Complete Execution Output (JSON):
{
"case_context_agent": {
"agent_type": "assistant",
"ai_response": "I need to extract case information, but I notice that the case number, processing type, and customer email are all marked as \"UNRESOLVED\". Without these critical pieces of information, I cannot proceed with extracting the case context.\n\nTo help you properly, I need:\n\n1. The actual case number that was extracted in Phase 1\n2. The customer\u0027s email content including sender information, subject, and body\n\nCould you please provide the actual case number and customer email content so I can extract the necessary information and provide the structured output required?",
"execution_details": {
"actual_result": {
"agent_type": "assistant",
"execution_details": {
"agent_type": "assistant",
"input_length": 255,
"model": "anthropic/claude-3.7-sonnet",
"output_length": 566,
"provider": "openrouter",
"system_message": "# Case Context Agent - Phase 2: Extract Case Information\n\nYou are responsible for extracting case information and setting up context for the workflow.\n\n## CRITICAL: YOU DO NOT CREATE NEW CASES - CASES ARE ALREADY CREATED IN PHASE 1\nYour job is to extract information from existing cases and customer emails.\n\n## PROCESS\n\n**Step 1: Extract Case Number from Previous Task**\nYou will receive a case number from the case_number_extractor task.\nUse this case number directly - it has already been validated and extracted.\n\n**Step 2: Try to Retrieve Case Details**\nUse get_case() with the extracted case number to get case details\n\n**Step 3: Extract Customer Information**\nFrom the customer email, extract:\n- contact_email: Extract ONLY the email address from the sender field\n- subject: Extract the exact subject line\n- email_body: Use the complete content of the email\n- customer_name: Extract name from sender field\n- description: Create a concise 1-2 sentence summary\n\n**Step 4: Provide Structured Output**\nAlways provide your response in this EXACT format:\n\n```\n## CASE CONTEXT ANALYSIS\n\n**EXTRACTED_CASE_NUMBER**: [case_number_from_extractor]\n**CUSTOMER_EMAIL**: [email_address]\n**CUSTOMER_NAME**: [extracted_from_sender]\n**SUBJECT**: [email_subject]\n**REQUEST_SUMMARY**: [brief_description]\n**CASE_STATUS**: [from_get_case_if_successful_or_N/A]\n\n## CASE DETAILS\n[Any additional case information from get_case, or note if case retrieval failed]\n\n## EMAIL CONTENT\n[Complete email body content]\n```\n\n## IMPORTANT RULES\n1. ALWAYS use the case number provided by the case_number_extractor\n2. Use the EXACT case number format (digits only, no prefixes)\n3. If get_case fails, note it but continue with the extracted case number\n4. NEVER create new cases - work with existing case from Phase 1\n5. ALWAYS include the structured output format above\n"
},
"input_format": "text",
"model_client_id": "openrouter_claude_sonnet",
"output": "I need to extract case information, but I notice that the case number, processing type, and customer email are all marked as \"UNRESOLVED\". Without these critical pieces of information, I cannot proceed with extracting the case context.\n\nTo help you properly, I need:\n\n1. The actual case number that was extracted in Phase 1\n2. The customer\u0027s email content including sender information, subject, and body\n\nCould you please provide the actual case number and customer email content so I can extract the necessary information and provide the structured output required?\n__OUTPUTS__ {\"ai_response\": \"I need to extract case information, but I notice that the case number, processing type, and customer email are all marked as \\\"UNRESOLVED\\\". Without these critical pieces of information, I cannot proceed with extracting the case context.\\n\\nTo help you properly, I need:\\n\\n1. The actual case number that was extracted in Phase 1\\n2. The customer\u0027s email content including sender information, subject, and body\\n\\nCould you please provide the actual case number and customer email content so I can extract the necessary information and provide the structured output required?\", \"model_client_id\": \"openrouter_claude_sonnet\", \"agent_type\": \"assistant\", \"model\": \"anthropic/claude-3.7-sonnet\", \"provider\": \"openrouter\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 1600, \"completion_tokens\": 117, \"total_tokens\": 1717, \"estimated_cost\": {\"amount\": 0.05502, \"currency\": \"USD\"}, \"model\": \"anthropic/claude-3.7-sonnet\", \"provider\": \"openrouter\"}}",
"output_format": "text",
"return_code": 0,
"status": "completed",
"stderr": "",
"token_usage": {
"completion_tokens": 117,
"estimated_cost": {
"amount": 0.05502,
"currency": "USD"
},
"model": "anthropic/claude-3.7-sonnet",
"prompt_tokens": 1600,
"provider": "openrouter",
"total_tokens": 1717
}
},
"duration_seconds": 6.762386,
"end_time": "2025-08-25T05:35:27.621485",
"message_sent": true,
"start_time": "2025-08-25T05:35:20.859099",
"timestamp": "2025-08-25T05:35:27.621485",
"worker_executed": true,
"workers_notified": true
},
"model": "anthropic/claude-3.7-sonnet",
"model_client_id": "openrouter_claude_sonnet",
"output": "I need to extract case information, but I notice that the case number, processing type, and customer email are all marked as \"UNRESOLVED\". Without these critical pieces of information, I cannot proceed with extracting the case context.\n\nTo help you properly, I need:\n\n1. The actual case number that was extracted in Phase 1\n2. The customer\u0027s email content including sender information, subject, and body\n\nCould you please provide the actual case number and customer email content so I can extract the necessary information and provide the structured output required?\n__OUTPUTS__ {\"ai_response\": \"I need to extract case information, but I notice that the case number, processing type, and customer email are all marked as \\\"UNRESOLVED\\\". Without these critical pieces of information, I cannot proceed with extracting the case context.\\n\\nTo help you properly, I need:\\n\\n1. The actual case number that was extracted in Phase 1\\n2. The customer\u0027s email content including sender information, subject, and body\\n\\nCould you please provide the actual case number and customer email content so I can extract the necessary information and provide the structured output required?\", \"model_client_id\": \"openrouter_claude_sonnet\", \"agent_type\": \"assistant\", \"model\": \"anthropic/claude-3.7-sonnet\", \"provider\": \"openrouter\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 1600, \"completion_tokens\": 117, \"total_tokens\": 1717, \"estimated_cost\": {\"amount\": 0.05502, \"currency\": \"USD\"}, \"model\": \"anthropic/claude-3.7-sonnet\", \"provider\": \"openrouter\"}}",
"provider": "openrouter",
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "case_context_agent",
"token_usage": {
"completion_tokens": 117,
"estimated_cost": {
"amount": 0.05502,
"currency": "USD"
},
"model": "anthropic/claude-3.7-sonnet",
"prompt_tokens": 1600,
"provider": "openrouter",
"total_tokens": 1717
}
},
"case_number_extractor": {
"error": "Python script failed with return code 1: Traceback (most recent call last):\n File \"/tmp/tmplmvjg_lz.py\", line 16, in \u003cmodule\u003e\n orchestrator_result = orchestrator_output[\u0027ai_response\u0027].strip()\n ~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^\nKeyError: \u0027ai_response\u0027\n",
"execution_details": {
"failed": true,
"message_sent": true,
"worker_executed": true,
"workers_notified": true
},
"output": "Task failed: Python script failed with return code 1: Traceback (most recent call last):\n File \"/tmp/tmplmvjg_lz.py\", line 16, in \u003cmodule\u003e\n orchestrator_result = orchestrator_output[\u0027ai_response\u0027].strip()\n ~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^\nKeyError: \u0027ai_response\u0027\n",
"status": "FAILED",
"task_id": "case_number_extractor"
},
"case_orchestrator": {
"error": "Error code: 429 - {\u0027error\u0027: {\u0027message\u0027: \u0027You exceeded your current quota, please check your plan and billing details. For more information on this error, read the docs: https://platform.openai.com/docs/guides/error-codes/api-errors.\u0027, \u0027type\u0027: \u0027insufficient_quota\u0027, \u0027param\u0027: None, \u0027code\u0027: \u0027insufficient_quota\u0027}}",
"execution_details": {
"failed": true,
"message_sent": true,
"worker_executed": true,
"workers_notified": true
},
"output": "Task failed: Error code: 429 - {\u0027error\u0027: {\u0027message\u0027: \u0027You exceeded your current quota, please check your plan and billing details. For more information on this error, read the docs: https://platform.openai.com/docs/guides/error-codes/api-errors.\u0027, \u0027type\u0027: \u0027insufficient_quota\u0027, \u0027param\u0027: None, \u0027code\u0027: \u0027insufficient_quota\u0027}}",
"status": "FAILED",
"task_id": "case_orchestrator"
},
"classification_agent": {
"error": "Error code: 429 - {\u0027error\u0027: {\u0027message\u0027: \u0027You exceeded your current quota, please check your plan and billing details. For more information on this error, read the docs: https://platform.openai.com/docs/guides/error-codes/api-errors.\u0027, \u0027type\u0027: \u0027insufficient_quota\u0027, \u0027param\u0027: None, \u0027code\u0027: \u0027insufficient_quota\u0027}}",
"execution_details": {
"failed": true,
"message_sent": true,
"worker_executed": true,
"workers_notified": true
},
"output": "Task failed: Error code: 429 - {\u0027error\u0027: {\u0027message\u0027: \u0027You exceeded your current quota, please check your plan and billing details. For more information on this error, read the docs: https://platform.openai.com/docs/guides/error-codes/api-errors.\u0027, \u0027type\u0027: \u0027insufficient_quota\u0027, \u0027param\u0027: None, \u0027code\u0027: \u0027insufficient_quota\u0027}}",
"status": "FAILED",
"task_id": "classification_agent"
},
"email_generator_agent": {
"agent_type": "assistant",
"ai_response": "I understand you\u0027re trying to generate a final personalized email, but I notice there\u0027s an issue with the data provided. The template router output indicates that the case information is marked as \"UNRESOLVED\", which means we don\u0027t have the actual case data to work with.\n\nTo generate a personalized email, I need specific information that\u0027s currently missing:\n- A valid case number (currently showing as \"UNRESOLVED_case_number_extractor.case_number\")\n- Customer details (name, email)\n- The nature of the customer\u0027s inquiry\n- Template data structure\n\nWithout this information, I cannot properly personalize an email template. In a normal workflow, I would:\n1. Extract the case number\n2. Use that to retrieve the template data\n3. Personalize the template with customer information\n4. Update the case with the email content\n\nCould you please provide the actual case number and template data so I can generate a properly personalized email? Alternatively, if you have the complete template router output with the TEMPLATE_DATA_FOR_EMAIL_GENERATOR section, that would contain all the information I need.",
"execution_details": {
"actual_result": {
"agent_type": "assistant",
"execution_details": {
"agent_type": "assistant",
"input_length": 1736,
"model": "anthropic/claude-3.7-sonnet",
"output_length": 1100,
"provider": "openrouter",
