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Mastering GCP Read, Embed, and Search Data in BigQuery Vector Database Context Summarization by LLM
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Learn how to seamlessly integrate various Google Cloud Platform (GCP) services for advanced data processing and retrieval. In this tutorial, we walk through the steps to:
Read files from a GCP bucket.
Perform document embedding.
Push documents to Google Big Query Vector Database.
Conduct a similarity search using custom metadata filters.
Send the RAG (Retrieval-Augmented Generation) search results to ChatVertexAI for summarization.
Whether you're a data scientist, developer, or cloud enthusiast, this video provides a comprehensive guide to leveraging GCP's powerful tools for efficient and accurate information retrieval and summarization with LLM.
Read files from a GCP bucket.
Perform document embedding.
Push documents to Google Big Query Vector Database.
Conduct a similarity search using custom metadata filters.
Send the RAG (Retrieval-Augmented Generation) search results to ChatVertexAI for summarization.
Whether you're a data scientist, developer, or cloud enthusiast, this video provides a comprehensive guide to leveraging GCP's powerful tools for efficient and accurate information retrieval and summarization with LLM.
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Mastering GCP Read, Embed, and Search Data in BigQuery Vector Database Context Summarization by LLM
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