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hassanaiengineer/README.md

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πŸ™‹β€β™‚οΈ About Me

  • πŸ€– Senior AI Engineer building production-grade LLM systems, not just demos
  • 🧠 4+ years experience delivering end-to-end AI platforms (RAG, Agents, OCR, Voice AI)
  • πŸš€ Built 15+ real-world AI systems handling messy, unstructured, enterprise data
  • πŸ” Specialized in RAG architectures, hallucination control, and hybrid retrieval systems
  • βš™οΈ Strong focus on scalable FastAPI backends, async pipelines, and system reliability
  • πŸ“ Based in Islamabad, Pakistan, delivering high-impact AI ownership globally 🌍.
  • πŸ’¬ Ask me about RAG failure modes, hallucination mitigation strategies, or designing scalable LLM APIs in production.

πŸ’‘ I don’t just integrate APIs - I design AI systems that actually work in production.


πŸ› οΈ Tech Stack

πŸ—οΈ AI Systems Architecture & Backend

Python FastAPI Django REST API Async Microservices

🧠 LLM Engineering & RAG Systems

RAG Agentic AI LangChain LlamaIndex LangGraph Prompt Engineering Evaluation

πŸ€– LLM Providers & Local Models

OpenAI Claude Gemini Llama Mistral Ollama

πŸ” Vector Search & Retrieval

FAISS ChromaDB Hybrid Search Semantic Search

πŸ“„ Document AI & OCR

OCR Tesseract PaddleOCR OpenCV PDF Processing

πŸ—„οΈ Databases & Storage

PostgreSQL MongoDB Redis

☁️ DevOps & Deployment

Docker Docker Compose RunPod GCP Nginx CI/CD

⚑ Automation & Workflow

n8n Zapier

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🧠 Core Expertise

  • πŸ”· Designing Agentic RAG Systems with self-correction and multi-step reasoning
  • πŸ”· Building Hybrid Search Pipelines (BM25 + Vector + RRF)
  • πŸ”· Developing Document Intelligence Systems (PDF β†’ Structured Data)
  • πŸ”· Handling noisy OCR data and complex layouts
  • πŸ”· Reducing LLM hallucinations with retrieval + validation layers
  • πŸ”· Creating real-time AI APIs with streaming responses
  • πŸ”· Deploying LLM systems on GPU infra (RunPod, local models)

πŸš€ Featured Projects

Project Description Tech Stack
Agentic RAG System Production-ready Agentic RAG system with self-correction loops, hybrid retrieval (RRF), and multi-tenant architecture. FastAPI, Gemini, ChromaDB, LangGraph
RAG Tutorials 30+ hands-on implementations covering naive β†’ advanced RAG, hybrid search, reranking, and agent workflows. Python, LangChain, FAISS
Multi-Engine OCR High-accuracy OCR pipeline combining multiple engines with preprocessing for real-world noisy documents. Python, Docling, OpenCV
Sarah Voice Agent Real-time conversational AI voice agent with speech-to-speech pipeline and contextual memory. Python, FastAPI
Rahnuma Urdu conversational AI assistant with custom prompts and localized intelligence. Python, LLM

πŸ“Š GitHub Analytics


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  1. Multi-Engine-OCR Multi-Engine-OCR Public

    Advanced OCR repository combining Docling, PaddleOCR, and OpenCV preprocessing for superior accuracy on noisy documents and resumes.

    Python 3

  2. agentic-rag-system agentic-rag-system Public

    Production-grade Agentic RAG with hybrid retrieval, LangGraph self-correction, real-time streaming, and enterprise multi-tenancy β€” built on FastAPI + Gemini + ChromaDB.

    TypeScript 1

  3. rag-tutorials-by-hassan-khan rag-tutorials-by-hassan-khan Public

    RAG tutorials by Hassan Khan β€” 30 production-focused examples: covering RAG patterns, hybrid search, routing, agentic RAG, knowledge graphs, multimodal RAG, and debugging.

    Python 1

  4. DocuChat.ai DocuChat.ai Public

    Python

  5. OmniDoc.AI OmniDoc.AI Public

    OmniDoc AI is an enterprise-grade OCR-first document intelligence platform that transforms messy scanned documents into clean, structured, AI-ready knowledge.

    Python

  6. IntelliDocs IntelliDocs Public

    A production-ready Retrieval-Augmented Generation (RAG) system that transforms your documents into intelligent conversations.

    JavaScript 1