Function main

tools/llm_api.py:244–271

()

        return None

def main():
    parser = argparse.ArgumentParser(description='Query an LLM with a prompt')
    parser.add_argument('--prompt', type=str, help='The prompt to send to the LLM', required=True)
    parser.add_argument('--provider', choices=['openai','anthropic','gemini','local','deepseek','azure','siliconflow'], default='openai', help='The API provider to use')
    parser.add_argument('--model', type=str, help='The model to use (default depends on provider)')
    parser.add_argument('--image', type=str, help='Path to an image file to attach to the prompt')
    args = parser.parse_args()

    if not args.model:
        if args.provider == 'openai':
            args.model = "gpt-4o" 
        elif args.provider == "deepseek":
            args.model = "deepseek-chat"
        elif args.provider == "siliconflow":
            args.model = "deepseek-ai/DeepSeek-R1"
        elif args.provider == 'anthropic':
            args.model = "claude-3-7-sonnet-20250219"
        elif args.provider == 'gemini':
            args.model = "gemini-2.0-flash-exp"
        elif args.provider == 'azure':
            args.model = os.getenv('AZURE_OPENAI_MODEL_DEPLOYMENT', 'gpt-4o-ms')  # Get from env with fallback

    client = create_llm_client(args.provider)
    response = query_llm(args.prompt, client, model=args.model, provider=args.provider, image_path=args.image)
    if response:
        print(response)
    else:
        print("Failed to get response from LLM")

if __name__ == "__main__":
    main()