What is DeepDoc？
DeepDoc is an open-source deep research tool focused on exploring local knowledge bases. The tool uses a research-oriented workflow to extract text from local resources (such as PDF, DOCX, JPG, TXT, etc.), splits the content, and stores it in a vector database for semantic similarity search. Users can query and generate content structures based on instructions and provide feedback to optimize the structure. DeepDoc outputs clear reports in Markdown format. It is suitable for scenarios where insights need to be quickly extracted from local files without manually browsing through large amounts of data.
Key Features of DeepDoc
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Local Resource Research: Supports multiple local file formats (PDF, DOCX, JPG, TXT, etc.) and extracts and splits text content for further processing.
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Semantic Similarity Search: Embeds text blocks into a vector database for efficient semantic similarity search, quickly locating relevant content.
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Research-Oriented Workflow: Generates content structures based on user instructions and supports feedback optimization to improve research accuracy.
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Multi-Step Research Process: Generates high-quality report content through steps such as knowledge generation, query creation, and search optimization.
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Structured Report Generation: Produces clear Markdown-format reports for easy viewing and usage.
Technical Principles of DeepDoc
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Text Extraction and Segmentation: Uses Optical Character Recognition (OCR) to extract text from image files (e.g., JPG). Text is split into page-level blocks for easier processing.
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Vector Database Storage: Split text blocks are embedded into a vector space and stored in a vector database (e.g., Qdrant) for efficient semantic similarity searches, quickly retrieving the most relevant text blocks for user queries.
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Multi-Step Research Process: For each report section, a research agent generates knowledge and creates research queries. A search agent runs on local data to find the most relevant text blocks. A reflection agent optimizes the search results to ensure accuracy and usefulness. Finally, all sections are compiled into a complete report.
DeepDoc Project Link
- GitHub Repository: https://github.com/Datalore-ai/deepdoc
Application Scenarios of DeepDoc
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Academic Research: Helps researchers quickly organize and analyze large volumes of literature, generating structured research reports and saving time on manual literature review.
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Enterprise Knowledge Management: Enables companies to deeply explore internal documents, reports, and project materials, quickly extracting key information to support decision-making.
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Legal Document Analysis: Assists legal professionals in analyzing large amounts of legal documents, cases, and contracts, quickly locating relevant clauses and case references to improve efficiency.
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Market Research: Allows market researchers to analyze collected reports, consumer feedback, and competitor information, quickly generating structured market research reports.
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Personal Knowledge Management: Helps individuals organize and analyze personal notes, study materials, and project documents, quickly extracting key insights to improve learning and work efficiency.
