Function query_llm

tools/llm_api.py:124–242

Query an LLM with a prompt and optional image attachment. Args: prompt (str): The text prompt to send client: The LLM client instance model (str, optional): The model to use provider (str): The API provider to use image_path (str, optional): Path

(prompt: str, client=None, model=None, provider="openai", image_path: Optional[str] = None)

        raise ValueError(f"Unsupported provider: {provider}")

def query_llm(prompt: str, client=None, model=None, provider="openai", image_path: Optional[str] = None) -> Optional[str]:
    """
    Query an LLM with a prompt and optional image attachment.
    
    Args:
        prompt (str): The text prompt to send
        client: The LLM client instance
        model (str, optional): The model to use
        provider (str): The API provider to use
        image_path (str, optional): Path to an image file to attach
        
    Returns:
        Optional[str]: The LLM's response or None if there was an error
    """
    if client is None:
        client = create_llm_client(provider)
    
    try:
        # Set default model
        if model is None:
            if provider == "openai":
                model = os.getenv('OPENAI_MODEL_DEPLOYMENT', 'gpt-4o')
            elif provider == "azure":
                model = os.getenv('AZURE_OPENAI_MODEL_DEPLOYMENT', 'gpt-4o-ms')  # Get from env with fallback
            elif provider == "deepseek":
                model = "deepseek-chat"
            elif provider == "siliconflow":
                model = "deepseek-ai/DeepSeek-R1"
            elif provider == "anthropic":
                model = "claude-3-7-sonnet-20250219"
            elif provider == "gemini":
                model = "gemini-2.0-flash-exp"
            elif provider == "local":
                model = "Qwen/Qwen2.5-32B-Instruct-AWQ"
        
        if provider in ["openai", "local", "deepseek", "azure", "siliconflow"]:
            messages = [{"role": "user", "content": []}]
            
            # Add text content
            messages[0]["content"].append({
                "type": "text",
                "text": prompt
            })
            
            # Add image content if provided
            if image_path:
                if provider == "openai":
                    encoded_image, mime_type = encode_image_file(image_path)
                    messages[0]["content"] = [
                        {"type": "text", "text": prompt},
                        {"type": "image_url", "image_url": {"url": f"data:{mime_type};base64,{encoded_image}"}}
                    ]
            
            kwargs = {
                "model": model,
                "messages": messages,
                "temperature": 0.7,
            }