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133 Commits

Author SHA1 Message Date
Mark Backman
35c7f13fed Add changelog for #3751 2026-02-14 17:34:46 -05:00
Mark Backman
8d5d8219da Fix RTVIObserver missing transcriptions from Realtime LLMs
Realtime LLMs (OpenAI Realtime, Gemini Live) push TranscriptionFrame
and InterimTranscriptionFrame upstream only, but the RTVIObserver
filtered to downstream-only frames. Allow transcription frames
regardless of direction so user transcriptions are reported to
RTVI clients in all pipeline configurations.
2026-02-14 17:26:38 -05:00
Mark Backman
c682a44bb6 Merge pull request #3738 from lukepayyapilli/fix/mute-events-before-start-frame
Fix LLMUserAggregator broadcasting mute events before StartFrame
2026-02-14 09:40:40 -05:00
Filipi da Silva Fuchter
f6bb5fa124 Merge pull request #3741 from pipecat-ai/filipi/update_prebuilt
Using the latest version of pipecat-ai-small-webrtc-prebuilt.
2026-02-13 15:31:48 -05:00
filipi87
2489c76bc6 Using the latest version of pipecat-ai-small-webrtc-prebuilt. 2026-02-13 16:43:25 -03:00
Mark Backman
73cb96bf66 Merge pull request #3739 from pipecat-ai/mb/docs-skill
Add /update-docs Claude Code skill
2026-02-13 13:26:06 -05:00
Mark Backman
79ec61d1d8 Merge pull request #3642 from pipecat-ai/cb/rime-arcana-v3
Update RimeTTSService for arcana and mistv2 model support
2026-02-13 13:25:27 -05:00
Mark Backman
ca440594fe Merge pull request #3720 from pipecat-ai/mb/fix-grok-realtime
Fix Grok Realtime voice type validation for server responses
2026-02-13 13:24:53 -05:00
Mark Backman
6c25dd4aa2 Merge pull request #3736 from pipecat-ai/mb/improve-events-docstrings
Improve events docstrings
2026-02-13 13:24:15 -05:00
Mark Backman
09bb6bb03b Merge pull request #3735 from pipecat-ai/mb/fix-llm-tracing-error-handilng
Fix double execution of service functions on tracing errors
2026-02-13 13:23:55 -05:00
Mark Backman
746fdfbfef Merge pull request #3728 from pipecat-ai/mb/upgrade-pillow
Bump Pillow upper bound from <12 to <13
2026-02-13 13:23:41 -05:00
Mark Backman
f7af9f1efd Broaden /update-docs scope to detect missing doc sections 2026-02-13 13:14:45 -05:00
Mark Backman
a5f95acaf5 Add changelog for PR #3735 2026-02-13 13:08:03 -05:00
Mark Backman
e50b138ab2 Fix double execution of service functions when tracing errors occur
The outer try/except in each service decorator caught both tracing
setup errors and application errors from the wrapped function. If the
function itself raised (e.g. LLM rate limit, TTS timeout), the
exception was caught and the function was called a second time.

Fix by tracking whether the original function was called via a
fn_called flag. If the function was already called, re-raise the
exception instead of falling back to untraced re-execution.
2026-02-13 13:08:03 -05:00
Mark Backman
3640c7a2dd Merge pull request #3733 from pipecat-ai/mb/fix-traceable-init
Deprecate unused class_decorators tracing module and fix stale comments
2026-02-13 13:04:34 -05:00
Mark Backman
2454bedf29 Add /update-docs skill for keeping docs in sync with source changes
Adds a Claude Code skill that analyzes the current branch diff against
main, maps changed source files to their doc pages, and makes targeted
updates to Configuration, InputParams, Usage, Notes, and Event Handlers
sections.
2026-02-13 12:52:23 -05:00
Luke Payyapilli
3adb2f50a6 Fix LLMUserAggregator broadcasting mute events before StartFrame 2026-02-13 11:59:56 -05:00
Mark Backman
01b7a93e08 Deprecate unused Traceable/class_decorators module and fix stale comments
The class_decorators.py module (Traceable, @traceable, @traced) is not
used anywhere in the codebase. Mark it deprecated and fix the misleading
comment in service_decorators.py that referenced it as if it were active.
2026-02-13 11:25:40 -05:00
Mark Backman
347eaf582d Merge pull request #3721 from pipecat-ai/fix/pipeline-scoped-tracing-context
Replace singleton context providers with pipeline-scoped TracingContext
2026-02-13 11:24:37 -05:00
Mark Backman
25ca296477 Move tracing fields to AIService and extract _get_turn_context helper
Consolidate _tracing_enabled and _tracing_context from LLMService,
STTService, and TTSService into the shared AIService base class.
Extract _get_turn_context() helper in service_decorators.py to
encapsulate the repeated pattern across all traced decorators.
2026-02-13 11:21:24 -05:00
Mark Backman
3fce88555f Improve events docstrings 2026-02-13 09:39:44 -05:00
Mark Backman
9e6f27c9f1 Merge pull request #3625 from ianbbqzy/ian/inworld-async-timestamp
[inworld] Allow Async delivery of timestamps info
2026-02-12 21:20:22 -05:00
Ian Lee
94f01af545 [inworld] Allow Async delivery of timestamps info
* speed up first audio chunk latency
2026-02-12 17:48:58 -08:00
Filipi da Silva Fuchter
432870cc36 Merge pull request #3729 from pipecat-ai/filipi/elevenlabs_issue
TTS services fixes.
2026-02-12 16:31:46 -05:00
Filipi da Silva Fuchter
e065907745 Merge pull request #3718 from pipecat-ai/filipi/bot_started_speaking
Fixing an issue in RTVI where we were sometimes receiving bot output messages before the bot started speaking.
2026-02-12 16:31:14 -05:00
Mark Backman
b7a5ca3d1e Merge pull request #3730 from pipecat-ai/mb/stt-keepalive
Move STT keepalive from WebsocketSTTService to STTService base class
2026-02-12 15:37:23 -05:00
filipi87
9569625f03 Changelog entries for the TTS fixes. 2026-02-12 16:11:02 -03:00
Mark Backman
18afe37bd1 Add changelog entries for PR #3642 2026-02-12 14:09:24 -05:00
Mark Backman
2b9777b812 Update RimeTTSService InputParams for arcana and mistv2 model support
Add model-specific params (arcana: repetition_penalty, temperature, top_p;
mistv2: no_text_normalization, save_oovs, segment) with dynamic query param
building via _build_settings(). Model/voice/param changes now trigger
WebSocket reconnection since all settings are URL query params.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-02-12 14:01:41 -05:00
filipi87
8866ab1585 Fixing RimeTTSService to reuse the same context when needed. 2026-02-12 15:53:38 -03:00
filipi87
f0995164d9 Fixing PlayHTTTSService to reuse the same context when needed. 2026-02-12 15:50:18 -03:00
filipi87
136732afae Fixing InworldTTSService to reuse the same context when needed. 2026-02-12 15:46:59 -03:00
filipi87
3410eb82b3 Fixing CartesiaTTSService to reuse the same context when needed. 2026-02-12 15:26:49 -03:00
Chad Bailey
794811fbdb Updated WSS endpoint for Rime Arcana v3 support 2026-02-12 13:24:29 -05:00
filipi87
abea22ec57 Fixing AsyncAITTSService to reuse the same context when needed. 2026-02-12 15:17:47 -03:00
Mark Backman
08beb0264a Add changelog entries for PR #3730 2026-02-12 13:14:11 -05:00
Mark Backman
2e15b4842c Move STT keepalive mechanism from WebsocketSTTService to STTService base class
This allows non-websocket STT services (like SarvamSTTService, which uses
the Sarvam Python SDK for connection management) to reuse the same keepalive
pattern. Subclasses override _send_keepalive() and _is_keepalive_ready() for
their specific protocol.
2026-02-12 11:09:39 -05:00
filipi87
6d95a2425c Fixing ElevenLabs TTS word timestamp interleaving across sentences. 2026-02-12 12:54:47 -03:00
Mark Backman
4667a3d66d Add changelog for #3728 2026-02-12 09:42:23 -05:00
Mark Backman
0bf2477d2c Bump Pillow upper bound from <12 to <13 2026-02-12 09:41:18 -05:00
Mark Backman
71a752c971 Add tests for TracingContext and TurnTraceObserver
Cover pipeline-scoped tracing context lifecycle, span hierarchy,
conversation/turn context management, and concurrent pipeline isolation.
2026-02-11 23:27:35 -05:00
Mark Backman
358f237507 Replace singleton context providers with pipeline-scoped TracingContext
ConversationContextProvider and TurnContextProvider were singletons that
stored tracing context as class-level state. When two PipelineTask instances
ran concurrently, they would overwrite each other's context, causing service
spans to attach to the wrong pipeline's turn span.

Replace both singletons with a single TracingContext object owned by each
PipelineTask, threaded to services via StartFrame.
2026-02-11 21:58:10 -05:00
Mark Backman
d99a256715 Merge pull request #3706 from ianbbqzy/ian/inworld-user-agent
[Inworld] add User-Agent and X-Request-Id for better traceability
2026-02-11 19:38:26 -05:00
Ian Lee
dcbcab1542 [Inworld] add User-Agent and X-Request-Id for better traceability 2026-02-11 15:47:20 -08:00
Mark Backman
a966947220 Add changelog for #3720 2026-02-11 18:04:58 -05:00
Mark Backman
16b060d9e9 Fix Grok Realtime voice type validation for server responses
The Grok API now returns prefixed voice names (e.g. "human_Ara") in
session.updated events, causing Pydantic validation errors. Widen the
voice field type from GrokVoice to GrokVoice | str to accept both
user-facing names and server-returned values.
2026-02-11 18:04:20 -05:00
filipi87
ed7fde324e Adding changelog entry for the RTVIObserver fix. 2026-02-11 16:23:42 -03:00
filipi87
beb4e86b5f Fixing an issue in RTVI where we were sometimes receiving bot output messages before the bot started speaking. 2026-02-11 16:17:28 -03:00
Aleix Conchillo Flaqué
e75ccd9c2f Merge pull request #3717 from pipecat-ai/aleix/update-claude-md-pr-instructions
Add /pr-submit skill and clean up CLAUDE.md
2026-02-11 10:40:20 -08:00
Aleix Conchillo Flaqué
a80919ceff Move PR submission instructions from CLAUDE.md to /pr-submit skill
Extract the procedural PR workflow into an actionable skill that can be
invoked with /pr-submit. CLAUDE.md is better suited for project context
and conventions, not step-by-step procedures.
2026-02-11 09:57:42 -08:00
Aleix Conchillo Flaqué
1fe4538982 Update PR submission instructions in CLAUDE.md
Expand the Pull Requests section with detailed step-by-step instructions
including branch naming, commit guidance, changelog generation, and PR
description updates.
2026-02-11 09:51:10 -08:00
Filipi da Silva Fuchter
9a48d93bd2 Merge pull request #3713 from pipecat-ai/filipi/smallwebrtc_8khz
Fixing smallwebrtc transport input audio resampling logic.
2026-02-11 11:58:32 -05:00
filipi87
0c3e59ed61 Adding changelog entry for the SmallWebRTCTransport fix. 2026-02-11 13:07:52 -03:00
filipi87
ec2b38dc29 Fixing smallwebrtc transport input audio resampling logic. 2026-02-11 13:01:25 -03:00
Mark Backman
0574167fbd Merge pull request #3709 from pipecat-ai/mb/fix-quickstart-pcc-deploy
Fix quickstart pcc-deploy.toml
2026-02-10 22:19:37 -05:00
Mark Backman
972ad93e18 Fix quickstart pcc-deploy.toml 2026-02-10 22:17:09 -05:00
Mark Backman
ac53594967 Merge pull request #3708 from pipecat-ai/mb/fix-quickstart-pyproject
Fix quickstart pyproject.toml
2026-02-10 22:09:49 -05:00
Mark Backman
b063d9d43b Fix quickstart pyproject.toml 2026-02-10 22:06:38 -05:00
Mark Backman
48e93beadf Merge pull request #3705 from pipecat-ai/mb/quickstart-0.0.102
Update quickstart for 0.0.102
2026-02-10 21:57:33 -05:00
Aleix Conchillo Flaqué
640940a41a Merge pull request #3704 from pipecat-ai/changelog-0.0.102
Release 0.0.102 - Changelog Update
2026-02-10 18:31:30 -08:00
aconchillo
f1e2001a4e Update changelog for version 0.0.102 2026-02-10 18:28:21 -08:00
Aleix Conchillo Flaqué
12dc6c0b9e Merge pull request #3707 from pipecat-ai/aleix/fix-openai-stream-close-compat
fix(openai): use compatible stream closing for non-OpenAI providers
2026-02-10 18:26:18 -08:00
Aleix Conchillo Flaqué
93f4402198 Update stream close test to match new _closing helper 2026-02-10 18:19:57 -08:00
Aleix Conchillo Flaqué
f3eb5b30a0 Add changelog for #3707 2026-02-10 18:01:29 -08:00
Aleix Conchillo Flaqué
18aad05a7c fix(openai): use compatible stream closing for non-OpenAI providers
OpenAI's AsyncStream uses close() while async generators (e.g. from
OpenPipe) use aclose(). Replace direct async-with on the stream with a
helper that handles both protocols.
2026-02-10 17:59:21 -08:00
Mark Backman
883b24f577 Update quickstart for 0.0.102 2026-02-10 18:14:04 -05:00
Mark Backman
17ab9c425f Merge pull request #3675 from pipecat-ai/mb/elevenlabs-realtime-send-silence
Add silence-based keepalive to WebsocketSTTService
2026-02-10 18:03:38 -05:00
Mark Backman
2f5e61ac55 Add silence-based keepalive to WebsocketSTTService
Adds opt-in keepalive_timeout and keepalive_interval params to
WebsocketSTTService. When enabled, a background task sends silent audio
(or a service-specific protocol message) when the connection has been
idle, preventing server-side timeout disconnects.

Subclasses override _send_keepalive(silence) to wrap the silence in
their wire format. The default sends raw PCM bytes.

