Update seo_analyzer_ui.py

seo_analyzer_ui.py

@@ -1,7 +1,6 @@
 """
-SEO Analyzer UI using Gradio, Web Crawler, and OpenAI
+SEO Analyzer UI with Auto Ad Generator Tab
 """
-
 import gradio as gr
 import logging
 import json
@@ -19,6 +18,9 @@ from concurrent.futures import ThreadPoolExecutor
 from datetime import datetime
 import tempfile
 
+from bs4 import BeautifulSoup
+import requests
+
 from crawler import Crawler
 from frontier import URLFrontier
 from models import URL, Page
@@ -28,7 +30,6 @@ from dotenv import load_dotenv, find_dotenv
 
 load_dotenv(find_dotenv())
 
-# Check if we're in deployment mode (e.g., Hugging Face Spaces)
 IS_DEPLOYMENT = os.getenv('DEPLOYMENT', 'false').lower() == 'true'
 
 # Custom CSS for better styling
@@ -694,15 +695,284 @@ def create_ui() -> gr.Interface:
 
     return iface
 
+# ----- SEO Analyzer UI (as a function) -----
+def seo_analyzer_ui():
+    def analyze(url: str, api_key: str, max_pages: int, progress: gr.Progress = gr.Progress()) -> Tuple[str, str]:
+        try:
+            analyzer = SEOAnalyzer(api_key)
+            analysis, _, logs = analyzer.analyze_website(url, max_pages, progress)
+            log_output = ""
+            while not analyzer.log_queue.empty():
+                try:
+                    log_output += analyzer.log_queue.get_nowait() + "\n"
+                except queue.Empty:
+                    break
+            progress(1.0, "Analysis complete")
+            return analysis, log_output
+        except Exception as e:
+            error_msg = f"Error: {str(e)}"
+            logger.error(error_msg)
+            return error_msg, error_msg
+
+    about_markdown = """
+    # 🔍 SEO Analyzer Pro
+    Analyze your website's SEO performance using advanced crawling and AI technology.
+    ...
+    """
+    with gr.Blocks() as seo_tab:
+        gr.Markdown(about_markdown)
+        with gr.Row():
+            with gr.Column(scale=2):
+                with gr.Group(elem_classes="input-section"):
+                    gr.Markdown("### 📝 Enter Website Details")
+                    url_input = gr.Textbox(
+                        label="Website URL",
+                        placeholder="https://example.com",
+                        elem_classes="input-container",
+                        info="Enter the full URL of the website you want to analyze (e.g., https://example.com)"
+                    )
+                    api_key = gr.Textbox(
+                        label="OpenAI API Key",
+                        placeholder="sk-...",
+                        type="password",
+                        elem_classes="input-container",
+                        info="Your OpenAI API key is required for AI-powered analysis. Keep this secure!"
+                    )
+                    max_pages = gr.Slider(
+                        minimum=1,
+                        maximum=50,
+                        value=10,
+                        step=1,
+                        label="Maximum Pages to Crawl",
+                        elem_classes="slider-container",
+                        info="Choose how many pages to analyze. More pages = more comprehensive analysis but takes longer"
+                    )
+                    analyze_btn = gr.Button(
+                        "🔍 Analyze Website",
+                        elem_classes="primary-button"
+                    )
+
+        with gr.Row():
+            with gr.Column():
+                with gr.Group(elem_classes="analysis-section"):
+                    gr.Markdown("### 📊 Analysis Results")
+                    analysis_output = gr.Markdown(
+                        label="SEO Analysis",
+                        elem_classes="markdown-output"
+                    )
+        with gr.Row():
+            with gr.Column():
+                with gr.Group(elem_classes="log-section"):
+                    gr.Markdown("### 📋 Process Logs")
+                    logs_output = gr.Textbox(
+                        label="Logs",
+                        lines=10,
+                        elem_classes="log-output"
+                    )
+        analyze_btn.click(
+            fn=analyze,
