app.py

import gradio as gr
import requests
import socket
import logging
import time
import re
from bs4 import BeautifulSoup
from urllib.parse import urlparse, urljoin
from typing import Dict, Tuple, Optional
from google import genai

# -------------------------------------------------
# Logging setup
# -------------------------------------------------
logging.basicConfig(
    level=logging.INFO,
    format="%(asctime)s | %(levelname)s | %(message)s",
)
logger = logging.getLogger(__name__)

logger.info("AI Website Review Tool starting up")

# -------------------------------------------------
# Constants
# -------------------------------------------------
TIMEOUT = 15
MAX_RETRIES = 2
CONTENT_LIMIT = 12000

# -----------------------------
# URL Validation & Normalization
# -----------------------------
def normalize_url(url: str) -> str:
    """Normalize and validate URL format."""
    url = url.strip()
    parsed = urlparse(url)
    if not parsed.scheme:
        url = "https://" + url
    return url


def validate_url(url: str) -> Tuple[bool, str]:
    """Validate URL format and accessibility."""
    try:
        parsed = urlparse(url)
        if not parsed.netloc:
            return False, "Invalid URL format. Please include domain name."
        
        # Check for obviously invalid domains
        if len(parsed.netloc) < 4 or '.' not in parsed.netloc:
            return False, "Invalid domain name."
        
        return True, ""
    except Exception as e:
        return False, f"URL validation error: {str(e)}"


# -----------------------------
# Proxy Option (if AFC blocks direct requests)
# -----------------------------
USE_PROXY = False  # Set to True if you need to use a proxy service

def fetch_via_proxy(url: str) -> str:
    """Fetch content via a proxy service (for AFC restrictions)."""
    # Option 1: ScraperAPI (free tier available)
    # proxy_url = f"http://api.scraperapi.com?api_key=YOUR_KEY&url={url}"
    
    # Option 2: WebScraping.AI (free tier available)
    # proxy_url = f"https://api.webscraping.ai/html?api_key=YOUR_KEY&url={url}"
    
    # Option 3: ScrapingBee (free tier available)
    proxy_url = f"https://app.scrapingbee.com/api/v1/?api_key=YOUR_KEY&url={url}"
    
    response = requests.get(proxy_url, timeout=30)
    response.raise_for_status()
    return response.text

# -----------------------------
# Enhanced Content Extraction
# -----------------------------
def extract_website_info(soup: BeautifulSoup, url: str) -> Dict[str, str]:
    """Extract key website elements for analysis."""
    info = {}
    
    # Title
    info['title'] = soup.title.string.strip() if soup.title else ""
    
    # Meta description
    meta_desc = soup.find("meta", attrs={"name": "description"})
    info['meta_description'] = meta_desc.get("content", "").strip() if meta_desc else ""
    
    # Headings
    info['h1'] = soup.find("h1").get_text(strip=True) if soup.find("h1") else ""
    h2_tags = soup.find_all("h2", limit=5)
    info['h2s'] = " | ".join([h2.get_text(strip=True) for h2 in h2_tags])
    
    # CTAs (buttons and prominent links)
    cta_patterns = ['button', 'btn', 'cta', 'call-to-action']
    ctas = []
    for pattern in cta_patterns:
        elements = soup.find_all(class_=re.compile(pattern, re.I))
        ctas.extend([el.get_text(strip=True) for el in elements[:3]])
    info['ctas'] = " | ".join(ctas[:5]) if ctas else "No clear CTAs found"
    
    # Contact information
    contact_indicators = soup.find_all(string=re.compile(r'contact|email|phone|call', re.I))
    info['has_contact'] = len(contact_indicators) > 0
    