Enables keepalive for ElevenLabs (10s), Gladia (20s), and Soniox (1s),
replacing their per-service custom keepalive tasks.
2026-02-10 17:58:47 -05:00
Aleix Conchillo Flaqué
1128c5b7fb Merge pull request #3702 from pipecat-ai/aleix/add-missing-local-smartturn-dependency
pyproject: add local smartturn as a default dependency
2026-02-10 14:34:43 -08:00
Aleix Conchillo Flaqué
a9a5edd8ca pyproject: add local smartturn as a default dependency 2026-02-10 14:32:32 -08:00
Filipi da Silva Fuchter
a98c884e31 Merge pull request #3621 from pipecat-ai/filipi/context_compressure
Context summarization feature implementation
2026-02-10 17:04:47 -05:00
filipi87
2475697955 Changelog entries for context summarization 2026-02-10 18:59:12 -03:00
filipi87
ba242d4875 Context summarization example with Google 2026-02-10 18:59:03 -03:00
filipi87
5deb80932b Context summarization example with OpenAI 2026-02-10 18:58:55 -03:00
filipi87
4a00e6829f Automated tests for the context summarizer. 2026-02-10 18:58:44 -03:00
filipi87
9d89afa7d4 Automated tests for the context summarization feature. 2026-02-10 18:58:33 -03:00
filipi87
92b6ecd945 New Claude skill to help refactor and cleanup the code. 2026-02-10 18:58:22 -03:00
filipi87
314d074c61 Context summarization feature implementation. 2026-02-10 18:58:12 -03:00
Filipi da Silva Fuchter
9c627e7292 Merge pull request #3653 from pipecat-ai/filipi/heygen_lite
HeyGen improvements.
2026-02-10 12:12:22 -05:00
Filipi da Silva Fuchter
ad179b0852 Merge pull request #3584 from pipecat-ai/filipi/speak_frame
TTS services improvements.
2026-02-10 12:11:47 -05:00
filipi87
5128089d42 Add changelog entries for PR #3653. 2026-02-10 14:02:32 -03:00
filipi87
87a79df048 Updating the heygen examples to use sandbox by default. 2026-02-10 14:02:20 -03:00
filipi87
24f90715e3 Use LITE as the default mode, and add support for video_settings and is_sandbox in LiveAvatarNewSessionRequest. 2026-02-10 14:02:09 -03:00
filipi87
e00b98343e Changelog entries for TTS context tracking 2026-02-10 11:37:21 -03:00
filipi87
ad1bec4583 Updated openai example to use on_tts_request and append_to_text. 2026-02-10 11:28:35 -03:00
filipi87
a47d7f98ee Refactored all 30+ TTS service implementations to support context tracking 2026-02-10 11:28:08 -03:00
filipi87
19cd242261 Added TTS context tracking system to trace audio generation through the pipeline. 2026-02-10 11:27:58 -03:00
filipi87
9bb712a47b Simplified universal context aggregators, _handle_text() to only check frame.append_to_context instead of also checking self._started 2026-02-10 11:27:30 -03:00
filipi87
1dccbe7c0b Simplified context aggregators, _handle_text() to only check frame.append_to_context instead of also checking self._started 2026-02-10 11:27:13 -03:00
Mark Backman
2dd3e2f1e7 Merge pull request #3697 from pipecat-ai/mb/soniox-rt-4
Update SonioxSTTService default model to stt-rt-v4
2026-02-10 09:24:39 -05:00
filipi87
f206aaa28d - Added context_id field to all TTS-related frames (TTSAudioRawFrame, TTSStartedFrame, TTSStoppedFrame, AggregatedTextFrame, TTSTextFrame)
- Added append_to_context parameter to TTSSpeakFrame for conditional LLM context addition
2026-02-10 11:22:26 -03:00
Mark Backman
60e42f5690 Merge pull request #3701 from pipecat-ai/mb/changelog-3700 2026-02-10 09:19:42 -05:00
Mark Backman
88e981c013 Set vad_force_turn_endpoint to False in SonioxSTTService 2026-02-10 09:16:03 -05:00
Mark Backman
7bd8dfe898 Add changelog for PR 3700 2026-02-10 08:20:03 -05:00
Mark Backman
83039a1a35 Merge pull request #3700 from ashotbagh/chore/async-migration
chore: update Async API URL and default model
2026-02-10 08:17:04 -05:00
Ashot
28e8b61eb4 chore: update Async API URL and default model 2026-02-10 15:23:51 +04:00
Mark Backman
d47d95e1f0 Update SonioxSTTService default model to stt-rt-v4 2026-02-09 23:48:08 -05:00
Mark Backman
79b9d929c5 Merge pull request #3682 from eoinoreilly30/patch-1
Add new voice options 'marin' and 'cedar'
2026-02-09 23:47:39 -05:00
Eoin
dfc0856d54 Added changelog entry 2026-02-10 12:31:26 +09:00
Eoin
f3c1cd4cd6 Lint 2026-02-10 12:31:26 +09:00
Eoin
18d91d6df3 Add new voice options 'marin' and 'cedar' 2026-02-10 12:31:26 +09:00
Mark Backman
688f502488 Merge pull request #3644 from pipecat-ai/mb/update-assembly-ai-default-config
AssemblyAISTTService: Disable turn detection when setting vad_force_t…
2026-02-09 22:27:44 -05:00
Mark Backman
7684a94c33 AssemblyAISTTService: Disable turn detection when setting vad_force_turn_endpoint to True 2026-02-09 22:20:35 -05:00
Aleix Conchillo Flaqué
e27f4bccfb Merge pull request #3695 from pipecat-ai/aleix/more-claude-updates
CLAUDE.md: add pipeline task and pipeline runner
2026-02-09 18:14:30 -08:00
Mark Backman
fa8b0aeda8 Merge pull request #3690 from pipecat-ai/mb/add-claude-settings
Add shared Claude Code settings
2026-02-09 19:22:28 -05:00
Aleix Conchillo Flaqué
946f0f4e77 CLAUDE.md: add pipeline task and pipeline runner 2026-02-09 16:19:11 -08:00
Mark Backman
b9cf3f3225 Merge pull request #3694 from pipecat-ai/mb/claude-updates
Add observers, error handling, task management, and testing to CLAUDE.md
2026-02-09 19:05:49 -05:00
Aleix Conchillo Flaqué
d32c4b2f5f Merge pull request #3693 from pipecat-ai/aleix/update-examples-remove-default-turn-analyzer
remove the now default turn analyzer from examples
2026-02-09 16:04:19 -08:00
Mark Backman
77a5d16a10 Merge pull request #3692 from pipecat-ai/mb/request-metadata-updates
Rename RequestMetadataFrame to ServiceSwitcherRequestMetadataFrame with service targeting
2026-02-09 18:19:29 -05:00
Mark Backman
ca224834b2 Add observers, error handling, task management, and testing to CLAUDE.md 2026-02-09 18:12:24 -05:00
Aleix Conchillo Flaqué
3867bc6302 LLMUserAggregator: update turn analyzer warning 2026-02-09 14:33:38 -08:00
Aleix Conchillo Flaqué
83a8379401 examples: remove the now default turn analyzer user turn stop strategy 2026-02-09 14:33:38 -08:00
mattie ruth backman
f2688deb0d Update args field in RTVILLMFunctionCallInProgressMessageData to match API of existing RTVILLMFunctionCallResultData. 2026-02-09 17:17:01 -05:00
Mark Backman
981253c703 Rename RequestMetadataFrame to ServiceSwitcherRequestMetadataFrame with service targeting
Add a `service` field so the frame targets a specific service, allowing
ServiceSwitcher.push_frame to consume it only when the targeted service
matches the active service. STTService and test mocks now push the frame
downstream after handling instead of silently consuming it.
2026-02-09 16:48:34 -05:00
Mark Backman
aa6c9797ca Merge pull request #3671 from pipecat-ai/mb/sarvam-cleanup
Clean up on Sarvam STT and TTS classes
2026-02-09 15:58:34 -05:00
Mark Backman
6305e04569 Clean up on Sarvam STT and TTS classes 2026-02-09 15:53:05 -05:00
Mark Backman
3ff9b7b5ad Merge pull request #3687 from pipecat-ai/mb/rtvi-mute-events
Emit RTVI events for user mute/unmute
2026-02-09 15:18:28 -05:00
Mark Backman
cc797ba3cf Add shared Claude Code settings to disable commit attribution 2026-02-09 15:15:31 -05:00
Aleix Conchillo Flaqué
91c8122c17 Merge pull request #3689 from pipecat-ai/aleix/default-smart-turn-stop-strategy
Use TurnAnalyzerUserTurnStopStrategy as default stop strategy
2026-02-09 12:07:16 -08:00
Aleix Conchillo Flaqué
944ac92593 Fix test_langchain to use explicit stop strategy
The default stop strategy changed to TurnAnalyzerUserTurnStopStrategy,
which requires actual audio analysis. Use SpeechTimeoutUserTurnStopStrategy
explicitly since this test is not testing turn detection.
2026-02-09 12:00:41 -08:00
Aleix Conchillo Flaqué
ca0d2e68c3 Add changelog for #3689 2026-02-09 11:58:09 -08:00
Aleix Conchillo Flaqué
631463e573 Use TurnAnalyzerUserTurnStopStrategy as default stop strategy
Change the default user turn stop strategy from
TranscriptionUserTurnStopStrategy to TurnAnalyzerUserTurnStopStrategy
with LocalSmartTurnAnalyzerV3. Also reduce AUDIO_INPUT_TIMEOUT_SECS
from 1.0 to 0.5 and remove its debug log.
2026-02-09 11:58:09 -08:00
Mark Backman
6a553367a2 Merge pull request #3676 from pipecat-ai/mb/code-review-skill
Add Claude code-review skill
2026-02-09 14:48:20 -05:00
Mark Backman
00ec6c77ea Emit RTVI events for user mute/unmute state changes
Add UserMuteStartedFrame/UserMuteStoppedFrame and corresponding RTVI
messages so clients can observe when mute strategies activate/deactivate.
2026-02-09 14:44:32 -05:00
Mark Backman
ee6520db30 Merge pull request #3637 from pipecat-ai/mb/improve-user-stop-turn
Improve user turn stop timing by triggering timeout from VAD stop, push STT metadata to user aggregator
2026-02-09 14:43:22 -05:00
Aleix Conchillo Flaqué
2a572aedba Simplify ServiceSwitcher with closure-based filters
- Make ServiceSwitcherStrategy inherit from BaseObject with properties
  for services and active_service, and move initial service selection
  into the base class
- Add on_service_switched event to ServiceSwitcherStrategy
- handle_frame now returns the switched-to service (or None), allowing
  ServiceSwitcher to swallow ManuallySwitchServiceFrame on switch and
  request metadata from the new active service
- Override push_frame to suppress RequestMetadataFrame and
  ServiceMetadataFrame from inactive services
- Remove ServiceSwitcherFilter and ServiceSwitcherFilterFrame in favor
  of plain FunctionFilter instances with closures that check the
  strategy's active service directly
- FunctionFilter: add FilterType alias
- FunctionFilter: when direction is None, frames in both directions
  are filtered instead of just one
- Add docstrings to ServiceSwitcher and its components
2026-02-09 14:12:33 -05:00
Mark Backman
5e66702cf5 Improved the accuracy of the UserBotLatencyObserver and UserBotLatencyLogObserver 2026-02-09 14:12:33 -05:00
Mark Backman
34b068d657 Improve user turn stop timing by triggering timeout from VAD stop
Refactor TranscriptionUserTurnStopStrategy and TurnAnalyzerUserTurnStopStrategy
to use VADUserStoppedSpeakingFrame as the ground truth for when speech ended,
rather than triggering timeouts from transcription frames.
2026-02-09 14:12:33 -05:00
Mark Backman
05e2a013b3 Merge pull request #3672 from pipecat-ai/mb/rtvi-duplicate-events
Filter RTVIObserver to downstream frames only and broadcast FunctionCallCancelFrame
2026-02-09 12:58:28 -05:00
Mark Backman
5f64dae0cf Filter RTVIObserver to downstream frames only and broadcast FunctionCallCancelFrame
RTVIObserver now skips upstream frames to prevent duplicate RTVI messages
when frames are broadcast in both directions. Also changed
FunctionCallCancelFrame to use broadcast_frame for consistency with
other function call frames.
2026-02-09 12:39:25 -05:00
Mark Backman
1bf8b54502 Merge pull request #3683 from dhruvladia-sarvam/sarvam-v3-update 2026-02-09 06:49:59 -05:00
dhruvladia-sarvam
947ff03c9f v3 addition 2026-02-09 13:04:45 +05:30
Mark Backman
3494a94cac Add Claude code-review skill 2026-02-08 11:06:48 -05:00
300 changed files with 7566 additions and 2934 deletions

5
.claude/settings.json Normal file
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{
"attribution": {
"commit": ""
}
}

