使用SQLCoder生成经过验证的分析SQL

Use SQLCoder when an analytics agent needs to turn natural-language questions plus schema context into SQL drafts that can be reviewed, validated, and run inside a controlled data workflow.

Prerequisites

Python environment, SQLCoder package or Hugging Face model weights, schema metadata for the target database, and a controlled database execution or review path.

Installation

Use the upstream install or setup path that matches your environment:

• pip install "sqlcoder[transformers]"
• pip install "sqlcoder[llama-cpp]"

Requirements and caveats from upstream:

• python inference.py -q "Question about the sample database goes here"

Basic usage or getting-started notes:

• If running on a non-apple silicon computer without GPU access, please run this on Linux/Intel Mac

• And run this on Windows

• In your terminal, run

• Source: https://github.com/1991513ccie-png/skills

• Extracted from upstream docs: https://raw.githubusercontent.com/defog-ai/sqlcoder/HEAD/README.md

Documentation

• https://github.com/1991513ccie-png/skills