Real-World Projects
Hands-on projects that cement every concept from the learning modules. All code lives on GitHub, so you can clone, run, and modify everything.
gaurav-pahuja-ai/ai-real-world-projectsSemantic Vector Bot
A production-ready Q&A system that ingests PDFs, indexes them in ChromaDB, and answers questions with source citations. Powered by Google Gemini (free tier) with a Gradio UI.
BM25 Keyword Bot
A RAG pipeline that retrieves context using pure keyword search - BM25 and TF-IDF - with zero vector databases or embeddings. Proves you can build accurate, fast Q&A without the overhead of a vector store.
Enterprise Knowledge Base Search
Multi-tenant RAG system for internal company knowledge. Supports Confluence, Notion, and Google Drive connectors with access-control-aware retrieval.
Hello MCP Server
The smallest useful MCP server: one tool, no API keys, no external services. The exact code walked through in the Build Your First MCP Server lesson, under 150 lines start to finish.
GitHub MCP Server
A fully-featured MCP server that exposes GitHub operations (issues, PRs, file reads, search) as tools for any MCP-compatible AI model.
Postgres MCP Server
An MCP server that lets AI models query a Postgres database safely. Includes read-only enforcement, query validation, and schema discovery.
Autonomous Research Agent
A ReAct agent that takes a research question, searches the web, reads papers, cross-references sources, and produces a structured Markdown summary on its own.
AI Code Review Agent
A multi-agent system that reviews pull requests. One agent checks security, another checks performance, a third reviews code style, and an orchestrator combines all the findings.