metadata

license: mit
title: 🧠 Multi-Agent AI Assistant
sdk: docker
emoji: 💻
colorFrom: indigo
colorTo: indigo
pinned: true

🧠 Multi-Agent AI Assistant

This project is a voice- and text-based AI assistant powered by FastAPI, LangGraph, and LangChain. It supports:

🤖 Multi-agent system
🗣️ Voice input via speech-to-text
🌄 Image processing
📂 File processing
🌐 Web search, GitHub actions, weather, time, and geolocation tools
🧠 Memory-based conversation history per user
📍 Location-aware capabilities (e.g., timezone, weather)

🚀 Features

FastAPI backend with /text, /image, /voice and /file endpoints
LangGraph agents with memory, tools, and typed state
User database with persistent settings and config
Agents:
- Supervisor agent
- Deep research agent
- Coding agent
Supervisor tools:
- Web search
- Current time
- Weather
- Yahoo finance news
Deep research tools:
- Web search
- Wikipedia
- Yahoo finance news
Coder tools:
- Github toolkit
- Web search (For docs research)

🛠️ Setup Instructions

1. Environment

This project requires no manual environment configuration — all secrets are passed dynamically with each request and stored in the database.

Just run:

docker build -t multi-agent-assistant .
docker run -p 7860:7860 multi-agent-assistant

The server will launch automatically at http://localhost:7860, with all dependencies installed and configured inside the container.

📦 API Reference

`/text` – Send Text Prompt

POST /text
Form data:
- state (str): JSON-encoded state dict

`/voice` – Send Audio Prompt

POST /voice
Form data:
- state (str): JSON-encoded state dict
- file (binary): Audio file (WAV, MP3, etc.)

`/image` – Send Image Prompt

POST /image
Form data:
- state (str): JSON-encoded state dict
- file (binary): Image file (JPEG, PNG, etc.)

`/file` – Send File Prompt

POST /file
Form data:
- state (str): JSON-encoded state dict
- file (binary): Image file (PDF, TXT, etc.)

🧩 Agent State Structure

The system operates using a JSON-based shared state object passed between agents.
It follows a TypedDict schema and may contain keys such as:

{
    message: AnyMessage (message to the agent)
    user_id: str (unique user id) 
    first_name: str
    last_name: str
    assistant_name: str
    latitude: str
    longitude: str
    location: str (user-readable location)
    openweathermap_api_key: str
    github_token: str
    tavily_api_key: str
    groq_api_key: str
    clear_history: bool (True/False)
    messages: list (Filled automatically from the database) 

}

This dictionary acts as a single mutable state shared across all agent steps, allowing for data accumulation, tool responses, and message tracking.

🧠 Built With

📝 License

MIT — Feel free to use, modify, and contribute!