app.py

import os
import re
import requests
import torch
import streamlit as st
from langchain_huggingface import HuggingFaceEndpoint
from langchain_core.prompts import PromptTemplate
from langchain_core.output_parsers import StrOutputParser
from transformers import pipeline
from langdetect import detect  # Ensure this package is installed

# ✅ Check for GPU or Default to CPU
device = "cuda" if torch.cuda.is_available() else "cpu"
print(f"✅ Using device: {device}")  # Debugging info

# ✅ Environment Variables
HF_TOKEN = os.getenv("HF_TOKEN")
if HF_TOKEN is None:
    raise ValueError("HF_TOKEN is not set. Please add it to your environment variables.")

NASA_API_KEY = os.getenv("NASA_API_KEY")
if NASA_API_KEY is None:
    raise ValueError("NASA_API_KEY is not set. Please add it to your environment variables.")

# ✅ Set Up Streamlit
st.set_page_config(page_title="HAL - NASA ChatBot", page_icon="🚀")

# ✅ Initialize Session State Variables (Ensuring Chat History Persists)
if "chat_history" not in st.session_state:
    st.session_state.chat_history = [{"role": "assistant", "content": "Hello! I'm HAL, your NASA AI Assistant. You can speak to me directly or type your questions. How can I help you today?"}]
if "auto_speak" not in st.session_state:
    st.session_state.auto_speak = True

# ✅ Initialize Hugging Face Model (Explicitly Set to CPU/GPU)
def get_llm_hf_inference(model_id="meta-llama/Llama-2-7b-chat-hf", max_new_tokens=800, temperature=0.3):
    return HuggingFaceEndpoint(
        repo_id=model_id,
        max_new_tokens=max_new_tokens,
        temperature=temperature,  # 🔥 Lowered temperature for more factual and structured responses
        token=HF_TOKEN,
        task="text-generation",
        device=-1 if device == "cpu" else 0  # ✅ Force CPU (-1) or GPU (0)
    )

# ✅ Ensure English Responses
def ensure_english(text):
    try:
        detected_lang = detect(text)
        if detected_lang != "en":
            return "⚠️ Sorry, I only respond in English. Can you rephrase your question?"
    except:
        return "⚠️ Language detection failed. Please ask your question again."
    return text

# ✅ Main Response Function (Fixing Repetition & Context)
def get_response(system_message, chat_history, user_text, max_new_tokens=800):
    # ✅ Ensure conversation history is included correctly
    filtered_history = "\n".join(
        f"{msg['role'].capitalize()}: {msg['content']}"
        for msg in chat_history[-5:]  # ✅ Only keep the last 5 exchanges to prevent overflow
    )
 
    prompt = PromptTemplate.from_template(
        "[INST] You are a highly knowledgeable AI assistant. Answer concisely, avoid repetition, and structure responses well."
        "\n\nCONTEXT:\n{chat_history}\n"
        "\nLATEST USER INPUT:\nUser: {user_text}\n"
        "\n[END CONTEXT]\n"
        "Assistant:"
    )

    # ✅ Invoke Hugging Face Model
    hf = get_llm_hf_inference(max_new_tokens=max_new_tokens, temperature=0.3)  # 🔥 Lowered temperature
    chat = prompt | hf.bind(skip_prompt=True) | StrOutputParser(output_key='content')

    response = chat.invoke(input=dict(system_message=system_message, user_text=user_text, chat_history=filtered_history))
    
    # Clean up the response - remove any "HAL:" prefix if present
    response = response.split("HAL:")[-1].strip() if "HAL:" in response else response.strip()
    response = ensure_english(response)

    if not response:
        response = "I'm sorry, but I couldn't generate a response. Can you rephrase your question?"

    # ✅ Update conversation history
    chat_history.append({'role': 'user', 'content': user_text})
    chat_history.append({'role': 'assistant', 'content': response})

    # ✅ Keep only last 10 exchanges to prevent unnecessary repetition
    return response, chat_history[-10:]

# ✅ NASA API Function to get space data
def get_nasa_data(query):
    try:
        if "apod" in query.lower() or "picture of the day" in query.lower():
            response = requests.get(f"https://api.nasa.gov/planetary/apod?api_key={NASA_API_KEY}")
            if response.status_code == 200:
                data = response.json()
                return {
                    "title": data.get("title", "NASA Image"),
                    "date": data.get("date", ""),
                    "explanation": data.get("explanation", ""),
                    "url": data.get("url", "")
                }
        return None
    except Exception as e:
        print(f"Error fetching NASA data: {e}")
        return None

