Update app.py

app.py

@@ -11,86 +11,62 @@ from autogen_agentchat.teams import SelectorGroupChat
 from autogen_ext.models.openai import OpenAIChatCompletionClient
 from autogen_ext.agents.web_surfer import MultimodalWebSurfer
 
-# Enable nested event loops
+# Enable nested event loops for Jupyter compatibility
 nest_asyncio.apply()
 
 class AIShoppingAnalyzer:
     def __init__(self, api_key: str):
         self.api_key = api_key
+        # Set the API key in environment
         os.environ["OPENAI_API_KEY"] = api_key
         self.model_client = OpenAIChatCompletionClient(model="gpt-4o")
         self.termination = MaxMessageTermination(max_messages=20) | TextMentionTermination("TERMINATE")
         
     def create_websurfer(self) -> MultimodalWebSurfer:
         """Initialize the web surfer agent for e-commerce research"""
-        description = (
-            "E-commerce research specialist that:\n"
-            "1. Searches multiple retailers for product options\n"
-            "2. Compares prices and reviews\n"
-            "3. Checks product specifications and availability\n"
-            "4. Analyzes website structure and findability\n"
-            "5. Detects and analyzes structured data (Schema.org, JSON-LD, Microdata)\n"
-            "6. Evaluates product markup and rich snippets\n"
-            "7. Checks for proper semantic HTML and data organization"
-        )
-        
         return MultimodalWebSurfer(
             name="websurfer_agent",
-            description=description,
+            description="""E-commerce research specialist that:
+            1. Searches multiple retailers for product options
+            2. Compares prices and reviews
+            3. Checks product specifications and availability
+            4. Analyzes website structure and findability
+            5. Detects and analyzes structured data (Schema.org, JSON-LD, Microdata)
+            6. Evaluates product markup and rich snippets
+            7. Checks for proper semantic HTML and data organization""",
             model_client=self.model_client,
-            headless=True,
-            browser_type="chromium",
-            playwright_browser_launch_kwargs={
-                "args": [
-                    "--disable-dev-shm-usage",
-                    "--no-sandbox",
-                    "--disable-setuid-sandbox"
-                ]
-            }
+            headless=True
         )
 
     def create_assistant(self) -> AssistantAgent:
         """Initialize the shopping assistant agent"""
-        system_message = (
-            "You are an expert shopping assistant and e-commerce analyst. "
-            "Analyze websites and provide reports in this format:\n\n"
-            "📊 E-COMMERCE ANALYSIS REPORT\n"
-            "============================\n"
-            "Site: {url}\n"
-            "Date: {date}\n\n"
-            "🔍 FINDABILITY SCORE: [★★★★☆]\n"
-            "-----------------------------\n"
-            "• Category Organization\n"
-            "• Navigation Structure\n"
-            "• Filter Systems\n\n"
-            "📝 INFORMATION QUALITY: [★★★★☆]\n"
-            "------------------------------\n"
-            "• Product Details\n"
-            "• Image Quality\n"
-            "• Technical Specs\n"
-            "• Structured Data\n\n"
-            "🔄 NAVIGATION & SEARCH: [★★★★☆]\n"
-            "------------------------------\n"
-            "• Search Features\n"
-            "• User Experience\n"
-            "• Mobile Design\n\n"
-            "💰 PRICING TRANSPARENCY: [★★★★☆]\n"
-            "------------------------------\n"
-            "• Price Display\n"
-            "• Special Offers\n"
-            "• Comparison Tools\n\n"
-            "📈 OVERALL ASSESSMENT\n"
-            "-------------------\n"
-            "[Summary]\n\n"
-            "🔧 TECHNICAL INSIGHTS\n"
-            "-------------------\n"
-            "[Technical Details]"
-        )
-        
         return AssistantAgent(
             name="assistant_agent",
             description="E-commerce shopping advisor and website analyzer",
-            system_message=system_message,
+            system_message="""You are an expert shopping assistant and e-commerce analyst. Your role is to:
+            1. Help find products based on user needs
+            2. Compare prices and features across different sites
+            3. Analyze website usability and product findability
+            4. Evaluate product presentation and information quality
+            5. Assess the overall e-commerce experience
+            6. Analyze structured data implementation:
+               - Check for Schema.org markup
+               - Validate JSON-LD implementation
+               - Evaluate microdata usage
+               - Assess rich snippet potential
+            7. Report on data structure quality:
+               - Product markup completeness
+               - Price and availability markup
+               - Review and rating markup
+               - Inventory status markup
+
+            When working with the websurfer_agent:
+            - Guide their research effectively
+            - Verify the information they find
+            - Analyze how easy it was to find products
+            - Evaluate product page quality
+            - Say 'keep going' if more research is needed
+            - Say 'TERMINATE' only when you have a complete analysis""",
             model_client=self.model_client
         )
 
