blog_app.py

import os
from constants import openai_key
from langchain.llms import OpenAI
from langchain import PromptTemplate
from langchain.chains import LLMChain
from langchain.memory import ConversationBufferMemory
from langchain.chains import SequentialChain
import streamlit as st

os.environ["OPENAI_API_KEY"] = openai_key

# streamlit framework
st.title('Generate Effective Article on any topic with Trending Hashtags')
input_text = st.text_input("Search the topic you want")
search_button = st.button("Search")

# Prompt Templates
first_input_prompt = PromptTemplate(
    input_variables=['name'],
    template='''Generate article ideas on the topic: {name}
    but first create a simple description for this topic {name}, then generate your ideas,
    '''
)

# Memory
person_memory = ConversationBufferMemory(input_key='name', memory_key='chat_history')
dob_memory = ConversationBufferMemory(input_key='person', memory_key='chat_history')

# OPENAI LLMS
llm = OpenAI(temperature=0.8)
chain = LLMChain(llm=llm, prompt=first_input_prompt, verbose=True, output_key='person', memory=person_memory)

second_input_prompt = PromptTemplate(
    input_variables=['name'],
    template="Generate some trending hashtags for {name}"
)

chain2 = LLMChain(llm=llm, prompt=second_input_prompt, verbose=True, output_key='Hashtags', memory=dob_memory)

parent_chain = SequentialChain(chains=[chain, chain2], input_variables=['name'], output_variables=['person', 'Hashtags'], verbose=True)

if search_button:
    if input_text:
        st.write(parent_chain({'name': input_text}))

        with st.expander('Article History'):
            st.info(dob_memory.buffer)