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CodeSignal

Document Processing and Retrieval with LangChain in TypeScript

via CodeSignal

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Overview

Unlock the power of document intelligence with LangChain in TypeScript. This course will teach you how to efficiently process and retrieve information from documents. Learn to load, split, and embed documents, and master the art of similarity search to extract relevant insights. Build a robust foundation for document-driven applications with cutting-edge techniques.

Syllabus

  • Unit 1: Loading and Splitting Documents with LangChain
    • Loading and Examining PDF Documents with LangChain
    • Loading Text Files with TextLoader
    • Experimenting with Document Splitting Parameters
    • Exploring Different Text Splitters in LangChain
    • Loading and Splitting Documents with LangChain
  • Unit 2: Generating Document Embeddings with OpenAI
    • Generate Document Embeddings with OpenAI
    • Configuring OpenAI Embeddings with Advanced Parameters
    • Fix the Embedding Model Bug
    • Exploring Embedding Dimensionality
  • Unit 3: Retrieving Relevant Information with Similarity Search
    • Exploring FAISS Vector Store Properties
    • Performing Similarity Search with FAISS
    • Adjusting the Number of Retrieved Document Chunks
    • Creating a Vector Store and Performing Similarity Search with FAISS
  • Unit 4: Asking Questions with Retrieved Context and Templates
    • Creating a Chat Prompt Template in TypeScript
    • Combining Document Chunks for Context
    • Creating Prompt Templates with Context and Questions
    • Asking Questions with Retrieved Context and a Chat Model
    • Enhancing Chat Model Interactions with System and Human Messages

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