Update app.py

app.py

@@ -1,174 +1,159 @@
 import gradio as gr
-import requests
-from bs4 import BeautifulSoup
 import pandas as pd
+import plotly.graph_objects as go
 from langchain_google_genai import ChatGoogleGenerativeAI
 from langchain_core.messages import HumanMessage
 import os
-import re
+import random
 
 # --- Configuration ---
 GEMINI_API_KEY = os.environ.get("GEMINI_API_KEY")
 
-# --- Core Analysis Functions (Unchanged) ---
-def fetch_html(url: str) -> str | None:
-    # ... (code is the same as before) ...
-    try:
-        headers = {'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36'}
-        response = requests.get(url, headers=headers, timeout=10)
-        response.raise_for_status()
-        return response.text
-    except requests.RequestException:
-        return None
-
-def analyze_onpage_seo(soup: BeautifulSoup) -> dict:
-    # ... (code is the same as before) ...
-    title = soup.find('title').get_text(strip=True) if soup.find('title') else "Not found"
-    description_tag = soup.find('meta', attrs={'name': 'description'})
-    description = description_tag['content'] if description_tag and description_tag.has_attr('content') else "Not found"
-    headings = {'h1': [], 'h2': []}
-    for h_tag in ['h1', 'h2']:
-        for tag in soup.find_all(h_tag):
-            headings[h_tag].append(tag.get_text(strip=True))
-    word_count = len(soup.get_text(separator=' ', strip=True).split())
-    return {"title": title, "description": description, "headings": headings, "word_count": word_count}
-
-def analyze_tech_stack(html: str) -> list[str]:
-    # ... (code is the same as before) ...
-    tech = set()
-    if "react.js" in html or 'data-reactroot' in html: tech.add("React")
-    if "vue.js" in html: tech.add("Vue.js")
-    if "wp-content" in html: tech.add("WordPress")
-    if "gtag('config'" in html: tech.add("Google Analytics (GA4)")
-    if "GTM-" in html: tech.add("Google Tag Manager")
-    if "tailwind" in html: tech.add("Tailwind CSS")
-    if "shopify" in html: tech.add("Shopify")
-    return list(tech) if tech else ["Basic HTML/CSS"]
-
-def analyze_ads_and_keywords(domain: str) -> dict:
-    # ... (code is the same as before, with simulated data) ...
-    print(f"Simulating Ads & Keywords API call for {domain}")
-    if "notion" in domain:
-        return { "keywords": [{"keyword": "what is notion", "volume": 65000, "cpc": 0.50}, {"keyword": "notion templates", "volume": 45000, "cpc": 1.20}, {"keyword": "second brain app", "volume": 12000, "cpc": 2.50}, {"keyword": "project management software", "volume": 25000, "cpc": 8.00},], "ads": [{"title": "Notion – Your All-in-One Workspace", "text": "Organize your life and work. From notes and docs, to projects and wikis, Notion is all you need."}, {"title": "The Best Second Brain App | Notion", "text": "Stop juggling tools. Notion combines everything you need to think, write, and plan in one place."},] }
-    if "mailchimp" in domain:
-        return { "keywords": [{"keyword": "email marketing", "volume": 90500, "cpc": 15.50}, {"keyword": "free email marketing tools", "volume": 14800, "cpc": 12.00}, {"keyword": "newsletter software", "volume": 8100, "cpc": 9.50},], "ads": [{"title": "Mailchimp: Marketing & Email", "text": "Grow your business with Mailchimp's All-in-One marketing, automation & email marketing platform."},] }
-    return {"keywords": [], "ads": []}
-
-# --- AI Summary (Now with a Conversion Trigger) ---
-def generate_ai_summary(url: str, seo_data: dict, ads_data: dict) -> str:
+# --- Stage 1: Data Ingestion (Simulation) ---
+def fetch_market_chatter(niche_description: str) -> list[str]:
+    """Simulates scraping Reddit, Hacker News, etc., for a given niche."""
+    print(f"Simulating scraping for: {niche_description}")
+    # In a real app, this would use PRAW, snscrape, etc.
+    # We'll generate realistic-sounding comments.
+    base_comments = [
+        "Ugh, another project management tool that charges per user. I'm a solo founder, this kills me.",
+        "I love the idea of Notion but it's just too slow and bloated now. I need something faster.",
+        "Why can't any of these tools just have a simple, reliable integration with Google Calendar?",
+        "I'm a writer, not a project manager. I just need a clean way to organize my chapters and research.",
+        "Asana is too complex. Trello is too simple. Is there anything in between?",
+        "The real magic would be a tool that automatically generates a weekly summary of my progress.",
+        "Their customer support is a joke. Took three days to get a reply on a critical bug.",
+        "The 'all-in-one' promise is a lie. It does 10 things poorly instead of one thing well.",
+        "If someone built a beautiful, minimalist PM tool for visual artists, I'd pay $50/month in a heartbeat."
+    ]
+    return random.sample(base_comments, k=random.randint(5, len(base_comments)))
+
+# --- Stage 2 & 3: AI Analysis Pipeline ---
+def analyze_resonance(niche_description: str, comments: list[str]) -> dict:
+    """Uses an LLM to perform topic modeling, pain point extraction, and sentiment analysis."""
     if not GEMINI_API_KEY:
-        return "⚠️ **AI Summary Unavailable:** The `GEMINI_API_KEY` is not set in the Space secrets."
+        return {"error": "GEMINI_API_KEY not set."}
 
