app.py

import gradio as gr
from transformers import pipeline
import re

def anomalies_detector(logs: str) -> str:
    """
    Detect anomalies in software logs using a Hugging Face transformer model.
    This function uses a specialized model trained to identify unusual patterns
    in system logs, such as:
    - Error messages
    - Unusual system states
    - Security-related events
    - Performance anomalies
    - Unexpected behavior patterns
    
    Args:
        logs (str): The input text containing log entries
        
    Returns:
        str: Formatted analysis results with detected anomalies
    """
    if not logs or not logs.strip():
        return "⚠️ No log data provided. Please enter log entries to analyze."
    
    # Initialize the text classification pipeline
    classifier = pipeline(
        "text-classification",
        model="distilbert/distilbert-base-uncased-finetuned-sst-2-english"
    )
    
    # Split logs into lines
    log_lines = [line for line in logs.split('\n') if line.strip()]
    
    if not log_lines:
        return "⚠️ No valid log entries found."
    
    # Process each line
    anomalies = []
    total_lines = len(log_lines)
    negative_count = 0
    
    for line_num, line in enumerate(log_lines, 1):
        try:
            # Get classification result
            result = classifier(line[:512])[0]  # Limit to 512 chars for model
            
            # Consider "NEGATIVE" sentiment as potential anomaly
            if result['label'] == 'NEGATIVE' and result['score'] > 0.7:
                anomalies.append({
                    'line': line_num,
                    'text': line,
                    'confidence': result['score']
                })
                negative_count += 1
        except Exception as e:
            continue
    
    # Format output
    output = f"📊 **Analysis Summary**\n"
    output += f"{'='*60}\n\n"
    output += f"📝 Total log entries analyzed: **{total_lines}**\n"
    output += f"🔍 Potential anomalies detected: **{negative_count}**\n"
    output += f"✅ Health rate: **{((total_lines - negative_count) / total_lines * 100):.1f}%**\n\n"
    
    if anomalies:
        output += f"⚠️ **Detected Anomalies:**\n"
        output += f"{'-'*60}\n\n"
        for idx, anomaly in enumerate(anomalies, 1):
            output += f"**#{idx} | Line {anomaly['line']}** (Confidence: {anomaly['confidence']:.2%})\n"
            output += f"```\n{anomaly['text']}\n```\n\n"
    else:
        output += "✨ **No significant anomalies detected!**\n"
        output += "Your logs appear to be healthy.\n"
    
    return output


# Custom CSS for dark navy blue and electric blue theme
custom_css = """
:root {
    --electric-blue: #00D4FF;
    --bright-blue: #0099FF;
    --navy-blue: #001F3F;
    --dark-navy: #001129;
    --deep-navy: #000814;
    --white: #FFFFFF;
    --off-white: #F8FCFF;
    --light-gray: #E8F4F8;
    --cyber-glow: rgba(0, 212, 255, 0.3);
}

/* Main background */
.gradio-container {
    background: linear-gradient(135deg, var(--deep-navy) 0%, var(--dark-navy) 50%, var(--navy-blue) 100%) !important;
    font-family: 'Inter', -apple-system, BlinkMacSystemFont, 'Segoe UI', sans-serif !important;
    position: relative !important;
}

.gradio-container::before {
    content: '' !important;
    position: absolute !important;
    top: 0 !important;
    left: 0 !important;
    right: 0 !important;
    bottom: 0 !important;
    background: radial-gradient(circle at 20% 50%, rgba(0, 212, 255, 0.08) 0%, transparent 50%),
                radial-gradient(circle at 80% 80%, rgba(0, 153, 255, 0.06) 0%, transparent 50%) !important;
    pointer-events: none !important;
}

/* Header styling */
.contain {
    background: rgba(255, 255, 255, 0.98) !important;
    border-radius: 20px !important;
    box-shadow: 0 20px 60px rgba(0, 212, 255, 0.2), 0 0 40px rgba(0, 153, 255, 0.1) !important;
    padding: 2rem !important;
    margin: 2rem auto !important;
    max-width: 1400px !important;
    border: 1px solid rgba(0, 212, 255, 0.1) !important;
}

