Create app.py

app.py

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+import gradio as gr
+from io import BytesIO
+from base64 import b64encode
+from pinecone_text.sparse import BM25Encoder
+from pinecone import Pinecone
+from sentence_transformers import SentenceTransformer
+from datasets import load_dataset
+
+model = SentenceTransformer('sentence-transformers/clip-ViT-B-32')
+
+fashion = load_dataset("ashraq/fashion-product-images-small", split="train")
+images = fashion['image']
+metadata = fashion.remove_columns('image')
+
+INDEX_NAME = 'srinivas-hybrid-search'
+PINECONE_API_KEY = os.getenv(pinecone_api_key)
+pinecone = Pinecone(api_key=PINECONE_API_KEY)
+index = pinecone.Index(INDEX_NAME)
+bm25 = BM25Encoder()
+bm25.fit(metadata['productDisplayName'])
+