app.py

import os
import streamlit as st
from groq import Groq

# Set up the Groq API Key
GROQ_API_KEY = "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"
os.environ["GROQ_API_KEY"] = GROQ_API_KEY

# Initialize the Groq client
client = Groq(api_key=GROQ_API_KEY)

# Streamlit user interface setup
st.title("Subject-specific AI Chatbot")
st.write("Hello! I'm your AI Study Assistant. You can ask me any questions related to your subjects, and I'll try to help.")

# Initialize session state for maintaining conversation
if 'conversation_history' not in st.session_state:
    st.session_state.conversation_history = []

# Define a list of subjects for which the chatbot will answer
subjects = ["Chemistry", "Computer", "English", "Islamiat", "Mathematics", "Physics", "Urdu"]

# Function to generate chatbot response based on subject-specific user input
def generate_chatbot_response(user_message):
    # Check if the user's question is related to any subject
    related_subject = None
    for subject in subjects:
        if subject.lower() in user_message.lower():
            related_subject = subject
            break
    
    # Custom response for "who created you" type of questions
    if "kisne banaya" in user_message.lower() or "who created you" in user_message.lower():
        return "Mujhe Abdel Basit ne banaya hai. 😊"

    if related_subject:
        prompt = f"You are a helpful AI chatbot for studying {related_subject}. The user is asking: {user_message}. Provide a detailed, helpful response related to {related_subject}."
    else:
        prompt = f"You are a helpful AI chatbot. The user is asking: {user_message}. If the question is not related to any of the specified subjects (Chemistry, Computer, English, Islamiat, Mathematics, Physics, Urdu), politely let them know."

    # Generate response using Groq API
    chat_completion = client.chat.completions.create(
        messages=[{"role": "user", "content": prompt}],
        model="llama3-8b-8192",  # You can replace with the appropriate model name
    )

    response = chat_completion.choices[0].message.content
    return response

# User input for conversation (now placed at the bottom)
user_input = st.chat_input("Ask me a subject-related question:")

# Handle user input and display conversation
if user_input:
    chatbot_response = generate_chatbot_response(user_input)

    # Save the conversation history
    st.session_state.conversation_history.append(("User: " + user_input, "Chatbot: " + chatbot_response))

# Display chat history
for question, answer in st.session_state.conversation_history:
    st.write(f"**{question}**")
    st.write(answer)