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Documentation •
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Welcome to TEN
TEN is an open-source framework for real-time multimodal conversational AI.
TEN Ecosystem includes TEN Framework, Agent Examples, VAD, Turn Detection and Portal.
| Community Channel | Purpose |
|---|
| Follow TEN Framework on X for updates and announcements |
| Join our Discord community to connect with developers |
| Follow TEN Framework on LinkedIn for updates and announcements |
| Join our Hugging Face community to explore our spaces and models |
Agent Examples
Multi-Purpose Voice Assistant — This low-latency, high-quality real-time assistant supports both RTC and WebSocket connections, and you can extend it with Memory, VAD, Turn Detection, and other extensions.
See the Example code for more details.
Doodler — A doodle board that turns spoken or typed prompts into simple hand-drawn sketches, complete with a crayon palette and real-time drawing.
Example code
Speaker Diarization — Real-time diarization that detects and labels speakers, the Who Likes What game shows an interactive use case.
Example code
Lip Sync Avatars — Works with multiple avatar vendors, the main character features Kei, an anime character with MotionSync-powered lip sync, and also supports realistic avatars from Trulience, HeyGen, and Tavus.
See the Example code for different Live2D characters.
SIP Call — SIP extension that enables phone calls powered by TEN.
Example code
Transcription — A transcription tool that transcribes audio to text.
Example code
ESP32-S3 Korvo V3 — Runs TEN agent example on the Espressif ESP32-S3 Korvo V3 development board to integrate LLM-powered communication with hardware.
See the integration guide for more details.
Quick Start with Agent Examples
Localhost
Step ⓵ - Prerequisites
Step ⓶ - Build agent examples in VM
1. Clone the repo, cd into ai_agents, and create a .env file from .env.example
cd ai_agents
cp ./.env.example ./.env
2. Set up the Agora App ID and App Certificate in .env
AGORA_APP_ID=
AGORA_APP_CERTIFICATE=
# Deepgram (required for speech-to-text)
DEEPGRAM_API_KEY=
# OpenAI (required for language model)
OPENAI_API_KEY=
# ElevenLabs (required for text-to-speech)
ELEVENLABS_TTS_KEY=
3. Start agent development containers
docker compose up -d
4. Enter the container
docker exec -it ten_agent_dev bash
5. Build the agent with the default example (~5-8 min)
Check the agents/examples folder for additional samples.
Start with one of these defaults:
# use the chained voice assistant
cd agents/examples/voice-assistant
# or use the speech-to-speech voice assistant in real time
cd agents/examples/voice-assistant-realtime
6. Start the web server
Run task install before the first launch and after changing dependencies or Go source code. It installs the TEN, Python, and frontend dependencies and builds the Go API server. Python-only source changes do not require reinstalling.
task install
task run
7. Access the agent
Once the agent example is running, you can access the following interfaces:
| localhost:49483 | localhost:3000 |
|---|
| |
Step ⓷ - Customize your agent example
- Open localhost:49483.
- Right-click the STT, LLM, and TTS extensions.
- Open their properties and enter the corresponding API keys.
- Submit your changes, now you can see the updated Agent Example in localhost:3000.
Run a transcriber app from TEN Manager without Docker (Beta)
TEN also provides a transcriber app that you can run from TEN Manager without using Docker.
This is the beginning of the README. Read the rest at the original. Read the full README ↗
