add api auth

.gitignore

@@ -2,4 +2,6 @@ __pycache__/
 .venv/
 
 weights/
-.env
+.env
+
+*test*

Dockerfile

@@ -9,7 +9,6 @@ ENV PATH="$VIRTUAL_ENV/bin:$PATH"
 
 COPY requirements.txt .
 RUN uv pip install --no-cache -r requirements.txt
-# RUN uv pip install numpy --upgrade
 
 COPY . .
 

main.py

@@ -1,15 +1,23 @@
 import os
 import atexit
 import numpy as np
+import json, requests
 from PIL import Image
 import tensorflow as tf
 from pathlib import Path
 from pydantic import BaseModel
-from fastapi import FastAPI, UploadFile
 from starlette.responses import RedirectResponse
 from database import update_data_field, cleanup
+from fastapi import FastAPI, UploadFile, HTTPException, Security, Depends
+from fastapi.security import APIKeyHeader
 
 
+DRISHTI_AUTH_KEY = os.environ.get("DRISHTI_AUTH_KEY")
+DRISHTI_AUTH_KEY_NAME = os.environ.get("DRISHTI_AUTH_KEY_NAME")
+
+if not DRISHTI_AUTH_KEY:
+    raise ValueError("DRISHTI_AUTH_KEY environment variable must be set")
+
 class Item(BaseModel):
     uuid: str
     time: str
@@ -18,10 +26,19 @@ class Item(BaseModel):
     soil_moisture: str
 
 
+api_key_header = APIKeyHeader(name=DRISHTI_AUTH_KEY_NAME, auto_error=True)
+
+async def verify_api_key(api_key: str = Security(api_key_header)):
+    if api_key != DRISHTI_AUTH_KEY:
+        raise HTTPException(
+            status_code=403,
+            detail="Invalid API key",
+        )
+    return api_key
+
 mongo_string = os.environ.get("MONGO_STRING")
 app = FastAPI(title="Dristhi Backend", description="APIs for Dristhi", version="1.0")
 
-
 def load_model():
     model_path = (
         Path(__file__).resolve().parent.parent
@@ -29,17 +46,18 @@ def load_model():
         / "plant_disease_classifier.h5"
     )
     model = tf.keras.models.load_model(model_path)
-
     return model
 
-
 @app.get("/")
-def display() -> str:
+async def display() -> str:
     response = RedirectResponse(url='https://github.com/epicshi')
     return response
 
 @app.post("/predict")
-def predict(file: UploadFile) -> str:
+async def predict(
+    file: UploadFile,
+    api_key: str = Depends(verify_api_key)
+) -> str:
     model = load_model()
 
     original_image = Image.open(file.file).convert("RGB")
@@ -48,14 +66,16 @@ def predict(file: UploadFile) -> str:
     preds = model.predict(np.expand_dims(preprocessed_image, axis=0))
 
     labels = ["Healthy", "Powdery", "Rust"]
-
     preds_class = np.argmax(preds)
     preds_label = labels[preds_class]
 
     return preds_label
 
 @app.post("/update-data")
-def update_data(item: Item) -> str:
+async def update_data(
+    item: Item,
+    api_key: str = Depends(verify_api_key)
+) -> str:
     if (
         item.humidity.lower() == "nan"
         or item.temperature.lower() == "nan"
@@ -73,11 +93,37 @@ def update_data(item: Item) -> str:
         },
     )
 
+@app.get("/fetch-news")
+async def fetch_news(
+    api_key: str = Depends(verify_api_key)
+):
+    news_api_key = os.environ.get("NEWS_API_KEY")
+    if not news_api_key:
+        raise HTTPException(
+            status_code=500,
+            detail="News API key not configured"
+        )
+    
+    response = requests.get(
+        'https://newsapi.org/v2/everything',
+        params={
+            'q': '(farmer OR agriculture OR "rural development" OR "farm laws" OR kisaan OR kisan) AND (India OR Maharashtra OR Punjab OR Karnataka OR "Uttar Pradesh")',
+            'language': 'en',
+            'sortBy': 'publishedAt',
+            'apiKey': news_api_key
+        }
+    )
+    if response.status_code != 200:
+        raise HTTPException(
+            status_code=500,
+            detail="News API request failed"
+        )
+    return json.loads(response.content)
 
 if __name__ == "__main__":
     import uvicorn
     try:
-        uvicorn.run(app, host="0.0.0.0", port=7860)
+        uvicorn.run("main:app", host="0.0.0.0", port=7860)
     finally:
         cleanup()
         atexit.register(cleanup)