Morphik Core introduces an open-source alternative to traditional Retrieval-Augmented Generation (RAG) systems, specifically designed for complex technical and visual document processing. This multimodal platform enables developers to overcome limitations in traditional text-only systems by offering comprehensive tools that understand both visual and textual content—filling a critical gap for organizations dealing with technical documentation containing diagrams, schematics, and other visual elements.
The big picture: Morphik provides an integrated solution for processing multimodal documents through a combination of visual understanding technology and knowledge graph capabilities.
- The platform can process diverse document types including images, PDFs, and videos through a unified endpoint, eliminating the need for separate systems for different content types.
- Its open-source nature (with MIT licensing for core functionality) allows developers to implement advanced document understanding without proprietary constraints.
Key features: The system offers several capabilities beyond standard RAG approaches, focusing on visual content understanding and metadata extraction.
- It employs ColPali techniques for visual content comprehension, enabling users to query information contained within images and diagrams.
- The platform can automatically generate domain-specific knowledge graphs with minimal coding, using either pre-built system prompts or custom configurations.
- Morphik includes fast metadata extraction capabilities for documents, identifying elements like bounding boxes, classifications, and labels.
Integration capabilities: The platform is designed to work within existing enterprise ecosystems rather than requiring complete infrastructure changes.
- It offers connections to productivity tools like Google Suite, Slack, and Confluence, allowing organizations to enhance their current document systems.
- The system includes cache-augmented generation to create persistent key-value caches of documents, significantly improving response time for repeated queries.
Deployment options: Users can access Morphik through either cloud-based or self-hosted implementations depending on their requirements.
- A free tier is available through the cloud service, offering 200 pages and 100 queries at no cost.
- Self-hosting options exist for organizations with specific security or compliance requirements, though with limited support.
Implementation approach: Getting started with Morphik involves minimal code, with a Python SDK that simplifies document processing and querying.
- The example code shows that developers can ingest complex files and query specific technical details (like dimensions of components in assembly instructions) with just a few lines of code.
- While core functionality is open-source, certain enterprise features in the “ee” namespace operate under different licensing terms.
GitHub - morphik-org/morphik-core: Open source multi-modal RAG for building AI apps over private knowledge.