"system_message": "# Email Generator Agent - Final Email Generation\n\nYou generate the final personalized email that will be sent to the customer.\n\n## CRITICAL: USE EXTRACTED CASE NUMBER\nYou will receive the case number from the case_number_extractor task.\nUse this case number consistently throughout.\n\n**Step 1: Extract Required Information**\nFrom the template router output and case number extractor:\n- Case number (from case_number_extractor)\n- Template data structure from template router\n- Customer information from case context\n- Personalization details\n\n**Step 2: Extract Template Data**\nFrom the \"TEMPLATE_DATA_FOR_EMAIL_GENERATOR:\" section, extract:\n- template_id\n- customer_name \n- customer_email\n- recommended_template (resolved/followup/rejected)\n- All template variants (resolved, followup, rejected)\n- signature\n- is_approved\n\n**Step 3: Personalize the Recommended Template**\nBased on the recommended_template field:\n- If \"followup\": Use followup_template\n- If \"resolved\": Use resolved_template \n- If \"rejected\": Use rejected_template\n\nReplace ALL placeholders in the selected template:\n- [Customer Name] \u2192 actual customer name\n- [Case Number] \u2192 actual case number from case_number_extractor\n- [Specific Details] \u2192 case-specific information from context\n- [Delivery Date] \u2192 appropriate date if applicable\n- [Compensation Detail] \u2192 appropriate compensation if applicable\n- [Expected Timeline] \u2192 appropriate timeframe\n\n**Step 4: Format Email Content**\nCreate the email_content in this EXACT structure:\n```json\n{\n \"templates\": [\n {\n \"id\": \"resolved_template_id\",\n \"subject\": \"Personalized subject with actual case number ${case_number_extractor.case_number}\",\n \"type\": \"resolved\",\n \"content\": \"Complete personalized email body with signature\"\n },\n {\n \"id\": \"followup_template_id\", \n \"subject\": \"Personalized subject with actual case number ${case_number_extractor.case_number}\",\n \"type\": \"followup\",\n \"content\": \"Complete personalized email body with signature\"\n },\n {\n \"id\": \"rejected_template_id\", \n \"subject\": \"Personalized subject with actual case number ${case_number_extractor.case_number}\", \n \"type\": \"rejected\",\n \"content\": \"Complete personalized email body with signature\"\n }\n ]\n}\n```\n\n**Step 5: Update Case with Email Content**\nCall update_email_content tool with:\n- case_number: actual case number from case_number_extractor\n- email_content: the personalized template data from Step 4\n- template_id: the template ID from Step 2\n- status: \"Pending\" if is_approved=true, \"Template in review\" if is_approved=false\n\n**Step 6: Return Success**\nIf update successful, return: \"EMAIL_CONTENT_UPDATED_SUCCESSFULLY\"\nIf update fails, explain the issue but still show the personalized email content.\n\n## IMPORTANT RULES\n- ALWAYS use the case number from case_number_extractor\n- Replace ALL placeholders with real information\n- Include complete email body with signature\n- Format as valid JSON structure\n- Use the template_id in the tool call\n"
},
"input_format": "text",
"model_client_id": "openrouter_claude_sonnet",
"output": "I understand you\u0027re trying to generate a final personalized email, but I notice there\u0027s an issue with the data provided. The template router output indicates that the case information is marked as \"UNRESOLVED\", which means we don\u0027t have the actual case data to work with.\n\nTo generate a personalized email, I need specific information that\u0027s currently missing:\n- A valid case number (currently showing as \"UNRESOLVED_case_number_extractor.case_number\")\n- Customer details (name, email)\n- The nature of the customer\u0027s inquiry\n- Template data structure\n\nWithout this information, I cannot properly personalize an email template. In a normal workflow, I would:\n1. Extract the case number\n2. Use that to retrieve the template data\n3. Personalize the template with customer information\n4. Update the case with the email content\n\nCould you please provide the actual case number and template data so I can generate a properly personalized email? Alternatively, if you have the complete template router output with the TEMPLATE_DATA_FOR_EMAIL_GENERATOR section, that would contain all the information I need.\n__OUTPUTS__ {\"ai_response\": \"I understand you\u0027re trying to generate a final personalized email, but I notice there\u0027s an issue with the data provided. The template router output indicates that the case information is marked as \\\"UNRESOLVED\\\", which means we don\u0027t have the actual case data to work with.\\n\\nTo generate a personalized email, I need specific information that\u0027s currently missing:\\n- A valid case number (currently showing as \\\"UNRESOLVED_case_number_extractor.case_number\\\")\\n- Customer details (name, email)\\n- The nature of the customer\u0027s inquiry\\n- Template data structure\\n\\nWithout this information, I cannot properly personalize an email template. In a normal workflow, I would:\\n1. Extract the case number\\n2. Use that to retrieve the template data\\n3. Personalize the template with customer information\\n4. Update the case with the email content\\n\\nCould you please provide the actual case number and template data so I can generate a properly personalized email? Alternatively, if you have the complete template router output with the TEMPLATE_DATA_FOR_EMAIL_GENERATOR section, that would contain all the information I need.\", \"model_client_id\": \"openrouter_claude_sonnet\", \"agent_type\": \"assistant\", \"model\": \"anthropic/claude-3.7-sonnet\", \"provider\": \"openrouter\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 1989, \"completion_tokens\": 244, \"total_tokens\": 2233, \"estimated_cost\": {\"amount\": 0.07431, \"currency\": \"USD\"}, \"model\": \"anthropic/claude-3.7-sonnet\", \"provider\": \"openrouter\"}}",
"output_format": "text",
"return_code": 0,
"status": "completed",
"stderr": "",
"token_usage": {
"completion_tokens": 244,
"estimated_cost": {
"amount": 0.07431,
"currency": "USD"
},
"model": "anthropic/claude-3.7-sonnet",
"prompt_tokens": 1989,
"provider": "openrouter",
"total_tokens": 2233
}
},
"duration_seconds": 8.653388,
"end_time": "2025-08-25T05:38:54.857497",
"message_sent": true,
"start_time": "2025-08-25T05:38:46.204109",
"timestamp": "2025-08-25T05:38:54.857497",
"worker_executed": true,
"workers_notified": true
},
"model": "anthropic/claude-3.7-sonnet",
"model_client_id": "openrouter_claude_sonnet",
"output": "I understand you\u0027re trying to generate a final personalized email, but I notice there\u0027s an issue with the data provided. The template router output indicates that the case information is marked as \"UNRESOLVED\", which means we don\u0027t have the actual case data to work with.\n\nTo generate a personalized email, I need specific information that\u0027s currently missing:\n- A valid case number (currently showing as \"UNRESOLVED_case_number_extractor.case_number\")\n- Customer details (name, email)\n- The nature of the customer\u0027s inquiry\n- Template data structure\n\nWithout this information, I cannot properly personalize an email template. In a normal workflow, I would:\n1. Extract the case number\n2. Use that to retrieve the template data\n3. Personalize the template with customer information\n4. Update the case with the email content\n\nCould you please provide the actual case number and template data so I can generate a properly personalized email? Alternatively, if you have the complete template router output with the TEMPLATE_DATA_FOR_EMAIL_GENERATOR section, that would contain all the information I need.\n__OUTPUTS__ {\"ai_response\": \"I understand you\u0027re trying to generate a final personalized email, but I notice there\u0027s an issue with the data provided. The template router output indicates that the case information is marked as \\\"UNRESOLVED\\\", which means we don\u0027t have the actual case data to work with.\\n\\nTo generate a personalized email, I need specific information that\u0027s currently missing:\\n- A valid case number (currently showing as \\\"UNRESOLVED_case_number_extractor.case_number\\\")\\n- Customer details (name, email)\\n- The nature of the customer\u0027s inquiry\\n- Template data structure\\n\\nWithout this information, I cannot properly personalize an email template. In a normal workflow, I would:\\n1. Extract the case number\\n2. Use that to retrieve the template data\\n3. Personalize the template with customer information\\n4. Update the case with the email content\\n\\nCould you please provide the actual case number and template data so I can generate a properly personalized email? Alternatively, if you have the complete template router output with the TEMPLATE_DATA_FOR_EMAIL_GENERATOR section, that would contain all the information I need.\", \"model_client_id\": \"openrouter_claude_sonnet\", \"agent_type\": \"assistant\", \"model\": \"anthropic/claude-3.7-sonnet\", \"provider\": \"openrouter\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 1989, \"completion_tokens\": 244, \"total_tokens\": 2233, \"estimated_cost\": {\"amount\": 0.07431, \"currency\": \"USD\"}, \"model\": \"anthropic/claude-3.7-sonnet\", \"provider\": \"openrouter\"}}",
"provider": "openrouter",
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "email_generator_agent",
"token_usage": {
"completion_tokens": 244,
"estimated_cost": {
"amount": 0.07431,
"currency": "USD"
},
"model": "anthropic/claude-3.7-sonnet",
"prompt_tokens": 1989,
"provider": "openrouter",
"total_tokens": 2233
}
},
"execution_summary": {
"completed_tasks": 5,
"dependencies_detected": false,
"end_time": "2025-08-25T05:38:54.884969",
"execution_mode": "distributed",
"start_time": "2025-08-25T05:29:18.807191",
"total_tasks": 9
},
"phase_router": {
"all_conditions_checked": [
{
"condition": "contains(${case_orchestrator.ai_response}, \"DUPLICATE_PROCESSED\") || contains(${case_number_extractor.processing_type}, \"duplicate\")",
"name": "duplicate_workflow",
"result": false,
"route": "duplicate_end"
},
{
"condition": "contains(${case_orchestrator.ai_response}, \"NEW_CASE_CREATED\") || contains(${case_orchestrator.ai_response}, \"CASE_RETRIEVED_FOR_UPDATE\")",
"name": "analysis_workflow",
"result": false,
"route": "continue_analysis"
}
],
"duration_seconds": 0.000603,
"ended_at": "2025-08-25T05:35:20.733101",
"evaluation_details": {},
"execution_details": {
"actual_result": {
"output": "Route selected: continue_analysis\n__OUTPUTS__ {\"router_type\": \"condition\", \"selected_route\": \"continue_analysis\", \"route_reason\": \"no_conditions_matched\", \"evaluation_details\": {}, \"all_conditions_checked\": [{\"name\": \"duplicate_workflow\", \"condition\": \"contains(${case_orchestrator.ai_response}, \\\"DUPLICATE_PROCESSED\\\") || contains(${case_number_extractor.processing_type}, \\\"duplicate\\\")\", \"result\": false, \"route\": \"duplicate_end\"}, {\"name\": \"analysis_workflow\", \"condition\": \"contains(${case_orchestrator.ai_response}, \\\"NEW_CASE_CREATED\\\") || contains(${case_orchestrator.ai_response}, \\\"CASE_RETRIEVED_FOR_UPDATE\\\")\", \"result\": false, \"route\": \"continue_analysis\"}], \"duration_seconds\": 0.000603, \"started_at\": \"2025-08-25T05:35:20.732498\", \"ended_at\": \"2025-08-25T05:35:20.733101\"}",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 0.225097,
"end_time": "2025-08-25T05:35:20.825016",
"message_sent": true,
"start_time": "2025-08-25T05:35:20.599919",
"timestamp": "2025-08-25T05:35:20.825016",
"worker_executed": true,
"workers_notified": true
},
"output": "Route selected: continue_analysis\n__OUTPUTS__ {\"router_type\": \"condition\", \"selected_route\": \"continue_analysis\", \"route_reason\": \"no_conditions_matched\", \"evaluation_details\": {}, \"all_conditions_checked\": [{\"name\": \"duplicate_workflow\", \"condition\": \"contains(${case_orchestrator.ai_response}, \\\"DUPLICATE_PROCESSED\\\") || contains(${case_number_extractor.processing_type}, \\\"duplicate\\\")\", \"result\": false, \"route\": \"duplicate_end\"}, {\"name\": \"analysis_workflow\", \"condition\": \"contains(${case_orchestrator.ai_response}, \\\"NEW_CASE_CREATED\\\") || contains(${case_orchestrator.ai_response}, \\\"CASE_RETRIEVED_FOR_UPDATE\\\")\", \"result\": false, \"route\": \"continue_analysis\"}], \"duration_seconds\": 0.000603, \"started_at\": \"2025-08-25T05:35:20.732498\", \"ended_at\": \"2025-08-25T05:35:20.733101\"}",
"return_code": 0,
"route_reason": "no_conditions_matched",
"router_type": "condition",
"selected_route": "continue_analysis",
"started_at": "2025-08-25T05:35:20.732498",
"status": "completed",
"stderr": "",
"task_id": "phase_router"
},
"sentiment_analysis_agent": {
