Create app.py

app.py

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+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)