Begin by breaking down your entire knowledge base into smaller, manageable chunks. Each chunk should represent a distinct piece of information that can be queried. This data can come from various sources, such as Confluence documentation or supplemented PDF reports.
Step 2: Embed the text corpus
Utilize an embedding model to transform each chunk of text into a vector representation. This embedding process captures the essence of the information and encodes it into a numerical format suitable for querying.
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