# ✅ Streamlit UI
st.title("🚀 HAL - NASA AI Assistant")

# ✅ Add styles and speech recognition JavaScript
st.markdown("""
    <style>
    .user-msg, .assistant-msg {
        padding: 11px;
        border-radius: 10px;
        margin-bottom: 5px;
        width: fit-content;
        max-width: 80%;
        text-align: justify;
    }
    .user-msg { background-color: #696969; color: white; }
    .assistant-msg { background-color: #333333; color: white; }
    .container { display: flex; flex-direction: column; align-items: flex-start; }
    .speak-button {
        background-color: #2196F3;
        border: none;
        color: white;
        padding: 5px 10px;
        text-align: center;
        text-decoration: none;
        display: inline-block;
        font-size: 12px;
        margin: 2px 2px;
        cursor: pointer;
        border-radius: 12px;
    }
    .voice-indicator {
        display: inline-block;
        width: 12px;
        height: 12px;
        border-radius: 50%;
        margin-left: 8px;
        vertical-align: middle;
        background-color: #ccc;
    }
    .voice-indicator.active {
        background-color: #4CAF50;
        animation: pulse 1.5s infinite;
    }
    .status-bar {
        padding: 6px 12px;
        border-radius: 5px;
        background-color: #f1f1f1;
        display: flex;
        align-items: center;
        margin-bottom: 10px;
        font-size: 14px;
    }
    @keyframes pulse {
        0% { opacity: 1; }
        50% { opacity: 0.5; }
        100% { opacity: 1; }
    }
    @media (max-width: 600px) { .user-msg, .assistant-msg { font-size: 16px; max-width: 100%; } }
    </style>
    
    <script>
    // Speech Recognition Setup with continuous mode
    let recognition;
    let isListening = false;
    let silenceTimer;
    let lastSpeechTime = Date.now();
    let lastTranscript = '';
    const SILENCE_THRESHOLD = 3000; // Submit after 3 seconds of silence
    
    function setupSpeechRecognition() {
        try {
            window.SpeechRecognition = window.SpeechRecognition || window.webkitSpeechRecognition;
            recognition = new SpeechRecognition();
            recognition.lang = 'en-US';
            recognition.interimResults = true;
            recognition.continuous = true;
            
            recognition.onstart = function() {
                isListening = true;
                document.getElementById('voice-indicator').classList.add('active');
                document.getElementById('voice-status').textContent = 'Listening...';
            };
            
            recognition.onresult = function(event) {
                lastSpeechTime = Date.now();
                clearTimeout(silenceTimer);
                
                // Get the latest transcript
                let interimTranscript = '';
                let finalTranscript = '';
                
                for (let i = event.resultIndex; i < event.results.length; i++) {
                    const transcript = event.results[i][0].transcript;
                    if (event.results[i].isFinal) {
                        finalTranscript += transcript + ' ';
                    } else {
                        interimTranscript += transcript;
                    }
                }
                
                // Update the hidden input with the latest transcript
                const speechResult = (finalTranscript || interimTranscript).trim();
                if (speechResult && speechResult !== lastTranscript) {
                    document.getElementById('speech-result').value = speechResult;
                    document.getElementById('voice-status').textContent = 'I heard: ' + speechResult;
                    lastTranscript = speechResult;
                    
                    // Set a timer to submit after silence
                    silenceTimer = setTimeout(() => {
                        if (speechResult) {
                            document.getElementById('submit-speech').click();
                            lastTranscript = '';
                            document.getElementById('speech-result').value = '';
                        }
                    }, SILENCE_THRESHOLD);
                }
            };
            
            recognition.onerror = function(event) {
                console.error('Speech recognition error:', event.error);
                if (event.error === 'no-speech') {
                    // Just restart listening if there was no speech detected
                    restartRecognition();
                } else {
                    isListening = false;
                    document.getElementById('voice-indicator').classList.remove('active');
                    document.getElementById('voice-status').textContent = 'Voice recognition paused. Click to restart.';
                }
            };
            
            recognition.onend = function() {
                // Auto restart if it ends unintentionally
                if (isListening) {
                    restartRecognition();
                } else {
                    document.getElementById('voice-indicator').classList.remove('active');
                    document.getElementById('voice-status').textContent = 'Voice recognition disabled.';
                }
            };
            
            return true;
        } catch (error) {
            console.error('Speech recognition not supported:', error);
            document.getElementById('voice-status').textContent = 'Voice recognition not supported in this browser.';
            return false;
        }
    }
    
    function toggleVoiceRecognition() {
        if (!recognition) {
            if (!setupSpeechRecognition()) {
                return;
            }
        }
        
        if (isListening) {
            recognition.stop();
            isListening = false;
            document.getElementById('voice-indicator').classList.remove('active');
            document.getElementById('voice-status').textContent = 'Voice recognition paused. Click to restart.';
        } else {
            startRecognition();
        }
    }
    
    function startRecognition() {
        try {
            recognition.start();
            document.getElementById('voice-status').textContent = 'Listening...';
        } catch (e) {
            console.error('Error starting recognition:', e);
            setTimeout(startRecognition, 200);
        }
    }
    
    function restartRecognition() {
        try {
            recognition.stop();
        } catch (e) {}
        
        setTimeout(startRecognition, 200);
    }
    
    // Text-to-Speech functionality
    function speakText(text) {
        const utterance = new SpeechSynthesisUtterance(text);
        utterance.lang = 'en-US';
        utterance.pitch = 1;
        utterance.rate = 1;
        window.speechSynthesis.speak(utterance);
    }
    
