* feat(vertex_ai): add Vertex AI Gemini Live support via unified /realtime endpoint
Adds VertexAIRealtimeConfig which translates the OpenAI Realtime WebSocket
protocol to Vertex AI BidiGenerateContent. Supports voice in/voice out
(16 kHz mic → 24 kHz speaker) and text in/text out through the proxy's
/realtime endpoint.
Key changes:
- New litellm/llms/vertex_ai/realtime/transformation.py with VertexAIRealtimeConfig
- Builds correct wss:// URL (regional + global)
- OAuth2 Bearer token auth (not API key)
- Full model path (projects/.../publishers/google/models/...)
- Ignores session.update (Vertex AI only accepts one setup message)
- realtime_api/main.py: vertex_ai branch resolves OAuth token + constructs config
- llm_http_handler.py: auto-sends session setup before bidirectional_forward
- gemini/realtime/transformation.py: fix crashes on empty turnComplete events
- realtime_streaming.py: try/except guard so bad messages don't kill the loop
- proxy_server.py: add missing websockets.exceptions import
* docs: add vertex_realtime to sidebars
* fix: drop unknown event types in Gemini transform; add vertex_ai health check
* fix: propagate UUID fallback IDs from transform_content_done_event to return_additional_content_done_events
* fix: route guardrail backend sends through provider transform; fix str.strip misuse for model prefix
* fix: handle Vertex AI full resource path in session.created; route guardrail block sends through _send_to_backend
* fix: remove unused VertexBase in transformation.py; apply UUID fallback in return_additional_content_done_events
Adds a new block_code_execution guardrail that detects markdown fenced code blocks
in request/response content and blocks or masks them by language. Includes full
UI integration, type definitions, compliance test dataset, and 26 unit tests.
Key guardrail capabilities:
- Regex-based fenced code block detection with configurable blocked languages
- Confidence scoring with tunable threshold
- Execution-intent heuristics (request-side only) with conflict resolution
- Block or mask actions for detected code
- Support for pre_call, post_call, and during_call event hooks
Security hardening:
- Response-side blocking skips intent heuristics (LLM output doesn't contain
user intent phrases, so checking would silently disable post_call blocking)
- No-execution short-circuit includes conflict resolution: if both no-execution
and execution phrases match, execution intent wins
- Tightened overly broad phrases to prevent trivial bypass
- _normalize_escaped_newlines only applies to pure-escaped payloads to avoid
corrupting content that discusses escape sequences
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
* feat(realtime): add guardrails query param to /v1/realtime WebSocket endpoint
- Add 'guardrails' query param (comma-separated) to realtime_websocket_endpoint
- Import websockets and websockets.exceptions at module level (fixes NameError in except clause)
- Split try/except into Phase 1 (pre-call) and Phase 2 (routing) so guardrail
errors send back a typed error event before closing, while upstream errors
close silently with 1011
* feat(ui): pass selectedGuardrails from sidebar to RealtimePlayground WebSocket URL
* docs(realtime): add guardrails section with dynamic passing examples
* Add claims agent guardrails with 243-case eval dataset
5 new category guardrails for healthcare claims agent chatbots:
- claims_fraud_coaching: fraud coaching, exaggeration, document forgery
- claims_phi_disclosure: unauthorized PHI access, bulk data extraction
- claims_prior_auth_gaming: code manipulation, medical necessity misrepresentation
- claims_system_override: system injection, rule bypass, role impersonation
- claims_medical_advice: medical advice (claims-context-aware)
Plus claims_agent_safety.yaml policy template combining all 5.
All 5 eval suites pass at 100% precision/recall/F1 (243 test cases).
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* Add claims agent chatbot safety policy template
Combines the 5 claims guardrails into a single deployable policy template:
fraud coaching, PHI disclosure, prior-auth gaming, system override, and medical advice.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* Add guardrail benchmark results and UI compliance prompts
Adds benchmark results for claims, discrimination, and content filter guardrails.
Updates UI compliance prompt data.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* Remove duplicate "file an appeal" exception in claims_prior_auth_gaming.yaml
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* Remove unused claims_agent_safety.yaml policy template
The claims-agent-safety template in policy_templates.json references
individual category files in categories/, not this combined file.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
2026-02-25 18:09:38 -08:00
Steve GGitHubSteveCursorgreptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com>
* Add post-call hook for Lakera guardrail and mask PII in responses
* Add post-call hook for Lakera and mask PII in responses
* Fix post-call hook: pass event_type to call_v2_guard
* Address Greptile review: return ModelResponse, fix mutation, add header, test location, mask order
- PII masking path: return ModelResponse instead of dict so deployment hook accepts it
- Avoid mutating request data: deep copy original_messages and messages in _mask_pii_in_messages
- Add guardrail header in PII-only return path
- Add test in tests/test_litellm/ (test_lakera_ai_v2.py) per PR checklist
- Sort PII payload spans by (start,end) descending so multiple spans in one message mask correctly
Co-authored-by: Cursor <cursoragent@cursor.com>
* Updated ponteital for index mismatch when choices have null content and inconsistent on_flagged access pattern
* Update litellm/proxy/guardrails/guardrail_hooks/lakera_ai_v2.py
Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com>
* Update to explicitly state supported endpoints - chat completions
* Fix minor lint error on masked_entity_count
---------
Co-authored-by: Steve <steve.giguere@lakera.ai>
Co-authored-by: Cursor <cursoragent@cursor.com>
Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com>
Add a prominent warning banner to the UI dashboard when detailed debug
mode (LITELLM_LOG=DEBUG) is enabled. This alerts users to significant
performance degradation caused by extensive diagnostic logging.
