLogger when otel callback is configured and
Phoenix env vars (PHOENIX_API_KEY, PHOENIX_COLLECTOR_*) are detected
- Use exact type check in get_custom_logger_compatible_class to prevent
ArizePhoenixLogger (subclass) from being returned when looking up otel
- Fix tool_permission guardrail to check non-function tools like
code_interpreter (previously skipped with `type != "function"`)
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
