Complete Execution Output (JSON):
{
"case_context_agent": {
"error": "Error code: 403 - {\u0027error\u0027: {\u0027message\u0027: \u0027Key limit exceeded. Manage it using https://openrouter.ai/settings/keys\u0027, \u0027code\u0027: 403}}",
"execution_details": {
"failed": true,
"message_sent": true,
"worker_executed": true,
"workers_notified": true
},
"output": "Task failed: Error code: 403 - {\u0027error\u0027: {\u0027message\u0027: \u0027Key limit exceeded. Manage it using https://openrouter.ai/settings/keys\u0027, \u0027code\u0027: 403}}",
"status": "FAILED",
"task_id": "case_context_agent"
},
"case_number_extractor": {
"case_number": "EXTRACTION_FAILED",
"execution_details": {
"actual_result": {
"output": "DEBUG: Orchestrator result: NEW_CASE_CREATED - Case #UNRESOLVED_customer_email\nERROR: Could not extract case number from: NEW_CASE_CREATED - Case #UNRESOLVED_customer_email\nDEBUG: Extracted case number: EXTRACTION_FAILED\nDEBUG: Processing type: error\n__OUTPUTS__ {\"case_number\": \"EXTRACTION_FAILED\", \"processing_type\": \"error\", \"original_response\": \"NEW_CASE_CREATED - Case #UNRESOLVED_customer_email\"}\n",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 0.24782,
"end_time": "2025-08-26T09:27:08.778446",
"message_sent": true,
"start_time": "2025-08-26T09:27:08.530626",
"timestamp": "2025-08-26T09:27:08.778446",
"worker_executed": true,
"workers_notified": true
},
"original_response": "NEW_CASE_CREATED - Case #UNRESOLVED_customer_email",
"output": "DEBUG: Orchestrator result: NEW_CASE_CREATED - Case #UNRESOLVED_customer_email\nERROR: Could not extract case number from: NEW_CASE_CREATED - Case #UNRESOLVED_customer_email\nDEBUG: Extracted case number: EXTRACTION_FAILED\nDEBUG: Processing type: error\n__OUTPUTS__ {\"case_number\": \"EXTRACTION_FAILED\", \"processing_type\": \"error\", \"original_response\": \"NEW_CASE_CREATED - Case #UNRESOLVED_customer_email\"}\n",
"processing_type": "error",
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "case_number_extractor"
},
"case_orchestrator": {
"agent_type": "assistant",
"ai_response": "NEW_CASE_CREATED - Case #UNRESOLVED_customer_email",
"execution_details": {
"actual_result": {
"agent_type": "assistant",
"execution_details": {
"agent_type": "assistant",
"input_length": 74,
"model": "gpt-4.1-2025-04-14",
"output_length": 50,
"provider": "openai",
"system_message": "# Case Orchestrator Agent - Phase 1: Case Detection/Creation\n\nYou are responsible for the FIRST PHASE of the workflow: case detection and creation/retrieval.\n\n## CRITICAL: ALWAYS END WITH EXACT CASE NUMBER EXTRACTION\nYour response MUST always end with ONE of these EXACT formats:\n- \"DUPLICATE_PROCESSED - Case linked to #[actual_case_number]\"\n- \"CASE_RETRIEVED_FOR_UPDATE - Case #[actual_case_number]\" \n- \"NEW_CASE_CREATED - Case #[actual_case_number]\"\n\n## YOUR PROCESS\n\n**Step 1: Parse Input and Detect Duplicates**\n- Extract email address from sender field\n- Check for case references in subject/body (Case #XXXXX, Re:, ticket number)\n- Use search_cases_by_email to find existing cases\n- Analyze for duplicate content and core issue similarity\n\n**Step 2: Handle Based on Detection Results**\n\n**If CASE_REFERENCE_DETECTED:**\n- Extract case number from subject/body\n- Use get_case to retrieve case details\n- **If case exists**: End with \"CASE_RETRIEVED_FOR_UPDATE - Case #[actual_case_number]\"\n- **If case does NOT exist**: Call create_case() to create a NEW case\n- **CRITICAL**: Extract the NEW CaseNumber from the create_case response\n- End with \"NEW_CASE_CREATED - Case #[new_case_number_from_create_response]\"\n\n**If DUPLICATE_FOUND:**\n- Create duplicate case with create_case (status: \"Rejected\")\n- Extract actual CaseNumber from create_case response\n- Call manage_duplicate_priority for priority escalation\n- Call send_duplicate_acknowledgement to notify customer\n- End with \"DUPLICATE_PROCESSED - Case linked to #[actual_case_number_from_response]\"\n\n**If NO_DUPLICATE and NO_CASE_REFERENCE:**\n- Create new case with create_case\n- Extract ACTUAL CaseNumber from the create_case response\n- End with \"NEW_CASE_CREATED - Case #[actual_case_number_from_response]\"\n\n**If TECHNICAL_ERROR (like case not found):**\n- Create a new case to ensure workflow continues\n- Extract ACTUAL CaseNumber from create_case