AgenticFleet

Self-optimizing multi-agent orchestration powered by DSPy + Microsoft Agent Framework.

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Project Name and Description

AgenticFleet is a production-ready multi-agent orchestration runtime that routes tasks to specialized agents through a five-phase pipeline (analysis → routing → execution → progress → quality). It combines DSPy for structured reasoning with the Microsoft Agent Framework for reliable execution, streaming rich events to both CLI and web clients.

🛠️ Technology Stack

• Backend: Python 3.12 / 3.13, FastAPI, Typer CLI, DSPy, Microsoft Agent Framework (Magentic Fleet pattern), Pydantic v2
• Package Manager: uv (Python), npm (Frontend)
• Orchestration & Tools: ToolRegistry adapters (Tavily search, browser automation, code execution, MCP), offline-compiled DSPy modules
• Frontend: React 19, TypeScript, Vite, Tailwind CSS, Radix UI, Shadcn UI, Lucide Icons; real-time SSE/WebSocket streaming
• Infrastructure & Storage: Azure Cosmos DB (primary store), SQLite/local persistence, Docker + Docker Compose
• Observability & Evaluation: OpenTelemetry (Jaeger, Azure Monitor), Azure AI Evaluation, Langfuse; retries via Tenacity; async concurrency with AnyIO/Asyncer

📋 Requirements

• Python: 3.12 or 3.13
• Dependency Manager: uv
• Node.js: 18+ (for the frontend)
• API Keys: OpenAI API Key (required), Tavily API Key (optional, for web search)
• Optional: Docker + Docker Compose, Azure credentials for Cosmos/monitoring

🚀 Getting Started

Installation

# Clone the repository
git clone https://github.com/Qredence/agentic-fleet.git
cd agentic-fleet

# Full development setup (Python + Frontend + Pre-commit)
make dev-setup

# Or individual steps:
# make install            # Python deps via uv
# make frontend-install   # Frontend deps via npm

# Configure environment
cp .env.example .env
# Set OPENAI_API_KEY and other variables in .env

Run Commands

# Full stack development (backend + frontend)
make dev

# Backend only (port 8000)
make backend

# Frontend only (port 5173)
make frontend-dev

# Interactive CLI console
make run

# Single task via CLI
uv run agentic-fleet run -m "Research the latest advances in AI agents" --verbose

📜 Scripts

The project uses a Makefile to centralize development commands:

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