app.py

import os
import uuid
import time
import threading
import io
from datetime import datetime, timedelta
from collections import defaultdict, deque

from flask import Flask, request, jsonify, render_template
from detoxify import Detoxify
import numpy as np
import requests
from PIL import Image
from tensorflow.keras.models import load_model

app = Flask(__name__, static_folder='static', template_folder='templates')
app.logger.setLevel('INFO')

API_KEY = os.environ.get('API_KEY')
if not API_KEY:
    raise ValueError("API_KEY environment variable not set.")

print("Loading Detoxify model for text moderation...")
detoxify_model = Detoxify('multilingual')
print("Detoxify model loaded successfully.")

MODEL_PATH = 'keras_model.h5'
LABELS_PATH = 'labels.txt'
image_model = None
image_labels = None

try:
    print("Loading Teachable Machine model for image moderation...")
    image_model = load_model(MODEL_PATH, compile=False)
    with open(LABELS_PATH, 'r') as f:
        image_labels = [line.strip().split(' ')[1] for line in f.readlines()]
    print("Image moderation model loaded successfully.")
except Exception as e:
    app.logger.warning(f"Could not load image moderation model. Image moderation will be disabled. Error: {e}")
    image_model = None
    image_labels = None

request_durations = deque(maxlen=100)
request_timestamps = deque(maxlen=1000)
daily_requests = defaultdict(int)
concurrent_requests = 0
concurrent_requests_lock = threading.Lock()

def is_url(string):
    return isinstance(string, str) and string.strip().startswith(('http://', 'https://'))

def classify_image(image_bytes):
    if not image_model or not image_labels:
        raise RuntimeError("Image moderation model is not available.")
    
    image = Image.open(io.BytesIO(image_bytes)).convert('RGB')
    image = image.resize((224, 224))
    
    image_array = np.asarray(image)
    normalized_image_array = (image_array.astype(np.float32) / 127.5) - 1
    
    data = np.ndarray(shape=(1, 224, 224, 3), dtype=np.float32)
    data[0] = normalized_image_array
    
    prediction = image_model.predict(data)
    
    scores = {label.lower(): float(score) for label, score in zip(image_labels, prediction[0])}
    return scores

def transform_text_predictions(prediction_dict):
    category_keys = [
        "toxicity", "severe_toxicity", "obscene", "threat",
        "insult", "identity_attack", "sexual_explicit"
    ]
    scores = {key: float(prediction_dict.get(key, 0.0)) for key in category_keys}
    
    threshold = 0.5
    categories = {key: (scores[key] > threshold) for key in category_keys}
    flagged = any(categories.values())
    
    return flagged, categories, scores

def transform_image_predictions(prediction_dict):
    nsfw_score = prediction_dict.get('nsfw', 0.0)
    
    categories = {
        "sexual": nsfw_score > 0.8,
        "hate": False,
        "harassment": False,
        "self-harm": False,
        "sexual/minors": nsfw_score > 0.9,
        "hate/threatening": False,
        "violence/graphic": False,
        "self-harm/intent": False,
        "self-harm/instructions": False,
        "harassment/threatening": False,
        "violence": False,
    }
    
    category_scores = {
        "sexual": nsfw_score,
        "hate": 0.0,
        "harassment": 0.0,
        "self-harm": 0.0,
        "sexual/minors": nsfw_score,
        "hate/threatening": 0.0,
        "violence/graphic": 0.0,
        "self-harm/intent": 0.0,
        "self-harm/instructions": 0.0,
        "harassment/threatening": 0.0,
        "violence": 0.0,
    }
    
    flagged = any(categories.values())
    
    return flagged, categories, category_scores
    
def track_request_metrics(start_time):
    duration = time.time() - start_time
    request_durations.append(duration)
    request_timestamps.append(datetime.now())
    today = datetime.now().strftime("%Y-%m-%d")
    daily_requests[today] += 1

def get_performance_metrics():
    with concurrent_requests_lock:
        current_concurrent = concurrent_requests
    
    avg_request_time = sum(request_durations) / len(request_durations) if request_durations else 0
    peak_request_time = max(request_durations) if request_durations else 0
    
    now = datetime.now()
    one_minute_ago = now - timedelta(seconds=60)
    requests_last_minute = sum(1 for ts in request_timestamps if ts > one_minute_ago)
    today_requests = daily_requests.get(now.strftime("%Y-%m-%d"), 0)

    last_7_days = []
    for i in range(7):
        date = (now - timedelta(days=i)).strftime("%Y-%m-%d")
        last_7_days.append({
            "date": date,
            "requests": daily_requests.get(date, 0),
        })

    return {
        "avg_request_time_ms": avg_request_time * 1000,
        "peak_request_time_ms": peak_request_time * 1000,
        "requests_per_minute": requests_last_minute,
        "concurrent_requests": current_concurrent,
        "today_requests": today_requests,
        "last_7_days": last_7_days
    }

