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── 99313 repos indexed ── | filtered by tag: #multimodal-search
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lancedb/vectordb-recipes ★ 974 168 APPLICATION

This repository is a comprehensive collection of examples, tutorials, and applications demonstrating how to use LanceDB (a vector database) for various AI/ML applications. It showcases patterns for retrieval-augmented generation (RAG), multimodal search, chatbots, recommendation systems, and AI agents. The repository contains both Python and JavaScript/TypeScript implementations, with many examples featuring web interfaces using Streamlit, Gradio, or React. While it serves as a valuable resource for learning LanceDB integration patterns, the quality varies across examples, and some content is marked as archived.

RATING: 7.8/10 MAINT: active DRIFT: medium
#vector-database #rag-systems #llm-applications #multimodal-search #chatbots #ai #deep-learning #llms #machine-learning #multimodal #agents #embeddings #fine-tuning #gpt #langchain #llama-index #openai #rag #gpt-4-vision #multimodal-ai #lancedb
▸ 3 reusable components found
CaraJ7/MMSearch ★ 497 33 APPLICATION

MMSearch is a framework for evaluating large multimodal models (LMMs) as multi-modal search engines. It provides a pipeline (MMSearch-Engine) that enables any LMM to perform multimodal search by generating queries, retrieving web content, reranking results, and summarizing answers. The repository includes evaluation scripts for four tasks (end2end, requery, rerank, summarization) and a demo for running the engine on custom queries. The system relies on external dependencies like DuckDuckGo search, Playwright for web scraping, and Hugging Face datasets. The architecture is modular with separate components for model loading, prompt templating, web retrieval, content processing, and scoring.

RATING: 7.3/10 MAINT: active DRIFT: low
#multimodal-search #llm-evaluation #web-search-pipeline #image-processing #content-extraction #reranking #summarization
▸ 2 reusable components found
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