app.py

import os
from apikey import apikey

import streamlit as st
from langchain.llms import OpenAI
from langchain.prompts import PromptTemplate
# from langchain.chains import LLMChain, SequentialChain
from langchain.chains import LLMChain
from langchain.memory import ConversationBufferMemory
from langchain.utilities import WikipediaAPIWrapper

os.environ['OPENAI_API_KEY'] = apikey

# App framework
st.title('🦜️🔗 Book GPT Recommender 📚')
prompt = st.text_input('Give me a topic, you\'ll get back some good books:')

# Prompt templates
title_template = PromptTemplate(
    input_variables=['topic'],
    template='give me some book titles about {topic}'
)

script_template = PromptTemplate(
    input_variables=['title', 'wikipedia_research'],
    template='write me a summary script of the given topic 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
)

# sequential_chain = SequentialChain(
#     chains=[title_chain, script_chain],
#     input_variables=['topic'],
#     output_variables=['title', 'script'],
#     verbose=True
# )

wiki = WikipediaAPIWrapper()

# Show response to the screen if there's a prompt
if prompt:
    # response = sequential_chain({'topic': prompt})
    
    # st.write(response['title'])
    # st.write(response['script'])

    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'):
        st.info(wiki_research)