@app.route('/')
def home():
    return render_template('index.html')

@app.route('/v1/moderations', methods=['POST'])
def moderations():
    global concurrent_requests
    
    auth_header = request.headers.get('Authorization')
    if not auth_header or not auth_header.startswith("Bearer ") or auth_header.split(" ")[1] != API_KEY:
        return jsonify({"error": {"message": "Incorrect API key provided.", "type": "invalid_request_error", "code": "invalid_api_key"}}), 401

    with concurrent_requests_lock:
        concurrent_requests += 1
    
    start_time = time.time()
    
    try:
        data = request.get_json()
        if not data:
            return jsonify({"error": "Invalid JSON body"}), 400
            
        raw_input = data.get('input')
        if raw_input is None:
            return jsonify({"error": "'input' field is required"}), 400

        inputs = [raw_input] if isinstance(raw_input, str) else raw_input
        if not isinstance(inputs, list):
            return jsonify({"error": "'input' must be a string or a list of strings/URLs"}), 400

        results = []
        texts_to_process = []
        text_indices = []

        for i, item in enumerate(inputs):
            if is_url(item):
                try:
                    response = requests.get(item, timeout=10)
                    response.raise_for_status()
                    image_scores = classify_image(response.content)
                    flagged, categories, category_scores = transform_image_predictions(image_scores)
                    results.append((i, {"flagged": flagged, "categories": categories, "category_scores": category_scores}))
                except requests.RequestException as e:
                     results.append((i, {"error": f"Failed to download image: {e}"}))
                except Exception as e:
                     results.append((i, {"error": f"Failed to process image: {e}"}))
            elif isinstance(item, str):
                texts_to_process.append(item)
                text_indices.append(i)
            else:
                results.append((i, {"error": "Invalid input type. Must be a string or URL."}))

        if texts_to_process:
            text_predictions = detoxify_model.predict(texts_to_process)
            for i, original_index in enumerate(text_indices):
                single_prediction = {key: value[i] for key, value in text_predictions.items()}
                flagged, categories, category_scores = transform_text_predictions(single_prediction)
                results.append((original_index, {"flagged": flagged, "categories": categories, "category_scores": category_scores}))
        
        results.sort(key=lambda x: x[0])
        final_results = [res for _, res in results]

        response_data = {
            "id": "modr-" + uuid.uuid4().hex[:24],
            "model": "smart-moderator-multimodal-v1",
            "results": final_results
        }
        
        return jsonify(response_data)

    except Exception as e:
        app.logger.error(f"An error occurred: {e}", exc_info=True)
        return jsonify({"error": "An internal server error occurred."}), 500
    finally:
        track_request_metrics(start_time)
        with concurrent_requests_lock:
            concurrent_requests -= 1

@app.route('/v1/metrics', methods=['GET'])
def metrics():
    auth_header = request.headers.get('Authorization')
    if not auth_header or not auth_header.startswith("Bearer ") or auth_header.split(" ")[1] != API_KEY:
        return jsonify({"error": "Unauthorized"}), 401
    
    return jsonify(get_performance_metrics())

def create_app_structure():
    os.makedirs('templates', exist_ok=True)
    os.makedirs('static', exist_ok=True)
    
