Using Contextual Retrieval with Box and Pinecone

In a recent article, contextual retrieval is explored using Box, an enterprise content management platform, and Pinecone, a managed vector database, to create a custom Retrieval-Augmented Generation (RAG) pipeline. This setup allows developers to transform internal HR knowledge stored in Box, such as PDFs and Word documents, into a searchable format by indexing the content in Pinecone. The process involves extracting text from Box, dividing it into contextualized chunks, generating embeddings with OpenAI's models, and upserting these vectors into Pinecone for efficient retrieval. This method enhances AI-generated responses by providing context from enterprise data, resulting in more relevant and credible answers. By demonstrating contextual retrieval in action, the article highlights how developers can leverage Box and Pinecone to build intelligent, content-driven applications, emphasizing the importance of context in improving AI accuracy and user satisfaction.

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