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# Code Cleanup Skill
The **Code Cleanup Skill** reviews, refactors, and documents code changes in your current branch, ensuring alignment with **Pipecats architecture, coding standards, and example patterns**.
It focuses on **readability, correctness, performance, and consistency**, while avoiding breaking changes.
---
## Skill Overview
This skill analyzes all changes introduced in your branch and performs the following actions:
1. **Analyze Branch Changes**
- Review uncommitted changes and outgoing commits
2. **Refactor for Readability**
- Improve clarity, naming, structure, and modern Python usage
3. **Enhance Performance**
- Identify safe, conservative optimization opportunities
4. **Add Documentation**
- Apply Pipecat-style, Google-format docstrings
5. **Ensure Pattern Consistency**
- Match existing Pipecat services, pipelines, and examples
6. **Validate Examples**
- Ensure examples follow foundational patterns (e.g. `07-interruptible.py`)
---
## Usage
Invoke the skill using any of the following commands:
- “Clean up my branch code”
- “Refactor the changes in my branch”
- “Review and improve my branch code”
- `/cleanup`
---
## What This Skill Does
### 1. Analyze Branch Changes
The skill retrieves all uncommitted changes and outgoing commits to understand:
- New files added
- Modified files
- Code additions and deletions
- Overall scope and intent of changes
---
### 2. Code Refactoring
#### Readability Improvements
- Replace tuples with named classes or dataclasses
- Improve variable, method, and class naming
- Extract complex logic into well-named helper methods
- Add missing type hints
- Simplify nested or complex conditionals
- Replace deprecated methods and features
- Normalize formatting to match Pipecat style
#### Performance Enhancements
- Identify inefficient loops or repeated work
- Suggest appropriate data structures
- Optimize async workflows and I/O
- Remove redundant operations
> Performance changes are conservative and non-breaking.
---
### 3. Documentation
Documentation follows **Google-style docstrings**, consistent with Pipecat conventions.
#### Class Documentation
```python
class ExampleService:
"""Brief one-line description.
Detailed explanation of the class purpose, responsibilities,
and important behaviors.
Supported features:
- Feature 1
- Feature 2
- Feature 3
"""
```
#### Method Documentation
```python
def process_data(self, data: str, options: Optional[dict] = None) -> bool:
"""Process incoming data with optional configuration.
Args:
data: The input data to process.
options: Optional configuration dictionary.
Returns:
True if processing succeeded, False otherwise.
Raises:
ValueError: If data is empty or invalid.
"""
```
#### Pydantic Model Parameters
```python
class InputParams(BaseModel):
"""Configuration parameters for the service.
Parameters:
timeout: Request timeout in seconds.
retry_count: Number of retry attempts.
enable_logging: Whether to enable debug logging.
"""
timeout: Optional[float] = None
retry_count: int = 3
enable_logging: bool = False
```
---
### 4. Pattern Consistency Checks
#### Service Classes
- Correct inheritance (`TTSService`, `STTService`, `LLMService`)
- Consistent constructor signatures
- Frame emission patterns
- Metrics support:
- `can_generate_metrics()`
- TTFB metrics
- Usage metrics
- Alignment with similar existing services
#### Examples
Validated against `examples/foundational/07-interruptible.py`:
- Proper `create_transport()` usage
- Correct pipeline structure
- Task setup and observers
- Event handler registration
- Runner and bot entrypoint consistency
---
### 5. Specific Implementation Patterns
#### Service Implementation
```python
class ExampleTTSService(TTSService):
def __init__(self, *, api_key: Optional[str] = None, **kwargs):
super().__init__(**kwargs)
self._api_key = api_key or os.getenv("SERVICE_API_KEY")
def can_generate_metrics(self) -> bool:
return True
async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]:
try:
await self.start_ttfb_metrics()
yield TTSStartedFrame()
# ... processing ...
yield TTSAudioRawFrame(...)
finally:
await self.stop_ttfb_metrics()
```
---
#### Example Structure Pattern
```python
transport_params = {
"daily": lambda: DailyParams(...),
"twilio": lambda: FastAPIWebsocketParams(...),
"webrtc": lambda: TransportParams(...),
}
async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
stt = DeepgramSTTService(...)
tts = SomeTTSService(...)
llm = OpenAILLMService(...)
context = LLMContext(messages)
user_aggregator, assistant_aggregator = LLMContextAggregatorPair(...)
pipeline = Pipeline([...])
task = PipelineTask(pipeline, params=..., observers=[...])
@transport.event_handler("on_client_connected")
async def on_client_connected(transport, client):
await task.queue_frames([LLMRunFrame()])
runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
await runner.run(task)
async def bot(runner_args: RunnerArguments):
"""Main bot entry point compatible with Pipecat Cloud."""
transport = await create_transport(runner_args, transport_params)
await run_bot(transport, runner_args)
```
---
## Execution Flow
1. Fetch uncommitted and outgoing changes
2. Categorize files (services, examples, tests, utilities)
3. Analyze each file:
- Readability
- Performance
- Documentation
- Pattern consistency
4. Generate actionable recommendations
5. Apply Pipecat standards
---
## Examples
### Before: Tuple Usage
```python
def get_audio_info(self) -> Tuple[int, int]:
return (48000, 1)
```
### After: Named Class
```python
class AudioInfo:
"""Audio configuration information.
Parameters:
sample_rate: Sample rate in Hz.
num_channels: Number of audio channels.
"""
sample_rate: int
num_channels: int
def get_audio_info(self) -> AudioInfo:
return AudioInfo(sample_rate=48000, num_channels=1)
```
---
### Before: Missing Documentation
```python
class NewTTSService(TTSService):
def __init__(self, api_key: str, voice: str):
self._api_key = api_key
self._voice = voice
```
### After: Fully Documented
```python
class NewTTSService(TTSService):
"""Text-to-speech service using NewProvider API.
Streams PCM audio and emits TTSAudioRawFrame frames compatible
with Pipecat transports.
Supported features:
- Text-to-speech synthesis
- Streaming PCM audio
- Voice customization
- TTFB metrics
"""
def __init__(self, *, api_key: str, voice: str, **kwargs):
"""Initialize the NewTTSService.
Args:
api_key: API key for authentication.
voice: Voice identifier to use.
**kwargs: Additional arguments passed to the parent service.
"""
super().__init__(**kwargs)
self._api_key = api_key
self.set_voice(voice)
```
---
## Notes
- Non-breaking improvements only
- Backward compatibility preserved
- Conservative performance changes
- Google-style docstrings
- Pattern checks follow recent Pipecat code

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---
name: code-review
description: Automated code review for pull requests using multiple specialized agents
disable-model-invocation: true
allowed-tools: Bash(gh issue view:*), Bash(gh search:*), Bash(gh issue list:*), Bash(gh pr comment:*), Bash(gh pr diff:*), Bash(gh pr view:*), Bash(gh pr list:*)
---
Provide a code review for the given pull request.
**Agent assumptions (applies to all agents and subagents):**
- All tools are functional and will work without error. Do not test tools or make exploratory calls. Make sure this is clear to every subagent that is launched.
- Only call a tool if it is required to complete the task. Every tool call should have a clear purpose.
To do this, follow these steps precisely:
1. Launch a haiku agent to check if any of the following are true:
- The pull request is closed
- The pull request is a draft
- The pull request does not need code review (e.g. automated PR, trivial change that is obviously correct)
- Claude has already commented on this PR (check `gh pr view <PR> --comments` for comments left by claude)
If any condition is true, stop and do not proceed.
Note: Still review Claude generated PR's.
2. Launch a haiku agent to return a list of file paths (not their contents) for all relevant CLAUDE.md files including:
- The root CLAUDE.md file, if it exists
- Any CLAUDE.md files in directories containing files modified by the pull request
3. Launch a sonnet agent to view the pull request and return a summary of the changes
4. Launch 4 agents in parallel to independently review the changes. Each agent should return the list of issues, where each issue includes a description and the reason it was flagged (e.g. "CLAUDE.md adherence", "bug"). The agents should do the following:
Agents 1 + 2: CLAUDE.md compliance sonnet agents
Audit changes for CLAUDE.md compliance in parallel. Note: When evaluating CLAUDE.md compliance for a file, you should only consider CLAUDE.md files that share a file path with the file or parents.
Agent 3: Opus bug agent (parallel subagent with agent 4)
Scan for obvious bugs. Focus only on the diff itself without reading extra context. Flag only significant bugs; ignore nitpicks and likely false positives. Do not flag issues that you cannot validate without looking at context outside of the git diff.
Agent 4: Opus bug agent (parallel subagent with agent 3)
Look for problems that exist in the introduced code. This could be security issues, incorrect logic, etc. Only look for issues that fall within the changed code.
**CRITICAL: We only want HIGH SIGNAL issues.** Flag issues where:
- The code will fail to compile or parse (syntax errors, type errors, missing imports, unresolved references)
- The code will definitely produce wrong results regardless of inputs (clear logic errors)
- Clear, unambiguous CLAUDE.md violations where you can quote the exact rule being broken
Do NOT flag:
- Code style or quality concerns
- Potential issues that depend on specific inputs or state
- Subjective suggestions or improvements
If you are not certain an issue is real, do not flag it. False positives erode trust and waste reviewer time.
In addition to the above, each subagent should be told the PR title and description. This will help provide context regarding the author's intent.
5. For each issue found in the previous step by agents 3 and 4, launch parallel subagents to validate the issue. These subagents should get the PR title and description along with a description of the issue. The agent's job is to review the issue to validate that the stated issue is truly an issue with high confidence. For example, if an issue such as "variable is not defined" was flagged, the subagent's job would be to validate that is actually true in the code. Another example would be CLAUDE.md issues. The agent should validate that the CLAUDE.md rule that was violated is scoped for this file and is actually violated. Use Opus subagents for bugs and logic issues, and sonnet agents for CLAUDE.md violations.
6. Filter out any issues that were not validated in step 5. This step will give us our list of high signal issues for our review.
7. If issues were found, skip to step 8 to post comments.
If NO issues were found, post a summary comment using `gh pr comment` (if `--comment` argument is provided):
"No issues found. Checked for bugs and CLAUDE.md compliance."
8. Create a list of all comments that you plan on leaving. This is only for you to make sure you are comfortable with the comments. Do not post this list anywhere.
9. Post inline comments for each issue using `gh pr review` with inline comments. For each comment:
- Provide a brief description of the issue
- For small, self-contained fixes, include a committable suggestion block
- For larger fixes (6+ lines, structural changes, or changes spanning multiple locations), describe the issue and suggested fix without a suggestion block
- Never post a committable suggestion UNLESS committing the suggestion fixes the issue entirely. If follow up steps are required, do not leave a committable suggestion.
**IMPORTANT: Only post ONE comment per unique issue. Do not post duplicate comments.**
Use this list when evaluating issues in Steps 4 and 5 (these are false positives, do NOT flag):
- Pre-existing issues
- Something that appears to be a bug but is actually correct
- Pedantic nitpicks that a senior engineer would not flag
- Issues that a linter will catch (do not run the linter to verify)
- General code quality concerns (e.g., lack of test coverage, general security issues) unless explicitly required in CLAUDE.md
- Issues mentioned in CLAUDE.md but explicitly silenced in the code (e.g., via a lint ignore comment)
Notes:
- Use gh CLI to interact with GitHub (e.g., fetch pull requests, create comments). Do not use web fetch.
- Create a todo list before starting.
- You must cite and link each issue in inline comments (e.g., if referring to a CLAUDE.md, include a link to it).
- If no issues are found, post a comment with the following format:
---
## Code review
No issues found. Checked for bugs and CLAUDE.md compliance.
---
- When linking to code in inline comments, follow the following format precisely, otherwise the Markdown preview won't render correctly: `https://github.com/OWNER/REPO/blob/FULL_SHA/path/to/file.py#L10-L15`
- Requires full git sha
- You must provide the full sha. Commands like `https://github.com/owner/repo/blob/$(git rev-parse HEAD)/foo/bar` will not work, since your comment will be directly rendered in Markdown.
- Repo name must match the repo you're code reviewing
- # sign after the file name
- Line range format is L[start]-L[end]
- Provide at least 1 line of context before and after, centered on the line you are commenting about (eg. if you are commenting about lines 5-6, you should link to `L4-7`)

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---
name: pr-submit
description: Create and submit a GitHub PR from the current branch
---
Submit the current changes as a GitHub pull request.
## Instructions
1. Check the current state of the repository:
- Run `git status` to see staged, unstaged, and untracked changes
- Run `git diff` to see current changes
- Run `git log --oneline -10` to see recent commits
2. If there are uncommitted changes relevant to the PR:
- Ask the user if they want a specific prefix for the branch name (e.g., `alice/`, `fix/`, `feat/`)
- Create a new branch based on the current branch
- Commit the changes using multiple commits if the changes are unrelated
3. Push the branch and create the PR:
- Push with `-u` flag to set upstream tracking
- Create the PR using `gh pr create`
4. After the PR is created:
- Run `/changelog <pr_number>` to generate changelog files, then commit and push them
- Run `/pr-description <pr_number>` to update the PR description
5. Return the PR URL to the user.