    index_html_content = r'''
<!DOCTYPE html>
<html lang="en">
<head>
    <meta charset="UTF-8">
    <meta name="viewport" content="width=device-width, initial-scale=1.0">
    <title>Smart Moderator API</title>
    <script src="https://cdn.tailwindcss.com"></script>
    <script src="https://cdn.jsdelivr.net/npm/chart.js"></script>
    <link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/6.4.0/css/all.min.css">
    <script>
        tailwind.config = { darkMode: 'class' }
    </script>
    <style>
        .gradient-bg { background: linear-gradient(135deg, #667eea 0%, #764ba2 100%); }
        .dark .gradient-bg { background: linear-gradient(135deg, #1e3a8a 0%, #4c1d95 100%); }
        .loading-spinner { border-top-color: #3b82f6; animation: spinner 1.5s linear infinite; }
        @keyframes spinner { 0% { transform: rotate(0deg); } 100% { transform: rotate(360deg); } }
    </style>
</head>
<body class="bg-gray-50 dark:bg-gray-900 text-gray-900 dark:text-gray-100 min-h-screen font-sans">
    <header class="gradient-bg text-white shadow-lg">
        <div class="container mx-auto px-4 py-6 flex justify-between items-center">
            <div class="flex items-center space-x-3">
                <div class="w-10 h-10 rounded-full bg-white flex items-center justify-center">
                    <i class="fas fa-shield-alt text-indigo-600 text-xl"></i>
                </div>
                <h1 class="text-2xl font-bold">Smart Moderator</h1>
            </div>
            <div>
                <button id="darkModeToggle" class="bg-white/20 p-2 rounded-lg hover:bg-white/30 transition">
                    <i class="fas fa-moon dark:hidden"></i>
                    <i class="fas fa-sun hidden dark:inline"></i>
                </button>
            </div>
        </div>
    </header>

    <main class="container mx-auto px-4 py-8">
        <section class="mb-12">
            <h2 class="text-2xl font-bold mb-6 flex items-center"><i class="fas fa-tachometer-alt mr-3 text-indigo-500"></i>Performance Metrics</h2>
            <div class="grid grid-cols-1 md:grid-cols-2 lg:grid-cols-4 gap-6 mb-8">
                <div class="bg-white dark:bg-gray-800 rounded-xl shadow-lg p-6"><p class="text-gray-500 dark:text-gray-400 text-sm">Avg. Response</p><p class="text-2xl font-bold" id="avgResponseTime">0ms</p></div>
                <div class="bg-white dark:bg-gray-800 rounded-xl shadow-lg p-6"><p class="text-gray-500 dark:text-gray-400 text-sm">Requests / Minute</p><p class="text-2xl font-bold" id="requestsPerMinute">0</p></div>
                <div class="bg-white dark:bg-gray-800 rounded-xl shadow-lg p-6"><p class="text-gray-500 dark:text-gray-400 text-sm">Peak Response</p><p class="text-2xl font-bold" id="peakResponseTime">0ms</p></div>
                <div class="bg-white dark:bg-gray-800 rounded-xl shadow-lg p-6"><p class="text-gray-500 dark:text-gray-400 text-sm">Today's Requests</p><p class="text-2xl font-bold" id="todayRequests">0</p></div>
            </div>
            <div class="bg-white dark:bg-gray-800 rounded-xl shadow-lg p-6">
                <h3 class="text-lg font-semibold mb-4">Last 7 Days Activity</h3>
                <div class="h-64"><canvas id="activityChart"></canvas></div>
            </div>
        </section>

        <section class="mb-12">
            <h2 class="text-2xl font-bold mb-6 flex items-center"><i class="fas fa-vial mr-3 text-indigo-500"></i>API Tester</h2>
            <div class="bg-white dark:bg-gray-800 rounded-xl shadow-lg p-6">
                <form id="apiTestForm">
                    <div class="mb-4"><label class="block text-sm font-medium mb-2" for="apiKey">API Key</label><input type="password" id="apiKey" class="w-full px-4 py-2 rounded-lg border bg-white dark:bg-gray-700 focus:outline-none focus:ring-2 focus:ring-indigo-500" placeholder="Enter your API key"></div>
                    <div class="mb-4"><label class="block text-sm font-medium mb-2">Input (Text or Image URL)</label><textarea id="apiInput" class="w-full px-4 py-2 rounded-lg border bg-white dark:bg-gray-700 focus:outline-none focus:ring-2 focus:ring-indigo-500" rows="4" placeholder="Enter text to moderate, or a public image URL. For multiple items, separate them with a new line."></textarea></div>
                    <button type="submit" id="analyzeBtn" class="bg-indigo-600 hover:bg-indigo-700 text-white font-medium py-2 px-6 rounded-lg transition"><i class="fas fa-search mr-2"></i>Analyze</button>
                </form>
            </div>
        </section>

        <section id="resultsSection" class="hidden">
            <h2 class="text-2xl font-bold mb-6 flex items-center"><i class="fas fa-clipboard-check mr-3 text-indigo-500"></i>Analysis Results</h2>
            <div id="resultsContainer" class="bg-white dark:bg-gray-800 rounded-xl shadow-lg p-6"></div>
        </section>
        
