![]() Feed that into GPT-3.5 as context in the prompt.When a user asks a question, we will use the FAISS vector index to find the closest matching text.Store all of the embeddings in a vector store (Faiss in our case) which can be searched in the application.Index the pdf document (azure functions documentation), split the document into chunks, indexing all of the text creating embeddings.Then answer arbitrary questions by referencing the documentation text. ![]() Let’s build a tool that can read developers documentation – in this case Azure Functions Documentation as PDF. In this article, we will explore the concept of vector databases and their applications in various fields. The number of dimensions in each vector can vary widely, ranging from tens to thousands, depending on the complexity and granularity of the data. These vectors are mathematical representations of the features or attributes of the data being stored.
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