0a163201ea
- Enhance TranscriptHandler to aggregate transcript fragments into complete sentences using match_endofsentence() - Add Whisker debugger integration for real-time pipeline visualization - Implement sentence buffering for both user and assistant messages - Add finalize_partial_sentences() method to handle incomplete sentences on disconnect - Improves transcript readability by reducing fragmented output Changes: - Import match_endofsentence utility for sentence boundary detection - Add pipecat_whisker.WhiskerObserver for debugging capabilities - Modify on_transcript_update() to accumulate and aggregate messages - Create _save_sentence() helper method for complete sentence handling - Update client disconnect handler to preserve partial sentences
Pipecat Foundational Examples
This directory contains examples showing how to build voice and multimodal agents with Pipecat. Each example demonstrates specific features, progressing from basic to advanced concepts.
Setup
-
Follow the README steps to get your local environment configured.
Run from root directory: Make sure you are running the steps from the root directory.
Using local audio?: The
LocalAudioTransportrequires a system dependency forportaudio. Install the dependency to use the transport. -
Copy the
env.examplefile and add API keys for services you plan to use:cp env.example .env # Edit .env with your API keys -
Navigate to the examples directory if you aren't already there:
cd examples/foundational -
Run any example:
uv run python 01-say-one-thing.py -
Open the web interface at http://localhost:7860/client/ and click "Connect"
Running examples with other transports
Most examples support running with other transports, like Twilio or Daily.
Daily
You need to create a Daily account at https://dashboard.daily.co/u/signup. Once signed up, you can create your own room from the dashboard and set the environment variables DAILY_SAMPLE_ROOM_URL and DAILY_API_KEY. Alternatively, you can let the example create a room for you (still needs DAILY_API_KEY environment variable). Then, start any example with -t daily:
uv run 07-interruptible.py -t daily
Twilio
It is also possible to run the example through a Twilio phone number. You will need to setup a few things:
- Install and run ngrok.
ngrok http 7860
- Configure your Twilio phone number. One way is to setup a TwiML app and set the request URL to the ngrok URL from step (1). Then, set your phone number to use the new TwiML app.
Then, run the example with:
uv run 07-interruptible.py -t twilio -x NGROK_HOST_NAME
Examples by Feature
Basics
- 01-say-one-thing.py: Most basic bot that says one phrase and exits (Transport, TTS, Event handlers)
- 02-llm-say-one-thing.py: Bot generates a response with an LLM (LLM initialization)
- 03-still-frame.py: Displays a static image (Video transport, Image service)
- 04-transport.py: Different transport options (WebRTC, Daily, Livekit)
Conversational AI
- 07-interruptible.py: Basic voice assistant bot (STT, TTS, LLM, Interruptible speech)
- 10-wake-phrase.py: Bot activated by wake phrase (WakeCheckFilter)
- 22-natural-conversation.py: Smart turn detection (Multiple LLMs, Turn management)
- 38-smart-turn-fal.py: ML-based turn detection (Fal service, Local models)
Common Utilities
- 17-detect-user-idle.py: Handle inactive users (UserIdleProcessor)
- 24-stt-mute-filter.py: Selectively mute user input (STTMuteFilter)
- 28-transcription-processor.py: Record conversation text (TranscriptProcessor)
- 30-observer.py: Access frame data (Custom observers)
- 31-heartbeats.py: Detect idle pipelines (Pipeline monitoring)
- 34-audio-recording.py: Record conversation audio (Composite and track-level recording)
Advanced LLM Features
- 14-function-calling.py: Bot with tool usage (Function schemas, Tool registration)
- 20a-persistent-context-openai.py: Persistent conversation context (Memory management)
- 32-gemini-grounding-metadata.py: Web search capabilities (Google search integration)
- 33-gemini-rag.py: Retrieval-augmented generation (Data sources, Grounding)
- 37-mem0.py: Long-term agent memory (Mem0 service integration)
Media Handling
- 05-sync-speech-and-images.py: Synchronized narration with images (Custom processors, SyncParallelPipeline)
- 06a-image-sync.py: Dynamic image updates while speaking (Synchronized A/V pipelines)
- 09-mirror.py: Mirror user's audio and video (Custom frame processors)
- 11-sound-effects.py: Add sounds when bot speaks (Sound playback, Event synchronization)
- 23-bot-background-sound.py: Play background audio (SoundfileMixer)
Vision & Multimodal
- 12a-describe-video-gemini-flash.py: Bot describes user's video (Video input, Multimodal LLMs)
- 26c-gemini-multimodal-live-video.py: Gemini with video input (Streaming video, Function calls)
Voice & Language
- 13-transcription.py: Speech transcription demo (STT providers, Real-time transcription)
- 15-switch-voices.py: Dynamic voice/language changing (ParallelPipelines, FunctionFilters)
- 25-google-audio-in.py: Gemini for speech recognition (Alternative transcription)
- 35-pattern-pair-voice-switching.py: Dynamic TTS voice switching (XML parsing, PatternPairAggregator)
- 36-user-email-gathering.py: Spelling mode for TTS (Confirmation patterns, XML tags)
Integration Examples
- 18-gstreamer-filesrc.py: GStreamer video streaming (Video processing)
- 19-openai-realtime-beta.py: OpenAI Speech-to-Speech (Direct S2S, Function calls)
- 21-tavus-layer-tavus-transport.py: Tavus digital twin (Avatar integration)
- 27-simli-layer.py: Simli avatar integration (Video synchronization)
Performance & Optimization
- 16-gpu-container-local-bot.py: GPU-accelerated local bot (Performance measurement)
Advanced Usage
Customizing Network Settings
uv run python <example-name> --host 0.0.0.0 --port 8080
Troubleshooting
- No audio/video: Check browser permissions for microphone and camera
- Connection errors: Verify API keys in
.envfile - Port conflicts: Use
--portto change the port
For more examples, visit our the `pipecat-examples repository.