P D F Upload and Search - Copy this React, Tailwind Component to your project

PDF Upload: Create a web interface or API that allows users to upload PDF files. Text Extraction: Extract the text from the uploaded PDF files using libraries like PyPDF2, PDFMiner, or Tesseract OCR. Topic Modeling: Use Natural Language Processing (NLP) techniques like Latent Dirichlet Allocation (LDA) or Non Negative Matrix Factorization (NMF) to identify topics within the extracted text. Search: Create a search interface that allows users to search for specific topics. Answer Generation: Use NLP techniques like question answering or text summarization to generate detailed answers for the searched topics. Answer Display: Display the generated answers in a user friendly format, including explanations, summaries, and other relevant information. Some possible tools and technologies to help you achieve this include: PDF Upload: Flask, Django, or Express.js for building a web interface, or AWS S3 for storing and processing PDF files. Text Extraction: PyPDF2, PDFMiner, or Tesseract OCR for extracting text from PDF files. Topic Modeling: Gensim, spaCy, or scikit learn for topic modeling using LDA or NMF. Search: Elasticsearch, Solr, or Algolia for building a search interface. Answer Generation: Hugging Face Transformers, StanfordNLP, or spaCy for question answering and text summarization. Answer Display: React, Angular, or Vue.js for building a user friendly interface to display answers. create full project code write