- Add Nebius LLM service wrapping OpenAI-compatible Token Factory API
- Set supports_developer_role = False (Nebius rejects developer role)
- Default to openai/gpt-oss-120b model (supports function calling)
- Add Nebius function-calling example and env.example entry
- Fix Sarvam developer role support
- Update examples to use developer role for intro messages
Adds an OpenAI-compatible LLM service for Nebius Token Factory, supporting
open-source models (Meta Llama, Qwen, DeepSeek) via their OpenAI-compatible
REST API at https://api.tokenfactory.nebius.com/v1/.
When the remote side disconnects while send() is in flight, send() was
setting _closing=True. This prevented the receive loop from firing
on_client_disconnected, causing the pipeline to hang waiting for a
disconnect signal that never came.
The fix removes _closing from send() (that flag means we initiated the
close) and instead checks Starlette application_state in _can_send()
to suppress subsequent sends after a failure.
Fixes#3912
Add `await asyncio.sleep(0)` after `create_task()` calls in
UserIdleController, SpeechTimeoutUserTurnStopStrategy,
TurnAnalyzerUserTurnStopStrategy, and UserTurnCompletionLLMServiceMixin
so the event loop schedules the newly created timer tasks before the
caller continues.
The base serializer filters out RTVI protocol messages by default
(ignore_rtvi_messages=True) to prevent them from being sent over
telephony media streams. ProtobufFrameSerializer is used by WebSocket
transports, which are the delivery channel for these messages, so
disable the filter there.
All recent Gemini Live models (including the default
gemini-2.5-flash-native-audio-preview-12-2025, and going at least as
far back as gemini-2.5-flash-native-audio-preview-09-2025) only
support AUDIO as a response modality. We considered using
`modalities=TEXT` as a Pipecat-level signal to suppress audio output
frames (so developers could pair Gemini Live with an external TTS),
but the output transcription from the API arrives too late relative
to the audio to be useful for driving an external TTS service.
For now, just log a warning when a TEXT modality is configured
(at init or via set_model_modalities) and proceed as normal. The 26d
text-modality example is removed since it no longer represents a
viable configuration.
The heartbeat monitor timeout (`HEARTBEAT_MONITOR_SECS`) was a static
module-level constant that never derived from the user-configurable
`heartbeats_period_secs`. This meant overriding the heartbeat interval
had no effect on the monitor window, causing spurious warnings or
delayed detection depending on the configured interval.
Add a new `heartbeats_monitor_secs` parameter to `PipelineParams` so
the monitor timeout is independently configurable (defaults to 10s).
The monitor handler now reads from the instance param instead of the
hard-coded constant.
Made-with: Cursor
This fixes the 26c example when using Gemini 3.1 Flash Live, which seems to be more strict about not receiving real-time input (at least, video messages) before conversation history.
Rime's WebSocket API sends a done message when synthesis completes.
Handle it to stop TTFB metrics, push TTSStoppedFrame, and remove the
audio context immediately instead of relying on the 3-second
stop_frame_timeout_s fallback.
DailyCallbacks gained a required on_dtmf_event field in PR #4047.
PR #4079 fixed this for TavusTransportClient but
LemonSliceTransportClient.setup() was not updated, causing a pydantic
ValidationError at pipeline setup time.
Only trigger handle_error for ErrorFrames originating from the active
service, not any managed service. This prevents edge cases where errors
from a non-active service could incorrectly trigger failover.
Expose a public method for retrieving all stored memories outside the
pipeline, avoiding the need for callers to reimplement client branching,
OR filter construction, and asyncio.to_thread wrapping. Simplify the
example get_initial_greeting() to use it.
Move blocking Mem0 API calls off the event loop using asyncio.to_thread().
Store messages as a fire-and-forget background task via create_task() since
the result is not needed. Insert memory messages at the configured position
in the context instead of always appending.
Closes#1741