"error": "Error code: 429 - {\u0027error\u0027: {\u0027message\u0027: \u0027You exceeded your current quota, please check your plan and billing details. For more information on this error, read the docs: https://platform.openai.com/docs/guides/error-codes/api-errors.\u0027, \u0027type\u0027: \u0027insufficient_quota\u0027, \u0027param\u0027: None, \u0027code\u0027: \u0027insufficient_quota\u0027}}",
"execution_details": {
"failed": true,
"message_sent": true,
"worker_executed": true,
"workers_notified": true
},
"output": "Task failed: Error code: 429 - {\u0027error\u0027: {\u0027message\u0027: \u0027You exceeded your current quota, please check your plan and billing details. For more information on this error, read the docs: https://platform.openai.com/docs/guides/error-codes/api-errors.\u0027, \u0027type\u0027: \u0027insufficient_quota\u0027, \u0027param\u0027: None, \u0027code\u0027: \u0027insufficient_quota\u0027}}",
"status": "FAILED",
"task_id": "sentiment_analysis_agent"
},
"status": "FAILED",
"summary_agent": {
"agent_type": "assistant",
"ai_response": "I\u0027ll create a comprehensive analysis and AI summary based on the information provided. However, I notice that the case number, processing type, case context, classification, sentiment analysis, and original email are all marked as \"UNRESOLVED\". This means I don\u0027t have access to the actual data from the previous agents.\n\nTo proceed properly, I need to access the actual outputs from the previous agents. Without this information, I cannot create an accurate analysis or update the case with the required details.\n\nCould you please provide the actual outputs from the previous agents? Specifically, I need:\n1. The case number from case_number_extractor\n2. The processing type from case_number_extractor\n3. The case context from case_context_agent\n4. The classification results from classification_agent\n5. The sentiment analysis from sentiment_analysis_agent\n6. The original customer email\n\nOnce I have this information, I can create a comprehensive analysis and properly update the case with the AI summary.",
"execution_details": {
"actual_result": {
"agent_type": "assistant",
"execution_details": {
"agent_type": "assistant",
"input_length": 456,
"model": "anthropic/claude-3.7-sonnet",
"output_length": 1008,
"provider": "openrouter",
"system_message": "# Summary Agent - Phase 2: Comprehensive Case Analysis with AI Summary Creation\n\nCreate a comprehensive case analysis and ENSURE the AI Summary is properly created and stored.\n\n## CRITICAL: PROPER DATA ACCESS FROM PREVIOUS AGENTS\nYou will receive outputs from previous agents. Access them properly using these patterns:\n- Case context information from case_context_agent\n- Classification results from classification_agent \n- Sentiment analysis from sentiment_analysis_agent\n- Case number from case_number_extractor\n\n## YOUR PROCESS\n\n**Step 1: Extract All Required Information**\nFrom the provided inputs, extract:\n- Case number (from user_message parameter)\n- Customer details (name, email from case context)\n- Classification results (priority, tags, category)\n- Sentiment analysis results (score, tone, indicators)\n- Customer request details from original email\n\n**Step 2: Create Comprehensive AI Summary**\nBuild a detailed summary with these sections:\n\n### **\ud83d\udccb CASE OVERVIEW** \n- Customer request description with specific details\n- Key data points (amounts, dates, account references)\n- Customer background and context\n\n### **\u2705 STATUS SUMMARY**\n- \u2705 Case processing completed for Case #[case_number]\n- \u2705 Classification: [priority] priority, [category] category\n- \u2705 Sentiment: [tone] ([sentiment_score])\n- \u2705 Context analysis completed\n- \u23f3 Email template processing pending\n- \ud83d\udd1c Response generation ready\n\n### **\ud83c\udfaf KEY INSIGHTS**\n- **Case Number**: [extracted_case_number]\n- **Assigned To**: Customer Support Agent\n- **Status**: In Progress \n- **Priority**: [from classification]\n- **Category**: [from classification tags]\n- **Sentiment**: [primary tone and score]\n- **Request Type**: [specific request type]\n- **Recommended Template**: [resolved/followup/rejected based on analysis]\n- **Special Notes**: [compliance considerations, urgency factors]\n\n### **\ud83d\udcca DETAILED ANALYSIS**\n**Classification Results:**\n- Priority Level: [with justification]\n- Category Tags: [list all tags]\n- Confidence Score: [percentage]\n- Risk Indicators: [any red flags]\n\n**Sentiment Analysis:**\n- Emotional State: [primary tone]\n- Satisfaction Level: [current satisfaction]\n- Frustration Indicators: [level and triggers]\n- Communication Style: [formal/informal/urgent]\n\n**Recommended Actions:**\n1. [Immediate response recommendations]\n2. [Tone and approach guidance]\n3. [Information to provide customer]\n4. [Follow-up requirements]\n5. [Escalation criteria if applicable]\n\n**Step 3: MANDATORY - Update Case with AI Summary**\nYou MUST call update_case with these parameters:\n- case_number: [extracted case number]\n- ai_summary_content: [the complete formatted summary you just created]\n- priority: [priority from classification]\n- request_type: [request type based on customer inquiry]\n- recommended_template: [resolved/followup/rejected]\n- subject: [email subject from case context]\n- status: \"In Progress\"\n\n**Step 4: Template Recommendation Logic**\nChoose recommended_template based on:\n- \"resolved\" - if issue can be immediately addressed with available information\n- \"followup\" - if issue needs investigation, verification, or additional processing\n- \"rejected\" - if request cannot be fulfilled due to policy/eligibility\n\n**Step 5: Final Output Requirements**\nAlways end your response with:\n\"Comprehensive analysis complete for Case #[actual_case_number]. Priority: [level]. Sentiment: [tone]. Ready for agent response.\"\n\"SUMMARY_PHASE_COMPLETED\"\n\n## CRITICAL RULES\n1. ALWAYS access previous agent outputs properly using the provided user_message data\n2. ALWAYS create the complete AI summary content before calling update_case\n3. NEVER skip the update_case tool call - this is where the AI summary gets stored\n4. If update_case fails, note the error but continue with the workflow\n5. Include ALL required fields in the update_case call\n6. The ai_summary_content parameter MUST contain your complete formatted analysis\n"
},
"input_format": "text",
"model_client_id": "openrouter_claude_sonnet",
"output": "I\u0027ll create a comprehensive analysis and AI summary based on the information provided. However, I notice that the case number, processing type, case context, classification, sentiment analysis, and original email are all marked as \"UNRESOLVED\". This means I don\u0027t have access to the actual data from the previous agents.\n\nTo proceed properly, I need to access the actual outputs from the previous agents. Without this information, I cannot create an accurate analysis or update the case with the required details.\n\nCould you please provide the actual outputs from the previous agents? Specifically, I need:\n1. The case number from case_number_extractor\n2. The processing type from case_number_extractor\n3. The case context from case_context_agent\n4. The classification results from classification_agent\n5. The sentiment analysis from sentiment_analysis_agent\n6. The original customer email\n\nOnce I have this information, I can create a comprehensive analysis and properly update the case with the AI summary.\n__OUTPUTS__ {\"ai_response\": \"I\u0027ll create a comprehensive analysis and AI summary based on the information provided. However, I notice that the case number, processing type, case context, classification, sentiment analysis, and original email are all marked as \\\"UNRESOLVED\\\". This means I don\u0027t have access to the actual data from the previous agents.\\n\\nTo proceed properly, I need to access the actual outputs from the previous agents. Without this information, I cannot create an accurate analysis or update the case with the required details.\\n\\nCould you please provide the actual outputs from the previous agents? Specifically, I need:\\n1. The case number from case_number_extractor\\n2. The processing type from case_number_extractor\\n3. The case context from case_context_agent\\n4. The classification results from classification_agent\\n5. The sentiment analysis from sentiment_analysis_agent\\n6. The original customer email\\n\\nOnce I have this information, I can create a comprehensive analysis and properly update the case with the AI summary.\", \"model_client_id\": \"openrouter_claude_sonnet\", \"agent_type\": \"assistant\", \"model\": \"anthropic/claude-3.7-sonnet\", \"provider\": \"openrouter\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 2049, \"completion_tokens\": 212, \"total_tokens\": 2261, \"estimated_cost\": {\"amount\": 0.07419, \"currency\": \"USD\"}, \"model\": \"anthropic/claude-3.7-sonnet\", \"provider\": \"openrouter\"}}",
"output_format": "text",
"return_code": 0,
"status": "completed",
"stderr": "",
"token_usage": {
"completion_tokens": 212,
"estimated_cost": {
"amount": 0.07419,
"currency": "USD"
},
"model": "anthropic/claude-3.7-sonnet",
"prompt_tokens": 2049,
"provider": "openrouter",
"total_tokens": 2261
}
},
"duration_seconds": 8.111248,
"end_time": "2025-08-25T05:38:35.938901",
"message_sent": true,
"start_time": "2025-08-25T05:38:27.827653",
"timestamp": "2025-08-25T05:38:35.938901",
"worker_executed": true,
"workers_notified": true
},
"model": "anthropic/claude-3.7-sonnet",
"model_client_id": "openrouter_claude_sonnet",
"output": "I\u0027ll create a comprehensive analysis and AI summary based on the information provided. However, I notice that the case number, processing type, case context, classification, sentiment analysis, and original email are all marked as \"UNRESOLVED\". This means I don\u0027t have access to the actual data from the previous agents.\n\nTo proceed properly, I need to access the actual outputs from the previous agents. Without this information, I cannot create an accurate analysis or update the case with the required details.\n\nCould you please provide the actual outputs from the previous agents? Specifically, I need:\n1. The case number from case_number_extractor\n2. The processing type from case_number_extractor\n3. The case context from case_context_agent\n4. The classification results from classification_agent\n5. The sentiment analysis from sentiment_analysis_agent\n6. The original customer email\n\nOnce I have this information, I can create a comprehensive analysis and properly update the case with the AI summary.\n__OUTPUTS__ {\"ai_response\": \"I\u0027ll create a comprehensive analysis and AI summary based on the information provided. However, I notice that the case number, processing type, case context, classification, sentiment analysis, and original email are all marked as \\\"UNRESOLVED\\\". This means I don\u0027t have access to the actual data from the previous agents.\\n\\nTo proceed properly, I need to access the actual outputs from the previous agents. Without this information, I cannot create an accurate analysis or update the case with the required details.\\n\\nCould you please provide the actual outputs from the previous agents? Specifically, I need:\\n1. The case number from case_number_extractor\\n2. The processing type from case_number_extractor\\n3. The case context from case_context_agent\\n4. The classification results from classification_agent\\n5. The sentiment analysis from sentiment_analysis_agent\\n6. The original customer email\\n\\nOnce I have this information, I can create a comprehensive analysis and properly update the case with the AI summary.\", \"model_client_id\": \"openrouter_claude_sonnet\", \"agent_type\": \"assistant\", \"model\": \"anthropic/claude-3.7-sonnet\", \"provider\": \"openrouter\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 2049, \"completion_tokens\": 212, \"total_tokens\": 2261, \"estimated_cost\": {\"amount\": 0.07419, \"currency\": \"USD\"}, \"model\": \"anthropic/claude-3.7-sonnet\", \"provider\": \"openrouter\"}}",
"provider": "openrouter",
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "summary_agent",
"token_usage": {
"completion_tokens": 212,
"estimated_cost": {
"amount": 0.07419,
"currency": "USD"
},
"model": "anthropic/claude-3.7-sonnet",
