338 lines
17 KiB
Python
338 lines
17 KiB
Python
"""
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Placeholder Factory
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Centralized placeholder extraction functions for all workflow modes.
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Each function corresponds to a {{KEY:PLACEHOLDER_NAME}} in prompt templates.
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NAMING CONVENTION:
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- All functions follow pattern: extract{PlaceholderName}()
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- Placeholder names are in UPPER_CASE with underscores
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- Function names are in camelCase
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MAPPING TABLE (keys → function) with usage [global | react | actionplan]:
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{{KEY:USER_PROMPT}} -> extractUserPrompt() [global, react, actionplan]
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{{KEY:USER_LANGUAGE}} -> extractUserLanguage() [react, actionplan]
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{{KEY:AVAILABLE_DOCUMENTS_SUMMARY}} -> extractAvailableDocumentsSummary() [react, actionplan]
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{{KEY:AVAILABLE_DOCUMENTS_INDEX}} -> extractAvailableDocumentsIndex() [react]
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{{KEY:AVAILABLE_CONNECTIONS_INDEX}} -> extractAvailableConnectionsIndex() [react, actionplan]
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{{KEY:AVAILABLE_CONNECTIONS_SUMMARY}} -> extractAvailableConnectionsSummary() [unused]
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{{KEY:WORKFLOW_HISTORY}} -> extractWorkflowHistory() [actionplan]
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{{KEY:AVAILABLE_METHODS}} -> extractAvailableMethods() [react, actionplan]
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{{KEY:REVIEW_CONTENT}} -> extractReviewContent() [react, actionplan]
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{{KEY:PREVIOUS_ACTION_RESULTS}} -> extractPreviousActionResults() [react]
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{{KEY:LEARNINGS_AND_IMPROVEMENTS}} -> extractLearningsAndImprovements() [react]
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{{KEY:LATEST_REFINEMENT_FEEDBACK}} -> extractLatestRefinementFeedback() [react]
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Following placeholders are populated directly by prompt builders with according context in promptGenerationActionsReact module:
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- ACTION_OBJECTIVE,
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- SELECTED_ACTION,
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- ACTION_SIGNATURE
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"""
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import json
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import logging
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from typing import Dict, Any, List
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from modules.datamodels.datamodelChat import ChatDocument
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logger = logging.getLogger(__name__)
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from modules.workflows.processing.shared.methodDiscovery import (methods, discoverMethods)
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def extractUserPrompt(context: Any) -> str:
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"""Extract user prompt from context. Maps to {{KEY:USER_PROMPT}}.
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Prefer the cleaned intent stored on the services object if available via context.
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Fallback to the task_step objective.
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"""
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try:
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# Prefer services.currentUserPrompt when accessible through context
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services = getattr(context, 'services', None)
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if services and getattr(services, 'currentUserPrompt', None):
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return services.currentUserPrompt
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except Exception:
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pass
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if hasattr(context, 'task_step') and context.task_step:
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return context.task_step.objective or 'No request specified'
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return 'No request specified'
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def extractWorkflowHistory(service: Any, context: Any) -> str:
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"""Extract workflow history from context. Maps to {{KEY:WORKFLOW_HISTORY}}"""
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if hasattr(context, 'workflow') and context.workflow:
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return getPreviousRoundContext(service, context.workflow) or "No previous workflow rounds - this is the first round."
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return "No previous workflow rounds - this is the first round."
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def extractAvailableMethods(service: Any) -> str:
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"""Extract available methods for action planning. Maps to {{KEY:AVAILABLE_METHODS}}"""
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try:
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# Get the methods dictionary directly from the global methods variable
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if not methods:
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discoverMethods(service)
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# Create a flat JSON format with compound action names for better AI parsing
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available_actions_json = {}
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for methodName, methodInfo in methods.items():
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# Convert MethodAi -> ai, MethodDocument -> document, etc.
