from langchain_huggingface import ChatHuggingFace, HuggingFaceEndpoint
from langchain_openai import ChatOpenAI

from args import LLMInterface, Args, AgentPreset


class LLMFactory():

    @classmethod
    def create(cls, agent_preset: AgentPreset):
        interface = agent_preset.get_interface()

        if interface == LLMInterface.OPENAI:
            model = cls._create_openai_model(agent_preset)
        elif interface == LLMInterface.HUGGINGFACE:
            model = cls._create_huggingface_model(agent_preset)
        else:
            raise ValueError(f"Interface '{interface}' is not supported !")
        
        return model

    @staticmethod
    def _create_openai_model(agent_preset: AgentPreset):
        model_name = agent_preset.get_model_name()
        temperature = agent_preset.get_temperature()
        max_tokens = agent_preset.get_max_tokens()
        repeat_penalty = agent_preset.get_repeat_penalty()

        kwargs = {
            "name": model_name,
            "model": model_name,
            "base_url": Args.api_base,
            "api_key": Args.api_key,
            "temperature": temperature,
            "max_completion_tokens": max_tokens,
            "frequency_penalty": repeat_penalty
        }

        model = ChatOpenAI(**kwargs)

        return model

    @staticmethod
    def _create_huggingface_model(agent_preset: AgentPreset):
        model_name = agent_preset.get_model_name()
        temperature = agent_preset.get_temperature()
        max_tokens = agent_preset.get_max_tokens()
        repeat_penalty = agent_preset.get_repeat_penalty()

        kwargs = {
            "name": model_name,
            "model": model_name,
            "temperature": temperature,
            "max_new_tokens": max_tokens,
            "repetition_penalty": repeat_penalty
        }

        llm = HuggingFaceEndpoint(**kwargs)
        model = ChatHuggingFace(llm=llm)

        return model