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---
name: update-docs
description: Update documentation pages to match source code changes on the current branch
---
Update documentation pages to reflect source code changes on the current branch. Analyzes the diff against main, maps changed source files to their corresponding doc pages, and makes targeted edits.
## Arguments
```
/update-docs [DOCS_PATH]
```
- `DOCS_PATH` (optional): Path to the docs repository root. If not provided, ask the user.
Examples:
- `/update-docs /Users/me/src/docs`
- `/update-docs`
## Instructions
### Step 1: Resolve docs path
If `DOCS_PATH` was provided as an argument, use it. Otherwise, ask the user for the path to their docs repository.
Verify the path exists and contains `server/services/` subdirectory.
### Step 2: Create docs branch
Get the current pipecat branch name:
```bash
git rev-parse --abbrev-ref HEAD
```
In the docs repo, create a new branch off main with a matching name:
```bash
cd DOCS_PATH && git checkout main && git pull && git checkout -b {branch-name}-docs
```
For example, if the pipecat branch is `feat/new-service`, the docs branch becomes `feat/new-service-docs`.
All doc edits in subsequent steps are made on this branch.
### Step 3: Detect changed source files
Run:
```bash
git diff main..HEAD --name-only
```
Filter to files that could affect documentation:
- `src/pipecat/services/**/*.py` (service implementations)
- `src/pipecat/transports/**/*.py` (transport implementations)
- `src/pipecat/serializers/**/*.py` (serializer implementations)
- `src/pipecat/processors/**/*.py` (processor implementations)
- `src/pipecat/audio/**/*.py` (audio utilities)
- `src/pipecat/turns/**/*.py` (turn management)
- `src/pipecat/observers/**/*.py` (observers)
- `src/pipecat/pipeline/**/*.py` (pipeline core)
Ignore `__init__.py`, `__pycache__`, test files, and files that only contain type re-exports.
### Step 4: Map source files to doc pages
For each changed source file, find the corresponding doc page. Read the mapping file at `.claude/skills/update-docs/SOURCE_DOC_MAPPING.md` and apply its tiered lookup: tier 1 (known exceptions) → tier 2 (pattern matching) → tier 3 (search fallback). **First match wins.**
### Step 5: Analyze each source-doc pair
For each mapped pair:
1. **Read the full source file** to understand current state
2. **Read the diff** for that file: `git diff main..HEAD -- <source_file>`
3. **Read the current doc page** in full
Identify what changed by comparing source to docs:
- **Constructor parameters**: Compare `__init__` signature to the Configuration section's `<ParamField>` entries
- **InputParams fields**: Compare `InputParams(BaseModel)` class fields to the InputParams table
- **Event handlers**: Compare `_register_event_handler` calls and event handler definitions to Event Handlers section
- **Class names / imports**: Check if Usage examples reference correct names
- **Behavioral changes**: Check if Notes section needs updating
### Step 6: Make targeted edits
For each doc page that needs updates, edit **only the sections that need changes**. Preserve all other content exactly as-is.
#### Rules
- **Never remove content** unless the corresponding source code was removed
- **Never rewrite sections** that are already accurate
- **Match existing formatting** — if the page uses `<ParamField>` tags, use them; if it uses tables, use tables
- **Keep descriptions concise** — match the tone and length of surrounding content
- **Preserve CardGroup, links, and examples** unless they reference removed functionality
- **Don't touch frontmatter** unless the class was renamed
#### Section-specific guidance
**Configuration** (constructor params):
- Use `<ParamField path="name" type="type" default="value">` format if the page already uses it
- Add new params in logical order (required first, then optional)
- Remove params that no longer exist in source
- Update types/defaults that changed
**InputParams** (runtime settings):
- Use markdown table format: `| Parameter | Type | Default | Description |`
- Match the field names and types from the `InputParams(BaseModel)` class
- Include the default values from the source
**Usage** (code examples):
- Update import paths, class names, and parameter names
- Only modify examples if they would break or be misleading with the new API
- Don't rewrite working examples just to add new optional params
**Notes**:
- Add notes for new behavioral gotchas or breaking changes
- Remove notes about limitations that were fixed
- Keep existing notes that are still accurate
**Event Handlers**:
- Update the event table and example code
- Add new events, remove deleted ones
- Update handler signatures if they changed
**Overview / Key Features / Prerequisites**:
- Only update if the PR fundamentally changes what the service does (new capability, removed capability, renamed class)
- Most PRs will NOT need changes to these sections
### Step 7: Update guides
Guides at `DOCS_PATH/guides/` reference specific class names, parameters, imports, and code patterns. After completing reference doc edits, check if any guides need updates too.
For each changed source file, collect the class names, renamed parameters, and changed imports from the diff. Search the guides directory:
```bash
grep -rl "ClassName\|old_param_name" DOCS_PATH/guides/
```
For each guide that references changed code:
1. Read the full guide
2. Update class names, parameter names, import paths, and code examples that are now incorrect
3. **Don't rewrite prose** — only fix the specific references that changed
4. Leave guides alone if they reference the service generally but don't use any changed APIs
Guide directories:
- `guides/learn/` — conceptual tutorials (pipeline, LLM, STT, TTS, etc.)
- `guides/fundamentals/` — practical how-tos (metrics, recording, transcripts, etc.)
- `guides/features/` — feature-specific guides (Gemini Live, OpenAI audio, WhatsApp, etc.)
- `guides/telephony/` — telephony integration guides (Twilio, Plivo, Telnyx, etc.)
### Step 8: Identify doc gaps
After processing all mapped pairs, check for two kinds of gaps:
**Missing pages**: Source files that had no doc page mapping (neither tier 1, 2, nor 3) and are not marked as "(skip)". For each, tell the user:
- The source file path
- The main class(es) it defines
- Whether a new doc page should be created
**Missing sections**: Mapped doc pages that are missing standard sections compared to the source. For example, a transport page with no Configuration section, or a service page with no InputParams table when the source defines `InputParams(BaseModel)`. Flag these and offer to add the missing sections.
If the user wants a new page, create it using this template structure:
```
---
title: "Service Name"
description: "Brief description"
---
## Overview
[Description from class docstring or source analysis]
<CardGroup cols={2}>
[Cards for API reference and examples if available]
</CardGroup>
## Installation
```bash
pip install "pipecat-ai[package-name]"
```
## Prerequisites
[Environment variables and account setup]
## Configuration
[ParamField entries for constructor params]
## InputParams
[Table of InputParams fields, if the service has them]
## Usage
### Basic Setup
```python
[Minimal working example]
```
## Notes
[Important caveats]
## Event Handlers
[Event table and example code]
```
### Step 9: Output summary
After all edits are complete, print a summary:
```
## Documentation Updates
### Updated reference pages
- `server/services/stt/deepgram.mdx` — Updated Configuration (added `new_param`), InputParams (updated `language` default)
- `server/services/tts/elevenlabs.mdx` — Updated Event Handlers (added `on_connected`)
### Updated guides
- `guides/learn/speech-to-text.mdx` — Updated code example (renamed `old_param``new_param`)
### Unmapped source files
- `src/pipecat/services/newprovider/tts.py` — NewProviderTTSService (no doc page exists)
### Skipped files
- `src/pipecat/services/ai_service.py` — internal base class
```
## Guidelines
- **Be conservative** — only change what the diff warrants. Don't "improve" docs beyond what changed in source.
- **Read before editing** — always read the full doc page before making changes so you understand the existing structure.
- **Preserve voice** — match the writing style of the existing doc page, don't impose a different tone.
- **One PR at a time** — this skill operates on the current branch's diff against main. Don't look at other branches.
- **Parallel analysis** — when multiple source files map to different doc pages, analyze and edit them in parallel for efficiency.
- **Shared source files** — files like `services/google/google.py` are shared bases. Check which services import from them and update all affected doc pages.
## Checklist
Before finishing, verify:
- [ ] All changed source files were checked against the mapping table
- [ ] Each doc page edit matches the actual source code change (not guessed)
- [ ] No content was removed unless the corresponding source was removed
- [ ] New parameters have accurate types and defaults from source
- [ ] Formatting matches the existing page style
- [ ] Guides referencing changed APIs were checked and updated
- [ ] Unmapped files were reported to the user

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# Source-to-Doc Mapping
Maps pipecat source files to their documentation pages. Source paths are relative to `src/pipecat/`. Doc paths are relative to `DOCS_PATH`.
## Name mismatches
These source paths don't follow the standard `services/{provider}/{type}.py``server/services/{type}/{provider}.mdx` pattern.
| Source path | Doc page |
|---|---|
| `services/google/llm.py` | `server/services/llm/gemini.mdx` |
| `services/google/llm_vertex.py` | `server/services/llm/google-vertex.mdx` |
| `services/google/google.py` | (shared base — check which services use it) |
| `services/google/gemini_live/**` | `server/services/s2s/gemini-live.mdx` |
| `services/google/gemini_live/llm_vertex.py` | `server/services/s2s/gemini-live-vertex.mdx` |
| `services/aws_nova_sonic/**` | `server/services/s2s/aws.mdx` |
| `services/ultravox/**` | `server/services/s2s/ultravox.mdx` |
| `services/grok/realtime/**` | `server/services/s2s/grok.mdx` |
| `services/openai/realtime/**` | `server/services/s2s/openai.mdx` |
| `processors/frameworks/rtvi.py` | `server/frameworks/rtvi/rtvi-processor.mdx` and `server/frameworks/rtvi/rtvi-observer.mdx` |
| `processors/transcript_processor.py` | `server/utilities/transcript-processor.mdx` |
| `processors/user_idle_processor.py` | `server/utilities/user-idle-processor.mdx` |
| `processors/idle_frame_processor.py` | `server/pipeline/pipeline-idle-detection.mdx` |
| `pipeline/task.py` | `server/pipeline/pipeline-task.mdx` |
| `pipeline/runner.py` | `server/utilities/runner/guide.mdx` |
| `transports/base_transport.py` | `server/services/transport/transport-params.mdx` |
## Skip list
These files should never trigger doc updates.
| Pattern | Reason |
|---|---|
| `services/ai_service.py` | Internal base class |
| `services/stt_service.py` | Internal base class |
| `services/tts_service.py` | Internal base class |
| `services/llm_service.py` | Internal base class |
| `services/websocket_service.py` | Internal base class |
| `services/openai_realtime_beta/**` | Deprecated |
| `services/openai_realtime/**` | Deprecated |
| `services/gemini_multimodal_live/**` | Deprecated |
| `services/aws/agent_core.py` | Internal |
| `services/aws/sagemaker/**` | No doc page |
| `transports/base_input.py` | Internal base class |
| `transports/base_output.py` | Internal base class |
| `transports/websocket/client.py` | No doc page |
| `serializers/base_serializer.py` | Internal base class |
| `serializers/protobuf.py` | Internal |
| `processors/audio/**` | Internal |
| `pipeline/pipeline.py` | Core architecture, not a service doc |
## Pattern matching
For files not in the tables above, apply these patterns. Convert underscores to hyphens in provider names for doc filenames.
| Source pattern | Doc pattern |
|---|---|
| `services/{provider}/stt*.py` | `server/services/stt/{provider}.mdx` |
| `services/{provider}/tts*.py` | `server/services/tts/{provider}.mdx` |
| `services/{provider}/llm*.py` | `server/services/llm/{provider}.mdx` |
| `services/{provider}/image*.py` | `server/services/image-generation/{provider}.mdx` |
| `services/{provider}/video*.py` | `server/services/video/{provider}.mdx` |
| `services/{provider}/realtime/**` | `server/services/s2s/{provider}.mdx` |
| `transports/{name}/**` | `server/services/transport/{name}.mdx` |
| `serializers/{name}.py` | `server/services/serializers/{name}.mdx` |
| `observers/**` | `server/utilities/observers/` (match by class name) |
| `audio/vad/**` | `server/utilities/audio/` (match by class name) |
| `audio/filters/**` | `server/utilities/audio/` (match by class name) |
| `audio/mixers/**` | `server/utilities/audio/` (match by class name) |
| `processors/filters/**` | `server/utilities/filters/` (match by class name) |
If the doc file doesn't exist at the resolved path, the file is **unmapped**.
## Search fallback
For files that don't match any table or pattern above:
1. Extract the main class name(s) from the source file
2. Search the docs directory for that class name: `grep -r "ClassName" DOCS_PATH/server/`
3. If found in a doc page, use that as the mapping

View File

@@ -39,7 +39,9 @@ jobs:
--extra google \
--extra langchain \
--extra livekit \
--extra local-smart-turn-v3 \
--extra piper \
--extra tracing \
--extra websocket
- name: Run tests with coverage

View File

@@ -14,7 +14,7 @@ jobs:
strategy:
fail-fast: false
matrix:
python-version: ['3.10.18', '3.11.13', '3.12.11', '3.13.5']
python-version: ['3.10.19', '3.11.14', '3.12.12', '3.13.12']
name: Python ${{ matrix.python-version }}
steps:
@@ -40,20 +40,10 @@ jobs:
uv python install ${{ matrix.python-version }}
uv python pin ${{ matrix.python-version }}
- name: Test uv sync with all extras (Python < 3.13)
if: "!startsWith(matrix.python-version, '3.13.')"
- name: Test uv sync with all extras
run: |
uv sync --group dev --all-extras --no-extra krisp
- name: Test uv sync without PyTorch extras (Python 3.13+)
if: startsWith(matrix.python-version, '3.13.')
run: |
uv sync --group dev --all-extras \
--no-extra krisp \
--no-extra local-smart-turn \
--no-extra moondream \
--no-extra mlx-whisper
- name: Verify installation
run: |
uv run python --version

View File

@@ -43,7 +43,9 @@ jobs:
--extra google \
--extra langchain \
--extra livekit \
--extra local-smart-turn-v3 \
--extra piper \
--extra tracing \
--extra websocket
- name: Test with pytest