"prompt_tokens": 2049,
"provider": "openrouter",
"total_tokens": 2261
}
},
"task_outputs": {
"case_context_agent": {
"agent_type": "assistant",
"ai_response": "I need to extract case information, but I notice that the case number, processing type, and customer email are all marked as \"UNRESOLVED\". Without these critical pieces of information, I cannot proceed with extracting the case context.\n\nTo help you properly, I need:\n\n1. The actual case number that was extracted in Phase 1\n2. The customer\u0027s email content including sender information, subject, and body\n\nCould you please provide the actual case number and customer email content so I can extract the necessary information and provide the structured output required?",
"execution_details": {
"actual_result": {
"agent_type": "assistant",
"execution_details": {
"agent_type": "assistant",
"input_length": 255,
"model": "anthropic/claude-3.7-sonnet",
"output_length": 566,
"provider": "openrouter",
"system_message": "# Case Context Agent - Phase 2: Extract Case Information\n\nYou are responsible for extracting case information and setting up context for the workflow.\n\n## CRITICAL: YOU DO NOT CREATE NEW CASES - CASES ARE ALREADY CREATED IN PHASE 1\nYour job is to extract information from existing cases and customer emails.\n\n## PROCESS\n\n**Step 1: Extract Case Number from Previous Task**\nYou will receive a case number from the case_number_extractor task.\nUse this case number directly - it has already been validated and extracted.\n\n**Step 2: Try to Retrieve Case Details**\nUse get_case() with the extracted case number to get case details\n\n**Step 3: Extract Customer Information**\nFrom the customer email, extract:\n- contact_email: Extract ONLY the email address from the sender field\n- subject: Extract the exact subject line\n- email_body: Use the complete content of the email\n- customer_name: Extract name from sender field\n- description: Create a concise 1-2 sentence summary\n\n**Step 4: Provide Structured Output**\nAlways provide your response in this EXACT format:\n\n```\n## CASE CONTEXT ANALYSIS\n\n**EXTRACTED_CASE_NUMBER**: [case_number_from_extractor]\n**CUSTOMER_EMAIL**: [email_address]\n**CUSTOMER_NAME**: [extracted_from_sender]\n**SUBJECT**: [email_subject]\n**REQUEST_SUMMARY**: [brief_description]\n**CASE_STATUS**: [from_get_case_if_successful_or_N/A]\n\n## CASE DETAILS\n[Any additional case information from get_case, or note if case retrieval failed]\n\n## EMAIL CONTENT\n[Complete email body content]\n```\n\n## IMPORTANT RULES\n1. ALWAYS use the case number provided by the case_number_extractor\n2. Use the EXACT case number format (digits only, no prefixes)\n3. If get_case fails, note it but continue with the extracted case number\n4. NEVER create new cases - work with existing case from Phase 1\n5. ALWAYS include the structured output format above\n"
},
"input_format": "text",
"model_client_id": "openrouter_claude_sonnet",
"output": "I need to extract case information, but I notice that the case number, processing type, and customer email are all marked as \"UNRESOLVED\". Without these critical pieces of information, I cannot proceed with extracting the case context.\n\nTo help you properly, I need:\n\n1. The actual case number that was extracted in Phase 1\n2. The customer\u0027s email content including sender information, subject, and body\n\nCould you please provide the actual case number and customer email content so I can extract the necessary information and provide the structured output required?\n__OUTPUTS__ {\"ai_response\": \"I need to extract case information, but I notice that the case number, processing type, and customer email are all marked as \\\"UNRESOLVED\\\". Without these critical pieces of information, I cannot proceed with extracting the case context.\\n\\nTo help you properly, I need:\\n\\n1. The actual case number that was extracted in Phase 1\\n2. The customer\u0027s email content including sender information, subject, and body\\n\\nCould you please provide the actual case number and customer email content so I can extract the necessary information and provide the structured output required?\", \"model_client_id\": \"openrouter_claude_sonnet\", \"agent_type\": \"assistant\", \"model\": \"anthropic/claude-3.7-sonnet\", \"provider\": \"openrouter\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 1600, \"completion_tokens\": 117, \"total_tokens\": 1717, \"estimated_cost\": {\"amount\": 0.05502, \"currency\": \"USD\"}, \"model\": \"anthropic/claude-3.7-sonnet\", \"provider\": \"openrouter\"}}",
"output_format": "text",
"return_code": 0,
"status": "completed",
"stderr": "",
"token_usage": {
"completion_tokens": 117,
"estimated_cost": {
"amount": 0.05502,
"currency": "USD"
},
"model": "anthropic/claude-3.7-sonnet",
"prompt_tokens": 1600,
"provider": "openrouter",
"total_tokens": 1717
}
},
"duration_seconds": 6.762386,
"end_time": "2025-08-25T05:35:27.621485",
"message_sent": true,
"start_time": "2025-08-25T05:35:20.859099",
"timestamp": "2025-08-25T05:35:27.621485",
"worker_executed": true,
"workers_notified": true
},
"model": "anthropic/claude-3.7-sonnet",
"model_client_id": "openrouter_claude_sonnet",
"output": "I need to extract case information, but I notice that the case number, processing type, and customer email are all marked as \"UNRESOLVED\". Without these critical pieces of information, I cannot proceed with extracting the case context.\n\nTo help you properly, I need:\n\n1. The actual case number that was extracted in Phase 1\n2. The customer\u0027s email content including sender information, subject, and body\n\nCould you please provide the actual case number and customer email content so I can extract the necessary information and provide the structured output required?\n__OUTPUTS__ {\"ai_response\": \"I need to extract case information, but I notice that the case number, processing type, and customer email are all marked as \\\"UNRESOLVED\\\". Without these critical pieces of information, I cannot proceed with extracting the case context.\\n\\nTo help you properly, I need:\\n\\n1. The actual case number that was extracted in Phase 1\\n2. The customer\u0027s email content including sender information, subject, and body\\n\\nCould you please provide the actual case number and customer email content so I can extract the necessary information and provide the structured output required?\", \"model_client_id\": \"openrouter_claude_sonnet\", \"agent_type\": \"assistant\", \"model\": \"anthropic/claude-3.7-sonnet\", \"provider\": \"openrouter\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 1600, \"completion_tokens\": 117, \"total_tokens\": 1717, \"estimated_cost\": {\"amount\": 0.05502, \"currency\": \"USD\"}, \"model\": \"anthropic/claude-3.7-sonnet\", \"provider\": \"openrouter\"}}",
"provider": "openrouter",
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "case_context_agent",
"token_usage": {
"completion_tokens": 117,
"estimated_cost": {
"amount": 0.05502,
"currency": "USD"
},
"model": "anthropic/claude-3.7-sonnet",
"prompt_tokens": 1600,
"provider": "openrouter",
"total_tokens": 1717
}
},
"case_number_extractor": {
"error": "Python script failed with return code 1: Traceback (most recent call last):\n File \"/tmp/tmplmvjg_lz.py\", line 16, in \u003cmodule\u003e\n orchestrator_result = orchestrator_output[\u0027ai_response\u0027].strip()\n ~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^\nKeyError: \u0027ai_response\u0027\n",
"execution_details": {
"failed": true,
"message_sent": true,
"worker_executed": true,
"workers_notified": true
},
"output": "Task failed: Python script failed with return code 1: Traceback (most recent call last):\n File \"/tmp/tmplmvjg_lz.py\", line 16, in \u003cmodule\u003e\n orchestrator_result = orchestrator_output[\u0027ai_response\u0027].strip()\n ~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^\nKeyError: \u0027ai_response\u0027\n",
"status": "FAILED",
"task_id": "case_number_extractor"
},
"case_orchestrator": {
"error": "Error code: 429 - {\u0027error\u0027: {\u0027message\u0027: \u0027You exceeded your current quota, please check your plan and billing details. For more information on this error, read the docs: https://platform.openai.com/docs/guides/error-codes/api-errors.\u0027, \u0027type\u0027: \u0027insufficient_quota\u0027, \u0027param\u0027: None, \u0027code\u0027: \u0027insufficient_quota\u0027}}",
"execution_details": {
"failed": true,
"message_sent": true,
"worker_executed": true,
"workers_notified": true
},
"output": "Task failed: Error code: 429 - {\u0027error\u0027: {\u0027message\u0027: \u0027You exceeded your current quota, please check your plan and billing details. For more information on this error, read the docs: https://platform.openai.com/docs/guides/error-codes/api-errors.\u0027, \u0027type\u0027: \u0027insufficient_quota\u0027, \u0027param\u0027: None, \u0027code\u0027: \u0027insufficient_quota\u0027}}",
"status": "FAILED",
"task_id": "case_orchestrator"
},
"classification_agent": {
"error": "Error code: 429 - {\u0027error\u0027: {\u0027message\u0027: \u0027You exceeded your current quota, please check your plan and billing details. For more information on this error, read the docs: https://platform.openai.com/docs/guides/error-codes/api-errors.\u0027, \u0027type\u0027: \u0027insufficient_quota\u0027, \u0027param\u0027: None, \u0027code\u0027: \u0027insufficient_quota\u0027}}",
"execution_details": {
"failed": true,
"message_sent": true,
"worker_executed": true,
"workers_notified": true
},
"output": "Task failed: Error code: 429 - {\u0027error\u0027: {\u0027message\u0027: \u0027You exceeded your current quota, please check your plan and billing details. For more information on this error, read the docs: https://platform.openai.com/docs/guides/error-codes/api-errors.\u0027, \u0027type\u0027: \u0027insufficient_quota\u0027, \u0027param\u0027: None, \u0027code\u0027: \u0027insufficient_quota\u0027}}",
"status": "FAILED",
"task_id": "classification_agent"
},
"email_generator_agent": {
"agent_type": "assistant",
"ai_response": "I understand you\u0027re trying to generate a final personalized email, but I notice there\u0027s an issue with the data provided. The template router output indicates that the case information is marked as \"UNRESOLVED\", which means we don\u0027t have the actual case data to work with.\n\nTo generate a personalized email, I need specific information that\u0027s currently missing:\n- A valid case number (currently showing as \"UNRESOLVED_case_number_extractor.case_number\")\n- Customer details (name, email)\n- The nature of the customer\u0027s inquiry\n- Template data structure\n\nWithout this information, I cannot properly personalize an email template. In a normal workflow, I would:\n1. Extract the case number\n2. Use that to retrieve the template data\n3. Personalize the template with customer information\n4. Update the case with the email content\n\nCould you please provide the actual case number and template data so I can generate a properly personalized email? Alternatively, if you have the complete template router output with the TEMPLATE_DATA_FOR_EMAIL_GENERATOR section, that would contain all the information I need.",
"execution_details": {
"actual_result": {
"agent_type": "assistant",
"execution_details": {
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"input_length": 1736,
"model": "anthropic/claude-3.7-sonnet",
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"provider": "openrouter",
