Upload app.py

app.py

@@ -0,0 +1,111 @@
+"""
+Semantic Quote Search Engine
+AIPI 510 - Deployed on Hugging Face Spaces, Jaideep
+"""
+
+import gradio as gr
+from sentence_transformers import SentenceTransformer
+import chromadb
+import os
+
+# intialization
+
+# Load embedding model
+
+model = SentenceTransformer('sentence-transformers/all-MiniLM-L6-v2')
+print("Model loaded!")
+
+# Load existing ChromaDB (pre-built, not created on the fly)
+
+chroma_path = "./chromadb"
+client = chromadb.PersistentClient(path=chroma_path)
+collection = client.get_collection("quotes_collection")
+print(f"Loaded collection with {collection.count()} documents!")
+
+
+# SEARCH FUNCTION
+def semantic_search(query, n_results=5):
+    """
+    Perform semantic search over the quotes collection.
+    """
+    # Encode query using the same model
+    query_embedding = model.encode([query])
+    
+    # Query ChromaDB for similar documents
+    results = collection.query(
+        query_embeddings=query_embedding.tolist(),
+        n_results=n_results,
+        include=['documents', 'metadatas', 'distances']
+    )
+    
+    # Format results nicely
+    output = []
+    for i in range(len(results['documents'][0])):
+        meta = results['metadatas'][0][i]
+        distance = results['distances'][0][i]
+        similarity = 1 - (distance / 2)  # Convert distance to similarity score
+        
+        result_text = f"""
+### Result {i+1} (Similarity: {similarity:.1%})
+
+> "{meta['quote']}"
+
+**— {meta['author']}**
+
+🏷️ *Tags: {meta['tags']}*
+"""
+        output.append(result_text)
+    
+    return "\n---\n".join(output)
+
+
+def search_quotes(query, num_results):
+    """Wrapper function for Gradio interface"""
+    if not query.strip():
+        return "Please enter a search query!"
+    return semantic_search(query, n_results=int(num_results))
+
+
+# gradio interface
+demo = gr.Interface(
+    fn=search_quotes,
+    inputs=[
+        gr.Textbox(
+            label="🔍 Search Query",
+            placeholder="Try: 'love', 'success', 'wisdom', 'courage'...",
+            lines=2
+        ),
+        gr.Slider(
+            minimum=1,
+            maximum=10,
+            value=5,
+            step=1,
+            label=" Number of Results"
+        )
+    ],
+    outputs=gr.Markdown(label=" Search Results"),
+    title=" Semantic Quote Search Engine",
+    description="""
+## Search through famous quotes using AI-powered semantic similarity!
+
+Unlike traditional keyword search, this understands the **meaning** of your query.
+
+**How it works:**
+1. Your query is converted to a vector using a transformer model
+2. We find quotes with the most similar meaning in our database
+3. Results are ranked by semantic similarity
+
+*Built for AIPI 510: Data Sourcing for Analytics | Duke University*
+""",
+    examples=[
+        ["finding happiness in life", 5],
+        ["overcoming fear and challenges", 5],
+        ["the importance of friendship", 3],
+        ["learning from mistakes", 5],
+        ["believing in yourself", 3]
+    ]
+)
+
+# Launch the app
+if __name__ == "__main__":
+    demo.launch()