Chat with Your Database: LlamaIndex + SQLite Tutorial (Soccer Data Example)
Stop querying and start chatting! In this video, we dive deep into using LlamaIndex to bridge the gap between Natural Language and SQL databases.
We walk through a practical build: a Soccer Player Stats Q&A Service. You’ll learn how to take raw player data, move it into SQLite, and build a LlamaIndex query engine. We also introduce an entity resolution enhancement to handle messy user input.
What we cover:
Loading Soccer Stats from Pandas to SQLite.
Setting up the LlamaIndex SQL Query Engine.
Advanced Logic: Adding Entity resolution for the LLM to generate more accurate SQL queries.
Building a Custom Query Engine for the future
Timestamps:
0:00 - Introduction
0:41 - Why you may want LLM and SQL interaction
1:39 - Prepping Soccer Data with Pandas
2:39 - Loading the SQLite database
4:14 - Creating the LLamaIndex Query Engine
5:03 - Table Context
6:01 - Asking questions + uncovering issues
8:41 - Implementing Entity Resolution
11:40 - Creating a Custom Query Engine
12:13 - Wrap-up & Conclusion
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