"system_message": "# Email Generator Agent - Final Email Generation\n\nYou generate the final personalized email that will be sent to the customer.\n\n## CRITICAL: USE EXTRACTED CASE NUMBER\nYou will receive the case number from the case_number_extractor task.\nUse this case number consistently throughout.\n\n**Step 1: Extract Required Information**\nFrom the template router output and case number extractor:\n- Case number (from case_number_extractor)\n- Template data structure from template router\n- Customer information from case context\n- Personalization details\n\n**Step 2: Extract Template Data**\nFrom the \"TEMPLATE_DATA_FOR_EMAIL_GENERATOR:\" section, extract:\n- template_id\n- customer_name \n- customer_email\n- recommended_template (resolved/followup/rejected)\n- All template variants (resolved, followup, rejected)\n- signature\n- is_approved\n\n**Step 3: Personalize the Recommended Template**\nBased on the recommended_template field:\n- If \"followup\": Use followup_template\n- If \"resolved\": Use resolved_template \n- If \"rejected\": Use rejected_template\n\nReplace ALL placeholders in the selected template:\n- [Customer Name] \u2192 actual customer name\n- [Case Number] \u2192 actual case number from case_number_extractor\n- [Specific Details] \u2192 case-specific information from context\n- [Delivery Date] \u2192 appropriate date if applicable\n- [Compensation Detail] \u2192 appropriate compensation if applicable\n- [Expected Timeline] \u2192 appropriate timeframe\n\n**Step 4: Format Email Content**\nCreate the email_content in this EXACT structure:\n```json\n{\n \"templates\": [\n {\n \"id\": \"resolved_template_id\",\n \"subject\": \"Personalized subject with actual case number ${case_number_extractor.case_number}\",\n \"type\": \"resolved\",\n \"content\": \"Complete personalized email body with signature\"\n },\n {\n \"id\": \"followup_template_id\", \n \"subject\": \"Personalized subject with actual case number ${case_number_extractor.case_number}\",\n \"type\": \"followup\",\n \"content\": \"Complete personalized email body with signature\"\n },\n {\n \"id\": \"rejected_template_id\", \n \"subject\": \"Personalized subject with actual case number ${case_number_extractor.case_number}\", \n \"type\": \"rejected\",\n \"content\": \"Complete personalized email body with signature\"\n }\n ]\n}\n```\n\n**Step 5: Update Case with Email Content**\nCall update_email_content tool with:\n- case_number: actual case number from case_number_extractor\n- email_content: the personalized template data from Step 4\n- template_id: the template ID from Step 2\n- status: \"Pending\" if is_approved=true, \"Template in review\" if is_approved=false\n\n**Step 6: Return Success**\nIf update successful, return: \"EMAIL_CONTENT_UPDATED_SUCCESSFULLY\"\nIf update fails, explain the issue but still show the personalized email content.\n\n## IMPORTANT RULES\n- ALWAYS use the case number from case_number_extractor\n- Replace ALL placeholders with real information\n- Include complete email body with signature\n- Format as valid JSON structure\n- Use the template_id in the tool call\n"
},
"input_format": "text",
"model_client_id": "openrouter_claude_sonnet",
"output": "I understand you\u0027re trying to generate a final personalized email, but I notice there\u0027s an issue with the data provided. The template router output indicates that the case information is marked as \"UNRESOLVED\", which means we don\u0027t have the actual case data to work with.\n\nTo generate a personalized email, I need specific information that\u0027s currently missing:\n- A valid case number (currently showing as \"UNRESOLVED_case_number_extractor.case_number\")\n- Customer details (name, email)\n- The nature of the customer\u0027s inquiry\n- Template data structure\n\nWithout this information, I cannot properly personalize an email template. In a normal workflow, I would:\n1. Extract the case number\n2. Use that to retrieve the template data\n3. Personalize the template with customer information\n4. Update the case with the email content\n\nCould you please provide the actual case number and template data so I can generate a properly personalized email? Alternatively, if you have the complete template router output with the TEMPLATE_DATA_FOR_EMAIL_GENERATOR section, that would contain all the information I need.\n__OUTPUTS__ {\"ai_response\": \"I understand you\u0027re trying to generate a final personalized email, but I notice there\u0027s an issue with the data provided. The template router output indicates that the case information is marked as \\\"UNRESOLVED\\\", which means we don\u0027t have the actual case data to work with.\\n\\nTo generate a personalized email, I need specific information that\u0027s currently missing:\\n- A valid case number (currently showing as \\\"UNRESOLVED_case_number_extractor.case_number\\\")\\n- Customer details (name, email)\\n- The nature of the customer\u0027s inquiry\\n- Template data structure\\n\\nWithout this information, I cannot properly personalize an email template. In a normal workflow, I would:\\n1. Extract the case number\\n2. Use that to retrieve the template data\\n3. Personalize the template with customer information\\n4. Update the case with the email content\\n\\nCould you please provide the actual case number and template data so I can generate a properly personalized email? Alternatively, if you have the complete template router output with the TEMPLATE_DATA_FOR_EMAIL_GENERATOR section, that would contain all the information I need.\", \"model_client_id\": \"openrouter_claude_sonnet\", \"agent_type\": \"assistant\", \"model\": \"anthropic/claude-3.7-sonnet\", \"provider\": \"openrouter\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 1989, \"completion_tokens\": 244, \"total_tokens\": 2233, \"estimated_cost\": {\"amount\": 0.07431, \"currency\": \"USD\"}, \"model\": \"anthropic/claude-3.7-sonnet\", \"provider\": \"openrouter\"}}",
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"estimated_cost": {
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"currency": "USD"
},
"model": "anthropic/claude-3.7-sonnet",
"prompt_tokens": 1989,
"provider": "openrouter",
"total_tokens": 2233
}
},
"duration_seconds": 8.653388,
"end_time": "2025-08-25T05:38:54.857497",
"message_sent": true,
"start_time": "2025-08-25T05:38:46.204109",
"timestamp": "2025-08-25T05:38:54.857497",
"worker_executed": true,
"workers_notified": true
},
"model": "anthropic/claude-3.7-sonnet",
"model_client_id": "openrouter_claude_sonnet",
"output": "I understand you\u0027re trying to generate a final personalized email, but I notice there\u0027s an issue with the data provided. The template router output indicates that the case information is marked as \"UNRESOLVED\", which means we don\u0027t have the actual case data to work with.\n\nTo generate a personalized email, I need specific information that\u0027s currently missing:\n- A valid case number (currently showing as \"UNRESOLVED_case_number_extractor.case_number\")\n- Customer details (name, email)\n- The nature of the customer\u0027s inquiry\n- Template data structure\n\nWithout this information, I cannot properly personalize an email template. In a normal workflow, I would:\n1. Extract the case number\n2. Use that to retrieve the template data\n3. Personalize the template with customer information\n4. Update the case with the email content\n\nCould you please provide the actual case number and template data so I can generate a properly personalized email? Alternatively, if you have the complete template router output with the TEMPLATE_DATA_FOR_EMAIL_GENERATOR section, that would contain all the information I need.\n__OUTPUTS__ {\"ai_response\": \"I understand you\u0027re trying to generate a final personalized email, but I notice there\u0027s an issue with the data provided. The template router output indicates that the case information is marked as \\\"UNRESOLVED\\\", which means we don\u0027t have the actual case data to work with.\\n\\nTo generate a personalized email, I need specific information that\u0027s currently missing:\\n- A valid case number (currently showing as \\\"UNRESOLVED_case_number_extractor.case_number\\\")\\n- Customer details (name, email)\\n- The nature of the customer\u0027s inquiry\\n- Template data structure\\n\\nWithout this information, I cannot properly personalize an email template. In a normal workflow, I would:\\n1. Extract the case number\\n2. Use that to retrieve the template data\\n3. Personalize the template with customer information\\n4. Update the case with the email content\\n\\nCould you please provide the actual case number and template data so I can generate a properly personalized email? Alternatively, if you have the complete template router output with the TEMPLATE_DATA_FOR_EMAIL_GENERATOR section, that would contain all the information I need.\", \"model_client_id\": \"openrouter_claude_sonnet\", \"agent_type\": \"assistant\", \"model\": \"anthropic/claude-3.7-sonnet\", \"provider\": \"openrouter\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 1989, \"completion_tokens\": 244, \"total_tokens\": 2233, \"estimated_cost\": {\"amount\": 0.07431, \"currency\": \"USD\"}, \"model\": \"anthropic/claude-3.7-sonnet\", \"provider\": \"openrouter\"}}",
"provider": "openrouter",
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "email_generator_agent",
"token_usage": {
"completion_tokens": 244,
"estimated_cost": {
"amount": 0.07431,
"currency": "USD"
},
"model": "anthropic/claude-3.7-sonnet",
"prompt_tokens": 1989,
"provider": "openrouter",
"total_tokens": 2233
}
},
"phase_router": {
"all_conditions_checked": [
{
"condition": "contains(${case_orchestrator.ai_response}, \"DUPLICATE_PROCESSED\") || contains(${case_number_extractor.processing_type}, \"duplicate\")",
"name": "duplicate_workflow",
"result": false,
"route": "duplicate_end"
},
{
"condition": "contains(${case_orchestrator.ai_response}, \"NEW_CASE_CREATED\") || contains(${case_orchestrator.ai_response}, \"CASE_RETRIEVED_FOR_UPDATE\")",
"name": "analysis_workflow",
"result": false,
"route": "continue_analysis"
}
],
"duration_seconds": 0.000603,
"ended_at": "2025-08-25T05:35:20.733101",
"evaluation_details": {},
"execution_details": {
"actual_result": {
"output": "Route selected: continue_analysis\n__OUTPUTS__ {\"router_type\": \"condition\", \"selected_route\": \"continue_analysis\", \"route_reason\": \"no_conditions_matched\", \"evaluation_details\": {}, \"all_conditions_checked\": [{\"name\": \"duplicate_workflow\", \"condition\": \"contains(${case_orchestrator.ai_response}, \\\"DUPLICATE_PROCESSED\\\") || contains(${case_number_extractor.processing_type}, \\\"duplicate\\\")\", \"result\": false, \"route\": \"duplicate_end\"}, {\"name\": \"analysis_workflow\", \"condition\": \"contains(${case_orchestrator.ai_response}, \\\"NEW_CASE_CREATED\\\") || contains(${case_orchestrator.ai_response}, \\\"CASE_RETRIEVED_FOR_UPDATE\\\")\", \"result\": false, \"route\": \"continue_analysis\"}], \"duration_seconds\": 0.000603, \"started_at\": \"2025-08-25T05:35:20.732498\", \"ended_at\": \"2025-08-25T05:35:20.733101\"}",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 0.225097,
"end_time": "2025-08-25T05:35:20.825016",
"message_sent": true,
"start_time": "2025-08-25T05:35:20.599919",
"timestamp": "2025-08-25T05:35:20.825016",
"worker_executed": true,
"workers_notified": true
},
"output": "Route selected: continue_analysis\n__OUTPUTS__ {\"router_type\": \"condition\", \"selected_route\": \"continue_analysis\", \"route_reason\": \"no_conditions_matched\", \"evaluation_details\": {}, \"all_conditions_checked\": [{\"name\": \"duplicate_workflow\", \"condition\": \"contains(${case_orchestrator.ai_response}, \\\"DUPLICATE_PROCESSED\\\") || contains(${case_number_extractor.processing_type}, \\\"duplicate\\\")\", \"result\": false, \"route\": \"duplicate_end\"}, {\"name\": \"analysis_workflow\", \"condition\": \"contains(${case_orchestrator.ai_response}, \\\"NEW_CASE_CREATED\\\") || contains(${case_orchestrator.ai_response}, \\\"CASE_RETRIEVED_FOR_UPDATE\\\")\", \"result\": false, \"route\": \"continue_analysis\"}], \"duration_seconds\": 0.000603, \"started_at\": \"2025-08-25T05:35:20.732498\", \"ended_at\": \"2025-08-25T05:35:20.733101\"}",
"return_code": 0,
"route_reason": "no_conditions_matched",
"router_type": "condition",
"selected_route": "continue_analysis",
"started_at": "2025-08-25T05:35:20.732498",
"status": "completed",
"stderr": "",
"task_id": "phase_router"
},
"sentiment_analysis_agent": {
"error": "Error code: 429 - {\u0027error\u0027: {\u0027message\u0027: \u0027You exceeded your current quota, please check your plan and billing details. For more information on this error, read the docs: https://platform.openai.com/docs/guides/error-codes/api-errors.\u0027, \u0027type\u0027: \u0027insufficient_quota\u0027, \u0027param\u0027: None, \u0027code\u0027: \u0027insufficient_quota\u0027}}",