View File

@@ -7,6 +7,353 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
<!-- towncrier release notes start -->
## [0.0.102] - 2026-02-10
### Added
- Added `ResembleAITTSService` for text-to-speech using Resemble AI's streaming
WebSocket API with word-level timestamps and jitter buffering for smooth
audio playback.
(PR [#3134](https://github.com/pipecat-ai/pipecat/pull/3134))
- Added `UserBotLatencyObserver` for tracking user-to-bot response latency.
When tracing is enabled, latency measurements are automatically recorded as
`turn.user_bot_latency_seconds` attributes on OpenTelemetry turn spans.
(PR [#3355](https://github.com/pipecat-ai/pipecat/pull/3355))
- Added `append_to_context` parameter to `TTSSpeakFrame` for conditional LLM
context addition.
- Allows fine-grained control over whether text should be added to
conversation context
- Defaults to `True` to maintain backward compatibility
(PR [#3584](https://github.com/pipecat-ai/pipecat/pull/3584))
- Added TTS context tracking system with `context_id` field to trace audio
generation through the pipeline.
- `TTSAudioRawFrame`, `TTSStartedFrame`, `TTSStoppedFrame` now include
`context_id`
- `AggregatedTextFrame` and `TTSTextFrame` now include `context_id`
- Enables tracking which TTS request generated specific audio chunks
(PR [#3584](https://github.com/pipecat-ai/pipecat/pull/3584))
- Added support for Inworld TTS Websocket Auto Mode for improved latency
(PR [#3593](https://github.com/pipecat-ai/pipecat/pull/3593))
- Added new frames for context summarization: `LLMContextSummaryRequestFrame`
and `LLMContextSummaryResultFrame`.
(PR [#3621](https://github.com/pipecat-ai/pipecat/pull/3621))
- Added context summarization feature to automatically compress conversation
history when conversation length limits (by token or message count) are
reached, enabling efficient long-running conversations.
- Configure via `enable_context_summarization=True` in
`LLMAssistantAggregatorParams`
- Customize behavior with `LLMContextSummarizationConfig` (max tokens,
thresholds, etc.)
- Automatically preserves incomplete function call sequences during
summarization
- See new examples:
`examples/foundational/54-context-summarization-openai.py` and
`examples/foundational/54a-context-summarization-google.py`
(PR [#3621](https://github.com/pipecat-ai/pipecat/pull/3621))
- Added RTVI function call lifecycle events (`llm-function-call-started`,
`llm-function-call-in-progress`, `llm-function-call-stopped`) with
configurable security levels via
`RTVIObserverParams.function_call_report_level`. Supports per-function
control over what information is exposed (`DISABLED`, `NONE`, `NAME`, or
`FULL`).
(PR [#3630](https://github.com/pipecat-ai/pipecat/pull/3630))
- Added `RequestMetadataFrame` and metadata handling for `ServiceSwitcher` to
ensure STT services correctly emit `STTMetadataFrame` when switching between
services. Only the active service's metadata is propagated downstream,
switching services triggers the newly active service to re-emit its metadata,
and proper frame ordering is maintained at startup.
(PR [#3637](https://github.com/pipecat-ai/pipecat/pull/3637))
- Added `STTMetadataFrame` to broadcast STT service latency information at
pipeline start.
- STT services broadcast P99 time-to-final-segment (`ttfs_p99_latency`) to
downstream processors
- Turn stop strategies automatically configure their STT timeout from this
metadata
- Developers can override `ttfs_p99_latency` via constructor argument for
custom deployments
- Added measured P99 values for STT providers.
- See [stt-benchmark](https://github.com/pipecat-ai/stt-benchmark) to
measure latency for your configuration
(PR [#3637](https://github.com/pipecat-ai/pipecat/pull/3637))
- Added support for `is_sandbox` parameter in `LiveAvatarNewSessionRequest` to
enable sandbox mode for HeyGen LiveAvatar sessions.
(PR [#3653](https://github.com/pipecat-ai/pipecat/pull/3653))
- Added support for `video_settings` parameter in `LiveAvatarNewSessionRequest`
to configure video encoding (H264/VP8) and quality levels.
(PR [#3653](https://github.com/pipecat-ai/pipecat/pull/3653))
- Added `OpenAIRealtimeSTTService` for real-time streaming speech-to-text using
OpenAI's Realtime API WebSocket transcription sessions. Supports local VAD
and server-side VAD modes, noise reduction, and automatic reconnection.
(PR [#3656](https://github.com/pipecat-ai/pipecat/pull/3656))
- Added `bulbul:v3-beta` TTS model support for Sarvam AI with temperature
control and 25 new speaker voices.
(PR [#3671](https://github.com/pipecat-ai/pipecat/pull/3671))
- Added `saaras:v3` STT model support for Sarvam AI with new `mode` parameter
(transcribe, translate, verbatim, translit, codemix) and prompt support.
(PR [#3671](https://github.com/pipecat-ai/pipecat/pull/3671))
- Added new OpenAI TTS voice options `marin` and `cedar`.
(PR [#3682](https://github.com/pipecat-ai/pipecat/pull/3682))
- Added `UserMuteStartedFrame` and `UserMuteStoppedFrame` system frames, and
corresponding `user-mute-started` / `user-mute-stopped` RTVI messages, so
clients can observe when mute strategies activate or deactivate.
(PR [#3687](https://github.com/pipecat-ai/pipecat/pull/3687))
### Changed
- Updated all 30+ TTS service implementations to support context tracking with
`context_id`.
- Services now generate and propagate context IDs through TTS frames
- Enables end-to-end tracing of TTS requests through the pipeline
(PR [#3584](https://github.com/pipecat-ai/pipecat/pull/3584))
- ⚠️ `TTSService.run_tts()` now requires a `context_id` parameter for context
tracking.
- Custom TTS service implementations must update their `run_tts()`
signature
- Before: `async def run_tts(self, text: str) -> AsyncGenerator[Frame,
None]:`
- After: `async def run_tts(self, text: str, context_id: str) ->
AsyncGenerator[Frame, None]:`
(PR [#3584](https://github.com/pipecat-ai/pipecat/pull/3584))
- Simplified context aggregators to use `frame.append_to_context` flag instead
of tracking internal state.
- Cleaner logic in `LLMResponseAggregator` and
`LLMResponseUniversalAggregator`
- More consistent behavior across aggregator implementations
(PR [#3584](https://github.com/pipecat-ai/pipecat/pull/3584))
- Updated timestamps to be cumulative within an agent turn, using
flushCompleted message as an indication of when timestamps from the server
are reset to 0
(PR [#3593](https://github.com/pipecat-ai/pipecat/pull/3593))
- Changed `KokoroTTSService` to use `kokoro-onnx` instead of `kokoro` as the
underlying TTS engine.
(PR [#3612](https://github.com/pipecat-ai/pipecat/pull/3612))
- Improved user turn stop timing in `TranscriptionUserTurnStopStrategy` and
`TurnAnalyzerUserTurnStopStrategy`.
- Timeout now starts on `VADUserStoppedSpeakingFrame` for tighter, more
predictable timing
- Added support for finalized transcripts
(`TranscriptionFrame.finalized=True`) to trigger earlier
- Added fallback timeout for edge cases where transcripts arrive without
VAD events
- Removed `InterimTranscriptionFrame` handling (no longer affects timing)
(PR [#3637](https://github.com/pipecat-ai/pipecat/pull/3637))
- Improved the accuracy of the `UserBotLatencyObserver` and
`UserBotLatencyLogObserver` by measuring from the time when the user actually
starts speaking.
(PR [#3637](https://github.com/pipecat-ai/pipecat/pull/3637))
- ⚠️ Renamed `timeout` parameter to `user_speech_timeout` in
`TranscriptionUserTurnStopStrategy`.
(PR [#3637](https://github.com/pipecat-ai/pipecat/pull/3637))
- Updated the `VADUserStartedSpeakingFrame` to include `start_secs` and
`timestamp` and `VADUserStoppedSpeakingFrame` to include `stop_secs` and
`timestamp`, removing the need to separately handle the
`SpeechControlParamsFrame` for VADParams values.
(PR [#3637](https://github.com/pipecat-ai/pipecat/pull/3637))
- ⚠️ Renamed `TranscriptionUserTurnStopStrategy` to
`SpeechTimeoutUserTurnStopStrategy`. The old name is deprecated and will be
removed in a future release.
(PR [#3637](https://github.com/pipecat-ai/pipecat/pull/3637))
- `AssemblyAISTTService` now automatically configures optimal settings for
manual turn detection when `vad_force_turn_endpoint=True`. This sets
`end_of_turn_confidence_threshold=1.0` and `max_turn_silence=2000` by
default, which disables model-based turn detection and reduces latency by
relying on external VAD for turn endpoints. Warnings are logged if
conflicting settings are detected.
(PR [#3644](https://github.com/pipecat-ai/pipecat/pull/3644))
- Upgraded the `pipecat-ai-small-webrtc-prebuilt` package to v2.1.0.
(PR [#3652](https://github.com/pipecat-ai/pipecat/pull/3652))
- Changed default session mode from "CUSTOM" to "LITE" in HeyGen LiveAvatar
integration, with VP8 as the default video encoding.
(PR [#3653](https://github.com/pipecat-ai/pipecat/pull/3653))
- ⚠️ The default `VADParams` `stop_secs` default is changing from `0.8` seconds
to `0.2` seconds. This change both simplifies the developer experience and
improves the performance of STT services. With a shorter `stop_secs` value,
STT services using a local VAD can finalize sooner, resulting in faster
transcription.
- `SpeechTimeoutUserTurnStopStrategy`: control how long to wait for
additional user speech using `user_speech_timeout` (default: 0.6 sec).
- `TurnAnalyzerUserTurnStopStrategy`: the turn analyzer automatically
adjusts the user wait time based on the audio input.
(PR [#3659](https://github.com/pipecat-ai/pipecat/pull/3659))
- Moved interruption wait event from per-processor instance state to
`InterruptionFrame` itself. Added `InterruptionFrame.complete()` to signal
when the interruption has fully traversed the pipeline. Custom processors
that block or consume an `InterruptionFrame` before it reaches the pipeline
sink must call `frame.complete()` to avoid stalling
`push_interruption_task_frame_and_wait()`. A warning is logged if completion
does not happen within 2 seconds.
(PR [#3660](https://github.com/pipecat-ai/pipecat/pull/3660))
- Update the default model to `scribe_v2` for `ElevenLabsSTTService`.
(PR [#3664](https://github.com/pipecat-ai/pipecat/pull/3664))
- Changed the `DeepgramSTTService` default setting for `smart_format` to
`False`, as agents don't need smart formatting. Disabling this setting
provides a small performance improvement, as well.
(PR [#3666](https://github.com/pipecat-ai/pipecat/pull/3666))
- Changed `FunctionCallCancelFrame` to broadcast in both directions for
consistency with other function call frames.
(PR [#3672](https://github.com/pipecat-ai/pipecat/pull/3672))
- Changed default user turn stop strategy from
`TranscriptionUserTurnStopStrategy` to `TurnAnalyzerUserTurnStopStrategy`
with `LocalSmartTurnAnalyzerV3`.
(PR [#3689](https://github.com/pipecat-ai/pipecat/pull/3689))
- Renamed `RequestMetadataFrame` to `ServiceSwitcherRequestMetadataFrame` and
added a `service` field to target a specific service. The frame is now pushed
downstream by services after handling instead of being silently consumed.
(PR [#3692](https://github.com/pipecat-ai/pipecat/pull/3692))
- Update `SonioxSTTService` to set `vad_force_turn_endpoint` to `True`. This
setting disabled the turn detection logic available natively in Soniox.
Instead, Soniox relies on a local VAD to finalize the transcript. This
configuration meaningfully reduces the time to final segment for Soniox. With
this setting enabled, Soniox outputs a transcript in ~250ms (median). Pipecat
enables smart-turn detection by default using the `LocalSmartTurnAnalyzerV3`.
To use the native turn detection logic in Soniox, just set
`vad_force_turn_endpoint` to `False`.
(PR [#3697](https://github.com/pipecat-ai/pipecat/pull/3697))
- Update `SonioxSTTService` default model to `stt-rt-v4`.
(PR [#3697](https://github.com/pipecat-ai/pipecat/pull/3697))
- Updated the default model to `async_flash_v1.0` and base URL to
`https://api.async.com` for `AsyncAITTSService`.
(PR [#3701](https://github.com/pipecat-ai/pipecat/pull/3701))
### Deprecated
- Deprecated `UserBotLatencyLogObserver`. Use `UserBotLatencyObserver` directly
with its `on_latency_measured` event handler instead.
(PR [#3355](https://github.com/pipecat-ai/pipecat/pull/3355))
- Deprecated `RTVILLMFunctionCallMessage`, `RTVILLMFunctionCallMessageData`,
and `RTVIProcessor.handle_function_call()`. Use the new
`llm-function-call-in-progress` event sent automatically by `RTVIObserver`
instead.
(PR [#3630](https://github.com/pipecat-ai/pipecat/pull/3630))
### Removed
- ⚠️ Removed `timeout` parameter from `TurnAnalyzerUserTurnStopStrategy`. The
timeout is now managed internally based on STT latency.
(PR [#3637](https://github.com/pipecat-ai/pipecat/pull/3637))
### Fixed
- Fixed pipeline freeze when `InterruptionFrame` discards `EndFrame` or
`StopFrame` by making terminal frames uninterruptible.
(PR [#3542](https://github.com/pipecat-ai/pipecat/pull/3542))
- Fixed OpenAI LLM stream not being closed on cancellation/exception, which
could leak sockets.
(PR [#3589](https://github.com/pipecat-ai/pipecat/pull/3589))
- Fixed `PipelineTask` adding duplicate `RTVIProcessor` and `RTVIObserver` when
they were already provided in the pipeline or observers list. They are now
detected and skipped, with appropriate warnings and errors logged for
mismatched configurations.
(PR [#3610](https://github.com/pipecat-ai/pipecat/pull/3610))
- Fixed function call timeout task not being cancelled when the handler
completes without calling `result_callback` or is cancelled externally, which
caused `RuntimeWarning: coroutine was never awaited`.
(PR [#3616](https://github.com/pipecat-ai/pipecat/pull/3616))
- Fixed sentence splitting for Japanese, Chinese, Korean, and other non-Latin
languages in TTS pipeline. NLTK's sentence tokenizer does not support CJK
languages, causing text to accumulate until flush instead of being split at
sentence boundaries. Added fallback detection for unambiguous non-Latin
sentence-ending punctuation (e.g., ``, ``, ``).
(PR [#3617](https://github.com/pipecat-ai/pipecat/pull/3617))
- Fixed `PipelineTask` to also call `set_bot_ready()` when an external
`RTVIProcessor` is provided.
(PR [#3623](https://github.com/pipecat-ai/pipecat/pull/3623))
- Fixed `VADController` not broadcasting `SpeechControlParamsFrame` on startup,
which prevented STT services from receiving VAD params needed for TTFB
measurement.
(PR [#3628](https://github.com/pipecat-ai/pipecat/pull/3628))
- Fixed `StopAsyncIteration` exceptions in `parse_telephony_websocket()` when
WebSocket connections close before sending expected messages.
(PR [#3629](https://github.com/pipecat-ai/pipecat/pull/3629))
- Fixed WebSocket transport error when broadcasting
`InputTransportMessageFrame` by correctly instantiating the frame with its
message parameter.
(PR [#3635](https://github.com/pipecat-ai/pipecat/pull/3635))
- Fixed orphan OpenTelemetry spans during flow initialization and transitions
in tracing.
(PR [#3649](https://github.com/pipecat-ai/pipecat/pull/3649))
- Fixed `SambaNovaLLMService` and `GoogleLLMOpenAIBetaService` streams not
being closed on cancellation/exception, which could leak sockets.
(PR [#3663](https://github.com/pipecat-ai/pipecat/pull/3663))
- Fixed an issue in `InworldTTSService` where punctuation was pronounced. Now,
the `InworldTTSService` ensures proper spacing between sentences, resolving
pronunciation issues.
(PR [#3667](https://github.com/pipecat-ai/pipecat/pull/3667))
- Fixed `ParallelPipeline` allowing frames pushed by internal processors to
escape during lifecycle frame (`StartFrame`/`EndFrame`/`CancelFrame`)
synchronization. These frames are now buffered and flushed after all branches
complete.
(PR [#3668](https://github.com/pipecat-ai/pipecat/pull/3668))
- Fixed issues in Sarvam STT and TTS services: missing event handler
registration for VAD signals, `Optional[bool]` type annotations, WebSocket
state cleanup on API errors, and TTS disconnect/reconnection state
management.
(PR [#3671](https://github.com/pipecat-ai/pipecat/pull/3671))
- Fixed `RTVIObserver` sending duplicate client messages for frames that are
broadcast in both directions (e.g. `UserStartedSpeakingFrame`,
`FunctionCallResultFrame`).
(PR [#3672](https://github.com/pipecat-ai/pipecat/pull/3672))
- Fixed WebSocket STT services (ElevenLabs, Cartesia, Gladia, Soniox)
disconnecting due to idle timeout when no audio is being sent (e.g. when
inactive behind a `ServiceSwitcher`). `WebsocketSTTService` now provides
opt-in silence-based keepalive via `keepalive_timeout` and
`keepalive_interval` parameters.
(PR [#3675](https://github.com/pipecat-ai/pipecat/pull/3675))
## [0.0.101] - 2026-01-30
### Added

