Update app.py

app.py

@@ -11,62 +11,85 @@ 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 for Jupyter compatibility
+# Enable nested event loops
 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="""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""",
+            description=description,
             model_client=self.model_client,
-            headless=True
+            headless=True,
+            browser_kwargs={
+                "args": [
+                    "--disable-dev-shm-usage",
+                    "--no-sandbox",
+                    "--disable-setuid-sandbox"
+                ]
+            }
         )
 
     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="""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""",
+            system_message=system_message,
             model_client=self.model_client
         )
 
@@ -77,17 +100,17 @@ 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="""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.""",
+            selector_prompt=selector_prompt,
             model_client=self.model_client,
             termination_condition=self.termination
         )
@@ -99,24 +122,21 @@ class AIShoppingAnalyzer:
         """Run the analysis with proper cleanup"""
         websurfer = None
         try:
-            # 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"""
+            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"
+            )
             
             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):
@@ -136,9 +156,8 @@ 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.Interface:
+def create_gradio_interface() -> gr.Blocks:
     """Create the Gradio interface for the AI Shopping Analyzer"""
     
     css = """
@@ -175,7 +194,6 @@ def create_gradio_interface() -> gr.Interface:
         background-color: #e5e7eb;
     }
     
-    /* Custom styling for form elements */
     .gr-form {
         background: transparent !important;
         border: none !important;
@@ -209,18 +227,63 @@ def create_gradio_interface() -> gr.Interface:
     .gr-button:hover {
         background-color: #3a3ab8 !important;
     }
+
+    .analysis-output {
+        background: white;
+        padding: 20px;
+        border-radius: 8px;
+        border: 1px solid #e0e5ff;
+        margin-top: 20px;
+    }
+
+    .analysis-output h1 {
+        font-size: 1.5em;
+        font-weight: bold;
+        margin-bottom: 1em;
+    }
+
+    .analysis-output h2 {
+        font-size: 1.25em;
+        font-weight: 600;
+        margin-top: 1.5em;
+        margin-bottom: 0.5em;
+    }
+
+    .analysis-output h3 {
+        font-size: 1.1em;
+        font-weight: 600;
+        margin-top: 1em;
+        margin-bottom: 0.5em;
+    }
+
+    .analysis-output ul {
+        margin-left: 1.5em;
+        margin-bottom: 1em;
+    }
+
+    .analysis-output li {
+        margin-bottom: 0.5em;
+    }
+
+    .analysis-output p {
+        margin-bottom: 1em;
+        line-height: 1.6;
+    }
+
+    .analysis-output code {
+        background: #f3f4f6;
+        padding: 0.2em 0.4em;
+        border-radius: 4px;
+        font-size: 0.9em;
+    }
     """
-    
-    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 validate_api_key(api_key):
+        if not api_key.startswith("sk-"):
             return "Please enter a valid OpenAI API key (should start with 'sk-')"
         
         if not website_url:
@@ -240,34 +303,72 @@ def create_gradio_interface() -> gr.Interface:
         except Exception as e:
             return f"Error during analysis: {str(e)}"
 
-    # 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"
-    )
+    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.Markdown(
+                label="Analysis Results",
+                value="Results will appear here...",
+                elem_classes="analysis-output"
+            )
+            
+            analyze_button.click(
+                fn=run_analysis,
+                inputs=[api_key, website_url, product_category, specific_product],
+                outputs=analysis_output
+            )
+    
+    return demo
 
 if __name__ == "__main__":
-    # Install Playwright browsers and dependencies
-    import subprocess
+    print("Setting up Playwright...")
     try:
-        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}")
+        import subprocess
+        subprocess.run(
+            ["playwright", "install", "chromium"],
+            check=True,
+            capture_output=True,
+            text=True
+        )
     except Exception as e:
-        print(f"Unexpected error during setup: {e}")
-
-    # Create and launch the interface
-    iface = create_gradio_interface()
-    iface.launch()
+        print(f"Warning: Playwright setup encountered an issue: {str(e)}")
+    
+    print("Starting Gradio interface...")
+    demo = create_gradio_interface()
+    demo.launch()