Building a PDF Chatbot: From Scratch with PDF Miner and Sentence Transformer
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Today on Abhishek Thakur's channel, we witness a thrilling endeavor to construct a PDF chatbot without relying on the crutches of open AI or other common libraries. The team dives headfirst into the intricate world of pre-processing, utilizing the powerful tools of PDF Miner and Sentence Transformer. With a swagger in their step, they craft an argument parser to streamline the process and delve into the art of embedding text for the chatbot's foundation.
As the adrenaline builds, they embark on a journey to extract text and tokens from the PDF using PDF Miner, setting the stage for a symphony of sentences and paragraphs. Armed with the mighty Sentence Transformer, they harness the power to encode these textual elements, paving the way for a semantic search that promises to uncover hidden gems within the document. The team's enthusiasm is palpable as they navigate the complexities of re-ranking search results using a cross encoder, fine-tuning their chatbot's ability to deliver precise and relevant responses.
With the stage set and the engines revving, Abhishek Thakur's crew plunges into the heart of the action, deploying both a local model and a Hugging Face inference endpoint to unleash the full potential of their creation. The air crackles with anticipation as they deftly navigate the intricacies of generating prompts tailored to each model, culminating in a showdown that pits the 7B and 40B models against each other in a battle of wits. Through meticulous parameter tuning and strategic query formatting, they unleash a torrent of responses that showcase the prowess and versatility of their PDF chatbot.
Image copyright Youtube
Image copyright Youtube
Image copyright Youtube
Image copyright Youtube
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Viewers appreciate the detailed explanations and coding in the video
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Questions about fine-tuning models, preventing randomly generated outputs, and creating custom models from PDFs in different languages
Requests for tutorials on multiple instance learning using Neural networks and adding a web UI to the code
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