app.py

import streamlit as st
from openai import OpenAI
import time
import os
import logging
from groq import Groq

# Logging setup
logging.basicConfig(level=logging.INFO)

# Streamlit page configuration
st.set_page_config(
    page_title="Groq AI Reasoning Chatbot",
    page_icon="🤖",
    layout="centered"
)

# Custom CSS for better visuals
st.markdown("""
<style>
    .stApp {
        background-color: #F5F5F5;
    }
    .chat-container {
        background-color: #FFFFFF;
        margin: 1rem 0;
        padding: 1rem;
        border-radius: 10px;
        box-shadow: 0px 4px 6px rgba(0, 0, 0, 0.1);
    }
    .user-message {
        text-align: right;
        background-color: #007AFF;
        color: white;
        padding: 0.5rem 1rem;
        border-radius: 15px;
        margin: 0.5rem 0;
        display: inline-block;
        max-width: 70%;
    }
    .bot-message {
        text-align: left;
        background-color: #E9ECEF;
        padding: 0.5rem 1rem;
        border-radius: 15px;
        margin: 0.5rem 0;
        display: inline-block;
        max-width: 70%;
    }
</style>
""", unsafe_allow_html=True)

# Groq API client initialization
@st.cache_resource
def init_groq_client():
    return Groq(api_key=os.getenv("GROQ_API_KEY"))

# Chat with Groq model
def chat_with_groq(client, message, history):
    try:
        # Build the conversation context
        messages = [
            {"role": "system", "content": "You are a helpful assistant. Think step by step before answering."},
            *[{"role": "user" if i % 2 == 0 else "assistant", "content": m} for h in history for i, m in enumerate(h)],
            {"role": "user", "content": message}
        ]

        # Call the Groq model
        completion = client.chat.completions.create(
            model="deepseek-r1-distill-llama-70b",
            messages=messages,
            temperature=0.6,
            max_tokens=1024,
            top_p=0.95,
            stream=True,  # Stream the response
        )

        # Stream the response chunk by chunk
        response = ""
        for chunk in completion:
            content = chunk.choices[0].delta.content or ""
            response += content
            yield response

    except Exception as e:
        logging.error(f"Error during Groq inference: {str(e)}")
        yield f"An error occurred: {str(e)}. Please check your API key and network connection."

# Initialize app state
if "history" not in st.session_state:
    st.session_state["history"] = []  # [(user_message, bot_response), ...]

# Display the app title and description
st.title("Groq AI Reasoning Chatbot 🤖")
st.write("Ask the chatbot anything and it will provide step-by-step reasoning.")

# Input form
with st.form("chat_form", clear_on_submit=True):
    user_message = st.text_input("Your Message:", key="user_input")
    submitted = st.form_submit_button("Send")

# Process user input and display chat
if submitted and user_message:
    # Add user message to history
    st.session_state["history"].append((user_message, None))

    # Display chat history
    for user_text, bot_text in st.session_state["history"]:
        st.markdown(f'<div class="user-message">{user_text}</div>', unsafe_allow_html=True)
        if bot_text:
            st.markdown(f'<div class="bot-message">{bot_text}</div>', unsafe_allow_html=True)

    # Initialize Groq client
    groq_client = init_groq_client()

    # Generate bot response
    response_placeholder = st.empty()  # Placeholder for streaming updates
    bot_response = ""
    for partial_response in chat_with_groq(groq_client, user_message, st.session_state["history"][:-1]):
        bot_response = partial_response  # Update bot response incrementally
        response_placeholder.markdown(f'<div class="bot-message">{bot_response}</div>', unsafe_allow_html=True)

    # Update history with full bot response
    st.session_state["history"][-1] = (user_message, bot_response)

# Clear chat history button
if st.button("Clear Chat"):
    st.session_state["history"] = []
    st.experimental_rerun()

# Footer
st.markdown("---")
st.markdown("Made with ❤️ using Groq AI")