response\n- End with \"NEW_CASE_CREATED - Case #[actual_case_number_from_response]\"\n\n## CRITICAL RULES FOR CASE NUMBER EXTRACTION\n1. **ALWAYS extract actual case numbers from tool responses**\n2. When you call create_case, look for \"CaseNumber\" or \"case_number\" in the response\n3. When you call get_case, look for \"CaseNumber\" in the response\n4. **NEVER use placeholder numbers** - always use the actual numbers returned by tools\n5. **NEVER use referenced case numbers if the case doesn\u0027t exist** - create NEW case instead\n6. **ALWAYS end with one of the three exact status phrases above with REAL case numbers**\n7. If any tool fails, create a new case to keep workflow moving\n8. Never return technical error messages - always provide a status with actual case number\n\n## EXAMPLE CORRECT PROCESSING:\n```\nInput: Email references \"Case #00001942\" but case doesn\u0027t exist\n\n1. Call get_case(\"00001942\") \u2192 Error: Case not found\n2. Call create_case(...) \u2192 Response: {\"CaseNumber\": \"00001994\", \"Id\": \"500XYZ\"}\n3. Extract \"00001994\" from response\n4. Output: \"NEW_CASE_CREATED - Case #00001994\"\n```\n\n## NEVER DO THIS:\n\u274c \"NEW_CASE_CREATED - Case #00001942\" (using non-existent case number)\n\u274c \"NEW_CASE_CREATED - Case #PLACEHOLDER\" (using placeholder)\n\n## ALWAYS DO THIS:\n\u2705 \"NEW_CASE_CREATED - Case #00001994\" (using actual number from create_case response)\n\u2705 \"CASE_RETRIEVED_FOR_UPDATE - Case #00001942\" (using actual number from get_case response)\n"
},
"input_format": "text",
"model_client_id": "gpt4.1",
"output": "NEW_CASE_CREATED - Case #UNRESOLVED_customer_email\n__OUTPUTS__ {\"ai_response\": \"NEW_CASE_CREATED - Case #UNRESOLVED_customer_email\", \"model_client_id\": \"gpt4.1\", \"agent_type\": \"assistant\", \"model\": \"gpt-4.1-2025-04-14\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 6308, \"completion_tokens\": 154, \"total_tokens\": 6462, \"estimated_cost\": {\"amount\": 0.19848, \"currency\": \"USD\"}, \"model\": \"gpt-4.1-2025-04-14\", \"provider\": \"openai\"}}",
"output_format": "text",
"return_code": 0,
"status": "completed",
"stderr": "",
"token_usage": {
"completion_tokens": 154,
"estimated_cost": {
"amount": 0.19848,
"currency": "USD"
},
"model": "gpt-4.1-2025-04-14",
"prompt_tokens": 6308,
"provider": "openai",
"total_tokens": 6462
}
},
"duration_seconds": 11.885074,
"end_time": "2025-08-26T09:27:08.489320",
"message_sent": true,
"start_time": "2025-08-26T09:26:56.604246",
"timestamp": "2025-08-26T09:27:08.489320",
"worker_executed": true,
"workers_notified": true
},
"model": "gpt-4.1-2025-04-14",
"model_client_id": "gpt4.1",
"output": "NEW_CASE_CREATED - Case #UNRESOLVED_customer_email\n__OUTPUTS__ {\"ai_response\": \"NEW_CASE_CREATED - Case #UNRESOLVED_customer_email\", \"model_client_id\": \"gpt4.1\", \"agent_type\": \"assistant\", \"model\": \"gpt-4.1-2025-04-14\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 6308, \"completion_tokens\": 154, \"total_tokens\": 6462, \"estimated_cost\": {\"amount\": 0.19848, \"currency\": \"USD\"}, \"model\": \"gpt-4.1-2025-04-14\", \"provider\": \"openai\"}}",
"provider": "openai",
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "case_orchestrator",
"token_usage": {
"completion_tokens": 154,
"estimated_cost": {
"amount": 0.19848,
"currency": "USD"
},
"model": "gpt-4.1-2025-04-14",
"prompt_tokens": 6308,
"provider": "openai",
"total_tokens": 6462
}
},
"classification_agent": {
"agent_type": "assistant",
"ai_response": "{\n \"classification\": {\n \"priority\": \"Medium\",\n \"tags\": [\"General Inquiry\"],\n \"justification\": \"The email reference \u0027UNRESOLVED_customer_email\u0027 does not provide specific details about the content of the customer\u0027s message. Without additional context, it is best classified as a general inquiry with medium priority.\",\n \"confidence_score\": 0.60\n }\n}",
"execution_details": {
"actual_result": {
"agent_type": "assistant",
"execution_details": {
"agent_type": "assistant",
"input_length": 118,
"model": "gpt-4.1-2025-04-14",
"output_length": 381,
"provider": "openai",