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shortName = methodName.replace('Method', '').lower()
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for actionName, actionInfo in methodInfo['actions'].items():
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# Create compound action name: method.action
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compoundActionName = f"{shortName}.{actionName}"
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# Get the action description
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action_description = actionInfo.get('description', f"Execute {actionName} action")
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available_actions_json[compoundActionName] = action_description
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return json.dumps(available_actions_json, indent=2, ensure_ascii=False)
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except Exception as e:
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logger.error(f"Error extracting available methods: {str(e)}")
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return json.dumps({}, indent=2, ensure_ascii=False)
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def extractUserLanguage(service: Any) -> str:
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"""Extract user language from service. Maps to {{KEY:USER_LANGUAGE}}"""
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return service.user.language if service and service.user else 'en'
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def getConnectionReferenceList(services) -> List[str]:
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"""Get list of available connections"""
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try:
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# Get connections from the database
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if hasattr(services, 'interfaceDbApp') and hasattr(services, 'user'):
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userId = services.user.id
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connections = services.interfaceDbApp.getUserConnections(userId)
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if connections:
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# Format connections as reference strings
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connectionRefs = []
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for conn in connections:
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# Create reference string in format: conn_{authority}_{id}
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ref = f"conn_{conn.authority.value}_{conn.id}"
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connectionRefs.append(ref)
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return connectionRefs
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return []
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except Exception as e:
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logger.error(f"Error getting connection reference list: {str(e)}")
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return []
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def getPreviousRoundContext(services, context: Any) -> str:
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"""Get previous round context for prompt"""
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try:
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if not context or not hasattr(context, 'workflow_id'):
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return "No previous round context available"
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workflowId = context.workflow_id
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if not workflowId:
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return "No previous round context available"
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# Get previous round results
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previousResults = getattr(context, 'previous_results', [])
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if not previousResults:
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return "No previous round context available"
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contextList = []
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for i, result in enumerate(previousResults, 1):
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if hasattr(result, 'success') and hasattr(result, 'resultLabel'):
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status = "Success" if result.success else "Failed"
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contextList.append(f"{i}. {result.resultLabel} - {status}")
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elif isinstance(result, dict):
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status = "Success" if result.get('success', False) else "Failed"
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label = result.get('resultLabel', 'Unknown')
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contextList.append(f"{i}. {label} - {status}")
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else:
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contextList.append(f"{i}. {str(result)}")
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return "\n".join(contextList) if contextList else "No previous round context available"
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except Exception as e:
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logger.error(f"Error getting previous round context: {str(e)}")
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return "Error retrieving previous round context"
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def extractReviewContent(context: Any) -> str:
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"""Extract review content for result validation. Maps to {{KEY:REVIEW_CONTENT}}"""
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try:
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if hasattr(context, 'action_results') and context.action_results:
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# Build result summary
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result_summary = ""
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for i, result in enumerate(context.action_results):
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result_summary += f"\nRESULT {i+1}:\n"
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result_summary += f" Success: {result.success}\n"
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if result.error:
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result_summary += f" Error: {result.error}\n"
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if result.documents:
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result_summary += f" Documents: {len(result.documents)} document(s)\n"
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for doc in result.documents:
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# Extract all available metadata without content
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doc_metadata = {
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"name": getattr(doc, 'documentName', 'Unknown'),
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"mimeType": getattr(doc, 'mimeType', 'Unknown'),
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"size": getattr(doc, 'size', 'Unknown'),
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"created": getattr(doc, 'created', 'Unknown'),
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"modified": getattr(doc, 'modified', 'Unknown'),
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"typeGroup": getattr(doc, 'typeGroup', 'Unknown'),
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"documentId": getattr(doc, 'documentId', 'Unknown'),
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"reference": getattr(doc, 'reference', 'Unknown')
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}
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# Remove 'Unknown' values to keep it clean
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doc_metadata = {k: v for k, v in doc_metadata.items() if v != 'Unknown'}
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result_summary += f" - {json.dumps(doc_metadata, indent=6, ensure_ascii=False)}\n"
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else:
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result_summary += f" Documents: None\n"
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return result_summary
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elif hasattr(context, 'observation') and context.observation:
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# For observation data, show full content but handle documents specially
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if isinstance(context.observation, dict):
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# Create a copy to modify
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obs_copy = context.observation.copy()
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# If there are previews with documents, show only metadata
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if 'previews' in obs_copy and isinstance(obs_copy['previews'], list):
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for preview in obs_copy['previews']:
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if isinstance(preview, dict) and 'snippet' in preview:
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# Replace snippet with metadata indicator
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preview['snippet'] = f"[Content: {len(preview.get('snippet', ''))} characters]"
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return json.dumps(obs_copy, indent=2, ensure_ascii=False)
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else:
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return json.dumps(context.observation, ensure_ascii=False)
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elif hasattr(context, 'step_result') and context.step_result and 'observation' in context.step_result:
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# For observation data in step_result, show full content but handle documents specially
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observation = context.step_result['observation']
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if isinstance(observation, dict):
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# Create a copy to modify
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obs_copy = observation.copy()
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# If there are previews with documents, show only metadata
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if 'previews' in obs_copy and isinstance(obs_copy['previews'], list):
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for preview in obs_copy['previews']:
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if isinstance(preview, dict) and 'snippet' in preview:
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# Replace snippet with metadata indicator
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preview['snippet'] = f"[Content: {len(preview.get('snippet', ''))} characters]"
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return json.dumps(obs_copy, indent=2, ensure_ascii=False)
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else:
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return json.dumps(observation, ensure_ascii=False)
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else:
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return "No review content available"
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except Exception as e:
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logger.error(f"Error extracting review content: {str(e)}")
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return "No review content available"
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def extractPreviousActionResults(context: Any) -> str:
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"""Extract previous action results for learning context. Maps to {{KEY:PREVIOUS_ACTION_RESULTS}}"""
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try:
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if not hasattr(context, 'previous_action_results') or not context.previous_action_results:
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return "No previous actions executed yet"
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results = []
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for i, result in enumerate(context.previous_action_results[-5:], 1): # Last 5 results
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if hasattr(result, 'resultLabel') and hasattr(result, 'status'):
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status = "SUCCESS" if result.status == "completed" else "FAILED"
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results.append(f"Action {i}: {result.resultLabel} - {status}")
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if hasattr(result, 'error') and result.error:
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results.append(f" Error: {result.error}")
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return "\n".join(results) if results else "No previous actions executed yet"
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except Exception as e:
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logger.error(f"Error extracting previous action results: {str(e)}")
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return "No previous actions executed yet"
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def extractLearningsAndImprovements(context: Any) -> str:
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"""Extract learnings and improvements from previous actions. Maps to {{KEY:LEARNINGS_AND_IMPROVEMENTS}}"""
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try:
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learnings = []
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# Get improvements from context
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if hasattr(context, 'improvements') and context.improvements and isinstance(context.improvements, list):
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learnings.append("IMPROVEMENTS:")
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for improvement in context.improvements[-3:]: # Last 3 improvements
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learnings.append(f"- {improvement}")
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# Get failure patterns
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if hasattr(context, 'failure_patterns') and context.failure_patterns and isinstance(context.failure_patterns, list):
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learnings.append("FAILURE PATTERNS TO AVOID:")
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for pattern in context.failure_patterns[-3:]: # Last 3 patterns
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learnings.append(f"- {pattern}")
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# Get successful actions
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if hasattr(context, 'successful_actions') and context.successful_actions and isinstance(context.successful_actions, list):
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learnings.append("SUCCESSFUL APPROACHES:")
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for action in context.successful_actions[-3:]: # Last 3 successful
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learnings.append(f"- {action}")
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return "\n".join(learnings) if learnings else "No learnings available yet"
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except Exception as e:
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logger.error(f"Error extracting learnings and improvements: {str(e)}")
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return "No learnings available yet"
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def extractLatestRefinementFeedback(context: Any) -> str:
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"""Extract the latest refinement feedback. Maps to {{KEY:LATEST_REFINEMENT_FEEDBACK}}"""
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try:
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if not hasattr(context, 'previous_review_result') or not context.previous_review_result or not isinstance(context.previous_review_result, list):
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return "No previous refinement feedback available"
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# Get the most recent refinement decision
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latest_decision = context.previous_review_result[-1]
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if not isinstance(latest_decision, dict):
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return "No previous refinement feedback available"
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feedback_parts = []
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# Add decision and reason
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decision = latest_decision.get('decision', 'unknown')
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reason = latest_decision.get('reason', 'No reason provided')
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feedback_parts.append(f"Latest Decision: {decision}")
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feedback_parts.append(f"Reason: {reason}")
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# Add any specific feedback or suggestions
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if 'feedback' in latest_decision:
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feedback_parts.append(f"Feedback: {latest_decision['feedback']}")
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if 'suggestions' in latest_decision:
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feedback_parts.append(f"Suggestions: {latest_decision['suggestions']}")
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return "\n".join(feedback_parts)
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except Exception as e:
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logger.error(f"Error extracting latest refinement feedback: {str(e)}")
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return "No previous refinement feedback available"
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def extractAvailableDocumentsSummary(service: Any, context: Any) -> str:
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"""Summary of available documents (count only)."""
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try:
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if hasattr(context, 'workflow') and context.workflow:
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documents = service.workflow.getAvailableDocuments(context.workflow)
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if documents and documents != "No documents available":
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doc_count = documents.count("docList:") + documents.count("docItem:")
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return f"{doc_count} documents available from previous tasks"
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return "No documents available"
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return "No documents available"
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except Exception as e:
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logger.error(f"Error getting document summary: {str(e)}")
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return "No documents available"
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def extractAvailableDocumentsIndex(service: Any, context: Any) -> str:
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"""Index of available documents with detailed references for parameter generation."""
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try:
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if hasattr(context, 'workflow') and context.workflow:
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return service.workflow.getAvailableDocuments(context.workflow)
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return "No documents available"
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except Exception as e:
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logger.error(f"Error getting document index: {str(e)}")
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return "No documents available"
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def extractAvailableConnectionsSummary(service: Any) -> str:
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"""Summary of available connections (count only)."""
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try:
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connections = getConnectionReferenceList(service)
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if connections:
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return f"{len(connections)} connections available"
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return "No connections available"
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except Exception as e:
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logger.error(f"Error getting connection summary: {str(e)}")
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return "No connections available"
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def extractAvailableConnectionsIndex(service: Any) -> str:
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"""Index of available connections with detailed references for parameter generation."""
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try:
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connections = getConnectionReferenceList(service)
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if connections:
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return '\n'.join(f"- {conn}" for conn in connections)
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return "No connections available"
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except Exception as e:
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logger.error(f"Error getting connection index: {str(e)}")
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return "No connections available"
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