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Create Text Embeddings for a Vector Store using LangChain

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Create Text Embeddings for a Vector Store using LangChain

Create Text Embeddings for a Vector Store using LangChain

This is a self-paced lab that takes place in the Google Cloud console. In this lab, you will learn how to use LangChain to store documents as embeddings in a vector store. You will use the LangChain framework to split a set of documents into chunks, vectorize (embed) each chunk, and then store the embeddings in a vector database.

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Create Text Embeddings for a Vector Store using LangChain

Create Text Embeddings for a Vector Store using LangChain
Create Text Embeddings for a Vector Store using LangChain

Create Text Embeddings for a Vector Store using LangChain
Create Text Embeddings for a Vector Store using LangChain

Create Text Embeddings for a Vector Store using LangChain
Create Text Embeddings for a Vector Store using LangChain

Create Text Embeddings for a Vector Store using LangChain
Create Text Embeddings for a Vector Store using LangChain

Create Text Embeddings for a Vector Store using LangChain
Create Text Embeddings for a Vector Store using LangChain

Create Text Embeddings for a Vector Store using LangChain