Update app.py

app.py

@@ -1,7 +1,6 @@
 import gradio as gr
 import chromadb
 from transformers import AutoTokenizer, AutoModel
-import faiss
 import numpy as np
 import torch
 
@@ -18,56 +17,7 @@ collection = client.create_collection(name="tree_images")
 
 # Custom dataset of tree descriptions (both decorated and undecorated)
 content = [
-    "Tree 1: Decorated with colorful lights and a star on top", 
-    "Tree 2: Undecorated, only a bare tree with no lights or ornaments",
-    "Tree 3: Decorated with silver tinsel and baubles", 
-    "Tree 4: Undecorated, only green branches",
-    "Tree 5: Decorated with red ribbons and golden ornaments",
-    "Tree 6: Undecorated, a plain pine tree",
-    "Tree 7: Decorated with multicolored lights and silver bells",
-    "Tree 8: Undecorated, just a tree with no decorations",
-    "Tree 9: Decorated with handmade ornaments and garlands",
-    "Tree 10: Undecorated, a simple tree without any adornment",
-    "Tree 11: Decorated with blue and white lights and a snowflake theme",
-    "Tree 12: Undecorated, only branches with no adornments",
-    "Tree 13: Decorated with red and green ornaments and candy canes",
-    "Tree 14: Undecorated, just a tall and natural-looking tree",
-    "Tree 15: Decorated with silver garlands and a star topper",
-    "Tree 16: Undecorated, a bare spruce tree",
-    "Tree 17: Decorated with gold and red ornaments, and a snowman figure",
-    "Tree 18: Undecorated, a simple fir tree with no extras",
-    "Tree 19: Decorated with colorful LED lights and a bow on top",
-    "Tree 20: Undecorated, just a bare tree with no lights or baubles",
-    "Tree 21: Decorated with small fairy lights and a red ribbon",
-    "Tree 22: Undecorated, just a simple tree with green branches",
-    "Tree 23: Decorated with golden stars and white snowflakes",
-    "Tree 24: Undecorated, just a natural green pine tree",
-    "Tree 25: Decorated with pink ornaments and a gold topper",
-    "Tree 26: Undecorated, no decorations, just a plain tree",
-    "Tree 27: Decorated with silver and blue ornaments and a festive ribbon",
-    "Tree 28: Undecorated, just a fresh pine tree",
-    "Tree 29: Decorated with white fairy lights and a Christmas angel on top",
-    "Tree 30: Undecorated, only the green foliage of the tree",
-    "Tree 31: Decorated with bright red ornaments and golden tinsel",
-    "Tree 32: Undecorated, no lights or decorations, just branches",
-    "Tree 33: Decorated with silver tinsel, green ribbons, and a star",
-    "Tree 34: Undecorated, plain with no adornments",
-    "Tree 35: Decorated with red and white ornaments, and a Santa figurine",
-    "Tree 36: Undecorated, just a bare tree",
-    "Tree 37: Decorated with rainbow lights and colorful ornaments",
-    "Tree 38: Undecorated, a simple evergreen tree with no additions",
-    "Tree 39: Decorated with small golden bells and a red bow",
-    "Tree 40: Undecorated, no ornaments or lights",
-    "Tree 41: Decorated with silver baubles, white snowflakes, and a red star",
-    "Tree 42: Undecorated, just a natural tree with no accessories",
-    "Tree 43: Decorated with multicolor ribbons and white angel decorations",
-    "Tree 44: Undecorated, no adornments, just the tree itself",
-    "Tree 45: Decorated with large silver baubles and a golden star",
-    "Tree 46: Undecorated, no decorations, just a green tree",
-    "Tree 47: Decorated with white snowflakes, red ribbons, and a Santa hat",
-    "Tree 48: Undecorated, a bare tree with no lights or ornaments",
-    "Tree 49: Decorated with small lights and star-shaped ornaments",
-    "Tree 50: Undecorated, only the tree, no adornments or lights"
+    # Your tree descriptions here...
 ]
 
 # Function to generate embeddings using the pre-trained model
@@ -83,33 +33,24 @@ def generate_embeddings(texts):
 # Generate embeddings for the content
 embeddings = generate_embeddings(content)
 
-# Add the embeddings to Chroma
+# Add the embeddings to Chroma using upsert
 for idx, text in enumerate(content):
-    collection.add_documents(
+    collection.upsert(
         documents=[text],  # the document (text) itself
         metadatas=[{"id": idx}],  # metadata associated with the document
         embeddings=[embeddings[idx]]  # the corresponding embeddings for the document
     )
 
-# Build FAISS index for efficient retrieval
-embeddings_np = np.array(embeddings).astype('float32')
-faiss_index = faiss.IndexFlatL2(embeddings_np.shape[1])
-faiss_index.add(embeddings_np)
-
 # Define the search function for Gradio interface
 def search(query):
     # Generate embedding for the query
     query_embedding = generate_embeddings([query])[0].reshape(1, -1)
     
-    # FAISS-based search
-    distances, indices = faiss_index.search(query_embedding, 3)
-    faiss_results = [content[i] for i in indices[0]]
-    
     # Chroma-based search
     chroma_results = collection.query(query_embeddings=query_embedding, n_results=3)["documents"]
     
     # Return results
-    return "FAISS Results: " + ", ".join(faiss_results) + "\nChroma Results: " + ", ".join(chroma_results)
+    return "Chroma Results: " + ", ".join(chroma_results)
 
 # Create the Gradio interface
 interface = gr.Interface(fn=search, inputs="text", outputs="text")