A simple project demonstrating Retrieval Augmented Generation (RAG) using SQLite, sqlite-vec, and OpenAI. It embeds text files, stores them in a SQLite database, and retrieves relevant documents using vector search. The project features lightweight single-file SQLite databases, vector search capabilities, and OpenAI integration for embeddings and chat responses.
A new plugin for sqlite-utils CLI tool called sqlite-utils-ask allows users to ask human-language questions directly of SQLite databases and CSV/JSON files, using an LLM to generate SQL queries and execute them.
- New Feature:
openai-to-sqlitetool now allows enriching data in a SQLite database using OpenAI's GPT3.5 model. - Sentiment Analysis Example:
- Update a
sentimentcolumn in amessagestable usingchatgpt()function.