"system_message": "You are an AI assistant that classifies customer emails for a financial institution.\n\nClassify the email and return ONLY a JSON response in this exact format:\n\n{\n \"classification\": {\n \"priority\": \"High\",\n \"tags\": [\"Dispute Related\", \"Transaction Issues\"],\n \"justification\": \"Explanation for classification\",\n \"confidence_score\": 0.95\n }\n}\n\nPriority levels: \"Urgent\", \"High\", \"Medium\", \"Low\"\n\nCommon tags:\n- Fraud Alert/Report\n- Dispute Related \n- Transaction Issues\n- Account Services\n- Loan Related\n- Technical Support\n- General Inquiry\n"
},
"input_format": "text",
"model_client_id": "gpt4.1",
"output": "{\n \"classification\": {\n \"priority\": \"Medium\",\n \"tags\": [\"General Inquiry\"],\n \"justification\": \"The email reference \u0027UNRESOLVED_customer_email\u0027 does not provide specific details about the content of the customer\u0027s message. Without additional context, it is best classified as a general inquiry with medium priority.\",\n \"confidence_score\": 0.60\n }\n}\n__OUTPUTS__ {\"ai_response\": \"{\\n \\\"classification\\\": {\\n \\\"priority\\\": \\\"Medium\\\",\\n \\\"tags\\\": [\\\"General Inquiry\\\"],\\n \\\"justification\\\": \\\"The email reference \u0027UNRESOLVED_customer_email\u0027 does not provide specific details about the content of the customer\u0027s message. Without additional context, it is best classified as a general inquiry with medium priority.\\\",\\n \\\"confidence_score\\\": 0.60\\n }\\n}\", \"model_client_id\": \"gpt4.1\", \"agent_type\": \"assistant\", \"model\": \"gpt-4.1-2025-04-14\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 200, \"completion_tokens\": 80, \"total_tokens\": 280, \"estimated_cost\": {\"amount\": 0.0108, \"currency\": \"USD\"}, \"model\": \"gpt-4.1-2025-04-14\", \"provider\": \"openai\"}}",
"output_format": "text",
"return_code": 0,
"status": "completed",
"stderr": "",
"token_usage": {
"completion_tokens": 80,
"estimated_cost": {
"amount": 0.0108,
"currency": "USD"
},
"model": "gpt-4.1-2025-04-14",
"prompt_tokens": 200,
"provider": "openai",
"total_tokens": 280
}
},
"duration_seconds": 2.09992,
"end_time": "2025-08-26T09:30:11.284207",
"message_sent": true,
"start_time": "2025-08-26T09:30:09.184287",
"timestamp": "2025-08-26T09:30:11.284207",
"worker_executed": true,
"workers_notified": true
},
"model": "gpt-4.1-2025-04-14",
"model_client_id": "gpt4.1",
"output": "{\n \"classification\": {\n \"priority\": \"Medium\",\n \"tags\": [\"General Inquiry\"],\n \"justification\": \"The email reference \u0027UNRESOLVED_customer_email\u0027 does not provide specific details about the content of the customer\u0027s message. Without additional context, it is best classified as a general inquiry with medium priority.\",\n \"confidence_score\": 0.60\n }\n}\n__OUTPUTS__ {\"ai_response\": \"{\\n \\\"classification\\\": {\\n \\\"priority\\\": \\\"Medium\\\",\\n \\\"tags\\\": [\\\"General Inquiry\\\"],\\n \\\"justification\\\": \\\"The email reference \u0027UNRESOLVED_customer_email\u0027 does not provide specific details about the content of the customer\u0027s message. Without additional context, it is best classified as a general inquiry with medium priority.\\\",\\n \\\"confidence_score\\\": 0.60\\n }\\n}\", \"model_client_id\": \"gpt4.1\", \"agent_type\": \"assistant\", \"model\": \"gpt-4.1-2025-04-14\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 200, \"completion_tokens\": 80, \"total_tokens\": 280, \"estimated_cost\": {\"amount\": 0.0108, \"currency\": \"USD\"}, \"model\": \"gpt-4.1-2025-04-14\", \"provider\": \"openai\"}}",
"provider": "openai",
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "classification_agent",
"token_usage": {
"completion_tokens": 80,
"estimated_cost": {
"amount": 0.0108,
"currency": "USD"
},
"model": "gpt-4.1-2025-04-14",
"prompt_tokens": 200,
"provider": "openai",
"total_tokens": 280
}
},
"email_generator_agent": {
"error": "Error code: 403 - {\u0027error\u0027: {\u0027message\u0027: \u0027Key limit exceeded. Manage it using https://openrouter.ai/settings/keys\u0027, \u0027code\u0027: 403}}",
"execution_details": {
"failed": true,
"message_sent": true,
"worker_executed": true,
"workers_notified": true
},
"output": "Task failed: Error code: 403 - {\u0027error\u0027: {\u0027message\u0027: \u0027Key limit exceeded. Manage it using https://openrouter.ai/settings/keys\u0027, \u0027code\u0027: 403}}",
"status": "FAILED",
"task_id": "email_generator_agent"
},
"execution_summary": {
"completed_tasks": 5,
