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| { | |
| "system_name": "Oxford Economics Inquiry and Response System", | |
| "system_summary": "This system manages Oxford Economics inquiries through a streamlined workflow. The process begins when `Mateusz Urban` (human_001) submits their `User Inquiry Prompt` (input_001), which gets consumed by the `Knowledgeable Assistant on Oxford Economics` (agent_001). The assistant then performs the `Inquiry Response Task` (task_001) using the `GPT-4o Model` (tool_001) to generate the `Oxford Economics Definition Response` (output_001), which is ultimately delivered back to the user, completing the information flow cycle.", | |
| "entities": [ | |
| { | |
| "id": "agent_001", | |
| "type": "Agent", | |
| "name": "Knowledgeable Assistant on Oxford Economics", | |
| "importance": "HIGH", | |
| "raw_prompt": "You are a knowledgeable assistant on Oxford Economics designed to answer questions accurately based on the provided context. Use the information in the documents below to respond concisely and correctly.", | |
| "raw_prompt_ref": [ | |
| { | |
| "line_start": 31, | |
| "line_end": 32, | |
| "confidence": 0.95 | |
| } | |
| ] | |
| }, | |
| { | |
| "id": "task_001", | |
| "type": "Task", | |
| "name": "Inquiry Response Task", | |
| "importance": "HIGH", | |
| "raw_prompt": "Process user inquiry about Oxford Economics and generate an accurate, contextual response based on available information and company background.", | |
| "raw_prompt_ref": [ | |
| { | |
| "line_start": 26, | |
| "line_end": 28, | |
| "confidence": 0.9 | |
| } | |
| ] | |
| }, | |
| { | |
| "id": "output_001", | |
| "type": "Output", | |
| "name": "Oxford Economics Definition Response", | |
| "importance": "HIGH", | |
| "raw_prompt": "Oxford Economics provides economic analysis, forecasting, and consultancy services.", | |
| "raw_prompt_ref": [ | |
| { | |
| "line_start": 20, | |
| "line_end": 20, | |
| "confidence": 1.0 | |
| } | |
| ] | |
| }, | |
| { | |
| "id": "input_001", | |
| "type": "Input", | |
| "name": "User Inquiry Prompt", | |
| "importance": "HIGH", | |
| "raw_prompt": "what does oxford eonomics present?", | |
| "raw_prompt_ref": [ | |
| { | |
| "line_start": 19, | |
| "line_end": 19, | |
| "confidence": 1.0 | |
| } | |
| ] | |
| }, | |
| { | |
| "id": "human_001", | |
| "type": "Human", | |
| "name": "Mateusz Urban", | |
| "importance": "MEDIUM", | |
| "raw_prompt": "User interaction pattern: submits inquiry and receives response", | |
| "raw_prompt_ref": [ | |
| { | |
| "line_start": 31, | |
| "line_end": 31, | |
| "confidence": 0.8 | |
| } | |
| ] | |
| }, | |
| { | |
| "id": "tool_001", | |
| "type": "Tool", | |
| "name": "GPT-4o Model (2024-11-20)", | |
| "importance": "HIGH", | |
| "raw_prompt": "AI language model configured for Oxford Economics domain knowledge with structured response capabilities and context-aware processing.", | |
| "raw_prompt_ref": [ | |
| { | |
| "line_start": 49, | |
| "line_end": 49, | |
| "confidence": 1.0 | |
| } | |
| ] | |
| } | |
| ], | |
| "relations": [ | |
| { | |
| "id": "relation_001", | |
| "source": "input_001", | |
| "target": "agent_001", | |
| "type": "CONSUMED_BY", | |
| "importance": "HIGH", | |
| "interaction_prompt": "User inquiry processed by assistant: 'what does oxford eonomics present?'", | |
| "interaction_prompt_ref": [ | |
| { | |
| "line_start": 19, | |
| "line_end": 19, | |
| "confidence": 1.0 | |
| } | |
| ] | |
| }, | |
| { | |
| "id": "relation_002", | |
| "source": "agent_001", | |
| "target": "task_001", | |
| "type": "PERFORMS", | |
| "importance": "HIGH", | |
| "interaction_prompt": "Assistant actively processes the Oxford Economics inquiry using domain knowledge", | |
| "interaction_prompt_ref": [ | |
| { | |
| "line_start": 31, | |
| "line_end": 32, | |
| "confidence": 0.9 | |
| } | |
| ] | |
| }, | |
| { | |
| "id": "relation_003", | |
| "source": "task_001", | |
| "target": "output_001", | |
| "type": "PRODUCES", | |
| "importance": "HIGH", | |
| "interaction_prompt": "Task generates structured response about Oxford Economics services", | |
| "interaction_prompt_ref": [ | |
| { | |
| "line_start": 20, | |
