afm-langchain 0.1.1

AFM LangChain execution backend

AFM LangChain Backend

LangChain execution backend for Agent-Flavored Markdown (AFM) agents.

This package implements the AgentRunner protocol from afm-core, providing LLM orchestration using the LangChain framework.

Features

• AgentRunner Protocol Implementation: Pluggable backend for AFM agents
• LLM Provider Support: OpenAI and Anthropic models
• MCP Tool Integration: Connect external tools via Model Context Protocol
• Conversation Management: Session history and state management
• Plugin Registration: Auto-discovered via Python entry points

Installation

This package is typically installed as part of afm-cli. For LangChain-specific use:

pip install afm-langchain

Supported Providers

OpenAI

model:
  provider: openai
  name: gpt-4o  # or other OpenAI models

Requires: OPENAI_API_KEY environment variable

Anthropic

model:
  provider: anthropic
  name: claude-sonnet-4-5  # or other Claude models

Requires: ANTHROPIC_API_KEY environment variable

Development

Setup

This project uses uv for dependency management.

# Clone the repository
git clone https://github.com/wso2/reference-implementations-afm.git
cd python-interpreter

# Install dependencies
uv sync

# Activate the virtual environment
source .venv/bin/activate

Running Tests

# Run afm-langchain tests
uv run pytest packages/afm-langchain/tests/

# Run with coverage
uv run pytest packages/afm-langchain/tests/ --cov=afm_langchain

Code Quality

# Format code
uv run ruff format

# Lint code
uv run ruff check

Project Structure

packages/afm-langchain/src/afm_langchain/
├── __init__.py
├── backend.py          # LangChainRunner implementation
├── model_factory.py    # LLM provider factory
├── mcp_manager.py      # MCP tool management
└── tools_adapter.py    # Tool calling adapter

Usage

The LangChain backend is automatically registered and used when you run an AFM agent:

from afm.runner import get_runner

# Get the LangChain runner
runner = get_runner("langchain")

# Run an agent
result = await runner.run(agent, user_input)

Documentation

For comprehensive documentation, see the project README.

License

Apache-2.0