The codebase for the book "AI-Powered Search" (Manning Publications, 2025)
LitePali is a minimal, efficient implementation of ColPali for image retrieval and indexing, optimized for cloud deployment.
Knowledge pills on Neural Search
An Effective and Scalable Framework for Multimodal Search of Target Modality
PostgreSQL-native semantic search engine with multi-modal capabilities. Add AI-powered search to your existing database without separate vector databases, vendor fees, or complex setup. Features text + image search using CLIP embeddings, native SQL joins, and 10-minute Docker deployment.
3D Medical Image Retrieval in Radiology
Genomics Visualization Retrieval for Authoring with Multimodality
Collections of multimodal search libraries, service and research papers
Multimodal saree search app built using Amazon Titan Multimodal Embeddings model
An Effective and Scalable Framework for Multimodal Search with Target Modality
Leverage vector databases to swiftly construct a diverse range of applications through "Building Applications with Vector Databases" course!
Multi-Modal Search over fashion datasets. Information Retrieval Tasks optimised using Spotify's Annoy, using text embeddings over captions and words generated from image via classifiers. Experimentation and Optimisation of hyper-parameters
A multimodal search engine combining text and image embeddings for unified, efficient information retrieval.
A powerful multimodal document search engine that converts PDF documents into searchable vector embeddings using OpenAI's CLIP model. Enables cross-modal search across text and images with natural language queries through a modern Streamlit interface.
The first public transport search written in Flutter Web
HACKTOBERFEST '23 Open Source Contribution to Weaviate: Implemented python version of Multi-Modal Search using Weaviate
PoC мультимодального поиска изображений по текстовому описанию для фотохостинга с использованием ResNet50 и BERT. Использованы Python, TensorFlow, SentenceTransformers.
Multimodal search & recommender demo for the Netflix catalogue – powered by Sentence-Transformers, BLIP and Gradio.
🔍 Lab to learn how to implement multimodal search using Weaviate as a vector database
Add a description, image, and links to the multimodal-search topic page so that developers can more easily learn about it.
To associate your repository with the multimodal-search topic, visit your repo's landing page and select "manage topics."