"execution_details": {
"failed": true,
"message_sent": true,
"worker_executed": true,
"workers_notified": true
},
"output": "Task failed: Error code: 429 - {\u0027error\u0027: {\u0027message\u0027: \u0027You exceeded your current quota, please check your plan and billing details. For more information on this error, read the docs: https://platform.openai.com/docs/guides/error-codes/api-errors.\u0027, \u0027type\u0027: \u0027insufficient_quota\u0027, \u0027param\u0027: None, \u0027code\u0027: \u0027insufficient_quota\u0027}}",
"status": "FAILED",
"task_id": "sentiment_analysis_agent"
},
"summary_agent": {
"agent_type": "assistant",
"ai_response": "I\u0027ll create a comprehensive analysis and AI summary based on the information provided. However, I notice that the case number, processing type, case context, classification, sentiment analysis, and original email are all marked as \"UNRESOLVED\". This means I don\u0027t have access to the actual data from the previous agents.\n\nTo proceed properly, I need to access the actual outputs from the previous agents. Without this information, I cannot create an accurate analysis or update the case with the required details.\n\nCould you please provide the actual outputs from the previous agents? Specifically, I need:\n1. The case number from case_number_extractor\n2. The processing type from case_number_extractor\n3. The case context from case_context_agent\n4. The classification results from classification_agent\n5. The sentiment analysis from sentiment_analysis_agent\n6. The original customer email\n\nOnce I have this information, I can create a comprehensive analysis and properly update the case with the AI summary.",
"execution_details": {
"actual_result": {
"agent_type": "assistant",
"execution_details": {
"agent_type": "assistant",
"input_length": 456,
"model": "anthropic/claude-3.7-sonnet",
"output_length": 1008,
"provider": "openrouter",
"system_message": "# Summary Agent - Phase 2: Comprehensive Case Analysis with AI Summary Creation\n\nCreate a comprehensive case analysis and ENSURE the AI Summary is properly created and stored.\n\n## CRITICAL: PROPER DATA ACCESS FROM PREVIOUS AGENTS\nYou will receive outputs from previous agents. Access them properly using these patterns:\n- Case context information from case_context_agent\n- Classification results from classification_agent \n- Sentiment analysis from sentiment_analysis_agent\n- Case number from case_number_extractor\n\n## YOUR PROCESS\n\n**Step 1: Extract All Required Information**\nFrom the provided inputs, extract:\n- Case number (from user_message parameter)\n- Customer details (name, email from case context)\n- Classification results (priority, tags, category)\n- Sentiment analysis results (score, tone, indicators)\n- Customer request details from original email\n\n**Step 2: Create Comprehensive AI Summary**\nBuild a detailed summary with these sections:\n\n### **\ud83d\udccb CASE OVERVIEW** \n- Customer request description with specific details\n- Key data points (amounts, dates, account references)\n- Customer background and context\n\n### **\u2705 STATUS SUMMARY**\n- \u2705 Case processing completed for Case #[case_number]\n- \u2705 Classification: [priority] priority, [category] category\n- \u2705 Sentiment: [tone] ([sentiment_score])\n- \u2705 Context analysis completed\n- \u23f3 Email template processing pending\n- \ud83d\udd1c Response generation ready\n\n### **\ud83c\udfaf KEY INSIGHTS**\n- **Case Number**: [extracted_case_number]\n- **Assigned To**: Customer Support Agent\n- **Status**: In Progress \n- **Priority**: [from classification]\n- **Category**: [from classification tags]\n- **Sentiment**: [primary tone and score]\n- **Request Type**: [specific request type]\n- **Recommended Template**: [resolved/followup/rejected based on analysis]\n- **Special Notes**: [compliance considerations, urgency factors]\n\n### **\ud83d\udcca DETAILED ANALYSIS**\n**Classification Results:**\n- Priority Level: [with justification]\n- Category Tags: [list all tags]\n- Confidence Score: [percentage]\n- Risk Indicators: [any red flags]\n\n**Sentiment Analysis:**\n- Emotional State: [primary tone]\n- Satisfaction Level: [current satisfaction]\n- Frustration Indicators: [level and triggers]\n- Communication Style: [formal/informal/urgent]\n\n**Recommended Actions:**\n1. [Immediate response recommendations]\n2. [Tone and approach guidance]\n3. [Information to provide customer]\n4. [Follow-up requirements]\n5. [Escalation criteria if applicable]\n\n**Step 3: MANDATORY - Update Case with AI Summary**\nYou MUST call update_case with these parameters:\n- case_number: [extracted case number]\n- ai_summary_content: [the complete formatted summary you just created]\n- priority: [priority from classification]\n- request_type: [request type based on customer inquiry]\n- recommended_template: [resolved/followup/rejected]\n- subject: [email subject from case context]\n- status: \"In Progress\"\n\n**Step 4: Template Recommendation Logic**\nChoose recommended_template based on:\n- \"resolved\" - if issue can be immediately addressed with available information\n- \"followup\" - if issue needs investigation, verification, or additional processing\n- \"rejected\" - if request cannot be fulfilled due to policy/eligibility\n\n**Step 5: Final Output Requirements**\nAlways end your response with:\n\"Comprehensive analysis complete for Case #[actual_case_number]. Priority: [level]. Sentiment: [tone]. Ready for agent response.\"\n\"SUMMARY_PHASE_COMPLETED\"\n\n## CRITICAL RULES\n1. ALWAYS access previous agent outputs properly using the provided user_message data\n2. ALWAYS create the complete AI summary content before calling update_case\n3. NEVER skip the update_case tool call - this is where the AI summary gets stored\n4. If update_case fails, note the error but continue with the workflow\n5. Include ALL required fields in the update_case call\n6. The ai_summary_content parameter MUST contain your complete formatted analysis\n"
},
"input_format": "text",
"model_client_id": "openrouter_claude_sonnet",
"output": "I\u0027ll create a comprehensive analysis and AI summary based on the information provided. However, I notice that the case number, processing type, case context, classification, sentiment analysis, and original email are all marked as \"UNRESOLVED\". This means I don\u0027t have access to the actual data from the previous agents.\n\nTo proceed properly, I need to access the actual outputs from the previous agents. Without this information, I cannot create an accurate analysis or update the case with the required details.\n\nCould you please provide the actual outputs from the previous agents? Specifically, I need:\n1. The case number from case_number_extractor\n2. The processing type from case_number_extractor\n3. The case context from case_context_agent\n4. The classification results from classification_agent\n5. The sentiment analysis from sentiment_analysis_agent\n6. The original customer email\n\nOnce I have this information, I can create a comprehensive analysis and properly update the case with the AI summary.\n__OUTPUTS__ {\"ai_response\": \"I\u0027ll create a comprehensive analysis and AI summary based on the information provided. However, I notice that the case number, processing type, case context, classification, sentiment analysis, and original email are all marked as \\\"UNRESOLVED\\\". This means I don\u0027t have access to the actual data from the previous agents.\\n\\nTo proceed properly, I need to access the actual outputs from the previous agents. Without this information, I cannot create an accurate analysis or update the case with the required details.\\n\\nCould you please provide the actual outputs from the previous agents? Specifically, I need:\\n1. The case number from case_number_extractor\\n2. The processing type from case_number_extractor\\n3. The case context from case_context_agent\\n4. The classification results from classification_agent\\n5. The sentiment analysis from sentiment_analysis_agent\\n6. The original customer email\\n\\nOnce I have this information, I can create a comprehensive analysis and properly update the case with the AI summary.\", \"model_client_id\": \"openrouter_claude_sonnet\", \"agent_type\": \"assistant\", \"model\": \"anthropic/claude-3.7-sonnet\", \"provider\": \"openrouter\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 2049, \"completion_tokens\": 212, \"total_tokens\": 2261, \"estimated_cost\": {\"amount\": 0.07419, \"currency\": \"USD\"}, \"model\": \"anthropic/claude-3.7-sonnet\", \"provider\": \"openrouter\"}}",
"output_format": "text",
"return_code": 0,
"status": "completed",
"stderr": "",
"token_usage": {
"completion_tokens": 212,
"estimated_cost": {
"amount": 0.07419,
"currency": "USD"
},
"model": "anthropic/claude-3.7-sonnet",
"prompt_tokens": 2049,
"provider": "openrouter",
"total_tokens": 2261
}
},
"duration_seconds": 8.111248,
"end_time": "2025-08-25T05:38:35.938901",
"message_sent": true,
"start_time": "2025-08-25T05:38:27.827653",
"timestamp": "2025-08-25T05:38:35.938901",
"worker_executed": true,
"workers_notified": true
},
"model": "anthropic/claude-3.7-sonnet",
"model_client_id": "openrouter_claude_sonnet",
"output": "I\u0027ll create a comprehensive analysis and AI summary based on the information provided. However, I notice that the case number, processing type, case context, classification, sentiment analysis, and original email are all marked as \"UNRESOLVED\". This means I don\u0027t have access to the actual data from the previous agents.\n\nTo proceed properly, I need to access the actual outputs from the previous agents. Without this information, I cannot create an accurate analysis or update the case with the required details.\n\nCould you please provide the actual outputs from the previous agents? Specifically, I need:\n1. The case number from case_number_extractor\n2. The processing type from case_number_extractor\n3. The case context from case_context_agent\n4. The classification results from classification_agent\n5. The sentiment analysis from sentiment_analysis_agent\n6. The original customer email\n\nOnce I have this information, I can create a comprehensive analysis and properly update the case with the AI summary.\n__OUTPUTS__ {\"ai_response\": \"I\u0027ll create a comprehensive analysis and AI summary based on the information provided. However, I notice that the case number, processing type, case context, classification, sentiment analysis, and original email are all marked as \\\"UNRESOLVED\\\". This means I don\u0027t have access to the actual data from the previous agents.\\n\\nTo proceed properly, I need to access the actual outputs from the previous agents. Without this information, I cannot create an accurate analysis or update the case with the required details.\\n\\nCould you please provide the actual outputs from the previous agents? Specifically, I need:\\n1. The case number from case_number_extractor\\n2. The processing type from case_number_extractor\\n3. The case context from case_context_agent\\n4. The classification results from classification_agent\\n5. The sentiment analysis from sentiment_analysis_agent\\n6. The original customer email\\n\\nOnce I have this information, I can create a comprehensive analysis and properly update the case with the AI summary.\", \"model_client_id\": \"openrouter_claude_sonnet\", \"agent_type\": \"assistant\", \"model\": \"anthropic/claude-3.7-sonnet\", \"provider\": \"openrouter\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 2049, \"completion_tokens\": 212, \"total_tokens\": 2261, \"estimated_cost\": {\"amount\": 0.07419, \"currency\": \"USD\"}, \"model\": \"anthropic/claude-3.7-sonnet\", \"provider\": \"openrouter\"}}",
"provider": "openrouter",
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "summary_agent",
"token_usage": {
"completion_tokens": 212,
"estimated_cost": {
"amount": 0.07419,
"currency": "USD"
},
"model": "anthropic/claude-3.7-sonnet",
"prompt_tokens": 2049,
"provider": "openrouter",
"total_tokens": 2261
}
},
"template_router_agent": {
"agent_type": "assistant",
