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HEMANT GHUGE

Problem Zeroth, Tech... • 4m

Most people think of RAG (Retrieval-Augmented Generation) as a text-only thing. But when we apply it to images, it unlocks serious potential — especially in safety, retail, and surveillance. I recently explored Vision-RAG using Weaviate + LangChain to enable text-to-image retrieval from large camera datasets. Here’s a simplified breakdown: 🧠 Query: “Show me all images with a broken bumper” 🔍 Weaviate retrieves semantically matched images (via CLIP embeddings) 🖼️ GenAI or Vision models add context, summaries, or auto-tags 💡 Outcome: Faster QA, visual analytics, or even chatbot interfaces for cameras It’s like giving memory and understanding to your visual data. Would love to hear how others are using RAG outside of just documents.

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