dchat is an AI-powered RAG-based chatbot that allows users to upload files and ask questions related to their content. It offers versatile use cases, with a key innovation focused on privacy. Uploaded files are securely handled, ensuring confidentiality. By logging in with a Google account, users can maintain and manage their chat history seamlessly. The chatbot leverages the Mistral AI LLM model, ensuring high-quality responses and efficient processing of user queries.
- Clone the Repository
https://github.com/blockx3/dchat.git
cd fastapi- Environment File
Create .env file and Copy the contents from .env.example
- Run server
python main.pycd web- Environment File
Create .env file and Copy the contents from .env.example
npm install
npm run dev- Pick an issue and suggest your solution OR create an issue regarding what better you can add to the project.
- Start working on the issue and create a branch and open pull request.
- Once the PR is reviewed and approved, it will be merged to the main branch 💫.
- Mistral AI for the large language model (LLM)
- PGVector as the vector database
- LangChain for integrating AI and retrieval-augmented generation (RAG)
- FastAPI for the backend
- Next.js & React for the frontend
- Shadcn/UI & Tailwind CSS for styling
- Prisma ORM & PostgreSQL for database management
- Next-Auth for authentication
- Docker for containerized deployment
This project is licensed under the MIT License. See the LICENSE file for details.
For any questions or inquiries, please contact:
- Thinley: [email protected]