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import streamlit as st
from langchain.llms import OpenAI
from langchain.prompts import PromptTemplate
from langchain import FewShotPromptTemplate
from langchain.prompts.example_selector import LengthBasedExampleSelector
from dotenv import load_dotenv
load_dotenv() # load the env-sample.txt file
def getLLMResponse(query, age_option,tasktype_option):
examples = []
llm = OpenAI(temperature=.9, model="gpt-3.5-turbo-instruct")
# if age_option=="Kid": #Silly and Sweet Kid
#
# examples = [
# {
# "query": "What is a mobile?",
# "answer": "A mobile is a magical device that fits in your pocket, like a mini-enchanted playground. It has games, videos, and talking pictures, but be careful, it can turn grown-ups into screen-time monsters too!"
# }
# ]
#
# elif age_option=="Adult": #Curious and Intelligent adult
# examples = [
# {
# "query": "What is a mobile?",
# "answer": "A mobile is a portable communication device, commonly known as a mobile phone or cell phone. It allows users to make calls, send messages, access the internet, and use various applications. Additionally, 'mobile' can also refer to a type of kinetic sculpture that hangs and moves in the air, often found in art installations or as decorative pieces."
# }
# ]
#
# elif age_option=="Senior Citizen": #A 90 years old guys
# examples = [
# {
# "query": "What is a mobile?",
# "answer": "A mobile, also known as a cellphone or smartphone, is a portable device that allows you to make calls, send messages, take pictures, browse the internet, and do many other things. In the last 50 years, I have seen mobiles become smaller, more powerful, and capable of amazing things like video calls and accessing information instantly."
# }
# ]
example_template = """
Question: {query}
Response: {answer}
"""
example_prompt = PromptTemplate(
input_variables=["query", "answer"],
template=example_template
)
prefix = """You are a {template_ageoption}, and you are going to {template_tasktype_option} ,
you give one answer for each query. it is strictly limited to 1 answer only, and the answer MUST be LESS THAN 200 words.
For a tweet, you SHOULD NOT give more than 150 words. If it is not to write for a tweet, DO NOT give a tweet suggestion in your answer.
"""
suffix = """
Question: {template_userInput}
Response: """
example_selector = LengthBasedExampleSelector(
examples=examples,
example_prompt=example_prompt,
max_length = numberOfWords
)
new_prompt_template = FewShotPromptTemplate(
example_selector=example_selector, # use example_selector instead of examples
example_prompt=example_prompt,
prefix=prefix,
suffix=suffix,
input_variables=["template_userInput","template_ageoption","template_tasktype_option"],
example_separator="\n"
)
print(new_prompt_template.format(template_userInput=query,template_ageoption=age_option,template_tasktype_option=tasktype_option))
response=llm(new_prompt_template.format(template_userInput=query,template_ageoption=age_option,template_tasktype_option=tasktype_option))
print(response)
return response
#UI Starts here
st.set_page_config(page_title="Marketing Tool",
page_icon='✅',
layout='centered',
initial_sidebar_state='collapsed')
st.header("Hey, How can I help you?")
form_input = st.text_area('Enter text', height=100)
tasktype_option = st.selectbox(
'Please select the action to be performed',
('Write a sales copy', 'Create a tweet', 'Write a product description'),key=1)
age_option= st.selectbox(
'For which target age group?',
('Kid' ,'Adult', 'senior Citizen'),key=2)
# numberOfWords= st.slider('Words limit', 1, 200, 25)
numberOfWords = 40 # the model doesn't take this.
submit = st.button("Generate")
if submit:
st.write(getLLMResponse(form_input,tasktype_option,age_option))
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