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关于

This Python application serves as a backend for Large Language Models (LLMs), enabling them to access structured data from a Google Drive Excel file. To enhance efficiency and mitigate Google Drive API limitations, it implements a SQLite-based cache that refreshes daily and upon server restart. The tool integrates APScheduler for managing background synchronization tasks and utilizes `mcpo` to transform the MCP server into an OpenAI-compatible proxy, facilitating seamless integration with LLM frontends like OpenWebUI.

主要功能

• SQLite-based data caching for enhanced performance
• Daily and on-restart cache synchronization with Google Drive spreadsheets
• OpenAI-compatible proxy for seamless LLM integration via `mcpo`
• Background data updates managed by APScheduler
• Supports Google Drive API for spreadsheet access and parsing
• 0 GitHub stars

使用案例

• Serving structured data from Google Drive to LLM applications
• Integrating LLM agents with external data sources requiring efficient caching
• Creating an OpenAI-compatible endpoint for data-driven LLM tool interactions