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.
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
-
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
- Install AgenticFleet using uv (recommended):
uv pip install agentic-fleetplaywright 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 modeThe web interface will be available at http://localhost:8001.
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]
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/callbackAgenticFleet implements comprehensive error handling:
- Graceful degradation on service failures
- Detailed error logging and reporting
- Automatic cleanup of resources
- Session state recovery
- Execution timeout management
- Python 3.10-3.12 (Python 3.13 is not yet supported)
- uv package manager (recommended)
- Azure OpenAI API access
- 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/- Installation Guide - Detailed setup instructions
- Usage Guide - How to use AgenticFleet
- API Reference - Complete API documentation
- Architecture Overview - System architecture and design
We welcome contributions! Please see our Contributing Guide for details.
For security concerns, please review our Security Policy.
This project is licensed under the Apache-2.0 License - see the LICENSE file for details.