DataChad 🤖

This is an app that let's you ask questions about any data source by leveraging embeddings, vector databases, large language models and last but not least langchains

How does it work?

1. Upload any file or enter any path or url
2. The data source is detected and loaded into text documents
3. The text documents are embedded using openai embeddings
4. The embeddings are stored as a vector dataset to activeloop's database hub
5. A langchain is created consisting of a LLM model (gpt-3.5-turbo by default) and the vector store as retriever
6. When sending questions to the bot this chain is used as context to answer your questions
7. Finally the chat history is cached locally to enable a ChatGPT like Q&A conversation

Good to know

• As default context this git repository is taken so you can directly start asking question about its functionality without chosing an own data source.
• To run locally or deploy somewhere, execute cp .env.template .env and set credentials in the newly created .env file. Other options are manually setting of system environment variables, or storing them into .streamlit/secrets.toml when hosted via streamlit.
• If you have credentials set like explained above, you can just hit submit in the authentication without reentering your credentials in the app.
• To enable Local Mode (disabled for the demo) set ENABLE_LOCAL_MODE to True in datachad/constants.py. You need to have the model binaries downloaded and stored inside ./models/
• Currently supported Local Mode OSS model is GPT4all. To add more models update datachad/models.py
• If you are running Local Mode all your data stays locally on your machine. No API calls are made. Same with the embeddings database which stores its data to ./data/
• Your data won't load? Feel free to open an Issue or PR and contribute!
• Yes, Chad in DataChad refers to the well-known meme

How does it look like?

TODO LIST

If you like to contribute, feel free to grab any task

• Refactor utils, especially the loaders
• Add option to choose model and embeddings
• Enable fully local / private mode
• Add Image caption and Audio transcription support