An enterprise-grade, serverless RAG pipeline transforming multi-page PDF documents into interactive, context-aware knowledge networks using modern LangChain (LCEL) architectures.
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Updated
Jun 30, 2026 - Python
An enterprise-grade, serverless RAG pipeline transforming multi-page PDF documents into interactive, context-aware knowledge networks using modern LangChain (LCEL) architectures.
Educational Python project demonstrating a 4-stage LangChain prompt chain for recipe generation and review.
a multi-step web research agent over the web, Wikipedia, and arXiv - built with LangGraph + LCEL, streams each step in real-time, and grounds every report in sources it actually fetches and reads.
Explore how developers can integrate Artificial Intelligence into software applications by working with LLM APIs, prompt engineering, AI workflows, and practical developer-focused use cases.
Multi-source conversational RAG chatbot supporting PDFs, DOCX, TXT, CSV, websites, APIs, and YouTube transcripts using LangChain, Groq Llama 3.3, FAISS, and Streamlit.
A production-ready Advanced RAG API featuring background ingestion, schema-driven routing, and dynamic metadata filtering. Built with FastAPI, ChromaDB, and Ollama, it utilizes RabbitMQ workers for scalable, idempotent document processing and autonomous query expansion.
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