A powerful multi-agent system for adaptive AI reasoning and automation
Project description
AgenticFleet
A powerful multi-agent system for adaptive AI reasoning and automation. AgenticFleet combines Chainlit's interactive interface with AutoGen's multi-agent capabilities to create a flexible, powerful AI assistant platform.
Core Components
AgenticFleet operates through a coordinated team of specialized agents:
-
WebSurfer: Expert web navigation agent
- Extracts information from web pages
- Captures and processes screenshots
- Provides structured summaries of findings
-
FileSurfer: File system specialist
- Searches and analyzes workspace files
- Manages file operations efficiently
- Extracts relevant information from documents
-
Coder: Development expert
- Generates and reviews code
- Implements solutions
- Maintains code quality
-
Executor: Code execution specialist
- Safely runs code in isolated workspace
- Monitors execution and handles timeouts
- Provides detailed execution feedback
Key Features
-
Multi-Agent System
- Coordinated team of specialized AI agents
- Real-time inter-agent communication
- Task planning and execution tracking
-
Interactive Interface
- Real-time streaming responses
- Code syntax highlighting
- Markdown rendering
- File upload/download support
- Progress visualization with task lists
-
Advanced Capabilities
- GitHub OAuth authentication
- Configurable agent behaviors
- Comprehensive error handling and recovery
- Multi-modal content processing (text, images)
- Execution workspace isolation
-
Developer-Friendly
- Easy-to-use CLI
- Extensive documentation
- Flexible configuration
- Active community support
Quick Start
- Install AgenticFleet using uv (recommended):
uv pip install agentic-fleet
playwright install --with-deps chromium # Optional: Install Playwright Chromium dependencies
- Copy and configure environment variables:
# Copy the example environment file
cp .env.example .env
# Open .env and update with your values
# Required: Add your Azure OpenAI credentials
# Optional: Configure OAuth settings
- Start the server:
agenticfleet start # Enable GitHub authentication
agenticfleet start --no-oauth # Default local mode
The web interface will be available at http://localhost:8001.
System Architecture
graph TD
User[Chainlit UI] -->|HTTP| App[app.py]
App --> AgentTeam[MagenticOneGroupChat]
AgentTeam --> WebSurfer
AgentTeam --> FileSurfer
AgentTeam --> Coder
AgentTeam --> Executor
WebSurfer -->|Selenium| Web[External Websites]
FileSurfer -->|OS| FileSystem[Local Files]
Executor -->|Subprocess| Code[Python/Runtime]
Configuration
The .env.example file contains all required and recommended settings:
# Required: Azure OpenAI Configuration
AZURE_OPENAI_API_KEY=your_api_key
AZURE_OPENAI_ENDPOINT=your_endpoint
AZURE_OPENAI_DEPLOYMENT=your_deployment
AZURE_OPENAI_MODEL=your_model
# Optional: OAuth Configuration
USE_OAUTH=false
OAUTH_GITHUB_CLIENT_ID=
OAUTH_GITHUB_CLIENT_SECRET=
OAUTH_REDIRECT_URI=http://localhost:8001/oauth/callback
Error Handling
AgenticFleet implements comprehensive error handling:
- Graceful degradation on service failures
- Detailed error logging and reporting
- Automatic cleanup of resources
- Session state recovery
- Execution timeout management
Development
Prerequisites
- Python 3.10-3.12 (Python 3.13 is not yet supported)
- uv package manager (recommended)
- Azure OpenAI API access
Setup
- Clone and install:
git clone https://github.com/qredence/agenticfleet.git
cd agenticfleet
pip install uv
uv pip install -e .
uv pip install -e ".[dev]"
- Run tests:
pytest tests/
Documentation
- Installation Guide - Detailed setup instructions
- Usage Guide - How to use AgenticFleet
- API Reference - Complete API documentation
- Architecture Overview - System architecture and design
Contributing
We welcome contributions! Please see our Contributing Guide for details.
Security
For security concerns, please review our Security Policy.
License
This project is licensed under the Apache-2.0 License - see the LICENSE file for details.
Support
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