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- ---
- 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}},
- }
- ```
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