Скачать или смотреть Langchain Tutorial | Retrievers| Part 5 | Parent Document Retriever | Optimize | Effective Retrieval

Discover the ParentDocumentRetriever and its powerful ability to strike the perfect balance between small, meaningful chunks and large, context-rich documents. In this step-by-step tutorial, we explore how to efficiently retrieve documents using LangChain, Chroma, OpenAI Embeddings, and Recursive Character Text Splitter. Whether you're retrieving full documents or larger chunks, this video demonstrates practical examples and best practices for document storage and retrieval.
What You’ll Learn:

Why balancing small and large document chunks is crucial for accurate embeddings.
How the ParentDocumentRetriever works to retrieve small chunks and their parent documents.
Step-by-step implementation using tools like InMemoryStore, TextLoader, Chroma, and more.
How to set up text splitters for child and parent document chunks using RecursiveCharacterTextSplitter.
Practical examples of indexing and retrieving documents with LangChain.

Code Example Highlights:

Loading documents using TextLoader.
Creating and indexing child documents with a vectorstore like Chroma.
Retrieving larger parent documents or specific sub-chunks with ParentDocumentRetriever.
Customizing chunk sizes to meet your retrieval needs.

Perfect for developers working on retrieval-augmented generation (RAG), NLP-based search, and anyone exploring LangChain document retrieval systems.

Github: https://github.com/NajiAboo/Langchain...

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