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README in English 简体中文操作指南

Documentation   •   Getting Started   •   Tutorials


Astra Agent

Astra multimodal agent

Astra is a multimodal agent powered by TEN , demonstrating its capabilities in speech, vision, and reasoning through RAG from local documentation.

Showcase Astra multimodal agent

How to build Astra locally

Prerequisites

Keys

Installation

Minimum system requirements

  • CPU >= 2 Core
  • RAM >= 4 GB

Docker setting on Apple Silicon

You will need to uncheck "Use Rosetta for x86_64/amd64 emulation on Apple Silicon" option for Docker if you are on Apple Silicon, otherwise the server is not going to work.

Docker Setting

Next step

1. Modify config files

In the root of the project, use cp command to create .env from the example.

It will be used to store information for docker compose later.

cp ./.env.example ./.env

2. Setup API keys

Open the .env file and fill in the keys and regions. This is also where you can choose to use any different extensions:

# Agora App ID and Agora App Certificate
AGORA_APP_ID=
# Leave empty unless you have enabled the certificate within the Agora account.
AGORA_APP_CERTIFICATE=

# Extension: bedrock_llm
# Extension: polly_tts
# Extension: transcribe_asr
AWS_ACCESS_KEY_ID=
AWS_SECRET_ACCESS_KEY=

# model id supported by Bedrock Converse API, the model you choose should support system prompt. https://docs.aws.amazon.com/bedrock/latest/userguide/conversation-inference.html
AWS_BEDROCK_MODEL=mistral.mistral-large-2407-v1:0

AWS_REGION=us-east-1 # the Region you're using

3. Start agent development containers

In the same directory, run the docker compose up command to compose containers:

docker compose up

Finish and verify 🎉

Astra multimodal agent

Open up http://localhost:3000 in browser to play and test the Astra agent.

Graph designer

Open up another tab go to http://localhost:3001, and use Graph Designer to create, connect and edit extensions on canvas.

TEN Graph Designer


Astra Agent Comparison

Features Astra Agent Pipecat LiveKit:KITT Vapi.ai DailyBots Play.ai
Vision
Rich TTS Support for different languages
Go support for extension
C++ support for extension
RAG support
Workflow builder for extension
Rich LLM Support
Python support for extension
Open source

Stay Tuned

Before we dive further, be sure to star our repository and get instant notifications for all new releases!

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Code Contributors

TEN


Contribution Guidelines

Contributions are welcome! Please read the contribution guidelines first.


License

This project is licensed under the Apache 2.0 License - see the LICENSE file for details.