upload

.gitignore

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+__pycache__/
+*.pyc
+*.pyo
+*.pyd
+.Python
+.env
+.venv
+env/
+venv/
+.DS_Store
+*.log
+.pytest_cache/
+.coverage
+htmlcov/
+dist/
+build/
+*.egg-info/

app.py

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+# app.py - Hugging Face Spaces version
+import os
+from fastapi import FastAPI, HTTPException
+from fastapi.middleware.cors import CORSMiddleware
+from pydantic import BaseModel
+import chromadb
+from sentence_transformers import SentenceTransformer
+import gradio as gr
+
+# Database path
+DB_PATH = "./medqa_db"
+
+# Initialize
+print(f"Loading database from: {DB_PATH}")
+client = chromadb.PersistentClient(path=DB_PATH)
+collection = client.get_collection("medqa")
+print(f"Loading MedCPT model...")
+model = SentenceTransformer('ncbi/MedCPT-Query-Encoder')
+print("Initialization complete!")
+
+# FastAPI app
+app = FastAPI(title="MedQA Search API")
+
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=["*"],
+    allow_credentials=True,
+    allow_methods=["*"],
+    allow_headers=["*"],
+)
+
+class SearchRequest(BaseModel):
+    query: str
+    num_results: int = 3
+
+class SearchResponse(BaseModel):
+    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 SearchResponse(results=formatted_results)
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=str(e))
+
+# Gradio interface (optional - gives you a web UI)
+def search_interface(query: str, num_results: int = 3):
+    """Simple web interface for testing"""
+    try:
+        embedding = model.encode(query).tolist()
+        results = collection.query(
+            query_embeddings=[embedding], 
+            n_results=num_results
+        )
+        
+        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
+demo = gr.Interface(
+    fn=search_interface,
+    inputs=[
+        gr.Textbox(label="Medical Topic or Clinical Scenario", placeholder="e.g., hyponatremia"),
+        gr.Slider(1, 5, value=3, step=1, label="Number of Examples")
+    ],
+    outputs=gr.Textbox(label="Similar USMLE Questions", lines=20),
+    title="MedQA Search - USMLE Question Database",
+    description="Search for similar USMLE Step 1 questions using semantic similarity"
+)
+
+# Mount Gradio app and FastAPI
+app = gr.mount_gradio_app(app, demo, path="/")
+
+if __name__ == "__main__":
+    import uvicorn
+    uvicorn.run(app, host="0.0.0.0", port=7860)

readme.txt

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+---
+title: MedQA Search
+emoji: 🏥
+colorFrom: blue
+colorTo: green
+sdk: gradio
+sdk_version: 4.44.0
+app_file: app.py
+pinned: false
+---
+
+# MedQA Search API
+
+USMLE Step 1 question database with semantic search.

requirements.txt

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+fastapi==0.104.1
+uvicorn[standard]==0.24.0
+chromadb==0.4.18
+sentence-transformers==2.2.2
+pydantic==2.5.0
+torch==2.1.0
+numpy==1.24.3