from openai import AsyncOpenAI

LLM_URL = "http://172.16.29.102:8001/v1/"

# item structure:
# item = {
#     'id' : '',
#     'system_prompt' : '',
#     'user_prompt' : '',
#     'assistant_prompt' : '',
# }
                
async def process_item(messages, reasoning_effort= 'medium', temperature= 0.4, top_p= 0.9, max_tokens= 2048):
    """
    generates answer with gpt-oss-120b model
    
    **Args:
        reasoning_effort = 'medium' # -> low / high / medium
        temperature = 0.4  # 0-1 -> creativity
        top_p = 0.9  # 0-1 -> logic
        max_tokens = 2048 # -> ... 128K
    ** Returns(tuple):
        returns True, generated answer / False, failed message
    """
    try:
        async with AsyncOpenAI(base_url= LLM_URL, api_key="EMPTY") as client:
            
            model_name = 'gpt-oss-120b'
            
            # messages = [
            #     {"role": "system", "content": prompt_params.get("system_prompt", "")},
            #     {"role": "user", "content": prompt_params.get("user_prompt", "")},
            # ]
            # if prompt_params.get("assistant_prompt"):
            #     messages.append(
            #         {"role": "assistant", "content": prompt_params["assistant_prompt"]}
            #     )
            # print(f'==== max_token {max_token}')

            response = await client.chat.completions.parse(
                model= model_name,
                messages= messages,
                temperature= temperature, # 0-1
                top_p=top_p, # 0-1
                reasoning_effort= reasoning_effort, # low , high , medium
                # max_tokens= max_tokens, # ... 128K
                stop= None,
                )
            
            # print('666666666666666666666666666666666')
            # print(f"response.choices[0].message.parsed: {response.choices[0].message.parsed}")
            # print('666666666666666666666666666666666')
            
            if response and response.choices : # and response.choices[0].message.parsed:
                response_message = response.choices[0].message.content
                return True, response_message
                
    except Exception as e:
        response_message = 'error in llm response generation!'
        print('!!!!!!!!!!!!!!!!!!!!!!!!!')
        print(e)
        print('!!!!!!!!!!!!!!!!!!!!!!!!!')
        return False, response_message