from transformers import AutoTokenizer, TFGPT2LMHeadModel, pipeline
from transformers.pipelines import TextGenerationPipeline
from typing import Union

class QuoteGenerator():
    def __init__(self, model_name:str='gruhit13/quote_generator_v1'):
        self.model_name = model_name
        self.quote_generator: TextGenerationPipeline
        self.tokenizer = AutoTokenizer.from_pretrained(self.model_name)
        self.model = TFGPT2LMHeadModel.from_pretrained(self.model_name)
        self.default_tags = 'love,life'
        print("Model has been loaded")
    
    def load_generator(self) -> None:
        self.quote_generator = pipeline('text-generation', model=self.model, tokenizer=self.tokenizer)
        print("Pipeline has been generated")
    
    def preprocess_tags(self, tags: Union[None, str] = None) -> str:
        if tags is None:
            tags = self.default_tags
        
        return self.tokenizer.bos_token + tags + '<bot>:'

    def generate_quote(self, tags:Union[None, str]=None, 
                       min_length: int=3, max_length:int=60, 
                       top_p:float=0.9, top_k:int=5):
        
        tags = self.preprocess_tags(tags)
        print("Tags = ", tags)
        output = self.quote_generator(tags, min_length=min_length, max_length=max_length,
                                      temperature=1.0, top_k=5, top_p=top_p, early_stopping=True,
                                      num_beams=4)
        
        return output[0]['generated_text']