Metadata-Version: 2.4
Name: afm-langchain
Version: 0.1.1
Summary: AFM LangChain execution backend
License-Expression: Apache-2.0
Classifier: Development Status :: 3 - Alpha
Classifier: Programming Language :: Python :: 3.11
Requires-Dist: afm-core>=0.1.0,<0.2.0
Requires-Dist: langchain>=1.2.8
Requires-Dist: langchain-openai>=1.1.7
Requires-Dist: langchain-anthropic>=1.3.1
Requires-Dist: mcp>=1.26.0
Requires-Dist: langchain-mcp-adapters>=0.2.1
Requires-Python: >=3.11
Project-URL: Repository, https://github.com/wso2/reference-implementations-afm
Description-Content-Type: text/markdown

# AFM LangChain Backend

[![PyPI version](https://img.shields.io/pypi/v/afm-langchain.svg)](https://pypi.org/project/afm-langchain/)
[![Python version](https://img.shields.io/pypi/pyversions/afm-langchain.svg)](https://pypi.org/project/afm-langchain/)
[![License](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](https://opensource.org/licenses/Apache-2.0)

LangChain execution backend for [Agent-Flavored Markdown (AFM)](https://github.com/wso2/agent-flavored-markdown) 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:

```bash
pip install afm-langchain
```

## Supported Providers

### OpenAI

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

Requires: `OPENAI_API_KEY` environment variable

### Anthropic

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

Requires: `ANTHROPIC_API_KEY` environment variable

## Development

### Setup

This project uses [uv](https://docs.astral.sh/uv/) for dependency management.

```bash
# 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

```bash
# 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

```bash
# Format code
uv run ruff format

# Lint code
uv run ruff check
```

### Project Structure

```text
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:

```python
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](https://github.com/wso2/reference-implementations-afm/tree/main/python-interpreter).

## License

Apache-2.0
