Update main.py

main.py

@@ -5,6 +5,7 @@ import uvicorn
 import numpy as np
 from projects.DL_CatDog.DL_CatDog import preprocess_image, read_image, model_DL_CatDog
 from projects.ML_StudentPerformance.ML_StudentPerformace import predict_student_performance, create_custom_data, form1
+from projects.ML_DiabetesPrediction.ML_DiabetesPrediction import model_ML_DiabetesPrediction, form2
 
 app = FastAPI()
 
@@ -34,7 +35,7 @@ async def predict_DL_CatDog(file: UploadFile = File(...)):
     except Exception as e:
         return JSONResponse(content={"ok": -1, "message": f"Something went wrong! {str(e)}"}, status_code=500)
 
-# New Prediction route for ML_StudentPerformance
+# Prediction route for ML_StudentPerformance
 @app.post("/api/predict2")
 async def predict_student_performance_api(request: form1):
     print(request, end='\n\n\n\n')
@@ -55,6 +56,26 @@ async def predict_student_performance_api(request: form1):
     except Exception as e:
         return JSONResponse(content={"ok": -1, "message": f"Something went wrong! {str(e)}"}, status_code=500)
 
+# Prediction route for ML_DiabetesPrediction
+@app.post("/api/predict3")
+async def predict_student_performance_api(req: form2):
+    try:
+        input_data = (req.Pregnancies, req.Glucose, req.BloodPressure, req.SkinThickness, req.Insulin, req.BMI, req.DiabetesPedigreeFunction, req.Age)
+
+        # changing the input_data to numpy array
+        input_data_as_numpy_array = np.asarray(input_data)
+
+        # reshape the array as we are predicting for one instance
+        input_data_reshaped = input_data_as_numpy_array.reshape(1,-1)
+
+        # Perform the prediction
+        prediction = model_ML_DiabetesPrediction.predict(input_data_reshaped)
+
+        return JSONResponse(content={"ok": 1, "prediction": prediction[0]})
+    except Exception as e:
+        return JSONResponse(content={"ok": -1, "message": f"Something went wrong! {str(e)}"}, status_code=500)
+
+
 # Main function to run the FastAPI server
 if __name__ == "__main__":
     uvicorn.run(app, host="0.0.0.0", port=7860)