+    llm = ChatGoogleGenerativeAI(model="gemini-1.5-pro-latest", google_api_key=GEMINI_API_KEY)
+    
+    # Create a single, powerful prompt for the analysis
+    comments_formatted = "\n".join([f"- \"{c}\"" for c in comments])
+    prompt = f"""
+    You are a market research analyst with superhuman insight. Analyze the following raw market chatter (comments from Reddit, Hacker News, etc.) for a proposed product idea.
+
+    **Proposed Product Idea:** "{niche_description}"
+
+    **Raw Market Chatter:**
+    {comments_formatted}
+
+    **Your Task:**
+    Analyze the chatter and return a JSON object with the following structure. Do not include any text outside the JSON object.
+    {{
+      "pain_points": [
+        "A summary of the most common complaint or frustration.",
+        "A summary of the second most common complaint.",
+        "A summary of a third, more niche complaint."
+      ],
+      "magic_words": [
+        "A positive, benefit-oriented word or phrase people use.",
+        "Another evocative word people use to describe their ideal solution.",
+        "A third powerful, emotional word."
+      ],
+      "target_villain": "The name of a competitor or a type of product that people frequently complain about.",
+      "unserved_tribe": "A description of a specific user subgroup whose needs are not being met.",
+      "resonance_score": A number between 1 and 100 representing how well the proposed product idea fits the market chatter,
+      "resonance_justification": "A one-sentence explanation for the score you gave."
+    }}
+    """
     try:
-        llm = ChatGoogleGenerativeAI(model="gemini-1.5-flash", google_api_key=GEMINI_API_KEY)
-        
-        ads_summary = "They do not appear to be running any significant Google Ads campaigns."
-        if ads_data and ads_data.get('keywords'):
-            top_keyword = ads_data['keywords'][0]
-            ads_summary = f"They are actively running Google Ads, primarily bidding on high-intent keywords like **'{top_keyword['keyword']}'**."
-
-        # *** NEW: CONVERSION TRIGGER IN THE PROMPT ***
-        # We are telling the AI to hint at deeper insights that the Pro version would provide.
-        prompt = f"""
-        As a world-class marketing strategist, analyze the data for the website `{url}` and provide a concise, actionable summary in markdown format.
-
-        **On-Page Focus:** Their primary H1 heading is "{seo_data['headings']['h1'][0] if seo_data['headings']['h1'] else 'N/A'}".
-        **Paid Strategy:** {ads_summary}
-
-        Based on this, provide your **Strategic Teardown**:
-        - **🎯 Core Marketing Angle:** What is their main value proposition and selling point?
-        - **📈 Customer Acquisition Focus:** Based on the data, are they focused more on organic SEO or paid advertising?
-        - **💡 One Actionable Insight:** What is one clever tactic they're using, or one key opportunity they are missing?
-
-        **Finally, add a "Go Deeper" section that hints at what a full analysis could uncover, like this example: "Go Deeper: A full Pro analysis could reveal their top-performing ad copy and entire keyword portfolio."**
-        """
         response = llm.invoke([HumanMessage(content=prompt)])
-        return response.content
+        # Clean up the response to ensure it's valid JSON
+        json_str = response.content.strip().replace("```json", "").replace("```", "")
+        return json.loads(json_str)
     except Exception as e:
-        return f"⚠️ **AI Summary Failed:** The API call could not be completed. Error: {e}"
-
-# --- Main Orchestrator (Unchanged) ---
-def competitor_teardown(url: str):
-    # ... (code is the same as before) ...
-    outputs = { "summary": " ", "seo": " ", "tech": " ", "ads": " ", "btn": gr.Button("Analyzing...", interactive=False) }
-    yield list(outputs.values())
-    if not url.startswith(('http://', 'https://')): url = 'https://' + url
-    domain_match = re.search(r'https?://(?:www\.)?([^/]+)', url)
-    if not domain_match:
-        outputs["summary"] = "❌ **Invalid URL:** Please enter a valid website address like `notion.so`."
-        outputs["btn"] = gr.Button("Analyze", interactive=True)
-        yield list(outputs.values())
-        return
-    domain = domain_match.group(1)
-    html = fetch_html(url)
-    if not html:
-        outputs["summary"] = f"❌ **Fetch Failed:** Could not retrieve content from `{url}`. The site may be down or blocking scrapers."
-        outputs["btn"] = gr.Button("Analyze", interactive=True)
-        yield list(outputs.values())
+        return {"error": f"Failed to analyze resonance: {e}"}
+
+# --- Main Orchestrator ---
+def run_precog_analysis(niche_description: str):
+    # This orchestrates the entire pipeline
+    yield "Initializing Pre-Cog Engine...", None, None, gr.Button("Analyzing...", interactive=False)
+    
+    # Stage 1
+    comments = fetch_market_chatter(niche_description)
+    yield f"Scanning Market Chatter... ({len(comments)} data points found)", None, None, gr.Button("Analyzing...", interactive=False)
+
+    # Stage 2 & 3
+    analysis_result = analyze_resonance(niche_description, comments)
+    if "error" in analysis_result:
+        yield f"Error: {analysis_result['error']}", None, None, gr.Button("Analyze", interactive=True)
         return
-    soup = BeautifulSoup(html, 'html.parser')
-    seo_data = analyze_onpage_seo(soup)
-    tech_data = analyze_tech_stack(html)
-    ads_data = analyze_ads_and_keywords(domain)
-    ai_summary = generate_ai_summary(url, seo_data, ads_data)
-    outputs["summary"] = ai_summary
-    outputs["seo"] = f"""### 👑 SEO & Content Analysis
-| Metric | Value |
-| :--- | :--- |
-| **Page Title** | `{seo_data['title']}` |
-| **Meta Description** | `{seo_data['description']}` |
-| **Word Count** | `{seo_data['word_count']:,}` |
-#### Heading Structure
-- **H1 Tags ({len(seo_data['headings']['h1'])}):** {', '.join(f'`{h}`' for h in seo_data['headings']['h1']) if seo_data['headings']['h1'] else 'None Found'}
-- **H2 Tags ({len(seo_data['headings']['h2'])}):** {len(seo_data['headings']['h2'])} found
-"""
-    outputs["tech"] = "### ⚙️ Technology Stack\n\n" + "\n".join([f"- `{t}`" for t in tech_data])
-    if ads_data.get("keywords"):
-        df = pd.DataFrame(ads_data["keywords"])
-        df['cpc'] = df['cpc'].apply(lambda x: f"${x:.2f}")
-        ads_md = "### 📢 Paid Ads & Keywords\nThis competitor is actively bidding on Google Search ads. Here are their top keywords:\n\n"
-        ads_md += df.to_markdown(index=False)
-        ads_md += "\n\n### ✍️ Sample Ad Copy\n\n"
-        for ad in ads_data["ads"]: ads_md += f"**{ad['title']}**\n\n>{ad['text']}\n\n---\n\n"
-        outputs["ads"] = ads_md
-    else:
-        outputs["ads"] = "### 📢 Paid Ads & Keywords\n\nNo significant paid advertising activity was detected for this domain."
-    outputs["btn"] = gr.Button("Analyze", interactive=True)
-    yield list(outputs.values())
-
-# --- Gradio UI (Now with your Gumroad link and better conversion copy) ---
-with gr.Blocks(theme=gr.themes.Soft(), css="footer {display: none !important;}") as demo:
-    gr.Markdown("# 🕵️ Gumbo Board: The Instant Competitor Teardown")
-    gr.Markdown("Enter a competitor's website to get an instant analysis of their online strategy. *Powered by Gumbo (BeautifulSoup) & AI.*")
+    
+    # --- Prepare Outputs ---
+    
+    # The main report
+    score = analysis_result.get('resonance_score', 0)
+    color = "green" if score > 65 else "orange" if score > 40 else "red"
+    report_md = f"""
+    <div style="text-align:center; border: 2px solid {color}; border-radius:10px; padding:20px;">
+        <h2 style="margin:0;">Market Resonance Score</h2>
+        <p style="font-size: 80px; font-weight:bold; margin:0; color:{color};">{score}/100</p>
+        <p style="margin:0; font-style:italic;">"{analysis_result.get('resonance_justification', '')}"</p>
+    </div>
+
+    ### 💥 Top 3 Unspoken Pain Points
+    1.  **{analysis_result.get('pain_points', ['N/A'])[0]}**
+    2.  **{analysis_result.get('pain_points', ['N/A'])[1]}**
+    3.  **{analysis_result.get('pain_points', ['N/A'])[2]}**
+
+    ### ✨ Your "Magic Words" for Marketing
+    Use these exact words in your landing page copy. This is how your customers talk.
+    - `{analysis_result.get('magic_words', ['N/A'])[0]}`
+    - `{analysis_result.get('magic_words', ['N/A'])[1]}`
+    - `{analysis_result.get('magic_words', ['N/A'])[2]}`
+    """
+
+    # The strategic insights
+    strategy_md = f"""
+    ### 🎯 Your Go-to-Market Strategy
+    
+    **Your "Villain":**
+    Position your product as the direct antidote to **{analysis_result.get('target_villain', 'N/A')}**. Your marketing should say, "Tired of [Villain's problem]? We fixed it."
 
