import os
import streamlit as st
from langchain.llms import OpenAI
from langchain.prompts import PromptTemplate
from langchain.chains import LLMChain, SequentialChain
from langchain.memory import ConversationBufferMemory
from langchain.utilities import WikipediaAPIWrapper
from transformers import GPT2LMHeadModel, GPT2Tokenizer

# Load the GPT-2 model and tokenizer
model_name = "gpt2"
tokenizer = GPT2Tokenizer.from_pretrained(model_name)
OpenAI = GPT2LMHeadModel.from_pretrained(model_name)


# app framework
st.title('Youtube Content Studio 🚀')
prompt=st.text_input('Plug in your prompt here')

#Prompt templates
title_template=PromptTemplate(
    input_variables=['topic'],
    template='write me a youtube video title about {topic}'
)
script_template=PromptTemplate(
    input_variables=['title','wikipedia_research'],
    template='write me a youtube script based on this title TITLE: {title} while leveraging this wikipedia research: {wikipedia_research}'
)

# Memory
title_memory=ConversationBufferMemory(input_key='topic',memory_key='chat_history')
script_memory=ConversationBufferMemory(input_key='title',memory_key='chat_history')
# LLMS
llm=OpenAI(temperature=0.9)
title_chain=LLMChain(llm=llm,prompt=title_template,verbose=True,output_key='title',memory=title_memory)
script_chain=LLMChain(llm=llm,prompt=script_template,verbose=True,output_key='script',memory=script_memory)

wiki=WikipediaAPIWrapper()

# Show stuff to the screen if there is a prompt
if prompt:
    title=title_chain.run(prompt)
    wiki_research=wiki.run(prompt)
    script=script_chain.run(title=title,wikipedia_research=wiki_research)
    st.write(title)
    st.write(script)
    
    
    with st.expander('Title History'):
        st.info(title_memory.buffer)
    with st.expander('Script History'):
        st.info(script_memory.buffer)    
    with st.expander('Wikipedia research History'):
        st.info(wiki_research)