from application.llm.base import BaseLLM


class HuggingFaceLLM(BaseLLM):

    def __init__(
        self,
        api_key=None,
        user_api_key=None,
        llm_name="Arc53/DocsGPT-7B",
        q=False,
        *args,
        **kwargs,
    ):
        global hf

        from langchain.llms import HuggingFacePipeline

        if q:
            import torch
            from transformers import (
                AutoModelForCausalLM,
                AutoTokenizer,
                pipeline,
                BitsAndBytesConfig,
            )

            tokenizer = AutoTokenizer.from_pretrained(llm_name)
            bnb_config = BitsAndBytesConfig(
                load_in_4bit=True,
                bnb_4bit_use_double_quant=True,
                bnb_4bit_quant_type="nf4",
                bnb_4bit_compute_dtype=torch.bfloat16,
            )
            model = AutoModelForCausalLM.from_pretrained(
                llm_name, quantization_config=bnb_config
            )
        else:
            from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline

            tokenizer = AutoTokenizer.from_pretrained(llm_name)
            model = AutoModelForCausalLM.from_pretrained(llm_name)

        super().__init__(*args, **kwargs)
        self.api_key = api_key
        self.user_api_key = user_api_key
        pipe = pipeline(
            "text-generation",
            model=model,
            tokenizer=tokenizer,
            max_new_tokens=2000,
            device_map="auto",
            eos_token_id=tokenizer.eos_token_id,
        )
        hf = HuggingFacePipeline(pipeline=pipe)

    def _raw_gen(self, baseself, model, messages, stream=False, **kwargs):
        context = messages[0]["content"]
        user_question = messages[-1]["content"]
        prompt = f"### Instruction \n {user_question} \n ### Context \n {context} \n ### Answer \n"

        result = hf(prompt)

        return result.content

    def _raw_gen_stream(self, baseself, model, messages, stream=True, **kwargs):

        raise NotImplementedError("HuggingFaceLLM Streaming is not implemented yet.")