import streamlit as st
from langchain_groq import ChatGroq
from langchain.chains import LLMChain
from langchain.prompts import PromptTemplate

# Streamlit Application Title
st.title('AI Scientist')
st.subheader('Here you will find solutions for your problem')

# Input Fields
A = st.text_input('Enter Academic year')
B = st.text_input('Enter Streams of education')

details = f"""
Academic year: {A}
Stream: {B}
"""

# Question Input and Submit Button
A1 = st.text_input('Enter your question')
SUB = st.button('SUBMIT')

# Define the Prompt Template for Questions
B2 = PromptTemplate(
    input_variables=["details", "k"],
    template="Tell me about {k} based on the following details: {details} in 20 words."
)

# Initialize the ChatGroq Model
model = ChatGroq(
    temperature=0.6,
    groq_api_key='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'  # Replace with your actual API key
)

# Process the Question on Button Click
if SUB and A1:  # Ensure question input is provided
    X = B2.format(k=A1, details=details)
    response = model.predict(X)  # Use predict method to interact with the model
    st.write(response)