src/step10_demo_request.py

import sys
import requests
import mimetypes
import os

def main():
    if len(sys.argv) < 2:
        print("Usage: python src/step10_demo_request.py path/to/image.jpg")
        sys.exit(1)

    img_path = sys.argv[1]
    url = "http://127.0.0.1:8000/predict"

    mime_type, _ = mimetypes.guess_type(img_path)
    if mime_type is None:
        mime_type = "application/octet-stream"

    print(f"Sending: {img_path} -> {url} (mime: {mime_type})")

    try:
        with open(img_path, "rb") as f:
            files = {"file": (os.path.basename(img_path), f, mime_type)}
            r = requests.post(url, files=files, timeout=60)

        print("Request sent.")
        print("Status code:", r.status_code)
        print("Response headers:", dict(r.headers))

        try:
            print("JSON response:", r.json())
        except ValueError:
            print("Non-JSON response text:", r.text)

        # Optional: raise for non-2xx to get exception trace if desired
        # r.raise_for_status()

    except requests.exceptions.RequestException as e:
        print("Request failed:", repr(e))
    except FileNotFoundError:
        print("File not found:", img_path)
    except Exception as e:
        print("Unexpected error:", repr(e))

if __name__ == "__main__":
    main()
# --- IGNORE ---
# This script demonstrates how to send an image file to the FastAPI
# prediction endpoint and print the response containing predicted
# vehicle damage classes and confidence scores.