    # Links analysis
    links = soup.find_all('a', href=True)
    info['total_links'] = len(links)
    external_links = [l for l in links if urlparse(l['href']).netloc and urlparse(l['href']).netloc != urlparse(url).netloc]
    info['external_links'] = len(external_links)
    
    return info


def fetch_website_text(url: str) -> Tuple[str, bool]:
    """
    Fetch and parse website content.
    Returns (content_string, success_boolean)
    """
    socket.setdefaulttimeout(TIMEOUT)

    headers = {
        "User-Agent": (
            "Mozilla/5.0 (Windows NT 10.0; Win64; x64) "
            "AppleWebKit/537.36 (KHTML, like Gecko) "
            "Chrome/121.0 Safari/537.36"
        ),
        "Accept": "text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8",
        "Accept-Language": "en-US,en;q=0.9",
        "Accept-Encoding": "gzip, deflate",
        "DNT": "1",
    }

    for attempt in range(MAX_RETRIES):
        try:
            if USE_PROXY:
                html_content = fetch_via_proxy(url)
                soup = BeautifulSoup(html_content, "html.parser")
                break
            else:
                response = requests.get(
                    url,
                    headers=headers,
                    timeout=TIMEOUT,
                    allow_redirects=True,
                )
                response.raise_for_status()
                soup = BeautifulSoup(response.text, "html.parser")
                break
        except requests.exceptions.RequestException as e:
            if attempt == MAX_RETRIES - 1:
                raise
            time.sleep(1)

    # Remove noisy tags
    for tag in soup(["script", "style", "noscript", "iframe", "nav", "footer"]):
        tag.decompose()

    # Extract structured info
    info = extract_website_info(soup, url)

    # Body content
    body_text = " ".join(soup.stripped_strings)
    body_text = body_text[:CONTENT_LIMIT]

    content = f"""
PAGE TITLE: {info['title']}
META DESCRIPTION: {info['meta_description']}
PRIMARY H1: {info['h1']}
KEY H2 HEADINGS: {info['h2s']}
CALL-TO-ACTION BUTTONS: {info['ctas']}
CONTACT INFO PRESENT: {"Yes" if info['has_contact'] else "No"}
LINK ANALYSIS: {info['total_links']} total links, {info['external_links']} external

VISIBLE CONTENT:
{body_text}
"""
    return content, True


def fetch_website_text_safe(url: str) -> Tuple[str, bool]:
    """Safe wrapper that never crashes."""
    try:
        return fetch_website_text(url)
    except requests.exceptions.Timeout:
        return """⚠️ Website took too long to respond (timeout).
This might indicate slow server performance.
Analysis will be based on URL structure and general best practices.""", False
    except requests.exceptions.SSLError:
        return """⚠️ SSL Certificate error detected.
This is a major trust issue that should be fixed immediately.
Analysis will include this critical security concern.""", False
    except requests.exceptions.ConnectionError:
        return """⚠️ Could not connect to website.
Website may be down or have DNS issues.
Analysis will be based on general best practices.""", False
    except Exception as e:
        return f"""⚠️ Unable to fully fetch website content.
Error: {str(e)}
Analysis will be based on available information and general best practices.""", False


# -----------------------------
# Gemini Analysis
# -----------------------------
def analyze_website(api_key: str, url: str, industry: str, goal: str) -> str:
    """Main analysis function."""
    
    # Validate inputs
    if not api_key or len(api_key) < 20:
        return "❌ Please enter a valid Gemini API key. Get one at https://aistudio.google.com/apikey"

    if not url:
        return "❌ Please enter a website URL."

    # Normalize and validate URL
    url = normalize_url(url)
    is_valid, error_msg = validate_url(url)
    if not is_valid:
        return f"❌ {error_msg}"

    try:
        # Initialize client
        try:
            client = genai.Client(api_key=api_key)
        except Exception as e:
            return f"❌ Invalid API key. Please check your Gemini API key.\nError: {str(e)}"

        # Fetch website content
        website_text, fetch_success = fetch_website_text_safe(url)
        
        fetch_status = "✅ Full content analysis" if fetch_success else "⚠️ Limited analysis"

        # Build enhanced prompt
        prompt = f"""You are an AI consultant with the company Esquire IT helping small businesses improve their websites.

Business Context:
- Industry: {industry}
- Primary Goal: {goal}
- URL: {url}
- Content Fetch Status: {fetch_status}

Analyze the website content below and provide a comprehensive business-focused review.

Structure your response with clear sections:

## 1. Messaging Clarity (Score: X/10)
**Main Issue:** [One sentence summary]
**Recommendations:**
- [Specific actionable item]
- [Specific actionable item]
- [Specific actionable item]

## 2. Conversion Effectiveness (Score: X/10)
**Main Issue:** [One sentence summary]
**Recommendations:**
- [Specific actionable item]
- [Specific actionable item]
- [Specific actionable item]

## 3. Trust & Credibility (Score: X/10)
**Main Issue:** [One sentence summary]
**Recommendations:**
- [Specific actionable item]
- [Specific actionable item]
- [Specific actionable item]

## 4. User Experience Issues
- [Issue 1]
- [Issue 2]
- [Issue 3]

## 5. AI & Automation Opportunities
For a {industry} business with limited tech resources:
- [Practical AI tool/solution #1]
- [Practical AI tool/solution #2]
- [Practical AI tool/solution #3]

## Summary
**Overall Score:** X/100
**Top 3 Priority Fixes:**
1. [Most urgent fix]
2. [Second priority]
3. [Third priority]

Use clear, non-technical language that a small business owner would understand.

Website Content:
{website_text}
"""

        # Generate analysis
        response = client.models.generate_content(
            model="gemini-2.5-flash-lite",
            contents=prompt,
        )

        result = f"# Analysis for {url}\n\n{response.text}"
        
        if not fetch_success:
            result += "\n\n---\n⚠️ **Note:** Analysis was performed with limited content due to website access issues."
        
        return result

    except Exception as e:
        logger.error(f"Analysis error: {str(e)}")
        return f"❌ Error during analysis: {str(e)}\n\nPlease check your API key and try again."


# -----------------------------
# Gradio UI
# -----------------------------
with gr.Blocks(
    title="AI Website Review Tool",
    theme=gr.themes.Soft(),
    css="""
        .gradio-container {max-width: 900px !important}
        #output {min-height: 500px}
    """
) as demo:
    gr.Markdown("# 🔍 Esquire IT AI Website Review Tool")
    gr.Markdown(
        "Get actionable insights to improve your small business website using Esquire IT's AI analysis."
    )

    with gr.Row():
        with gr.Column():
            api_key = gr.Textbox(
                label="🔑 Gemini API Key",
                placeholder="Paste your Gemini API key here",
                type="password",
                info="Get your free API key at https://aistudio.google.com/apikey",
            )

            url = gr.Textbox(
                label="🌐 Website URL",
                placeholder="example.com or https://example.com",
                info="Enter the homepage or any page you want analyzed",
            )
            
            # gr.Examples(
            #    examples=[
            #        ["https://www.stripe.com"],
            #        ["https://www.shopify.com"],
            #    ],
            #    inputs=url,
            #    label="Try example websites",
            # )

            with gr.Row():
                industry = gr.Dropdown(
                    label="🏢 Industry",
                    choices=[
                        "General SMB",
                        "Law Firm",
                        "Hospitality",
                        "Healthcare",
                        "Real Estate",
                        "E-commerce",
                        "Consulting",
                        "Restaurant",
                        "Fitness",
                        "Education",
                    ],
                    value="General SMB",
                )

                goal = gr.Dropdown(
                    label="🎯 Primary Goal",
                    choices=[
                        "Generate leads",
                        "Sell products",
                        "Sell services",
                        "Build credibility",
                        "Educate visitors",
                        "Book appointments",
                    ],
                    value="Generate leads",
                )

            analyze_btn = gr.Button("🚀 Analyze Website", variant="primary", size="lg")

    with gr.Row():
        output = gr.Markdown(elem_id="output")

    analyze_btn.click(
        fn=analyze_website,
        inputs=[api_key, url, industry, goal],
        outputs=output,
    )

demo.launch()