* 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.
video_remix_handler and async_video_remix_handler were not falling back
to litellm_params.api_key when the api_key parameter was None, causing
Authorization: Bearer None to be sent to the provider. This matches the
pattern already used by async_video_generation_handler.
Remove the Claude Code-powered duplicate PR detection workflow and revert
the duplicate issue checker back to wow-actions/potential-duplicates with
text similarity matching.
openai videos models support the features to download variants.
See more details here: https://developers.openai.com/api/docs/guides/video-generation#use-image-references.
Plumb variant (e.g. "thumbnail", "spritesheet") through the full
video content download chain: avideo_content → video_content →
video_content_handler → transform_video_content_request. OpenAI
appends ?variant=<value> to the GET URL; other providers accept
the parameter in their signature but ignore it.
* Add OpenAI Agents SDK tutorial to docs
* Update OpenAI Agents SDK tutorial to use LiteLLM environment variables
* Enhance OpenAI Agents SDK tutorial with built-in LiteLLM extension details and updated configuration steps. Adjust section headings for clarity and improve the flow of information regarding model setup and usage.
Concurrent requests via run_in_executor + asyncio.gather caused a race
condition where more requests slipped through the rate limiter than
expected, leading to flaky test failures (e.g. 3 successes instead of 2
with rpm_limit=2).
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Google added INCOMPLETE to the Interactions API OpenAPI spec status enum.
Update both the Status3 enum in the SDK types and the test's expected
values to match.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