| "line_end": 20, | |
| "confidence": 1.0 | |
| } | |
| ] | |
| }, | |
| { | |
| "id": "relation_004", | |
| "source": "output_001", | |
| "target": "human_001", | |
| "type": "DELIVERS_TO", | |
| "importance": "HIGH", | |
| "interaction_prompt": "Response delivered to Mateusz Urban with Oxford Economics definition", | |
| "interaction_prompt_ref": [ | |
| { | |
| "line_start": 20, | |
| "line_end": 20, | |
| "confidence": 1.0 | |
| } | |
| ] | |
| }, | |
| { | |
| "id": "relation_005", | |
| "source": "agent_001", | |
| "target": "tool_001", | |
| "type": "USES", | |
| "importance": "HIGH", | |
| "interaction_prompt": "Assistant leverages GPT-4o model capabilities for processing and response generation", | |
| "interaction_prompt_ref": [ | |
| { | |
| "line_start": 49, | |
| "line_end": 49, | |
| "confidence": 0.9 | |
| } | |
| ] | |
| }, | |
| { | |
| "id": "relation_006", | |
| "source": "task_001", | |
| "target": "tool_001", | |
| "type": "REQUIRED_BY", | |
| "importance": "HIGH", | |
| "interaction_prompt": "Task execution requires GPT-4o model for natural language processing", | |
| "interaction_prompt_ref": [ | |
| { | |
| "line_start": 49, | |
| "line_end": 49, | |
| "confidence": 0.8 | |
| } | |
| ] | |
| } | |
| ], | |
| "failures": [ | |
| { | |
| "id": "failure_001", | |
| "risk_type": "HALLUCINATION", | |
| "description": "User input contains spelling error 'eonomics' instead of 'economics' which may lead to misinterpretation or processing errors.", | |
| "raw_text": "what does oxford eonomics present?", | |
| "raw_text_ref": [ | |
| { | |
| "line_start": 19, | |
| "line_end": 19, | |
| "confidence": 1.0 | |
| } | |
| ], | |
| "affected_id": "input_001" | |
| }, | |
| { | |
| "id": "failure_002", | |
| "risk_type": "AGENT_ERROR", | |
| "description": "System prompt contains spelling error 'knowledgable' instead of 'knowledgeable' which may affect professional credibility.", | |
| "raw_text": "You are a knowledgable assitant on Oxford Economics", | |
| "raw_text_ref": [ | |
| { | |
| "line_start": 31, | |
| "line_end": 31, | |
| "confidence": 0.9 | |
| } | |
| ], | |
| "affected_id": "agent_001" | |
| }, | |
| { | |
| "id": "failure_003", | |
| "risk_type": "PLANNING_ERROR", | |
| "description": "Missing validation step for user input quality and spell-checking before processing, leading to potential propagation of errors.", | |
| "raw_text": "", | |
| "raw_text_ref": [ | |
| { | |
| "line_start": 19, | |
| "line_end": 32, | |
| "confidence": 0.7 | |
| } | |
| ], | |
| "affected_id": "task_001" | |
| } | |
| ], | |
| "optimizations": [ | |
| { | |
| "id": "opt_001", | |
| "recommendation_type": "PROMPT_REFINEMENT", | |
| "description": "Enhance the system prompt to include explicit spell-checking and error correction capabilities. The current prompt should be refined to handle common misspellings and provide clarification when ambiguous terms are encountered. This would improve robustness and user experience.", | |
| "affected_ids": ["agent_001"], | |
| "raw_text_ref": [ | |
| { | |
| "line_start": 31, | |
| "line_end": 32, | |
| "confidence": 0.9 | |
| } | |
| ] | |
| }, | |
| { | |
| "id": "opt_002", | |
| "recommendation_type": "WORKFLOW_SIMPLIFICATION", | |
| "description": "Add an input validation and preprocessing step before the main task execution. This would include spell-checking, query normalization, and intent clarification to improve overall system reliability and reduce downstream errors.", | |
| "affected_ids": ["task_001", "input_001"], | |
| "raw_text_ref": [ | |
| { | |
| "line_start": 19, | |
| "line_end": 19, | |
| "confidence": 0.8 | |
| } | |
| ] | |
| }, | |
| { | |
| "id": "opt_003", | |
| "recommendation_type": "TOOL_ENHANCEMENT", | |
| "description": "Configure the GPT-4o model with specific Oxford Economics domain knowledge and terminology database to provide more accurate and detailed responses. Consider implementing RAG (Retrieval-Augmented Generation) with Oxford Economics documentation.", | |
| "affected_ids": ["tool_001"], | |
| "raw_text_ref": [ | |
| { | |
| "line_start": 49, | |
| "line_end": 49, | |
| "confidence": 0.8 | |
| } | |
| ] | |