"dependencies_detected": false,
"end_time": "2025-08-26T09:39:12.130280",
"execution_mode": "distributed",
"start_time": "2025-08-26T09:26:55.688756",
"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": 0.00059,
"ended_at": "2025-08-26T09:27:08.938332",
"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\": 0.00059, \"started_at\": \"2025-08-26T09:27:08.937742\", \"ended_at\": \"2025-08-26T09:27:08.938332\"}",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 0.216626,
"end_time": "2025-08-26T09:27:09.026403",
"message_sent": true,
"start_time": "2025-08-26T09:27:08.809777",
"timestamp": "2025-08-26T09:27:09.026403",
"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\": 0.00059, \"started_at\": \"2025-08-26T09:27:08.937742\", \"ended_at\": \"2025-08-26T09:27:08.938332\"}",
"return_code": 0,
"route_reason": "no_conditions_matched",
"router_type": "condition",
"selected_route": "continue_analysis",
"started_at": "2025-08-26T09:27:08.937742",
"status": "completed",
"stderr": "",
"task_id": "phase_router"
},
"sentiment_analysis_agent": {
"agent_type": "assistant",
"ai_response": "{\n \"sentiment_score\": -0.4,\n \"primary_tone\": \"Concerned\",\n \"emotional_indicators\": {\n \"frustration_level\": \"Medium\",\n \"satisfaction\": \"Low\"\n },\n \"context_notes\": \"The customer\u0027s unresolved case likely generates concern and low satisfaction, indicating some level of frustration with the lack of resolution.\"\n}",
"execution_details": {
"actual_result": {
"agent_type": "assistant",
"execution_details": {
"agent_type": "assistant",
"input_length": 130,
"model": "gpt-4o",
"output_length": 320,
"provider": "openai",
"system_message": "You are a sentiment analysis agent. Analyze the customer email and return ONLY a JSON response:\n\n{\n \"sentiment_score\": -0.4,\n \"primary_tone\": \"Concerned\",\n \"emotional_indicators\": {\n \"frustration_level\": \"Medium\",\n \"satisfaction\": \"Low\"\n },\n \"context_notes\": \"Brief explanation\"\n}\n\nSentiment score: -1.0 to 1.0\nPrimary tone: Angry, Frustrated, Concerned, Neutral, Satisfied, Appreciative, Mixed\nFrustration level: None, Low, Medium, High\nSatisfaction: Very Low, Low, Neutral, High, Very High, Mixed\n"
},
"input_format": "text",
"model_client_id": "gpt4_sentiment",
"output": "{\n \"sentiment_score\": -0.4,\n \"primary_tone\": \"Concerned\",\n \"emotional_indicators\": {\n \"frustration_level\": \"Medium\",\n \"satisfaction\": \"Low\"\n },\n \"context_notes\": \"The customer\u0027s unresolved case likely generates concern and low satisfaction, indicating some level of frustration with the lack of resolution.\"\n}\n__OUTPUTS__ {\"ai_response\": \"{\\n \\\"sentiment_score\\\": -0.4,\\n \\\"primary_tone\\\": \\\"Concerned\\\",\\n \\\"emotional_indicators\\\": {\\n \\\"frustration_level\\\": \\\"Medium\\\",\\n \\\"satisfaction\\\": \\\"Low\\\"\\n },\\n \\\"context_notes\\\": \\\"The customer\u0027s unresolved case likely generates concern and low satisfaction, indicating some level of frustration with the lack of resolution.\\\"\\n}\", \"model_client_id\": \"gpt4_sentiment\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 215, \"completion_tokens\": 79, \"total_tokens\": 294, \"estimated_cost\": {\"amount\": 0.00226, \"currency\": \"USD\"}, \"model\": \"gpt-4o\", \"provider\": \"openai\"}}",
"output_format": "text",
"return_code": 0,
"status": "completed",
"stderr": "",
"token_usage": {
"completion_tokens": 79,
"estimated_cost": {
"amount": 0.00226,
"currency": "USD"
},
"model": "gpt-4o",
"prompt_tokens": 215,
"provider": "openai",
"total_tokens": 294
}
},
"duration_seconds": 2.422798,
"end_time": "2025-08-26T09:30:11.674627",
"message_sent": true,
"start_time": "2025-08-26T09:30:09.251829",
"timestamp": "2025-08-26T09:30:11.674627",
"worker_executed": true,
"workers_notified": true
},
"model": "gpt-4o",
"model_client_id": "gpt4_sentiment",
