wingetCollections
  • Auto
  • Search
  • Awesome Collections
  • Awesome Programs
  • My Favorite Collections
  • My Collections
  • Account / Settings
  • Terms of Service
  • Privacy
  • About

© 2026 winget.ragerworks.com

Loading...
Install tman using Winget - wingetCollections
  1. Go back
  2. Packages
  3. tman
tman logo

tman TEN Framework Team

ai cli developer-tools extension-manager multi-modal package-manager real-time ten ten-framework video voice
Use this command to install tman:
winget install --id=ten-framework.tman -e

tman: The TEN Framework Package Manager

tman serves as the official package manager for the TEN Framework, designed to streamline the management of extensions, protocols, and other components essential for real-time communication applications. Its primary purpose is to simplify the installation, updates, and integration of these elements within the framework.

Key Features:

  • Efficient Package Installation: tman allows developers to easily install and manage packages, ensuring that all necessary components are up-to-date.
  • Automatic Dependency Resolution: It automatically handles dependencies, eliminating manual conflicts and ensuring smooth operations.
  • Version Control and Updates: Developers can effortlessly manage package versions and receive updates, keeping their projects current with the latest features.

Audience & Benefits: Ideal for developers building real-time applications, tman significantly enhances development efficiency. By providing seamless integration and easy access to a diverse range of packages, it empowers developers to focus on innovation while leveraging community contributions. Whether through CLI or within project setups, tman ensures projects are built faster and more effectively.

Install tman via winget to start managing your TEN Framework components with ease.

README

Image

TEN Releases Coverage Status Release Date Commits Issues closed Contributors GitHub license Ask DeepWiki ReadmeX

README in English 简体中文操作指南 日本語のREADME README in 한국어 README en Español

Versions
0.11.53
0.11.52
0.11.51
0.11.50
0.11.49
0.11.48
0.11.47
0.11.46
0.11.45
0.11.42
Website
github.com
License
Last updated
2/4/2026
Download latest version
README en Français
README in Italiano

TEN-framework%2Ften_framework | Trendshift

Official Site • Documentation • Blog

Table of Contents

  • Welcome to TEN
  • Agent Examples
  • Quick Start with Agent Examples
    • Localhost
    • Codespaces
  • Agent Examples Self-Hosting
    • Deploying with Docker
    • Deploying with other cloud services
  • Stay Tuned
  • TEN Ecosystem
  • Questions
  • Contributing
    • Code Contributors
    • Contribution Guidelines
    • License

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 ChannelPurpose
Follow on XFollow TEN Framework on X for updates and announcements
Discord TEN CommunityJoin our Discord community to connect with developers
Follow on LinkedInFollow TEN Framework on LinkedIn for updates and announcements
Hugging Face SpaceJoin our Hugging Face community to explore our spaces and models
WeChatJoin our WeChat group for Chinese community discussions

Agent Examples

Image

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.

divider divider

Image

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

divider divider

Image

Speaker Diarization — Real-time diarization that detects and labels speakers, the Who Likes What game shows an interactive use case.

Example code

divider divider

Image

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.

divider divider

Image

SIP Call — SIP extension that enables phone calls powered by TEN.

Example code

divider divider

Image

Transcription — A transcription tool that transcribes audio to text.

Example code

divider divider

Image

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

CategoryRequirements
Keys• Agora App ID and App Certificate• OpenAI API key• Deepgram ASR • ElevenLabs TTS
Installation• Docker / Docker Compose• Node.js (LTS) v18
Minimum System Requirements• CPU >= 2 cores• RAM >= 4 GB

divider divider

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 build if you changed any local source code. This step is required for compiled languages (for example, TypeScript or Go) and not needed for Python.

task install
task run
7. Access the agent

Once the agent example is running, you can access the following interfaces:

localhost:49483localhost:3000
Screenshot 1Screenshot 2
  • TMAN Designer: localhost:49483
  • Agent Examples UI: localhost:3000

divider divider

Step ⓷ - Customize your agent example

  1. Open localhost:49483.
  2. Right-click the STT, LLM, and TTS extensions.
  3. Open their properties and enter the corresponding API keys.
  4. Submit your changes, now you can see the updated Agent Example in localhost:3000.

divider divider

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.