+            inputs=[url_input, api_key, max_pages],
+            outputs=[analysis_output, logs_output],
+        )
+    return seo_tab
+
+# ---- Auto Ad Generator UI as a function ----
+def auto_ad_generator_ui():
+    openai.api_key = os.getenv("OPENAI_API_KEY")
+
+    def extract_text_from_url(url):
+        try:
+            resp = requests.get(url, timeout=30, headers={
+                "User-Agent": "Mozilla/5.0 (compatible; Bot/1.0)"
+            })
+            soup = BeautifulSoup(resp.content, "html.parser")
+            candidates = soup.find_all(['h1','h2','h3','h4','p','span','li'])
+            text = ' '.join([c.get_text(strip=True) for c in candidates])
+            text = text[:4000]
+            if len(text) < 100:
+                raise ValueError("Could not extract enough content (site may require JavaScript). Please enter keywords manually.")
+            return text
+        except Exception as e:
+            raise ValueError(f"URL extraction error: {e}")
+
+    def extract_keywords(text):
+        prompt = f"""
+        Extract up to 10 concise, relevant SEO keywords suitable for an automotive advertisement from the following content:
+        {text}
+        Keywords:
+        """
+        response = openai.ChatCompletion.create(
+            model="gpt-4",
+            messages=[{"role": "user", "content": prompt}],
+            temperature=0.6,
+            max_tokens=100
+        )
+        output = response.choices[0].message.content.strip()
+        if ',' in output:
+            keywords = output.split(',')
+        else:
+            keywords = output.split('\n')
+        return [kw.strip() for kw in keywords if kw.strip()]
+
+    def generate_ad_copy(platform, keywords):
+        prompt = f"""
+        Create a compelling, SEO-optimized {platform} ad using these keywords: {', '.join(keywords)}. 
+        Include a clear and enticing call-to-action.
+        """
+        response = openai.ChatCompletion.create(
+            model="gpt-4",
+            messages=[{"role": "user", "content": prompt}],
+            temperature=0.7,
+            max_tokens=300
+        )
+        return response.choices[0].message.content.strip()
+
+    def generate_ad_image(keywords):
+        kw_str = ", ".join(keywords)
+        image_prompt = (
+            f"High-quality, photorealistic automotive ad photo of a luxury car. "
+            f"Clean background, professional lighting, stylish dealership setting. "
+            f"Keywords: {kw_str}. Room for text overlay, wide format, visually appealing."
+        )
+        response = openai.Image.create(
+            prompt=image_prompt,
+            n=1,
+            size="512x512"
+        )
+        image_url = response["data"][0]["url"]
+        img_data = requests.get(image_url).content
+        img_file = "generated_ad_image.png"
+        with open(img_file, "wb") as f:
+            f.write(img_data)
+        return img_file
+
+    def platform_html(platform, ad_text):
+        if platform == "Facebook":
+            color = "#1877F2"
+            icon = "🌐"
+        elif platform == "Instagram":
+            color = "linear-gradient(90deg, #f58529 0%, #dd2a7b 50%, #8134af 100%)"
+            icon = "📸"
+        elif platform == "X (Twitter)":
+            color = "#14171A"
+            icon = "🐦"
+        else: # Google Search
+            color = "#4285F4"
+            icon = "🔍"
+
+        if platform == "Instagram":
+            content = f"""
+            <div style="background: {color}; padding: 2px; border-radius: 12px; margin-bottom:16px;">
+                <div style="background: white; color: #333; padding: 18px 20px; border-radius: 10px;">
+                    <span style="font-size: 1.5em;">{icon} <b>{platform}</b></span>
+                    <div style="margin-top: 12px; font-size: 1.1em; line-height:1.6;">{ad_text}</div>
+                </div>
+            </div>
+            """
+        else:
+            content = f"""
+            <div style="background: {color}; color: white; padding: 18px 20px; border-radius: 12px; margin-bottom:16px; min-height: 120px;">
+                <span style="font-size: 1.5em;">{icon} <b>{platform}</b></span>
+                <div style="margin-top: 12px; font-size: 1.1em; line-height:1.6;">{ad_text}</div>
+            </div>
+            """
+        return content
+
+    def main_workflow(input_mode, url_or_keywords):
+        error = None
+        keywords = []
+        ad_copies = {}
+        image_path = None
+
+        if input_mode == "URL":
+            try:
+                text = extract_text_from_url(url_or_keywords)
+                keywords = extract_keywords(text)
+            except Exception as e:
+                return None, None, None, f"{e}"
+        else:
+            keywords = [kw.strip() for kw in url_or_keywords.split(",") if kw.strip()]
+            if not keywords:
+                return None, None, None, "Please provide at least one keyword."
+        # Generate ad copies
+        platforms = ["Facebook", "Instagram", "X (Twitter)", "Google Search"]
+        for platform in platforms:
+            ad_copies[platform] = generate_ad_copy(platform, keywords)
+        # Generate image
+        try:
+            image_path = generate_ad_image(keywords)
+        except Exception as e:
+            error = f"Image generation error: {e}"
+
+        # Save ads to txt
+        output_txt = "generated_ads.txt"
+        with open(output_txt, "w", encoding="utf-8") as f:
+            for platform, content in ad_copies.items():
+                f.write(f"--- {platform} Ad Copy ---\n{content}\n\n")
+        return keywords, ad_copies, image_path, error
+
+    def run_space(input_mode, url, keywords):
+        url_or_keywords = url if input_mode == "URL" else keywords
+        keywords, ad_copies, image_path, error = main_workflow(input_mode, url_or_keywords)
+        ad_previews = ""
+        if ad_copies:
+            for platform, ad in ad_copies.items():
+                ad_previews += platform_html(platform, ad)
+        return (
+            keywords,
+            ad_previews,
+            image_path,
+            "generated_ads.txt" if ad_copies else None,
+            error
+        )
+
+    with gr.Blocks() as ad_tab:
+        gr.Markdown("# 🚗 Auto Ad Generator\nPaste a car listing URL **or** enter your own keywords, then preview AI-generated ads for each social media platform, plus an auto-generated image!")
+        input_mode = gr.Radio(["URL", "Keywords"], value="URL", label="Input Type")
+        url_input = gr.Textbox(label="Listing URL", placeholder="https://www.cars.com/listing/...", visible=True)
+        kw_input = gr.Textbox(label="Manual Keywords (comma separated)", placeholder="e.g. BMW, used car, sunroof", visible=False)
+        submit_btn = gr.Button("Generate Ads")
+
+        gr.Markdown("## Keywords")
+        kw_out = gr.JSON(label="Extracted/Provided Keywords")
+
+        gr.Markdown("## Ad Copy Previews")
+        ad_out = gr.HTML(label="Ad Copy Preview")
+
+        gr.Markdown("## Generated Ad Image")
+        img_out = gr.Image(label="Generated Ad Image", type="filepath")
+
+        gr.Markdown("## Download Ad Copies")
+        file_out = gr.File(label="Download TXT")
+
+        err_out = gr.Textbox(label="Errors", interactive=False)
+
+        def show_hide_fields(choice):
+            return (
+                gr.update(visible=choice == "URL"),
+                gr.update(visible=choice == "Keywords"),
+            )
+
+        input_mode.change(show_hide_fields, input_mode, [url_input, kw_input])
+
+        submit_btn.click(
+            run_space,
+            inputs=[input_mode, url_input, kw_input],
+            outputs=[kw_out, ad_out, img_out, file_out, err_out]
+        )
+    return ad_tab
+
+# ---- Main App: Two Tabs ----
 if __name__ == "__main__":
-    # Create base storage directory if it doesn't exist
     os.makedirs(config.STORAGE_PATH, exist_ok=True)
-    
-    # Create and launch UI
-    ui = create_ui()
-    ui.launch(
+    with gr.Blocks(css=CUSTOM_CSS) as demo:
+        with gr.Tab("SEO Analyzer"):
+            seo_analyzer_ui()
+        with gr.Tab("Auto Ad Generator"):
+            auto_ad_generator_ui()
+    demo.launch(
         share=False,
         server_name="0.0.0.0",
         show_api=False,
         show_error=True,
-    ) 
+    )