Chatwithpdf is a user-friendly ChatGPT plugin that streamlines the
interaction with PDF documents. Users can effortlessly load PDFs by
providing a temporary URL, allowing them to query, analyze, and ask
questions based on the content. The tool's standout feature is
its semantic search, which efficiently matches user queries with
relevant information extracted from the processed PDFs. Adding
Chatwithpdf as an unverified plugin in the ChatGPT UI's
"Plugin Store" is all it takes to access this web-based
tool, eliminating the need for installation. User privacy is
prioritized, as the tool doesn't store data permanently, and
PDFs are embedded and wiped clean with each deployment. In
conclusion, Chatwithpdf offers a seamless and secure solution for
extracting essential information from PDFs, ensuring a smooth user
experience.
Key Features of ChatWithPDF
Explore the many features provided by ChatWithPDF to maximize your PDF document experience. These encompass:
Search PDFs directly in ChatGPT
Search PDFs of any size
Search PDFs of any language
Search PDFs of any topic
Search PDFs of any length
Search PDFs of any quality
How it works:
Users submit a publicly
accessible PDF URL for loading and processing, ensuring
accessibility even in private browsing modes such as Incognito. The
plugin then downloads and analyzes the PDF document, extracting
pertinent information. User inquiries are subsequently compared with
the processed data from the PDF, and the most relevant matches are
retrieved and presented to the user.
Privacy:
ChatWithPDF ensures that no data is intentionally stored permanently. All PDFs are promptly embedded and erased. Embeddings are saved temporarily with ChromaDB on the deployment server and are wiped clean with each new deployment. Typically, manual purging of embeddings occurs every 12-24 hours due to limitations in our vector database, which is necessary to address size and memory constraints. In the future, all embeddings will be automatically deleted one hour after the user requests them. It's worth noting that if someone has your link, they can fetch embeddings from it, as it is cached in our vector database. However, users cannot discern the searches or embeddings of other users.
