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test1..py
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test1..py
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## Integrate our code OpenAI API
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('Celebrity Search Results')
input_text=st.text_input("Search the topic u want")
# Prompt Templates
first_input_prompt=PromptTemplate(
input_variables=['name'],
template="Tell me about celebrity {name}"
)
# Memory
person_memory = ConversationBufferMemory(input_key='name',
memory_key='chat_history')
dob_memory = ConversationBufferMemory(input_key='person',
memory_key='chat_history')
descr_memory = ConversationBufferMemory(input_key='dob',
memory_key='description_history')
## OPENAI LLMS
llm=OpenAI(temperature=0.8)
chain=LLMChain(
llm=llm,
prompt=first_input_prompt,
verbose=True,
output_key='person',
memory=person_memory)
# Prompt Templates
second_input_prompt=PromptTemplate(
input_variables=['person'],
template="when was {person} born"
)
chain2=LLMChain(
llm=llm,
prompt=second_input_prompt,
verbose=True,
output_key='dob',
memory=dob_memory)
# Prompt Templates
third_input_prompt=PromptTemplate(
input_variables=['dob'],
template="Mention 5 major events happened around {dob} in the world"
)
chain3=LLMChain(llm=llm,prompt=third_input_prompt,verbose=True,output_key='description',memory=descr_memory)
parent_chain=SequentialChain(
chains=[chain,chain2,chain3],
input_variables=['name'],
output_variables=['person',
'dob',
'description'],
verbose=True)
if input_text:
st.write(parent_chain({'name':input_text}))
with st.expander('Person Name'):
st.info(person_memory.buffer)
with st.expander('Major Events'):
st.info(descr_memory.buffer)