Delete geo_agent.py

geo_agent.py

@@ -1,114 +0,0 @@
-import requests
-from bs4 import BeautifulSoup
-from openai import OpenAI
-
-client = OpenAI(api_key="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")
-
-def scrape_website(url):
-    try:
-        headers = {'User-Agent': 'Mozilla/5.0 (compatible; GEOAgent/1.0)'}
-        response = requests.get(url, headers=headers, timeout=10)
-        response.raise_for_status() 
-        
-        soup = BeautifulSoup(response.content, 'html.parser')
-        
-        title = soup.find('title').text if soup.find('title') else 'No Title Found'
-        meta_desc = soup.find('meta', attrs={'name': 'description'})
-        meta_desc_content = meta_desc['content'] if meta_desc and meta_desc.get('content') else 'No Meta Description Found'
-        
-        main_content_tags = ['p', 'h1', 'h2', 'h3', 'li', 'td']
-        
-        main_content = []
-        for tag in soup.find_all(main_content_tags):
-            text = tag.get_text(strip=True)
-            if text and len(text) > 15: 
-                main_content.append(f"{tag.name}: {text}")
-
-        analysis_data = {
-            "URL": url,
-            "Title": title,
-            "Meta Description": meta_desc_content,
-            "Full Content Length": len("\n".join(main_content))
-        }
-
-        full_content_string = "\n".join(main_content)
-        
-        return analysis_data, full_content_string[:10000]
-
-    except requests.exceptions.RequestException as e:
-        return {"Error": f"Could not access the website: {e}"}, ""
-
-def run_agent_analysis(url, scraped_data_dict, full_content):
-    
-    system_prompt = f"""
-You are the world's leading Generative Engine Optimization (GEO) Expert Agent. Your task is to analyze the provided website content snippet and assign a GEO Score out of 10. The score must be based on the content's readiness to be cited, summarized, and trusted by advanced AI models (like yourself).
-
-**SCORING CRITERIA (Total 10.0 Points):**
-
-1.  **Citation Readiness (3.0 Points):**
-    * *Goal:* Can an AI easily extract a direct, quotable answer?
-    * *Check:* Are facts, statistics, and definitions stated concisely, often in the first 150 words? Is the language clear and non-ambiguous?
-2.  **Content Structure & Entity Optimization (2.5 Points):**
-    * *Goal:* Is the information logically structured for AI chunking and entity recognition?
-    * *Check:* Are headings (H1, H2, H3) descriptive and hierarchical? Is the main topic entity (brand, person, product) consistently named and defined?
-3.  **E-E-A-T & Trust Signals (2.5 Points):**
-    * *Goal:* Does the content demonstrate Experience, Expertise, Authoritativeness, and Trustworthiness?
-    * *Check:* Is the content recent? Are clear author/publisher signals present (even if scraped data is limited)? Does the tone sound expert and trustworthy?
-4.  **Technical & Schema Potential (2.0 Points):**
-    * *Goal:* Is the metadata and on-page structure compliant for rich AI results?
-    * *Check:* Is the Title compelling and descriptive? Is the Meta Description a good, concise summary? (Assume basic Schema is absent if not explicitly found).
-
-**INPUT DATA:**
----
-**URL:** {url}
-**Title:** {scraped_data_dict.get('Title', 'N/A')}
-**Meta Description:** {scraped_data_dict.get('Meta Description', 'N/A')}
-**Content Snippet (Max 10k chars):**
-{full_content}
----
-
-**YOUR TASK OUTPUT MUST BE IN THE FOLLOWING FORMAT (Do not include any other text or commentary outside this structure):**
-
-**GEO SCORE:** [X.X/10.0]
-
-**PILLAR SCORES:**
-* Citation Readiness: [X.X/3.0]
-* Content Structure & Entity Optimization: [X.X/2.5]
-* E-E-A-T & Trust Signals: [X.X/2.5]
-* Technical & Schema Potential: [X.X/2.0]
-
-**DETAILED SUGGESTIONS (Top 3 Priority Improvements):**
-1.  **[Pillar Name]:** Actionable step to improve the score.
-2.  **[Pillar Name]:** Actionable step to improve the score.
-3.  **[Pillar Name]:** Actionable step to improve the score.
-"""
-
-    try:
-        completion = client.chat.completions.create(
-            model="gpt-4o-mini",
-            messages=[
-                {"role": "system", "content": system_prompt}
-            ]
-        )
-        return completion.choices[0].message.content
-        
-    except Exception as e:
-        return f"An error occurred during AI processing: {e}"
-
-if __name__ == "__main__":
-    target_url = input("Enter the URL of the website to analyze (e.g., https://example.com): ")
-    
-    analysis_data, full_content_string = scrape_website(target_url)
-    
-    if "Error" in analysis_data:
-        print(analysis_data["Error"])
-    else:
-        print(f"\n--- Running GEO Agent Analysis for: {target_url} ---")
-        
-        ai_response = run_agent_analysis(target_url, analysis_data, full_content_string)
-        
-        print("\n" + "="*50)
-        print("           GEO AGENT AUDIT COMPLETE")
-        print("="*50 + "\n")
-        print(ai_response)
-        print("\n" + "="*50)