Create app.py

app.py

@@ -0,0 +1,172 @@
+import gradio as gr
+import os
+import asyncio
+import nest_asyncio
+from datetime import datetime
+from typing import Optional, Dict, Any
+
+from autogen_agentchat.agents import AssistantAgent, UserProxyAgent
+from autogen_agentchat.conditions import MaxMessageTermination, TextMentionTermination
+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
+nest_asyncio.apply()
+
+class AIShoppingAnalyzer:
+    def __init__(self, api_key: str):
+        self.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"""
+        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""",
+            model_client=self.model_client,
+            headless=True
+        )
+
+    def create_assistant(self) -> AssistantAgent:
+        """Initialize the shopping assistant agent"""
+        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
+
+            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
+        )
+
+    def create_team(self, websurfer_agent: MultimodalWebSurfer, assistant_agent: AssistantAgent) -> SelectorGroupChat:
+        """Set up the team of agents"""
+        user_proxy = UserProxyAgent(
+            name="user_proxy",
+            description="An e-commerce site owner looking for AI shopping analysis"
+        )
+
+        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.""",
+            model_client=self.model_client,
+            termination_condition=self.termination
+        )
+
+    async def analyze_site(self, 
+                         website_url: str, 
+                         product_category: str, 
+                         specific_product: Optional[str] = None) -> str:
+        """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"""
+            
+            if specific_product:
+                query += f"\n5. Detailed analysis of this specific product: {specific_product}"
+
+            # Initialize agents
+            websurfer = self.create_websurfer()
+            assistant = self.create_assistant()
+
+            # Create team
+            team = self.create_team(websurfer, assistant)
+
+            # Run the analysis
+            result = []
+            async for message in team.run_stream(task=query):
+                result.append(message)
+            
+            return "\n".join(result)
+
+        except Exception as e:
+            return f"Analysis error: {str(e)}"
+        finally:
+            if websurfer:
+                try:
+                    await websurfer.close()
+                except Exception as e:
+                    return f"Cleanup error: {str(e)}"
+
+def create_gradio_interface() -> gr.Interface:
+    """Create the Gradio interface for the AI Shopping Analyzer"""
+    
+    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):
+            return "Please enter a valid OpenAI API key (should start with 'sk-')"
+        
+        if not website_url:
+            return "Please enter a website URL"
+            
+        if not product_category:
+            return "Please specify a product category"
+            
+        try:
+            analyzer = AIShoppingAnalyzer(api_key)
+            result = await analyzer.analyze_site(
+                website_url=website_url,
+                product_category=product_category,
+                specific_product=specific_product if specific_product else None
+            )
+            return result
+        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"
+    )
+
+if __name__ == "__main__":
+    # Create and launch the interface
+    iface = create_gradio_interface()
+    iface.launch(share=True)