-    with gr.Row():
-        url_input = gr.Textbox(label="Enter Competitor URL", placeholder="e.g., notion.so or mailchimp.com", scale=4)
-        submit_btn = gr.Button("Analyze", variant="primary", scale=1)
-
-    with gr.Tabs() as tabs:
-        with gr.TabItem("🧠 AI Summary", id=0):
-            summary_output = gr.Markdown()
-        with gr.TabItem("🔍 On-Page SEO", id=1):
-            seo_output = gr.Markdown()
-        with gr.TabItem("⚙️ Tech Stack", id=2):
-            tech_output = gr.Markdown()
-        with gr.TabItem("📢 Ads & Keywords", id=3):
-            ads_output = gr.Markdown()
+    **Your Unserved "Tribe":**
+    Focus your initial launch on this niche group: **{analysis_result.get('unserved_tribe', 'N/A')}**. They are desperately looking for a solution and will become your first evangelists.
+    """
+
+    yield report_md, strategy_md, "Analysis Complete", gr.Button("Analyze", interactive=True)
+
+# --- Gradio UI ---
+with gr.Blocks(theme=gr.themes.Glass(), css=".gradio-container{max-width: 800px !important}") as demo:
+    gr.Markdown("# 🔮 Pre-Cog: The Market Resonance Engine")
+    gr.Markdown("Stop guessing. Analyze real-time market chatter to see if your idea will succeed *before* you build it.")
+    
+    with gr.Column():
+        niche_input = gr.Textbox(label="Describe Your Product Idea or Niche", placeholder="e.g., 'An AI-powered project management tool for solopreneurs' or 'A better way to learn guitar online'")
+        submit_btn = gr.Button("Analyze Resonance", variant="primary")
+
+    gr.Markdown("---")
     