"output": "{\n \"sentiment_score\": -0.4,\n \"primary_tone\": \"Concerned\",\n \"emotional_indicators\": {\n \"frustration_level\": \"Medium\",\n \"satisfaction\": \"Low\"\n },\n \"context_notes\": \"The customer\u0027s unresolved case likely generates concern and low satisfaction, indicating some level of frustration with the lack of resolution.\"\n}\n__OUTPUTS__ {\"ai_response\": \"{\\n \\\"sentiment_score\\\": -0.4,\\n \\\"primary_tone\\\": \\\"Concerned\\\",\\n \\\"emotional_indicators\\\": {\\n \\\"frustration_level\\\": \\\"Medium\\\",\\n \\\"satisfaction\\\": \\\"Low\\\"\\n },\\n \\\"context_notes\\\": \\\"The customer\u0027s unresolved case likely generates concern and low satisfaction, indicating some level of frustration with the lack of resolution.\\\"\\n}\", \"model_client_id\": \"gpt4_sentiment\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 215, \"completion_tokens\": 79, \"total_tokens\": 294, \"estimated_cost\": {\"amount\": 0.00226, \"currency\": \"USD\"}, \"model\": \"gpt-4o\", \"provider\": \"openai\"}}",
"provider": "openai",
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "sentiment_analysis_agent",
"token_usage": {
"completion_tokens": 79,
"estimated_cost": {
"amount": 0.00226,
"currency": "USD"
},
"model": "gpt-4o",
"prompt_tokens": 215,
"provider": "openai",
"total_tokens": 294
}
},
"status": "FAILED",
"summary_agent": {
"error": "Error code: 403 - {\u0027error\u0027: {\u0027message\u0027: \u0027Key limit exceeded. Manage it using https://openrouter.ai/settings/keys\u0027, \u0027code\u0027: 403}}",
"execution_details": {
"failed": true,
"message_sent": true,
"worker_executed": true,
"workers_notified": true
},
"output": "Task failed: Error code: 403 - {\u0027error\u0027: {\u0027message\u0027: \u0027Key limit exceeded. Manage it using https://openrouter.ai/settings/keys\u0027, \u0027code\u0027: 403}}",
"status": "FAILED",
"task_id": "summary_agent"
},
"task_outputs": {
"case_context_agent": {
"error": "Error code: 403 - {\u0027error\u0027: {\u0027message\u0027: \u0027Key limit exceeded. Manage it using https://openrouter.ai/settings/keys\u0027, \u0027code\u0027: 403}}",
"execution_details": {
"failed": true,
"message_sent": true,
"worker_executed": true,
"workers_notified": true
},
"output": "Task failed: Error code: 403 - {\u0027error\u0027: {\u0027message\u0027: \u0027Key limit exceeded. Manage it using https://openrouter.ai/settings/keys\u0027, \u0027code\u0027: 403}}",
"status": "FAILED",
"task_id": "case_context_agent"
},
"case_number_extractor": {
"case_number": "EXTRACTION_FAILED",
"execution_details": {
"actual_result": {
"output": "DEBUG: Orchestrator result: NEW_CASE_CREATED - Case #UNRESOLVED_customer_email\nERROR: Could not extract case number from: NEW_CASE_CREATED - Case #UNRESOLVED_customer_email\nDEBUG: Extracted case number: EXTRACTION_FAILED\nDEBUG: Processing type: error\n__OUTPUTS__ {\"case_number\": \"EXTRACTION_FAILED\", \"processing_type\": \"error\", \"original_response\": \"NEW_CASE_CREATED - Case #UNRESOLVED_customer_email\"}\n",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 0.24782,
"end_time": "2025-08-26T09:27:08.778446",
"message_sent": true,
"start_time": "2025-08-26T09:27:08.530626",
"timestamp": "2025-08-26T09:27:08.778446",
"worker_executed": true,
"workers_notified": true
},
"original_response": "NEW_CASE_CREATED - Case #UNRESOLVED_customer_email",
"output": "DEBUG: Orchestrator result: NEW_CASE_CREATED - Case #UNRESOLVED_customer_email\nERROR: Could not extract case number from: NEW_CASE_CREATED - Case #UNRESOLVED_customer_email\nDEBUG: Extracted case number: EXTRACTION_FAILED\nDEBUG: Processing type: error\n__OUTPUTS__ {\"case_number\": \"EXTRACTION_FAILED\", \"processing_type\": \"error\", \"original_response\": \"NEW_CASE_CREATED - Case #UNRESOLVED_customer_email\"}\n",
"processing_type": "error",
"return_code": 0,
"status": "completed",
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"task_id": "case_number_extractor"
},
"case_orchestrator": {
"agent_type": "assistant",
"ai_response": "NEW_CASE_CREATED - Case #UNRESOLVED_customer_email",
"execution_details": {
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"system_message": "# Case Orchestrator Agent - Phase 1: Case Detection/Creation\n\nYou are responsible for the FIRST PHASE of the workflow: case detection and creation/retrieval.