/* Title styling */
h1 {
    background: linear-gradient(135deg, var(--bright-blue), var(--electric-blue)) !important;
    -webkit-background-clip: text !important;
    -webkit-text-fill-color: transparent !important;
    background-clip: text !important;
    font-weight: 800 !important;
    font-size: 2.5rem !important;
    margin-bottom: 0.5rem !important;
    text-align: center !important;
    filter: drop-shadow(0 0 20px rgba(0, 212, 255, 0.3)) !important;
}

/* Description text */
.prose p {
    color: var(--navy-blue) !important;
    font-size: 1.1rem !important;
    text-align: center !important;
    margin-bottom: 1.5rem !important;
}

/* Input/Output boxes */
.input-text, .output-text, textarea {
    border: 2px solid var(--bright-blue) !important;
    border-radius: 12px !important;
    background: var(--white) !important;
    font-family: 'Fira Code', 'Courier New', monospace !important;
    font-size: 0.95rem !important;
    transition: all 0.3s ease !important;
    box-shadow: 0 2px 10px rgba(0, 153, 255, 0.1) !important;
}

.input-text:focus, textarea:focus {
    border-color: var(--electric-blue) !important;
    box-shadow: 0 0 0 3px var(--cyber-glow), 0 0 20px rgba(0, 212, 255, 0.2) !important;
    outline: none !important;
}

/* Labels */
label {
    color: var(--navy-blue) !important;
    font-weight: 600 !important;
    font-size: 1rem !important;
    margin-bottom: 0.5rem !important;
}

/* Submit button */
.submit-button, button[id$="-submit-button"] {
    background: linear-gradient(135deg, var(--bright-blue), var(--electric-blue)) !important;
    color: var(--white) !important;
    border: none !important;
    border-radius: 12px !important;
    padding: 0.75rem 2rem !important;
    font-weight: 600 !important;
    font-size: 1rem !important;
    cursor: pointer !important;
    transition: all 0.3s ease !important;
    box-shadow: 0 4px 15px rgba(0, 212, 255, 0.3), 0 0 20px rgba(0, 153, 255, 0.2) !important;
}

.submit-button:hover, button[id$="-submit-button"]:hover {
    transform: translateY(-2px) !important;
    box-shadow: 0 6px 20px rgba(0, 212, 255, 0.4), 0 0 30px rgba(0, 153, 255, 0.3) !important;
    filter: brightness(1.1) !important;
}

/* Clear button */
.clear-button, button.secondary {
    background: var(--white) !important;
    color: var(--navy-blue) !important;
    border: 2px solid var(--bright-blue) !important;
    border-radius: 12px !important;
    padding: 0.75rem 2rem !important;
    font-weight: 600 !important;
    transition: all 0.3s ease !important;
}

.clear-button:hover, button.secondary:hover {
    background: var(--electric-blue) !important;
    color: var(--white) !important;
    transform: translateY(-2px) !important;
    box-shadow: 0 4px 15px rgba(0, 212, 255, 0.3) !important;
}

/* Output markdown styling */
.markdown-text {
    background: var(--off-white) !important;
    padding: 1.5rem !important;
    border-radius: 12px !important;
    border-left: 4px solid var(--electric-blue) !important;
    box-shadow: 0 2px 10px rgba(0, 153, 255, 0.1) !important;
}

.markdown-text code {
    background: var(--white) !important;
    padding: 0.2rem 0.4rem !important;
    border-radius: 4px !important;
    color: var(--navy-blue) !important;
    border: 1px solid var(--bright-blue) !important;
}

.markdown-text pre {
    background: var(--white) !important;
    border: 2px solid var(--bright-blue) !important;
    border-radius: 8px !important;
    padding: 1rem !important;
    box-shadow: inset 0 2px 8px rgba(0, 153, 255, 0.05) !important;
}

