Skip to main content

Minimalist Python framework for building AI agents

Project description

AgentFlow

AgentFlow Logo

Tests Python 3.9+ License: MIT PyPI

The minimalist Python framework for building AI agents

AgentFlow is a production-ready framework that makes building AI agents simple, testable, and extensible. Inspired by FastAPI's philosophy of developer experience first.

🚀 Key Features

  • 🧪 Best-in-class Testing - MockModel + AgentTestClient (FastAPI-inspired)
  • 🔌 Native MCP Support - First Python framework with MCP integration
  • ⚡ Async-First - Built on asyncio for maximum performance
  • 🛡️ Production-Ready - Robust loop with JSON auto-repair, timeout protection, loop detection
  • 🔧 Tool Ecosystem - Mix local Python tools with MCP servers seamlessly
  • 📦 Multi-LLM - Ollama, OpenAI, Mistral support out of the box
  • 💾 Flexible Memory - InMemory and FileMemory with custom backend support

📥 Installation

pip install agentflow

⚡ Quick Start

Basic Usage

import asyncio
from agentflow import Agent

async def main():
    agent = Agent(model="llama3")
    response = await agent.arun("What is Python?")
    print(response)

asyncio.run(main())

With Tools

agent = Agent(model="gpt-4o")

@agent.tool
def calculate(expression: str) -> float:
    """Evaluate a mathematical expression."""
    return eval(expression)

response = await agent.arun("What is 123 * 456?")

With MCP Servers

from agentflow.mcp import MCPClient

# Connect to filesystem server
async with MCPClient(
    transport="stdio",
    command=["npx", "@modelcontextprotocol/server-filesystem", "/tmp"]
) as mcp:
    await agent.add_mcp_tools(mcp)
    response = await agent.arun("List files in /tmp")

🧪 Testing (Killer Feature)

from agentflow.testing import MockModel, AgentTestClient

# Test without real LLM calls
model = MockModel(responses=["Hello! I'm an AI assistant."])
agent = Agent(model=model)
client = AgentTestClient(agent)

response = client.run("Hello")
client.assert_response_contains("Hello")
client.assert_tool_called("my_tool")

🆚 Why AgentFlow?

Feature AgentFlow LangChain CrewAI AutoGen
Easy Testing ✅ MockModel + TestClient
Native MCP ✅ First framework
Async-First Partial
Minimalist ✅ <700 LOC core
Production-Ready ✅ v1.0 Partial Partial

📚 Documentation & Examples

  • Documentation - Comprehensive guides and API reference
  • Examples - 8 complete examples covering all features

🏗️ Architecture

AgentFlow follows these principles:

  • Explicit > Magic - Clear APIs, no hidden behavior
  • Minimal by default - Start simple, add complexity when needed
  • Testable - Built-in mocking and assertion helpers
  • Async-first - Non-blocking I/O for performance

🔧 Requirements

  • Python 3.9+
  • httpx

📄 License

MIT License - see LICENSE file for details.

🙏 Credits

Created by Hamadi Chaabani

Inspired by:

  • FastAPI's developer experience
  • Anthropic's MCP vision
  • The Python async ecosystem

🔗 Ecosystem

⭐ Star History

If you find AgentFlow useful, please star it on GitHub!


AgentFlow v1.0 - Production-ready. Fully tested. Simply powerful.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

agentflow_ai-1.0.0.tar.gz (16.6 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

agentflow_ai-1.0.0-py3-none-any.whl (14.0 kB view details)

Uploaded Python 3

File details

Details for the file agentflow_ai-1.0.0.tar.gz.

File metadata

  • Download URL: agentflow_ai-1.0.0.tar.gz
  • Upload date:
  • Size: 16.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.10.12

File hashes

Hashes for agentflow_ai-1.0.0.tar.gz
Algorithm Hash digest
SHA256 25c60922a841d5c53b16cbbbab4cb672c70a138e15207a8e291447398dd991d2
MD5 1febd289d0e23ea3e4ea253a34932402
BLAKE2b-256 bc43c409b340112a5798aaedd1f4d9f5288a39d89e81369a240afbc4accf7359

See more details on using hashes here.

File details

Details for the file agentflow_ai-1.0.0-py3-none-any.whl.

File metadata

  • Download URL: agentflow_ai-1.0.0-py3-none-any.whl
  • Upload date:
  • Size: 14.0 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.10.12

File hashes

Hashes for agentflow_ai-1.0.0-py3-none-any.whl
Algorithm Hash digest
SHA256 4c61f4634af04ed43085758fd6b2ec4ac0950f2936e3c077111500d588377c0f
MD5 a74875558d32cfea65b8bd01623341de
BLAKE2b-256 889b5318709188a4b3fb1d1e3c551d7a6323ef11da03713ec3d728c90c6cdefc

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page