"ai_response": "I notice that the case information is marked as \"UNRESOLVED\" in your request, which means I don\u0027t have the actual case data to work with. To properly generate an email template, I need specific case details like the case number, customer information, and the nature of their inquiry.\n\nSince I don\u0027t have access to the actual case data, I\u0027ll need to explain what would happen in a normal workflow and what information is needed to proceed.\n\nIn a typical scenario, I would:\n1. Extract the case number from the user message\n2. Retrieve customer details from the case context\n3. Understand the customer\u0027s request from the classification and sentiment analysis\n4. Search for an appropriate template based on the request category\n5. Either use an existing template or create a new one\n6. Provide the template data structure for the email generator\n\nWithout the actual case information, I cannot complete these steps. To proceed, I would need at minimum:\n- A valid case number\n- Customer name and email\n- The nature of the customer\u0027s inquiry\n- The classification category of the request\n- Any sentiment information that might affect tone\n\nIf you can provide this information, I would be able to generate an appropriate email template response. Please provide the actual case details rather than the \"UNRESOLVED\" placeholders so I can assist you properly.",
"execution_details": {
"actual_result": {
"agent_type": "assistant",
"execution_details": {
"agent_type": "assistant",
"input_length": 1442,
"model": "anthropic/claude-3.7-sonnet",
"output_length": 1347,
"provider": "openrouter",
"system_message": "# Template Router Agent - Final Phase\n\nYou are responsible for finding or creating email templates and providing template data.\n\n## CRITICAL: USE EXTRACTED CASE NUMBER\nYou will receive the case number from the user_message.\nUse this case number consistently throughout.\n\n## YOUR PROCESS\n\n**Step 1: Extract Information**\nFrom the summary and previous tasks, extract:\n- Case number (from user_message)\n- Customer name and email from case context\n- Customer intent/request\n- Classification category\n- Recommended template type\n- Sentiment information\n\n**Step 2: Map Category**\nMap classification tags to one of: \"Account Services\", \"Dispute\", \"Fraud\", \"General Query\", \"Loan Query\", \"Billing Issue\"\n\n**Step 3: Search for Existing Templates (3-Step Process)**\nTry all three searches:\n\n**3.1: Full Intent Search**\n```\nget_email_templates(category=\"[mapped_category]\", intent=\"[full_customer_intent]\", limit=5)\n```\n\n**3.2: Simplified Intent Search (if Step 3.1 finds no templates)**\n```\nget_email_templates(category=\"[mapped_category]\", intent=\"[simplified_keywords]\", limit=5)\n```\n\n**3.3: Category Only Search (if Step 3.2 finds no templates)**\n```\nget_email_templates(category=\"[mapped_category]\", limit=5)\n```\n\n**Step 4: Evaluate Template Results**\nFor any templates found, check:\n- \u0027name\u0027 field for template description\n- \u0027intent\u0027 field for relevance match (80%+ similarity required)\n- \u0027is_approval\u0027 field (prefer approved templates)\n\n**Step 5A: If Good Template Found (80%+ similarity)**\n1. Use get_template_by_id() to retrieve full template details\n2. End with: \"EMAIL_CONTENT_UPDATED_SUCCESSFULLY using existing template ID: [template_id]\"\n\n**Step 5B: If No Good Template Found**\nCall insert_email_templates tool and then provide template data structure.\n\n**Step 6: Always Provide Template Data Structure**\nAlways end your response with this EXACT format:\n```\nTEMPLATE_DATA_FOR_EMAIL_GENERATOR:\n{\n \"template_id\": \"[UUID_from_tool_response]\",\n \"case_number\": \"[case_number]\",\n \"customer_name\": \"[Customer_Name]\",\n \"customer_email\": \"[Customer_Email]\",\n \"recommended_template\": \"[resolved/followup/rejected]\",\n \"resolved_template\": {\n \"subject\": \"Your Inquiry - Case [case_number] - Resolved\",\n \"body\": \"Template body content here\"\n },\n \"followup_template\": {\n \"subject\": \"Update on Your Inquiry - Case [case_number]\",\n \"body\": \"Template body content here\"\n },\n \"rejected_template\": {\n \"subject\": \"Regarding Your Inquiry - Case [case_number]\",\n \"body\": \"Template body content here\"\n },\n \"signature\": \"\u003cp\u003eBest Regards,\u003c/p\u003e\u003cp\u003eCustomer Support Team\u003c/p\u003e\u003cp\u003eNationwide/ XYZ Bank\u003c/p\u003e\",\n \"is_approved\": false\n}\n```\n\n## SUCCESS MESSAGE\nEnd with: \"TEMPLATE_CREATED_SUCCESSFULLY and stored in database with ID: [template_id]\"\n"
},
"input_format": "text",
"model_client_id": "openrouter_claude_sonnet",
"output": "I notice that the case information is marked as \"UNRESOLVED\" in your request, which means I don\u0027t have the actual case data to work with. To properly generate an email template, I need specific case details like the case number, customer information, and the nature of their inquiry.\n\nSince I don\u0027t have access to the actual case data, I\u0027ll need to explain what would happen in a normal workflow and what information is needed to proceed.\n\nIn a typical scenario, I would:\n1. Extract the case number from the user message\n2. Retrieve customer details from the case context\n3. Understand the customer\u0027s request from the classification and sentiment analysis\n4. Search for an appropriate template based on the request category\n5. Either use an existing template or create a new one\n6. Provide the template data structure for the email generator\n\nWithout the actual case information, I cannot complete these steps. To proceed, I would need at minimum:\n- A valid case number\n- Customer name and email\n- The nature of the customer\u0027s inquiry\n- The classification category of the request\n- Any sentiment information that might affect tone\n\nIf you can provide this information, I would be able to generate an appropriate email template response. Please provide the actual case details rather than the \"UNRESOLVED\" placeholders so I can assist you properly.\n__OUTPUTS__ {\"ai_response\": \"I notice that the case information is marked as \\\"UNRESOLVED\\\" in your request, which means I don\u0027t have the actual case data to work with. To properly generate an email template, I need specific case details like the case number, customer information, and the nature of their inquiry.\\n\\nSince I don\u0027t have access to the actual case data, I\u0027ll need to explain what would happen in a normal workflow and what information is needed to proceed.\\n\\nIn a typical scenario, I would:\\n1. Extract the case number from the user message\\n2. Retrieve customer details from the case context\\n3. Understand the customer\u0027s request from the classification and sentiment analysis\\n4. Search for an appropriate template based on the request category\\n5. Either use an existing template or create a new one\\n6. Provide the template data structure for the email generator\\n\\nWithout the actual case information, I cannot complete these steps. To proceed, I would need at minimum:\\n- A valid case number\\n- Customer name and email\\n- The nature of the customer\u0027s inquiry\\n- The classification category of the request\\n- Any sentiment information that might affect tone\\n\\nIf you can provide this information, I would be able to generate an appropriate email template response. Please provide the actual case details rather than the \\\"UNRESOLVED\\\" placeholders so I can assist you properly.\", \"model_client_id\": \"openrouter_claude_sonnet\", \"agent_type\": \"assistant\", \"model\": \"anthropic/claude-3.7-sonnet\", \"provider\": \"openrouter\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 2523, \"completion_tokens\": 285, \"total_tokens\": 2808, \"estimated_cost\": {\"amount\": 0.09279, \"currency\": \"USD\"}, \"model\": \"anthropic/claude-3.7-sonnet\", \"provider\": \"openrouter\"}}",
"output_format": "text",
"return_code": 0,
"status": "completed",
"stderr": "",
"token_usage": {
"completion_tokens": 285,
"estimated_cost": {
"amount": 0.09279,
"currency": "USD"
},
"model": "anthropic/claude-3.7-sonnet",
"prompt_tokens": 2523,
"provider": "openrouter",
"total_tokens": 2808
}
},
"duration_seconds": 10.144225,
"end_time": "2025-08-25T05:38:46.129063",
"message_sent": true,
"start_time": "2025-08-25T05:38:35.984838",
"timestamp": "2025-08-25T05:38:46.129063",
"worker_executed": true,
"workers_notified": true
},
"model": "anthropic/claude-3.7-sonnet",
"model_client_id": "openrouter_claude_sonnet",
"output": "I notice that the case information is marked as \"UNRESOLVED\" in your request, which means I don\u0027t have the actual case data to work with. To properly generate an email template, I need specific case details like the case number, customer information, and the nature of their inquiry.\n\nSince I don\u0027t have access to the actual case data, I\u0027ll need to explain what would happen in a normal workflow and what information is needed to proceed.\n\nIn a typical scenario, I would:\n1. Extract the case number from the user message\n2. Retrieve customer details from the case context\n3. Understand the customer\u0027s request from the classification and sentiment analysis\n4. Search for an appropriate template based on the request category\n5. Either use an existing template or create a new one\n6. Provide the template data structure for the email generator\n\nWithout the actual case information, I cannot complete these steps. To proceed, I would need at minimum:\n- A valid case number\n- Customer name and email\n- The nature of the customer\u0027s inquiry\n- The classification category of the request\n- Any sentiment information that might affect tone\n\nIf you can provide this information, I would be able to generate an appropriate email template response. Please provide the actual case details rather than the \"UNRESOLVED\" placeholders so I can assist you properly.\n__OUTPUTS__ {\"ai_response\": \"I notice that the case information is marked as \\\"UNRESOLVED\\\" in your request, which means I don\u0027t have the actual case data to work with. To properly generate an email template, I need specific case details like the case number, customer information, and the nature of their inquiry.\\n\\nSince I don\u0027t have access to the actual case data, I\u0027ll need to explain what would happen in a normal workflow and what information is needed to proceed.\\n\\nIn a typical scenario, I would:\\n1. Extract the case number from the user message\\n2. Retrieve customer details from the case context\\n3. Understand the customer\u0027s request from the classification and sentiment analysis\\n4. Search for an appropriate template based on the request category\\n5. Either use an existing template or create a new one\\n6. Provide the template data structure for the email generator\\n\\nWithout the actual case information, I cannot complete these steps. To proceed, I would need at minimum:\\n- A valid case number\\n- Customer name and email\\n- The nature of the customer\u0027s inquiry\\n- The classification category of the request\\n- Any sentiment information that might affect tone\\n\\nIf you can provide this information, I would be able to generate an appropriate email template response. Please provide the actual case details rather than the \\\"UNRESOLVED\\\" placeholders so I can assist you properly.\", \"model_client_id\": \"openrouter_claude_sonnet\", \"agent_type\": \"assistant\", \"model\": \"anthropic/claude-3.7-sonnet\", \"provider\": \"openrouter\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 2523, \"completion_tokens\": 285, \"total_tokens\": 2808, \"estimated_cost\": {\"amount\": 0.09279, \"currency\": \"USD\"}, \"model\": \"anthropic/claude-3.7-sonnet\", \"provider\": \"openrouter\"}}",
"provider": "openrouter",
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "template_router_agent",
"token_usage": {
"completion_tokens": 285,
"estimated_cost": {
"amount": 0.09279,
"currency": "USD"
},
"model": "anthropic/claude-3.7-sonnet",
"prompt_tokens": 2523,
"provider": "openrouter",
"total_tokens": 2808
}
}
},
"template_router_agent": {