        <section>
            <h2 class="text-2xl font-bold mb-6 flex items-center"><i class="fas fa-book-open mr-3 text-indigo-500"></i>API Documentation</h2>
            <div class="bg-white dark:bg-gray-800 rounded-xl shadow-lg p-6">
                <h3 class="text-lg font-semibold mb-2">Endpoint</h3>
                <code class="block bg-gray-100 dark:bg-gray-700 p-3 rounded-lg text-sm mb-4">POST /v1/moderations</code>
                <h3 class="text-lg font-semibold mb-2">Headers</h3>
                <code class="block bg-gray-100 dark:bg-gray-700 p-3 rounded-lg text-sm mb-4">Authorization: Bearer YOUR_API_KEY<br>Content-Type: application/json</code>
                <h3 class="text-lg font-semibold mb-2">Request Body</h3>
                <p class="text-sm mb-2">The `input` field can be a single string/URL or a list of strings/URLs.</p>
                <code class="block bg-gray-100 dark:bg-gray-700 p-3 rounded-lg text-sm mb-4">{"input": "Text to moderate"}</code>
                <h3 class="text-lg font-semibold mb-2">Usage Example (cURL)</h3>
                <div class="space-y-4">
                    <div>
                        <h4 class="font-semibold text-md mb-1">Text Moderation</h4>
                        <pre class="bg-gray-100 dark:bg-gray-700 p-4 rounded-lg overflow-x-auto text-sm"><code>curl -X POST https://nixaut-codelabs-smart-moderator.hf.space/v1/moderations \
-H "Authorization: Bearer YOUR_API_KEY" \
-H "Content-Type: application/json" \
-d '{"input": "You are stupid and I hate you."}'</code></pre>
                    </div>
                    <div>
                        <h4 class="font-semibold text-md mb-1">Multimodal Moderation (Text + Image)</h4>
                        <pre class="bg-gray-100 dark:bg-gray-700 p-4 rounded-lg overflow-x-auto text-sm"><code>curl -X POST https://nixaut-codelabs-smart-moderator.hf.space/v1/moderations \
-H "Authorization: Bearer YOUR_API_KEY" \
-H "Content-Type: application/json" \
-d '{"input": [
    "This is a perfectly normal sentence.",
    "https://upload.wikimedia.org/wikipedia/commons/3/3f/Fronalpstock_big.jpg"
]}'</code></pre>
                    </div>
                </div>
            </div>
        </section>
    </main>
    <footer class="bg-gray-100 dark:bg-gray-800 border-t border-gray-200 dark:border-gray-700 mt-12">
        <div class="container mx-auto px-4 py-6 text-center text-gray-600 dark:text-gray-400 text-sm">
            © 2024 Smart Moderator by Nix-Aut Codelabs | <a href="https://nixaut-codelabs-smart-moderator.hf.space" class="hover:underline">nixaut-codelabs-smart-moderator.hf.space</a>
        </div>
    </footer>
    <script>
        const darkModeToggle = document.getElementById('darkModeToggle');
        if (localStorage.getItem('theme') === 'dark' || (!('theme' in localStorage) && window.matchMedia('(prefers-color-scheme: dark)').matches)) {
            document.documentElement.classList.add('dark');
        }
        darkModeToggle.addEventListener('click', () => {
            document.documentElement.classList.toggle('dark');
            localStorage.setItem('theme', document.documentElement.classList.contains('dark') ? 'dark' : 'light');
        });

        let activityChart;
        async function fetchMetrics() {
            const apiKey = document.getElementById('apiKey').value || 'temp-key';
            try {
                const response = await fetch('/v1/metrics', { headers: { 'Authorization': 'Bearer ' + apiKey } });
                if (!response.ok) return;
                const data = await response.json();
                document.getElementById('avgResponseTime').textContent = data.avg_request_time_ms.toFixed(0) + 'ms';
                document.getElementById('peakResponseTime').textContent = data.peak_request_time_ms.toFixed(0) + 'ms';
                document.getElementById('requestsPerMinute').textContent = data.requests_per_minute;
                document.getElementById('todayRequests').textContent = data.today_requests.toLocaleString();

                if (activityChart) {
                    const labels = data.last_7_days.map(d => new Date(d.date).toLocaleDateString('en-US', { month: 'short', day: 'numeric' })).reverse();
                    const requests = data.last_7_days.map(d => d.requests).reverse();
                    activityChart.data.labels = labels;
                    activityChart.data.datasets[0].data = requests;
                    activityChart.update();
                }
            } catch (e) { console.error("Could not fetch metrics", e); }
        }

