Loaders, Indexes & Vectorstores in LangChain - Question Answering on PDF Files with ChatGPT

Explore the functionalities of LangChain's data loaders, indexes, and vector stores in this comprehensive 24-minute tutorial. Learn to load text files, use VectorestoreIndexCreator for queries, and work with YouTube and PDF loaders. Discover text splitting techniques and create embeddings using OpenAI and SentenceTransformers models. Dive into vector stores for embedding storage and culminate by asking questions on custom PDF files using ChatGPT. Gain practical insights into LangChain's capabilities, from basic text file handling to advanced PDF querying, making this an ideal starting point for those seeking to enhance their understanding of LangChain's powerful features.

- Intro
- GitHub Repository
- Google Colab Setup
- TextLoader
- Loaders
- Text Splitters
- Embeddings
- Vectorstores
- Q&A on a PDF file
- Conclusion