๐๐จ๐๐๐ ๐ ๐ฅ๐๐ ๐๐๐๐ง๐๐ข๐ง ๐๐ฅ๐ข๐ ๐ฆ๐๐ฅ๐๐ง๐๐ You can build a simple RAG chatbot in about 40 lines of Python. This chatbot answers questions about a private knowledge base. Here's how it works:
- Break your documents into chunks
- Turn each chunk into a vector
- Keep these vectors
- When a question comes in, find the closest vectors and use them as context for the model You need Python 3.9 or newer and three packages: sentence-transformers, numpy, and anthropic. To get started, install these packages with pip:
- pip install sentence-transformers numpy anthropic Then, set your API key with:
- export ANTHROPIC_API_KEY=your_key_here This code uses a simple word-based chunker. You can improve this by splitting on sentences or headings. The chatbot retrieves the relevant chunks and uses them as context for the model. This keeps the model from making things up. You can try this code with your own documents or notes. What would you feed it first? Source: https://dev.to/markofrei919/build-a-rag-chatbot-from-scratch-in-about-40-lines-of-python-i0c Optional learning community: https://discord.gg/nWctKNRM