How pik1989/text-to-sql-chatbot works
This repository is a notebook-based natural-language-to-SQL chatbot. Its documented workflow takes a user question, uses an LLM chain to produce SQL, queries MySQL, and formats results in natural language. The README also describes loading source data into MySQL and evaluating chatbot quality; notebook filenames suggest related implementations, but their contents were not available to verify. The graph therefore shows only documented relationships, not inferred notebook internals.
Main entry points: Gemini Chatbot.ipynb Text-to-SQL chatbot · Data_CSV Sales CSV data
Components 7
Query workflow
- Text-to-SQL chatbot
Gemini Chatbot.ipynb - LLM chain
Gemini Chatbot.ipynb - Output parser
Gemini Chatbot.ipynb
Data and storage
- Sales CSV data
Data_CSV - MySQL database
Evaluation
- Chatbot evaluation
Gemini Chatbot (including RAGAS).ipynb
Other components
- Chat user
Connections 6
- Chat user → Text-to-SQL chatbot: asks question
README.md - Text-to-SQL chatbot → LLM chain: converts question
README.md - LLM chain → MySQL database: queries database
README.md - MySQL database → Output parser: returns results
README.md - Output parser → Chat user: formats response
README.md - Sales CSV data → MySQL database: loads data
README.md