View File

@@ -42,7 +42,7 @@ uv lock && uv sync
All data flows as **Frame** objects through a pipeline of **FrameProcessors**:
```
Transport Input → Pipeline Source → [Processor1] → [Processor2] → ... → Pipeline Sink → Transport Output
[Processor1] → [Processor2] → ... → [ProcessorN]
```
**Key components:**
@@ -55,7 +55,11 @@ Transport Input → Pipeline Source → [Processor1] → [Processor2] → ...
- **ParallelPipeline** (`src/pipecat/pipeline/parallel_pipeline.py`): Runs multiple pipelines in parallel.
- **Transports** (`src/pipecat/transports/`): External I/O layer (Daily WebRTC, LiveKit WebRTC, WebSocket, Local). Abstract interface via `BaseTransport`.
- **Transports** (`src/pipecat/transports/`): Transports are frame processors used for external I/O layer (Daily WebRTC, LiveKit WebRTC, WebSocket, Local). Abstract interface via `BaseTransport`, `BaseInputTransport` and `BaseOutputTransport`.
- **Pipeline Task (`src/pipecat/pipeline/task.py`)**: Runs and manages a pipeline. Pipeline tasks send the first frame, `StartFrame`, to the pipeline in order for processors to know they can start processing and pushing frames. Pipeline tasks internally create a pipeline with two additional processors, a source processor before the user-defined pipeline and a sink processor at the end. Those are used for multiple things: error handling, pipeline task level events, heartbeat monitoring, etc.
- **Pipeline Runner (`src/pipecat/pipeline/runner.py`)**: High-level entry point for executing pipeline tasks. Handles signal management (SIGINT/SIGTERM) for graceful shutdown and optional garbage collection. Run a single pipeline task with `await runner.run(task)` or multiple concurrently with `await asyncio.gather(runner.run(task1), runner.run(task2))`.
- **Services** (`src/pipecat/services/`): 60+ AI provider integrations (STT, TTS, LLM, etc.). Extend base classes: `AIService`, `LLMService`, `STTService`, `TTSService`, `VisionService`.
@@ -63,6 +67,8 @@ Transport Input → Pipeline Source → [Processor1] → [Processor2] → ...
- **RTVI** (`src/pipecat/processors/frameworks/rtvi.py`): Real-Time Voice Interface protocol bridging clients and the pipeline. `RTVIProcessor` handles incoming client messages (text input, audio, function call results). `RTVIObserver` converts pipeline frames to outgoing messages: user/bot speaking events, transcriptions, LLM/TTS lifecycle, function calls, metrics, and audio levels.
- **Observers** (`src/pipecat/observers/`): Monitor frame flow without modifying the pipeline. Passed to `PipelineTask` via the `observers` parameter. Implement `on_process_frame()` and `on_push_frame()` callbacks.
### Important Patterns
- **Context Aggregation**: `LLMContext` accumulates messages for LLM calls; `UserResponse` aggregates user input
@@ -76,7 +82,11 @@ Transport Input → Pipeline Source → [Processor1] → [Processor2] → ...
- **Uninterruptible Frames**: These are frames that will not be removed from internal queues even if there's an interruption. For example, `EndFrame` and `StopFrame`.
- **Events**: Most classes in Pipecat have `BaseObject` as the very base class. `BaseObject` has support for events. Events can run in the background in an async task (default) or synchronously (`sync=True`) if we want immediate action. Synchronous event handlers need to exectue fast.
- **Events**: Most classes in Pipecat have `BaseObject` as the very base class. `BaseObject` has support for events. Events can run in the background in an async task (default) or synchronously (`sync=True`) if we want immediate action. Synchronous event handlers need to execute fast.
- **Async Task Management**: Always use `self.create_task(coroutine, name)` instead of raw `asyncio.create_task()`. The `TaskManager` automatically tracks tasks and cleans them up on processor shutdown. Use `await self.cancel_task(task, timeout)` for cancellation.
- **Error Handling**: Use `await self.push_error(msg, exception, fatal)` to push errors upstream. Services should use `fatal=False` (the default) so application code can handle errors and take action (e.g. switch to another service).
### Key Directories
@@ -88,6 +98,7 @@ Transport Input → Pipeline Source → [Processor1] → [Processor2] → ...
| `src/pipecat/services/` | AI service integrations (60+ providers) |
| `src/pipecat/transports/` | Transport layer (Daily, LiveKit, WebSocket, Local) |
| `src/pipecat/serializers/`| Frame serialization for WebSocket protocols |
| `src/pipecat/observers/` | Pipeline observers for monitoring frame flow |
| `src/pipecat/audio/` | VAD, filters, mixers, turn detection, DTMF |
| `src/pipecat/turns/` | User turn management |
@@ -138,6 +149,7 @@ When adding a new service:
6. Add metrics tracking via `MetricsData` if relevant
7. Follow the pattern of existing services in `src/pipecat/services/`
## Pull Requests
## Testing
Test utilities live in `src/pipecat/tests/utils.py`. Use `run_test()` to send frames through a pipeline and assert expected output frames in each direction. Use `SleepFrame(sleep=N)` to add delays between frames.
After creating a PR, use `/changelog <pr_number>` to generate the changelog file and `/pr-description <pr_number>` to update the PR description.

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@@ -1 +0,0 @@
- Added `ResembleAITTSService` for text-to-speech using Resemble AI's streaming WebSocket API with word-level timestamps and jitter buffering for smooth audio playback.

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@@ -1 +0,0 @@
- Added `UserBotLatencyObserver` for tracking user-to-bot response latency. When tracing is enabled, latency measurements are automatically recorded as `turn.user_bot_latency_seconds` attributes on OpenTelemetry turn spans.

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@@ -1 +0,0 @@
- Deprecated `UserBotLatencyLogObserver`. Use `UserBotLatencyObserver` directly with its `on_latency_measured` event handler instead.

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@@ -1 +0,0 @@
- Fixed pipeline freeze when `InterruptionFrame` discards `EndFrame` or `StopFrame` by making terminal frames uninterruptible.

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@@ -1 +0,0 @@
- Fixed OpenAI LLM stream not being closed on cancellation/exception, which could leak sockets.

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@@ -1 +0,0 @@
- Added support for Inworld TTS Websocket Auto Mode for improved latency

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@@ -1 +0,0 @@
- Updated timestamps to be cumulative within an agent turn, using flushCompleted message as an indication of when timestamps from the server are reset to 0

View File

@@ -1 +0,0 @@
- Fixed `PipelineTask` adding duplicate `RTVIProcessor` and `RTVIObserver` when they were already provided in the pipeline or observers list. They are now detected and skipped, with appropriate warnings and errors logged for mismatched configurations.

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@@ -1 +0,0 @@
- Changed `KokoroTTSService` to use `kokoro-onnx` instead of `kokoro` as the underlying TTS engine.

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@@ -1 +0,0 @@
- Fixed function call timeout task not being cancelled when the handler completes without calling `result_callback` or is cancelled externally, which caused `RuntimeWarning: coroutine was never awaited`.

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@@ -1,5 +0,0 @@
- Fixed sentence splitting for Japanese, Chinese, Korean, and other non-Latin
languages in TTS pipeline. NLTK's sentence tokenizer does not support CJK
languages, causing text to accumulate until flush instead of being split at
sentence boundaries. Added fallback detection for unambiguous non-Latin
sentence-ending punctuation (e.g., `。`, ``, ``).

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@@ -1 +0,0 @@
- Fixed `PipelineTask` to also call `set_bot_ready()` when an external `RTVIProcessor` is provided.

1
changelog/3625.added.md Normal file
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@@ -0,0 +1 @@
- Added `"timestampTransportStrategy": "ASYNC"` to `InworldAITTSService`. This allows timestamps info to trail audio chunks arrival, resulting in much better first audio chunk latency

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@@ -1 +0,0 @@
- Fixed `VADController` not broadcasting `SpeechControlParamsFrame` on startup, which prevented STT services from receiving VAD params needed for TTFB measurement.

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@@ -1 +0,0 @@
- Fixed `StopAsyncIteration` exceptions in `parse_telephony_websocket()` when WebSocket connections close before sending expected messages.

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@@ -1 +0,0 @@
- Added RTVI function call lifecycle events (`llm-function-call-started`, `llm-function-call-in-progress`, `llm-function-call-stopped`) with configurable security levels via `RTVIObserverParams.function_call_report_level`. Supports per-function control over what information is exposed (`DISABLED`, `NONE`, `NAME`, or `FULL`).

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@@ -1 +0,0 @@
- Deprecated `RTVILLMFunctionCallMessage`, `RTVILLMFunctionCallMessageData`, and `RTVIProcessor.handle_function_call()`. Use the new `llm-function-call-in-progress` event sent automatically by `RTVIObserver` instead.

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@@ -1 +0,0 @@
- Fixed WebSocket transport error when broadcasting `InputTransportMessageFrame` by correctly instantiating the frame with its message parameter.

1
changelog/3642.added.md Normal file
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@@ -0,0 +1 @@
- Added model-specific `InputParams` to `RimeTTSService`: arcana params (`repetition_penalty`, `temperature`, `top_p`) and mistv2 params (`no_text_normalization`, `save_oovs`, `segment`). Model, voice, and param changes now trigger WebSocket reconnection.

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@@ -0,0 +1 @@
- ⚠️ `RimeTTSService` now defaults to `model="arcana"` and the `wss://users-ws.rime.ai/ws3` endpoint. `InputParams` defaults changed from mistv2-specific values to `None` — only explicitly-set params are sent as query params.

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@@ -1 +0,0 @@
- Fixed orphan OpenTelemetry spans during flow initialization and transitions in tracing.

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@@ -1 +0,0 @@
- Upgraded the `pipecat-ai-small-webrtc-prebuilt` package to v2.1.0.

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@@ -1 +0,0 @@
- Added `OpenAIRealtimeSTTService` for real-time streaming speech-to-text using OpenAI's Realtime API WebSocket transcription sessions. Supports local VAD and server-side VAD modes, noise reduction, and automatic reconnection.

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@@ -1,10 +0,0 @@
- ⚠️ The default `VADParams` `stop_secs` default is changing from `0.8` seconds
to `0.2` seconds. This change both simplifies the developer experience and
improves the performance of STT services. With a shorter `stop_secs` value,
STT services using a local VAD can finalize sooner, resulting in faster
transcription.
- `SpeechTimeoutUserTurnStopStrategy`: control how long to wait for
additional user speech using `user_speech_timeout` (default: 0.6 sec).
- `TurnAnalyzerUserTurnStopStrategy`: the turn analyzer automatically adjusts
the user wait time based on the audio input.

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@@ -1 +0,0 @@
- Moved interruption wait event from per-processor instance state to `InterruptionFrame` itself. Added `InterruptionFrame.complete()` to signal when the interruption has fully traversed the pipeline. Custom processors that block or consume an `InterruptionFrame` before it reaches the pipeline sink must call `frame.complete()` to avoid stalling `push_interruption_task_frame_and_wait()`. A warning is logged if completion does not happen within 2 seconds.

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@@ -1 +0,0 @@
- Fixed `SambaNovaLLMService` and `GoogleLLMOpenAIBetaService` streams not being closed on cancellation/exception, which could leak sockets.

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@@ -1 +0,0 @@
- Update the default model to `scribe_v2` for `ElevenLabsSTTService`.

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@@ -1 +0,0 @@
- Changed the `DeepgramSTTService` default setting for `smart_format` to `False`, as agents don't need smart formatting. Disabling this setting provides a small performance improvement, as well.

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@@ -1 +0,0 @@
- Fixed an issue in `InworldTTSService` where punctuation was pronounced. Now, the `InworldTTSService` ensures proper spacing between sentences, resolving pronunciation issues.

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@@ -1 +0,0 @@
- Fixed `ParallelPipeline` allowing frames pushed by internal processors to escape during lifecycle frame (`StartFrame`/`EndFrame`/`CancelFrame`) synchronization. These frames are now buffered and flushed after all branches complete.

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@@ -0,0 +1 @@
- Added `X-User-Agent` and `X-Request-Id` headers to `InworldTTSService` for better traceability.

1
changelog/3713.fixed.md Normal file
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@@ -0,0 +1 @@
- Fixed `SmallWebRTCTransport` input audio resampling to properly handle all sample rates, including 8kHz audio.

1
changelog/3718.fixed.md Normal file
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@@ -0,0 +1 @@
- Fixed a race condition in `RTVIObserver` where bot output messages could be sent before the bot-started-speaking event.

1
changelog/3720.fixed.md Normal file
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@@ -0,0 +1 @@
- Fixed Grok Realtime `session.updated` event parsing failure caused by the API returning prefixed voice names (e.g. `"human_Ara"` instead of `"Ara"`).

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@@ -0,0 +1 @@
- Bumped Pillow dependency upper bound from `<12` to `<13` to allow Pillow 12.x.

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@@ -0,0 +1 @@
- Fixed context ID reuse issue in `ElevenLabsTTSService`, `InworldTTSService`, `RimeTTSService`, `CartesiaTTSService`, `AsyncAITTSService`, and `PlayHTTTSService`. Services now properly reuse the same context ID across multiple `run_tts()` invocations within a single LLM turn, preventing context tracking issues and incorrect lifecycle signaling.

1
changelog/3729.fixed.md Normal file
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@@ -0,0 +1 @@
- Fixed word timestamp interleaving issue in `ElevenLabsTTSService` when processing multiple sentences within a single LLM turn.

1
changelog/3730.added.md Normal file
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@@ -0,0 +1 @@
- Added keepalive support to `SarvamSTTService` to prevent idle connection timeouts (e.g. when used behind a `ServiceSwitcher`).

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@@ -0,0 +1 @@
- Moved STT keepalive mechanism from `WebsocketSTTService` to the `STTService` base class, allowing any STT service (not just websocket-based ones) to use idle-connection keepalive via the `keepalive_timeout` and `keepalive_interval` parameters.

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@@ -0,0 +1 @@
- Deprecated unused `Traceable`, `@traceable`, `@traced`, and `AttachmentStrategy` in `pipecat.utils.tracing.class_decorators`. This module will be removed in a future release.

1
changelog/3735.fixed.md Normal file
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@@ -0,0 +1 @@
- Fixed tracing service decorators executing the wrapped function twice when the function itself raised an exception (e.g., LLM rate limit, TTS timeout).

1
changelog/3737.fixed.md Normal file
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@@ -0,0 +1 @@
- Fixed `LLMUserAggregator` broadcasting mute events before `StartFrame` reaches downstream processors.

