from langchain.chains import LLMChain
from langchain_community.llms import OpenAI
from langchain_core.prompts import PromptTemplate
import streamlit as st

mini_template = "You are an expert researcher. You\'ve talked to hundreds of {Target Audience}. \
Each person in the niche of {Target Audience} has certain struggles that make it easier to sell {My Course}. \
These are called Pain Points. There's a recipe for getting to the core of the Pain Points of {Target Audience}. \
Namely, answer each of these Questions 3 times, each getting deeper in the issues of {Target Audience}, \
appealing to their Emotions and uncertainties related to {My Course}. \
The Questions (answer each QUESTION 3 tiems in listicle format according to the instructions):\
1. What keeps them awake at night?\
2. What are they afraid of?\
3. What are they angry about?\
"


st.title("Saas Application")

prompt = PromptTemplate(
    input_variables = ["Target Audience", "My Course"],
    template=mini_template,
)

chain = LLMChain(llm=OpenAI(), prompt=prompt)

#target_audience = "professionals looking for course on Power BI"
#my_course = "Zero to Hero in PowerBI"

target_audience = st.text_input("Enter your target audience")
my_course = st.text_input("Enter your course name")

if st.button("Get resposne"):
    if target_audience and my_course:
        with st.spinner("Generating response..."):
            with st.expander("Show prompt", expanded=False):
                    st.info(prompt.template)
            answer = chain.run({"Target Audience": target_audience, "My Course":my_course})
    
        st.write(answer)
        st.success("Hope you like the resposne.❤")
    elif target_audience:
        st.error("Enter your course name.")
    elif my_course:
        st.error("Enter your target audience.")

    else:
        st.error("No input detected, Please provide the desired information.")