PDF Inquisitor is a sophisticated Python application that simplifies multi-dimensional interaction with PDF documents. This innovative tool goes beyond conventional PDF document viewing, allowing users to have natural language conversations with multiple PDF documents simultaneously. Leveraging state-of-the-art language models, this application promises to extract diverse information from the textual content within PDF documents. Please note that the application's responsiveness is dependent on questions
"PDF Inquisitor" tracks structured work processes to ensure accurate answers to user questions:
- Loading PDFs: The application starts by reading multiple PDF documents, extracting their textual content, and preparing it for analysis.
- Text segmentation: For processing optimization, the extracted text is divided into smaller, more manageable segments. This process enables efficient processing of the textual content of PDFs.
- Language model: A language model is used to generate vector representations (embeddings) of textual segments. These embeddings capture the semantic meaning of the text.
- Similarity matching: When a user poses a question, the application compares it with textual segments and identifies the most semantically similar segments.
- Answer generation: The selected textual segments are then passed to a language model that generates a coherent answer based on the relevant content of the PDFs. This answer is displayed to the user, providing answers to their questions.