/* Footer */
footer {
    background: transparent !important;
    color: var(--white) !important;
    text-align: center !important;
    padding: 2rem !important;
    text-shadow: 0 0 10px rgba(0, 212, 255, 0.5) !important;
}

footer a {
    color: var(--electric-blue) !important;
    text-decoration: underline !important;
}

/* Examples section */
.examples {
    background: var(--off-white) !important;
    border-radius: 12px !important;
    padding: 1rem !important;
    border: 2px solid var(--bright-blue) !important;
    box-shadow: 0 2px 10px rgba(0, 153, 255, 0.1) !important;
}

/* Scrollbar styling */
::-webkit-scrollbar {
    width: 10px !important;
}

::-webkit-scrollbar-track {
    background: var(--light-gray) !important;
    border-radius: 5px !important;
}

::-webkit-scrollbar-thumb {
    background: linear-gradient(180deg, var(--electric-blue), var(--bright-blue)) !important;
    border-radius: 5px !important;
    box-shadow: 0 0 10px rgba(0, 212, 255, 0.3) !important;
}

::-webkit-scrollbar-thumb:hover {
    background: var(--electric-blue) !important;
    box-shadow: 0 0 15px rgba(0, 212, 255, 0.5) !important;
}

/* Cyber glow effects */
.submit-button::before, button[id$="-submit-button"]::before {
    content: '' !important;
    position: absolute !important;
    top: -2px !important;
    left: -2px !important;
    right: -2px !important;
    bottom: -2px !important;
    background: linear-gradient(45deg, var(--electric-blue), var(--bright-blue)) !important;
    border-radius: 12px !important;
    z-index: -1 !important;
    opacity: 0 !important;
    transition: opacity 0.3s ease !important;
    filter: blur(10px) !important;
}

.submit-button:hover::before, button[id$="-submit-button"]:hover::before {
    opacity: 0.7 !important;
}
"""

# Example logs for demonstration
example_logs = [
    """2024-01-29 10:15:23 INFO User logged in successfully
2024-01-29 10:15:45 INFO Database connection established
2024-01-29 10:16:02 ERROR Failed to connect to payment gateway
2024-01-29 10:16:15 WARN Retry attempt 1 of 3
2024-01-29 10:16:30 ERROR Connection timeout after 30 seconds
2024-01-29 10:16:45 CRITICAL Payment service unavailable""",
    
    """2024-01-29 14:22:10 INFO Application started successfully
2024-01-29 14:22:15 INFO Loading configuration files
2024-01-29 14:22:18 INFO Server listening on port 8080
2024-01-29 14:22:20 INFO Ready to accept connections""",
    
    """2024-01-29 16:30:45 INFO User authentication request
2024-01-29 16:30:46 WARN Invalid credentials provided
2024-01-29 16:30:50 WARN Login attempt failed for user: admin
2024-01-29 16:30:55 ERROR Multiple failed login attempts detected
2024-01-29 16:31:00 CRITICAL Potential security breach - IP blocked"""
]

# Create the Gradio interface
demo = gr.Interface(
    fn=anomalies_detector,
    inputs=gr.Textbox(
        label="📋 Log Entries",
        placeholder="Paste your software logs here (mobile app, desktop, web server, etc.)\n\nExample:\n2024-01-29 10:15:23 INFO User logged in\n2024-01-29 10:16:02 ERROR Connection failed\n2024-01-29 10:16:15 WARN Retry attempt...",
        lines=15,
        max_lines=25
    ),
    outputs=gr.Markdown(
        label="🔍 Analysis Results"
    ),
    title="🛡️ Sentinel Log Analyzer",
    description="**Enterprise-grade anomaly detection for all your software logs.** Supports mobile apps, desktop applications, web servers, and more. Powered by advanced AI to identify errors, security events, and unusual patterns in real-time.",
    examples=example_logs,
    css=custom_css,
    theme=gr.themes.Soft(
        primary_hue="blue",
        secondary_hue="cyan",
    ),
    allow_flagging="never",
    analytics_enabled=False
)

# Launch the application
if __name__ == "__main__":
    demo.launch(
        server_name="0.0.0.0",
        server_port=7860,
        share=True,
        show_error=True
    )