    // Auto speak the latest response
    function autoSpeakLatest() {
        const messages = document.querySelectorAll('.assistant-msg');
        if (messages.length > 0) {
            const latestMessage = messages[messages.length - 1];
            const messageId = latestMessage.querySelector('span[id^="msg-"]').id;
            speakText(document.getElementById(messageId).textContent);
        }
    }
    
    // Initialize after the page loads
    document.addEventListener('DOMContentLoaded', function() {
        setupSpeechRecognition();
        // Start listening automatically
        setTimeout(startRecognition, 1000);
    });
    
    // Handle speech input submission
    document.getElementById('submit-speech').addEventListener('click', function() {
        const speechResult = document.getElementById('speech-result').value;
        if (speechResult) {
            // Update the Streamlit text input with the speech result
            const textInputs = document.querySelectorAll('input[type="text"]');
            if (textInputs.length > 0) {
                const lastInput = textInputs[0];
                lastInput.value = speechResult;
                lastInput.dispatchEvent(new Event('input', { bubbles: true }));
                
                // Find and click the submit button
                setTimeout(() => {
                    const buttons = document.querySelectorAll('button[kind="primaryForm"]');
                    for (const button of buttons) {
                        if (button.textContent.includes('Submit')) {
                            button.click();
                            break;
                        }
                    }
                }, 100);
            }
        }
    });
    
    // Auto-speak for newest message if enabled
    function checkForNewMessages() {
        const autoSpeakEnabled = document.querySelector('input[type="checkbox"][aria-label="Auto-speak responses"]').checked;
        if (autoSpeakEnabled) {
            const messages = document.querySelectorAll('.assistant-msg');
            if (messages.length > 0) {
                const latestMessage = messages[messages.length - 1];
                const messageId = latestMessage.querySelector('span[id^="msg-"]').id;
                
                // Only speak if this is a new message
                if (!latestMessage.hasAttribute('data-spoken')) {
                    speakText(document.getElementById(messageId).textContent);
                    latestMessage.setAttribute('data-spoken', 'true');
                }
            }
        }
    }
    
    // Check for new messages every second
    setInterval(checkForNewMessages, 1000);
    </script>
""", unsafe_allow_html=True)

# Add voice status indicator
st.markdown("""
    <div class="status-bar">
        <span id="voice-status">Initializing voice recognition...</span>
        <span id="voice-indicator" class="voice-indicator" onclick="toggleVoiceRecognition()"></span>
    </div>
""", unsafe_allow_html=True)

# Regular text input
user_input = st.chat_input("Type your message here or just speak...")

# Hidden input for speech results
speech_result = st.text_input("Speech Result", key="speech_input", label_visibility="collapsed")

# Hidden button to submit speech
st.markdown('<button id="submit-speech" style="display:none;">Submit Speech</button>', unsafe_allow_html=True)

# Auto-speak toggle
st.checkbox("Auto-speak responses", value=st.session_state.auto_speak, key="auto_speak_toggle", 
            on_change=lambda: setattr(st.session_state, "auto_speak", st.session_state.auto_speak_toggle))

# Display chat history
for i, msg in enumerate(st.session_state.chat_history):
    if msg["role"] == "user":
        st.markdown(f'<div class="container"><div class="user-msg">You: {msg["content"]}</div></div>', unsafe_allow_html=True)
    else:
        msg_id = f"msg-{i}"
        st.markdown(f'<div class="container"><div class="assistant-msg">HAL: <span id="{msg_id}">{msg["content"]}</span> <button class="speak-button" onclick="speakText(document.getElementById(\'{msg_id}\').textContent)">🔊</button></div></div>', unsafe_allow_html=True)

# Process user input
if user_input or speech_result:
    # Prioritize speech result if available
    query = speech_result if speech_result else user_input
    
    # Get NASA data if applicable
    nasa_data = get_nasa_data(query)
    
    # Generate response
    system_message = "You are HAL, an AI assistant specialized in NASA and space knowledge. Provide concise, factual responses."
    response, st.session_state.chat_history = get_response(system_message, st.session_state.chat_history, query)
    
    # Display NASA image if available
    if nasa_data:
        st.image(nasa_data["url"], caption=f"{nasa_data['title']} - {nasa_data['date']}")
        st.write(nasa_data["explanation"])
    
    # Force a rerun to update the chat display
    st.rerun()

# Add JavaScript to ensure the page scrolls to the bottom on new messages
st.markdown("""
<script>
    // Scroll to bottom of page on load
    window.onload = function() {
        window.scrollTo(0, document.body.scrollHeight);
    }
</script>
""", unsafe_allow_html=True)