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#!/usr/bin/env python3
"""
Test with known working Hugging Face models
"""
import requests
import json
from PIL import Image
from io import BytesIO
def load_settings():
try:
with open('settings.json', 'r') as f:
return json.load(f)
except FileNotFoundError:
return {}
def test_working_models():
"""Test with models that are known to work"""
settings = load_settings()
api_token = settings.get('hugging_face_api_token')
if not api_token:
print("No API token found")
return
print(f"Testing with token: {api_token[:10]}...")
# Create a simple test image
test_image = Image.new('RGB', (224, 224), color='red')
buffer = BytesIO()
test_image.save(buffer, format="JPEG")
image_bytes = buffer.getvalue()
# Test different API approaches
models_to_test = [
"Salesforce/blip-image-captioning-base-large",
"microsoft/DialoGPT-medium",
"google/vit-base-patch16-224"
]
for model_name in models_to_test:
print(f"\nTesting {model_name}...")
API_URL = f"https://api-inference.huggingface.co/models/{model_name}"
headers = {"Authorization": f"Bearer {api_token}"}
# Try different payload formats
response = requests.post(
API_URL,
headers=headers,
data=image_bytes
)
print(f"Status: {response.status_code}")
if response.status_code == 200:
print(f"SUCCESS! Response: {response.json()}")
break
elif response.status_code == 503:
print("Model is loading, please wait...")
else:
print(f"Error: {response.text}")
# Also test token validity
print("\nTesting token validity...")
headers = {"Authorization": f"Bearer {api_token}"}
response = requests.get("https://huggingface.co/api/whoami", headers=headers)
print(f"Token check status: {response.status_code}")
if response.status_code == 200:
print(f"Token is valid. User info: {response.json()}")
else:
print(f"Token validation failed: {response.text}")
if __name__ == "__main__":
test_working_models() |