import requests
import pprint

# The URL where your local FastAPI server is running
API_URL = "http://127.0.0.1:8000/run-prediction-batch"

def trigger_prediction_job():
    """
    Sends a POST request to the API to start the prediction batch job.
    """
    print(f"🚀 Sending request to API endpoint: {API_URL}")
    
    try:
        # The request doesn't need a body for this endpoint
        response = requests.post(API_URL, timeout=300) # 5-minute timeout

        # Raise an exception if the request returned an unsuccessful status code
        response.raise_for_status()

        print("\n✅ API request successful!")
        print("--- API Response ---")
        
        # Pretty-print the JSON response from the server
        pprint.pprint(response.json())

    except requests.exceptions.HTTPError as http_err:
        print(f"❌ HTTP error occurred: {http_err}")
        print(f"Response Body: {response.text}")
    except requests.exceptions.RequestException as req_err:
        print(f"❌ A critical request error occurred: {req_err}")
        print("Is the FastAPI server running? Start it with 'uvicorn main:app --reload'")
    except Exception as e:
        print(f"❌ An unexpected error occurred: {e}")

if __name__ == "__main__":
    # How to use:
    # 1. In one terminal, run your FastAPI server: uvicorn main:app --reload
    # 2. In a second terminal (with venv activated), run this script: python client.py
    trigger_prediction_job()