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This research aims to integrate TrOCR, an advanced Optical Character Recognition (OCR) technology, with the Langchain framework for Document question answering on image-based queries. The college has many number of students and they face many problems when it comes to the preparation for exams. There may be many question papers they have to prepare manually by searching the answers in books. Our model uses TrOCR to extract text from input images and the large text data is split using Langchain. Vector indexing is to process the text. This integration helps in information retrieval and question answering. The VectorstoreIndexCreator facilitates text vectorization and indexing, and HuggingFaceEmbeddings for semantic understanding. This research aims for information retrieval, document analysis, and natural language processing, offering a connection between image-based text and advanced language technology where users can have easy handling of the model and provides comprehensive answers for given complex questions.

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TrOCR-Enhanced Language Chains: Bridging Image-Based Text and Single Document Question Answering

  • 会议论文

  • 发表日期：

    2025年

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  • Patan Althaf,
  • Surendra Reddy Vinta

摘要

This research aims to integrate TrOCR, an advanced Optical Character Recognition (OCR) technology, with the Langchain framework for Document question answering on image-based queries. The college has many number of students and they face many problems when it comes to the preparation for exams. There may be many question papers they have to prepare manually by searching the answers in books. Our model uses TrOCR to extract text from input images and the large text data is split using Langchain. Vector indexing is to process the text. This integration helps in information retrieval and question answering. The VectorstoreIndexCreator facilitates text vectorization and indexing, and HuggingFaceEmbeddings for semantic understanding. This research aims for information retrieval, document analysis, and natural language processing, offering a connection between image-based text and advanced language technology where users can have easy handling of the model and provides comprehensive answers for given complex questions.