from langchain.prompts import PromptTemplate
from langchain.chains import LLMChain
from langchain.llms import OpenAI

from load_model import call_palm
from calling_apis import google_api_key, openai_api_key

def product_description_gen(product_name:str, product_desc:str, tone_of_voice:str, language='En', model_name = 'Google Palm 2', creativity = 'Original') -> str:
    
    '''
    Description:
        This function generates an engaging product description based on user-provided inputs. 
        It utilizes the LangChain library to prompt an AI model (Language Model) to create a product description tailored to the specified product name, description, tone of voice, and a provided LLM (Long Language Model).
    '''

    '''
    Parameters:
        product_name (str) -> Required: The name of the product for which the description is generated.
        product_desc (str) -> Required: A brief description of the product.
        tone_of_voice (str) -> Required: The intended tone of the product description (e.g., professional, friendly, persuasive).
        language (str): Opitonal Parameter -> The language of the model.
        creativity (str): Optional Parameter -> Controling the randomness of the model. Default value is Original
        model_name (str): Optional Parameter -> select the LLM model. Default Value is Google Palm 2
    '''

    '''
    Return Value:
        product_desc (str): The generated Amazon product description.
    '''
    
    temp = 0

    if creativity == 'Original':
        temp = 0
    elif creativity == 'Balanced':
        temp = 0.25
    elif creativity == 'Creative':
        temp = 0.5
    elif creativity == 'Spirited':
        temp = 0.75
    elif creativity == 'Visionary':
        temp = 1


    if model_name == 'Google Palm 2':
        llm = call_palm(google_api_key, temperature=temp)

    elif model_name == 'GPT-3.5':
        llm = OpenAI(model_name='gpt-3.5-turbo', openai_api_key=openai_api_key, temperature=temp)

    elif model_name == 'GPT-4':
        llm = OpenAI(model_name='gpt-4', openai_api_key=openai_api_key, temperature=temp)


    if language == 'En':
        
        productDesc_prompt = f"Write an engagging and {tone_of_voice} Amazon product description of {product_name} Product here is a short description of my product:\n\n{product_desc}\n"
        productDesc_promptTemp = PromptTemplate(
        input_variables=["text_input"],
        template="You are a content creator and product description writer who helps clients to write their product description on amazon:\n{text_input}\nAmazon Product Description:")
    
    elif language == 'Ar':
        
        productDesc_prompt = f"اكتب وصفًا جذابًا و{tone_of_voice} عن منتج {product_name} في أمازون. هنا وصف قصير لمنتجي:\n\n{product_desc}\n"
        productDesc_promptTemp = PromptTemplate(
        input_variables=["text_input"],
        template="أنت كاتب محتوى وكاتب وصف المنتجات الذي يساعد العملاء في كتابة وصف منتجاتهم على أمازون:\n{text_input}\nوصف منتج أمازون:")

    productDesc_extraction_chain = LLMChain(llm=llm, prompt=productDesc_promptTemp)
    product_desc = productDesc_extraction_chain.run(productDesc_prompt)
    
    return product_desc