File size: 2,176 Bytes
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List all deployed Azure OpenAI models
Useful for verifying available models
"""
import os
from dotenv import load_dotenv
from openai import AzureOpenAI
# Load environment variables
load_dotenv()
def list_azure_models():
"""List all deployed Azure OpenAI models"""
try:
client = AzureOpenAI(
api_key=os.getenv('AZURE_OPENAI_API_KEY'),
api_version=os.getenv('AZURE_OPENAI_API_VERSION', '2024-08-01-preview'),
azure_endpoint=os.getenv('AZURE_OPENAI_ENDPOINT')
)
print("="*80)
print("AZURE OPENAI DEPLOYED MODELS")
print("="*80)
# List models
models = client.models.list()
print(f"\n📊 Total Models: {len(list(models))}")
print(f"\nDeployed Models:")
print("-" * 80)
model_list = []
for model in models:
model_list.append({
'id': model.id,
'created': model.created if hasattr(model, 'created') else 'N/A'
})
# Sort by id
model_list.sort(key=lambda x: x['id'])
# Categorize models
vision_models = []
text_models = []
for model in model_list:
model_id = model['id']
if any(keyword in model_id.lower() for keyword in ['vision', 'multimodal', 'gpt-4.1', 'gpt-5', 'claude']):
vision_models.append(model_id)
else:
text_models.append(model_id)
print(f"\n🖼️ Vision Models ({len(vision_models)}):")
for model_id in vision_models:
print(f" ✅ {model_id}")
print(f"\n📝 Text Models ({len(text_models)}):")
for model_id in text_models:
print(f" ✅ {model_id}")
print("\n" + "="*80)
except Exception as e:
print("="*80)
print("AZURE OPENAI CONNECTION ERROR")
print("="*80)
print(f"\n❌ Error: {e}")
print("\nPlease check:")
print(" 1. AZURE_OPENAI_API_KEY in .env file")
print(" 2. AZURE_OPENAI_ENDPOINT in .env file")
print(" 3. API version compatibility")
if __name__ == "__main__":
list_azure_models()
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