1
changelog/3751.fixed.md Normal file
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@@ -0,0 +1 @@
- Fixed `RTVIObserver` not sending user transcription messages when using Realtime LLMs (OpenAI Realtime, Gemini Live) that push transcription frames upstream.

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@@ -17,7 +17,6 @@ from fastapi.responses import RedirectResponse
from loguru import logger
from pipecat_ai_small_webrtc_prebuilt.frontend import SmallWebRTCPrebuiltUI
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.frames.frames import LLMRunFrame
from pipecat.pipeline.pipeline import Pipeline
@@ -34,8 +33,6 @@ from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.smallwebrtc.connection import IceServer, SmallWebRTCConnection
from pipecat.transports.smallwebrtc.transport import SmallWebRTCTransport
from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy
from pipecat.turns.user_turn_strategies import UserTurnStrategies
load_dotenv(override=True)
@@ -85,12 +82,7 @@ async def run_example(webrtc_connection: SmallWebRTCConnection):
context = LLMContext(messages)
user_aggregator, assistant_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
user_turn_strategies=UserTurnStrategies(
stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())]
),
vad_analyzer=SileroVADAnalyzer(),
),
user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()),
)
pipeline = Pipeline(

View File

@@ -12,7 +12,6 @@ import aiohttp
from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.frames.frames import LLMRunFrame
from pipecat.pipeline.pipeline import Pipeline
@@ -27,8 +26,6 @@ from pipecat.runner.daily import configure
from pipecat.services.cartesia.tts import CartesiaTTSService
from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.daily.transport import DailyParams, DailyTransport
from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy
from pipecat.turns.user_turn_strategies import UserTurnStrategies
load_dotenv(override=True)
@@ -68,14 +65,7 @@ async def main():
context = LLMContext(messages)
user_aggregator, assistant_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
user_turn_strategies=UserTurnStrategies(
stop=[
TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())
]
),
vad_analyzer=SileroVADAnalyzer(),
),
user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()),
)
pipeline = Pipeline(

View File

@@ -12,7 +12,6 @@ import sys
from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.frames.frames import (
InterruptionFrame,
@@ -34,8 +33,6 @@ from pipecat.services.cartesia.tts import CartesiaTTSService
from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.livekit.transport import LiveKitParams, LiveKitTransport
from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy
from pipecat.turns.user_turn_strategies import UserTurnStrategies
load_dotenv(override=True)
@@ -78,12 +75,7 @@ async def main():
context = LLMContext(messages)
user_aggregator, assistant_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
user_turn_strategies=UserTurnStrategies(
stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())]
),
vad_analyzer=SileroVADAnalyzer(),
),
user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()),
)
pipeline = Pipeline(

View File

@@ -9,7 +9,6 @@ import os
from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.frames.frames import Frame, LLMRunFrame, MetricsFrame
from pipecat.metrics.metrics import (
@@ -35,8 +34,6 @@ from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy
from pipecat.turns.user_turn_strategies import UserTurnStrategies
load_dotenv(override=True)
@@ -103,12 +100,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
context = LLMContext(messages)
user_aggregator, assistant_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
user_turn_strategies=UserTurnStrategies(
stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())]
),
vad_analyzer=SileroVADAnalyzer(),
),
user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()),
)
pipeline = Pipeline(

View File

@@ -10,7 +10,6 @@ from dotenv import load_dotenv
from loguru import logger
from PIL import Image
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.frames.frames import (
BotStartedSpeakingFrame,
@@ -35,8 +34,6 @@ from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy
from pipecat.turns.user_turn_strategies import UserTurnStrategies
load_dotenv(override=True)
@@ -118,12 +115,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
context = LLMContext(messages)
user_aggregator, assistant_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
user_turn_strategies=UserTurnStrategies(
stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())]
),
vad_analyzer=SileroVADAnalyzer(),
),
user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()),
)
image_sync_aggregator = ImageSyncAggregator(

View File

@@ -9,7 +9,6 @@ import os
from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.frames.frames import LLMRunFrame
from pipecat.pipeline.pipeline import Pipeline
@@ -28,8 +27,6 @@ from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy
from pipecat.turns.user_turn_strategies import UserTurnStrategies
load_dotenv(override=True)
@@ -74,12 +71,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
context = LLMContext(messages)
user_aggregator, assistant_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
user_turn_strategies=UserTurnStrategies(
stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())]
),
vad_analyzer=SileroVADAnalyzer(),
),
user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()),
)
pipeline = Pipeline(

View File

@@ -9,7 +9,6 @@ import os
from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.frames.frames import LLMRunFrame
from pipecat.pipeline.pipeline import Pipeline
@@ -28,8 +27,6 @@ from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy
from pipecat.turns.user_turn_strategies import UserTurnStrategies
load_dotenv(override=True)
@@ -73,12 +70,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
context = LLMContext(messages)
user_aggregator, assistant_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
user_turn_strategies=UserTurnStrategies(
stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())]
),
vad_analyzer=SileroVADAnalyzer(),
),
user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()),
)
pipeline = Pipeline(

View File

@@ -10,7 +10,6 @@ import aiohttp
from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.frames.frames import LLMRunFrame
from pipecat.pipeline.pipeline import Pipeline
@@ -31,8 +30,6 @@ from pipecat.transcriptions.language import Language
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy
from pipecat.turns.user_turn_strategies import UserTurnStrategies
load_dotenv(override=True)
@@ -114,14 +111,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
context = LLMContext(messages)
user_aggregator, assistant_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
user_turn_strategies=UserTurnStrategies(
stop=[
TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())
]
),
vad_analyzer=SileroVADAnalyzer(),
),
user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()),
)
pipeline = Pipeline(

View File

@@ -15,7 +15,6 @@ from langchain_core.runnables.history import RunnableWithMessageHistory
from langchain_openai import ChatOpenAI
from loguru import logger
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.frames.frames import LLMMessagesUpdateFrame
from pipecat.pipeline.pipeline import Pipeline
@@ -34,8 +33,6 @@ from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy
from pipecat.turns.user_turn_strategies import UserTurnStrategies
load_dotenv(override=True)
@@ -100,12 +97,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
context = LLMContext()
user_aggregator, assistant_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
user_turn_strategies=UserTurnStrategies(
stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())]
),
vad_analyzer=SileroVADAnalyzer(),
),
user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()),
)
pipeline = Pipeline(

View File

@@ -11,7 +11,6 @@ import aiohttp
from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.frames.frames import LLMRunFrame
from pipecat.pipeline.pipeline import Pipeline
@@ -30,8 +29,6 @@ from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy
from pipecat.turns.user_turn_strategies import UserTurnStrategies
load_dotenv(override=True)
@@ -78,14 +75,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
context = LLMContext(messages)
user_aggregator, assistant_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
user_turn_strategies=UserTurnStrategies(
stop=[
TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())
]
),
vad_analyzer=SileroVADAnalyzer(),
),
user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()),
)
pipeline = Pipeline(

View File

@@ -10,7 +10,6 @@ import os
from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.frames.frames import LLMRunFrame
from pipecat.pipeline.pipeline import Pipeline
@@ -29,8 +28,6 @@ from pipecat.services.deepgram.tts import DeepgramTTSService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy
from pipecat.turns.user_turn_strategies import UserTurnStrategies
load_dotenv(override=True)
@@ -83,12 +80,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
context = LLMContext(messages)
user_aggregator, assistant_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
user_turn_strategies=UserTurnStrategies(
stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())]
),
vad_analyzer=SileroVADAnalyzer(),
),
user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()),
)
pipeline = Pipeline(

View File

@@ -10,7 +10,6 @@ import os
from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.frames.frames import LLMRunFrame
from pipecat.pipeline.pipeline import Pipeline
@@ -29,8 +28,6 @@ from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy
from pipecat.turns.user_turn_strategies import UserTurnStrategies
load_dotenv(override=True)
@@ -72,12 +69,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
context = LLMContext(messages)
user_aggregator, assistant_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
user_turn_strategies=UserTurnStrategies(
stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())]
),
vad_analyzer=SileroVADAnalyzer(),
),
user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()),
)
pipeline = Pipeline(

View File

@@ -11,7 +11,6 @@ import aiohttp
from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.frames.frames import LLMRunFrame
from pipecat.pipeline.pipeline import Pipeline
@@ -30,8 +29,6 @@ from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy
from pipecat.turns.user_turn_strategies import UserTurnStrategies
load_dotenv(override=True)
@@ -82,14 +79,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
context = LLMContext(messages)
user_aggregator, assistant_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
user_turn_strategies=UserTurnStrategies(
stop=[
TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())
]
),
vad_analyzer=SileroVADAnalyzer(),
),
user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()),
)
pipeline = Pipeline(

View File

@@ -10,7 +10,6 @@ import os
from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.frames.frames import LLMRunFrame
from pipecat.pipeline.pipeline import Pipeline
@@ -29,8 +28,6 @@ from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy
from pipecat.turns.user_turn_strategies import UserTurnStrategies
load_dotenv(override=True)
@@ -75,12 +72,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
context = LLMContext(messages)
user_aggregator, assistant_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
user_turn_strategies=UserTurnStrategies(
stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())]
),
vad_analyzer=SileroVADAnalyzer(),
),
user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()),
)
pipeline = Pipeline(

View File

@@ -10,7 +10,6 @@ import os
from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.frames.frames import LLMRunFrame
from pipecat.pipeline.pipeline import Pipeline
@@ -29,8 +28,6 @@ from pipecat.services.playht.tts import PlayHTHttpTTSService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy
from pipecat.turns.user_turn_strategies import UserTurnStrategies
load_dotenv(override=True)
@@ -75,12 +72,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
context = LLMContext(messages)
user_aggregator, assistant_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
user_turn_strategies=UserTurnStrategies(
stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())]
),
vad_analyzer=SileroVADAnalyzer(),
),
user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()),
)
pipeline = Pipeline(

View File

@@ -10,7 +10,6 @@ import os
from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.frames.frames import LLMRunFrame
from pipecat.pipeline.pipeline import Pipeline
@@ -30,8 +29,6 @@ from pipecat.transcriptions.language import Language
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy
from pipecat.turns.user_turn_strategies import UserTurnStrategies
load_dotenv(override=True)
@@ -77,12 +74,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
context = LLMContext(messages)
user_aggregator, assistant_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
user_turn_strategies=UserTurnStrategies(
stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())]
),
vad_analyzer=SileroVADAnalyzer(),
),
user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()),
)
pipeline = Pipeline(

View File

@@ -10,7 +10,6 @@ import os
from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.frames.frames import LLMRunFrame
from pipecat.pipeline.pipeline import Pipeline
@@ -29,8 +28,6 @@ from pipecat.services.azure.tts import AzureHttpTTSService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy
from pipecat.turns.user_turn_strategies import UserTurnStrategies
load_dotenv(override=True)
@@ -81,12 +78,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
context = LLMContext(messages)
user_aggregator, assistant_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
user_turn_strategies=UserTurnStrategies(
stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())]
),
vad_analyzer=SileroVADAnalyzer(),
),
user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()),
)
pipeline = Pipeline(

View File

@@ -10,7 +10,6 @@ import os
from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.frames.frames import LLMRunFrame
from pipecat.pipeline.pipeline import Pipeline
@@ -29,8 +28,6 @@ from pipecat.services.azure.tts import AzureTTSService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy
from pipecat.turns.user_turn_strategies import UserTurnStrategies
load_dotenv(override=True)
@@ -81,12 +78,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
context = LLMContext(messages)
user_aggregator, assistant_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
user_turn_strategies=UserTurnStrategies(
stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())]
),
vad_analyzer=SileroVADAnalyzer(),
),
user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()),
)
pipeline = Pipeline(

View File

@@ -10,7 +10,6 @@ import os
from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.audio.vad.vad_analyzer import VADParams
from pipecat.frames.frames import LLMRunFrame
@@ -30,8 +29,6 @@ from pipecat.services.openai.tts import OpenAITTSService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy
from pipecat.turns.user_turn_strategies import UserTurnStrategies
load_dotenv(override=True)
@@ -76,12 +73,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
context = LLMContext(messages)
user_aggregator, assistant_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
user_turn_strategies=UserTurnStrategies(
stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())]
),
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
),
user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()),
)
pipeline = Pipeline(

View File

@@ -10,7 +10,6 @@ import os
from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.frames.frames import LLMRunFrame
from pipecat.pipeline.pipeline import Pipeline
@@ -30,8 +29,6 @@ from pipecat.transcriptions.language import Language
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy
from pipecat.turns.user_turn_strategies import UserTurnStrategies
load_dotenv(override=True)
@@ -81,12 +78,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
context = LLMContext(messages)
user_aggregator, assistant_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
user_turn_strategies=UserTurnStrategies(
stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())]
),
vad_analyzer=SileroVADAnalyzer(),
),
user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()),
)
pipeline = Pipeline(

View File

@@ -11,7 +11,6 @@ import time
from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.frames.frames import LLMRunFrame
from pipecat.pipeline.pipeline import Pipeline
@@ -30,8 +29,6 @@ from pipecat.services.openpipe.llm import OpenPipeLLMService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy
from pipecat.turns.user_turn_strategies import UserTurnStrategies
load_dotenv(override=True)
@@ -80,12 +77,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
context = LLMContext(messages)
user_aggregator, assistant_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
user_turn_strategies=UserTurnStrategies(
stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())]
),
vad_analyzer=SileroVADAnalyzer(),
),
user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()),
)
pipeline = Pipeline(

View File

@@ -11,7 +11,6 @@ import aiohttp
from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.frames.frames import LLMRunFrame
from pipecat.pipeline.pipeline import Pipeline
@@ -30,8 +29,6 @@ from pipecat.services.xtts.tts import XTTSService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy
from pipecat.turns.user_turn_strategies import UserTurnStrategies
load_dotenv(override=True)
@@ -78,14 +75,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
context = LLMContext(messages)
user_aggregator, assistant_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
user_turn_strategies=UserTurnStrategies(
stop=[
TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())
]
),
vad_analyzer=SileroVADAnalyzer(),
),
user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()),
)
pipeline = Pipeline(