Check the quick start guide for more details.

divider divider

Codespaces

GitHub offers free Codespaces for each repository. You can run Agent Examples in Codespaces without using Docker. Codespaces typically start faster than local Docker environments.

Check out this guide for more details.

Agent Examples Self-Hosting

Deploying with Docker

Once you have customized your agent (either by using the TMAN Designer or editing property.json directly), you can deploy it by creating a release Docker image for your service.

Release as Docker image

Note: The following commands need to be executed outside of any Docker container.

Build image
cd ai_agents
docker build -f agents/examples//Dockerfile -t example-app .
Run
docker run --rm -it --env-file .env -p 3000:3000 example-app

divider divider

Deploying with other cloud services

You can split the deployment into two pieces when you want to host TEN on providers such as Vercel or Netlify.

  1. Run the TEN backend on any container-friendly platform (a VM with Docker, Fly.io, Render, ECS, Cloud Run, or similar). Use the example Docker image without modifying it and expose port 8080 from that service.

  2. Deploy only the frontend to Vercel or Netlify. Point the project root to ai_agents/agents/examples//frontend, run pnpm install (or bun install) followed by pnpm build (or bun run build), and keep the default .next output directory.

  3. Configure environment variables in your hosting dashboard so that AGENT_SERVER_URL points to the backend URL, and add any NEXT_PUBLIC_* keys the UI needs (for example, Agora credentials you surface to the browser).

  4. Ensure your backend accepts requests from the frontend origin — via open CORS or by using the built-in proxy middleware.

With this setup, the backend handles long-running worker processes, while the hosted frontend simply forwards API traffic to it.

Stay Tuned

Get instant notifications for new releases and updates. Your support helps us grow and improve TEN!

Image

TEN Ecosystem

ProjectPreview
️TEN FrameworkOpen-source framework for conversational AI Agents.
TEN VADLow-latency, lightweight and high-performance streaming voice activity detector (VAD).
️ TEN Turn DetectionTEN Turn Detection enables full-duplex dialogue communication.
TEN Agent ExamplesUsecases powered by TEN.
TEN PortalThe official site of the TEN Framework with documentation and a blog.

Questions

TEN Framework is available on these AI-powered Q&A platforms. They can help you find answers quickly and accurately in multiple languages, covering everything from basic setup to advanced implementation details.

ServiceLink
DeepWikiAsk DeepWiki
ReadmeXReadmeX

Contributing

We welcome all forms of open-source collaboration! Whether you're fixing bugs, adding features, improving documentation, or sharing ideas, your contributions help advance personalized AI tools. Check out our GitHub Issues and Projects to find ways to contribute and show your skills. Together, we can build something amazing!

> [!TIP] > > Welcome all kinds of contributions 🙏 > > Join us in building TEN better! Every contribution makes a difference, from code to documentation. Share your TEN Agent projects on social media to inspire others! > > Connect with one of the TEN maintainers @elliotchen200 on 𝕏 or @cyfyifanchen on GitHub for project updates, discussions, and collaboration opportunities.

divider divider

Code Contributors

TEN

Contribution Guidelines

Contributions are welcome! Please read the contribution guidelines first.

divider divider

License

  1. The entire TEN framework (except for the folders explicitly listed below) is released pursuant the Apache License, Version 2.0, with additional restrictions. For details, please refer to the LICENSE file located in the root directory of the TEN framework.

  2. The components within the packages directory are released under the Apache License, Version 2.0. For details, please refer to the LICENSE file located in each package's root directory.

  3. The third-party libraries used by the TEN framework are listed and described in detail. For more information, please refer to the third_party folder.