AI-Powered Catalog Search
Replace keyword-based catalog search with AI-powered semantic and visual search. Understands natural language queries like "lightweight summer dress under $50" and combines text understanding with visual similarity for comprehensive product discovery.
from mixpeek import Mixpeekclient = Mixpeek(api_key="YOUR_API_KEY")# Create product catalog collectioncollection = client.collections.create(namespace_id="ns_your_namespace",name="product_catalog",extractors=["multimodal-extractor", "text-extractor"])# Upload product data with rich metadataclient.buckets.upload(bucket_id="bkt_products",url="s3://your-bucket/products/",metadata_mapping={"price": "price", "category": "category", "brand": "brand"})# Build production retriever with filtering and rerankingretriever = client.retrievers.create(namespace_id="ns_your_namespace",name="catalog_search",collection_ids=["col_product_catalog"],stages=[{"type": "feature_search", "top_k": 100},{"type": "attribute_filter"},{"type": "rerank", "top_k": 20}])# Natural language catalog searchresults = client.retrievers.execute(retriever_id=retriever["retriever_id"],query={"text": "lightweight summer dress under $50"},filters={"in_stock": True, "price": {"$lte": 50}})for doc in results["results"]:print(f"{doc['metadata']['name']} - ${doc['metadata']['price']}")
Feature Extractors
Retriever Stages
rerank
Rerank documents using cross-encoder models for accurate relevance
