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 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
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
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
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
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
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
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
* feat(realtime guardrails): end_session_after_n_fails + Endpoint Settings wizard step
Adds per-session violation thresholds and an optional endpoint-settings step
to the guardrail wizard for /v1/realtime.
Backend:
- Add end_session_after_n_fails, on_violation, realtime_violation_message fields
to BaseLitellmParams (no DB migration — stored in existing JSON column)
- Store same fields on CustomGuardrail instance attrs
- Pass through in litellm_content_filter initializer
- Track _violation_count per RealTimeStreaming session; close backend_ws when
on_violation=end_session OR violation count >= end_session_after_n_fails
- Use realtime_violation_message as the spoken text (falls back to guardrail
error string if not configured)
UI (add_guardrail_form.tsx):
- Rename "Default Categories" step to "Topics"
- Add step 5 "Endpoint Settings (Optional)" for content filter guardrails
- Call type dropdown shows /v1/realtime
- Settings are in a collapsed accordion (closed by default)
- "End session after X violations" + on_violation radio + spoken message field
Tests: 2 new tests in test_realtime_streaming.py
- test_end_session_after_n_fails_closes_connection
- test_on_violation_end_session_closes_on_first_fail
* fix(test): move inline imports to module level in realtime streaming tests
* Update ui/litellm-dashboard/src/components/guardrails/add_guardrail_form.tsx
Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com>
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Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com>
* fix(realtime): guardrails with pre_call/post_call mode now work on realtime WebSocket; return error directly to consumer
* fix(realtime guardrails): address code review feedback
- Restore session.update injection for audio/VAD path, but only when
realtime_input_transcription guardrails are configured (not pre_call).
Forward session.created to the client first so no error arrives before
the client sees the session.
- Change _swallow_next_response_create bool to int counter so consecutive
blocked items are handled correctly.
- Extract _build_litellm_metadata() helper to eliminate duplicated
metadata-building logic across OpenAI/Azure/XAI provider branches.
- Plumb litellm_metadata and user_api_key_dict to Azure and XAI handlers
so guardrails work for those providers too.
- Add tests for session.update injection, no-inject for pre_call-only,
and consecutive-block counter.
* simplify: remove response.create swallowing after guardrail block
When an item is blocked, the error event is already sent to the client.
The subsequent response.create from the client is fine to forward through —
the LLM may respond to previous context which is acceptable behavior.
Removing the swallow counter eliminates unnecessary state tracking.
* feat: add pretty view for realtime API logs in dashboard
- Create RealtimePrettyView component that renders structured session
config, conversation turns with transcripts, and token breakdowns
- Update PrettyMessagesView to detect realtime responses (via
isRealtimeResponse helper) and delegate to the new component
- Session card shows model, voice, modalities, temperature, instructions
in a collapsible panel
- Conversation turns show status, per-turn token usage, and audio/text
transcripts with appropriate icons
- Add 24 tests for RealtimePrettyView and 3 tests for PrettyMessagesView
- All 75 LogDetailsDrawer tests pass
Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com>
* chore: remove dev_config.yaml from tracked files
Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com>
* feat: show turn count in realtime pretty view session header and output header
- Add purple 'N turns' tag to Session card header for at-a-glance turn count
- Add 'Turns: N' to the Output section header next to tokens/cost
- Extend SectionHeader to accept optional turnCount prop
- Add 3 new tests for turn count display (singular, plural, output header)
Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com>
* fix: address Greptile review feedback
- Remove response.audio.done and conversation.item.created from
isRealtimeResponse() detection since the view doesn't render them;
prevents misleading fallback for responses with only those events
- Remove dead code: index >= 0 is always true in .map() callback
Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com>
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Co-authored-by: Cursor Agent <cursoragent@cursor.com>
Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com>
* 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>
* 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>
