pytidb
OfficialConnect Python with TiDB for vector search.
System Documentation
What problem does it solve?
This Skill provides Python tooling to connect to TiDB from Python, model tables, and build vector/full-text/hybrid search features, enabling AI-powered apps with nearby memory and RAG capabilities. It guides you through templates and examples to accelerate development, reduce boilerplate, and keep credentials safe via environment variables.
Core Features & Use Cases
- ORM-like experience: Interact with TiDB using Python classes and SQLAlchemy-inspired patterns.
- Vector/full-text/hybrid search: Build semantic search for app data and AI tasks.
- Agent-oriented examples: RAG, memory, and text-to-sql workflows to accelerate AI apps.
- Use Case: Spin up a quick starter that connects, creates a table with auto-embedded vectors, inserts sample data, and runs a semantic search.
Quick Start
Use the pytidb skill to connect to TiDB from Python using pytidb, configure env vars, and run a quickstart template that creates a table with auto-embedding and performs a vector search.
Dependency Matrix
Required Modules
Components
💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: pytidb Download link: https://github.com/pingcap/agent-rules/archive/main.zip#pytidb Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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