Notion RAG CLI

A comprehensive command-line tool that transforms Notion pages into a powerful RAG (Retrieval-Augmented Generation) system using Gemini 2.5 Flash-Lite Preview. The tool fetches and indexes Notion content, implements ChromaDB vector search, provides cost tracking, and offers specialized prompt templates for semantic search, summarization, and content analysis.

July 2025
PythonChromaDBGemini 2.5 Flash-LiteNotion APIPytestEmbedding GenerationPrompt EngineeringCommand-Line interface (CLI)tiktoken

The Challenge

Notion's built-in AI feature is expensive and limited, costing users significant money for basic AI-powered information retrieval. Users struggle to leverage their Notion knowledge base for intelligent queries without paying premium fees for Notion AI. Traditional approaches require complex setup, manual data processing, and lack integration between personal knowledge management systems and modern AI capabilities. There's a gap between having valuable information in Notion and being able to query it intelligently using AI in a cost-effective way.

The Solution

Developed a comprehensive command-line tool that transforms Notion pages into a powerful RAG (Retrieval-Augmented Generation) system using Gemini 2.5 Flash-Lite Preview. The tool seamlessly extracts content from Notion, processes it through advanced embedding generation, stores it in ChromaDB for efficient vector search, and provides intelligent querying capabilities through sophisticated prompt engineering with real-time cost tracking.

Technical Highlights

  • Integrated Gemini 2.5 Flash-Lite Preview for advanced AI-powered responses
  • Built modular Python architecture with ChromaDB vector store achieving ~1.4s average query response time
  • Implemented comprehensive cost tracking and API usage monitoring with tiktoken token counting
  • Created specialized prompt templates for semantic search, summarization, and content analysis
  • Developed recursive page fetching with metadata preservation and secure credential management

Key Results & Impact

Achieved ~0.8s fetch time for 9 pages and ~14s load time for 54K characters
Maintained ~1.4s average query response time with optimized ChromaDB vector search
Implemented comprehensive cost tracking and API usage monitoring system
Created user-friendly CLI tool with interactive chat and specialized prompt templates
Established foundation for scalable AI-powered knowledge management solutions

Business Impact

This tool democratizes AI-powered knowledge management by making sophisticated RAG systems accessible to individual users and small teams. The integration with Gemini 2.5 Flash-Lite Preview provides cutting-edge AI capabilities while the performance metrics demonstrate production-ready efficiency. It bridges the gap between personal knowledge management and AI capabilities, enabling users to leverage their Notion content for intelligent information retrieval and analysis.

Key Achievements

Integrated Gemini 2.5 Flash-Lite Preview for advanced AI-powered responses
Achieved ~1.4s average query response time with ChromaDB vector search
Implemented comprehensive cost tracking and API usage monitoring
Built recursive page fetching with metadata preservation
Created specialized prompt templates for semantic search and content analysis

Interested in Learning More?

Check out the source code or see the project in action