Update app.py to resolve credentials

app.py

@@ -5,7 +5,6 @@ from pydantic import BaseModel
 from fastapi import FastAPI, File, UploadFile
 import mlflow
 from xgboost import XGBClassifier
-import os
 from dotenv import load_dotenv
 
 description = """
@@ -30,14 +29,13 @@ tags_metadata = [
 ]
 
 load_dotenv()
-MLFLOW_TRACKING_APP_URI = os.environ["MLFLOW_TRACKING_APP_URI"]
-AWS_ACCESS_KEY_ID = os.environ["AWS_ACCESS_KEY_ID"]
-AWS_SECRET_ACCESS_KEY = os.environ["AWS_SECRET_ACCESS_KEY"]
 
-MODEL_URI = "models:/climate-fake-news-detector-model-XGBoost-v1@production"
+os.environ["AWS_ACCESS_KEY_ID"] = os.getenv("AWS_ACCESS_KEY_ID")
+os.environ["AWS_SECRET_ACCESS_KEY"] = os.getenv("AWS_SECRET_ACCESS_KEY")
+
+mlflow.set_tracking_uri("https://olivier-52-ml-flow.hf.space")
 
-mlflow.set_tracking_uri(MLFLOW_TRACKING_APP_URI)
-model = mlflow.sklearn.load_model(MODEL_URI)
+model = mlflow.sklearn.load_model("models:/climate-fake-news-detector-model-XGBoost-v1@production")
 
 app = FastAPI(
     title="API for Climate Fake News Detector",
@@ -86,4 +84,4 @@ def predict(features: PredictionFeatures):
     return {"prediction": float(prediction)}
 
 if __name__ == "__main__":
-    uvicorn.run(app, host="localhost", port=8000)
+    uvicorn.run(app, host="localhost", port=8001)