Langchain Summary and QA with Chromadb Using OpenAI Embeddings and GPT-3 With Token Count

Explore the creation of five distinct Langchain applications for summarization and question-answering using Chromadb as an OpenAI embeddings vector store. Learn to leverage the GPT-3 API for document summarization and context-based question answering. Discover techniques for token counting and custom prompt building in Langchain. Gain hands-on experience with various chain types, including "stuff," "map reduce," "refine," and "map rerank." This 20-minute tutorial covers installation from scratch, code reviews for summary generation, and implementations of different chain types, providing a comprehensive overview of Langchain's capabilities in natural language processing tasks.

Intro and Documnetation:
Installing everything from scratch
Code review for Summary
Code review for Stuff chain type
Code review for Map Reduce chain type
Code review for Refine chain type
Code review for Map Rerank chain type