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Create a RAG Pipeline with Pinecone
Quickstart with Pinecone Approximate time to complete: 5-10 minutes, excluding prerequisites This quickstart will walk you through creating and scheduling a pipeline that collects data from an Amazon S3 bucket, creates vector embeddings using an OpenAI embedding model, and writes the vectors to your Pinecone search index. Before you begin Before starting, ensure you have access to the credentials, connection parameters, and API keys as appropriate for the following: A Vectorize account (Create one free here ↗ ) An Amazon S3 bucket & IAM access keys (Walkthrough documentation) An OpenAI API Key (How to article) A Pinecone account (Create one on Pinecone ↗ ) Step 1: Create a Pinecone Index Navigate to the Pinecone application console ↗.
Approximate time to complete: 5-10 minutes, excluding prerequisites This quickstart will walk you through creating and scheduling a pipeline that collects data from an Amazon S3 bucket, creates vector embeddings using an OpenAI embedding model, and writes the vectors to your Pinecone search index. Before starting, ensure you have access to the credentials, connection parameters, and API keys as appropriate for the following:
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