---
title: TherapyNote
app_file: app.py
sdk: gradio
sdk_version: 5.9.0
organization: pxpab
---
# Therapy Session Analysis Pipeline

A Python project that downloads YouTube therapy session captions and extracts structured information using LLMs, LangChain, and LangGraph.

## Features

- Downloads captions from YouTube therapy sessions
- Extracts structured information using LLMs and LangChain
- Supports multiple note formats (SOAP, DAP, BIRP, etc.)
- Uses LangGraph for data extraction workflows
- Manages prompts in a dedicated "langhub" directory
- Integrates with LangSmith for conversation and run logging

## Prerequisites

- Python 3.9+
- uv package manager
- OpenAI API key
- LangChain API key (for logging)

## Installation

1. Clone the repository:
```bash
git clone https://github.com/yourusername/therapy-session-analysis.git
cd therapy-session-analysis
```

2. Install dependencies using uv:
```bash
uv pip install -r requirements.txt
```

3. Set up environment variables:
```bash
export OPENAI_API_KEY="your-openai-key"
export LANGCHAIN_API_KEY="your-langchain-key"
export LANGCHAIN_TRACING_V2="true"
```

## Project Structure

```
project/
├── config/
│   ├── __init__.py
│   └── settings.py
├── langhub/
│   ├── __init__.py
│   └── prompts/
│       ├── __init__.py
│       └── therapy_extraction_prompt.yaml
├── forms/
│   ├── __init__.py
│   └── schemas.py
├── utils/
│   ├── __init__.py
│   ├── youtube.py
│   └── text_processing.py
├── models/
│   ├── __init__.py
│   └── llm_provider.py
├── main.py
├── requirements.txt
└── README.md
```

## Usage

Run the main script:
```bash
python main.py
```

## Note Formats

The system supports multiple therapy note formats:
- SOAP (Subjective, Objective, Assessment, Plan)
- DAP (Data, Assessment, Plan)
- BIRP (Behavior, Intervention, Response, Plan)
- And more...

## Contributing

1. Fork the repository
2. Create your feature branch (`git checkout -b feature/amazing-feature`)
3. Commit your changes (`git commit -m 'Add some amazing feature'`)
4. Push to the branch (`git push origin feature/amazing-feature`)
5. Open a Pull Request

## License

This project is licensed under the MIT License - see the LICENSE file for details.