@@ -101,17 +77,17 @@ class AIShoppingAnalyzer:
             description="An e-commerce site owner looking for AI shopping analysis"
         )
 
-        selector_prompt = (
-            "You are coordinating an e-commerce analysis system. Select the next role from these participants:\n"
-            "- The websurfer_agent searches products and analyzes website structure\n"
-            "- The assistant_agent evaluates findings and makes recommendations\n"
-            "- The user_proxy provides input when needed\n\n"
-            "Return only the role name."
-        )
-
         return SelectorGroupChat(
             participants=[websurfer_agent, assistant_agent, user_proxy],
-            selector_prompt=selector_prompt,
+            selector_prompt="""You are coordinating an e-commerce analysis system. The following roles are available:
+            {roles}
+
+            Given the conversation history {history}, select the next role from {participants}.
+            - The websurfer_agent searches products and analyzes website structure
+            - The assistant_agent evaluates findings and makes recommendations
+            - The user_proxy provides input when needed
+
+            Return only the role name.""",
             model_client=self.model_client,
             termination_condition=self.termination
         )
@@ -123,21 +99,24 @@ class AIShoppingAnalyzer:
         """Run the analysis with proper cleanup"""
         websurfer = None
         try:
-            query = (
-                f"Analyze the e-commerce experience for {website_url} focusing on:\n"
-                f"1. Product findability in the {product_category} category\n"
-                "2. Product information quality\n"
-                "3. Navigation and search functionality\n"
-                "4. Price visibility and comparison features"
-            )
+            # Set up the analysis query
+            query = f"""Analyze the e-commerce experience for {website_url} focusing on:
+            1. Product findability in the {product_category} category
+            2. Product information quality
+            3. Navigation and search functionality
+            4. Price visibility and comparison features"""
             
             if specific_product:
                 query += f"\n5. Detailed analysis of this specific product: {specific_product}"
 
+            # Initialize agents with automatic browser management
             websurfer = self.create_websurfer()
             assistant = self.create_assistant()
+
+            # Create team
             team = self.create_team(websurfer, assistant)
             
+            # Modified execution to handle EOF errors
             try:
                 result = []
                 async for message in team.run_stream(task=query):
@@ -157,8 +136,9 @@ class AIShoppingAnalyzer:
                     await websurfer.close()
                 except Exception as e:
                     print(f"Cleanup error: {str(e)}")
+                    # Continue even if cleanup fails
 
-def create_gradio_interface() -> gr.Blocks:
+def create_gradio_interface() -> gr.Interface:
     """Create the Gradio interface for the AI Shopping Analyzer"""
     
     css = """
@@ -195,6 +175,7 @@ def create_gradio_interface() -> gr.Blocks:
         background-color: #e5e7eb;
     }
     
