---
title: '👨‍💻 Development'
description: 'Contribute to Embedchain framework development'
---

Thank you for your interest in contributing to the EmbedChain project! We welcome your ideas and contributions to help improve the project. Please follow the instructions below to get started:

1. **Fork the repository**: Click on the "Fork" button at the top right corner of this repository page. This will create a copy of the repository in your own GitHub account.

2. **Install the required dependencies**: Ensure that you have the necessary dependencies installed in your Python environment. You can do this by running the following command:

```bash
make install
```

3. **Make changes in the code**: Create a new branch in your forked repository and make your desired changes in the codebase.
4. **Format code**: Before creating a pull request, it's important to ensure that your code follows our formatting guidelines. Run the following commands to format the code:

```bash
make lint format
```

5. **Create a pull request**: When you are ready to contribute your changes, submit a pull request to the EmbedChain repository. Provide a clear and descriptive title for your pull request, along with a detailed description of the changes you have made.

# Tech Stack

embedchain is built on the following stack:

- [Langchain](https://github.com/hwchase17/langchain) as an LLM framework to load, chunk and index data
- [OpenAI's Ada embedding model](https://platform.openai.com/docs/guides/embeddings) to create embeddings
- [OpenAI's ChatGPT API](https://platform.openai.com/docs/guides/gpt/chat-completions-api) as LLM to get answers given the context
- [Chroma](https://github.com/chroma-core/chroma) as the vector database to store embeddings
- [gpt4all](https://github.com/nomic-ai/gpt4all) as an open source LLM
- [sentence-transformers](https://huggingface.co/sentence-transformers) as open source embedding model

## Team

### Authors

- Taranjeet Singh ([@taranjeetio](https://twitter.com/taranjeetio))
- Deshraj Yadav ([@deshrajdry](https://twitter.com/taranjeetio))

### Citation

If you utilize this repository, please consider citing it with:

```
@misc{embedchain,
  author = {Taranjeet Singh, Deshraj Yadav},
  title = {Embechain: Data platform for LLMs - Load, index, retrieve and sync any unstructured data},
  year = {2023},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/embedchain/embedchain}},
}
```