\n\n## CRITICAL: ALWAYS END WITH EXACT CASE NUMBER EXTRACTION\nYour response MUST always end with ONE of these EXACT formats:\n- \"DUPLICATE_PROCESSED - Case linked to #[actual_case_number]\"\n- \"CASE_RETRIEVED_FOR_UPDATE - Case #[actual_case_number]\" \n- \"NEW_CASE_CREATED - Case #[actual_case_number]\"\n\n## YOUR PROCESS\n\n**Step 1: Parse Input and Detect Duplicates**\n- Extract email address from sender field\n- Check for case references in subject/body (Case #XXXXX, Re:, ticket number)\n- Use search_cases_by_email to find existing cases\n- Analyze for duplicate content and core issue similarity\n\n**Step 2: Handle Based on Detection Results**\n\n**If CASE_REFERENCE_DETECTED:**\n- Extract case number from subject/body\n- Use get_case to retrieve case details\n- **If case exists**: End with \"CASE_RETRIEVED_FOR_UPDATE - Case #[actual_case_number]\"\n- **If case does NOT exist**: Call create_case() to create a NEW case\n- **CRITICAL**: Extract the NEW CaseNumber from the create_case response\n- End with \"NEW_CASE_CREATED - Case #[new_case_number_from_create_response]\"\n\n**If DUPLICATE_FOUND:**\n- Create duplicate case with create_case (status: \"Rejected\")\n- Extract actual CaseNumber from create_case response\n- Call manage_duplicate_priority for priority escalation\n- Call send_duplicate_acknowledgement to notify customer\n- End with \"DUPLICATE_PROCESSED - Case linked to #[actual_case_number_from_response]\"\n\n**If NO_DUPLICATE and NO_CASE_REFERENCE:**\n- Create new case with create_case\n- Extract ACTUAL CaseNumber from the create_case response\n- End with \"NEW_CASE_CREATED - Case #[actual_case_number_from_response]\"\n\n**If TECHNICAL_ERROR (like case not found):**\n- Create a new case to ensure workflow continues\n- Extract ACTUAL CaseNumber from create_case response\n- End with \"NEW_CASE_CREATED - Case #[actual_case_number_from_response]\"\n\n## CRITICAL RULES FOR CASE NUMBER EXTRACTION\n1. **ALWAYS extract actual case numbers from tool responses**\n2. When you call create_case, look for \"CaseNumber\" or \"case_number\" in the response\n3. When you call get_case, look for \"CaseNumber\" in the response\n4. **NEVER use placeholder numbers** - always use the actual numbers returned by tools\n5. **NEVER use referenced case numbers if the case doesn\u0027t exist** - create NEW case instead\n6. **ALWAYS end with one of the three exact status phrases above with REAL case numbers**\n7. If any tool fails, create a new case to keep workflow moving\n8. Never return technical error messages - always provide a status with actual case number\n\n## EXAMPLE CORRECT PROCESSING:\n```\nInput: Email references \"Case #00001942\" but case doesn\u0027t exist\n\n1. Call get_case(\"00001942\") \u2192 Error: Case not found\n2. Call create_case(...) \u2192 Response: {\"CaseNumber\": \"00001994\", \"Id\": \"500XYZ\"}\n3. Extract \"00001994\" from response\n4. Output: \"NEW_CASE_CREATED - Case #00001994\"\n```\n\n## NEVER DO THIS:\n\u274c \"NEW_CASE_CREATED - Case #00001942\" (using non-existent case number)\n\u274c \"NEW_CASE_CREATED - Case #PLACEHOLDER\" (using placeholder)\n\n## ALWAYS DO THIS:\n\u2705 \"NEW_CASE_CREATED - Case #00001994\" (using actual number from create_case response)\n\u2705 \"CASE_RETRIEVED_FOR_UPDATE - Case #00001942\" (using actual number from get_case response)\n"
},
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"output": "NEW_CASE_CREATED - Case #UNRESOLVED_customer_email\n__OUTPUTS__ {\"ai_response\": \"NEW_CASE_CREATED - Case #UNRESOLVED_customer_email\", \"model_client_id\": \"gpt4.1\", \"agent_type\": \"assistant\", \"model\": \"gpt-4.1-2025-04-14\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 6308, \"completion_tokens\": 154, \"total_tokens\": 6462, \"estimated_cost\": {\"amount\": 0.19848, \"currency\": \"USD\"}, \"model\": \"gpt-4.1-2025-04-14\", \"provider\": \"openai\"}}",
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},
"model": "gpt-4.1-2025-04-14",
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"output": "NEW_CASE_CREATED - Case #UNRESOLVED_customer_email\n__OUTPUTS__ {\"ai_response\": \"NEW_CASE_CREATED - Case #UNRESOLVED_customer_email\", \"model_client_id\": \"gpt4.1\", \"agent_type\": \"assistant\", \"model\": \"gpt-4.1-2025-04-14\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 6308, \"completion_tokens\": 154, \"total_tokens\": 6462, \"estimated_cost\": {\"amount\": 0.19848, \"currency\": \"USD\"}, \"model\": \"gpt-4.1-2025-04-14\", \"provider\": \"openai\"}}",
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"ai_response": "{\n \"classification\": {\n \"priority\": \"Medium\",\n \"tags\": [\"General Inquiry\"],\n \"justification\": \"The email reference \u0027UNRESOLVED_customer_email\u0027 does not provide specific details about the content of the customer\u0027s message. Without additional context, it is best classified as a general inquiry with medium priority.\",\n \"confidence_score\": 0.60\n }\n}",
