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Morphik - An open-source multimodal retrieval enhancement and generation tool

Morphik is an open-source multimodal retrieval augmented generation (RAG) tool designed for processing highly technical and visually rich documents. It supports searching various document formats including images, PDFs, and videos, and utilizes ColPal...

What is Morphik?

Morphik is an open-source multimodal retrieval augmented generation (RAG) tool designed for handling highly technical and visually rich documents. It supports searching documents in various formats, including images, PDFs, and videos, and employs technologies such as ColPali to understand the visual content within documents. Morphik features fast metadata extraction capabilities, capable of extracting bounding boxes, tags, and categories from documents.

Morphik's main functions

  • Multimodal data processingIt can handle various file formats such as text, PDF, images, and videos.
  • Intelligent file parsingIt automatically divides files into smaller chunks and generates embeddings, making subsequent retrieval and processing easier.
  • ColPali Multimodal EmbeddingIt combines text and image content for efficient retrieval and understands the visual content of documents.
  • Knowledge Graph ConstructionWith just one line of code, you can build a knowledge graph for a specific domain and automatically extract entities and relationships.
  • Natural Language Rule EngineDefine rules using natural language to extract structured information from unstructured data.
  • Data Management and IntegrationIt supports multi-user and folder-level data organization and isolation. It supports the registration and use of hundreds of different AI models, which can be flexibly configured according to task requirements.
  • Fast metadata extractionQuickly extract metadata from documents, including bounding boxes, tags, categories, etc.

Morphik's technical principles

  • Multimodal embedding technology (ColPali)Morphik employs ColPali technology, treating document pages as images and generating embedded representations that include layout, typography, and visual context information, enabling unified retrieval of images and text. This allows the system to process text content and understand information within images, such as charts and pictures.
  • Enhance search capabilitiesThe introduction of knowledge graphs enhances the accuracy and depth of retrieval. Users can more intuitively understand the concepts and information in documents through the relationship paths in the graph.
  • Pretreatment and freezing techniquesMorphik creates a persistent key-value cache by preprocessing data and "freezing" document state. This reduces the overhead of repetitive calculations, lowers computational costs, and significantly improves the speed of retrieval and generation.
  • Hybrid retrieval architectureMorphik's retrieval process combines multiple technologies, including vector-based semantic search, rule-based filtering, knowledge graph expansion, and relevance reordering algorithms. This ensures the accuracy and relevance of the retrieval results.

Morphik's project address

Application scenarios of Morphik

  • Technical document processingSuitable for handling complex documents such as technical manuals, API documentation, and research papers.
  • Enterprise knowledge managementAs an enterprise-level knowledge base, it helps researchers and enterprise users manage and retrieve knowledge efficiently.
  • Smart application developmentIt provides developers with tools to quickly build AI-driven applications.
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