Update app.py

app.py

@@ -1,53 +1,54 @@
 import os
 import streamlit as st
 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
 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)
-
+model = GPT2LMHeadModel.from_pretrained(model_name)
 
 # app framework
 st.title('Youtube Content Studio 🚀')
-prompt=st.text_input('Plug in your prompt here')
+prompt = st.text_input('Plug in your prompt here')
 
-#Prompt templates
-title_template=PromptTemplate(
+# 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'],
+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')
+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)
+llm = model
+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()
+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)
+    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)    
+        st.info(script_memory.buffer)
     with st.expander('Wikipedia research History'):
-        st.info(wiki_research)    
+        st.info(wiki_research)
+