This project is a PDF-based chatbot application using Retrieval-Augmented Generation (RAG). Users can upload a PDF document, and the chatbot will answer queries related to the document using the document's content.
- PDF Upload: Users can upload PDF documents to the app.
- RAG-based Querying: Queries are processed using a Retrieval-Augmented Generation (RAG) pipeline, fetching relevant content from the uploaded document and generating responses.
- Document-Specific Queries: All user queries are answered based on the content of the uploaded document. If the answer cannot be found in the document, the chatbot will notify the user.
- Real-time Response: The chatbot provides concise and accurate answers in real-time using the provided context.
- Next.js: A React framework for building server-side rendered applications.
- Convex: A backend as a service framework for building applications.
- OpenAI: For utilizing OpenAI embeddings and chat models.
- Convex Vector Store: For storing and retrieving document embeddings.
- Convex Storage: For managing file uploads.
To run this app, you'll need:
- OpenAI API Key