RT Avi Chawla (@_avichawla)Get RAG-ready data from any unstructured file!@tensorlake transforms unstructured docs into RAG-ready data in a few lines of code. It returns the document layout, structured extraction, bounding boxes, etc.Works on any complex layout, handwritten docs and multilingual data. https://t.co/lZoNWZb2ip ...

If you found it insightful, reshare it with your network.Find me → @_avichawlaEvery day, I share tutorials and insights on DS, ML, LLMs, and RAGs.Avi Chawla (@_avichawla):Get RAG-ready data from any unstructured file!@tensorlake transforms unstructured docs into RAG-ready data in a few lines of code. It returns the document layout, structured extraction, bounding boxes, etc.Works on any complex layout, handwritten docs and multilingual data. https://t.co/lZoNWZb2ip ...

Product Overview - Tensorlake transforms unstructured documents into RAG-ready data with a few lines of code [1] - The solution provides document layout, structured extraction, and bounding boxes [1] - It supports complex layouts, handwritten documents, and multilingual data [1] Technology Focus - The company focuses on enabling RAG (Retrieval-Augmented Generation) applications [1] - The technology extracts structured information from unstructured files [1]

Model Context Protocol (MCP) - Model Context Protocol (MCP) 的清晰解释（附带视觉效果）[1]

General Overview - The document is a wrap-up message encouraging readers to reshare the content if they found it insightful [1] - It promotes the author's profile for daily tutorials and insights on DS (Data Science), ML (Machine Learning), LLMs (Large Language Models), and RAGs (Retrieval-Augmented Generation) [1] Focus Area - The author, Avi Chawla, shares explanations on Model Context Protocol (MCP) with visuals [1]

I hope this clarifies what MCP does.Over to you! What is your take on MCP and its future?In the thread below, I explained how to build an MCP server locally. https://t.co/d6O2fVrW33Avi Chawla (@_avichawla):Let's build an MCP server (100% locally): ...

Protocol Overview - Model Context Protocol (MCP) is explained with visuals [1]

System Overview - RAG-Anything is a graph-driven, all-in-one multimodal document processing RAG system built on LightRAG [1] - The system supports all content modalities within a single integrated framework [1] Open Source - The system is 100% open-source [1]

That's a wrap!If you found it insightful, reshare it with your network.Find me → @_avichawlaEvery day, I share tutorials and insights on DS, ML, LLMs, and RAGs.Avi Chawla (@_avichawla):A graph-powered all-in-one RAG system!RAG-Anything is a graph-driven, all-in-one multimodal document processing RAG system built on LightRAG.It supports all content modalities within a single integrated framework.100% open-source. https://t.co/XGpDK0Ctht ...

GitHub repo: https://t.co/Z1z6QE1v94 ...