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Voice Agent WebRTC + LangGraph (Quick Start)
This example launches a complete voice agent stack:
- LangGraph dev server for local agents
- Pipecat-based speech pipeline (WebRTC, ASR, LLM adapter, TTS)
- Static UI you can open in a browser
1) Mandatory environment variables
Create .env next to this README (or copy from env.example) and set at least:
NVIDIA_API_KEYorRIVA_API_KEY: required for NVIDIA NIM-hosted Riva ASR/TTSUSE_LANGGRAPH=true: enable LangGraph-backed LLMLANGGRAPH_BASE_URL(defaulthttp://127.0.0.1:2024)LANGGRAPH_ASSISTANT(defaultace-base-agent)USER_EMAIL(any email for routing, e.g.test@example.com)LANGGRAPH_STREAM_MODE(defaultvalues)LANGGRAPH_DEBUG_STREAM(defaulttrue)
Optional but commonly used:
RIVA_ASR_LANGUAGE(defaulten-US)RIVA_TTS_LANGUAGE(defaulten-US)RIVA_TTS_VOICE_ID(e.g.Magpie-ZeroShot.Female-1)RIVA_TTS_MODEL(e.g.magpie_tts_ensemble-Magpie-ZeroShot)ZERO_SHOT_AUDIO_PROMPTif using Magpie Zero‑shot and a custom voice promptZERO_SHOT_AUDIO_PROMPT_URLto auto-download prompt on startupENABLE_SPECULATIVE_SPEECH(defaulttrue)- TURN/Twilio for WebRTC if needed:
TWILIO_ACCOUNT_SID,TWILIO_AUTH_TOKEN, orTURN_SERVER_URL,TURN_USERNAME,TURN_PASSWORD
2) What it does
- Starts LangGraph dev server to serve local agents from
agents/. - Starts the Pipecat pipeline (
pipeline.py) exposing:- HTTP:
http://<host>:7860(health and RTC config) - WebSocket:
ws://<host>:7860/wsfor audio and transcripts
- HTTP:
- Serves the built UI at
http://<host>:9000/(via the container).
By default it uses:
- ASR: NVIDIA Riva (NIM) with
RIVA_API_KEYandNVIDIA_ASR_FUNCTION_ID - LLM: LangGraph adapter streaming from the selected assistant
- TTS: NVIDIA Riva Magpie (NIM) with
RIVA_API_KEYandNVIDIA_TTS_FUNCTION_ID
3) Run
Option A: Docker (recommended)
From this directory:
docker compose up --build -d
Then open http://<machine-ip>:9000/.
Chrome on http origins: enable “Insecure origins treated as secure” at chrome://flags/ and add http://<machine-ip>:9000.
Option B: Python (local)
Requires Python 3.12 and uv.
uv run pipeline.py
Then start the UI from ui/ (see ui/README.md).
4) Swap TTS providers (Magpie ⇄ ElevenLabs)
The default TTS in pipeline.py is NVIDIA Riva Magpie via NIM:
tts = RivaTTSService(
api_key=os.getenv("RIVA_API_KEY"),
function_id=os.getenv("NVIDIA_TTS_FUNCTION_ID", "4e813649-d5e4-4020-b2be-2b918396d19d"),
voice_id=os.getenv("RIVA_TTS_VOICE_ID", "Magpie-ZeroShot.Female-1"),
model=os.getenv("RIVA_TTS_MODEL", "magpie_tts_ensemble-Magpie-ZeroShot"),
language=os.getenv("RIVA_TTS_LANGUAGE", "en-US"),
zero_shot_audio_prompt_file=(
Path(os.getenv("ZERO_SHOT_AUDIO_PROMPT")) if os.getenv("ZERO_SHOT_AUDIO_PROMPT") else None
),
)
To use ElevenLabs instead:
- Ensure
pipecatElevenLabs dependency is available (already included via project deps). - Set environment:
ELEVENLABS_API_KEY- Optionally
ELEVENLABS_VOICE_IDand model settings supported by ElevenLabs
- Change the TTS construction in
pipeline.pyto useElevenLabsTTSServiceWithEndOfSpeech:
from nvidia_pipecat.services.elevenlabs import ElevenLabsTTSServiceWithEndOfSpeech
# Replace RivaTTSService(...) with:
tts = ElevenLabsTTSServiceWithEndOfSpeech(
api_key=os.getenv("ELEVENLABS_API_KEY"),
voice_id=os.getenv("ELEVENLABS_VOICE_ID", "Rachel"),
sample_rate=16000,
channels=1,
)
That’s it. No other pipeline changes are required. The transcript synchronization already supports ElevenLabs end‑of‑speech events.
Notes for Magpie Zero‑shot:
- Provide
RIVA_TTS_VOICE_IDlikeMagpie-ZeroShot.Female-1andRIVA_TTS_MODELlikemagpie_tts_ensemble-Magpie-ZeroShot. - If using a custom voice prompt, mount it via
docker-compose.ymland setZERO_SHOT_AUDIO_PROMPT. You can also setZERO_SHOT_AUDIO_PROMPT_URLto auto-download at startup.
5) Troubleshooting
- Healthcheck:
curl -f http://localhost:7860/get_prompt - If UI can’t access mic on http, use Chrome flag above or host UI via HTTPS.
- For NAT/firewall issues, configure TURN or Twilio credentials.