* auth_with_role_name add region_name arg for cross-account sts
* update tests to include case with aws_region_name for _auth_with_aws_role
* Only pass region_name to STS client when aws_region_name is set
* Add optional aws_sts_endpoint to _auth_with_aws_role
* Parametrize ambient-credentials test for no opts, region_name, and aws_sts_endpoint
* consistently passing region and endpoint args into explicit credentials irsa
* fix env var leakage
* fix: bedrock openai-compatible imported-model should also have model arn encoded
* fix: team assignment fails for keys with special model names (#21880)
---------
Co-authored-by: An Tang <ta@stripe.com>
Co-authored-by: Sameer Kankute <sameer@berri.ai>
* auth_with_role_name add region_name arg for cross-account sts
* update tests to include case with aws_region_name for _auth_with_aws_role
* Only pass region_name to STS client when aws_region_name is set
* Add optional aws_sts_endpoint to _auth_with_aws_role
* Parametrize ambient-credentials test for no opts, region_name, and aws_sts_endpoint
* consistently passing region and endpoint args into explicit credentials irsa
* fix env var leakage
* fix: bedrock openai-compatible imported-model should also have model arn encoded
* fix: custom pricing not applied for /v1/videos endpoint (#21907)
* fix: resolve mypy type errors for video pricing model_info parameter
Use Optional[ModelInfo] instead of Optional[dict] and restructure
cost_info narrowing so mypy can properly track non-None state.
---------
Co-authored-by: An Tang <ta@stripe.com>
Co-authored-by: Sameer Kankute <sameer@berri.ai>
- Rename "Agentic Research API" to "Agent API"
Expand
- supported Responses API parameters
- Fix function
tool handling to pass custom function tools through unchanged instead of heuristically mapping them.
-Update model registry with current Perplexity
models and presets
- Add Function Calling and Structured Outputs documentation sections.
- Unit tests for transformation logic.
- Wrap onboarding page with QueryClientProvider to prevent runtime crash
(mirrors the same pattern used in LoginPage)
- Stage deletion of stale litellm/ui/litellm-dashboard/src/app/onboarding/page.tsx
committed at the wrong path
- Rename all 16 test names to start with "should" per AGENTS.md convention
* feat(realtime): add guardrail hook for voice transcription in Realtime API
Adds a new `realtime_input_transcription` guardrail event hook that fires
after Whisper transcription completes, before the LLM generates a response.
When a guardrail blocks, a synthetic warning is sent to the client and
`response.create` is never forwarded — the LLM never responds.
Also rewrites `create_response: true` → `false` in client `session.update`
so the proxy controls when responses are triggered.
* feat(realtime): speak guardrail block message as audio via TTS
Instead of sending synthetic text events when a guardrail blocks,
send response.create with forced instructions so OpenAI's TTS speaks
the warning message — user hears the block instead of just seeing text.
* fix(realtime): speak exact content filter error message via TTS
Extract the human-readable error string from HTTPException.detail
so the spoken warning says e.g. "Content blocked: keyword 'system update'
detected" instead of the raw str(e) repr.
* fix(realtime): reliably enforce create_response=false for guardrails
- Proxy now injects session.update with create_response=false immediately
on session.created (when guardrails are active), instead of rewriting
the client's session.update — works regardless of what the client sends
- Add response.cancel before the warning response.create to kill any
in-flight LLM response that snuck through before the guardrail fired
* refactor(realtime): call apply_guardrail directly, remove dedicated hook method
The async_realtime_input_transcription_hook in CustomGuardrail and
ContentFilterGuardrail was just a thin wrapper that called apply_guardrail —
the same interface used by /chat and /messages. Remove the wrapper and call
apply_guardrail directly from run_realtime_guardrails, keeping the pattern
consistent across all endpoints.
* docs: add Realtime API guardrails tutorial and flow diagram
* fix: address Greptile review comments
- Forward user_api_key_dict through realtime_api/main.py (_arealtime) so
it actually reaches RealTimeStreaming instead of always being None
- Run guardrail interception in provider_config path too (e.g. Gemini),
not only the OpenAI direct path
- Narrow exception catch to HTTPException/ValueError only; re-raise
unexpected errors so programming bugs surface in logs rather than
silently appearing as guardrail blocks
- Update tests: mock apply_guardrail directly (hook method was removed),
replace session.update client-rewrite test with session.created
injection test matching the new server-side approach
* fix: address latest Greptile review comments
- Remove fastapi import from SDK-layer file; check for status_code/detail
attrs instead to identify guardrail-block exceptions vs programming errors
- Add store_message() before continue in transcription interception so
transcription events are logged in the non-provider_config path
- Inject create_response=false on session.created in provider_config path
(Gemini etc.) to match the OpenAI path — prevents LLM auto-responding
before guardrail runs on VAD-detected turns
Adds YAML topic category files for military_status, disability, age_discrimination,
religion, and gender_sexual_orientation to block employment discrimination prompts
like "Do not hire veterans because they may have mental health issues."
Previously these were not blocked because:
- The prebuilt regex patterns used strict \b word boundaries that didn't match
plurals (veterans, disabilities, Muslims)
- gender_sexual_orientation pattern was LGBTQ+-focused and missed women/female
- age_discrimination pattern missed "over 50" phrasing
- No conditional (identifier + discriminatory intent) detection existed for these
protected classes
Each new YAML file uses the bias_racial.yaml pattern: identifier_words (protected
class terms) + additional_block_words (discriminatory employment actions), plus
always_block_keywords for explicit discriminatory phrases. Exceptions prevent false
positives for legitimate diversity programs, accommodation discussions, etc.
Also fixes regex plurals in patterns.json: veterans?, disabilit(y|ies), muslims?,
adds wom[ae]n?/females? to gender pattern, and over\s+\d+ to age pattern.
Evals: 100% precision/recall/F1/accuracy on all 5 new categories (89 total cases,
0 FP, 0 FN). Existing insults and investment evals unaffected.