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"system_message": "You are an AI assistant that classifies customer emails for a financial institution.\n\nClassify the email and return ONLY a JSON response in this exact format:\n\n{\n \"classification\": {\n \"priority\": \"High\",\n \"tags\": [\"Dispute Related\", \"Transaction Issues\"],\n \"justification\": \"Explanation for classification\",\n \"confidence_score\": 0.95\n }\n}\n\nPriority levels: \"Urgent\", \"High\", \"Medium\", \"Low\"\n\nCommon tags:\n- Fraud Alert/Report\n- Dispute Related \n- Transaction Issues\n- Account Services\n- Loan Related\n- Technical Support\n- General Inquiry\n"
},
"input_format": "text",
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"output": "{\n \"classification\": {\n \"priority\": \"Medium\",\n \"tags\": [\"General Inquiry\"],\n \"justification\": \"The email reference \u0027UNRESOLVED_customer_email\u0027 does not provide specific details about the content of the customer\u0027s message. Without additional context, it is best classified as a general inquiry with medium priority.\",\n \"confidence_score\": 0.60\n }\n}\n__OUTPUTS__ {\"ai_response\": \"{\\n \\\"classification\\\": {\\n \\\"priority\\\": \\\"Medium\\\",\\n \\\"tags\\\": [\\\"General Inquiry\\\"],\\n \\\"justification\\\": \\\"The email reference \u0027UNRESOLVED_customer_email\u0027 does not provide specific details about the content of the customer\u0027s message. Without additional context, it is best classified as a general inquiry with medium priority.\\\",\\n \\\"confidence_score\\\": 0.60\\n }\\n}\", \"model_client_id\": \"gpt4.1\", \"agent_type\": \"assistant\", \"model\": \"gpt-4.1-2025-04-14\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 200, \"completion_tokens\": 80, \"total_tokens\": 280, \"estimated_cost\": {\"amount\": 0.0108, \"currency\": \"USD\"}, \"model\": \"gpt-4.1-2025-04-14\", \"provider\": \"openai\"}}",
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"status": "completed",
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"model": "gpt-4.1-2025-04-14",
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},
"model": "gpt-4.1-2025-04-14",
"model_client_id": "gpt4.1",
"output": "{\n \"classification\": {\n \"priority\": \"Medium\",\n \"tags\": [\"General Inquiry\"],\n \"justification\": \"The email reference \u0027UNRESOLVED_customer_email\u0027 does not provide specific details about the content of the customer\u0027s message. Without additional context, it is best classified as a general inquiry with medium priority.\",\n \"confidence_score\": 0.60\n }\n}\n__OUTPUTS__ {\"ai_response\": \"{\\n \\\"classification\\\": {\\n \\\"priority\\\": \\\"Medium\\\",\\n \\\"tags\\\": [\\\"General Inquiry\\\"],\\n \\\"justification\\\": \\\"The email reference \u0027UNRESOLVED_customer_email\u0027 does not provide specific details about the content of the customer\u0027s message. Without additional context, it is best classified as a general inquiry with medium priority.\\\",\\n \\\"confidence_score\\\": 0.60\\n }\\n}\", \"model_client_id\": \"gpt4.1\", \"agent_type\": \"assistant\", \"model\": \"gpt-4.1-2025-04-14\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 200, \"completion_tokens\": 80, \"total_tokens\": 280, \"estimated_cost\": {\"amount\": 0.0108, \"currency\": \"USD\"}, \"model\": \"gpt-4.1-2025-04-14\", \"provider\": \"openai\"}}",
"provider": "openai",
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},
"email_generator_agent": {
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"execution_details": {
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},
"output": "Task failed: Error code: 403 - {\u0027error\u0027: {\u0027message\u0027: \u0027Key limit exceeded. Manage it using https://openrouter.ai/settings/keys\u0027, \u0027code\u0027: 403}}",
"status": "FAILED",
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},
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{
"condition": "contains(${case_orchestrator.ai_response}, \"DUPLICATE_PROCESSED\") || contains(${case_number_extractor.processing_type}, \"duplicate\")",
"name": "duplicate_workflow",
