runtime error Better Gradio interface with proper error handling Cleaner layout Examples for testing Proper FastAPI + Gradio mounting

app.py

@@ -1,4 +1,4 @@
-# app.py - Hugging Face Spaces version with auto-extract
+# app.py - Hugging Face Spaces version - FIXED
 import os
 import zipfile
 from fastapi import FastAPI, HTTPException
@@ -28,7 +28,79 @@ print(f"Loading MedCPT model...")
 model = SentenceTransformer('ncbi/MedCPT-Query-Encoder')
 print("Initialization complete!")
 
-# FastAPI app
+# Gradio interface function
+def search_interface(query: str, num_results: int = 3):
+    """Simple web interface for testing"""
+    if not query.strip():
+        return "Please enter a search query."
+    
+    try:
+        embedding = model.encode(query).tolist()
+        results = collection.query(
+            query_embeddings=[embedding], 
+            n_results=int(num_results)
+        )
+        
+        if not results['documents'][0]:
+            return "No results found."
+        
+        output = ""
+        for i in range(len(results['documents'][0])):
+            output += f"\n{'='*60}\n"
+            output += f"Example {i+1}\n"
+            output += f"{'='*60}\n"
+            output += results['documents'][0][i] + "\n"
+            output += f"\nAnswer: {results['metadatas'][0][i].get('answer', 'N/A')}\n"
+            output += f"Similarity: {1 - results['distances'][0][i]:.3f}\n"
+        
+        return output
+    except Exception as e:
+        return f"Error: {str(e)}"
+
+# Create Gradio interface
+with gr.Blocks(title="MedQA Search") as demo:
+    gr.Markdown("# MedQA Search - USMLE Question Database")
+    gr.Markdown("Search for similar USMLE Step 1 questions using semantic similarity")
+    
+    with gr.Row():
+        with gr.Column():
+            query_input = gr.Textbox(
+                label="Medical Topic or Clinical Scenario",
+                placeholder="e.g., hyponatremia",
+                lines=2
+            )
+            num_results_slider = gr.Slider(
+                minimum=1,
+                maximum=5,
+                value=3,
+                step=1,
+                label="Number of Examples"
+            )
+            search_btn = gr.Button("Search", variant="primary")
+        
+        with gr.Column():
+            output_text = gr.Textbox(
+                label="Similar USMLE Questions",
+                lines=25,
+                max_lines=50
+            )
+    
+    search_btn.click(
+        fn=search_interface,
+        inputs=[query_input, num_results_slider],
+        outputs=output_text
+    )
+    
+    gr.Examples(
+        examples=[
+            ["hyponatremia", 3],
+            ["myocardial infarction", 2],
+            ["diabetic ketoacidosis", 3]
+        ],
+        inputs=[query_input, num_results_slider]
+    )
+
+# FastAPI for API endpoints
 app = FastAPI(title="MedQA Search API")
 
 app.add_middleware(
@@ -44,4 +116,33 @@ class SearchRequest(BaseModel):
     num_results: int = 3
 
 class SearchResponse(BaseModel):
-    results: list
+    results: list[dict]
+
+@app.get("/")
+async def root():
+    return {
+        "message": "MedQA Search API - Hugging Face Version", 
+        "status": "running",
+        "collection_count": collection.count()
+    }
+
+@app.post("/search_medqa", response_model=SearchResponse)
+async def search_medqa(request: SearchRequest):
+    """Search MedQA database for similar USMLE questions"""
+    try:
+        embedding = model.encode(request.query).tolist()
+        results = collection.query(
+            query_embeddings=[embedding], 
+            n_results=request.num_results
+        )
+        
+        formatted_results = []
+        for i in range(len(results['documents'][0])):
+            formatted_results.append({
+                "example_number": i + 1,
+                "question": results['documents'][0][i],
+                "answer": results['metadatas'][0][i].get('answer', 'N/A'),
+                "distance": results['distances'][0][i] if 'distances' in results else None
+            })
+        
+        return Sea