Backend changes:
- Enhanced /health/readiness endpoint to include log_level and
is_detailed_debug fields
- Added detection using verbose_logger.getEffectiveLevel()
- Backward compatible - old clients ignore new fields
Frontend changes:
- Updated useHealthReadiness TypeScript interface
- Created DebugWarningBanner component using Ant Design Alert
- Integrated banner into dashboard layout below navbar
- Banner only shows when DEBUG level is active
- Non-dismissible to ensure users are aware of performance impact
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
Backend - Spend Log Storage for Realtime Calls:
- Collect user voice transcripts and text input during WebSocket sessions
- Store collected messages in spend logs when store_prompts_in_spend_logs enabled
- Capture tool definitions from session.update and tool calls from response.done
- Enrich proxy_server_request with tools and response with tool_calls for UI
Backend - WebSocket Auth:
- Support browser-based auth via Sec-WebSocket-Protocol subprotocol
- Echo back subprotocol on WebSocket accept
UI - Realtime Playground:
- New RealtimePlayground component with WebSocket voice+text chat
- Mic recording (PCM16 24kHz), server VAD, audio playback, text input
- Handle binary WebSocket frames (Blob/ArrayBuffer decoding)
- Add /v1/realtime endpoint option to playground endpoint selector
UI - Tools Section for Realtime Logs:
- Extract tool calls from realtime response format (response.tool_calls
and response.results[].response.output[].type=function_call)
Tests:
- 15 new backend tests for realtime streaming and spend log storage
- 4 new UI tests for realtime tool call extraction
Fixes pre-existing build errors:
- ToolPolicies.tsx: duplicate import, antd styles type
- create_key_button.tsx: missing message import
Co-authored-by: Cursor Agent <cursoragent@cursor.com>
Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com>
* docs: document x-litellm-tags header and request body tags parameter
- Add documentation for x-litellm-tags header (comma-separated or array)
- Add documentation for tags in request body
- Clarify that dynamic tags override config tags
Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com>
* docs: consolidate tag documentation and improve cross-references
- Make request_tags.md the single source of truth for all tag options
- Add cross-reference from cost_tracking.md to request_tags.md
- Document both direct tags and metadata.tags formats
- Add key/team tag setup and custom header tracking to request_tags.md
- Reduce duplication and make navigation clearer
Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com>
* docs: use generic examples instead of specific company names
Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com>
* docs: clarify x-litellm-tags header format is comma-separated string
HTTP headers are always strings, not arrays. Remove misleading
array format documentation for the header parameter.
Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com>
* Update docs/my-website/docs/proxy/request_tags.md
Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com>
---------
Co-authored-by: Cursor Agent <cursoragent@cursor.com>
Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com>
Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com>
Replace literal Base64-encoded example value in docstring with a
placeholder to prevent GitGuardian/ggshield from flagging it as a
leaked Basic Authentication credential in container scans.
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
Use the backend-provided request_duration_ms field instead of computing
duration client-side from startTime/endTime. Add sort support for the
Duration column, which sends sortBy=request_duration_ms to the API.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
The backend validator and frontend form both enforced auth_value as
required when auth_type is api_key, bearer_token, or basic. Users who
want to provide auth dynamically (via per-request headers or OAuth2
flows) could not skip the field.
- Remove required validation from auth_value in create_mcp_server.tsx
(keep whitespace-only rejection, matching the edit flow)
- Remove validate_credentials_requirements in NewMCPServerRequest
(all downstream code already treats auth_value as optional)
- Add tests for the create MCP server component
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
* feat(proxy): add max_iterations limiter for agent session loops (#22058)
Adds a new proxy hook that enforces a per-session cap on the number of
LLM calls an agentic loop can make. Callers send a session_id with each
request, and the hook counts calls per session, returning 429 when the
configured max_iterations limit is exceeded.
- Uses Redis Lua script for atomic increment (multi-instance safe)
- Falls back to in-memory cache when Redis unavailable
- Follows parallel_request_limiter_v3 pattern
- Configurable via key metadata: {"max_iterations": 25}
- Session counters auto-expire via TTL (default 1hr)
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
* feat: add new code execution dataset
* feat(agent_endpoints/): allow giving agents keys
* fix: ui fixes
* feat: allow assigning mcp servers to agents
* fix: eliminate duplicate DB queries in MCP agent auth and N+1 in agent listing (#22110)
- Extract _get_agent_object_permission helper so _get_allowed_mcp_servers_for_agent
and _get_agent_tool_permissions_for_server share a single DB fetch instead of
each independently querying the same agent row (was 1+N queries per MCP request)
- Use include={"object_permission": True} on find_many in get_all_agents_from_db
to eagerly load permissions in one query instead of N+1
- Use include={"object_permission": True} on create/update/find_unique in all
agent CRUD operations, removing attach_object_permission_to_dict follow-up calls
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
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Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
Add new document explaining automatic credential usage tracking and tagging. When models use reusable credentials, LiteLLM automatically injects a Credential: <name> tag on requests, enabling credential-level spend tracking on the Usage page with no additional configuration.
Co-Authored-By: Claude Haiku 4.5 <noreply@anthropic.com>
Sameer Kankute