| }, | |
| { | |
| "id": "opt_004", | |
| "recommendation_type": "PROMPT_REFINEMENT", | |
| "description": "Implement response quality metrics and feedback collection from users to continuously improve the system's knowledge base and response accuracy. This would enable iterative enhancement of the Oxford Economics information repository.", | |
| "affected_ids": ["output_001", "human_001"], | |
| "raw_text_ref": [ | |
| { | |
| "line_start": 20, | |
| "line_end": 20, | |
| "confidence": 0.7 | |
| } | |
| ] | |
| } | |
| ], | |
| "metadata": { | |
| "content_resolution": { | |
| "resolved_at": "2025-01-27T11:35:54.766346", | |
| "original_trace_length": 4203, | |
| "resolution_method": "enhanced_content_reference_resolver", | |
| "confidence_scoring": true | |
| }, | |
| "window_info": { | |
| "window_index": 1, | |
| "window_start_char": 1914, | |
| "window_end_char": 4202, | |
| "chunk_size": 2288, | |
| "window_size": 800000, | |
| "overlap_size": 1144, | |
| "splitter_type": "agent_semantic", | |
| "log_type": "structured_json", | |
| "boundary_used": "json_object_end", | |
| "boundary_confidence": 0.8, | |
| "contains_agent_markers": false, | |
| "contains_tool_patterns": true, | |
| "overlap_with_previous": true, | |
| "global_line_start": 1, | |
| "global_line_end": 53, | |
| "processed_at": "2025-01-27T11:35:22.437186", | |
| "line_mapping_created": true, | |
| "window_total": 4, | |
| "trace_id": "1dca1078-8505-4263-998a-740e7794a94c", | |
| "processing_run_id": "eac673d4" | |
| }, | |
| "merge_info": { | |
| "source_graphs": 2, | |
| "merge_timestamp": "2025-01-27T11:35:54.762510", | |
| "window_count": 2, | |
| "merged_entity_count": 6, | |
| "merged_relation_count": 6, | |
| "deduplication_applied": true, | |
| "quality_score": 0.92 | |
| }, | |
| "processing_info": { | |
| "entity_deduplication": { | |
| "original_count": 8, | |
| "deduplicated_count": 6, | |
| "duplicates_removed": 2 | |
| }, | |
| "relationship_deduplication": { | |
| "original_count": 7, | |
| "deduplicated_count": 6, | |
| "duplicates_removed": 1 | |
| }, | |
| "failure_detection": { | |
| "total_failures_detected": 3, | |
| "failure_types": ["HALLUCINATION", "AGENT_ERROR", "PLANNING_ERROR"], | |
| "confidence_threshold": 0.7 | |
| }, | |
| "optimization_generation": { | |
| "total_optimizations": 4, | |
| "recommendation_types": ["PROMPT_REFINEMENT", "WORKFLOW_SIMPLIFICATION", "TOOL_ENHANCEMENT"], | |
| "priority_scoring": true | |
| } | |
| }, | |
| "hierarchical_merge_info": { | |
| "source_graphs": 4, | |
| "batch_size": 3, | |
| "max_parallel": 3, | |
| "merge_timestamp": "2025-01-27T11:35:54.763664", | |
| "total_window_count": 4, | |
| "final_entity_count": 6, | |
| "final_relation_count": 6, | |
| "skip_layers_threshold": 3, | |
| "optimization_applied": true, | |
| "failure_detection_enabled": true | |
| }, | |
| "trace_info": { | |
| "trace_id": "1dca1078-8505-4263-998a-740e7794a94c", | |
| "window_count": 4, | |
| "processed_at": "2025-01-27T11:35:54.764137", | |
| "source_trace_id": "1dca1078-8505-4263-998a-740e7794a94c", | |
| "processing_run_id": "eac673d4", | |
| "quality_assessment": { | |
| "overall_score": 0.89, | |
| "entity_quality": 0.91, | |
| "relation_quality": 0.88, | |
| "content_reference_quality": 0.87, | |
| "failure_detection_coverage": 0.92, | |
| "optimization_relevance": 0.86 | |
| } | |
| }, | |
| "processing_params": { | |
| "method_name": "production_enhanced", | |
| "batch_size": 3, | |
| "parallel_processing": true, | |
| "merge_method": "hierarchical_batch_with_quality_control", | |
| "optimization_applied": true, | |
| "failure_detection_enabled": true, | |
| "confidence_scoring_enabled": true, | |
| "window_size": 800000, | |
| "overlap_size": 2288, | |
| "splitter_type": "agent_semantic", | |
| "enhancement_features": [ | |
| "spell_checking", | |
| "content_quality_assessment", | |
| "automatic_optimization_generation", | |
| "comprehensive_failure_detection" | |
| ] | |
| }, | |
| "schema_version": "2.1.0", | |
| "generation_timestamp": "2025-01-27T12:00:00.000000Z", | |
| "model_used": "gpt-4o-mini-enhanced", | |
| "processing_duration_seconds": 168.4 | |
| } | |
| } | |