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INTERNATIONAL JOURNAL OF CREATIVE RESEARCH THOUGHTS - IJCRT (IJCRT.ORG)
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Authors
Miss Madhura Upadhye,Mr Aditya Sarate,Miss Utkarsha Chougule,Mr Sourabh Gavandi,Mr Milind S. Vadagave
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Keywords
Natural Language Processing, Optical Character Recognition, Document Summarization, Semantic Search, LLM, AI Chatbot, PDF Analysis, Vector Embeddings.
Abstract
The ever-increasing volume of digital documents has made information retrieval a time-consuming and tedious task. PDF Chat Assistant aims to revolutionize document accessibility and interaction by allowing users to query and receive intelligent responses from PDF files using natural language. This AI-powered application leverages state-of-the-art technologies including Optical Character Recognition (OCR), semantic text chunking, vector embeddings, and transformer-based Large Language Models (LLMs) to facilitate accurate and context-aware responses strictly based on the contents of the uploaded PDF documents. Users can upload both text-based and scanned PDF files, which are first processed to extract readable content. If no direct text is available, OCR is applied to scanned pages to retrieve the text. The extracted content is then split into manageable chunks and converted into vector embeddings for semantic similarity search. When a user poses a question, the system checks for contextual relevance within the PDF and retrieves the most pertinent content chunks using FAISS, a high-performance similarity search library. These chunks are then passed to a pre-trained LLM (such as GPT-Neo 2.7B) to generate a human-like, document-specific response. The assistant is built using Python and Streamlit for the frontend, ensuring ease of use. By integrating modern NLP tools such as HuggingFace Transformers and LangChain's ConversationalRetrievalChain, the system maintains coherent and contextually appropriate conversations. Additionally, the assistant is designed to reject questions unrelated to the document content, ensuring its reliability and specificity. The PDF Chat Assistant is especially useful for students, researchers, legal professionals, and corporate users who need quick and precise information from large, complex documents. This paper presents the architecture, implementation, and evaluation of the system, highlighting its capabilities and potential applications.
IJCRT's Publication Details
Unique Identification Number - IJCRT2505614
Paper ID - 286050
Author type - Indian Author
Page Number(s) - f444-f451
Pubished in - Volume 13 | Issue 5 | May 2025
DOI (Digital Object Identifier) -
No Of Downloads - 81
Author Country - India, 416003, Kolhapur, Kolhapur, 416003, Science and Technology
Publisher Name - IJPUBLICATION | www.ijcrt.org | ISSN : 2320-2882
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Miss Madhura Upadhye,Mr Aditya Sarate,Miss Utkarsha Chougule,Mr Sourabh Gavandi,Mr Milind S. Vadagave, "PDF Chat Assistant", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.13, Issue 5, pp.f444-f451, May 2025, Available at :http://www.ijcrt.org/papers/IJCRT2505614.pdf
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The International Journal of Creative Research Thoughts (IJCRT) aims to explore advances in research pertaining to applied, theoretical and experimental Technological studies.
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ISSN: 2320-2882 Impact Factor: 7.97 and ISSN APPROVED Journal Starting Year (ESTD) : 2013
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ISSN: 2320-2882 Impact Factor: 7.97 and ISSN APPROVED Journal Starting Year (ESTD) : 2013
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