Update app.py

app.py

@@ -1,56 +1,37 @@
 from fastapi import FastAPI, HTTPException
+from fastapi.middleware.cors import CORSMiddleware
 from pydantic import BaseModel
 import numpy as np
-from huggingface_hub import hf_hub_download, HfApi
+from huggingface_hub import hf_hub_url, cached_download
 import joblib
-import os
-from datetime import datetime, timedelta
 
 app = FastAPI()
 
-REPO_ID = "GodfreyOwino/NPK_needs_mode2"
-FILENAME = "npk_needs_model.joblib"
-UPDATE_FREQUENCY = timedelta(days=1)
-
-def get_latest_model():
-    try:
-        api = HfApi()
-        remote_info = api.model_info(repo_id=REPO_ID)
-        remote_mtime = remote_info.lastModified
+# Add CORS middleware
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=["*"],
+    allow_credentials=True,
+    allow_methods=["*"],
+    allow_headers=["*"],
+)
 
-        cached_path = hf_hub_download(repo_id=REPO_ID, filename=FILENAME)
-        
-        if os.path.exists(cached_path):
-            local_mtime = datetime.fromtimestamp(os.path.getmtime(cached_path))
-            
-            if datetime.now() - local_mtime < UPDATE_FREQUENCY:
-                print("Using cached model (checked recently)")
-                return joblib.load(cached_path)
-            
-            if remote_mtime > local_mtime:
-                print("Downloading updated model")
-                cached_path = hf_hub_download(repo_id=REPO_ID, filename=FILENAME, force_download=True)
-            else:
-                print("Cached model is up-to-date")
-        else:
-            print("Downloading model for the first time")
-            cached_path = hf_hub_download(repo_id=REPO_ID, filename=FILENAME)
-        
-    except Exception as e:
-        print(f"Error checking/downloading model: {e}")
-        print(f"Error type: {type(e)}")
-        print(f"Error details: {str(e)}")
-        raise HTTPException(status_code=500, detail="Unable to download or find the model.")
-    
-    return joblib.load(cached_path)
+REPO_ID = "GodfreyOwino/NPK_needs_mode2"  # Replace with your actual repo name
+FILENAME = "npk_needs_model.joblib"
 
-model = get_latest_model()
-print("Model loaded successfully")
+try:
+    model = joblib.load(cached_download(hf_hub_url(REPO_ID, FILENAME)))
+    print("Model loaded successfully")
+except Exception as e:
+    print(f"Error loading model: {e}")
+    print(f"Error type: {type(e)}")
+    print(f"Error details: {str(e)}")
+    raise HTTPException(status_code=500, detail="Unable to download or find the model.")
 
 class InputData(BaseModel):
     features: list[float]
 
-@app.post("/predict")
+@app.post("/predict", tags=["Prediction"])
 async def predict(data: InputData):
     try:
         input_data = np.array(data.features).reshape(1, -1)
@@ -59,6 +40,6 @@ async def predict(data: InputData):
     except Exception as e:
         raise HTTPException(status_code=500, detail=f"Prediction error: {str(e)}")
 
-@app.get("/")
+@app.get("/", tags=["Root"])
 async def root():
     return {"message": "NPK Needs Prediction Model API"}