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For instance, problems like “write a Python function that takes a list of names, splits them by first and last name, and sorts by last name.” Instead what I decided to do was to parse the “landing pages” for each paper that contains metadata such as its title, abstract, and publication date. That is the basic premise of my project.
The knowledge base sync process handles chunking and embedding of the transcript, and storing embedding vectors and file metadata in an Amazon OpenSearch Serverless vector database. Below are retrieved chunks of transcript with metadata including the file name. For instructions, see Working with the AWS CDK in Python.
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