Docker LabAdvanced4 hours
Build a RAG Pipeline with LangChain
Implement Retrieval-Augmented Generation to build a chatbot that answers questions from your own documents.
Part of Generative AI Engineering (Week 5)
What You'll Build
A document Q&A system that ingests PDFs, chunks text, generates embeddings, stores them in ChromaDB, and uses GPT-4 to answer questions with source citations.
Tools Used
PythonLangChainChromaDBOpenAI APIFastAPI
Skills Practiced
RAG architectureVector embeddingsPrompt engineeringLLM integration
Prerequisites
- Python intermediate
- REST API basics
Why This Matters in Real Jobs
RAG is the most practical Gen AI pattern in enterprise. Companies are building internal knowledge assistants, customer support bots, and document search systems using this exact architecture.
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This lab is part of the Generative AI Engineering course. Enrol to get access to all labs, projects, and career support.