+    /* Custom styling for form elements */
     .gr-form {
         background: transparent !important;
         border: none !important;
@@ -229,13 +210,17 @@ def create_gradio_interface() -> gr.Blocks:
         background-color: #3a3ab8 !important;
     }
     """
+    
+    def validate_api_key(api_key: str) -> bool:
+        """Validate the OpenAI API key format"""
+        return api_key.startswith("sk-") and len(api_key) > 20
 
     async def run_analysis(api_key: str,
                          website_url: str,
                          product_category: str,
                          specific_product: str) -> str:
         """Handle the analysis submission"""
-        if not api_key.startswith("sk-"):
+        if not validate_api_key(api_key):
             return "Please enter a valid OpenAI API key (should start with 'sk-')"
         
         if not website_url:
@@ -255,72 +240,34 @@ def create_gradio_interface() -> gr.Blocks:
         except Exception as e:
             return f"Error during analysis: {str(e)}"
 
-    with gr.Blocks(css=css) as demo:
-        gr.HTML("""
-            <div class="dashboard-container p-6">
-                <h1 class="text-2xl font-bold mb-2">AI Shopping Agent Analyzer</h1>
-                <p class="text-gray-600 mb-6">Analyze how your e-commerce site performs with AI shoppers</p>
-            </div>
-        """)
-        
-        with gr.Group():
-            api_key = gr.Textbox(
-                label="OpenAI API Key",
-                placeholder="sk-...",
-                type="password",
-                container=True
-            )
-            
-            website_url = gr.Textbox(
-                label="Website URL",
-                placeholder="https://your-store.com",
-                container=True
-            )
-            
-            product_category = gr.Textbox(
-                label="Product Category",
-                placeholder="e.g., Electronics, Clothing, etc.",
-                container=True
-            )
-            
-            specific_product = gr.Textbox(
-                label="Specific Product (Optional)",
-                placeholder="e.g., Blue Widget Model X",
-                container=True
-            )
-            
-            analyze_button = gr.Button(
-                "Analyze Site",
-                variant="primary"
-            )
-            
-            analysis_output = gr.Textbox(
-                label="Analysis Results",
-                lines=20,
-                container=True
-            )
-            
-            analyze_button.click(
-                fn=run_analysis,
-                inputs=[api_key, website_url, product_category, specific_product],
-                outputs=analysis_output
-            )
-    
-    return demo
+    # Create the interface
+    return gr.Interface(
+        fn=run_analysis,
+        inputs=[
+            gr.Textbox(label="OpenAI API Key", placeholder="sk-...", type="password"),
+            gr.Textbox(label="Website URL", placeholder="https://your-store.com"),
+            gr.Textbox(label="Product Category", placeholder="e.g., Electronics, Clothing, etc."),
+            gr.Textbox(label="Specific Product (Optional)", placeholder="e.g., Blue Widget Model X")
+        ],
+        outputs=gr.Textbox(label="Analysis Results", lines=20),
+        title="AI Shopping Agent Analyzer",
+        description="""Analyze how your e-commerce site performs when the shopper is an AI agent.
+        This tool helps you understand your site's effectiveness for AI-powered shopping assistants.""",
+        theme="default",
+        allow_flagging="never"
+    )
 
 if __name__ == "__main__":
-    print("Setting up Playwright...")
+    # Install Playwright browsers and dependencies
+    import subprocess
     try:
-        import subprocess
-        subprocess.run(
-            ["playwright", "install", "chromium"],
-            check=True,
-            capture_output=True,
-            text=True
-        )
+        subprocess.run(["playwright", "install"], check=True)
+        subprocess.run(["playwright", "install-deps"], check=True)
+    except subprocess.CalledProcessError as e:
+        print(f"Error installing Playwright dependencies: {e}")
     except Exception as e:
-        print(f"Warning: Playwright setup encountered an issue: {str(e)}")
-    
-    print("Starting Gradio interface...")
-    demo = create_gradio_interface()
-    demo.launch()
+        print(f"Unexpected error during setup: {e}")
+
+    # Create and launch the interface
+    iface = create_gradio_interface()
+    iface.launch()