hope it works

Dockerfile

@@ -10,8 +10,8 @@ COPY . /app
 # Install the required packages from requirements.txt
 RUN pip install --no-cache-dir -r requirements.txt
 
-# Expose port 8000 for the FastAPI app
-EXPOSE 8000
+# Expose the correct port
+EXPOSE 7860
 
-# Command to run the FastAPI app with Uvicorn
-CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "8000"]
+# Run the FastAPI app on the expected port (7860)
+CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "7860"]

app.py

@@ -20,7 +20,7 @@ class AsteroidModel(torch.nn.Module):
 
 # Initialize the model and load the saved weights
 model = AsteroidModel()
-model.load_state_dict(torch.load('model.pth'))
+model.load_state_dict(torch.load('model.pth', weights_only=True))
 model.eval()  # Set model to evaluation mode
 
 app = FastAPI()
@@ -46,3 +46,10 @@ async def predict(features: dict):
         prediction = (output > 0.5).float().item()  # Convert to binary prediction
 
     return {"is_potentially_hazardous_asteroid": int(prediction)}
+
+import os
+
+if __name__ == "__main__":
+    import uvicorn
+    port = int(os.environ.get("PORT", 7860))  # Set the default port to 7860
+    uvicorn.run("app:app", host="0.0.0.0", port=port)

test.py

@@ -1,9 +1,9 @@
 import requests
 
-# URL of the deployed API (replace with your actual space URL)
-url = "https://<your-space-name>.hf.space/predict"
+# Replace with your actual Hugging Face Spaces URL
+url = "https://sushanadhikari-orreryspaceapp.hf.space/predict"
 
-# Sample input data
+# Sample input data based on the features used in your model
 data = {
     "absolute_magnitude_h": 22.1,
     "estimated_diameter_min_km": 0.127,
@@ -12,8 +12,13 @@ data = {
     "miss_distance_km": 386000.0
 }
 
-# Make a request to the API
+# Make a POST request to the API
 response = requests.post(url, json=data)
 
-# Display the prediction result
-print(response.json())
+# Check if the request was successful
+if response.status_code == 200:
+    # Print the model's prediction
+    print("Response from the model:", response.json())
+else:
+    print(f"Failed to get a response, status code: {response.status_code}")
+    print("Error details:", response.text)