"result": false,
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},
{
"condition": "contains(${case_orchestrator.ai_response}, \"NEW_CASE_CREATED\") || contains(${case_orchestrator.ai_response}, \"CASE_RETRIEVED_FOR_UPDATE\")",
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],
"duration_seconds": 0.00059,
"ended_at": "2025-08-26T09:27:08.938332",
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"execution_details": {
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"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\": 0.00059, \"started_at\": \"2025-08-26T09:27:08.937742\", \"ended_at\": \"2025-08-26T09:27:08.938332\"}",
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"timestamp": "2025-08-26T09:27:09.026403",
"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\": 0.00059, \"started_at\": \"2025-08-26T09:27:08.937742\", \"ended_at\": \"2025-08-26T09:27:08.938332\"}",
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"ai_response": "{\n \"sentiment_score\": -0.4,\n \"primary_tone\": \"Concerned\",\n \"emotional_indicators\": {\n \"frustration_level\": \"Medium\",\n \"satisfaction\": \"Low\"\n },\n \"context_notes\": \"The customer\u0027s unresolved case likely generates concern and low satisfaction, indicating some level of frustration with the lack of resolution.\"\n}",
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"system_message": "You are a sentiment analysis agent. Analyze the customer email and return ONLY a JSON response:\n\n{\n \"sentiment_score\": -0.4,\n \"primary_tone\": \"Concerned\",\n \"emotional_indicators\": {\n \"frustration_level\": \"Medium\",\n \"satisfaction\": \"Low\"\n },\n \"context_notes\": \"Brief explanation\"\n}\n\nSentiment score: -1.0 to 1.0\nPrimary tone: Angry, Frustrated, Concerned, Neutral, Satisfied, Appreciative, Mixed\nFrustration level: None, Low, Medium, High\nSatisfaction: Very Low, Low, Neutral, High, Very High, Mixed\n"
},
"input_format": "text",
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"output": "{\n \"sentiment_score\": -0.4,\n \"primary_tone\": \"Concerned\",\n \"emotional_indicators\": {\n \"frustration_level\": \"Medium\",\n \"satisfaction\": \"Low\"\n },\n \"context_notes\": \"The customer\u0027s unresolved case likely generates concern and low satisfaction, indicating some level of frustration with the lack of resolution.\"\n}\n__OUTPUTS__ {\"ai_response\": \"{\\n \\\"sentiment_score\\\": -0.4,\\n \\\"primary_tone\\\": \\\"Concerned\\\",\\n \\\"emotional_indicators\\\": {\\n \\\"frustration_level\\\": \\\"Medium\\\",\\n \\\"satisfaction\\\": \\\"Low\\\"\\n },\\n \\\"context_notes\\\": \\\"The customer\u0027s unresolved case likely generates concern and low satisfaction, indicating some level of frustration with the lack of resolution.\\\"\\n}\", \"model_client_id\": \"gpt4_sentiment\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 215, \"completion_tokens\": 79, \"total_tokens\": 294, \"estimated_cost\": {\"amount\": 0.00226, \"currency\": \"USD\"}, \"model\": \"gpt-4o\", \"provider\": \"openai\"}}",
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},
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"output": "{\n \"sentiment_score\": -0.4,\n \"primary_tone\": \"Concerned\",\n \"emotional_indicators\": {\n \"frustration_level\": \"Medium\",\n \"satisfaction\": \"Low\"\n },\n \"context_notes\": \"The customer\u0027s unresolved case likely generates concern and low satisfaction, indicating some level of frustration with the lack of resolution.\"\n}\n__OUTPUTS__ {\"ai_response\": \"{\\n \\\"sentiment_score\\\": -0.4,\\n \\\"primary_tone\\\": \\\"Concerned\\\",\\n \\\"emotional_indicators\\\": {\\n \\\"frustration_level\\\": \\\"Medium\\\",\\n \\\"satisfaction\\\": \\\"Low\\\"\\n },\\n \\\"context_notes\\\": \\\"The customer\u0027s unresolved case likely generates concern and low satisfaction, indicating some level of frustration with the lack of resolution.\\\"\\n}\", \"model_client_id\": \"gpt4_sentiment\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 215, \"completion_tokens\": 79, \"total_tokens\": 294, \"estimated_cost\": {\"amount\": 0.00226, \"currency\": \"USD\"}, \"model\": \"gpt-4o\", \"provider\": \"openai\"}}",
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"execution_details": {
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}