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  ## Multimodal Document Processing (MinerU Integration)
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- LightRAG now supports multimodal document parsing and retrieval-augmented generation (RAG) via [MinerU](https://github.com/opendatalab/MinerU). You can extract structured content (text, images, tables, formulas, etc.) from PDF, images, and Office documents, and use them in your RAG pipeline.
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  **Key Features:**
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- - Parse PDFs, images, DOC/DOCX/PPT/PPTX, and more
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- - Extract and index text, images, tables, formulas, and document structure
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- - Query and retrieve multimodal content (text, image, table, formula) in RAG
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- - Seamless integration with LightRAG core and RAGAnything
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-
 
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  **Quick Start:**
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  1. Install dependencies:
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  ```bash
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  pip install "magic-pdf[full]>=1.2.2" huggingface_hub
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  ```
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- 2. Download MinerU model weights (see [MinerU Integration Guide](docs/mineru_integration_en.md))
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- 3. Use the new `MineruParser` or RAGAnything's `process_document_complete` to process files:
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  ```python
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  from lightrag.mineru_parser import MineruParser
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  content_list, md_content = MineruParser.parse_pdf('path/to/document.pdf', 'output_dir')
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  # or for any file type:
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  content_list, md_content = MineruParser.parse_document('path/to/file', 'auto', 'output_dir')
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  ```
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- 4. Query multimodal content with LightRAG see [docs/mineru_integration_en.md](docs/mineru_integration_en.md).
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  ## Token Usage Tracking
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  ## Multimodal Document Processing (MinerU Integration)
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+ LightRAG now supports comprehensive multi-modal document processing through [MinerU](https://github.com/opendatalab/MinerU) integration, enabling advanced parsing and retrieval-augmented generation (RAG) capabilities. This powerful feature allows you to handle multi-modal documents seamlessly, extracting structured content—including text, images, tables, and formulasfrom various document formats for integration into your RAG pipeline.
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  **Key Features:**
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+ - **Multimodal Document Handling**: Process complex documents containing mixed content types (text, images, tables, formulas)
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+ - **Comprehensive Format Support**: Parse PDFs, images, DOC/DOCX/PPT/PPTX, and additional file types
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+ - **Multi-Element Extraction**: Extract and index text, images, tables, formulas, and document structure
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+ - **Multimodal Retrieval**: Query and retrieve diverse content types (text, images, tables, formulas) within RAG workflows
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+ - **Seamless Integration**: Works smoothly with LightRAG core and RAG-Anything frameworks
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+
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  **Quick Start:**
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  1. Install dependencies:
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  ```bash
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  pip install "magic-pdf[full]>=1.2.2" huggingface_hub
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  ```
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+ 2. Download MinerU model weights (refer to [MinerU Integration Guide](docs/mineru_integration_en.md))
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+ 3. Process multi-modal documents using the new MineruParser or RAG-Anything's process_document_complete:
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  ```python
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  from lightrag.mineru_parser import MineruParser
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  content_list, md_content = MineruParser.parse_pdf('path/to/document.pdf', 'output_dir')
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  # or for any file type:
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  content_list, md_content = MineruParser.parse_document('path/to/file', 'auto', 'output_dir')
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  ```
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+ 4. Query multimodal content with LightRAG refer to [docs/mineru_integration_en.md](docs/mineru_integration_en.md).
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  ## Token Usage Tracking
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