"agent_type": "assistant",
"ai_response": "I notice that the case information is marked as \"UNRESOLVED\" in your request, which means I don\u0027t have the actual case data to work with. To properly generate an email template, I need specific case details like the case number, customer information, and the nature of their inquiry.\n\nSince I don\u0027t have access to the actual case data, I\u0027ll need to explain what would happen in a normal workflow and what information is needed to proceed.\n\nIn a typical scenario, I would:\n1. Extract the case number from the user message\n2. Retrieve customer details from the case context\n3. Understand the customer\u0027s request from the classification and sentiment analysis\n4. Search for an appropriate template based on the request category\n5. Either use an existing template or create a new one\n6. Provide the template data structure for the email generator\n\nWithout the actual case information, I cannot complete these steps. To proceed, I would need at minimum:\n- A valid case number\n- Customer name and email\n- The nature of the customer\u0027s inquiry\n- The classification category of the request\n- Any sentiment information that might affect tone\n\nIf you can provide this information, I would be able to generate an appropriate email template response. Please provide the actual case details rather than the \"UNRESOLVED\" placeholders so I can assist you properly.",
"execution_details": {
"actual_result": {
"agent_type": "assistant",
"execution_details": {
"agent_type": "assistant",
"input_length": 1442,
"model": "anthropic/claude-3.7-sonnet",
"output_length": 1347,
"provider": "openrouter",
"system_message": "# Template Router Agent - Final Phase\n\nYou are responsible for finding or creating email templates and providing template data.\n\n## CRITICAL: USE EXTRACTED CASE NUMBER\nYou will receive the case number from the user_message.\nUse this case number consistently throughout.\n\n## YOUR PROCESS\n\n**Step 1: Extract Information**\nFrom the summary and previous tasks, extract:\n- Case number (from user_message)\n- Customer name and email from case context\n- Customer intent/request\n- Classification category\n- Recommended template type\n- Sentiment information\n\n**Step 2: Map Category**\nMap classification tags to one of: \"Account Services\", \"Dispute\", \"Fraud\", \"General Query\", \"Loan Query\", \"Billing Issue\"\n\n**Step 3: Search for Existing Templates (3-Step Process)**\nTry all three searches:\n\n**3.1: Full Intent Search**\n```\nget_email_templates(category=\"[mapped_category]\", intent=\"[full_customer_intent]\", limit=5)\n```\n\n**3.2: Simplified Intent Search (if Step 3.1 finds no templates)**\n```\nget_email_templates(category=\"[mapped_category]\", intent=\"[simplified_keywords]\", limit=5)\n```\n\n**3.3: Category Only Search (if Step 3.2 finds no templates)**\n```\nget_email_templates(category=\"[mapped_category]\", limit=5)\n```\n\n**Step 4: Evaluate Template Results**\nFor any templates found, check:\n- \u0027name\u0027 field for template description\n- \u0027intent\u0027 field for relevance match (80%+ similarity required)\n- \u0027is_approval\u0027 field (prefer approved templates)\n\n**Step 5A: If Good Template Found (80%+ similarity)**\n1. Use get_template_by_id() to retrieve full template details\n2. End with: \"EMAIL_CONTENT_UPDATED_SUCCESSFULLY using existing template ID: [template_id]\"\n\n**Step 5B: If No Good Template Found**\nCall insert_email_templates tool and then provide template data structure.\n\n**Step 6: Always Provide Template Data Structure**\nAlways end your response with this EXACT format:\n```\nTEMPLATE_DATA_FOR_EMAIL_GENERATOR:\n{\n \"template_id\": \"[UUID_from_tool_response]\",\n \"case_number\": \"[case_number]\",\n \"customer_name\": \"[Customer_Name]\",\n \"customer_email\": \"[Customer_Email]\",\n \"recommended_template\": \"[resolved/followup/rejected]\",\n \"resolved_template\": {\n \"subject\": \"Your Inquiry - Case [case_number] - Resolved\",\n \"body\": \"Template body content here\"\n },\n \"followup_template\": {\n \"subject\": \"Update on Your Inquiry - Case [case_number]\",\n \"body\": \"Template body content here\"\n },\n \"rejected_template\": {\n \"subject\": \"Regarding Your Inquiry - Case [case_number]\",\n \"body\": \"Template body content here\"\n },\n \"signature\": \"\u003cp\u003eBest Regards,\u003c/p\u003e\u003cp\u003eCustomer Support Team\u003c/p\u003e\u003cp\u003eNationwide/ XYZ Bank\u003c/p\u003e\",\n \"is_approved\": false\n}\n```\n\n## SUCCESS MESSAGE\nEnd with: \"TEMPLATE_CREATED_SUCCESSFULLY and stored in database with ID: [template_id]\"\n"
},
"input_format": "text",
"model_client_id": "openrouter_claude_sonnet",
"output": "I notice that the case information is marked as \"UNRESOLVED\" in your request, which means I don\u0027t have the actual case data to work with. To properly generate an email template, I need specific case details like the case number, customer information, and the nature of their inquiry.\n\nSince I don\u0027t have access to the actual case data, I\u0027ll need to explain what would happen in a normal workflow and what information is needed to proceed.\n\nIn a typical scenario, I would:\n1. Extract the case number from the user message\n2. Retrieve customer details from the case context\n3. Understand the customer\u0027s request from the classification and sentiment analysis\n4. Search for an appropriate template based on the request category\n5. Either use an existing template or create a new one\n6. Provide the template data structure for the email generator\n\nWithout the actual case information, I cannot complete these steps. To proceed, I would need at minimum:\n- A valid case number\n- Customer name and email\n- The nature of the customer\u0027s inquiry\n- The classification category of the request\n- Any sentiment information that might affect tone\n\nIf you can provide this information, I would be able to generate an appropriate email template response. Please provide the actual case details rather than the \"UNRESOLVED\" placeholders so I can assist you properly.\n__OUTPUTS__ {\"ai_response\": \"I notice that the case information is marked as \\\"UNRESOLVED\\\" in your request, which means I don\u0027t have the actual case data to work with. To properly generate an email template, I need specific case details like the case number, customer information, and the nature of their inquiry.\\n\\nSince I don\u0027t have access to the actual case data, I\u0027ll need to explain what would happen in a normal workflow and what information is needed to proceed.\\n\\nIn a typical scenario, I would:\\n1. Extract the case number from the user message\\n2. Retrieve customer details from the case context\\n3. Understand the customer\u0027s request from the classification and sentiment analysis\\n4. Search for an appropriate template based on the request category\\n5. Either use an existing template or create a new one\\n6. Provide the template data structure for the email generator\\n\\nWithout the actual case information, I cannot complete these steps. To proceed, I would need at minimum:\\n- A valid case number\\n- Customer name and email\\n- The nature of the customer\u0027s inquiry\\n- The classification category of the request\\n- Any sentiment information that might affect tone\\n\\nIf you can provide this information, I would be able to generate an appropriate email template response. Please provide the actual case details rather than the \\\"UNRESOLVED\\\" placeholders so I can assist you properly.\", \"model_client_id\": \"openrouter_claude_sonnet\", \"agent_type\": \"assistant\", \"model\": \"anthropic/claude-3.7-sonnet\", \"provider\": \"openrouter\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 2523, \"completion_tokens\": 285, \"total_tokens\": 2808, \"estimated_cost\": {\"amount\": 0.09279, \"currency\": \"USD\"}, \"model\": \"anthropic/claude-3.7-sonnet\", \"provider\": \"openrouter\"}}",
"output_format": "text",
"return_code": 0,
"status": "completed",
"stderr": "",
"token_usage": {
"completion_tokens": 285,
"estimated_cost": {
"amount": 0.09279,
"currency": "USD"
},
"model": "anthropic/claude-3.7-sonnet",
"prompt_tokens": 2523,
"provider": "openrouter",
"total_tokens": 2808
}
},
"duration_seconds": 10.144225,
"end_time": "2025-08-25T05:38:46.129063",
"message_sent": true,
"start_time": "2025-08-25T05:38:35.984838",
"timestamp": "2025-08-25T05:38:46.129063",
"worker_executed": true,
"workers_notified": true
},
"model": "anthropic/claude-3.7-sonnet",
"model_client_id": "openrouter_claude_sonnet",
"output": "I notice that the case information is marked as \"UNRESOLVED\" in your request, which means I don\u0027t have the actual case data to work with. To properly generate an email template, I need specific case details like the case number, customer information, and the nature of their inquiry.\n\nSince I don\u0027t have access to the actual case data, I\u0027ll need to explain what would happen in a normal workflow and what information is needed to proceed.\n\nIn a typical scenario, I would:\n1. Extract the case number from the user message\n2. Retrieve customer details from the case context\n3. Understand the customer\u0027s request from the classification and sentiment analysis\n4. Search for an appropriate template based on the request category\n5. Either use an existing template or create a new one\n6. Provide the template data structure for the email generator\n\nWithout the actual case information, I cannot complete these steps. To proceed, I would need at minimum:\n- A valid case number\n- Customer name and email\n- The nature of the customer\u0027s inquiry\n- The classification category of the request\n- Any sentiment information that might affect tone\n\nIf you can provide this information, I would be able to generate an appropriate email template response. Please provide the actual case details rather than the \"UNRESOLVED\" placeholders so I can assist you properly.\n__OUTPUTS__ {\"ai_response\": \"I notice that the case information is marked as \\\"UNRESOLVED\\\" in your request, which means I don\u0027t have the actual case data to work with. To properly generate an email template, I need specific case details like the case number, customer information, and the nature of their inquiry.\\n\\nSince I don\u0027t have access to the actual case data, I\u0027ll need to explain what would happen in a normal workflow and what information is needed to proceed.\\n\\nIn a typical scenario, I would:\\n1. Extract the case number from the user message\\n2. Retrieve customer details from the case context\\n3. Understand the customer\u0027s request from the classification and sentiment analysis\\n4. Search for an appropriate template based on the request category\\n5. Either use an existing template or create a new one\\n6. Provide the template data structure for the email generator\\n\\nWithout the actual case information, I cannot complete these steps. To proceed, I would need at minimum:\\n- A valid case number\\n- Customer name and email\\n- The nature of the customer\u0027s inquiry\\n- The classification category of the request\\n- Any sentiment information that might affect tone\\n\\nIf you can provide this information, I would be able to generate an appropriate email template response. Please provide the actual case details rather than the \\\"UNRESOLVED\\\" placeholders so I can assist you properly.\", \"model_client_id\": \"openrouter_claude_sonnet\", \"agent_type\": \"assistant\", \"model\": \"anthropic/claude-3.7-sonnet\", \"provider\": \"openrouter\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 2523, \"completion_tokens\": 285, \"total_tokens\": 2808, \"estimated_cost\": {\"amount\": 0.09279, \"currency\": \"USD\"}, \"model\": \"anthropic/claude-3.7-sonnet\", \"provider\": \"openrouter\"}}",
"provider": "openrouter",
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "template_router_agent",
"token_usage": {
"completion_tokens": 285,
"estimated_cost": {
"amount": 0.09279,
"currency": "USD"
},
"model": "anthropic/claude-3.7-sonnet",
"prompt_tokens": 2523,
"provider": "openrouter",
"total_tokens": 2808
}
}
}