Enables low-latency multimodal search across a footwear image database using voice, text, and image queries.
Sponsored
This project brings to life a multimodal search web application, allowing users to explore a footwear image database not just by typing keywords, but by speaking a description or showing an image. Built on an MCP-based architecture, it seamlessly blends voice, text, and image queries into a single, intuitive experience. The system aims to demonstrate how MCP architecture enhances multimodal search and how libraries like `faster-whisper` improve audio-to-text conversion latency, transforming search into a natural conversation with data.
Key Features
010 GitHub stars
02MCP Client–Server architecture for distributed multimodal processing
03Vector search with multimodal embeddings via ChromaDB
04Low-latency multilingual audio transcription powered by Faster-Whisper
05Interactive Gradio UI for seamless user interaction
06Detailed latency metrics for transcription, MCP tool, and post-processing
Use Cases
01Searching product databases (e.g., footwear) using natural language (voice/text) or images
02Enhancing e-commerce platforms with intuitive multimodal product discovery capabilities
03Demonstrating and benchmarking low-latency, multimodal search system architectures