        function initChart() {
            const ctx = document.getElementById('activityChart').getContext('2d');
            const isDark = document.documentElement.classList.contains('dark');
            activityChart = new Chart(ctx, {
                type: 'bar',
                data: { labels: [], datasets: [{ label: 'Requests', data: [], backgroundColor: 'rgba(99, 102, 241, 0.6)' }] },
                options: { responsive: true, maintainAspectRatio: false, scales: { y: { beginAtZero: true } } }
            });
        }
        
        document.getElementById('apiTestForm').addEventListener('submit', async (e) => {
            e.preventDefault();
            const apiKey = document.getElementById('apiKey').value;
            if (!apiKey) { alert('Please enter an API key.'); return; }
            
            const rawInput = document.getElementById('apiInput').value.trim();
            if (!rawInput) { alert('Please enter text or a URL to analyze.'); return; }

            const inputs = rawInput.split('\\n').map(item => item.trim()).filter(Boolean);
            const body = { input: inputs.length === 1 ? inputs[0] : inputs };

            const analyzeBtn = document.getElementById('analyzeBtn');
            analyzeBtn.disabled = true;
            analyzeBtn.innerHTML = '<div class="loading-spinner inline-block w-4 h-4 border-2 border-white rounded-full mr-2"></div>Analyzing...';

            try {
                const response = await fetch('/v1/moderations', {
                    method: 'POST',
                    headers: { 'Content-Type': 'application/json', 'Authorization': 'Bearer ' + apiKey },
                    body: JSON.stringify(body)
                });
                const data = await response.json();
                displayResults(data);
                fetchMetrics();
            } catch (error) {
                alert('An error occurred: ' + error.message);
            } finally {
                analyzeBtn.disabled = false;
                analyzeBtn.innerHTML = '<i class="fas fa-search mr-2"></i>Analyze';
            }
        });

        function displayResults(data) {
            const resultsContainer = document.getElementById('resultsContainer');
            resultsContainer.innerHTML = '';
            
            if (data.error) {
                 resultsContainer.innerHTML = `<div class="p-4 text-red-700 bg-red-100 dark:bg-red-900 dark:text-red-200 rounded-lg"><p><strong>Error:</strong> ${data.error.message || JSON.stringify(data.error)}</p></div>`;
            } else if (data.results) {
                data.results.forEach((result, index) => {
                    const resultCard = document.createElement('div');
                    resultCard.className = 'border-t border-gray-200 dark:border-gray-700 pt-4 mt-4 first:mt-0 first:border-t-0 first:pt-0';
                    const flaggedBadge = result.flagged 
                        ? '<span class="px-2 py-1 text-xs font-medium rounded-full bg-red-100 text-red-800">Flagged</span>'
                        : '<span class="px-2 py-1 text-xs font-medium rounded-full bg-green-100 text-green-800">Safe</span>';
                    
                    let categoriesHtml = Object.entries(result.category_scores).map(([category, score]) => {
                        const isFlagged = result.categories[category];
                        return `<div class="flex justify-between py-1"><span class="${isFlagged ? 'font-bold text-red-500' : ''}">${category.replace("/", " / ")}</span><span class="font-mono text-sm">${score.toFixed(4)}</span></div>`;
                    }).join('');

                    resultCard.innerHTML = `<div class="flex justify-between items-center mb-2"><h4 class="font-bold">Input ${index + 1}</h4>${flaggedBadge}</div><div>${categoriesHtml}</div>`;
                    resultsContainer.appendChild(resultCard);
                });
            }
            document.getElementById('resultsSection').classList.remove('hidden');
        }

        document.addEventListener('DOMContentLoaded', () => {
            initChart();
            fetchMetrics();
            setInterval(fetchMetrics, 20000);
        });
    </script>
</body>
</html>
'''
    index_path = os.path.join('templates', 'index.html')
    if not os.path.exists(index_path):
        with open(index_path, 'w', encoding='utf-8') as f:
            f.write(index_html_content)

if __name__ == '__main__':
    create_app_structure()
    port = int(os.environ.get('PORT', 7860))
    # For production, use a proper WSGI server like Gunicorn
    # gunicorn --bind 0.0.0.0:7860 app:app
    app.run(host='0.0.0.0', port=port, debug=False)