What types of search does AI Salesperson support?

It supports text-to-image product search using Fashion-CLIP, text-to-text semantic search with Sentence Transformers, and comprehensive metadata filtering by brand, category, gender, size, and price.

How does AI Salesperson integrate with e-commerce systems?

AI Salesperson offers seamless integration via the Model Context Protocol (MCP) using FastMCP, exposing all its powerful search and filtering tools through a streamable HTTP API for easy frontend connection.

What is AI Salesperson?

AI Salesperson is an AI-powered backend for e-commerce platforms, providing fast multimodal product search and robust metadata-based filtering capabilities to enhance online shopping experiences.

What data is needed to use AI Salesperson?

You need a product catalog in `output.json` format. This file should contain product metadata (brand, category, price, etc.) and precomputed image and text embeddings for efficient AI-powered search.

AI Salesperson

Name: AI Salesperson
Author: KrishChordiya

0•

Provides a fast, AI-powered backend for e-commerce platforms, enabling multimodal product search and metadata-based filtering.

This robust backend solution revolutionizes e-commerce product discovery by offering advanced AI-powered search capabilities. It supports text-to-image search using Fashion-CLIP for visual relevance and text-to-text semantic search with Sentence Transformers to deeply understand user queries. Furthermore, it provides a comprehensive API for filtering products by various metadata like brand, category, and price, alongside an inventory endpoint for dynamic filter generation, all built on the scalable FastMCP framework.

主要功能

01Robust Product Filtering API by brand, category, gender, size, and price

02Dynamic Inventory Metadata Endpoint for filter generation

03Text-to-Text Semantic Search with Sentence Transformers

04Text-to-Image Product Search using Fashion-CLIP

050 GitHub stars

06Seamless integration with Model Context Protocol (MCP) via FastMCP

使用案例

01Building dynamic and flexible product filtering systems for digital storefronts.

02Implementing intelligent search functionalities for e-commerce websites.

03Enhancing online store product discovery with multimodal search capabilities.