View File

@@ -10,7 +10,6 @@ import os
from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.frames.frames import LLMRunFrame
from pipecat.pipeline.pipeline import Pipeline
@@ -31,8 +30,6 @@ from pipecat.transcriptions.language import Language
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy
from pipecat.turns.user_turn_strategies import UserTurnStrategies
load_dotenv(override=True)
@@ -84,12 +81,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
context = LLMContext(messages)
user_aggregator, assistant_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
user_turn_strategies=UserTurnStrategies(
stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())]
),
vad_analyzer=SileroVADAnalyzer(),
),
user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()),
)
pipeline = Pipeline(

View File

@@ -10,7 +10,6 @@ import os
from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.frames.frames import LLMRunFrame
from pipecat.pipeline.pipeline import Pipeline
@@ -29,8 +28,6 @@ from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy
from pipecat.turns.user_turn_strategies import UserTurnStrategies
load_dotenv(override=True)
@@ -71,12 +68,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
context = LLMContext(messages)
user_aggregator, assistant_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
user_turn_strategies=UserTurnStrategies(
stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())]
),
vad_analyzer=SileroVADAnalyzer(),
),
user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()),
)
pipeline = Pipeline(

View File

@@ -10,7 +10,6 @@ import os
from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.frames.frames import LLMRunFrame
from pipecat.pipeline.pipeline import Pipeline
@@ -29,8 +28,6 @@ from pipecat.services.groq.tts import GroqTTSService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy
from pipecat.turns.user_turn_strategies import UserTurnStrategies
load_dotenv(override=True)
@@ -73,12 +70,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
context = LLMContext(messages)
user_aggregator, assistant_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
user_turn_strategies=UserTurnStrategies(
stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())]
),
vad_analyzer=SileroVADAnalyzer(),
),
user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()),
)
pipeline = Pipeline(

View File

@@ -8,7 +8,6 @@
from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.frames.frames import LLMMessagesAppendFrame
from pipecat.pipeline.pipeline import Pipeline
@@ -27,8 +26,6 @@ from pipecat.services.aws.tts import AWSPollyTTSService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy
from pipecat.turns.user_turn_strategies import UserTurnStrategies
# Strands agent setup
try:
@@ -118,12 +115,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
context = LLMContext()
user_aggregator, assistant_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
user_turn_strategies=UserTurnStrategies(
stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())]
),
vad_analyzer=SileroVADAnalyzer(),
),
user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()),
)
pipeline = Pipeline(

View File

@@ -8,7 +8,6 @@
from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.frames.frames import LLMRunFrame
from pipecat.pipeline.pipeline import Pipeline
@@ -27,8 +26,6 @@ from pipecat.services.aws.tts import AWSPollyTTSService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy
from pipecat.turns.user_turn_strategies import UserTurnStrategies
load_dotenv(override=True)
@@ -77,12 +74,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
context = LLMContext(messages)
user_aggregator, assistant_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
user_turn_strategies=UserTurnStrategies(
stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())]
),
vad_analyzer=SileroVADAnalyzer(),
),
user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()),
)
pipeline = Pipeline(

View File

@@ -25,7 +25,6 @@ import os
from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.frames.frames import LLMRunFrame
from pipecat.pipeline.pipeline import Pipeline
@@ -44,8 +43,6 @@ from pipecat.services.google.tts import GoogleTTSService
from pipecat.transcriptions.language import Language
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy
from pipecat.turns.user_turn_strategies import UserTurnStrategies
load_dotenv(override=True)
@@ -99,12 +96,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
context = LLMContext(messages)
user_aggregator, assistant_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
user_turn_strategies=UserTurnStrategies(
stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())]
),
vad_analyzer=SileroVADAnalyzer(),
),
user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()),
)
pipeline = Pipeline(

View File

@@ -10,7 +10,6 @@ import os
from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.frames.frames import LLMRunFrame
from pipecat.pipeline.pipeline import Pipeline
@@ -30,8 +29,6 @@ from pipecat.transcriptions.language import Language
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy
from pipecat.turns.user_turn_strategies import UserTurnStrategies
load_dotenv(override=True)
@@ -104,12 +101,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
context = LLMContext(messages)
user_aggregator, assistant_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
user_turn_strategies=UserTurnStrategies(
stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())]
),
vad_analyzer=SileroVADAnalyzer(),
),
user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()),
)
pipeline = Pipeline(

View File

@@ -10,7 +10,6 @@ import os
from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.frames.frames import LLMRunFrame
from pipecat.pipeline.pipeline import Pipeline
@@ -30,8 +29,6 @@ from pipecat.transcriptions.language import Language
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy
from pipecat.turns.user_turn_strategies import UserTurnStrategies
load_dotenv(override=True)
@@ -87,12 +84,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
context = LLMContext(messages)
user_aggregator, assistant_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
user_turn_strategies=UserTurnStrategies(
stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())]
),
vad_analyzer=SileroVADAnalyzer(),
),
user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()),
)
pipeline = Pipeline(

View File

@@ -10,7 +10,6 @@ import os
from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.frames.frames import LLMRunFrame
from pipecat.pipeline.pipeline import Pipeline
@@ -30,8 +29,6 @@ from pipecat.transcriptions.language import Language
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy
from pipecat.turns.user_turn_strategies import UserTurnStrategies
load_dotenv(override=True)
@@ -87,12 +84,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
context = LLMContext(messages)
user_aggregator, assistant_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
user_turn_strategies=UserTurnStrategies(
stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())]
),
vad_analyzer=SileroVADAnalyzer(),
),
user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()),
)
pipeline = Pipeline(

View File

@@ -10,7 +10,6 @@ import os
from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.frames.frames import LLMRunFrame
from pipecat.pipeline.pipeline import Pipeline
@@ -29,8 +28,6 @@ from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy
from pipecat.turns.user_turn_strategies import UserTurnStrategies
load_dotenv(override=True)
@@ -77,12 +74,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
context = LLMContext(messages)
user_aggregator, assistant_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
user_turn_strategies=UserTurnStrategies(
stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())]
),
vad_analyzer=SileroVADAnalyzer(),
),
user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()),
)
pipeline = Pipeline(

View File

@@ -47,8 +47,6 @@ from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy
from pipecat.turns.user_turn_strategies import UserTurnStrategies
load_dotenv(override=True)

View File

@@ -11,7 +11,6 @@ from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.filters.krisp_filter import KrispFilter
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.frames.frames import LLMRunFrame
from pipecat.pipeline.pipeline import Pipeline
@@ -30,8 +29,6 @@ from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy
from pipecat.turns.user_turn_strategies import UserTurnStrategies
load_dotenv(override=True)
@@ -75,12 +72,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
context = LLMContext(messages)
user_aggregator, assistant_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
user_turn_strategies=UserTurnStrategies(
stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())]
),
vad_analyzer=SileroVADAnalyzer(),
),
user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()),
)
pipeline = Pipeline(

View File

@@ -11,7 +11,6 @@ import aiohttp
from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.frames.frames import LLMRunFrame
from pipecat.pipeline.pipeline import Pipeline
@@ -30,8 +29,6 @@ from pipecat.services.rime.tts import RimeHttpTTSService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy
from pipecat.turns.user_turn_strategies import UserTurnStrategies
load_dotenv(override=True)
@@ -80,14 +77,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
context = LLMContext(messages)
user_aggregator, assistant_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
user_turn_strategies=UserTurnStrategies(
stop=[
TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())
]
),
vad_analyzer=SileroVADAnalyzer(),
),
user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()),
)
pipeline = Pipeline(

View File

@@ -10,7 +10,6 @@ import os
from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.frames.frames import LLMRunFrame
from pipecat.pipeline.pipeline import Pipeline
@@ -29,8 +28,6 @@ from pipecat.services.rime.tts import RimeTTSService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy
from pipecat.turns.user_turn_strategies import UserTurnStrategies
load_dotenv(override=True)
@@ -59,7 +56,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
tts = RimeTTSService(
api_key=os.getenv("RIME_API_KEY", ""),
voice_id="rex",
voice_id="luna",
)
llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"))
@@ -74,12 +71,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
context = LLMContext(messages)
user_aggregator, assistant_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
user_turn_strategies=UserTurnStrategies(
stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())]
),
vad_analyzer=SileroVADAnalyzer(),
),
user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()),
)
pipeline = Pipeline(

View File

@@ -10,7 +10,6 @@ import os
from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.frames.frames import LLMRunFrame
from pipecat.pipeline.pipeline import Pipeline
@@ -29,8 +28,6 @@ from pipecat.services.nvidia.tts import NvidiaTTSService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy
from pipecat.turns.user_turn_strategies import UserTurnStrategies
load_dotenv(override=True)
@@ -73,12 +70,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
context = LLMContext(messages)
user_aggregator, assistant_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
user_turn_strategies=UserTurnStrategies(
stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())]
),
vad_analyzer=SileroVADAnalyzer(),
),
user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()),
)
pipeline = Pipeline(

View File

@@ -12,7 +12,6 @@ from dotenv import load_dotenv
from google.genai.types import Content, Part
from loguru import logger
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.frames.frames import (
Frame,
@@ -43,8 +42,6 @@ from pipecat.transcriptions.language import Language
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy
from pipecat.turns.user_turn_strategies import UserTurnStrategies
load_dotenv(override=True)
@@ -246,12 +243,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
context = LLMContext(messages)
user_aggregator, assistant_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
user_turn_strategies=UserTurnStrategies(
stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())]
),
vad_analyzer=SileroVADAnalyzer(),
),
user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()),
)
audio_collector = UserAudioCollector(context, user_aggregator)
pull_transcript_out_of_llm_output = TranscriptExtractor(context)

View File

@@ -10,7 +10,6 @@ import os
from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.frames.frames import LLMRunFrame
from pipecat.pipeline.pipeline import Pipeline
@@ -29,8 +28,6 @@ from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy
from pipecat.turns.user_turn_strategies import UserTurnStrategies
load_dotenv(override=True)
@@ -75,12 +72,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
context = LLMContext(messages)
user_aggregator, assistant_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
user_turn_strategies=UserTurnStrategies(
stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())]
),
vad_analyzer=SileroVADAnalyzer(),
),
user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()),
)
pipeline = Pipeline(

View File

@@ -11,7 +11,6 @@ import aiohttp
from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.frames.frames import LLMRunFrame
from pipecat.pipeline.pipeline import Pipeline
@@ -30,8 +29,6 @@ from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy
from pipecat.turns.user_turn_strategies import UserTurnStrategies
load_dotenv(override=True)
@@ -79,14 +76,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
context = LLMContext(messages)
user_aggregator, assistant_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
user_turn_strategies=UserTurnStrategies(
stop=[
TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())
]
),
vad_analyzer=SileroVADAnalyzer(),
),
user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()),
)
pipeline = Pipeline(

View File

@@ -10,7 +10,6 @@ import os
from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.frames.frames import LLMRunFrame
from pipecat.pipeline.pipeline import Pipeline
@@ -29,8 +28,6 @@ from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy
from pipecat.turns.user_turn_strategies import UserTurnStrategies
load_dotenv(override=True)
@@ -74,12 +71,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
context = LLMContext(messages)
user_aggregator, assistant_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
user_turn_strategies=UserTurnStrategies(
stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())]
),
vad_analyzer=SileroVADAnalyzer(),
),
user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()),
)
pipeline = Pipeline(

View File

@@ -10,7 +10,6 @@ import os
from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.frames.frames import LLMRunFrame
from pipecat.pipeline.pipeline import Pipeline
@@ -29,8 +28,6 @@ from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy
from pipecat.turns.user_turn_strategies import UserTurnStrategies
load_dotenv(override=True)
@@ -77,12 +74,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
context = LLMContext(messages)
user_aggregator, assistant_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
user_turn_strategies=UserTurnStrategies(
stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())]
),
vad_analyzer=SileroVADAnalyzer(),
),
user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()),
)
pipeline = Pipeline(

View File

@@ -11,7 +11,6 @@ import sys
from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.frames.frames import LLMRunFrame
from pipecat.pipeline.pipeline import Pipeline
@@ -26,8 +25,6 @@ from pipecat.services.cartesia.tts import CartesiaTTSService
from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.local.audio import LocalAudioTransport, LocalAudioTransportParams
from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy
from pipecat.turns.user_turn_strategies import UserTurnStrategies
load_dotenv(override=True)
@@ -62,12 +59,7 @@ async def main():
context = LLMContext(messages)
user_aggregator, assistant_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
user_turn_strategies=UserTurnStrategies(
stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())]
),
vad_analyzer=SileroVADAnalyzer(),
),
user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()),
)
pipeline = Pipeline(

View File

@@ -11,7 +11,6 @@ import aiohttp
from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.frames.frames import LLMRunFrame
from pipecat.pipeline.pipeline import Pipeline
@@ -31,8 +30,6 @@ from pipecat.transcriptions.language import Language
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy
from pipecat.turns.user_turn_strategies import UserTurnStrategies
load_dotenv(override=True)
@@ -81,14 +78,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
context = LLMContext(messages)
user_aggregator, assistant_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
user_turn_strategies=UserTurnStrategies(
stop=[
TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())
]
),
vad_analyzer=SileroVADAnalyzer(),
),
user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()),
)
pipeline = Pipeline(

View File

@@ -11,7 +11,6 @@ import aiohttp
from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.frames.frames import LLMRunFrame
from pipecat.pipeline.pipeline import Pipeline
@@ -31,8 +30,6 @@ from pipecat.transcriptions.language import Language
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy
from pipecat.turns.user_turn_strategies import UserTurnStrategies
load_dotenv(override=True)
@@ -83,14 +80,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
context = LLMContext(messages)
user_aggregator, assistant_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
user_turn_strategies=UserTurnStrategies(
stop=[
TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())
]
),
vad_analyzer=SileroVADAnalyzer(),
),
user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()),
)
pipeline = Pipeline(

View File

@@ -9,7 +9,6 @@ import os
from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.frames.frames import LLMRunFrame
from pipecat.pipeline.pipeline import Pipeline
@@ -28,8 +27,6 @@ from pipecat.services.sarvam.tts import SarvamTTSService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy
from pipecat.turns.user_turn_strategies import UserTurnStrategies
load_dotenv(override=True)
@@ -77,12 +74,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
context = LLMContext(messages)
user_aggregator, assistant_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
user_turn_strategies=UserTurnStrategies(
stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())]
),
vad_analyzer=SileroVADAnalyzer(),
),
user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()),
)
pipeline = Pipeline(

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