SequentialChain and ConversationalBufferMemory

Author: screwgoth

first/app.py

@@ -4,11 +4,12 @@
 import streamlit as st
 from langchain.llms import OpenAI
 from langchain.prompts import PromptTemplate
-from langchain.chains import LLMChain, SimpleSequentialChain
+from langchain.chains import LLMChain, SequentialChain
+from langchain.memory import ConversationBufferMemory
 
 os.environ['OPENAI_API_KEY'] = apikey
 
-st.title('🦜🔗 LangChain 0.0.193 Tutorial - YouTube GPT Creator ')
+st.title('🦜🔗 LangChain Tutorial - YouTube GPT Creator - by Raseel ')
 prompt = st.text_input('Prompt: Write me a Youtube Video Script about')
 
 # Prompt Templates
@@ -22,14 +23,24 @@
     template='Write me a Youtube Video script based on this title, TITLE {title}'
 )
 
+# Memory
+memory = ConversationBufferMemory(input_key='topic', memory_key='chat_history')
+
 # LLMs
 llm = OpenAI(temperature=0.9)
-title_chain = LLMChain(llm=llm, prompt=title_template, verbose=True)
-script_chain = LLMChain(llm=llm, prompt=script_template, verbose=True)
+title_chain = LLMChain(llm=llm, prompt=title_template, verbose=True, output_key='title', memory=memory)
+script_chain = LLMChain(llm=llm, prompt=script_template, verbose=True, output_key='script', memory=memory)
 
-sequential_chain = SimpleSequentialChain(chains=[title_chain, script_chain], verbose=True)
+sequential_chain = SequentialChain(chains=[title_chain, script_chain],
+                                   input_variables=['topic'],
+                                   output_variables=['title', 'script'],
+                                   verbose=True)
 
 if prompt:
     #response = title_chain.run(topic=prompt)
-	response = sequential_chain.run(prompt)
-	st.write(response)
+	response = sequential_chain({'topic':prompt})
+	st.write(response['title'])
+	st.write(response['script'])
+
+	with st.expander('Message History:'):
+		st.info(memory.buffer)