from config import *

@st.cache_data(ttl=3600)
def make_request(messages, 
                 max_tokens=1000, 
                 stream=False):
    
    client = InferenceClient(
        MODEL_PATH,
        token=HUGGING_FACE_API_KEY,
    )

    try:
        response = client.chat_completion(
            messages=messages,
            max_tokens=max_tokens,
            stream=stream,
        )

        return response.choices[0].message['content']
    
    except Exception as e:
        st.write(f"An error occurred: {e}")
        st.stop()


        

def get_token_amount(text,
                     model_name="gpt-4") -> int:
    
    """Uses the tiktoken library to check if a text is too long for a given model.
    Even tough we are using a Llama model, we are using the GPT-4 model ans an approximation.
    
    Args:
        text (str): The text to check.
        model_name (str): The name of the model to check. Defaults to "gpt-4".
        
    Returns:
        int: The number of tokens in the text.
    """

    encoding = tiktoken.encoding_for_model(model_name)
    tokens = encoding.encode(text)
    return len(tokens)

@st.cache_data
def annotate(topic, value):

    """
    Annotate the text
    """
    return (topic.replace('▁',''), str(value))