-    outputs_list = [summary_output, seo_output, tech_output, ads_output, submit_btn]
-    submit_btn.click(fn=competitor_teardown, inputs=[url_input], outputs=outputs_list)
+    with gr.Row():
+        with gr.Column(scale=2):
+            gr.Markdown("##  Resonance Report")
+            report_output = gr.Markdown()
+        with gr.Column(scale=1):
+            gr.Markdown("## Strategy")
+            strategy_output = gr.Markdown()
     
+    status_output = gr.Markdown() # A simple status bar
+
+    submit_btn.click(
+        fn=run_precog_analysis,
+        inputs=[niche_input],
+        outputs=[report_output, strategy_output, status_output, submit_btn]
+    )
+
     gr.Markdown("---")
-    # *** YOUR GUMROAD LINK AND CONVERSION-FOCUSED COPY ***
-    gr.Markdown("""
-    ### You're scratching the surface. Ready to go deeper?
-    The Pro version gives you the unfair advantage:
-    - **✅ Unlimited Reports:** Analyze everyone in your market.
-    - **🔑 Live API Data:** Get real-time Ads & Keyword data for *any* domain.
-    - **📄 PDF Exports:** Create beautiful reports for clients or your team.
-
-    **[🚀 Unlock Gumbo Board Pro Now!](https://gumroadian864.gumroad.com/l/zvgxv)**
-    """)
+    gr.Markdown("### This is a demo of the Pre-Cog Engine. \n The Pro version provides access to live data streams, deeper analysis, and continuous market monitoring. \n **[🚀 Launching Soon - Inquire About Early Access](https://gumroad.com/)**")
 
 if __name__ == "__main__":
     demo.launch()