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Question Answering with Retrievers

Lab Overview​

Learn how to build a robust question-answering system using LangChain's retriever-based approach, enabling accurate and context-aware responses.

Lab Materials​

Key Topics​

  • Retriever implementation
  • Question processing
  • Context management
  • Answer generation
  • Response accuracy

Features​

  • Document-based QA
  • Context retrieval
  • Answer synthesis
  • Accuracy optimization
  • Source tracking

Technical Components​

  • Retriever setup
  • Document processing
  • Query handling
  • Context management
  • Response generation

Implementation Steps​

  1. Document preparation
  2. Retriever configuration
  3. Query processing setup
  4. Context retrieval system
  5. Answer generation pipeline
  6. Response optimization

Use Cases​

  • Document-based QA
  • Knowledge base queries
  • Information retrieval
  • Contextual responses
  • Source attribution

Prerequisites​

  • Google Colab account
  • OpenAI API key
  • Basic understanding of:
    • Information retrieval
    • NLP concepts
    • Python programming

Resources​