How to Chat With Any PDFs and Image Files Using Large Language Models — With Code
So much valuable information is trapped in PDF and image files. Luckily, we have these powerful brains capable of processing those files to find specific information, which in fact is great.
That is the whole purpose of this article. I will explain step-by-step how to build a system that can chat with any PDFs and image files.
It’s always good to have a clear understanding of the main components of the system being built. So let’s get started.
First, the user submits the document to be processed, which can be in PDF or image format.
A second module is used to detect the format of the file so that the relevant content extraction function is applied.
The content of the document is then split into multiple chunks using the Data Splitter module.
Those chunks are finally transformed into embeddings using the Chunk Transformer before they are stored in the vector store.
At the end of the process, the user’s query is used to find relevant chunks containing the answer to that query, and the result is returned as a JSON to the user.
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