Add application files

app.py

@@ -243,22 +243,97 @@ async def run_pipeline_gradio(company_names_input: str) -> AsyncGenerator[tuple,
             # Yield updates
             yield chat_history, status, format_workflow_logs(workflow_logs)
 
-        # Pipeline complete
-        final_msg = f"""
+        # Pipeline complete - Retrieve and display all results
+        try:
+            # Get all prospects from the store
+            store_client = mcp_registry.get_store_client()
+            all_prospects = await store_client.get_all_prospects()
+
+            # Display each company's results
+            for prospect in all_prospects:
+                company_name = prospect.get('company', {}).get('name', 'Unknown')
+
+                # Build result card
+                result_content = f"## 🏢 {company_name}\n\n"
+
+                # Company info
+                company = prospect.get('company', {})
+                result_content += f"**Industry:** {company.get('industry', 'N/A')}\n"
+                result_content += f"**Size:** {company.get('employee_count', 'N/A')} employees\n"
+                result_content += f"**Domain:** {company.get('domain', 'N/A')}\n\n"
+
+                # Contacts found
+                contacts = prospect.get('contacts', [])
+                if contacts:
+                    result_content += f"**👥 Contacts Found:** {len(contacts)}\n"
+                    for contact in contacts[:3]:  # Show first 3
+                        result_content += f"- {contact.get('name', 'N/A')} - {contact.get('title', 'N/A')}\n"
+                    if len(contacts) > 3:
+                        result_content += f"- ... and {len(contacts) - 3} more\n"
+                    result_content += "\n"
+
+                # Scoring
+                scores = prospect.get('scores', {})
+                if scores:
+                    result_content += f"**📊 Fit Score:** {scores.get('overall_score', 0):.2f}\n"
+                    result_content += f"- Industry Fit: {scores.get('fit_score', 0):.2f}\n"
+                    result_content += f"- Engagement: {scores.get('engagement_score', 0):.2f}\n"
+                    result_content += f"- Intent: {scores.get('intent_score', 0):.2f}\n\n"
+
+                # Content generated
+                content = prospect.get('content', {})
+                if content:
+                    summary = content.get('summary', '')
+                    if summary:
+                        result_content += f"**📝 Summary:**\n{summary}\n\n"
+
+                    email = content.get('email', {})
+                    if email:
+                        result_content += f"**✉️ Email Draft:**\n"
+                        result_content += f"*Subject:* {email.get('subject', 'N/A')}\n\n"
+                        result_content += f"{email.get('body', 'N/A')}\n\n"
+
+                # Email thread
+                thread_id = prospect.get('thread_id')
+                if thread_id:
+                    result_content += f"**📧 Email Thread:** {thread_id}\n\n"
+
+                # Handoff packet
+                handoff = prospect.get('handoff_packet', {})
+                if handoff:
+                    result_content += f"**📋 Handoff Status:** Ready for sales team\n"
+
+                # Add to chat
+                chat_history.append({
+                    "role": "assistant",
+                    "content": result_content
+                })
+
+            # Final summary
+            final_msg = f"""
 ✅ **Pipeline Execution Complete!**
 
 **Summary:**
-- Companies Processed: {len(pipeline_state['company_outputs'])}
+- Companies Processed: {len(all_prospects)}
 - Total Events: {len(workflow_logs)}
 - MCP Interactions: {sum(1 for log in workflow_logs if 'MCP' in log['action'])}
 - Agents Run: {len(set(log['agent'] for log in workflow_logs))}
+- Contacts Discovered: {sum(len(p.get('contacts', [])) for p in all_prospects)}
 
 All prospects have been enriched, scored, and prepared for outreach through the autonomous agent system.
 """
-        chat_history.append({
-            "role": "assistant",
-            "content": final_msg
-        })
+            chat_history.append({
+                "role": "assistant",
+                "content": final_msg
+            })
+
+        except Exception as e:
+            error_msg = f"⚠️ Error retrieving results: {str(e)}\n\nPipeline completed but could not display all results."
+            chat_history.append({
+                "role": "assistant",
+                "content": error_msg
+            })
+
         yield chat_history, "✅ Pipeline Complete", format_workflow_logs(workflow_logs)
 
     except Exception as e: