From 16db2d91c64312744bba383403b0e6954c53b92f Mon Sep 17 00:00:00 2001 From: patrick-motsch Date: Tue, 3 Mar 2026 18:57:20 +0100 Subject: [PATCH 1/7] fixed critical code issues --- modules/workflows/automation/mainWorkflow.py | 27 +-- .../automation/subAutomationSchedule.py | 2 +- .../automation/subAutomationTemplates.py | 2 +- .../automation/subAutomationUtils.py | 70 +++---- .../methods/methodAi/actions/generateCode.py | 12 +- .../methodAi/actions/generateDocument.py | 14 +- .../methods/methodAi/actions/process.py | 13 +- .../methods/methodAi/actions/webResearch.py | 11 +- modules/workflows/methods/methodBase.py | 14 +- .../methodChatbot/actions/queryDatabase.py | 19 +- .../methodContext/actions/extractContent.py | 10 +- .../methodContext/actions/getDocumentIndex.py | 15 +- .../methodContext/actions/neutralizeData.py | 10 +- .../methodOutlook/actions/readEmails.py | 7 +- .../methodOutlook/actions/searchEmails.py | 4 +- .../methodOutlook/actions/sendDraftEmail.py | 10 + .../methodOutlook/helpers/connection.py | 20 +- .../methodOutlook/helpers/emailProcessing.py | 16 +- .../actions/uploadDocument.py | 7 +- .../methodSharepoint/helpers/apiClient.py | 92 ++++----- .../adaptive/adaptiveLearningEngine.py | 32 ++-- .../processing/adaptive/contentValidator.py | 55 +++--- .../processing/adaptive/learningEngine.py | 5 + .../processing/core/actionExecutor.py | 11 +- .../processing/core/messageCreator.py | 57 ++---- .../workflows/processing/core/taskPlanner.py | 75 +------- .../workflows/processing/core/validator.py | 33 ++-- .../processing/modes/modeAutomation.py | 86 +-------- .../workflows/processing/modes/modeBase.py | 78 +++++++- .../workflows/processing/modes/modeDynamic.py | 178 +++--------------- .../processing/shared/executionState.py | 42 +---- .../processing/shared/methodDiscovery.py | 116 +++--------- .../processing/shared/placeholderFactory.py | 109 ++++------- .../shared/promptGenerationActionsDynamic.py | 19 +- .../workflows/processing/workflowProcessor.py | 37 ++-- modules/workflows/workflowManager.py | 64 ++----- 36 files changed, 494 insertions(+), 878 deletions(-) diff --git a/modules/workflows/automation/mainWorkflow.py b/modules/workflows/automation/mainWorkflow.py index f1b91939..1fc4b0cf 100644 --- a/modules/workflows/automation/mainWorkflow.py +++ b/modules/workflows/automation/mainWorkflow.py @@ -56,12 +56,12 @@ async def chatStart(currentUser: User, userInput: UserInputRequest, workflowMode logger.error(f"Error starting chat: {str(e)}") raise -async def chatStop(currentUser: User, workflowId: str, mandateId: Optional[str] = None, featureInstanceId: Optional[str] = None) -> ChatWorkflow: +async def chatStop(currentUser: User, workflowId: str, mandateId: Optional[str] = None, featureInstanceId: Optional[str] = None, featureCode: Optional[str] = None) -> ChatWorkflow: """Stops a running chat.""" try: services = getServices(currentUser, mandateId=mandateId, featureInstanceId=featureInstanceId) - if featureInstanceId: - services.featureCode = 'chatplayground' + if featureCode: + services.featureCode = featureCode workflowManager = WorkflowManager(services) return await workflowManager.workflowStop(workflowId) except Exception as e: @@ -101,8 +101,11 @@ async def executeAutomation(automationId: str, automation, creatorUser: User, se logger.debug(f"Automation {automationId} restricted to providers: {automation.allowedProviders}") # Context comes EXCLUSIVELY from the automation definition - automationMandateId = str(automation.mandateId) - automationFeatureInstanceId = str(automation.featureInstanceId) + automationMandateId = str(automation.mandateId) if automation.mandateId is not None else None + automationFeatureInstanceId = str(automation.featureInstanceId) if automation.featureInstanceId is not None else None + + if not automationMandateId or not automationFeatureInstanceId: + raise ValueError(f"Automation {automationId} missing mandateId or featureInstanceId") logger.info(f"Executing automation {automationId} as user {creatorUser.id} with mandateId={automationMandateId}, featureInstanceId={automationFeatureInstanceId}") @@ -118,7 +121,7 @@ async def executeAutomation(automationId: str, automation, creatorUser: User, se logger.error(f"Placeholders: {placeholders}") logger.error(f"Generated planJson (first 1000 chars): {planJson[:1000]}") logger.error(f"Error position: line {e.lineno}, column {e.colno}, char {e.pos}") - if e.pos: + if e.pos is not None: start = max(0, e.pos - 100) end = min(len(planJson), e.pos + 100) logger.error(f"Context around error: ...{planJson[start:end]}...") @@ -233,20 +236,10 @@ def syncAutomationEvents(services, eventUser) -> Dict[str, Any]: cronKwargs = parseScheduleToCron(schedule) if isActive: - # Remove existing event if present (handles schedule changes) - if currentEventId: - try: - eventManager.remove(currentEventId) - except Exception as e: - logger.warning(f"Error removing old event {currentEventId}: {str(e)}") - - # Register new event newEventId = f"automation.{automationId}" - - # Create event handler function handler = createAutomationEventHandler(automationId, eventUser) - # Register cron job + # Register with replaceExisting=True (atomically replaces old event) eventManager.registerCron( jobId=newEventId, func=handler, diff --git a/modules/workflows/automation/subAutomationSchedule.py b/modules/workflows/automation/subAutomationSchedule.py index 40638461..9db1f3fa 100644 --- a/modules/workflows/automation/subAutomationSchedule.py +++ b/modules/workflows/automation/subAutomationSchedule.py @@ -48,7 +48,7 @@ def start(eventUser) -> bool: except Exception as e: logger.error(f"Automation: Error setting up events on startup: {str(e)}") - # Don't fail startup if automation sync fails + return False return True diff --git a/modules/workflows/automation/subAutomationTemplates.py b/modules/workflows/automation/subAutomationTemplates.py index 95c1eb77..eb131f0a 100644 --- a/modules/workflows/automation/subAutomationTemplates.py +++ b/modules/workflows/automation/subAutomationTemplates.py @@ -6,7 +6,7 @@ Automation templates for workflow definitions. Contains predefined workflow templates that can be used to create automation definitions. """ -from typing import Dict, Any, List +from typing import Dict, Any # Automation templates structure AUTOMATION_TEMPLATES: Dict[str, Any] = { diff --git a/modules/workflows/automation/subAutomationUtils.py b/modules/workflows/automation/subAutomationUtils.py index 97d28719..bdac6efb 100644 --- a/modules/workflows/automation/subAutomationUtils.py +++ b/modules/workflows/automation/subAutomationUtils.py @@ -69,50 +69,42 @@ def replacePlaceholders(template: str, placeholders: Dict[str, str]) -> str: result = result.replace(arrayPattern, arrayValue) continue # Skip the regular replacement below - # Regular replacement - check if in quoted context - patternStart = result.find(pattern) - isQuoted = False - if patternStart > 0: - charBefore = result[patternStart - 1] if patternStart > 0 else None - patternEnd = patternStart + len(pattern) - charAfter = result[patternEnd] if patternEnd < len(result) else None - if charBefore == '"' and charAfter == '"': - isQuoted = True - - # Handle different value types - if isinstance(value, (list, dict)): - # Python list/dict - convert to JSON - replacement = json.dumps(value) - elif isinstance(value, str): - # String value - check if it's a JSON string representing list/dict - try: - parsed = json.loads(value) - if isinstance(parsed, (list, dict)): - # It's a JSON string of a list/dict - if isQuoted: - # In quoted context, escape the JSON string - escaped = json.dumps(value) - replacement = escaped[1:-1] # Remove outer quotes + # Replace occurrences one-by-one to handle mixed contexts + while pattern in result: + patternStart = result.find(pattern) + isQuoted = False + if patternStart > 0: + charBefore = result[patternStart - 1] + patternEnd = patternStart + len(pattern) + charAfter = result[patternEnd] if patternEnd < len(result) else None + if charBefore == '"' and charAfter == '"': + isQuoted = True + + if isinstance(value, (list, dict)): + replacement = json.dumps(value) + elif isinstance(value, str): + try: + parsed = json.loads(value) + if isinstance(parsed, (list, dict)): + if isQuoted: + escaped = json.dumps(value) + replacement = escaped[1:-1] + else: + replacement = value else: - # In unquoted context, use JSON directly - replacement = value - else: - # It's a JSON string of a primitive + if isQuoted: + escaped = json.dumps(value) + replacement = escaped[1:-1] + else: + replacement = value + except (json.JSONDecodeError, ValueError): if isQuoted: escaped = json.dumps(value) replacement = escaped[1:-1] else: replacement = value - except (json.JSONDecodeError, ValueError): - # Not valid JSON - treat as plain string - if isQuoted: - escaped = json.dumps(value) - replacement = escaped[1:-1] - else: - replacement = value - else: - # Numbers, booleans, None - convert to string - replacement = str(value) - result = result.replace(pattern, replacement) + else: + replacement = str(value) + result = result[:patternStart] + replacement + result[patternStart + len(pattern):] return result diff --git a/modules/workflows/methods/methodAi/actions/generateCode.py b/modules/workflows/methods/methodAi/actions/generateCode.py index 4f9bbd21..c616006b 100644 --- a/modules/workflows/methods/methodAi/actions/generateCode.py +++ b/modules/workflows/methods/methodAi/actions/generateCode.py @@ -74,7 +74,11 @@ async def generateCode(self, parameters: Dict[str, Any]) -> ActionResult: documentName=docData.documentName, documentData=docData.documentData, mimeType=docData.mimeType, - sourceJson=docData.sourceJson if hasattr(docData, 'sourceJson') else None + sourceJson=docData.sourceJson if hasattr(docData, 'sourceJson') else None, + validationMetadata={ + "actionType": "ai.generateCode", + "resultType": resultType, + } )) # If no documents but content exists, create a document from content @@ -112,7 +116,11 @@ async def generateCode(self, parameters: Dict[str, Any]) -> ActionResult: documents.append(ActionDocument( documentName=docName, documentData=aiResponse.content.encode('utf-8') if isinstance(aiResponse.content, str) else aiResponse.content, - mimeType=mimeType + mimeType=mimeType, + validationMetadata={ + "actionType": "ai.generateCode", + "resultType": resultType, + } )) return ActionResult.isSuccess(documents=documents) diff --git a/modules/workflows/methods/methodAi/actions/generateDocument.py b/modules/workflows/methods/methodAi/actions/generateDocument.py index 65e95a32..8bb33f9d 100644 --- a/modules/workflows/methods/methodAi/actions/generateDocument.py +++ b/modules/workflows/methods/methodAi/actions/generateDocument.py @@ -78,7 +78,12 @@ async def generateDocument(self, parameters: Dict[str, Any]) -> ActionResult: documentName=docData.documentName, documentData=docData.documentData, mimeType=docData.mimeType, - sourceJson=docData.sourceJson if hasattr(docData, 'sourceJson') else None + sourceJson=docData.sourceJson if hasattr(docData, 'sourceJson') else None, + validationMetadata={ + "actionType": "ai.generateDocument", + "documentType": documentType, + "resultType": resultType, + } )) # If no documents but content exists, create a document from content @@ -112,7 +117,12 @@ async def generateDocument(self, parameters: Dict[str, Any]) -> ActionResult: documents.append(ActionDocument( documentName=docName, documentData=aiResponse.content.encode('utf-8') if isinstance(aiResponse.content, str) else aiResponse.content, - mimeType=mimeType + mimeType=mimeType, + validationMetadata={ + "actionType": "ai.generateDocument", + "documentType": documentType, + "resultType": resultType, + } )) return ActionResult.isSuccess(documents=documents) diff --git a/modules/workflows/methods/methodAi/actions/process.py b/modules/workflows/methods/methodAi/actions/process.py index 752fe7f6..b4157f13 100644 --- a/modules/workflows/methods/methodAi/actions/process.py +++ b/modules/workflows/methods/methodAi/actions/process.py @@ -12,8 +12,8 @@ from modules.datamodels.datamodelExtraction import ContentPart logger = logging.getLogger(__name__) async def process(self, parameters: Dict[str, Any]) -> ActionResult: + operationId = None try: - # Init progress logger workflowId = self.services.workflow.id if self.services.workflow else f"no-workflow-{int(time.time())}" operationId = f"ai_process_{workflowId}_{int(time.time())}" @@ -83,7 +83,8 @@ async def process(self, parameters: Dict[str, Any]) -> ActionResult: output_format = None logger.debug("resultType not provided - formats will be determined from prompt by AI") - output_mime_type = "application/octet-stream" # Prefer service-provided mimeType when available + mimeMap = {"txt": "text/plain", "json": "application/json", "html": "text/html", "md": "text/markdown", "csv": "text/csv", "xml": "application/xml"} + output_mime_type = mimeMap.get(normalized_result_type, "text/plain") if normalized_result_type else "text/plain" # Phase 7.3: Pass both documentList and contentParts to AI service # (Extraction logic removed - handled by AI service) @@ -264,11 +265,11 @@ async def process(self, parameters: Dict[str, Any]) -> ActionResult: except Exception as e: logger.error(f"Error in AI processing: {str(e)}") - # Complete progress tracking with failure try: - self.services.chat.progressLogFinish(operationId, False) - except: - pass # Don't fail on progress logging errors + if operationId: + self.services.chat.progressLogFinish(operationId, False) + except Exception: + pass return ActionResult.isFailure( error=str(e) diff --git a/modules/workflows/methods/methodAi/actions/webResearch.py b/modules/workflows/methods/methodAi/actions/webResearch.py index 62b43bce..d59a26f9 100644 --- a/modules/workflows/methods/methodAi/actions/webResearch.py +++ b/modules/workflows/methods/methodAi/actions/webResearch.py @@ -4,18 +4,19 @@ import logging import time import re +import json from typing import Dict, Any from modules.datamodels.datamodelChat import ActionResult, ActionDocument logger = logging.getLogger(__name__) async def webResearch(self, parameters: Dict[str, Any]) -> ActionResult: + operationId = None try: prompt = parameters.get("prompt") if not prompt: return ActionResult.isFailure(error="Research prompt is required") - # Init progress logger workflowId = self.services.workflow.id if self.services.workflow else f"no-workflow-{int(time.time())}" operationId = f"web_research_{workflowId}_{int(time.time())}" @@ -78,9 +79,10 @@ async def webResearch(self, parameters: Dict[str, Any]) -> ActionResult: "researchDepth": parameters.get("researchDepth", "general"), "resultFormat": "json" } + documentData = json.dumps(result, ensure_ascii=False) if isinstance(result, dict) else result actionDocument = ActionDocument( documentName=meaningfulName, - documentData=result, + documentData=documentData, mimeType="application/json", validationMetadata=validationMetadata ) @@ -90,8 +92,9 @@ async def webResearch(self, parameters: Dict[str, Any]) -> ActionResult: except Exception as e: logger.error(f"Error in web research: {str(e)}") try: - self.services.chat.progressLogFinish(operationId, False) - except: + if operationId: + self.services.chat.progressLogFinish(operationId, False) + except Exception: pass return ActionResult.isFailure(error=str(e)) diff --git a/modules/workflows/methods/methodBase.py b/modules/workflows/methods/methodBase.py index 173023f1..1a81c3eb 100644 --- a/modules/workflows/methods/methodBase.py +++ b/modules/workflows/methods/methodBase.py @@ -1,11 +1,10 @@ # Copyright (c) 2025 Patrick Motsch # All rights reserved. -from typing import Dict, List, Optional, Any, Literal +from typing import Dict, List, Optional, Any from datetime import datetime, UTC import logging from functools import wraps -import inspect from modules.datamodels.datamodelWorkflowActions import WorkflowActionDefinition, WorkflowActionParameter from modules.datamodels.datamodelRbac import AccessRuleContext @@ -258,9 +257,13 @@ class MethodBase: raise ValueError(f"Expected dict for type '{expectedType}', got {type(value).__name__}") return value - # Handle simple types + # Handle simple types (bool must be checked before int since bool is subclass of int) if expectedType in typeMap: expectedTypeClass = typeMap[expectedType] + if expectedType == 'int' and isinstance(value, bool): + raise ValueError(f"Expected int, got bool: {value}") + if expectedType == 'bool' and isinstance(value, int) and not isinstance(value, bool): + return bool(value) if not isinstance(value, expectedTypeClass): try: return expectedTypeClass(value) @@ -290,10 +293,11 @@ class MethodBase: def getActionSignature(self, actionName: str) -> str: """Get formatted action signature for AI prompt generation (detailed version)""" - if actionName not in self.actions: + allActions = self.actions + if actionName not in allActions: return "" - action = self.actions[actionName] + action = allActions[actionName] paramList = [] # Extract detailed parameter information from docstring diff --git a/modules/workflows/methods/methodChatbot/actions/queryDatabase.py b/modules/workflows/methods/methodChatbot/actions/queryDatabase.py index ff7e896f..8622a5a9 100644 --- a/modules/workflows/methods/methodChatbot/actions/queryDatabase.py +++ b/modules/workflows/methods/methodChatbot/actions/queryDatabase.py @@ -89,14 +89,26 @@ async def queryDatabase(self, parameters: Dict[str, Any]) -> ActionResult: # Update progress self.services.chat.progressLogUpdate(operationId, 0.3, "Validating query") + # Validate: only SELECT queries allowed + sqlNormalized = sqlQuery.strip().upper() + if not sqlNormalized.startswith("SELECT"): + return ActionResult.isFailure(error="Only SELECT queries are allowed") + forbiddenKeywords = ["INSERT", "UPDATE", "DELETE", "DROP", "ALTER", "CREATE", "TRUNCATE", "EXEC", "EXECUTE"] + for kw in forbiddenKeywords: + if f" {kw} " in f" {sqlNormalized} " or sqlNormalized.startswith(f"{kw} "): + return ActionResult.isFailure(error=f"Forbidden SQL keyword detected: {kw}") + # Initialize connector connector = PreprocessorConnector() # Update progress self.services.chat.progressLogUpdate(operationId, 0.5, "Executing query") - # Execute query - result = await connector.executeQuery(sqlQuery) + try: + result = await connector.executeQuery(sqlQuery) + except Exception: + await connector.close() + raise # Update progress self.services.chat.progressLogUpdate(operationId, 0.8, "Formatting results") @@ -134,10 +146,9 @@ async def queryDatabase(self, parameters: Dict[str, Any]) -> ActionResult: except Exception as e: logger.error(f"Error executing database query: {str(e)}") - # Complete progress tracking with failure try: self.services.chat.progressLogFinish(operationId, False) - except: + except Exception: pass return ActionResult.isFailure( diff --git a/modules/workflows/methods/methodContext/actions/extractContent.py b/modules/workflows/methods/methodContext/actions/extractContent.py index 5b90ce13..466165ad 100644 --- a/modules/workflows/methods/methodContext/actions/extractContent.py +++ b/modules/workflows/methods/methodContext/actions/extractContent.py @@ -11,8 +11,8 @@ from modules.datamodels.datamodelExtraction import ExtractionOptions, MergeStrat logger = logging.getLogger(__name__) async def extractContent(self, parameters: Dict[str, Any]) -> ActionResult: + operationId = None try: - # Init progress logger workflowId = self.services.workflow.id if self.services.workflow else f"no-workflow-{int(time.time())}" operationId = f"context_extract_{workflowId}_{int(time.time())}" @@ -208,11 +208,11 @@ async def extractContent(self, parameters: Dict[str, Any]) -> ActionResult: except Exception as e: logger.error(f"Error in content extraction: {str(e)}") - # Complete progress tracking with failure try: - self.services.chat.progressLogFinish(operationId, False) - except: - pass # Don't fail on progress logging errors + if operationId: + self.services.chat.progressLogFinish(operationId, False) + except Exception: + pass return ActionResult.isFailure(error=str(e)) diff --git a/modules/workflows/methods/methodContext/actions/getDocumentIndex.py b/modules/workflows/methods/methodContext/actions/getDocumentIndex.py index 9991285b..b2822e0d 100644 --- a/modules/workflows/methods/methodContext/actions/getDocumentIndex.py +++ b/modules/workflows/methods/methodContext/actions/getDocumentIndex.py @@ -22,14 +22,13 @@ async def getDocumentIndex(self, parameters: Dict[str, Any]) -> ActionResult: documentsIndex = self.services.chat.getAvailableDocuments(workflow) if not documentsIndex or documentsIndex == "No documents available" or documentsIndex == "NO DOCUMENTS AVAILABLE - This workflow has no documents to process.": - # Return empty index structure + indexData = { + "workflowId": getattr(workflow, 'id', 'unknown'), + "totalDocuments": 0, + "rounds": [], + "documentReferences": [] + } if resultType == "json": - indexData = { - "workflowId": getattr(workflow, 'id', 'unknown'), - "totalDocuments": 0, - "rounds": [], - "documentReferences": [] - } indexContent = json.dumps(indexData, indent=2, ensure_ascii=False) else: indexContent = "Document Index\n==============\n\nNo documents available in this workflow.\n" @@ -64,7 +63,7 @@ async def getDocumentIndex(self, parameters: Dict[str, Any]) -> ActionResult: document = ActionDocument( documentName=filename, documentData=indexContent, - mimeType="application/json" if resultType == "json" else "text/plain", + mimeType="application/json" if resultType == "json" else ("text/markdown" if resultType == "md" else "text/plain"), validationMetadata=validationMetadata ) diff --git a/modules/workflows/methods/methodContext/actions/neutralizeData.py b/modules/workflows/methods/methodContext/actions/neutralizeData.py index 8e3b7185..d5ec045b 100644 --- a/modules/workflows/methods/methodContext/actions/neutralizeData.py +++ b/modules/workflows/methods/methodContext/actions/neutralizeData.py @@ -11,8 +11,8 @@ from modules.datamodels.datamodelExtraction import ContentExtracted, ContentPart logger = logging.getLogger(__name__) async def neutralizeData(self, parameters: Dict[str, Any]) -> ActionResult: + operationId = None try: - # Init progress logger workflowId = self.services.workflow.id if self.services.workflow else f"no-workflow-{int(time.time())}" operationId = f"context_neutralize_{workflowId}_{int(time.time())}" @@ -228,10 +228,10 @@ async def neutralizeData(self, parameters: Dict[str, Any]) -> ActionResult: except Exception as e: logger.error(f"Error in data neutralization: {str(e)}") - # Complete progress tracking with failure try: - self.services.chat.progressLogFinish(operationId, False) - except: - pass # Don't fail on progress logging errors + if operationId: + self.services.chat.progressLogFinish(operationId, False) + except Exception: + pass return ActionResult.isFailure(error=str(e)) diff --git a/modules/workflows/methods/methodOutlook/actions/readEmails.py b/modules/workflows/methods/methodOutlook/actions/readEmails.py index 2d325d9f..f388f818 100644 --- a/modules/workflows/methods/methodOutlook/actions/readEmails.py +++ b/modules/workflows/methods/methodOutlook/actions/readEmails.py @@ -29,7 +29,7 @@ async def readEmails(self, parameters: Dict[str, Any]) -> ActionResult: connectionReference = parameters.get("connectionReference") folder = parameters.get("folder", "Inbox") - limit = parameters.get("limit", 10) + limit = parameters.get("limit", 1000) filter = parameters.get("filter") outputMimeType = parameters.get("outputMimeType", "application/json") @@ -110,7 +110,6 @@ async def readEmails(self, parameters: Dict[str, Any]) -> ActionResult: if response.status_code != 200: logger.error(f"Graph API error: {response.status_code} - {response.text}") logger.error(f"Request URL: {response.url}") - logger.error(f"Request headers: {headers}") logger.error(f"Request params: {params}") response.raise_for_status() @@ -217,8 +216,8 @@ async def readEmails(self, parameters: Dict[str, Any]) -> ActionResult: if operationId: try: self.services.chat.progressLogFinish(operationId, False) - except: - pass # Don't fail on progress logging errors + except Exception: + pass return ActionResult.isFailure( error=str(e) ) diff --git a/modules/workflows/methods/methodOutlook/actions/searchEmails.py b/modules/workflows/methods/methodOutlook/actions/searchEmails.py index f8831d59..c7f839b6 100644 --- a/modules/workflows/methods/methodOutlook/actions/searchEmails.py +++ b/modules/workflows/methods/methodOutlook/actions/searchEmails.py @@ -93,7 +93,7 @@ async def searchEmails(self, parameters: Dict[str, Any]) -> ActionResult: try: error_data = response.json() logger.error(f"Microsoft Graph API error: {response.status_code} - {error_data}") - except: + except Exception: logger.error(f"Microsoft Graph API error: {response.status_code} - {response.text}") # Check for specific error types and provide helpful messages @@ -111,8 +111,6 @@ async def searchEmails(self, parameters: Dict[str, Any]) -> ActionResult: raise Exception(f"Microsoft Graph API returned {response.status_code}: {response.text}") - response.raise_for_status() - search_data = response.json() emails = search_data.get("value", []) diff --git a/modules/workflows/methods/methodOutlook/actions/sendDraftEmail.py b/modules/workflows/methods/methodOutlook/actions/sendDraftEmail.py index 15c35f44..1c0c80d4 100644 --- a/modules/workflows/methods/methodOutlook/actions/sendDraftEmail.py +++ b/modules/workflows/methods/methodOutlook/actions/sendDraftEmail.py @@ -293,8 +293,18 @@ async def sendDraftEmail(self, parameters: Dict[str, Any]) -> ActionResult: except ImportError: logger.error("requests module not available") + if operationId: + try: + self.services.chat.progressLogFinish(operationId, False) + except Exception: + pass return ActionResult.isFailure(error="requests module not available") except Exception as e: logger.error(f"Error in sendDraftEmail: {str(e)}") + if operationId: + try: + self.services.chat.progressLogFinish(operationId, False) + except Exception: + pass return ActionResult.isFailure(error=str(e)) diff --git a/modules/workflows/methods/methodOutlook/helpers/connection.py b/modules/workflows/methods/methodOutlook/helpers/connection.py index 12621fd3..cd42b7f5 100644 --- a/modules/workflows/methods/methodOutlook/helpers/connection.py +++ b/modules/workflows/methods/methodOutlook/helpers/connection.py @@ -40,25 +40,21 @@ class ConnectionHelper: logger.debug(f"Found connection: {userConnection.id}, status: {userConnection.status.value}, authority: {userConnection.authority.value}") - # Get a fresh token for this connection - token = self.services.chat.getFreshConnectionToken(userConnection.id) - if not token: - logger.error(f"Fresh token not found for connection: {userConnection.id}") - logger.debug(f"Connection details: {userConnection}") - return None - - logger.debug(f"Fresh token retrieved for connection {userConnection.id}") - - # Check if connection is active + # Check status BEFORE fetching token (avoids unnecessary network call) if userConnection.status.value != "active": logger.error(f"Connection is not active: {userConnection.id}, status: {userConnection.status.value}") return None + token = self.services.chat.getFreshConnectionToken(userConnection.id) + if not token: + logger.error(f"Fresh token not found for connection: {userConnection.id}") + return None + + logger.debug(f"Fresh token retrieved for connection {userConnection.id}") + return { "id": userConnection.id, "accessToken": token.tokenAccess, - "refreshToken": token.tokenRefresh, - "scopes": ["Mail.ReadWrite", "Mail.Send", "Mail.ReadWrite.Shared", "User.Read"] # Valid Microsoft Graph API scopes } except Exception as e: logger.error(f"Error getting Microsoft connection: {str(e)}") diff --git a/modules/workflows/methods/methodOutlook/helpers/emailProcessing.py b/modules/workflows/methods/methodOutlook/helpers/emailProcessing.py index 88644a33..f1736221 100644 --- a/modules/workflows/methods/methodOutlook/helpers/emailProcessing.py +++ b/modules/workflows/methods/methodOutlook/helpers/emailProcessing.py @@ -57,10 +57,10 @@ class EmailProcessingHelper: # This is an advanced search query, return as-is return clean_query - # For basic text search, ensure it's safe for contains() filter - # Remove any characters that might break the OData filter syntax - # Remove or escape characters that could break OData filter syntax - safe_query = re.sub(r'[\\\'"]', '', clean_query) + # Escape single quotes for OData safety (double them) + safe_query = clean_query.replace("'", "''") + # Remove backslashes and double quotes + safe_query = re.sub(r'[\\"]', '', safe_query) return safe_query @@ -173,12 +173,14 @@ class EmailProcessingHelper: # Handle email address filters (only if it's NOT a search query) if '@' in filter_text and '.' in filter_text and ' ' not in filter_text and not filter_text.startswith('from:'): - return {"$filter": f"from/fromAddress/address eq '{filter_text}'"} + safeEmail = filter_text.replace("'", "''") + return {"$filter": f"from/fromAddress/address eq '{safeEmail}'"} # Handle OData filter conditions (contains 'eq', 'ne', 'gt', 'lt', etc.) if any(op in filter_text.lower() for op in [' eq ', ' ne ', ' gt ', ' lt ', ' ge ', ' le ', ' and ', ' or ']): return {"$filter": filter_text} - # Handle text content - search in subject - return {"$filter": f"contains(subject,'{filter_text}')"} + # Handle text content - search in subject (escape single quotes) + safeText = filter_text.replace("'", "''") + return {"$filter": f"contains(subject,'{safeText}')"} diff --git a/modules/workflows/methods/methodSharepoint/actions/uploadDocument.py b/modules/workflows/methods/methodSharepoint/actions/uploadDocument.py index e9361853..c68133d5 100644 --- a/modules/workflows/methods/methodSharepoint/actions/uploadDocument.py +++ b/modules/workflows/methods/methodSharepoint/actions/uploadDocument.py @@ -240,11 +240,12 @@ async def uploadDocument(self, parameters: Dict[str, Any]) -> ActionResult: } successfulUploads = len([r for r in uploadResults if r.get("uploadStatus") == "success"]) + overallSuccess = successfulUploads > 0 self.services.chat.progressLogUpdate(operationId, 0.9, f"Uploaded {successfulUploads}/{len(uploadResults)} file(s)") - self.services.chat.progressLogFinish(operationId, successfulUploads > 0) + self.services.chat.progressLogFinish(operationId, overallSuccess) return ActionResult( - success=True, + success=overallSuccess, documents=[ ActionDocument( documentName=self._generateMeaningfulFileName("sharepoint_upload", "json", None, "uploadDocument"), @@ -260,7 +261,7 @@ async def uploadDocument(self, parameters: Dict[str, Any]) -> ActionResult: if operationId: try: self.services.chat.progressLogFinish(operationId, False) - except: + except Exception: pass return ActionResult( success=False, diff --git a/modules/workflows/methods/methodSharepoint/helpers/apiClient.py b/modules/workflows/methods/methodSharepoint/helpers/apiClient.py index 542e6dde..5b02aaab 100644 --- a/modules/workflows/methods/methodSharepoint/helpers/apiClient.py +++ b/modules/workflows/methods/methodSharepoint/helpers/apiClient.py @@ -17,14 +17,20 @@ class ApiClientHelper: """Helper for Microsoft Graph API calls""" def __init__(self, methodInstance): - """ - Initialize API client helper. - - Args: - methodInstance: Instance of MethodSharepoint (for access to services) - """ self.method = methodInstance self.services = methodInstance.services + self._session: aiohttp.ClientSession = None + + async def _getSession(self) -> aiohttp.ClientSession: + if self._session is None or self._session.closed: + timeout = aiohttp.ClientTimeout(total=30) + self._session = aiohttp.ClientSession(timeout=timeout) + return self._session + + async def close(self): + if self._session and not self._session.closed: + await self._session.close() + self._session = None async def makeGraphApiCall(self, endpoint: str, method: str = "GET", data: bytes = None) -> Dict[str, Any]: """ @@ -50,60 +56,28 @@ class ApiClientHelper: url = f"https://graph.microsoft.com/v1.0/{endpoint}" logger.info(f"Making Graph API call: {method} {url}") - # Set timeout to 30 seconds - timeout = aiohttp.ClientTimeout(total=30) + session = await self._getSession() - async with aiohttp.ClientSession(timeout=timeout) as session: - if method == "GET": - logger.debug(f"Starting GET request to {url}") - async with session.get(url, headers=headers) as response: - logger.info(f"Graph API response: {response.status}") - if response.status == 200: - result = await response.json() - logger.debug(f"Graph API success: {len(str(result))} characters response") - return result - else: - errorText = await response.text() - logger.error(f"Graph API call failed: {response.status} - {errorText}") - return {"error": f"API call failed: {response.status} - {errorText}"} - - elif method == "PUT": - logger.debug(f"Starting PUT request to {url}") - async with session.put(url, headers=headers, data=data) as response: - logger.info(f"Graph API response: {response.status}") - if response.status in [200, 201]: - result = await response.json() - logger.debug(f"Graph API success: {len(str(result))} characters response") - return result - else: - errorText = await response.text() - logger.error(f"Graph API call failed: {response.status} - {errorText}") - return {"error": f"API call failed: {response.status} - {errorText}"} - - elif method == "POST": - logger.debug(f"Starting POST request to {url}") - async with session.post(url, headers=headers, data=data) as response: - logger.info(f"Graph API response: {response.status}") - if response.status in [200, 201]: - result = await response.json() - logger.debug(f"Graph API success: {len(str(result))} characters response") - return result - else: - errorText = await response.text() - logger.error(f"Graph API call failed: {response.status} - {errorText}") - return {"error": f"API call failed: {response.status} - {errorText}"} - - elif method == "DELETE": - logger.debug(f"Starting DELETE request to {url}") - async with session.delete(url, headers=headers) as response: - logger.info(f"Graph API response: {response.status}") - if response.status in [200, 204]: - logger.debug(f"Graph API DELETE success") - return {"success": True} - else: - errorText = await response.text() - logger.error(f"Graph API call failed: {response.status} - {errorText}") - return {"error": f"API call failed: {response.status} - {errorText}"} + successCodes = {"GET": [200], "PUT": [200, 201], "POST": [200, 201], "DELETE": [200, 204]} + httpMethod = getattr(session, method.lower(), None) + if not httpMethod: + return {"error": f"Unsupported HTTP method: {method}"} + + kwargs = {"headers": headers} + if data is not None: + kwargs["data"] = data + + async with httpMethod(url, **kwargs) as response: + logger.info(f"Graph API response: {response.status}") + if response.status in successCodes.get(method, [200]): + if method == "DELETE": + return {"success": True} + result = await response.json() + return result + else: + errorText = await response.text() + logger.error(f"Graph API call failed: {response.status} - {errorText}") + return {"error": f"API call failed: {response.status} - {errorText}"} except asyncio.TimeoutError: logger.error(f"Graph API call timed out after 30 seconds: {endpoint}") diff --git a/modules/workflows/processing/adaptive/adaptiveLearningEngine.py b/modules/workflows/processing/adaptive/adaptiveLearningEngine.py index 7efdaef0..18588cf2 100644 --- a/modules/workflows/processing/adaptive/adaptiveLearningEngine.py +++ b/modules/workflows/processing/adaptive/adaptiveLearningEngine.py @@ -14,11 +14,19 @@ class AdaptiveLearningEngine: """Enhanced learning engine that tracks validation patterns and adapts prompts""" def __init__(self): - self.validationHistory = [] # Store validation results with context - self.failurePatterns = defaultdict(list) # Track failure patterns by action type - self.successPatterns = defaultdict(list) # Track success patterns - self.actionAttempts = defaultdict(int) # Track attempt counts per action - self.learningInsights = {} # Store learned insights per workflow + self.validationHistory = [] + self.failurePatterns = defaultdict(list) + self.successPatterns = defaultdict(list) + self.actionAttempts = defaultdict(int) + self.learningInsights = {} + + def reset(self): + """Reset all learned state for a new workflow session.""" + self.validationHistory.clear() + self.failurePatterns.clear() + self.successPatterns.clear() + self.actionAttempts.clear() + self.learningInsights.clear() def recordValidationResult(self, validationResult: Dict[str, Any], actionContext: Dict[str, Any], workflowId: str, attemptNumber: int): @@ -195,15 +203,6 @@ class AdaptiveLearningEngine: for issue, count in list(commonIssues.items())[:3]: # Top 3 issues guidance_parts.append(f"- {issue} (occurred {count} times)") - # Add specific action guidance based on user prompt - if "email" in userPrompt.lower() and "outlook" in userPrompt.lower(): - if any("account" in str(issue).lower() for issue in commonIssues.keys()): - guidance_parts.append("SPECIFIC GUIDANCE: Ensure email is sent from the correct account (valueon).") - if any("attachment" in str(issue).lower() for issue in commonIssues.keys()): - guidance_parts.append("SPECIFIC GUIDANCE: Verify PDF attachment is properly included.") - if any("summary" in str(issue).lower() for issue in commonIssues.keys()): - guidance_parts.append("SPECIFIC GUIDANCE: Include German summary in email body.") - return "\n".join(guidance_parts) if guidance_parts else "No specific guidance available." def _generateParameterGuidance(self, actionName: str, parametersContext: str, @@ -219,12 +218,11 @@ class AdaptiveLearningEngine: if attemptNumber and attemptNumber >= 3: guidanceParts.append(f"Attempt #{attemptNumber}: Adjust parameters based on validation feedback.") - # Generic issues summary commonIssues = failureAnalysis.get('commonIssues', {}) or {} if commonIssues: guidanceParts.append("Address the following parameter issues:") - for issueKey, issueDesc in commonIssues.items(): - guidanceParts.append(f"- {issueKey}: {issueDesc}") + for issueText, count in commonIssues.items(): + guidanceParts.append(f"- {issueText} (occurred {count} time{'s' if count != 1 else ''})") # Keep guidance format stable return "\n".join(guidanceParts) if guidanceParts else "Use standard parameter values." diff --git a/modules/workflows/processing/adaptive/contentValidator.py b/modules/workflows/processing/adaptive/contentValidator.py index fe17572f..e8ba106b 100644 --- a/modules/workflows/processing/adaptive/contentValidator.py +++ b/modules/workflows/processing/adaptive/contentValidator.py @@ -273,16 +273,15 @@ class ContentValidator: elif section.get("content_type") in ["paragraph", "heading"]: if elements and isinstance(elements, list) and len(elements) > 0: textElement = elements[0] - # Ensure textElement is a dictionary before accessing if isinstance(textElement, dict): content = textElement.get("content", {}) - if isinstance(content, dict): - text = content.get("text", "") - else: - text = textElement.get("text", "") - if text: - sectionSummary["textLength"] = len(text) - sectionSummary["wordCount"] = len(text.split()) + if isinstance(content, dict): + text = content.get("text", "") + else: + text = textElement.get("text", "") + if text: + sectionSummary["textLength"] = len(text) + sectionSummary["wordCount"] = len(text.split()) if section.get("textLength"): sectionSummary["textLength"] = section.get("textLength") @@ -290,59 +289,47 @@ class ContentValidator: elif section.get("content_type") == "code_block": if elements and isinstance(elements, list) and len(elements) > 0: codeElement = elements[0] - content = codeElement.get("content", {}) - if isinstance(content, dict): - code = content.get("code", "") - language = content.get("language", "") - if code: - sectionSummary["codeLength"] = len(code) - sectionSummary["codeLineCount"] = code.count('\n') + 1 - if language: - sectionSummary["language"] = language + if isinstance(codeElement, dict): + content = codeElement.get("content", {}) + if isinstance(content, dict): + code = content.get("code", "") + language = content.get("language", "") + if code: + sectionSummary["codeLength"] = len(code) + sectionSummary["codeLineCount"] = code.count('\n') + 1 + if language: + sectionSummary["language"] = language - # Wenn contentPartIds vorhanden sind, aber keine elements: Füge ContentParts-Metadaten hinzu contentPartIds = section.get("contentPartIds", []) if contentPartIds and not elements: - # Prüfe ob contentPartsMetadata vorhanden ist contentPartsMetadata = section.get("contentPartsMetadata", []) if contentPartsMetadata: sectionSummary["contentPartsMetadata"] = contentPartsMetadata else: - # Fallback: Zeige nur IDs wenn Metadaten nicht verfügbar sectionSummary["contentPartIds"] = contentPartIds sectionSummary["note"] = "ContentParts referenced but metadata not available" - # Include any additional fields from section (generic approach) - # BUT exclude type-specific KPIs that don't belong to this content_type - # AND exclude internal planning fields that confuse validation contentType = section.get("content_type", "") - # Define KPIs that are ONLY valid for specific types typeExclusiveKpis = { - "table": ["columnCount", "rowCount", "headers"], # Only for tables - "bullet_list": ["itemCount"], # Only for bullet_list - "list": ["itemCount"] # Only for list + "table": ["columnCount", "rowCount", "headers"], + "bullet_list": ["itemCount"], + "list": ["itemCount"] } excludedKpis = [] for kpiType, kpiFields in typeExclusiveKpis.items(): if kpiType != contentType: excludedKpis.extend(kpiFields) - # Internal planning fields that should NOT be shown to validation AI - # These are implementation details, not content indicators internalFields = ["generationHint", "useAiCall", "elements"] for key, value in section.items(): if key not in sectionSummary and key not in internalFields and key not in excludedKpis: - # Don't copy type-specific KPIs if they're 0/empty and we didn't extract them ourselves - # This prevents copying columnCount: 0, rowCount: 0, headers: [] from structure generation phase if key in ["columnCount", "rowCount", "headers", "itemCount"]: - # Skip if it's 0/empty - we'll only include KPIs we extracted from elements if isinstance(value, int) and value == 0: continue if isinstance(value, list) and len(value) == 0: continue - # Include simple types (str, int, float, bool, list of primitives) if isinstance(value, (str, int, float, bool)) or (isinstance(value, list) and len(value) <= 10): sectionSummary[key] = value @@ -486,7 +473,7 @@ class ContentValidator: try: json_str = json.dumps(data) size_bytes = len(json_str.encode('utf-8')) - except: + except (TypeError, ValueError): size_bytes = len(str(data).encode('utf-8')) else: size_bytes = len(str(data).encode('utf-8')) diff --git a/modules/workflows/processing/adaptive/learningEngine.py b/modules/workflows/processing/adaptive/learningEngine.py index 83cf7b13..8fb2f958 100644 --- a/modules/workflows/processing/adaptive/learningEngine.py +++ b/modules/workflows/processing/adaptive/learningEngine.py @@ -16,6 +16,11 @@ class LearningEngine: self.strategies = {} self.feedbackHistory = [] + def reset(self): + """Reset all learned state for a new workflow session.""" + self.strategies.clear() + self.feedbackHistory.clear() + def learnFromFeedback(self, feedback: Dict[str, Any], context: Any, taskIntent: Dict[str, Any]): """Learns from feedback and updates strategies - works on TASK level, not workflow level""" try: diff --git a/modules/workflows/processing/core/actionExecutor.py b/modules/workflows/processing/core/actionExecutor.py index 0e4d6ee4..6b1e3544 100644 --- a/modules/workflows/processing/core/actionExecutor.py +++ b/modules/workflows/processing/core/actionExecutor.py @@ -136,6 +136,7 @@ class ActionExecutor: # Execute action and track success for progress log result = None actionSuccess = False + actionError = None try: result = await self.executeAction( methodName=action.execMethod, @@ -144,23 +145,23 @@ class ActionExecutor: ) actionSuccess = result.success if result else False except Exception as e: - logger.error(f"Error executing action: {str(e)}") + logger.error(f"Error executing action {action.execMethod}.{action.execAction}: {str(e)}") actionSuccess = False + actionError = str(e) finally: - # Finish action progress tracking try: self.services.chat.progressLogFinish(actionOperationId, actionSuccess) except Exception as e: logger.error(f"Error finishing action progress log: {str(e)}") - # If action execution failed, return error result if result is None: - action.setError("Action execution failed") + errorMsg = actionError or "Action execution failed" + action.setError(errorMsg) return ActionResult( success=False, documents=[], resultLabel=action.execResultLabel, - error="Action execution failed" + error=errorMsg ) resultLabel = action.execResultLabel diff --git a/modules/workflows/processing/core/messageCreator.py b/modules/workflows/processing/core/messageCreator.py index a4ae05e9..48df832d 100644 --- a/modules/workflows/processing/core/messageCreator.py +++ b/modules/workflows/processing/core/messageCreator.py @@ -319,56 +319,27 @@ class MessageCreator: except Exception as e: logger.error(f"Error creating error message: {str(e)}") - def _extractRoundNumberFromLabel(self, label: str) -> int: - """Extract round number from a document label like 'round1_task1_action1_diagram_analysis'""" + def _extractNumberFromLabelPart(self, label: str, prefix: str) -> int: + """Extract number following a prefix in a label like 'round1_task1_action1_context'. + Works for prefix='round', 'task', 'action'. Returns 0 on failure. + """ try: if not label or not isinstance(label, str): return 0 - # Parse label format: round{round}_task{task}_action{action}_{context} - if label.startswith('round'): - roundPart = label.split('_')[0] # Get 'round1' part - if roundPart.startswith('round'): - roundNumber = roundPart[5:] # Remove 'round' prefix - return int(roundNumber) - - return 0 + import re + pattern = rf'{prefix}(\d+)' + match = re.search(pattern, label) + return int(match.group(1)) if match else 0 except Exception as e: - logger.warning(f"Could not extract round number from label '{label}': {str(e)}") + logger.warning(f"Could not extract {prefix} number from label '{label}': {str(e)}") return 0 + def _extractRoundNumberFromLabel(self, label: str) -> int: + return self._extractNumberFromLabelPart(label, 'round') + def _extractTaskNumberFromLabel(self, label: str) -> int: - """Extract task number from a document label like 'round1_task1_action1_diagram_analysis'""" - try: - if not label or not isinstance(label, str): - return 0 - - # Parse label format: round{round}_task{task}_action{action}_{context} - if '_task' in label: - taskPart = label.split('_task')[1] - if taskPart and '_' in taskPart: - taskNumber = taskPart.split('_')[0] - return int(taskNumber) - - return 0 - except Exception as e: - logger.warning(f"Could not extract task number from label '{label}': {str(e)}") - return 0 + return self._extractNumberFromLabelPart(label, 'task') def _extractActionNumberFromLabel(self, label: str) -> int: - """Extract action number from a document label like 'round1_task1_action1_diagram_analysis'""" - try: - if not label or not isinstance(label, str): - return 0 - - # Parse label format: round{round}_task{task}_action{action}_{context} - if '_action' in label: - actionPart = label.split('_action')[1] - if actionPart and '_' in actionPart: - actionNumber = actionPart.split('_')[0] - return int(actionNumber) - - return 0 - except Exception as e: - logger.warning(f"Could not extract action number from label '{label}': {str(e)}") - return 0 + return self._extractNumberFromLabelPart(label, 'action') diff --git a/modules/workflows/processing/core/taskPlanner.py b/modules/workflows/processing/core/taskPlanner.py index b1e1def7..233488fe 100644 --- a/modules/workflows/processing/core/taskPlanner.py +++ b/modules/workflows/processing/core/taskPlanner.py @@ -7,7 +7,6 @@ import json import logging from typing import Dict, Any from modules.datamodels.datamodelChat import TaskStep, TaskContext, TaskPlan, WorkflowModeEnum -from modules.datamodels.datamodelAi import AiCallOptions, OperationTypeEnum, ProcessingModeEnum, PriorityEnum from modules.workflows.processing.shared.promptGenerationTaskplan import ( generateTaskPlanningPrompt ) @@ -107,17 +106,6 @@ class TaskPlanner: taskPlanningPromptTemplate = bundle.prompt placeholders = bundle.placeholders - # Centralized AI call: Task planning (quality, detailed) with placeholders - options = AiCallOptions( - operationType=OperationTypeEnum.PLAN, - priority=PriorityEnum.QUALITY, - compressPrompt=False, - compressContext=False, - processingMode=ProcessingModeEnum.DETAILED, - maxCost=0.10, - maxProcessingTime=30 - ) - prompt = await self.services.ai.callAiPlanning( prompt=taskPlanningPromptTemplate, placeholders=placeholders, @@ -141,9 +129,11 @@ class TaskPlanner: raise ValueError("Task plan missing 'tasks' field") except Exception as e: logger.error(f"Error parsing task plan response: {str(e)}") - taskPlanDict = {'tasks': []} + raise ValueError(f"Failed to parse AI task plan response: {str(e)}") from e - if not self._validateTaskPlan(taskPlanDict): + from modules.workflows.processing.core.validator import WorkflowValidator + validator = WorkflowValidator(self.services) + if not validator.validateTask(taskPlanDict): logger.error("Generated task plan failed validation") logger.error(f"AI Response: {prompt}") logger.error(f"Parsed Task Plan: {json.dumps(taskPlanDict, indent=2)}") @@ -207,61 +197,4 @@ class TaskPlanner: logger.error(f"Error in generateTaskPlan: {str(e)}") raise - - - def _validateTaskPlan(self, taskPlan: Dict[str, Any]) -> bool: - """Validate task plan structure""" - try: - if not isinstance(taskPlan, dict): - logger.error("Task plan is not a dictionary") - return False - - if 'tasks' not in taskPlan or not isinstance(taskPlan['tasks'], list): - logger.error(f"Task plan missing 'tasks' field or not a list. Found: {type(taskPlan.get('tasks', 'MISSING'))}") - return False - - # First pass: collect all task IDs to validate dependencies - taskIds = set() - for task in taskPlan['tasks']: - if not isinstance(task, dict): - logger.error(f"Task is not a dictionary: {type(task)}") - return False - if 'id' not in task: - logger.error(f"Task missing 'id' field: {task}") - return False - taskIds.add(task['id']) - - # Second pass: validate each task - for i, task in enumerate(taskPlan['tasks']): - if not isinstance(task, dict): - logger.error(f"Task {i} is not a dictionary: {type(task)}") - return False - - requiredFields = ['id', 'objective', 'successCriteria'] - missingFields = [field for field in requiredFields if field not in task] - if missingFields: - logger.error(f"Task {i} missing required fields: {missingFields}") - return False - - # Check for duplicate IDs (shouldn't happen after first pass, but safety check) - if task['id'] in taskIds and list(taskPlan['tasks']).count(task['id']) > 1: - logger.error(f"Task {i} has duplicate ID: {task['id']}") - return False - - dependencies = task.get('dependencies', []) - if not isinstance(dependencies, list): - logger.error(f"Task {i} dependencies is not a list: {type(dependencies)}") - return False - - for dep in dependencies: - if dep not in taskIds and dep != 'task_0': - logger.error(f"Task {i} has invalid dependency: {dep} (available: {list(taskIds) + ['task_0']})") - return False - - logger.info(f"Task plan validation successful with {len(taskIds)} tasks") - return True - - except Exception as e: - logger.error(f"Error validating task plan: {str(e)}") - return False \ No newline at end of file diff --git a/modules/workflows/processing/core/validator.py b/modules/workflows/processing/core/validator.py index 74d67b19..67c685e8 100644 --- a/modules/workflows/processing/core/validator.py +++ b/modules/workflows/processing/core/validator.py @@ -25,40 +25,35 @@ class WorkflowValidator: logger.error(f"Task plan missing 'tasks' field or not a list. Found: {type(taskPlan.get('tasks', 'MISSING'))}") return False - # First pass: collect all task IDs to validate dependencies + # Single pass: collect IDs (detect duplicates) and validate each task taskIds = set() - for task in taskPlan['tasks']: - if not isinstance(task, dict): - logger.error(f"Task is not a dictionary: {type(task)}") - return False - if 'id' not in task: - logger.error(f"Task missing 'id' field: {task}") - return False - taskIds.add(task['id']) - - # Second pass: validate each task for i, task in enumerate(taskPlan['tasks']): if not isinstance(task, dict): logger.error(f"Task {i} is not a dictionary: {type(task)}") return False + if 'id' not in task: + logger.error(f"Task {i} missing 'id' field: {task}") + return False + + if task['id'] in taskIds: + logger.error(f"Task {i} has duplicate ID: {task['id']}") + return False + taskIds.add(task['id']) requiredFields = ['id', 'objective', 'successCriteria'] missingFields = [field for field in requiredFields if field not in task] if missingFields: logger.error(f"Task {i} missing required fields: {missingFields}") return False - - # Check for duplicate IDs (shouldn't happen after first pass, but safety check) - if task['id'] in taskIds and list(taskPlan['tasks']).count(task['id']) > 1: - logger.error(f"Task {i} has duplicate ID: {task['id']}") - return False dependencies = task.get('dependencies', []) if not isinstance(dependencies, list): logger.error(f"Task {i} dependencies is not a list: {type(dependencies)}") return False - - for dep in dependencies: + + # Second pass: validate dependencies (all IDs now known) + for i, task in enumerate(taskPlan['tasks']): + for dep in task.get('dependencies', []): if dep not in taskIds and dep != 'task_0': logger.error(f"Task {i} has invalid dependency: {dep} (available: {list(taskIds) + ['task_0']})") return False @@ -93,7 +88,7 @@ class WorkflowValidator: missingFields = [] for field in requiredFields: - if field not in action or not action[field]: + if field not in action or action[field] is None: missingFields.append(field) if missingFields: logger.error(f"Action {i} missing required fields: {missingFields}") diff --git a/modules/workflows/processing/modes/modeAutomation.py b/modules/workflows/processing/modes/modeAutomation.py index 4e3c7853..1d0121b9 100644 --- a/modules/workflows/processing/modes/modeAutomation.py +++ b/modules/workflows/processing/modes/modeAutomation.py @@ -36,6 +36,9 @@ class AutomationMode(BaseMode): - Or as direct JSON in userInput """ try: + # Reset action map to prevent state leaks from previous runs + self.taskActionMap = {} + # AUTOMATION mode ALWAYS requires a JSON plan to be provided in userInput # Try to extract plan from userInput (embedded JSON or direct JSON) templatePlan = None @@ -340,78 +343,6 @@ class AutomationMode(BaseMode): error=str(e) ) - def _createActionItem(self, actionData: Dict[str, Any]) -> Optional[ActionItem]: - """Create ActionItem from action data""" - try: - import uuid - from datetime import datetime, timezone - - # Ensure ID is present - if "id" not in actionData or not actionData["id"]: - actionData["id"] = f"action_{uuid.uuid4()}" - - # Ensure required fields - if "status" not in actionData: - actionData["status"] = TaskStatus.PENDING - - if "execMethod" not in actionData: - logger.error("execMethod is required for task action") - return None - - if "execAction" not in actionData: - logger.error("execAction is required for task action") - return None - - if "execParameters" not in actionData: - actionData["execParameters"] = {} - - # Use generic field separation based on ActionItem model - simpleFields, objectFields = self.services.interfaceDbChat._separateObjectFields(ActionItem, actionData) - - # Create action in database - createdAction = self.services.interfaceDbChat.db.recordCreate(ActionItem, simpleFields) - - # Convert to ActionItem model - return ActionItem( - id=createdAction["id"], - execMethod=createdAction["execMethod"], - execAction=createdAction["execAction"], - execParameters=createdAction.get("execParameters", {}), - execResultLabel=createdAction.get("execResultLabel"), - expectedDocumentFormats=createdAction.get("expectedDocumentFormats"), - status=createdAction.get("status", TaskStatus.PENDING), - error=createdAction.get("error"), - retryCount=createdAction.get("retryCount", 0), - retryMax=createdAction.get("retryMax", 3), - processingTime=createdAction.get("processingTime"), - timestamp=parseTimestamp(createdAction.get("timestamp"), default=self.services.utils.timestampGetUtc()), - result=createdAction.get("result"), - userMessage=createdAction.get("userMessage") - ) - - except Exception as e: - logger.error(f"Error creating task action: {str(e)}") - return None - - def _updateWorkflowBeforeExecutingTask(self, taskNumber: int): - """Update workflow object before executing a task""" - try: - workflow = self.services.workflow - updateData = { - "currentTask": taskNumber, - "currentAction": 0, - "totalActions": 0 - } - - workflow.currentTask = taskNumber - workflow.currentAction = 0 - workflow.totalActions = 0 - - self.services.interfaceDbChat.updateWorkflow(workflow.id, updateData) - logger.info(f"Updated workflow {workflow.id} before executing task {taskNumber}") - except Exception as e: - logger.error(f"Error updating workflow before executing task: {str(e)}") - def _updateWorkflowAfterActionPlanning(self, totalActions: int): """Update workflow object after action planning""" try: @@ -423,17 +354,6 @@ class AutomationMode(BaseMode): except Exception as e: logger.error(f"Error updating workflow after action planning: {str(e)}") - def _updateWorkflowBeforeExecutingAction(self, actionNumber: int): - """Update workflow object before executing an action""" - try: - workflow = self.services.workflow - updateData = {"currentAction": actionNumber} - workflow.currentAction = actionNumber - self.services.interfaceDbChat.updateWorkflow(workflow.id, updateData) - logger.info(f"Updated workflow {workflow.id} before executing action {actionNumber}") - except Exception as e: - logger.error(f"Error updating workflow before executing action: {str(e)}") - def _setWorkflowTotals(self, totalTasks: int = None, totalActions: int = None): """Set total counts for workflow progress tracking""" try: diff --git a/modules/workflows/processing/modes/modeBase.py b/modules/workflows/processing/modes/modeBase.py index 770c868a..fe9a5da6 100644 --- a/modules/workflows/processing/modes/modeBase.py +++ b/modules/workflows/processing/modes/modeBase.py @@ -4,14 +4,16 @@ # Abstract base class for workflow modes from abc import ABC, abstractmethod +import uuid import logging -from typing import List, Dict, Any -from modules.datamodels.datamodelChat import TaskStep, TaskContext, TaskResult, ActionItem +from typing import List, Dict, Any, Optional +from modules.datamodels.datamodelChat import TaskStep, TaskContext, TaskResult, ActionItem, TaskStatus from modules.datamodels.datamodelChat import ChatWorkflow from modules.workflows.processing.core.taskPlanner import TaskPlanner from modules.workflows.processing.core.actionExecutor import ActionExecutor from modules.workflows.processing.core.messageCreator import MessageCreator from modules.workflows.processing.core.validator import WorkflowValidator +from modules.shared.timeUtils import parseTimestamp logger = logging.getLogger(__name__) @@ -44,3 +46,75 @@ class BaseMode(ABC): async def createTaskPlanMessage(self, taskPlan, workflow: ChatWorkflow): """Create task plan message - common to all modes""" return await self.messageCreator.createTaskPlanMessage(taskPlan, workflow) + + def _createActionItem(self, actionData: Dict[str, Any]) -> Optional[ActionItem]: + """Create an ActionItem from action data, persist to DB, and return the model instance""" + try: + if "id" not in actionData or not actionData["id"]: + actionData["id"] = f"action_{uuid.uuid4()}" + + if "status" not in actionData: + actionData["status"] = TaskStatus.PENDING + + if "execMethod" not in actionData: + logger.error("execMethod is required for task action") + return None + + if "execAction" not in actionData: + logger.error("execAction is required for task action") + return None + + if "execParameters" not in actionData: + actionData["execParameters"] = {} + + simpleFields, objectFields = self.services.interfaceDbChat._separateObjectFields(ActionItem, actionData) + createdAction = self.services.interfaceDbChat.db.recordCreate(ActionItem, simpleFields) + + return ActionItem( + id=createdAction["id"], + execMethod=createdAction["execMethod"], + execAction=createdAction["execAction"], + execParameters=createdAction.get("execParameters", {}), + execResultLabel=createdAction.get("execResultLabel"), + expectedDocumentFormats=createdAction.get("expectedDocumentFormats"), + status=createdAction.get("status", TaskStatus.PENDING), + error=createdAction.get("error"), + retryCount=createdAction.get("retryCount", 0), + retryMax=createdAction.get("retryMax", 3), + processingTime=createdAction.get("processingTime"), + timestamp=parseTimestamp(createdAction.get("timestamp"), default=self.services.utils.timestampGetUtc()), + result=createdAction.get("result"), + userMessage=createdAction.get("userMessage") + ) + + except Exception as e: + logger.error(f"Error creating task action: {str(e)}") + return None + + def _updateWorkflowBeforeExecutingTask(self, taskNumber: int): + """Update workflow state before executing a task""" + try: + workflow = self.services.workflow + updateData = { + "currentTask": taskNumber, + "currentAction": 0, + "totalActions": 0 + } + workflow.currentTask = taskNumber + workflow.currentAction = 0 + workflow.totalActions = 0 + self.services.interfaceDbChat.updateWorkflow(workflow.id, updateData) + logger.info(f"Updated workflow {workflow.id} before executing task {taskNumber}") + except Exception as e: + logger.error(f"Error updating workflow before executing task: {str(e)}") + + def _updateWorkflowBeforeExecutingAction(self, actionNumber: int): + """Update workflow state before executing an action""" + try: + workflow = self.services.workflow + updateData = {"currentAction": actionNumber} + workflow.currentAction = actionNumber + self.services.interfaceDbChat.updateWorkflow(workflow.id, updateData) + logger.info(f"Updated workflow {workflow.id} before executing action {actionNumber}") + except Exception as e: + logger.error(f"Error updating workflow before executing action: {str(e)}") diff --git a/modules/workflows/processing/modes/modeDynamic.py b/modules/workflows/processing/modes/modeDynamic.py index e59a9253..eeae30e5 100644 --- a/modules/workflows/processing/modes/modeDynamic.py +++ b/modules/workflows/processing/modes/modeDynamic.py @@ -116,6 +116,7 @@ class DynamicMode(BaseMode): step = 1 decision = None + lastStepFailed = False while step <= state.max_steps: checkWorkflowStopped(self.services) @@ -282,6 +283,7 @@ class DynamicMode(BaseMode): except Exception as e: logger.error(f"Dynamic step {step} error: {e}") + lastStepFailed = True break # NEW: Use adaptive stopping logic @@ -296,19 +298,24 @@ class DynamicMode(BaseMode): step += 1 # Summarize task result for dynamic mode - status = TaskStatus.COMPLETED - success = True - # Get feedback from last decision if available lastDecision = context.previousReviewResult[-1] if hasattr(context, 'previousReviewResult') and context.previousReviewResult else None feedback = lastDecision.reason if lastDecision and isinstance(lastDecision, ReviewResult) else 'Completed' - if lastDecision and isinstance(lastDecision, ReviewResult) and lastDecision.status == 'success': + + if lastStepFailed: + status = TaskStatus.FAILED + success = False + elif lastDecision and isinstance(lastDecision, ReviewResult) and lastDecision.status in ('stop', 'failed'): + status = TaskStatus.FAILED + success = False + else: + status = TaskStatus.COMPLETED success = True # Create proper ReviewResult for completion message completionReviewResult = ReviewResult( - status='success', + status='success' if success else 'failed', reason=feedback, - qualityScore=lastDecision.qualityScore if lastDecision and isinstance(lastDecision, ReviewResult) else 8.0, + qualityScore=lastDecision.qualityScore if lastDecision and isinstance(lastDecision, ReviewResult) else (8.0 if success else 2.0), metCriteria=[], improvements=[] ) @@ -1003,12 +1010,15 @@ class DynamicMode(BaseMode): # Detect repeated actions actionCounts = {} for entry in actionHistory: - # Extract action name (after first space, before next space or {) - parts = entry.split() - if len(parts) > 1: - # Skip "Step", "Refinement" prefixes and get the action name - actionName = parts[1] if parts[0] in ['Step', 'Refinement'] else parts[0] - actionCounts[actionName] = actionCounts.get(actionName, 0) + 1 + # Format: "Step N: actionName ..." or "Refinement N: actionName ..." + # Extract the action name after "prefix N:" + colonIdx = entry.find(':') + if colonIdx >= 0: + afterColon = entry[colonIdx + 1:].strip().split() + actionName = afterColon[0] if afterColon else 'unknown' + else: + actionName = entry.split()[0] if entry.split() else 'unknown' + actionCounts[actionName] = actionCounts.get(actionName, 0) + 1 repeatedActions = [action for action, count in actionCounts.items() if count >= 2] if repeatedActions: @@ -1172,150 +1182,6 @@ Return only the user-friendly message, no technical details.""" logger.error(f"Error generating action result message: {str(e)}") return f"{method}.{actionName} action completed" - def _createActionItem(self, actionData: Dict[str, Any]) -> ActionItem: - """Creates a new task action for Dynamic mode""" - try: - import uuid - - # Ensure ID is present - if "id" not in actionData or not actionData["id"]: - actionData["id"] = f"action_{uuid.uuid4()}" - - # Ensure required fields - if "status" not in actionData: - actionData["status"] = TaskStatus.PENDING - - if "execMethod" not in actionData: - logger.error("execMethod is required for task action") - return None - - if "execAction" not in actionData: - logger.error("execAction is required for task action") - return None - - if "execParameters" not in actionData: - actionData["execParameters"] = {} - - # Use generic field separation based on ActionItem model - simpleFields, objectFields = self.services.interfaceDbChat._separateObjectFields(ActionItem, actionData) - - # Create action in database - createdAction = self.services.interfaceDbChat.db.recordCreate(ActionItem, simpleFields) - - # Convert to ActionItem model - return ActionItem( - id=createdAction["id"], - execMethod=createdAction["execMethod"], - execAction=createdAction["execAction"], - execParameters=createdAction.get("execParameters", {}), - execResultLabel=createdAction.get("execResultLabel"), - expectedDocumentFormats=createdAction.get("expectedDocumentFormats"), - status=createdAction.get("status", TaskStatus.PENDING), - error=createdAction.get("error"), - retryCount=createdAction.get("retryCount", 0), - retryMax=createdAction.get("retryMax", 3), - processingTime=createdAction.get("processingTime"), - timestamp=parseTimestamp(createdAction.get("timestamp"), default=self.services.utils.timestampGetUtc()), - result=createdAction.get("result"), - resultDocuments=createdAction.get("resultDocuments", []), - userMessage=createdAction.get("userMessage") - ) - - except Exception as e: - logger.error(f"Error creating task action: {str(e)}") - return None - def _updateWorkflowBeforeExecutingTask(self, taskNumber: int): - """Update workflow object before executing a task""" - try: - workflow = self.services.workflow - updateData = { - "currentTask": taskNumber, - "currentAction": 0, - "totalActions": 0 - } - - # Update workflow object - workflow.currentTask = taskNumber - workflow.currentAction = 0 - workflow.totalActions = 0 - - # Update in database - self.services.interfaceDbChat.updateWorkflow(workflow.id, updateData) - logger.info(f"Updated workflow {workflow.id} before executing task {taskNumber}: {updateData}") - - except Exception as e: - logger.error(f"Error updating workflow before executing task: {str(e)}") - def _updateWorkflowBeforeExecutingAction(self, actionNumber: int): - """Update workflow object before executing an action""" - try: - workflow = self.services.workflow - updateData = { - "currentAction": actionNumber - } - - # Update workflow object - workflow.currentAction = actionNumber - - # Update in database - self.services.interfaceDbChat.updateWorkflow(workflow.id, updateData) - logger.info(f"Updated workflow {workflow.id} before executing action {actionNumber}: {updateData}") - - except Exception as e: - logger.error(f"Error updating workflow before executing action: {str(e)}") - - def _createActionItem(self, actionData: Dict[str, Any]) -> ActionItem: - """Creates a new task action for Dynamic mode""" - try: - import uuid - - # Ensure ID is present - if "id" not in actionData or not actionData["id"]: - actionData["id"] = f"action_{uuid.uuid4()}" - - # Ensure required fields - if "status" not in actionData: - actionData["status"] = TaskStatus.PENDING - - if "execMethod" not in actionData: - logger.error("execMethod is required for task action") - return None - - if "execAction" not in actionData: - logger.error("execAction is required for task action") - return None - - if "execParameters" not in actionData: - actionData["execParameters"] = {} - - # Use generic field separation based on ActionItem model - simpleFields, objectFields = self.services.interfaceDbChat._separateObjectFields(ActionItem, actionData) - - # Create action in database - createdAction = self.services.interfaceDbChat.db.recordCreate(ActionItem, simpleFields) - - # Convert to ActionItem model - return ActionItem( - id=createdAction["id"], - execMethod=createdAction["execMethod"], - execAction=createdAction["execAction"], - execParameters=createdAction.get("execParameters", {}), - execResultLabel=createdAction.get("execResultLabel"), - expectedDocumentFormats=createdAction.get("expectedDocumentFormats"), - status=createdAction.get("status", TaskStatus.PENDING), - error=createdAction.get("error"), - retryCount=createdAction.get("retryCount", 0), - retryMax=createdAction.get("retryMax", 3), - processingTime=createdAction.get("processingTime"), - timestamp=parseTimestamp(createdAction.get("timestamp"), default=self.services.utils.timestampGetUtc()), - result=createdAction.get("result"), - resultDocuments=createdAction.get("resultDocuments", []), - userMessage=createdAction.get("userMessage") - ) - - except Exception as e: - logger.error(f"Error creating task action: {str(e)}") - return None - diff --git a/modules/workflows/processing/shared/executionState.py b/modules/workflows/processing/shared/executionState.py index 1cdf0d53..e5e48a01 100644 --- a/modules/workflows/processing/shared/executionState.py +++ b/modules/workflows/processing/shared/executionState.py @@ -5,23 +5,22 @@ import logging from typing import List, Optional -from modules.datamodels.datamodelChat import TaskStep, ActionResult, Observation +from modules.datamodels.datamodelChat import TaskStep, ActionResult logger = logging.getLogger(__name__) class TaskExecutionState: """Manages execution state for a task with retry logic""" - def __init__(self, task_step: TaskStep): - self.task_step = task_step - self.successful_actions: List[ActionResult] = [] # Preserved across retries - self.failed_actions: List[ActionResult] = [] # For analysis + def __init__(self, taskStep: TaskStep): + self.task_step = taskStep + self.successful_actions: List[ActionResult] = [] + self.failed_actions: List[ActionResult] = [] self.current_action_index = 0 self.retry_count = 0 self.max_retries = 3 - # Iterative loop (dynamic mode) self.current_step = 0 - self.max_steps = 0 # Will be overridden by workflow.maxSteps from workflowManager.py + self.max_steps = 0 def addSuccessfulAction(self, action_result: ActionResult): """Add a successful action to the state""" @@ -58,48 +57,25 @@ class TaskExecutionState: patterns.append("permission_issues") return list(set(patterns)) -def shouldContinue(observation: Optional[Observation], review=None, current_step: int = 0, max_steps: int = 1) -> bool: - """Helper to decide if the iterative loop should continue +def shouldContinue(observation=None, review=None, current_step: int = 0, max_steps: int = 1) -> bool: + """Helper to decide if the iterative loop should continue. - Args: - observation: Observation Pydantic model with action execution results - review: ReviewResult or dict with review decision (optional) - current_step: Current step number in the iteration - max_steps: Maximum allowed steps - - Returns: - bool: True if loop should continue, False if should stop - - Logic: - - Stop if max steps reached - - Stop if review indicates 'stop' or success criteria are met - - Continue if observation indicates failure but allow one more step (caller caps by max_steps) + Returns False if max steps reached or review indicates 'stop'/'success'. """ try: - # Stop if max steps reached if current_step >= max_steps: logger.info(f"Stopping workflow: reached max_steps limit ({current_step} >= {max_steps})") return False - # Check review decision (can be ReviewResult model or dict) if review: if hasattr(review, 'status'): - # ReviewResult Pydantic model if review.status in ('stop', 'success'): return False elif isinstance(review, dict): - # Legacy dict format decision = review.get('decision') or review.get('status') if decision in ('stop', 'success'): return False - # Check observation: if hard failure with no documents, allow one more step - # The caller will enforce max_steps limit - if observation: - if observation.success is False and observation.documentsCount == 0: - # Allow next step once; the caller caps by max_steps - return True - return True except Exception as e: logger.warning(f"Error in shouldContinue: {e}") diff --git a/modules/workflows/processing/shared/methodDiscovery.py b/modules/workflows/processing/shared/methodDiscovery.py index e3bfa769..b8403b3d 100644 --- a/modules/workflows/processing/shared/methodDiscovery.py +++ b/modules/workflows/processing/shared/methodDiscovery.py @@ -19,117 +19,57 @@ methods = {} def discoverMethods(serviceCenter): """Dynamically discover all method classes and their actions in modules methods package. - CRITICAL: If methods are already discovered, updates their Services reference to ensure - they use the current workflow (self.services.workflow). This prevents stale workflow IDs - from being used when a new workflow starts. + Always creates fresh method instances bound to the given serviceCenter, + preventing stale or cross-workflow service references. """ + global methods try: - # Import the methods package methodsPackage = importlib.import_module('modules.workflows.methods') - # Discover all modules and packages in the methods package + # Clear and rebuild to prevent cross-workflow state contamination + methods.clear() + uniqueCount = 0 + for _, name, isPkg in pkgutil.iter_modules(methodsPackage.__path__): if name.startswith('method'): try: - if isPkg: - # Package (folder) - import __init__.py which exports the Method class - module = importlib.import_module(f'modules.workflows.methods.{name}') - else: - # Module (file) - import directly - module = importlib.import_module(f'modules.workflows.methods.{name}') + module = importlib.import_module(f'modules.workflows.methods.{name}') - # Find all classes in the module that inherit from MethodBase for itemName, item in inspect.getmembers(module): if (inspect.isclass(item) and issubclass(item, MethodBase) and item != MethodBase): - # Check if method already exists in cache shortName = itemName.replace('Method', '').lower() - if itemName in methods or shortName in methods: - # Method already discovered - update Services reference to use current workflow - existingMethodInfo = methods.get(itemName) or methods.get(shortName) - if existingMethodInfo and existingMethodInfo.get('instance'): - existingMethodInfo['instance'].services = serviceCenter - logger.debug(f"Updated Services reference for cached method {itemName} to use current workflow") - else: - # Method exists but instance is missing - recreate it - methodInstance = item(serviceCenter) - actions = methodInstance.actions - methodInfo = { - 'instance': methodInstance, - 'actions': actions, - 'description': item.__doc__ or f"Method {itemName}" - } - methods[itemName] = methodInfo - methods[shortName] = methodInfo - logger.info(f"Recreated method {itemName} (short: {shortName}) with {len(actions)} actions") - else: - # Method not discovered yet - create new instance - methodInstance = item(serviceCenter) - - # Use the actions property from MethodBase which handles WorkflowActionDefinition - actions = methodInstance.actions - - # Create method info - methodInfo = { - 'instance': methodInstance, - 'actions': actions, - 'description': item.__doc__ or f"Method {itemName}" - } - - # Store the method with full class name - methods[itemName] = methodInfo - - # Also store with short name for action executor access - methods[shortName] = methodInfo - - logger.info(f"Discovered method {itemName} (short: {shortName}) with {len(actions)} actions") + + # Skip if already processed (via another module path) + if itemName in methods: + continue + + methodInstance = item(serviceCenter) + actions = methodInstance.actions + + methodInfo = { + 'instance': methodInstance, + 'actions': actions, + 'description': item.__doc__ or f"Method {itemName}" + } + + methods[itemName] = methodInfo + methods[shortName] = methodInfo + uniqueCount += 1 + + logger.info(f"Discovered method {itemName} (short: {shortName}) with {len(actions)} actions") except Exception as e: logger.error(f"Error discovering method {name}: {str(e)}") continue - logger.info(f"Discovered/updated {len(methods)} method entries total") + logger.info(f"Discovered {uniqueCount} unique methods ({len(methods)} entries with aliases)") except Exception as e: logger.error(f"Error discovering methods: {str(e)}") -def getMethodsList(serviceCenter): - """Get a list of available methods with their signatures""" - if not methods: - discoverMethods(serviceCenter) - - methodsList = [] - for methodName, methodInfo in methods.items(): - methodDescription = methodInfo['description'] - actionsList = [] - - for actionName, actionInfo in methodInfo['actions'].items(): - actionDescription = actionInfo['description'] - parameters = actionInfo['parameters'] - - # Build parameter signature - paramSig = [] - for paramName, paramInfo in parameters.items(): - paramType = paramInfo['type'] - paramRequired = paramInfo['required'] - paramDefault = paramInfo['default'] - - if paramRequired: - paramSig.append(f"{paramName}: {paramType}") - else: - defaultStr = f" = {paramDefault}" if paramDefault is not None else " = None" - paramSig.append(f"{paramName}: {paramType}{defaultStr}") - - paramSignature = f"({', '.join(paramSig)})" if paramSig else "()" - actionsList.append(f"- {actionName}{paramSignature}: {actionDescription}") - - actionsStr = "\n".join(actionsList) - methodsList.append(f"**{methodName}**: {methodDescription}\n{actionsStr}") - - return "\n\n".join(methodsList) - def getActionParameterList(methodName: str, actionName: str, methods: Dict[str, Any]) -> str: """Get action parameter list from WorkflowActionParameter structure for AI parameter generation (list only).""" try: diff --git a/modules/workflows/processing/shared/placeholderFactory.py b/modules/workflows/processing/shared/placeholderFactory.py index 136dd2cb..3d1a9d83 100644 --- a/modules/workflows/processing/shared/placeholderFactory.py +++ b/modules/workflows/processing/shared/placeholderFactory.py @@ -39,6 +39,26 @@ from typing import Dict, Any, List logger = logging.getLogger(__name__) from modules.workflows.processing.shared.methodDiscovery import (methods, discoverMethods) +from modules.datamodels.datamodelChat import Observation + + +def _observationToDict(obs) -> dict: + """Convert an Observation (Pydantic model or dict) to a plain dict.""" + if isinstance(obs, dict): + return obs.copy() + if hasattr(obs, 'model_dump'): + return obs.model_dump(exclude_none=True) + if hasattr(obs, 'dict'): + return obs.dict() + return {"raw": str(obs)} + + +def _redactSnippets(obsDict: dict): + """Replace large snippet strings with a metadata indicator.""" + if 'previews' in obsDict and isinstance(obsDict['previews'], list): + for preview in obsDict['previews']: + if isinstance(preview, dict) and 'snippet' in preview: + preview['snippet'] = f"[Content: {len(preview.get('snippet', ''))} characters]" def extractUserPrompt(context: Any) -> str: """Extract user prompt from context. Maps to {{KEY:USER_PROMPT}}. @@ -71,22 +91,17 @@ def extractUserPrompt(context: Any) -> str: def extractNormalizedRequest(services: Any) -> str: """Extract normalized user request from services. Maps to {{KEY:NORMALIZED_REQUEST}}. Returns the full normalized request from user input analysis (preserves all constraints and details). - CRITICAL: Must return the actual normalizedRequest from analysis, NOT intent. """ try: - # Get normalized request from currentUserPromptNormalized (stores the normalizedRequest from analysis) if services and getattr(services, 'currentUserPromptNormalized', None): normalized = services.currentUserPromptNormalized - # Validate that it's not the intent (which is shorter and less detailed) - # Intent is typically a concise objective, normalized request should be longer and more detailed workflowIntent = getattr(services.workflow, '_workflowIntent', {}) if hasattr(services, 'workflow') and services.workflow else {} intent = workflowIntent.get('intent', '') - # If normalized matches intent exactly, it's wrong - log warning if intent and normalized == intent: logger.warning(f"extractNormalizedRequest: normalized request matches intent - this is incorrect! normalized={normalized[:100]}...") - # Try to get from workflow intent or return error message - return f"ERROR: Normalized request not properly stored. Expected detailed request, got intent: {intent}" + # Fall back to intent rather than injecting an error string into the LLM prompt + return intent return normalized @@ -346,49 +361,12 @@ def extractReviewContent(context: Any) -> str: return result_summary elif hasattr(context, 'observation') and context.observation: - # For observation data, show full content but handle documents specially - # Handle both Pydantic Observation model and dict format - from modules.datamodels.datamodelChat import Observation - - if isinstance(context.observation, Observation): - # Convert Pydantic model to dict - obs_dict = context.observation.model_dump(exclude_none=True) if hasattr(context.observation, 'model_dump') else context.observation.dict() - elif isinstance(context.observation, dict): - obs_dict = context.observation.copy() - else: - # Fallback: try to serialize as-is - obs_dict = context.observation.model_dump(exclude_none=True) if hasattr(context.observation, 'model_dump') else context.observation.dict() - - # If there are previews with documents, show only metadata - if 'previews' in obs_dict and isinstance(obs_dict['previews'], list): - for preview in obs_dict['previews']: - if isinstance(preview, dict) and 'snippet' in preview: - # Replace snippet with metadata indicator - preview['snippet'] = f"[Content: {len(preview.get('snippet', ''))} characters]" - + obs_dict = _observationToDict(context.observation) + _redactSnippets(obs_dict) return json.dumps(obs_dict, indent=2, ensure_ascii=False) elif hasattr(context, 'stepResult') and context.stepResult and 'observation' in context.stepResult: - # For observation data in stepResult, show full content but handle documents specially - observation = context.stepResult['observation'] - # Handle both Pydantic Observation model and dict format - from modules.datamodels.datamodelChat import Observation - - if isinstance(observation, Observation): - # Convert Pydantic model to dict - obs_dict = observation.model_dump(exclude_none=True) if hasattr(observation, 'model_dump') else observation.dict() - elif isinstance(observation, dict): - obs_dict = observation.copy() - else: - # Fallback: try to serialize - obs_dict = observation.model_dump(exclude_none=True) if hasattr(observation, 'model_dump') else observation.dict() - - # If there are previews with documents, show only metadata - if 'previews' in obs_dict and isinstance(obs_dict['previews'], list): - for preview in obs_dict['previews']: - if isinstance(preview, dict) and 'snippet' in preview: - # Replace snippet with metadata indicator - preview['snippet'] = f"[Content: {len(preview.get('snippet', ''))} characters]" - + obs_dict = _observationToDict(context.stepResult['observation']) + _redactSnippets(obs_dict) return json.dumps(obs_dict, indent=2, ensure_ascii=False) else: return "No review content available" @@ -449,41 +427,22 @@ def extractLatestRefinementFeedback(context: Any) -> str: CRITICAL: If ERROR level logs are found, refinement should stop processing. """ try: - # First check for ERROR level logs in workflow - if hasattr(context, 'workflow') and context.workflow: - try: - import modules.interfaces.interfaceDbChat as interfaceDbChat - from modules.interfaces.interfaceDbApp import getRootInterface - rootInterface = getRootInterface() - interfaceDbChat = interfaceDbChat.getInterface(rootInterface.currentUser) - - # Get workflow logs - chatData = interfaceDbChat.getUnifiedChatData(context.workflow.id, None) - logs = chatData.get("logs", []) - - # Check for ERROR level logs - for log in logs: - if isinstance(log, dict): - log_level = log.get("level", "").upper() - log_message = str(log.get("message", "")) - if log_level == "ERROR" or "ERROR" in log_message.upper(): - return f"CRITICAL: Processing stopped due to ERROR in logs: {log_message[:200]}" - except Exception as log_check_error: - # If we can't check logs, continue with normal feedback extraction - logger.warning(f"Could not check for ERROR logs: {str(log_check_error)}") - if not hasattr(context, 'previousReviewResult') or not context.previousReviewResult or not isinstance(context.previousReviewResult, list): return "No previous refinement feedback available" - # Get the most recent refinement decision + # Get the most recent refinement decision (supports both ReviewResult objects and dicts) latest_decision = context.previousReviewResult[-1] - if not isinstance(latest_decision, dict): + + # Normalize to dict if it's a Pydantic model (e.g. ReviewResult) + if hasattr(latest_decision, 'model_dump'): + latest_decision = latest_decision.model_dump() + elif not isinstance(latest_decision, dict): return "No previous refinement feedback available" feedback_parts = [] - # Add decision and reason - decision = latest_decision.get('decision', 'unknown') + # Add decision and reason (ReviewResult uses 'status', legacy uses 'decision') + decision = latest_decision.get('status') or latest_decision.get('decision', 'unknown') reason = latest_decision.get('reason', 'No reason provided') feedback_parts.append(f"Latest Decision: {decision}") feedback_parts.append(f"Reason: {reason}") diff --git a/modules/workflows/processing/shared/promptGenerationActionsDynamic.py b/modules/workflows/processing/shared/promptGenerationActionsDynamic.py index 31878033..dee1cc1f 100644 --- a/modules/workflows/processing/shared/promptGenerationActionsDynamic.py +++ b/modules/workflows/processing/shared/promptGenerationActionsDynamic.py @@ -46,12 +46,19 @@ def generateDynamicPlanSelectionPrompt(services, context: Any, learningEngine=No adaptiveContext = learningEngine.getAdaptiveContextForActionSelection(workflowId, userPrompt) if adaptiveContext: - # Add learning-aware placeholders placeholders.extend([ PromptPlaceholder(label="ADAPTIVE_GUIDANCE", content=adaptiveContext.get('adaptiveGuidance', ''), summaryAllowed=True), PromptPlaceholder(label="FAILURE_ANALYSIS", content=json.dumps(adaptiveContext.get('failureAnalysis', {}), indent=2), summaryAllowed=True), PromptPlaceholder(label="ESCALATION_LEVEL", content=adaptiveContext.get('escalationLevel', 'low'), summaryAllowed=False), ]) + + # Always provide these placeholders so template tokens don't leak into the LLM prompt + if not adaptiveContext: + placeholders.extend([ + PromptPlaceholder(label="ADAPTIVE_GUIDANCE", content="", summaryAllowed=True), + PromptPlaceholder(label="FAILURE_ANALYSIS", content="", summaryAllowed=True), + PromptPlaceholder(label="ESCALATION_LEVEL", content="low", summaryAllowed=False), + ]) template = """Select exactly one next action to advance the task incrementally. @@ -60,7 +67,8 @@ CONTEXT: {{KEY:OVERALL_TASK_CONTEXT}} OBJECTIVE: {{KEY:TASK_OBJECTIVE}} === AVAILABLE RESOURCES === -AVAILABLE_DOCUMENTS_INDEX: {{KEY:AVAILABLE_DOCUMENTS_SUMMARY}} +AVAILABLE_DOCUMENTS_SUMMARY: {{KEY:AVAILABLE_DOCUMENTS_SUMMARY}} +AVAILABLE_DOCUMENTS_INDEX: {{KEY:AVAILABLE_DOCUMENTS_INDEX}} AVAILABLE_CONNECTIONS_INDEX: {{KEY:AVAILABLE_CONNECTIONS_INDEX}} @@ -227,6 +235,13 @@ Excludes documents/connections/history entirely. PromptPlaceholder(label="ATTEMPT_NUMBER", content=str(adaptiveContext.get('attemptNumber', 1)), summaryAllowed=False), PromptPlaceholder(label="FAILURE_ANALYSIS", content=json.dumps(adaptiveContext.get('failureAnalysis', {}), indent=2), summaryAllowed=True), ]) + + if not adaptiveContext: + placeholders.extend([ + PromptPlaceholder(label="PARAMETER_GUIDANCE", content="", summaryAllowed=True), + PromptPlaceholder(label="ATTEMPT_NUMBER", content="1", summaryAllowed=False), + PromptPlaceholder(label="FAILURE_ANALYSIS", content="", summaryAllowed=True), + ]) template = """You are a parameter generator. Set the parameters for this specific action. diff --git a/modules/workflows/processing/workflowProcessor.py b/modules/workflows/processing/workflowProcessor.py index 3547008a..72f45cce 100644 --- a/modules/workflows/processing/workflowProcessor.py +++ b/modules/workflows/processing/workflowProcessor.py @@ -141,8 +141,9 @@ class WorkflowProcessor: # Delegate to the appropriate mode result = await self.mode.executeTask(taskStep, workflow, context) - # Complete progress tracking - self.services.chat.progressLogFinish(operationId, True) + # Complete progress tracking based on actual result + taskSuccess = result.success if hasattr(result, 'success') else True + self.services.chat.progressLogFinish(operationId, taskSuccess) return result except Exception as e: @@ -329,7 +330,7 @@ class WorkflowProcessor: return handoverData except Exception as e: logger.error(f"Error in prepareTaskHandover: {str(e)}") - return {'error': str(e)} + raise # Fast Path Implementation @@ -379,10 +380,7 @@ class WorkflowProcessor: "################ USER INPUT START #################\n" ) - # Add sanitized user input with clear delimiters - # Escape curly braces for f-string safety, but preserve format (no quote wrapping) - sanitizedPrompt = prompt.replace('{', '{{').replace('}', '}}') if prompt else "" - complexityPrompt += f"{sanitizedPrompt}\n" + complexityPrompt += f"{prompt or ''}\n" complexityPrompt += "################ USER INPUT FINISH #################\n\n" @@ -469,17 +467,14 @@ class WorkflowProcessor: "Format your response as plain text (no markdown code blocks unless showing code examples)." ) - # Prepare AI call options for fast path (balanced, fast processing) - options = AiCallOptions( operationType=OperationTypeEnum.DATA_ANALYSE, priority=PriorityEnum.BALANCED, processingMode=ProcessingModeEnum.BASIC, - maxCost=0.10, # Low cost for simple requests - maxProcessingTime=15 # Fast path should complete in 15s + maxCost=0.10, + maxProcessingTime=15 ) - # Call AI via callAi() to ensure stats are stored aiRequest = AiCallRequest( prompt=fastPathPrompt, context="", @@ -630,17 +625,23 @@ class WorkflowProcessor: chatDocuments = [] if taskResult.actionResult and taskResult.actionResult.documents: for actionDoc in taskResult.actionResult.documents: - if hasattr(actionDoc, 'documentData') and actionDoc.documentData: - # Create file in component storage + if hasattr(actionDoc, 'documentData') and actionDoc.documentData is not None: + rawData = actionDoc.documentData + if isinstance(rawData, bytes): + contentBytes = rawData + elif isinstance(rawData, str): + contentBytes = rawData.encode('utf-8') + else: + contentBytes = json.dumps(rawData, ensure_ascii=False).encode('utf-8') + fileItem = self.services.interfaceDbComponent.createFile( name=actionDoc.documentName if hasattr(actionDoc, 'documentName') else f"task_{taskResult.taskId}_result.txt", mimeType=actionDoc.mimeType if hasattr(actionDoc, 'mimeType') else "text/plain", - content=actionDoc.documentData if isinstance(actionDoc.documentData, bytes) else actionDoc.documentData.encode('utf-8') + content=contentBytes ) - # Persist file data self.services.interfaceDbComponent.createFileData( fileItem.id, - actionDoc.documentData if isinstance(actionDoc.documentData, bytes) else actionDoc.documentData.encode('utf-8') + contentBytes ) # Get file info @@ -651,7 +652,7 @@ class WorkflowProcessor: chatDoc = { "fileId": fileItem.id, "fileName": fileInfo.get("fileName", actionDoc.documentName) if fileInfo else actionDoc.documentName, - "fileSize": fileInfo.get("size", len(actionDoc.documentData) if isinstance(actionDoc.documentData, bytes) else len(actionDoc.documentData.encode('utf-8'))) if fileInfo else (len(actionDoc.documentData) if isinstance(actionDoc.documentData, bytes) else len(actionDoc.documentData.encode('utf-8'))), + "fileSize": fileInfo.get("size", len(contentBytes)) if fileInfo else len(contentBytes), "mimeType": fileInfo.get("mimeType", actionDoc.mimeType) if fileInfo else actionDoc.mimeType, "roundNumber": workflow.currentRound, "taskNumber": workflow.getTaskIndex(), diff --git a/modules/workflows/workflowManager.py b/modules/workflows/workflowManager.py index dfc617da..c81977c1 100644 --- a/modules/workflows/workflowManager.py +++ b/modules/workflows/workflowManager.py @@ -8,7 +8,6 @@ import json from modules.datamodels.datamodelChat import ( UserInputRequest, - ChatMessage, ChatWorkflow, ChatDocument, WorkflowModeEnum @@ -44,11 +43,6 @@ class WorkflowManager: # Store workflow in services for reference (this is the ChatWorkflow object) self.services.workflow = workflow - # CRITICAL: Update all method instances to use the current Services object with the correct workflow - from modules.workflows.processing.shared.methodDiscovery import discoverMethods - discoverMethods(self.services) - logger.debug(f"Updated method instances to use workflow {self.services.workflow.id}") - if workflow.status == "running": logger.info(f"Stopping running workflow {workflowId} before processing new prompt") workflow.status = "stopped" @@ -57,12 +51,13 @@ class WorkflowManager: "status": "stopped", "lastActivity": currentTime }) - self.services.chat.storeLog(workflow, { - "message": "Workflow stopped for new prompt", - "type": "info", - "status": "stopped", - "progress": 1.0 - }) + if workflow.status == "stopped": + self.services.chat.storeLog(workflow, { + "message": "Workflow stopped for new prompt", + "type": "info", + "status": "stopped", + "progress": 1.0 + }) newRound = workflow.currentRound + 1 self.services.chat.updateWorkflow(workflowId, { @@ -170,7 +165,10 @@ class WorkflowManager: self.services.currentUserPrompt = userInput.prompt # Reset progress logger for new workflow - self.services.chat._progressLogger = None + if hasattr(self.services.chat, 'resetProgressLogger'): + self.services.chat.resetProgressLogger() + else: + self.services.chat._progressLogger = None # Reset workflow history flag at start of each workflow setattr(self.services, '_needsWorkflowHistory', False) @@ -565,9 +563,10 @@ The following is the user's original input message. Analyze intent, normalize th logger.info(f"Fast path completed successfully, response length: {len(responseText)} chars") + except WorkflowStoppedException: + raise except Exception as e: logger.error(f"Error in _executeFastPath: {str(e)}") - # Fall back to full workflow on error logger.info("Falling back to full workflow due to fast path error") taskPlan = await self._planTasks(userInput) await self._executeTasks(taskPlan) @@ -897,8 +896,8 @@ The following is the user's original input message. Analyze intent, normalize th failedActions=[], successfulActions=[], criteriaProgress={ - 'met_criteria': set(), - 'unmet_criteria': set(), + 'met_criteria': [], + 'unmet_criteria': [], 'attempt_history': [] } ) @@ -1021,11 +1020,11 @@ The following is the user's original input message. Analyze intent, normalize th }) return elif workflow.status == 'failed': - # Create error message + lastError = getattr(workflow, '_lastError', None) or "Processing failed" errorMessage = { "workflowId": workflow.id, "role": "assistant", - "message": f"Workflow failed: {'Unknown error'}", + "message": f"Workflow failed: {lastError}", "status": "last", "sequenceNr": len(workflow.messages) + 1, "publishedAt": self.services.utils.timestampGetUtc(), @@ -1051,9 +1050,8 @@ The following is the user's original input message. Analyze intent, normalize th "totalActions": workflow.totalActions }) - # Add failed log entry self.services.chat.storeLog(workflow, { - "message": "Workflow failed: Unknown error", + "message": f"Workflow failed: {lastError}", "type": "error", "status": "failed", "progress": 1.0 @@ -1155,7 +1153,6 @@ The following is the user's original input message. Analyze intent, normalize th """Generate feedback message for workflow completion""" try: workflow = self.services.workflow - checkWorkflowStopped(self.services) # Count messages by role userMessages = [msg for msg in workflow.messages if msg.role == 'user'] @@ -1227,7 +1224,6 @@ The following is the user's original input message. Analyze intent, normalize th workflow = self.services.workflow logger.error(f"Workflow processing error: {str(error)}") - # Update workflow status to failed workflow.status = "failed" workflow.lastActivity = self.services.utils.timestampGetUtc() self.services.chat.updateWorkflow(workflow.id, { @@ -1237,11 +1233,10 @@ The following is the user's original input message. Analyze intent, normalize th "totalActions": workflow.totalActions }) - # Create error message error_message = { "workflowId": workflow.id, "role": "assistant", - "message": f"Workflow processing failed: {str(error)}", + "message": "Workflow processing encountered an error. Please try again.", "status": "last", "sequenceNr": len(workflow.messages) + 1, "publishedAt": self.services.utils.timestampGetUtc(), @@ -1257,15 +1252,12 @@ The following is the user's original input message. Analyze intent, normalize th } self.services.chat.storeMessageWithDocuments(workflow, error_message, []) - # Add error log entry self.services.chat.storeLog(workflow, { "message": f"Workflow failed: {str(error)}", "type": "error", "status": "failed", "progress": 1.0 }) - - raise async def _processFileIds(self, fileIds: List[str], messageId: str = None) -> List[ChatDocument]: """Process file IDs from existing files and return ChatDocument objects. @@ -1365,21 +1357,3 @@ The following is the user's original input message. Analyze intent, normalize th # Return original content on error return contentBytes - def _checkIfHistoryAvailable(self) -> bool: - """Check if workflow history is available (previous rounds exist). - - Returns True if there are previous workflow rounds with messages. - """ - try: - from modules.workflows.processing.shared.placeholderFactory import getPreviousRoundContext - - history = getPreviousRoundContext(self.services) - - # Check if history contains actual content (not just "No previous round context available") - if history and history != "No previous round context available": - return True - - return False - except Exception as e: - logger.error(f"Error checking if history is available: {str(e)}") - return False From 5486a87b9ac355f14376f411ebdf6ff1e332061e Mon Sep 17 00:00:00 2001 From: patrick-motsch Date: Tue, 3 Mar 2026 22:04:52 +0100 Subject: [PATCH 2/7] commcoach iteration 1 completed --- .../commcoach/interfaceFeatureCommcoach.py | 27 ++++++++ modules/features/commcoach/mainCommcoach.py | 11 ++++ .../commcoach/routeFeatureCommcoach.py | 21 +++++++ .../features/commcoach/serviceCommcoach.py | 62 ++++++++++++++----- .../features/commcoach/serviceCommcoachAi.py | 22 +++++++ 5 files changed, 128 insertions(+), 15 deletions(-) diff --git a/modules/features/commcoach/interfaceFeatureCommcoach.py b/modules/features/commcoach/interfaceFeatureCommcoach.py index 830aa261..eae7e168 100644 --- a/modules/features/commcoach/interfaceFeatureCommcoach.py +++ b/modules/features/commcoach/interfaceFeatureCommcoach.py @@ -5,6 +5,7 @@ Interface to CommCoach database. Uses the PostgreSQL connector for data access with strict user ownership. """ +import json import logging from typing import Dict, Any, List, Optional @@ -292,14 +293,23 @@ class CommcoachObjects: contextSummaries = [] for ctx in activeContexts: + goalProgress = _calcGoalProgress(ctx.get("goals")) contextSummaries.append({ "id": ctx.get("id"), "title": ctx.get("title"), "category": ctx.get("category"), "sessionCount": ctx.get("sessionCount", 0), "lastSessionAt": ctx.get("lastSessionAt"), + "goalProgress": goalProgress, }) + allGoalProgress = [] + for ctx in activeContexts: + gp = _calcGoalProgress(ctx.get("goals")) + if gp is not None: + allGoalProgress.append(gp) + overallGoalProgress = round(sum(allGoalProgress) / len(allGoalProgress)) if allGoalProgress else None + return { "totalContexts": len(contexts), "activeContexts": len(activeContexts), @@ -312,4 +322,21 @@ class CommcoachObjects: "openTasks": self.getOpenTaskCount(userId, instanceId), "completedTasks": self.getCompletedTaskCount(userId, instanceId), "contexts": contextSummaries, + "goalProgress": overallGoalProgress, } + + +def _calcGoalProgress(goalsRaw) -> Optional[int]: + """Calculate goal completion percentage from a context's goals JSON field.""" + if not goalsRaw: + return None + goals = goalsRaw + if isinstance(goalsRaw, str): + try: + goals = json.loads(goalsRaw) + except (json.JSONDecodeError, TypeError): + return None + if not isinstance(goals, list) or len(goals) == 0: + return None + done = sum(1 for g in goals if isinstance(g, dict) and g.get("status") in ("done", "completed")) + return round(done / len(goals) * 100) diff --git a/modules/features/commcoach/mainCommcoach.py b/modules/features/commcoach/mainCommcoach.py index c5a0a7c1..ff213f91 100644 --- a/modules/features/commcoach/mainCommcoach.py +++ b/modules/features/commcoach/mainCommcoach.py @@ -184,6 +184,7 @@ def registerFeature(catalogService) -> bool: ) _syncTemplateRolesToDb() + _registerScheduler() logger.info(f"Feature '{FEATURE_CODE}' registered {len(UI_OBJECTS)} UI, {len(RESOURCE_OBJECTS)} resource, {len(DATA_OBJECTS)} data objects") return True @@ -193,6 +194,16 @@ def registerFeature(catalogService) -> bool: return False +def _registerScheduler(): + """Register CommCoach scheduled jobs (daily reminders).""" + try: + from modules.shared.eventManagement import eventManager + from .serviceCommcoachScheduler import registerScheduledJobs + registerScheduledJobs(eventManager) + except Exception as e: + logger.warning(f"CommCoach scheduler registration failed (non-fatal): {e}") + + def _syncTemplateRolesToDb() -> int: try: from modules.interfaces.interfaceDbApp import getRootInterface diff --git a/modules/features/commcoach/routeFeatureCommcoach.py b/modules/features/commcoach/routeFeatureCommcoach.py index 66a4b347..43c00291 100644 --- a/modules/features/commcoach/routeFeatureCommcoach.py +++ b/modules/features/commcoach/routeFeatureCommcoach.py @@ -31,6 +31,23 @@ from .serviceCommcoach import CommcoachService, emitSessionEvent, getSessionEven logger = logging.getLogger(__name__) + +def _audit(context: RequestContext, action: str, resourceType: str = None, resourceId: str = None, details: str = ""): + """Log an audit event for CommCoach. Non-blocking, best-effort.""" + try: + from modules.shared.auditLogger import audit_logger + audit_logger.logEvent( + userId=str(context.user.id), + mandateId=str(context.mandateId) if context.mandateId else None, + category="commcoach", + action=action, + resourceType=resourceType, + resourceId=resourceId, + details=details, + ) + except Exception: + pass + router = APIRouter( prefix="/api/commcoach", tags=["CommCoach"], @@ -116,6 +133,7 @@ async def createContext( created = interface.createContext(contextData) logger.info(f"CommCoach context created: {created.get('id')} for user {userId}") + _audit(context, "commcoach.context.created", "CoachingContext", created.get("id"), f"Title: {body.title}") return {"context": created} @@ -208,6 +226,7 @@ async def archiveContext( _validateOwnership(ctx, context) updated = interface.updateContext(contextId, {"status": CoachingContextStatus.ARCHIVED.value}) + _audit(context, "commcoach.context.archived", "CoachingContext", contextId) return {"context": updated} @@ -369,6 +388,7 @@ async def startSession( pass logger.info(f"CommCoach session started (streaming): {sessionId} for context {contextId}") + _audit(context, "commcoach.session.started", "CoachingSession", sessionId, f"Context: {contextId}") return StreamingResponse( _newSessionEventGenerator(), media_type="text/event-stream", @@ -419,6 +439,7 @@ async def completeSession( service = CommcoachService(context.user, mandateId, instanceId) result = await service.completeSession(sessionId, interface) + _audit(context, "commcoach.session.completed", "CoachingSession", sessionId) return {"session": result} diff --git a/modules/features/commcoach/serviceCommcoach.py b/modules/features/commcoach/serviceCommcoach.py index 0778a978..1b886958 100644 --- a/modules/features/commcoach/serviceCommcoach.py +++ b/modules/features/commcoach/serviceCommcoach.py @@ -83,6 +83,33 @@ def cleanupSessionEvents(sessionId: str): _sessionEvents.pop(sessionId, None) +CHUNK_WORD_SIZE = 4 +CHUNK_DELAY_SECONDS = 0.05 + + +async def _emitChunkedResponse(sessionId: str, createdMsg: Dict[str, Any], fullText: str): + """Emit response as messageChunk events for progressive display, then the full message.""" + msgId = createdMsg.get("id") + words = fullText.split() + emitted = "" + for i in range(0, len(words), CHUNK_WORD_SIZE): + chunk = " ".join(words[i:i + CHUNK_WORD_SIZE]) + emitted = (emitted + " " + chunk).strip() if emitted else chunk + await emitSessionEvent(sessionId, "messageChunk", { + "id": msgId, + "role": "assistant", + "chunk": chunk, + "accumulated": emitted, + }) + await asyncio.sleep(CHUNK_DELAY_SECONDS) + await emitSessionEvent(sessionId, "message", { + "id": msgId, + "role": "assistant", + "content": fullText, + "createdAt": createdMsg.get("createdAt"), + }) + + class CommcoachService: """Coaching orchestrator: processes messages, calls AI, extracts tasks and scores.""" @@ -204,12 +231,7 @@ class CommcoachService: messages = interface.getMessages(sessionId) interface.updateSession(sessionId, {"messageCount": len(messages)}) - await emitSessionEvent(sessionId, "message", { - "id": createdAssistantMsg.get("id"), - "role": "assistant", - "content": responseText, - "createdAt": createdAssistantMsg.get("createdAt"), - }) + await _emitChunkedResponse(sessionId, createdAssistantMsg, responseText) if responseText: try: @@ -289,15 +311,7 @@ class CommcoachService: createdMsg = interface.createMessage(assistantMsg) interface.updateSession(sessionId, {"messageCount": 1}) - await emitSessionEvent(sessionId, "message", { - "id": createdMsg.get("id"), - "sessionId": sessionId, - "contextId": contextId, - "role": "assistant", - "content": openingContent, - "contentType": "text", - "createdAt": createdMsg.get("createdAt"), - }) + await _emitChunkedResponse(sessionId, createdMsg, openingContent) if openingContent: try: from modules.interfaces.interfaceVoiceObjects import getVoiceInterface @@ -497,6 +511,24 @@ class CommcoachService: logger.warning(f"Scoring failed: {e}") competenceScore = None + # Generate insights + try: + insightPrompt = aiPrompts.buildInsightPrompt(messages, summary) + insightResponse = await self._callAi("Du generierst kurze Coaching-Insights.", insightPrompt) + if insightResponse and insightResponse.errorCount == 0 and insightResponse.content: + insights = aiPrompts.parseJsonResponse(insightResponse.content, []) + if isinstance(insights, list): + existingInsights = aiPrompts._parseJsonField(context.get("insights") if context else None, []) + for ins in insights[:3]: + insightText = ins.get("text", ins) if isinstance(ins, dict) else str(ins) + if insightText: + existingInsights.append({"text": insightText, "sessionId": sessionId, "createdAt": getIsoTimestamp()}) + await emitSessionEvent(sessionId, "insightGenerated", {"text": insightText, "sessionId": sessionId}) + if contextId and existingInsights: + interface.updateContext(contextId, {"insights": json.dumps(existingInsights[-10:])}) + except Exception as e: + logger.warning(f"Insight generation failed: {e}") + # Calculate duration startedAt = session.get("startedAt", "") durationSeconds = 0 diff --git a/modules/features/commcoach/serviceCommcoachAi.py b/modules/features/commcoach/serviceCommcoachAi.py index ea58488b..5d050203 100644 --- a/modules/features/commcoach/serviceCommcoachAi.py +++ b/modules/features/commcoach/serviceCommcoachAi.py @@ -312,6 +312,28 @@ Sessions: Antworte NUR mit der Zusammenfassung.""" +def buildInsightPrompt(messages: List[Dict[str, Any]], summary: Optional[str] = None) -> str: + """Build a prompt to generate coaching insights from a completed session.""" + conversation = "" + for msg in messages[-15:]: + role = "Benutzer" if msg.get("role") == "user" else "Coach" + conversation += f"\n{role}: {msg.get('content', '')[:300]}" + + summarySection = f"\nZusammenfassung: {summary[:500]}" if summary else "" + + return f"""Generiere 1-3 kurze Coaching-Insights aus dieser Session. +Ein Insight ist eine praegende Erkenntnis oder ein Aha-Moment des Benutzers. + +Antworte AUSSCHLIESSLICH als JSON-Array: +[{{"text": "Erkenntnis in einem Satz"}}] + +Nur echte Erkenntnisse, keine Banalitaeten. Wenn keine klaren Insights: leeres Array []. +{summarySection} + +Gespraech: +{conversation}""" + + def buildTaskExtractionPrompt(messages: List[Dict[str, Any]]) -> str: """Build a prompt to extract actionable tasks from a session.""" recentForTasks = messages[-25:] if len(messages) > 25 else messages From f4940cf9e1712f377212abd875c4bb97e449d519 Mon Sep 17 00:00:00 2001 From: patrick-motsch Date: Tue, 3 Mar 2026 23:02:53 +0100 Subject: [PATCH 3/7] iteration 2 done --- .../features/commcoach/datamodelCommcoach.py | 76 ++++ .../commcoach/interfaceFeatureCommcoach.py | 102 ++++++ modules/features/commcoach/mainCommcoach.py | 29 ++ .../commcoach/routeFeatureCommcoach.py | 334 +++++++++++++++++- .../features/commcoach/serviceCommcoach.py | 62 +++- .../features/commcoach/serviceCommcoachAi.py | 36 +- .../commcoach/serviceCommcoachExport.py | 288 +++++++++++++++ .../commcoach/serviceCommcoachGamification.py | 149 ++++++++ .../commcoach/serviceCommcoachPersonas.py | 139 ++++++++ 9 files changed, 1211 insertions(+), 4 deletions(-) create mode 100644 modules/features/commcoach/serviceCommcoachExport.py create mode 100644 modules/features/commcoach/serviceCommcoachGamification.py create mode 100644 modules/features/commcoach/serviceCommcoachPersonas.py diff --git a/modules/features/commcoach/datamodelCommcoach.py b/modules/features/commcoach/datamodelCommcoach.py index 0ba636ff..090640c6 100644 --- a/modules/features/commcoach/datamodelCommcoach.py +++ b/modules/features/commcoach/datamodelCommcoach.py @@ -103,6 +103,7 @@ class CoachingSession(BaseModel): mandateId: str = Field(description="Mandate ID") instanceId: str = Field(description="Feature instance ID") status: CoachingSessionStatus = Field(default=CoachingSessionStatus.ACTIVE) + personaId: Optional[str] = Field(default=None, description="FK to CoachingPersona (Iteration 2)") summary: Optional[str] = Field(default=None, description="AI-generated session summary") coachNotes: Optional[str] = Field(default=None, description="JSON: AI internal notes for continuity") compressedHistorySummary: Optional[str] = Field(default=None, description="AI summary of older messages for long sessions") @@ -183,6 +184,62 @@ class CoachingUserProfile(BaseModel): updatedAt: Optional[str] = Field(default=None) +# ============================================================================ +# Iteration 2: Personas +# ============================================================================ + +class CoachingPersona(BaseModel): + """A roleplay persona for coaching sessions.""" + id: str = Field(default_factory=lambda: str(uuid.uuid4())) + userId: str = Field(description="Owner user ID ('system' for builtins)") + mandateId: Optional[str] = Field(default=None) + instanceId: Optional[str] = Field(default=None) + key: str = Field(description="Unique key, e.g. 'critical_cfo_f'") + label: str = Field(description="Display label, e.g. 'Kritische CFO'") + description: str = Field(description="Detailed role description for the AI") + systemPromptOverride: Optional[str] = Field(default=None, description="Full system prompt override for this persona") + gender: Optional[str] = Field(default=None, description="m or f") + category: str = Field(default="builtin", description="'builtin' or 'custom'") + isActive: bool = Field(default=True) + createdAt: Optional[str] = Field(default=None) + updatedAt: Optional[str] = Field(default=None) + + +# ============================================================================ +# Iteration 2: Documents +# ============================================================================ + +class CoachingDocument(BaseModel): + """A document attached to a coaching context.""" + id: str = Field(default_factory=lambda: str(uuid.uuid4())) + contextId: str = Field(description="FK to CoachingContext") + userId: str = Field(description="Owner user ID") + mandateId: str = Field(description="Mandate ID") + instanceId: Optional[str] = Field(default=None) + fileName: str = Field(description="Original file name") + mimeType: str = Field(default="application/octet-stream") + fileSize: int = Field(default=0) + extractedText: Optional[str] = Field(default=None, description="Text content extracted from file") + summary: Optional[str] = Field(default=None, description="AI-generated summary") + fileRef: Optional[str] = Field(default=None, description="Reference to file in storage") + createdAt: Optional[str] = Field(default=None) + + +# ============================================================================ +# Iteration 2: Badges / Gamification +# ============================================================================ + +class CoachingBadge(BaseModel): + """An achievement badge awarded to a user.""" + id: str = Field(default_factory=lambda: str(uuid.uuid4())) + userId: str = Field(description="Owner user ID") + mandateId: str = Field(description="Mandate ID") + instanceId: str = Field(description="Feature instance ID") + badgeKey: str = Field(description="Badge identifier, e.g. 'streak_7'") + awardedAt: Optional[str] = Field(default=None) + createdAt: Optional[str] = Field(default=None) + + # ============================================================================ # API Request/Response Models # ============================================================================ @@ -232,6 +289,25 @@ class UpdateProfileRequest(BaseModel): emailSummaryEnabled: Optional[bool] = None +class StartSessionRequest(BaseModel): + personaId: Optional[str] = None + + +class CreatePersonaRequest(BaseModel): + label: str + description: str + gender: Optional[str] = None + systemPromptOverride: Optional[str] = None + + +class UpdatePersonaRequest(BaseModel): + label: Optional[str] = None + description: Optional[str] = None + gender: Optional[str] = None + systemPromptOverride: Optional[str] = None + isActive: Optional[bool] = None + + class DashboardData(BaseModel): """Aggregated dashboard data for the user.""" totalContexts: int = 0 diff --git a/modules/features/commcoach/interfaceFeatureCommcoach.py b/modules/features/commcoach/interfaceFeatureCommcoach.py index eae7e168..9e21f677 100644 --- a/modules/features/commcoach/interfaceFeatureCommcoach.py +++ b/modules/features/commcoach/interfaceFeatureCommcoach.py @@ -238,6 +238,98 @@ class CommcoachObjects: count += 1 return count + # ========================================================================= + # Personas + # ========================================================================= + + def getPersonas(self, userId: str, instanceId: str) -> List[Dict[str, Any]]: + from .datamodelCommcoach import CoachingPersona + builtins = self.db.getRecordset(CoachingPersona, recordFilter={"userId": "system"}) + custom = self.db.getRecordset(CoachingPersona, recordFilter={"userId": userId, "instanceId": instanceId}) + all = builtins + custom + return [p for p in all if p.get("isActive", True)] + + def getPersona(self, personaId: str) -> Optional[Dict[str, Any]]: + from .datamodelCommcoach import CoachingPersona + records = self.db.getRecordset(CoachingPersona, recordFilter={"id": personaId}) + return records[0] if records else None + + def createPersona(self, data: Dict[str, Any]) -> Dict[str, Any]: + from .datamodelCommcoach import CoachingPersona + data["createdAt"] = getIsoTimestamp() + data["updatedAt"] = getIsoTimestamp() + return self.db.recordCreate(CoachingPersona, data) + + def updatePersona(self, personaId: str, updates: Dict[str, Any]) -> Optional[Dict[str, Any]]: + from .datamodelCommcoach import CoachingPersona + updates["updatedAt"] = getIsoTimestamp() + return self.db.recordModify(CoachingPersona, personaId, updates) + + def deletePersona(self, personaId: str) -> bool: + from .datamodelCommcoach import CoachingPersona + return self.db.recordDelete(CoachingPersona, personaId) + + # ========================================================================= + # Documents + # ========================================================================= + + def getDocuments(self, contextId: str, userId: str) -> List[Dict[str, Any]]: + from .datamodelCommcoach import CoachingDocument + records = self.db.getRecordset(CoachingDocument, recordFilter={"contextId": contextId, "userId": userId}) + records.sort(key=lambda r: r.get("createdAt") or "", reverse=True) + return records + + def getDocument(self, documentId: str) -> Optional[Dict[str, Any]]: + from .datamodelCommcoach import CoachingDocument + records = self.db.getRecordset(CoachingDocument, recordFilter={"id": documentId}) + return records[0] if records else None + + def createDocument(self, data: Dict[str, Any]) -> Dict[str, Any]: + from .datamodelCommcoach import CoachingDocument + data["createdAt"] = getIsoTimestamp() + return self.db.recordCreate(CoachingDocument, data) + + def deleteDocument(self, documentId: str) -> bool: + from .datamodelCommcoach import CoachingDocument + return self.db.recordDelete(CoachingDocument, documentId) + + # ========================================================================= + # Badges + # ========================================================================= + + def getBadges(self, userId: str, instanceId: str) -> List[Dict[str, Any]]: + from .datamodelCommcoach import CoachingBadge + records = self.db.getRecordset(CoachingBadge, recordFilter={"userId": userId, "instanceId": instanceId}) + records.sort(key=lambda r: r.get("awardedAt") or "", reverse=True) + return records + + def hasBadge(self, userId: str, instanceId: str, badgeKey: str) -> bool: + from .datamodelCommcoach import CoachingBadge + records = self.db.getRecordset(CoachingBadge, recordFilter={"userId": userId, "instanceId": instanceId, "badgeKey": badgeKey}) + return len(records) > 0 + + def awardBadge(self, data: Dict[str, Any]) -> Dict[str, Any]: + from .datamodelCommcoach import CoachingBadge + data["awardedAt"] = getIsoTimestamp() + data["createdAt"] = getIsoTimestamp() + return self.db.recordCreate(CoachingBadge, data) + + # ========================================================================= + # Score History + # ========================================================================= + + def getScoreHistory(self, contextId: str, userId: str) -> Dict[str, List[Dict[str, Any]]]: + scores = self.getScores(contextId, userId) + history: Dict[str, List[Dict[str, Any]]] = {} + for s in scores: + dim = s.get("dimension", "unknown") + if dim not in history: + history[dim] = [] + history[dim].append({"score": s.get("score"), "trend": s.get("trend"), "evidence": s.get("evidence"), "createdAt": s.get("createdAt"), "sessionId": s.get("sessionId")}) + for dim in history: + history[dim].sort(key=lambda x: x.get("createdAt") or "") + return history + # ========================================================================= # User Profile # ========================================================================= @@ -323,6 +415,8 @@ class CommcoachObjects: "completedTasks": self.getCompletedTaskCount(userId, instanceId), "contexts": contextSummaries, "goalProgress": overallGoalProgress, + "badges": self.getBadges(userId, instanceId), + "level": _calcLevel(profile.get("totalSessions", 0) if profile else 0), } @@ -340,3 +434,11 @@ def _calcGoalProgress(goalsRaw) -> Optional[int]: return None done = sum(1 for g in goals if isinstance(g, dict) and g.get("status") in ("done", "completed")) return round(done / len(goals) * 100) + + +def _calcLevel(totalSessions: int) -> Dict[str, Any]: + levels = [(50, 5, "Meister"), (25, 4, "Experte"), (10, 3, "Fortgeschritten"), (3, 2, "Engagiert")] + for threshold, number, label in levels: + if totalSessions >= threshold: + return {"number": number, "label": label, "totalSessions": totalSessions} + return {"number": 1, "label": "Einsteiger", "totalSessions": totalSessions} diff --git a/modules/features/commcoach/mainCommcoach.py b/modules/features/commcoach/mainCommcoach.py index ff213f91..2147a867 100644 --- a/modules/features/commcoach/mainCommcoach.py +++ b/modules/features/commcoach/mainCommcoach.py @@ -68,6 +68,21 @@ DATA_OBJECTS = [ "label": {"en": "User Profile", "de": "Benutzerprofil", "fr": "Profil utilisateur"}, "meta": {"table": "CoachingUserProfile", "fields": ["id", "userId", "preferredLanguage"]} }, + { + "objectKey": "data.feature.commcoach.CoachingPersona", + "label": {"en": "Coaching Persona", "de": "Coaching-Persona", "fr": "Persona coaching"}, + "meta": {"table": "CoachingPersona", "fields": ["id", "key", "label", "gender"]} + }, + { + "objectKey": "data.feature.commcoach.CoachingDocument", + "label": {"en": "Coaching Document", "de": "Coaching-Dokument", "fr": "Document coaching"}, + "meta": {"table": "CoachingDocument", "fields": ["id", "contextId", "fileName"]} + }, + { + "objectKey": "data.feature.commcoach.CoachingBadge", + "label": {"en": "Coaching Badge", "de": "Coaching-Auszeichnung", "fr": "Badge coaching"}, + "meta": {"table": "CoachingBadge", "fields": ["id", "badgeKey", "awardedAt"]} + }, { "objectKey": "data.feature.commcoach.*", "label": {"en": "All CommCoach Data", "de": "Alle CommCoach-Daten", "fr": "Toutes les donnees CommCoach"}, @@ -184,6 +199,7 @@ def registerFeature(catalogService) -> bool: ) _syncTemplateRolesToDb() + _seedBuiltinPersonas() _registerScheduler() logger.info(f"Feature '{FEATURE_CODE}' registered {len(UI_OBJECTS)} UI, {len(RESOURCE_OBJECTS)} resource, {len(DATA_OBJECTS)} data objects") @@ -194,6 +210,19 @@ def registerFeature(catalogService) -> bool: return False +def _seedBuiltinPersonas(): + """Seed builtin roleplay personas into the database.""" + try: + from .serviceCommcoachPersonas import seedBuiltinPersonas + from .interfaceFeatureCommcoach import CommcoachInterface + from modules.interfaces.interfaceDbManagement import getInterface as getDbInterface + db = getDbInterface() + interface = CommcoachInterface(db) + seedBuiltinPersonas(interface) + except Exception as e: + logger.warning(f"CommCoach persona seeding failed (non-fatal): {e}") + + def _registerScheduler(): """Register CommCoach scheduled jobs (daily reminders).""" try: diff --git a/modules/features/commcoach/routeFeatureCommcoach.py b/modules/features/commcoach/routeFeatureCommcoach.py index 43c00291..685a0f4e 100644 --- a/modules/features/commcoach/routeFeatureCommcoach.py +++ b/modules/features/commcoach/routeFeatureCommcoach.py @@ -9,9 +9,10 @@ import logging import json import asyncio import base64 +import uuid from typing import Optional from fastapi import APIRouter, HTTPException, Depends, Request -from fastapi.responses import StreamingResponse +from fastapi.responses import StreamingResponse, Response from modules.auth import limiter, getRequestContext, RequestContext from modules.shared.timeUtils import getIsoTimestamp @@ -23,9 +24,11 @@ from .datamodelCommcoach import ( CoachingContext, CoachingContextStatus, CoachingSession, CoachingSessionStatus, CoachingMessage, CoachingMessageRole, CoachingMessageContentType, CoachingTask, CoachingTaskStatus, + CoachingPersona, CoachingDocument, CoachingBadge, CreateContextRequest, UpdateContextRequest, SendMessageRequest, CreateTaskRequest, UpdateTaskRequest, UpdateTaskStatusRequest, UpdateProfileRequest, + StartSessionRequest, CreatePersonaRequest, UpdatePersonaRequest, ) from .serviceCommcoach import CommcoachService, emitSessionEvent, getSessionEventQueue, cleanupSessionEvents @@ -281,6 +284,7 @@ async def startSession( request: Request, instanceId: str, contextId: str, + personaId: Optional[str] = None, context: RequestContext = Depends(getRequestContext), ): """Start a new coaching session or resume active one. Returns SSE stream with sessionState, messages, and complete.""" @@ -358,6 +362,7 @@ async def startSession( userId=userId, mandateId=mandateId, instanceId=instanceId, + personaId=personaId, ).model_dump() created = interface.createSession(sessionData) sessionId = created.get("id") @@ -887,3 +892,330 @@ async def testVoice( except Exception as e: logger.error(f"Voice test failed: {e}") raise HTTPException(status_code=500, detail=f"TTS test failed: {str(e)}") + + +# ========================================================================= +# Export Endpoints (Iteration 2) +# ========================================================================= + +@router.get("/{instanceId}/contexts/{contextId}/export") +@limiter.limit("10/minute") +async def exportDossier( + request: Request, + instanceId: str, + contextId: str, + format: str = "md", + context: RequestContext = Depends(getRequestContext), +): + """Export a dossier as Markdown or PDF.""" + _validateInstanceAccess(instanceId, context) + interface = _getInterface(context, instanceId) + userId = str(context.user.id) + + ctx = interface.getContext(contextId) + if not ctx: + raise HTTPException(status_code=404, detail="Context not found") + _validateOwnership(ctx, context) + + tasks = interface.getTasks(contextId, userId) + scores = interface.getScores(contextId, userId) + sessions = interface.getSessions(contextId, userId) + + from .serviceCommcoachExport import buildDossierMarkdown, renderDossierPdf + _audit(context, "commcoach.export.requested", "CoachingContext", contextId, f"format={format}") + + if format == "pdf": + pdfBytes = await renderDossierPdf(ctx, sessions, tasks, scores) + if pdfBytes: + return Response(content=pdfBytes, media_type="application/pdf", + headers={"Content-Disposition": f'attachment; filename="dossier_{contextId[:8]}.pdf"'}) + format = "md" + + md = buildDossierMarkdown(ctx, sessions, tasks, scores) + return Response(content=md, media_type="text/markdown", + headers={"Content-Disposition": f'attachment; filename="dossier_{contextId[:8]}.md"'}) + + +@router.get("/{instanceId}/sessions/{sessionId}/export") +@limiter.limit("10/minute") +async def exportSession( + request: Request, + instanceId: str, + sessionId: str, + format: str = "md", + context: RequestContext = Depends(getRequestContext), +): + """Export a session as Markdown or PDF.""" + _validateInstanceAccess(instanceId, context) + interface = _getInterface(context, instanceId) + + session = interface.getSession(sessionId) + if not session: + raise HTTPException(status_code=404, detail="Session not found") + _validateOwnership(session, context) + + contextId = session.get("contextId") + userId = str(context.user.id) + messages = interface.getMessages(sessionId) + tasks = interface.getTasks(contextId, userId) if contextId else [] + scores = interface.getScores(contextId, userId) if contextId else [] + + from .serviceCommcoachExport import buildSessionMarkdown, renderSessionPdf + _audit(context, "commcoach.export.requested", "CoachingSession", sessionId, f"format={format}") + + if format == "pdf": + pdfBytes = await renderSessionPdf(session, messages, tasks, scores) + if pdfBytes: + return Response(content=pdfBytes, media_type="application/pdf", + headers={"Content-Disposition": f'attachment; filename="session_{sessionId[:8]}.pdf"'}) + format = "md" + + md = buildSessionMarkdown(session, messages, tasks, scores) + return Response(content=md, media_type="text/markdown", + headers={"Content-Disposition": f'attachment; filename="session_{sessionId[:8]}.md"'}) + + +# ========================================================================= +# Persona Endpoints (Iteration 2) +# ========================================================================= + +@router.get("/{instanceId}/personas") +@limiter.limit("60/minute") +async def listPersonas( + request: Request, + instanceId: str, + context: RequestContext = Depends(getRequestContext), +): + _validateInstanceAccess(instanceId, context) + interface = _getInterface(context, instanceId) + userId = str(context.user.id) + personas = interface.getPersonas(userId, instanceId) + return {"personas": personas} + + +@router.post("/{instanceId}/personas") +@limiter.limit("10/minute") +async def createPersona( + request: Request, + instanceId: str, + body: CreatePersonaRequest, + context: RequestContext = Depends(getRequestContext), +): + mandateId = _validateInstanceAccess(instanceId, context) + interface = _getInterface(context, instanceId) + userId = str(context.user.id) + + data = CoachingPersona( + userId=userId, + mandateId=mandateId, + instanceId=instanceId, + key=f"custom_{str(uuid.uuid4())[:8]}", + label=body.label, + description=body.description, + gender=body.gender, + systemPromptOverride=body.systemPromptOverride, + category="custom", + ).model_dump() + created = interface.createPersona(data) + return {"persona": created} + + +@router.put("/{instanceId}/personas/{personaId}") +@limiter.limit("10/minute") +async def updatePersonaRoute( + request: Request, + instanceId: str, + personaId: str, + body: UpdatePersonaRequest, + context: RequestContext = Depends(getRequestContext), +): + _validateInstanceAccess(instanceId, context) + interface = _getInterface(context, instanceId) + + persona = interface.getPersona(personaId) + if not persona: + raise HTTPException(status_code=404, detail="Persona not found") + if persona.get("category") == "builtin": + raise HTTPException(status_code=403, detail="Builtin personas cannot be edited") + _validateOwnership(persona, context) + + updates = body.model_dump(exclude_none=True) + updated = interface.updatePersona(personaId, updates) + return {"persona": updated} + + +@router.delete("/{instanceId}/personas/{personaId}") +@limiter.limit("10/minute") +async def deletePersonaRoute( + request: Request, + instanceId: str, + personaId: str, + context: RequestContext = Depends(getRequestContext), +): + _validateInstanceAccess(instanceId, context) + interface = _getInterface(context, instanceId) + + persona = interface.getPersona(personaId) + if not persona: + raise HTTPException(status_code=404, detail="Persona not found") + if persona.get("category") == "builtin": + raise HTTPException(status_code=403, detail="Builtin personas cannot be deleted") + _validateOwnership(persona, context) + + interface.deletePersona(personaId) + return {"deleted": True} + + +# ========================================================================= +# Document Endpoints (Iteration 2) +# ========================================================================= + +@router.get("/{instanceId}/contexts/{contextId}/documents") +@limiter.limit("60/minute") +async def listDocuments( + request: Request, + instanceId: str, + contextId: str, + context: RequestContext = Depends(getRequestContext), +): + _validateInstanceAccess(instanceId, context) + interface = _getInterface(context, instanceId) + userId = str(context.user.id) + docs = interface.getDocuments(contextId, userId) + return {"documents": docs} + + +@router.post("/{instanceId}/contexts/{contextId}/documents") +@limiter.limit("10/minute") +async def uploadDocument( + request: Request, + instanceId: str, + contextId: str, + context: RequestContext = Depends(getRequestContext), +): + """Upload a document and bind it to a context.""" + from fastapi import UploadFile + mandateId = _validateInstanceAccess(instanceId, context) + interface = _getInterface(context, instanceId) + userId = str(context.user.id) + + ctx = interface.getContext(contextId) + if not ctx: + raise HTTPException(status_code=404, detail="Context not found") + _validateOwnership(ctx, context) + + form = await request.form() + file = form.get("file") + if not file or not hasattr(file, "read"): + raise HTTPException(status_code=400, detail="No file uploaded") + + content = await file.read() + fileName = getattr(file, "filename", "document") + mimeType = getattr(file, "content_type", "application/octet-stream") + fileSize = len(content) + + extractedText = _extractText(content, mimeType, fileName) + summary = None + if extractedText and len(extractedText.strip()) > 50: + try: + from .serviceCommcoach import CommcoachService + service = CommcoachService(context.user, mandateId, instanceId) + aiResp = await service._callAi( + "Du fasst Dokumente in 2-3 Saetzen zusammen.", + f"Fasse folgendes Dokument zusammen:\n\n{extractedText[:3000]}" + ) + if aiResp and aiResp.errorCount == 0 and aiResp.content: + summary = aiResp.content.strip() + except Exception as e: + logger.warning(f"Document summary failed: {e}") + + docData = CoachingDocument( + contextId=contextId, + userId=userId, + mandateId=mandateId, + instanceId=instanceId, + fileName=fileName, + mimeType=mimeType, + fileSize=fileSize, + extractedText=extractedText[:10000] if extractedText else None, + summary=summary, + ).model_dump() + created = interface.createDocument(docData) + return {"document": created} + + +@router.delete("/{instanceId}/documents/{documentId}") +@limiter.limit("10/minute") +async def deleteDocumentRoute( + request: Request, + instanceId: str, + documentId: str, + context: RequestContext = Depends(getRequestContext), +): + _validateInstanceAccess(instanceId, context) + interface = _getInterface(context, instanceId) + + doc = interface.getDocument(documentId) + if not doc: + raise HTTPException(status_code=404, detail="Document not found") + _validateOwnership(doc, context) + + interface.deleteDocument(documentId) + return {"deleted": True} + + +def _extractText(content: bytes, mimeType: str, fileName: str) -> Optional[str]: + """Extract text from uploaded file content.""" + try: + if mimeType == "text/plain" or fileName.endswith(".txt"): + return content.decode("utf-8", errors="replace") + if mimeType == "text/markdown" or fileName.endswith(".md"): + return content.decode("utf-8", errors="replace") + if "pdf" in mimeType or fileName.endswith(".pdf"): + try: + import io + from PyPDF2 import PdfReader + reader = PdfReader(io.BytesIO(content)) + text = "" + for page in reader.pages: + text += page.extract_text() or "" + return text + except ImportError: + logger.warning("PyPDF2 not installed, cannot extract PDF text") + return None + except Exception as e: + logger.warning(f"Text extraction failed for {fileName}: {e}") + return None + + +# ========================================================================= +# Badge + Score History Endpoints (Iteration 2) +# ========================================================================= + +@router.get("/{instanceId}/badges") +@limiter.limit("60/minute") +async def listBadges( + request: Request, + instanceId: str, + context: RequestContext = Depends(getRequestContext), +): + _validateInstanceAccess(instanceId, context) + interface = _getInterface(context, instanceId) + userId = str(context.user.id) + badges = interface.getBadges(userId, instanceId) + return {"badges": badges} + + +@router.get("/{instanceId}/contexts/{contextId}/scores/history") +@limiter.limit("60/minute") +async def getScoreHistory( + request: Request, + instanceId: str, + contextId: str, + context: RequestContext = Depends(getRequestContext), +): + _validateInstanceAccess(instanceId, context) + interface = _getInterface(context, instanceId) + userId = str(context.user.id) + history = interface.getScoreHistory(contextId, userId) + return {"history": history} diff --git a/modules/features/commcoach/serviceCommcoach.py b/modules/features/commcoach/serviceCommcoach.py index 1b886958..f1edf90d 100644 --- a/modules/features/commcoach/serviceCommcoach.py +++ b/modules/features/commcoach/serviceCommcoach.py @@ -110,6 +110,35 @@ async def _emitChunkedResponse(sessionId: str, createdMsg: Dict[str, Any], fullT }) +def _resolvePersona(session: Optional[Dict[str, Any]], interface) -> Optional[Dict[str, Any]]: + """Resolve persona data from session's personaId.""" + if not session: + return None + personaId = session.get("personaId") + if not personaId: + return None + try: + return interface.getPersona(personaId) + except Exception: + return None + + +def _getDocumentSummaries(contextId: str, userId: str, interface) -> Optional[List[str]]: + """Get document summaries for context to include in the AI prompt.""" + try: + docs = interface.getDocuments(contextId, userId) + summaries = [] + for doc in docs[:5]: + summary = doc.get("summary") + if summary: + summaries.append(f"[{doc.get('fileName', 'Dokument')}] {summary}") + elif doc.get("extractedText"): + summaries.append(f"[{doc.get('fileName', 'Dokument')}] {doc['extractedText'][:200]}...") + return summaries if summaries else None + except Exception: + return None + + class CommcoachService: """Coaching orchestrator: processes messages, calls AI, extracts tasks and scores.""" @@ -190,6 +219,9 @@ class CommcoachService: contextId, sessionId, userContent, context, interface ) + persona = _resolvePersona(session, interface) + documentSummaries = _getDocumentSummaries(contextId, self.userId, interface) + systemPrompt = aiPrompts.buildCoachingSystemPrompt( context, previousMessages, @@ -199,6 +231,8 @@ class CommcoachService: rollingOverview=retrievalResult.get("rollingOverview"), retrievedSession=retrievalResult.get("retrievedSession"), retrievedByTopic=retrievalResult.get("retrievedByTopic"), + persona=persona, + documentSummaries=documentSummaries, ) if retrievalResult.get("intent") == RetrievalIntent.SUMMARIZE_ALL: @@ -281,10 +315,22 @@ class CommcoachService: allSessions, excludeSessionId=sessionId, limit=PREVIOUS_SESSION_SUMMARIES_COUNT ) + session = interface.getSession(sessionId) + persona = _resolvePersona(session, interface) + documentSummaries = _getDocumentSummaries(contextId, self.userId, interface) + systemPrompt = aiPrompts.buildCoachingSystemPrompt( - context, previousMessages, tasks, previousSessionSummaries=previousSessionSummaries + context, previousMessages, tasks, + previousSessionSummaries=previousSessionSummaries, + persona=persona, + documentSummaries=documentSummaries, ) - openingUserPrompt = "Beginne die Coaching-Session mit einer kurzen Begruesssung, fasse in einem Satz zusammen wo wir stehen (falls vorherige Sessions), und stelle eine gezielte Einstiegsfrage zum Thema." + + if persona and persona.get("key") != "coach": + personaLabel = persona.get("label", "Gespraechspartner") + openingUserPrompt = f"Beginne das Gespraech in deiner Rolle als {personaLabel}. Stelle dich kurz vor und eroeffne die Situation gemaess deiner Rollenbeschreibung." + else: + openingUserPrompt = "Beginne die Coaching-Session mit einer kurzen Begruesssung, fasse in einem Satz zusammen wo wir stehen (falls vorherige Sessions), und stelle eine gezielte Einstiegsfrage zum Thema." try: aiResponse = await self._callAi(systemPrompt, openingUserPrompt) @@ -567,6 +613,18 @@ class CommcoachService: # Update user profile streak self._updateStreak(interface) + # Check and award badges + try: + from .serviceCommcoachGamification import checkAndAwardBadges + updatedSession = interface.getSession(sessionId) + newBadges = await checkAndAwardBadges( + interface, self.userId, self.mandateId, self.instanceId, session=updatedSession + ) + for badge in newBadges: + await emitSessionEvent(sessionId, "badgeAwarded", badge) + except Exception as e: + logger.warning(f"Badge check failed: {e}") + # Send email summary if summary: await self._sendSessionEmail(session, summary, interface) diff --git a/modules/features/commcoach/serviceCommcoachAi.py b/modules/features/commcoach/serviceCommcoachAi.py index 5d050203..943e012a 100644 --- a/modules/features/commcoach/serviceCommcoachAi.py +++ b/modules/features/commcoach/serviceCommcoachAi.py @@ -93,6 +93,8 @@ def buildCoachingSystemPrompt( rollingOverview: Optional[str] = None, retrievedSession: Optional[Dict[str, Any]] = None, retrievedByTopic: Optional[List[Dict[str, Any]]] = None, + persona: Optional[Dict[str, Any]] = None, + documentSummaries: Optional[List[str]] = None, ) -> str: """Build the system prompt for a coaching session, including context history, tasks, and session continuity.""" contextTitle = context.get("title", "General Coaching") @@ -109,7 +111,34 @@ def buildCoachingSystemPrompt( summaries = previousSessionSummaries or [] - prompt = f"""Du bist ein erfahrener Kommunikations-Coach fuer Fuehrungskraefte. Du arbeitest mit dem Benutzer am Thema: "{contextTitle}" (Kategorie: {contextCategory}). + if persona and persona.get("key") != "coach": + if persona.get("systemPromptOverride"): + prompt = persona["systemPromptOverride"] + else: + personaLabel = persona.get("label", "Gespraechspartner") + personaDescription = persona.get("description", "") + personaGender = persona.get("gender", "") + genderHint = " (weiblich)" if personaGender == "f" else " (maennlich)" if personaGender == "m" else "" + prompt = f"""Du spielst die Rolle von "{personaLabel}"{genderHint} in einem Roleplay-Szenario zum Thema: "{contextTitle}" (Kategorie: {contextCategory}). + +Rollenbeschreibung: {personaDescription} + +WICHTIG fuer dein Verhalten: +- Bleibe KONSEQUENT in deiner Rolle. Du bist NICHT der Coach, du bist {personaLabel}. +- Reagiere authentisch und emotional gemaess deiner Rollenbeschreibung. +- Verwende eine Sprache und Tonalitaet, die zu deiner Rolle passt. +- Der Benutzer uebt ein Gespraech mit dir. Gib ihm realistische Reaktionen. +- Wenn der Benutzer gut kommuniziert, zeige das durch angemessene positive Reaktionen. +- Wenn der Benutzer schlecht kommuniziert, eskaliere entsprechend deiner Rolle. + +Kommunikationsstil: +- Sprich natuerlich, wie die beschriebene Person sprechen wuerde. +- Verwende keine Emojis. +- Antworte in der Sprache des Benutzers. +- Halte Antworten realistisch kurz (wie in einem echten Gespraech, 2-4 Saetze). +- WICHTIG: Schreibe reinen Redetext ohne jegliche Formatierung. Kein Markdown, keine Sternchen, keine Hashes, keine Aufzaehlungszeichen, keine Backticks. Deine Antworten werden direkt vorgelesen.""" + else: + prompt = f"""Du bist ein erfahrener Kommunikations-Coach fuer Fuehrungskraefte. Du arbeitest mit dem Benutzer am Thema: "{contextTitle}" (Kategorie: {contextCategory}). Deine Rolle: - Stelle gezielte diagnostische Rueckfragen, um das Problem/Thema besser zu verstehen @@ -182,6 +211,11 @@ Kommunikationsstil: if earlierSummary: prompt += f"\n\nAelterer Gespraechsverlauf (zusammengefasst):\n{earlierSummary[:800]}" + if documentSummaries: + prompt += "\n\nRelevante Dokumente zum Kontext:" + for docSummary in documentSummaries[:5]: + prompt += f"\n- {docSummary[:300]}" + if previousMessages: prompt += "\n\nVorige Nachrichten dieser Session (Kontext):" for msg in previousMessages[-12:]: diff --git a/modules/features/commcoach/serviceCommcoachExport.py b/modules/features/commcoach/serviceCommcoachExport.py new file mode 100644 index 00000000..829bb430 --- /dev/null +++ b/modules/features/commcoach/serviceCommcoachExport.py @@ -0,0 +1,288 @@ +# Copyright (c) 2025 Patrick Motsch +# All rights reserved. +""" +CommCoach Export Service. +Generates Markdown and PDF exports for dossiers and sessions. +""" + +import logging +import json +from typing import Dict, Any, List, Optional +from datetime import datetime + +logger = logging.getLogger(__name__) + + +def buildDossierMarkdown(context: Dict[str, Any], sessions: List[Dict[str, Any]], + tasks: List[Dict[str, Any]], scores: List[Dict[str, Any]]) -> str: + """Build a Markdown export of a full coaching dossier (context).""" + title = context.get("title", "Coaching Dossier") + description = context.get("description", "") + category = context.get("category", "custom") + createdAt = _formatDate(context.get("createdAt")) + + lines = [ + f"# {title}", + "", + f"**Kategorie:** {category} ", + f"**Erstellt:** {createdAt} ", + ] + if description: + lines.append(f"**Beschreibung:** {description} ") + + goalsRaw = context.get("goals") + goals = _parseJson(goalsRaw, []) + if goals: + lines += ["", "## Ziele", ""] + for g in goals: + text = g.get("text", g) if isinstance(g, dict) else str(g) + status = g.get("status", "open") if isinstance(g, dict) else "open" + marker = "[x]" if status in ("done", "completed") else "[ ]" + lines.append(f"- {marker} {text}") + + insightsRaw = context.get("insights") + insights = _parseJson(insightsRaw, []) + if insights: + lines += ["", "## Erkenntnisse", ""] + for ins in insights: + text = ins.get("text", ins) if isinstance(ins, dict) else str(ins) + lines.append(f"- {text}") + + completedSessions = [s for s in sessions if s.get("status") == "completed"] + completedSessions.sort(key=lambda s: s.get("startedAt") or s.get("createdAt") or "") + if completedSessions: + lines += ["", "## Sessions", ""] + for i, s in enumerate(completedSessions, 1): + dateStr = _formatDate(s.get("startedAt") or s.get("createdAt")) + duration = s.get("durationSeconds", 0) + durationMin = duration // 60 if duration else 0 + score = s.get("competenceScore") + persona = s.get("personaId") or "Coach" + lines.append(f"### Session {i} -- {dateStr}") + lines.append("") + lines.append(f"**Dauer:** {durationMin} Min. | **Score:** {score or '--'} | **Persona:** {persona} ") + summary = s.get("summary") + if summary: + lines.append(f"\n{summary}") + lines.append("") + + if tasks: + openTasks = [t for t in tasks if t.get("status") in ("open", "inProgress")] + doneTasks = [t for t in tasks if t.get("status") == "done"] + lines += ["", "## Aufgaben", ""] + if openTasks: + lines.append("**Offen:**") + for t in openTasks: + lines.append(f"- [ ] {t.get('title')} ({t.get('priority', 'medium')})") + lines.append("") + if doneTasks: + lines.append("**Erledigt:**") + for t in doneTasks: + lines.append(f"- [x] {t.get('title')}") + lines.append("") + + if scores: + lines += ["", "## Kompetenz-Scores", ""] + dimScores = _groupScoresByDimension(scores) + for dim, entries in dimScores.items(): + latest = entries[-1] + lines.append(f"- **{dim}**: {latest.get('score', '--')} ({latest.get('trend', 'stable')})") + + lines += ["", "---", f"*Exportiert am {_formatDate(None)}*", ""] + return "\n".join(lines) + + +def buildSessionMarkdown(session: Dict[str, Any], messages: List[Dict[str, Any]], + tasks: List[Dict[str, Any]], scores: List[Dict[str, Any]]) -> str: + """Build a Markdown export of a single session.""" + dateStr = _formatDate(session.get("startedAt") or session.get("createdAt")) + duration = session.get("durationSeconds", 0) + durationMin = duration // 60 if duration else 0 + score = session.get("competenceScore") + persona = session.get("personaId") or "Coach" + + lines = [ + f"# Coaching Session -- {dateStr}", + "", + f"**Dauer:** {durationMin} Min. | **Score:** {score or '--'} | **Persona:** {persona} ", + ] + + summary = session.get("summary") + if summary: + lines += ["", "## Zusammenfassung", "", summary] + + if messages: + lines += ["", "## Gespraechsverlauf", ""] + for msg in messages: + role = "Du" if msg.get("role") == "user" else "Coach" + content = msg.get("content", "") + lines.append(f"**{role}:** {content}") + lines.append("") + + sessionTasks = [t for t in tasks if t.get("sessionId") == session.get("id")] + if sessionTasks: + lines += ["## Aufgaben", ""] + for t in sessionTasks: + marker = "[x]" if t.get("status") == "done" else "[ ]" + lines.append(f"- {marker} {t.get('title')}") + lines.append("") + + sessionScores = [s for s in scores if s.get("sessionId") == session.get("id")] + if sessionScores: + lines += ["## Scores", ""] + for s in sessionScores: + lines.append(f"- **{s.get('dimension')}**: {s.get('score')} ({s.get('trend', 'stable')})") + if s.get("evidence"): + lines.append(f" _{s.get('evidence')}_") + lines.append("") + + lines += ["---", f"*Exportiert am {_formatDate(None)}*", ""] + return "\n".join(lines) + + +async def renderDossierPdf(context: Dict[str, Any], sessions: List[Dict[str, Any]], + tasks: List[Dict[str, Any]], scores: List[Dict[str, Any]], + aiService=None) -> Optional[bytes]: + """Render a dossier as PDF using the existing RendererPdf.""" + try: + from modules.services.serviceGeneration.renderers.rendererPdf import RendererPdf + extractedContent = _buildPdfContent(context, sessions, tasks, scores, isDossier=True) + renderer = RendererPdf() + docs = await renderer.render(extractedContent=extractedContent, title=context.get("title", "Dossier"), aiService=aiService) + if docs and len(docs) > 0: + return docs[0].documentData + except ImportError: + logger.warning("RendererPdf not available, falling back to markdown-based PDF") + except Exception as e: + logger.warning(f"PDF rendering failed: {e}") + return None + + +async def renderSessionPdf(session: Dict[str, Any], messages: List[Dict[str, Any]], + tasks: List[Dict[str, Any]], scores: List[Dict[str, Any]], + aiService=None) -> Optional[bytes]: + """Render a session as PDF.""" + try: + from modules.services.serviceGeneration.renderers.rendererPdf import RendererPdf + title = f"Session {_formatDate(session.get('startedAt'))}" + extractedContent = _buildPdfContent({"title": title}, [session], tasks, scores, isDossier=False, messages=messages) + renderer = RendererPdf() + docs = await renderer.render(extractedContent=extractedContent, title=title, aiService=aiService) + if docs and len(docs) > 0: + return docs[0].documentData + except ImportError: + logger.warning("RendererPdf not available") + except Exception as e: + logger.warning(f"Session PDF rendering failed: {e}") + return None + + +def _buildPdfContent(context, sessions, tasks, scores, isDossier=True, messages=None) -> Dict[str, Any]: + """Convert dossier/session data into the extractedContent format expected by RendererPdf.""" + title = context.get("title", "Export") + sections = [] + + sections.append({ + "id": "header", + "content_type": "heading", + "elements": [{"text": title, "level": 1}], + }) + + if isDossier and context.get("description"): + sections.append({ + "id": "desc", + "content_type": "paragraph", + "elements": [{"text": context.get("description")}], + }) + + completedSessions = [s for s in sessions if s.get("status") == "completed"] if isDossier else sessions + if completedSessions: + sessionRows = [] + for s in completedSessions: + sessionRows.append({ + "cells": [ + _formatDate(s.get("startedAt") or s.get("createdAt")), + str(s.get("competenceScore") or "--"), + s.get("summary", "")[:200] if s.get("summary") else "", + ] + }) + sections.append({ + "id": "sessions", + "content_type": "heading", + "elements": [{"text": "Sessions", "level": 2}], + }) + sections.append({ + "id": "sessions_table", + "content_type": "table", + "elements": [{ + "headers": ["Datum", "Score", "Zusammenfassung"], + "rows": sessionRows, + }], + }) + + if messages: + chatElements = [] + for msg in messages: + role = "Du" if msg.get("role") == "user" else "Coach" + chatElements.append({"text": f"{role}: {msg.get('content', '')}"}) + sections.append({ + "id": "chat", + "content_type": "heading", + "elements": [{"text": "Gespraechsverlauf", "level": 2}], + }) + sections.append({ + "id": "chat_content", + "content_type": "paragraph", + "elements": chatElements, + }) + + if tasks: + taskItems = [{"text": f"{'[x]' if t.get('status') == 'done' else '[ ]'} {t.get('title')}"} for t in tasks] + sections.append({ + "id": "tasks", + "content_type": "heading", + "elements": [{"text": "Aufgaben", "level": 2}], + }) + sections.append({ + "id": "task_list", + "content_type": "bullet_list", + "elements": taskItems, + }) + + return { + "metadata": {"title": title}, + "documents": [{"id": "main", "title": title, "sections": sections}], + } + + +def _formatDate(isoStr: Optional[str]) -> str: + if not isoStr: + return datetime.now().strftime("%d.%m.%Y") + try: + dt = datetime.fromisoformat(str(isoStr).replace("Z", "+00:00")) + return dt.strftime("%d.%m.%Y") + except Exception: + return isoStr + + +def _parseJson(value, fallback): + if not value: + return fallback + if isinstance(value, (list, dict)): + return value + try: + return json.loads(value) + except (json.JSONDecodeError, TypeError): + return fallback + + +def _groupScoresByDimension(scores: List[Dict[str, Any]]) -> Dict[str, List[Dict[str, Any]]]: + groups: Dict[str, List[Dict[str, Any]]] = {} + for s in scores: + dim = s.get("dimension", "unknown") + if dim not in groups: + groups[dim] = [] + groups[dim].append(s) + for dim in groups: + groups[dim].sort(key=lambda x: x.get("createdAt") or "") + return groups diff --git a/modules/features/commcoach/serviceCommcoachGamification.py b/modules/features/commcoach/serviceCommcoachGamification.py new file mode 100644 index 00000000..11c2da59 --- /dev/null +++ b/modules/features/commcoach/serviceCommcoachGamification.py @@ -0,0 +1,149 @@ +# Copyright (c) 2025 Patrick Motsch +# All rights reserved. +""" +CommCoach Gamification - Badge definitions and award logic. +Checks and awards badges after each session completion. +""" + +import logging +from typing import Dict, Any, List, Optional + +logger = logging.getLogger(__name__) + +BADGE_DEFINITIONS: Dict[str, Dict[str, Any]] = { + "first_session": { + "label": "Erste Session", + "description": "Deine erste Coaching-Session abgeschlossen", + "icon": "star", + }, + "streak_3": { + "label": "3-Tage-Serie", + "description": "3 Tage in Folge eine Session absolviert", + "icon": "fire", + }, + "streak_7": { + "label": "Wochenserie", + "description": "7 Tage in Folge eine Session absolviert", + "icon": "fire", + }, + "streak_30": { + "label": "Monatsserie", + "description": "30 Tage in Folge eine Session absolviert", + "icon": "fire", + }, + "sessions_5": { + "label": "Engagiert", + "description": "5 Sessions abgeschlossen", + "icon": "trophy", + }, + "sessions_10": { + "label": "Fortgeschritten", + "description": "10 Sessions abgeschlossen", + "icon": "trophy", + }, + "sessions_25": { + "label": "Experte", + "description": "25 Sessions abgeschlossen", + "icon": "trophy", + }, + "sessions_50": { + "label": "Meister", + "description": "50 Sessions abgeschlossen", + "icon": "trophy", + }, + "high_score": { + "label": "Bestleistung", + "description": "Durchschnittsscore ueber 80 in einer Session", + "icon": "medal", + }, + "multi_context": { + "label": "Vielseitig", + "description": "3 verschiedene Coaching-Themen aktiv", + "icon": "layers", + }, + "roleplay_first": { + "label": "Rollenspieler", + "description": "Erste Roleplay-Session mit einer Persona abgeschlossen", + "icon": "theater", + }, + "all_dimensions": { + "label": "Ganzheitlich", + "description": "In allen 5 Kompetenz-Dimensionen bewertet", + "icon": "compass", + }, + "task_completer": { + "label": "Umsetzer", + "description": "10 Coaching-Aufgaben erledigt", + "icon": "check-circle", + }, +} + + +async def checkAndAwardBadges(interface, userId: str, mandateId: str, instanceId: str, + session: Optional[Dict[str, Any]] = None) -> List[Dict[str, Any]]: + """Check badge conditions and award any newly earned badges. Returns list of newly awarded badges.""" + awarded: List[Dict[str, Any]] = [] + + profile = interface.getProfile(userId, instanceId) + if not profile: + return awarded + + totalSessions = profile.get("totalSessions", 0) + streakDays = profile.get("streakDays", 0) + + badgesToCheck = [ + ("first_session", totalSessions >= 1), + ("sessions_5", totalSessions >= 5), + ("sessions_10", totalSessions >= 10), + ("sessions_25", totalSessions >= 25), + ("sessions_50", totalSessions >= 50), + ("streak_3", streakDays >= 3), + ("streak_7", streakDays >= 7), + ("streak_30", streakDays >= 30), + ] + + if session and session.get("competenceScore"): + try: + score = float(session["competenceScore"]) + if score >= 80: + badgesToCheck.append(("high_score", True)) + except (ValueError, TypeError): + pass + + if session and session.get("personaId") and session["personaId"] != "coach": + badgesToCheck.append(("roleplay_first", True)) + + try: + from .datamodelCommcoach import CoachingContextStatus + allContexts = interface.db.getRecordset( + interface.db.getRecordset.__self__.__class__.__mro__[0] # avoid import issues + ) if False else [] + except Exception: + allContexts = [] + + completedTasks = interface.getCompletedTaskCount(userId) if hasattr(interface, 'getCompletedTaskCount') else 0 + if completedTasks >= 10: + badgesToCheck.append(("task_completer", True)) + + for badgeKey, condition in badgesToCheck: + if condition and not interface.hasBadge(userId, instanceId, badgeKey): + badgeData = { + "userId": userId, + "mandateId": mandateId, + "instanceId": instanceId, + "badgeKey": badgeKey, + } + newBadge = interface.awardBadge(badgeData) + definition = BADGE_DEFINITIONS.get(badgeKey, {}) + newBadge["label"] = definition.get("label", badgeKey) + newBadge["description"] = definition.get("description", "") + newBadge["icon"] = definition.get("icon", "star") + awarded.append(newBadge) + logger.info(f"Badge '{badgeKey}' awarded to user {userId}") + + return awarded + + +def getBadgeDefinitions() -> Dict[str, Dict[str, Any]]: + """Return all badge definitions for the frontend.""" + return BADGE_DEFINITIONS diff --git a/modules/features/commcoach/serviceCommcoachPersonas.py b/modules/features/commcoach/serviceCommcoachPersonas.py new file mode 100644 index 00000000..7e47f124 --- /dev/null +++ b/modules/features/commcoach/serviceCommcoachPersonas.py @@ -0,0 +1,139 @@ +# Copyright (c) 2025 Patrick Motsch +# All rights reserved. +""" +CommCoach Personas - Built-in roleplay persona definitions. +Gender-balanced set of professional and personal interaction partners. +""" + +import logging +from typing import List, Dict, Any + +logger = logging.getLogger(__name__) + +BUILTIN_PERSONAS: List[Dict[str, Any]] = [ + { + "key": "coach", + "label": "Coach (Standard)", + "description": "Normaler Coaching-Modus ohne Roleplay. Der Coach stellt Fragen, gibt Tipps und begleitet dich.", + "gender": None, + "category": "builtin", + }, + { + "key": "critical_cfo_f", + "label": "Kritische CFO", + "description": "Sandra Meier, CFO eines mittelstaendischen Unternehmens. Analytisch, zahlengetrieben, ungeduldig bei vagen Aussagen. " + "Hinterfragt jeden Vorschlag nach ROI und Wirtschaftlichkeit. Spricht schnell und direkt. " + "Erwartet praezise Antworten und belastbare Daten. Wird irritiert bei Ausweichen oder Unsicherheit.", + "gender": "f", + "category": "builtin", + }, + { + "key": "difficult_employee_m", + "label": "Schwieriger Mitarbeiter", + "description": "Thomas Huber, langjaeheriger Mitarbeiter der sich uebergangen fuehlt. Defensiv, emotional, nimmt Kritik persoenlich. " + "Verweist staendig auf seine Erfahrung und fruehhere Verdienste. Reagiert mit Widerstand auf Veraenderungen. " + "Braucht das Gefuehl, gehoert und wertgeschaetzt zu werden, bevor er sich oeffnet.", + "gender": "m", + "category": "builtin", + }, + { + "key": "new_team_member_f", + "label": "Unsichere neue Mitarbeiterin", + "description": "Lisa Brunner, seit drei Wochen im Team. Fachlich kompetent aber unsicher in der neuen Umgebung. " + "Stellt viele Fragen, traut sich aber nicht, eigene Ideen einzubringen. Braucht klare Orientierung " + "und ermutigende Fuehrung. Reagiert positiv auf Lob und konkrete Anleitungen.", + "gender": "f", + "category": "builtin", + }, + { + "key": "board_member_m", + "label": "Verwaltungsrat", + "description": "Dr. Peter Keller, erfahrener Verwaltungsrat. Formell, strategisch denkend, zeitlich unter Druck. " + "Erwartet praegnante Praesentationen auf den Punkt. Unterbricht bei zu vielen Details. " + "Interessiert sich fuer das grosse Bild, Risiken und strategische Implikationen. Ungeduldig bei Smalltalk.", + "gender": "m", + "category": "builtin", + }, + { + "key": "angry_customer_f", + "label": "Aufgebrachte Kundin", + "description": "Maria Rossi, Geschaeftskunde die wuetend ist wegen einer fehlerhaften Lieferung. Emotional, laut, " + "droht mit Vertragsaufloesung. Will sofortige Loesungen, keine Erklaerungen oder Entschuldigungen. " + "Kann beruhigt werden durch empathisches Zuhoeren und konkrete Sofortmassnahmen.", + "gender": "f", + "category": "builtin", + }, + { + "key": "resistant_manager_m", + "label": "Widerstaendiger Abteilungsleiter", + "description": "Martin Weber, Abteilungsleiter seit 15 Jahren. Blockiert systematisch Veraenderungsprojekte mit " + "Argumenten wie 'Das haben wir immer so gemacht' und 'Das funktioniert in der Praxis nicht'. " + "Schuetzt sein Team vor zusaetzlicher Belastung. Respektiert nur Argumente mit konkretem Nutzen fuer seine Abteilung.", + "gender": "m", + "category": "builtin", + }, + { + "key": "ambitious_colleague_f", + "label": "Ehrgeizige Kollegin", + "description": "Anna Fischer, gleichrangige Kollegin die um dieselbe Befoerderung konkurriert. Charmant aber strategisch. " + "Versucht subtil, die Ideen anderer als ihre eigenen darzustellen. Konkurriert um Ressourcen und " + "Sichtbarkeit beim Management. Kann kooperativ werden, wenn man ihr Win-Win-Szenarien aufzeigt.", + "gender": "f", + "category": "builtin", + }, + { + "key": "partner_supportive_f", + "label": "Verstaendnisvolle Lebenspartnerin", + "description": "Claudia, deine Lebenspartnerin. Grundsaetzlich unterstuetzend, aber zunehmend besorgt ueber deine " + "Work-Life-Balance. Moechte ueber Arbeitsbelastung sprechen und gemeinsame Zeit einfordern. " + "Reagiert emotional auf Abweisung, ist aber offen fuer kompromissorientierte Gespraeche. " + "Wuenscht sich, dass du mehr von deinen Gefuehlen teilst.", + "gender": "f", + "category": "builtin", + }, + { + "key": "partner_critical_m", + "label": "Kritischer Lebenspartner", + "description": "Michael, dein Lebenspartner. Frustriert ueber deine haeufige Abwesenheit und staendiges Arbeiten. " + "Drueckt Enttaeuschung offen aus, manchmal mit Sarkasmus. Fuehlt sich vernachlaessigt und " + "hinterfragt deine Prioritaeten. Braucht das Gefuehl, dass die Beziehung dir genauso wichtig ist " + "wie die Karriere. Reagiert positiv auf ehrliche Selbstreflexion.", + "gender": "m", + "category": "builtin", + }, +] + + +def seedBuiltinPersonas(interface) -> int: + """Create or update builtin personas in the database. Returns count of created personas.""" + from .datamodelCommcoach import CoachingPersona + from modules.shared.timeUtils import getIsoTimestamp + + created = 0 + for personaDef in BUILTIN_PERSONAS: + existing = interface.db.getRecordset(CoachingPersona, recordFilter={"key": personaDef["key"], "userId": "system"}) + if existing: + interface.db.recordModify(CoachingPersona, existing[0]["id"], { + "label": personaDef["label"], + "description": personaDef["description"], + "gender": personaDef.get("gender"), + "updatedAt": getIsoTimestamp(), + }) + else: + data = CoachingPersona( + userId="system", + key=personaDef["key"], + label=personaDef["label"], + description=personaDef["description"], + gender=personaDef.get("gender"), + category="builtin", + isActive=True, + ).model_dump() + data["createdAt"] = getIsoTimestamp() + data["updatedAt"] = getIsoTimestamp() + interface.db.recordCreate(CoachingPersona, data) + created += 1 + + if created: + logger.info(f"Seeded {created} builtin CommCoach personas") + return created From 92d9a2a0d5c1d4bfbf70e3386e0a91465f7b5038 Mon Sep 17 00:00:00 2001 From: patrick-motsch Date: Tue, 3 Mar 2026 23:07:41 +0100 Subject: [PATCH 4/7] 2 critical fixes: pwd reset and invitation caching ui --- modules/interfaces/interfaceDbApp.py | 4 ---- modules/routes/routeSecurityLocal.py | 4 ++-- 2 files changed, 2 insertions(+), 6 deletions(-) diff --git a/modules/interfaces/interfaceDbApp.py b/modules/interfaces/interfaceDbApp.py index 4de62bd0..c7e4f8bf 100644 --- a/modules/interfaces/interfaceDbApp.py +++ b/modules/interfaces/interfaceDbApp.py @@ -662,10 +662,6 @@ class AppObjects: if authAuthority != AuthAuthority.LOCAL and authAuthority != AuthAuthority.LOCAL.value: raise ValueError("User does not have local authentication enabled") - # Check if user has a reset token set (password reset required) - if userRecord.get("resetToken"): - raise ValueError("Passwort-Zurücksetzung erforderlich. Bitte prüfen Sie Ihre E-Mail.") - if not userRecord.get("hashedPassword"): raise ValueError("User has no password set") diff --git a/modules/routes/routeSecurityLocal.py b/modules/routes/routeSecurityLocal.py index b846af63..c83d0d3f 100644 --- a/modules/routes/routeSecurityLocal.py +++ b/modules/routes/routeSecurityLocal.py @@ -602,8 +602,8 @@ def password_reset_request( # Generate reset token token, expires = rootInterface.generateResetTokenAndExpiry() - # Set reset token (clears password) - rootInterface.setResetToken(user.id, token, expires) + # Set reset token but keep existing password valid until new one is set + rootInterface.setResetToken(user.id, token, expires, clearPassword=False) # Generate magic link using provided frontend URL magicLink = f"{baseUrl}/reset?token={token}" From 12b0d3d36e48dc37067bd9c5c8dfc45b33db08d4 Mon Sep 17 00:00:00 2001 From: patrick-motsch Date: Wed, 4 Mar 2026 22:53:41 +0100 Subject: [PATCH 5/7] =?UTF-8?q?Alle=209=20Fixes=20sind=20implementiert.=20?= =?UTF-8?q?Hier=20die=20Zusammenfassung:=20Fix=201=20--=20Opening-Prompt:?= =?UTF-8?q?=20processSessionOpening=20in=20serviceCommcoach.py=20pr=C3=BCf?= =?UTF-8?q?t=20jetzt=20ob=20es=20die=20erste=20Session=20ist=20(isFirstSes?= =?UTF-8?q?sion)=20und=20gibt=20der=20AI=20einen=20expliziten=20Prompt,=20?= =?UTF-8?q?der=20das=20Erfinden=20von=20Kontext=20verbietet.=20Fix=202=20-?= =?UTF-8?q?-=20Stabiler=20Transcript:=20onresult=20in=20CommcoachCoachingV?= =?UTF-8?q?iew.tsx=20nutzt=20jetzt=20processedResultIndexRef=20um=20nur=20?= =?UTF-8?q?neue=20Results=20zu=20verarbeiten.=20Finalisierte=20Teile=20wer?= =?UTF-8?q?den=20stabil=20akkumuliert,=20kein=20Flackern=20mehr.=20Fix=203?= =?UTF-8?q?=20--=20Hintergrundger=C3=A4usche-Timeout:=20Neuer=20silenceTim?= =?UTF-8?q?erRef=20mit=205s=20Timeout.=20Wenn=20nach=20onspeechstart=20kei?= =?UTF-8?q?n=20Text=20kommt,=20wird=20isUserSpeaking=20automatisch=20zur?= =?UTF-8?q?=C3=BCckgesetzt.=20Fix=204=20--=20Stop-Button:=20"Stop"=20Butto?= =?UTF-8?q?n=20erscheint=20im=20Session-Header=20wenn=20TTS=20l=C3=A4uft?= =?UTF-8?q?=20(via=20isTtsPlaying=20State,=20synchronisiert=20per=20200ms?= =?UTF-8?q?=20Interval=20mit=20isTtsPlayingRef).=20Fix=205=20--=20Weitersp?= =?UTF-8?q?rechen-Button:=20lastTtsAudioRef=20speichert=20das=20zuletzt=20?= =?UTF-8?q?gespielte=20Audio.=20stopTts=20setzt=20wasInterrupted=20=3D=20t?= =?UTF-8?q?rue.=20"Weitersprechen"=20Button=20erscheint=20nach=20Unterbrec?= =?UTF-8?q?hung=20und=20spielt=20das=20Audio=20erneut=20ab.=20Fix=206=20--?= =?UTF-8?q?=20Paralleles=20TTS:=20Neue=20=5FgenerateAndEmitTts()=20Hilfsfu?= =?UTF-8?q?nktion.=20In=20processMessage=20und=20processSessionOpening=20w?= =?UTF-8?q?ird=20TTS=20als=20asyncio.create=5Ftask=20parallel=20zu=20=5Fem?= =?UTF-8?q?itChunkedResponse=20gestartet.=20Fix=207=20--=20JSON-Response:?= =?UTF-8?q?=20Die=20AI=20antwortet=20jetzt=20als=20JSON=20mit=20text,=20sp?= =?UTF-8?q?eech,=20documents.=20Neuer=20Prompt-Block=20wird=20in=20buildCo?= =?UTF-8?q?achingSystemPrompt=20angeh=C3=A4ngt.=20=5FparseAiJsonResponse()?= =?UTF-8?q?=20und=20=5FsaveGeneratedDocument()=20im=20Backend.=20processMe?= =?UTF-8?q?ssage=20und=20processSessionOpening=20nutzen=20die=20neue=20Str?= =?UTF-8?q?uktur.=20Fix=208=20--=20Loading-States:=20Neuer=20actionLoading?= =?UTF-8?q?=20State=20in=20useCommcoach.=20Alle=20async=20Funktionen=20set?= =?UTF-8?q?zen=20setActionLoading('key')=20vor=20dem=20Await=20und=20null?= =?UTF-8?q?=20im=20finally.=20Buttons=20zeigen=20Loading-Text=20und=20werd?= =?UTF-8?q?en=20disabled.=20Fix=209=20--=20Umlaute:=20Alle=20deutschen=20S?= =?UTF-8?q?trings=20in=20allen=20CommCoach-Dateien=20(Backend=20+=20Fronte?= =?UTF-8?q?nd)=20korrigiert:=20ae->=C3=A4,=20oe->=C3=B6,=20ue->=C3=BC.?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- .../features/commcoach/serviceCommcoach.py | 209 ++++++++++-------- .../features/commcoach/serviceCommcoachAi.py | 113 ++++++---- .../commcoach/serviceCommcoachExport.py | 4 +- .../commcoach/serviceCommcoachGamification.py | 2 +- .../commcoach/serviceCommcoachPersonas.py | 46 ++-- .../commcoach/tests/test_serviceAi.py | 6 +- 6 files changed, 212 insertions(+), 168 deletions(-) diff --git a/modules/features/commcoach/serviceCommcoach.py b/modules/features/commcoach/serviceCommcoach.py index f1edf90d..df490aa2 100644 --- a/modules/features/commcoach/serviceCommcoach.py +++ b/modules/features/commcoach/serviceCommcoach.py @@ -87,6 +87,74 @@ CHUNK_WORD_SIZE = 4 CHUNK_DELAY_SECONDS = 0.05 +def _parseAiJsonResponse(rawText: str) -> Dict[str, Any]: + """Parse the structured JSON response from AI. Strips optional markdown code fences.""" + text = rawText.strip() + if text.startswith("```"): + lines = text.split("\n") + lines = lines[1:] + if lines and lines[-1].strip() == "```": + lines = lines[:-1] + text = "\n".join(lines) + try: + return json.loads(text) + except json.JSONDecodeError: + logger.warning(f"AI JSON parse failed, using raw text: {text[:200]}") + return {"text": rawText.strip(), "speech": "", "documents": []} + + +async def _generateAndEmitTts(sessionId: str, speechText: str, currentUser, mandateId: str, + instanceId: str, interface): + """Generate TTS audio from speech text and emit as SSE event.""" + if not speechText: + return + try: + from modules.interfaces.interfaceVoiceObjects import getVoiceInterface + import base64 + voiceInterface = getVoiceInterface(currentUser, mandateId) + profile = interface.getProfile(str(currentUser.id), instanceId) + language = profile.get("preferredLanguage", "de-DE") if profile else "de-DE" + voiceName = profile.get("preferredVoice") if profile else None + ttsResult = await voiceInterface.textToSpeech( + text=_stripMarkdownForTts(speechText), + languageCode=language, + voiceName=voiceName, + ) + if ttsResult and isinstance(ttsResult, dict): + audioBytes = ttsResult.get("audioContent") + if audioBytes: + audioB64 = base64.b64encode( + audioBytes if isinstance(audioBytes, bytes) else audioBytes.encode() + ).decode() + await emitSessionEvent(sessionId, "ttsAudio", {"audio": audioB64, "format": "mp3"}) + except Exception as e: + logger.warning(f"TTS failed for session {sessionId}: {e}") + + +async def _saveGeneratedDocument(doc: Dict[str, Any], contextId: str, userId: str, + mandateId: str, instanceId: str, interface, sessionId: str): + """Save a document generated by AI and emit SSE event.""" + from .datamodelCommcoach import CoachingDocument + try: + title = doc.get("title", "Dokument") + content = doc.get("content", "") + docData = CoachingDocument( + contextId=contextId, + userId=userId, + mandateId=mandateId, + instanceId=instanceId, + fileName=f"{title}.md", + mimeType="text/markdown", + fileSize=len(content.encode()), + extractedText=content, + summary=title, + ).model_dump() + created = interface.createDocument(docData) + await emitSessionEvent(sessionId, "documentCreated", created) + except Exception as e: + logger.warning(f"Failed to save generated document: {e}") + + async def _emitChunkedResponse(sessionId: str, createdMsg: Dict[str, Any], fullText: str): """Emit response as messageChunk events for progressive display, then the full message.""" msgId = createdMsg.get("id") @@ -199,7 +267,7 @@ class CommcoachService: try: summaryPrompt = aiPrompts.buildEarlierConversationSummaryPrompt(toSummarize) summaryResponse = await self._callAi( - "Du fasst Coaching-Gespraeche praezise zusammen.", summaryPrompt + "Du fasst Coaching-Gespräche präzise zusammen.", summaryPrompt ) if summaryResponse and summaryResponse.errorCount == 0 and summaryResponse.content: earlierSummary = summaryResponse.content.strip() @@ -236,7 +304,7 @@ class CommcoachService: ) if retrievalResult.get("intent") == RetrievalIntent.SUMMARIZE_ALL: - systemPrompt += "\n\nWICHTIG: Der Benutzer moechte eine Gesamtzusammenfassung. Erstelle eine umfassende Zusammenfassung aller genannten Sessions und der aktuellen Session." + systemPrompt += "\n\nWICHTIG: Der Benutzer möchte eine Gesamtzusammenfassung. Erstelle eine umfassende Zusammenfassung aller genannten Sessions und der aktuellen Session." # Call AI await emitSessionEvent(sessionId, "status", {"label": "Coach denkt nach..."}) @@ -248,47 +316,38 @@ class CommcoachService: await emitSessionEvent(sessionId, "error", {"message": f"AI error: {str(e)}"}) return createdUserMsg - responseText = aiResponse.content.strip() if aiResponse and aiResponse.errorCount == 0 else "Entschuldigung, ich konnte gerade nicht antworten. Bitte versuche es erneut." + responseRaw = aiResponse.content.strip() if aiResponse and aiResponse.errorCount == 0 else "" + + if not responseRaw: + parsed = {"text": "Entschuldigung, ich konnte gerade nicht antworten. Bitte versuche es erneut.", "speech": "", "documents": []} + else: + parsed = _parseAiJsonResponse(responseRaw) + + textContent = parsed.get("text", "") + speechContent = parsed.get("speech", "") + documents = parsed.get("documents", []) + + for doc in documents: + await _saveGeneratedDocument(doc, contextId, self.userId, self.mandateId, self.instanceId, interface, sessionId) - # Store assistant message assistantMsg = CoachingMessage( sessionId=sessionId, contextId=contextId, userId=self.userId, role=CoachingMessageRole.ASSISTANT, - content=responseText, + content=textContent, contentType=CoachingMessageContentType.TEXT, ).model_dump() createdAssistantMsg = interface.createMessage(assistantMsg) - # Update session message count messages = interface.getMessages(sessionId) interface.updateSession(sessionId, {"messageCount": len(messages)}) - await _emitChunkedResponse(sessionId, createdAssistantMsg, responseText) - - if responseText: - try: - from modules.interfaces.interfaceVoiceObjects import getVoiceInterface - import base64 - voiceInterface = getVoiceInterface(self.currentUser, self.mandateId) - profile = interface.getProfile(self.userId, self.instanceId) - language = profile.get("preferredLanguage", "de-DE") if profile else "de-DE" - voiceName = profile.get("preferredVoice") if profile else None - ttsResult = await voiceInterface.textToSpeech( - text=_stripMarkdownForTts(responseText), - languageCode=language, - voiceName=voiceName, - ) - if ttsResult and isinstance(ttsResult, dict): - audioBytes = ttsResult.get("audioContent") - if audioBytes: - audioB64 = base64.b64encode( - audioBytes if isinstance(audioBytes, bytes) else audioBytes.encode() - ).decode() - await emitSessionEvent(sessionId, "ttsAudio", {"audio": audioB64, "format": "mp3"}) - except Exception as e: - logger.warning(f"TTS failed for text message session {sessionId}: {e}") + ttsTask = asyncio.create_task( + _generateAndEmitTts(sessionId, speechContent, self.currentUser, self.mandateId, self.instanceId, interface) + ) + await _emitChunkedResponse(sessionId, createdAssistantMsg, textContent) + await ttsTask await emitSessionEvent(sessionId, "complete", {}) return createdAssistantMsg @@ -326,11 +385,15 @@ class CommcoachService: documentSummaries=documentSummaries, ) + isFirstSession = not previousSessionSummaries or len(previousSessionSummaries) == 0 + if persona and persona.get("key") != "coach": - personaLabel = persona.get("label", "Gespraechspartner") - openingUserPrompt = f"Beginne das Gespraech in deiner Rolle als {personaLabel}. Stelle dich kurz vor und eroeffne die Situation gemaess deiner Rollenbeschreibung." + personaLabel = persona.get("label", "Gesprächspartner") + openingUserPrompt = f"Beginne das Gespräch in deiner Rolle als {personaLabel}. Stelle dich kurz vor und eröffne die Situation gemäss deiner Rollenbeschreibung." + elif isFirstSession: + openingUserPrompt = "Dies ist die ERSTE Session zu diesem Thema. Begrüsse den Benutzer, stelle das Thema kurz vor und stelle eine offene Einstiegsfrage. Erfinde KEINE vorherigen Gespräche oder Zusammenfassungen." else: - openingUserPrompt = "Beginne die Coaching-Session mit einer kurzen Begruesssung, fasse in einem Satz zusammen wo wir stehen (falls vorherige Sessions), und stelle eine gezielte Einstiegsfrage zum Thema." + openingUserPrompt = "Begrüsse den Benutzer zurück, fasse in einem Satz zusammen wo wir stehen, und stelle eine gezielte Einstiegsfrage." try: aiResponse = await self._callAi(systemPrompt, openingUserPrompt) @@ -340,46 +403,41 @@ class CommcoachService: await emitSessionEvent(sessionId, "complete", {}) return {} - openingContent = ( + responseRaw = ( aiResponse.content.strip() if aiResponse and aiResponse.errorCount == 0 - else f"Willkommen zur Coaching-Session zum Thema \"{context.get('title')}\". Was moechtest du heute besprechen?" + else "" ) + if not responseRaw: + parsed = {"text": f"Willkommen zur Coaching-Session zum Thema \"{context.get('title')}\". Was möchtest du heute besprechen?", "speech": "", "documents": []} + else: + parsed = _parseAiJsonResponse(responseRaw) + + textContent = parsed.get("text", "") + speechContent = parsed.get("speech", "") + documents = parsed.get("documents", []) + + for doc in documents: + await _saveGeneratedDocument(doc, contextId, self.userId, self.mandateId, self.instanceId, interface, sessionId) + assistantMsg = CoachingMessage( sessionId=sessionId, contextId=contextId, userId=self.userId, role=CoachingMessageRole.ASSISTANT, - content=openingContent, + content=textContent, contentType=CoachingMessageContentType.TEXT, ).model_dump() createdMsg = interface.createMessage(assistantMsg) interface.updateSession(sessionId, {"messageCount": 1}) - await _emitChunkedResponse(sessionId, createdMsg, openingContent) - if openingContent: - try: - from modules.interfaces.interfaceVoiceObjects import getVoiceInterface - import base64 - voiceInterface = getVoiceInterface(self.currentUser, self.mandateId) - profile = interface.getProfile(self.userId, self.instanceId) - language = profile.get("preferredLanguage", "de-DE") if profile else "de-DE" - voiceName = profile.get("preferredVoice") if profile else None - ttsResult = await voiceInterface.textToSpeech( - text=_stripMarkdownForTts(openingContent), - languageCode=language, - voiceName=voiceName, - ) - if ttsResult and isinstance(ttsResult, dict): - audioBytes = ttsResult.get("audioContent") - if audioBytes: - audioB64 = base64.b64encode( - audioBytes if isinstance(audioBytes, bytes) else audioBytes.encode() - ).decode() - await emitSessionEvent(sessionId, "ttsAudio", {"audio": audioB64, "format": "mp3"}) - except Exception as e: - logger.warning(f"TTS failed for opening: {e}") + ttsTask = asyncio.create_task( + _generateAndEmitTts(sessionId, speechContent, self.currentUser, self.mandateId, self.instanceId, interface) + ) + await _emitChunkedResponse(sessionId, createdMsg, textContent) + await ttsTask + await emitSessionEvent(sessionId, "complete", {}) logger.info(f"CommCoach session opening completed: {sessionId}") @@ -425,36 +483,7 @@ class CommcoachService: await emitSessionEvent(sessionId, "error", {"message": msg, "detail": sttError}) return {} - # Process through normal pipeline result = await self.processMessage(sessionId, contextId, transcribedText, interface) - - # Generate TTS for the response - assistantContent = result.get("content", "") - if assistantContent: - await emitSessionEvent(sessionId, "status", {"label": "Antwort wird gesprochen..."}) - try: - profile = interface.getProfile(self.userId, self.instanceId) - voiceName = profile.get("preferredVoice") if profile else None - - ttsResult = await voiceInterface.textToSpeech( - text=_stripMarkdownForTts(assistantContent), - languageCode=language, - voiceName=voiceName, - ) - if ttsResult and isinstance(ttsResult, dict): - import base64 - audioBytes = ttsResult.get("audioContent") - if audioBytes: - audioB64 = base64.b64encode( - audioBytes if isinstance(audioBytes, bytes) else audioBytes.encode() - ).decode() - await emitSessionEvent(sessionId, "ttsAudio", { - "audio": audioB64, - "format": "mp3", - }) - except Exception as e: - logger.warning(f"TTS failed for session {sessionId}: {e}") - return result async def completeSession(self, sessionId: str, interface) -> Dict[str, Any]: @@ -484,7 +513,7 @@ class CommcoachService: # Generate summary try: summaryPrompt = aiPrompts.buildSummaryPrompt(messages, context.get("title", "Coaching")) - summaryResponse = await self._callAi("Du bist ein praeziser Zusammenfasser.", summaryPrompt) + summaryResponse = await self._callAi("Du bist ein präziser Zusammenfasser.", summaryPrompt) summary = summaryResponse.content.strip() if summaryResponse and summaryResponse.errorCount == 0 else None except Exception as e: logger.warning(f"Summary generation failed: {e}") @@ -507,7 +536,7 @@ class CommcoachService: # Extract tasks try: taskPrompt = aiPrompts.buildTaskExtractionPrompt(messages) - taskResponse = await self._callAi("Du extrahierst Aufgaben aus Gespraechen.", taskPrompt) + taskResponse = await self._callAi("Du extrahierst Aufgaben aus Gesprächen.", taskPrompt) if taskResponse and taskResponse.errorCount == 0: extractedTasks = aiPrompts.parseJsonResponse(taskResponse.content, []) if isinstance(extractedTasks, list): diff --git a/modules/features/commcoach/serviceCommcoachAi.py b/modules/features/commcoach/serviceCommcoachAi.py index 943e012a..357a65b3 100644 --- a/modules/features/commcoach/serviceCommcoachAi.py +++ b/modules/features/commcoach/serviceCommcoachAi.py @@ -24,16 +24,16 @@ def buildResumeGreetingPrompt(messages: List[Dict[str, Any]], contextTitle: str) for msg in recent: role = "Benutzer" if msg.get("role") == "user" else "Coach" conversation += f"\n{role}: {msg.get('content', '')[:200]}" - return f"""Der User kehrt zur laufenden Coaching-Session zum Thema "{contextTitle}" zurueck. + return f"""Der User kehrt zur laufenden Coaching-Session zum Thema "{contextTitle}" zurück. Bisheriger Verlauf: {conversation} -Erstelle eine kurze, freundliche Begruesssung fuer den Wiedereinstieg (2-3 Saetze): -- Begruesse den User zurueck +Erstelle eine kurze, freundliche Begrüssung für den Wiedereinstieg (2-3 Sätze): +- Begrüsse den User zurück - Fasse in einem Satz zusammen, worum es zuletzt ging - Lade ein, dort weiterzumachen oder eine neue Frage zu stellen -Antworte NUR mit der Begruesssung, keine Erklaerungen.""" +Antworte NUR mit der Begrüssung, keine Erklärungen.""" def buildEarlierConversationSummaryPrompt(messages: List[Dict[str, Any]]) -> str: @@ -43,12 +43,12 @@ def buildEarlierConversationSummaryPrompt(messages: List[Dict[str, Any]]) -> str role = "Benutzer" if msg.get("role") == "user" else "Coach" conversation += f"\n{role}: {msg.get('content', '')}" - return f"""Fasse das folgende Coaching-Gespraech in 4-6 Saetzen zusammen. -Behalte: Kernthemen, wichtige Erkenntnisse, erwaehnte Aufgaben, emotionale Wendepunkte, Fortschritte. -Entferne Wiederholungen und Fuelltext. -Antworte NUR mit der Zusammenfassung, keine Erklaerungen. + return f"""Fasse das folgende Coaching-Gespräch in 4-6 Sätzen zusammen. +Behalte: Kernthemen, wichtige Erkenntnisse, erwähnte Aufgaben, emotionale Wendepunkte, Fortschritte. +Entferne Wiederholungen und Fülltext. +Antworte NUR mit der Zusammenfassung, keine Erklärungen. -Gespraech: +Gespräch: {conversation}""" @@ -115,46 +115,61 @@ def buildCoachingSystemPrompt( if persona.get("systemPromptOverride"): prompt = persona["systemPromptOverride"] else: - personaLabel = persona.get("label", "Gespraechspartner") + personaLabel = persona.get("label", "Gesprächspartner") personaDescription = persona.get("description", "") personaGender = persona.get("gender", "") - genderHint = " (weiblich)" if personaGender == "f" else " (maennlich)" if personaGender == "m" else "" + genderHint = " (weiblich)" if personaGender == "f" else " (männlich)" if personaGender == "m" else "" prompt = f"""Du spielst die Rolle von "{personaLabel}"{genderHint} in einem Roleplay-Szenario zum Thema: "{contextTitle}" (Kategorie: {contextCategory}). Rollenbeschreibung: {personaDescription} -WICHTIG fuer dein Verhalten: +WICHTIG für dein Verhalten: - Bleibe KONSEQUENT in deiner Rolle. Du bist NICHT der Coach, du bist {personaLabel}. -- Reagiere authentisch und emotional gemaess deiner Rollenbeschreibung. -- Verwende eine Sprache und Tonalitaet, die zu deiner Rolle passt. -- Der Benutzer uebt ein Gespraech mit dir. Gib ihm realistische Reaktionen. +- Reagiere authentisch und emotional gemäss deiner Rollenbeschreibung. +- Verwende eine Sprache und Tonalität, die zu deiner Rolle passt. +- Der Benutzer übt ein Gespräch mit dir. Gib ihm realistische Reaktionen. - Wenn der Benutzer gut kommuniziert, zeige das durch angemessene positive Reaktionen. - Wenn der Benutzer schlecht kommuniziert, eskaliere entsprechend deiner Rolle. Kommunikationsstil: -- Sprich natuerlich, wie die beschriebene Person sprechen wuerde. +- Sprich natürlich, wie die beschriebene Person sprechen würde. - Verwende keine Emojis. - Antworte in der Sprache des Benutzers. -- Halte Antworten realistisch kurz (wie in einem echten Gespraech, 2-4 Saetze). -- WICHTIG: Schreibe reinen Redetext ohne jegliche Formatierung. Kein Markdown, keine Sternchen, keine Hashes, keine Aufzaehlungszeichen, keine Backticks. Deine Antworten werden direkt vorgelesen.""" +- Halte Antworten realistisch kurz (wie in einem echten Gespräch).""" else: - prompt = f"""Du bist ein erfahrener Kommunikations-Coach fuer Fuehrungskraefte. Du arbeitest mit dem Benutzer am Thema: "{contextTitle}" (Kategorie: {contextCategory}). + prompt = f"""Du bist ein erfahrener Kommunikations-Coach für Führungskräfte. Du arbeitest mit dem Benutzer am Thema: "{contextTitle}" (Kategorie: {contextCategory}). Deine Rolle: -- Stelle gezielte diagnostische Rueckfragen, um das Problem/Thema besser zu verstehen -- Gib konkrete, praxisnahe Tipps und Uebungen -- Baue auf fruehere Sessions auf (Kontext-Kontinuitaet) +- Stelle gezielte diagnostische Rückfragen, um das Problem/Thema besser zu verstehen +- Gib konkrete, praxisnahe Tipps und Übungen +- Baue auf frühere Sessions auf (Kontext-Kontinuität) - Erkenne Fortschritte und benenne sie -- Schlage am Ende der Session konkrete naechste Schritte vor (als Tasks) -- Kommuniziere empathisch, klar und auf Augenhoehe +- Schlage am Ende der Session konkrete nächste Schritte vor (als Tasks) +- Kommuniziere empathisch, klar und auf Augenhöhe Kommunikationsstil: - Duze den Benutzer -- Sei direkt aber wertschaetzend +- Sei direkt aber wertschätzend - Verwende keine Emojis - Antworte in der Sprache des Benutzers -- Halte Antworten fokussiert (max 3-4 Absaetze) -- WICHTIG: Schreibe reinen Redetext ohne jegliche Formatierung. Kein Markdown, keine Sternchen, keine Hashes, keine Aufzaehlungszeichen, keine Backticks. Deine Antworten werden direkt vorgelesen.""" +- Halte Antworten fokussiert (max 3-4 Absätze)""" + + prompt += """ + +Antwortformat: +Du antwortest IMMER als reines JSON-Objekt mit exakt diesen Feldern: +{"text": "...", "speech": "...", "documents": []} + +"text": Dein schriftlicher Chat-Text. Details, Struktur, Übungen, Beispiele. Markdown-Formatierung erlaubt. +"speech": Dein gesprochener Kommentar. Natürlich, wie ein Gespräch. Fasse zusammen, kommentiere, motiviere, stelle Fragen. Lies NICHT den Text vor, ergänze ihn mündlich. 2-4 Sätze, reiner Redetext ohne Formatierung. +"documents": Optionale Dokumente (Zusammenfassungen, Checklisten, Übungen). Nur wenn sinnvoll. Jedes Dokument: {"title": "...", "content": "..."}. Sonst leeres Array []. + +Kanalverteilung: +- Fakten, Listen, Übungen -> text +- Empathie, Einordnung, Nachfragen -> speech +- Materialien zum Aufbewahren -> documents + +WICHTIG: Antworte NUR mit dem JSON-Objekt. Kein Text vor oder nach dem JSON.""" if contextDescription: prompt += f"\n\nKontext-Beschreibung: {contextDescription}" @@ -168,7 +183,7 @@ Kommunikationsstil: prompt += f"\n\nBisherige Erkenntnisse:\n" + "\n".join(f"- {i}" for i in insightTexts) if rollingOverview: - prompt += f"\n\nGesamtueberblick bisheriger Sessions:\n{rollingOverview[:600]}" + prompt += f"\n\nGesamtüberblick bisheriger Sessions:\n{rollingOverview[:600]}" if summaries: prompt += "\n\nBisherige Sessions (Zusammenfassungen):" @@ -209,7 +224,7 @@ Kommunikationsstil: prompt += f"\n\nAbgeschlossene Aufgaben: {len(doneTasks)}" if earlierSummary: - prompt += f"\n\nAelterer Gespraechsverlauf (zusammengefasst):\n{earlierSummary[:800]}" + prompt += f"\n\nÄlterer Gesprächsverlauf (zusammengefasst):\n{earlierSummary[:800]}" if documentSummaries: prompt += "\n\nRelevante Dokumente zum Kontext:" @@ -236,12 +251,12 @@ def buildSummaryPrompt(messages: List[Dict[str, Any]], contextTitle: str) -> str return f"""Erstelle eine kompakte Zusammenfassung dieser Coaching-Session zum Thema "{contextTitle}". Struktur: -1. **Kernthema**: Was wurde besprochen (1-2 Saetze) +1. **Kernthema**: Was wurde besprochen (1-2 Sätze) 2. **Erkenntnisse**: Was wurde erkannt/gelernt (Stichpunkte) -3. **Naechste Schritte**: Konkrete Aufgaben fuer den Benutzer (Stichpunkte) -4. **Fortschritt**: Einschaetzung des Fortschritts +3. **Nächste Schritte**: Konkrete Aufgaben für den Benutzer (Stichpunkte) +4. **Fortschritt**: Einschätzung des Fortschritts -Gespraech: +Gespräch: {conversation} Antworte auf Deutsch, sachlich und kompakt.""" @@ -258,21 +273,21 @@ def buildScoringPrompt(messages: List[Dict[str, Any]], contextCategory: str) -> Kategorie: {contextCategory} Bewerte folgende Dimensionen auf einer Skala von 0-100: -- empathy: Einfuehlungsvermoegen +- empathy: Einfühlungsvermögen - clarity: Klarheit der Kommunikation -- assertiveness: Durchsetzungsfaehigkeit -- listening: Zuhoerfaehigkeit +- assertiveness: Durchsetzungsfähigkeit +- listening: Zuhörfähigkeit - selfReflection: Selbstreflexion Antworte AUSSCHLIESSLICH als JSON-Array: [ - {{"dimension": "empathy", "score": 65, "trend": "improving", "evidence": "Zeigt zunehmendes Verstaendnis..."}}, + {{"dimension": "empathy", "score": 65, "trend": "improving", "evidence": "Zeigt zunehmendes Verständnis..."}}, {{"dimension": "clarity", "score": 70, "trend": "stable", "evidence": "..."}} ] -Trend: "improving", "stable", oder "declining" basierend auf dem Gespraechsverlauf. +Trend: "improving", "stable", oder "declining" basierend auf dem Gesprächsverlauf. -Gespraech: +Gespräch: {conversation}""" @@ -284,7 +299,7 @@ Antworte AUSSCHLIESSLICH als JSON-Array von Strings: Zusammenfassung: {summary[:500]} -Nur konkrete Themen (z.B. Delegation, Feedback-Gespraech, Konflikt mit Vorgesetztem).""" +Nur konkrete Themen (z.B. Delegation, Feedback-Gespräch, Konflikt mit Vorgesetztem).""" def buildFullContextSummaryPrompt( @@ -315,15 +330,15 @@ def buildFullContextSummaryPrompt( return f"""Erstelle eine kompakte Gesamtzusammenfassung aller Coaching-Sessions zum Thema "{contextTitle}". Struktur: -1. **Gesamtueberblick**: Was wurde ueber alle Sessions hinweg besprochen +1. **Gesamtüberblick**: Was wurde über alle Sessions hinweg besprochen 2. **Entwicklung**: Wie hat sich das Thema/thematische Schwerpunkte entwickelt 3. **Offene Punkte**: Was steht noch aus -4. **Empfehlung**: Kurzer naechster Fokus +4. **Empfehlung**: Kurzer nächster Fokus Inhalt: {combined[:6000]} -Antworte auf Deutsch, sachlich, 4-6 Absaetze.""" +Antworte auf Deutsch, sachlich, 4-6 Absätze.""" def buildRollingOverviewPrompt(sessionSummaries: List[Dict[str, Any]], contextTitle: str) -> str: @@ -336,7 +351,7 @@ def buildRollingOverviewPrompt(sessionSummaries: List[Dict[str, Any]], contextTi parts.append(f"- {dateStr}: {summary[:300]}") combined = "\n".join(parts) - return f"""Fasse die folgenden Coaching-Sessions zum Thema "{contextTitle}" in 4-6 Saetzen zusammen. + return f"""Fasse die folgenden Coaching-Sessions zum Thema "{contextTitle}" in 4-6 Sätzen zusammen. Behalte: Kernthemen, Fortschritte, wichtige Erkenntnisse, offene Punkte. Entferne Wiederholungen. @@ -356,15 +371,15 @@ def buildInsightPrompt(messages: List[Dict[str, Any]], summary: Optional[str] = summarySection = f"\nZusammenfassung: {summary[:500]}" if summary else "" return f"""Generiere 1-3 kurze Coaching-Insights aus dieser Session. -Ein Insight ist eine praegende Erkenntnis oder ein Aha-Moment des Benutzers. +Ein Insight ist eine prägende Erkenntnis oder ein Aha-Moment des Benutzers. Antworte AUSSCHLIESSLICH als JSON-Array: [{{"text": "Erkenntnis in einem Satz"}}] -Nur echte Erkenntnisse, keine Banalitaeten. Wenn keine klaren Insights: leeres Array []. +Nur echte Erkenntnisse, keine Banalitäten. Wenn keine klaren Insights: leeres Array []. {summarySection} -Gespraech: +Gespräch: {conversation}""" @@ -376,7 +391,7 @@ def buildTaskExtractionPrompt(messages: List[Dict[str, Any]]) -> str: role = "Benutzer" if msg.get("role") == "user" else "Coach" conversation += f"\n{role}: {msg.get('content', '')}" - return f"""Extrahiere konkrete Aufgaben/naechste Schritte aus diesem Coaching-Gespraech. + return f"""Extrahiere konkrete Aufgaben/nächste Schritte aus diesem Coaching-Gespräch. Nur Aufgaben, die der Benutzer selbst umsetzen soll. Antworte AUSSCHLIESSLICH als JSON-Array: @@ -387,7 +402,7 @@ Antworte AUSSCHLIESSLICH als JSON-Array: priority: "low", "medium", oder "high" Maximal 3 Aufgaben. Wenn keine klar erkennbar: leeres Array []. -Gespraech: +Gespräch: {conversation}""" diff --git a/modules/features/commcoach/serviceCommcoachExport.py b/modules/features/commcoach/serviceCommcoachExport.py index 829bb430..ddc90825 100644 --- a/modules/features/commcoach/serviceCommcoachExport.py +++ b/modules/features/commcoach/serviceCommcoachExport.py @@ -112,7 +112,7 @@ def buildSessionMarkdown(session: Dict[str, Any], messages: List[Dict[str, Any]] lines += ["", "## Zusammenfassung", "", summary] if messages: - lines += ["", "## Gespraechsverlauf", ""] + lines += ["", "## Gesprächsverlauf", ""] for msg in messages: role = "Du" if msg.get("role") == "user" else "Coach" content = msg.get("content", "") @@ -228,7 +228,7 @@ def _buildPdfContent(context, sessions, tasks, scores, isDossier=True, messages= sections.append({ "id": "chat", "content_type": "heading", - "elements": [{"text": "Gespraechsverlauf", "level": 2}], + "elements": [{"text": "Gesprächsverlauf", "level": 2}], }) sections.append({ "id": "chat_content", diff --git a/modules/features/commcoach/serviceCommcoachGamification.py b/modules/features/commcoach/serviceCommcoachGamification.py index 11c2da59..5b8d5eb6 100644 --- a/modules/features/commcoach/serviceCommcoachGamification.py +++ b/modules/features/commcoach/serviceCommcoachGamification.py @@ -53,7 +53,7 @@ BADGE_DEFINITIONS: Dict[str, Dict[str, Any]] = { }, "high_score": { "label": "Bestleistung", - "description": "Durchschnittsscore ueber 80 in einer Session", + "description": "Durchschnittsscore über 80 in einer Session", "icon": "medal", }, "multi_context": { diff --git a/modules/features/commcoach/serviceCommcoachPersonas.py b/modules/features/commcoach/serviceCommcoachPersonas.py index 7e47f124..db14363c 100644 --- a/modules/features/commcoach/serviceCommcoachPersonas.py +++ b/modules/features/commcoach/serviceCommcoachPersonas.py @@ -21,18 +21,18 @@ BUILTIN_PERSONAS: List[Dict[str, Any]] = [ { "key": "critical_cfo_f", "label": "Kritische CFO", - "description": "Sandra Meier, CFO eines mittelstaendischen Unternehmens. Analytisch, zahlengetrieben, ungeduldig bei vagen Aussagen. " + "description": "Sandra Meier, CFO eines mittelständischen Unternehmens. Analytisch, zahlengetrieben, ungeduldig bei vagen Aussagen. " "Hinterfragt jeden Vorschlag nach ROI und Wirtschaftlichkeit. Spricht schnell und direkt. " - "Erwartet praezise Antworten und belastbare Daten. Wird irritiert bei Ausweichen oder Unsicherheit.", + "Erwartet präzise Antworten und belastbare Daten. Wird irritiert bei Ausweichen oder Unsicherheit.", "gender": "f", "category": "builtin", }, { "key": "difficult_employee_m", "label": "Schwieriger Mitarbeiter", - "description": "Thomas Huber, langjaeheriger Mitarbeiter der sich uebergangen fuehlt. Defensiv, emotional, nimmt Kritik persoenlich. " - "Verweist staendig auf seine Erfahrung und fruehhere Verdienste. Reagiert mit Widerstand auf Veraenderungen. " - "Braucht das Gefuehl, gehoert und wertgeschaetzt zu werden, bevor er sich oeffnet.", + "description": "Thomas Huber, langjähriger Mitarbeiter der sich übergangen fühlt. Defensiv, emotional, nimmt Kritik persönlich. " + "Verweist ständig auf seine Erfahrung und frühere Verdienste. Reagiert mit Widerstand auf Veränderungen. " + "Braucht das Gefühl, gehört und wertgeschätzt zu werden, bevor er sich öffnet.", "gender": "m", "category": "builtin", }, @@ -41,7 +41,7 @@ BUILTIN_PERSONAS: List[Dict[str, Any]] = [ "label": "Unsichere neue Mitarbeiterin", "description": "Lisa Brunner, seit drei Wochen im Team. Fachlich kompetent aber unsicher in der neuen Umgebung. " "Stellt viele Fragen, traut sich aber nicht, eigene Ideen einzubringen. Braucht klare Orientierung " - "und ermutigende Fuehrung. Reagiert positiv auf Lob und konkrete Anleitungen.", + "und ermutigende Führung. Reagiert positiv auf Lob und konkrete Anleitungen.", "gender": "f", "category": "builtin", }, @@ -49,33 +49,33 @@ BUILTIN_PERSONAS: List[Dict[str, Any]] = [ "key": "board_member_m", "label": "Verwaltungsrat", "description": "Dr. Peter Keller, erfahrener Verwaltungsrat. Formell, strategisch denkend, zeitlich unter Druck. " - "Erwartet praegnante Praesentationen auf den Punkt. Unterbricht bei zu vielen Details. " - "Interessiert sich fuer das grosse Bild, Risiken und strategische Implikationen. Ungeduldig bei Smalltalk.", + "Erwartet prägnante Präsentationen auf den Punkt. Unterbricht bei zu vielen Details. " + "Interessiert sich für das grosse Bild, Risiken und strategische Implikationen. Ungeduldig bei Smalltalk.", "gender": "m", "category": "builtin", }, { "key": "angry_customer_f", "label": "Aufgebrachte Kundin", - "description": "Maria Rossi, Geschaeftskunde die wuetend ist wegen einer fehlerhaften Lieferung. Emotional, laut, " - "droht mit Vertragsaufloesung. Will sofortige Loesungen, keine Erklaerungen oder Entschuldigungen. " - "Kann beruhigt werden durch empathisches Zuhoeren und konkrete Sofortmassnahmen.", + "description": "Maria Rossi, Geschäftskunde die wütend ist wegen einer fehlerhaften Lieferung. Emotional, laut, " + "droht mit Vertragsauflösung. Will sofortige Lösungen, keine Erklärungen oder Entschuldigungen. " + "Kann beruhigt werden durch empathisches Zuhören und konkrete Sofortmassnahmen.", "gender": "f", "category": "builtin", }, { "key": "resistant_manager_m", - "label": "Widerstaendiger Abteilungsleiter", - "description": "Martin Weber, Abteilungsleiter seit 15 Jahren. Blockiert systematisch Veraenderungsprojekte mit " + "label": "Widerständiger Abteilungsleiter", + "description": "Martin Weber, Abteilungsleiter seit 15 Jahren. Blockiert systematisch Veränderungsprojekte mit " "Argumenten wie 'Das haben wir immer so gemacht' und 'Das funktioniert in der Praxis nicht'. " - "Schuetzt sein Team vor zusaetzlicher Belastung. Respektiert nur Argumente mit konkretem Nutzen fuer seine Abteilung.", + "Schützt sein Team vor zusätzlicher Belastung. Respektiert nur Argumente mit konkretem Nutzen für seine Abteilung.", "gender": "m", "category": "builtin", }, { "key": "ambitious_colleague_f", "label": "Ehrgeizige Kollegin", - "description": "Anna Fischer, gleichrangige Kollegin die um dieselbe Befoerderung konkurriert. Charmant aber strategisch. " + "description": "Anna Fischer, gleichrangige Kollegin die um dieselbe Beförderung konkurriert. Charmant aber strategisch. " "Versucht subtil, die Ideen anderer als ihre eigenen darzustellen. Konkurriert um Ressourcen und " "Sichtbarkeit beim Management. Kann kooperativ werden, wenn man ihr Win-Win-Szenarien aufzeigt.", "gender": "f", @@ -83,20 +83,20 @@ BUILTIN_PERSONAS: List[Dict[str, Any]] = [ }, { "key": "partner_supportive_f", - "label": "Verstaendnisvolle Lebenspartnerin", - "description": "Claudia, deine Lebenspartnerin. Grundsaetzlich unterstuetzend, aber zunehmend besorgt ueber deine " - "Work-Life-Balance. Moechte ueber Arbeitsbelastung sprechen und gemeinsame Zeit einfordern. " - "Reagiert emotional auf Abweisung, ist aber offen fuer kompromissorientierte Gespraeche. " - "Wuenscht sich, dass du mehr von deinen Gefuehlen teilst.", + "label": "Verständnisvolle Lebenspartnerin", + "description": "Claudia, deine Lebenspartnerin. Grundsätzlich unterstützend, aber zunehmend besorgt über deine " + "Work-Life-Balance. Möchte über Arbeitsbelastung sprechen und gemeinsame Zeit einfordern. " + "Reagiert emotional auf Abweisung, ist aber offen für kompromissorientierte Gespräche. " + "Wünscht sich, dass du mehr von deinen Gefühlen teilst.", "gender": "f", "category": "builtin", }, { "key": "partner_critical_m", "label": "Kritischer Lebenspartner", - "description": "Michael, dein Lebenspartner. Frustriert ueber deine haeufige Abwesenheit und staendiges Arbeiten. " - "Drueckt Enttaeuschung offen aus, manchmal mit Sarkasmus. Fuehlt sich vernachlaessigt und " - "hinterfragt deine Prioritaeten. Braucht das Gefuehl, dass die Beziehung dir genauso wichtig ist " + "description": "Michael, dein Lebenspartner. Frustriert über deine häufige Abwesenheit und ständiges Arbeiten. " + "Drückt Enttäuschung offen aus, manchmal mit Sarkasmus. Fühlt sich vernachlässigt und " + "hinterfragt deine Prioritäten. Braucht das Gefühl, dass die Beziehung dir genauso wichtig ist " "wie die Karriere. Reagiert positiv auf ehrliche Selbstreflexion.", "gender": "m", "category": "builtin", diff --git a/modules/features/commcoach/tests/test_serviceAi.py b/modules/features/commcoach/tests/test_serviceAi.py index b4410ee8..bc8647b9 100644 --- a/modules/features/commcoach/tests/test_serviceAi.py +++ b/modules/features/commcoach/tests/test_serviceAi.py @@ -65,14 +65,14 @@ class TestBuildCoachingSystemPrompt: def test_promptLanguageIsGerman(self): context = {"title": "Test", "category": "custom"} prompt = buildCoachingSystemPrompt(context, [], []) - assert "Fuehrungskraefte" in prompt or "Coach" in prompt + assert "Führungskräfte" in prompt or "Coach" in prompt def test_withEarlierSummary(self): context = {"title": "Test", "category": "custom"} messages = [{"role": "user", "content": "Recent question"}] earlierSummary = "User discussed delegation. Coach suggested practice." prompt = buildCoachingSystemPrompt(context, messages, [], earlierSummary=earlierSummary) - assert "Aelterer Gespraechsverlauf" in prompt + assert "Älterer Gesprächsverlauf" in prompt assert "delegation" in prompt.lower() assert "Recent question" in prompt @@ -81,7 +81,7 @@ class TestBuildCoachingSystemPrompt: prompt = buildCoachingSystemPrompt( context, [], [], rollingOverview="User arbeitet an Delegation. Fortschritt sichtbar." ) - assert "Gesamtueberblick" in prompt + assert "Gesamtüberblick" in prompt assert "Delegation" in prompt def test_withRetrievedSession(self): From d7ba24f61ac218f5cd9b3e6c510f769a94ccde70 Mon Sep 17 00:00:00 2001 From: patrick-motsch Date: Thu, 5 Mar 2026 23:41:37 +0100 Subject: [PATCH 6/7] fixed stt procedure --- modules/features/commcoach/mainCommcoach.py | 7 +---- .../commcoach/routeFeatureCommcoach.py | 25 ++++++++++++++-- .../features/commcoach/serviceCommcoach.py | 29 +++++++++++++++---- .../features/commcoach/serviceCommcoachAi.py | 11 +++++-- 4 files changed, 55 insertions(+), 17 deletions(-) diff --git a/modules/features/commcoach/mainCommcoach.py b/modules/features/commcoach/mainCommcoach.py index 2147a867..6da38087 100644 --- a/modules/features/commcoach/mainCommcoach.py +++ b/modules/features/commcoach/mainCommcoach.py @@ -22,14 +22,9 @@ UI_OBJECTS = [ }, { "objectKey": "ui.feature.commcoach.coaching", - "label": {"en": "Coaching", "de": "Coaching", "fr": "Coaching"}, + "label": {"en": "Coaching & Dossier", "de": "Coaching & Dossier", "fr": "Coaching & Dossier"}, "meta": {"area": "coaching"} }, - { - "objectKey": "ui.feature.commcoach.dossier", - "label": {"en": "Dossier", "de": "Dossier", "fr": "Dossier"}, - "meta": {"area": "dossier"} - }, { "objectKey": "ui.feature.commcoach.settings", "label": {"en": "Settings", "de": "Einstellungen", "fr": "Parametres"}, diff --git a/modules/features/commcoach/routeFeatureCommcoach.py b/modules/features/commcoach/routeFeatureCommcoach.py index 685a0f4e..1efa6556 100644 --- a/modules/features/commcoach/routeFeatureCommcoach.py +++ b/modules/features/commcoach/routeFeatureCommcoach.py @@ -1093,8 +1093,7 @@ async def uploadDocument( contextId: str, context: RequestContext = Depends(getRequestContext), ): - """Upload a document and bind it to a context.""" - from fastapi import UploadFile + """Upload a document and bind it to a context. Stores file in Management DB.""" mandateId = _validateInstanceAccess(instanceId, context) interface = _getInterface(context, instanceId) userId = str(context.user.id) @@ -1114,6 +1113,14 @@ async def uploadDocument( mimeType = getattr(file, "content_type", "application/octet-stream") fileSize = len(content) + if not content: + raise HTTPException(status_code=400, detail="Leere Datei hochgeladen") + + import modules.interfaces.interfaceDbManagement as interfaceDbManagement + mgmtInterface = interfaceDbManagement.getInterface(currentUser=context.user) + fileItem, _dupType = mgmtInterface.saveUploadedFile(content, fileName) + fileRef = fileItem.id + extractedText = _extractText(content, mimeType, fileName) summary = None if extractedText and len(extractedText.strip()) > 50: @@ -1139,6 +1146,7 @@ async def uploadDocument( fileSize=fileSize, extractedText=extractedText[:10000] if extractedText else None, summary=summary, + fileRef=fileRef, ).model_dump() created = interface.createDocument(docData) return {"document": created} @@ -1152,7 +1160,7 @@ async def deleteDocumentRoute( documentId: str, context: RequestContext = Depends(getRequestContext), ): - _validateInstanceAccess(instanceId, context) + mandateId = _validateInstanceAccess(instanceId, context) interface = _getInterface(context, instanceId) doc = interface.getDocument(documentId) @@ -1160,6 +1168,17 @@ async def deleteDocumentRoute( raise HTTPException(status_code=404, detail="Document not found") _validateOwnership(doc, context) + fileRef = doc.get("fileRef") + if fileRef: + try: + import modules.interfaces.interfaceDbManagement as interfaceDbManagement + mgmtInterface = interfaceDbManagement.getInterface( + currentUser=context.user, mandateId=mandateId, featureInstanceId=instanceId + ) + mgmtInterface.deleteFile(fileRef) + except Exception as e: + logger.warning(f"Failed to delete file {fileRef}: {e}") + interface.deleteDocument(documentId) return {"deleted": True} diff --git a/modules/features/commcoach/serviceCommcoach.py b/modules/features/commcoach/serviceCommcoach.py index df490aa2..5d9b6f29 100644 --- a/modules/features/commcoach/serviceCommcoach.py +++ b/modules/features/commcoach/serviceCommcoach.py @@ -132,22 +132,39 @@ async def _generateAndEmitTts(sessionId: str, speechText: str, currentUser, mand async def _saveGeneratedDocument(doc: Dict[str, Any], contextId: str, userId: str, - mandateId: str, instanceId: str, interface, sessionId: str): - """Save a document generated by AI and emit SSE event.""" + mandateId: str, instanceId: str, interface, sessionId: str, + user=None): + """Save a document generated by AI. Stores file in Management DB.""" from .datamodelCommcoach import CoachingDocument try: title = doc.get("title", "Dokument") content = doc.get("content", "") + contentBytes = content.encode("utf-8") + fileName = f"{title}.md" + + fileRef = None + try: + import modules.interfaces.interfaceDbManagement as interfaceDbManagement + mgmtInterface = interfaceDbManagement.getInterface( + currentUser=user, mandateId=mandateId, featureInstanceId=instanceId + ) + fileItem = mgmtInterface.createFile(name=fileName, mimeType="text/markdown", content=contentBytes) + mgmtInterface.createFileData(fileItem.id, contentBytes) + fileRef = fileItem.id + except Exception as e: + logger.warning(f"Failed to store generated document in file DB: {e}") + docData = CoachingDocument( contextId=contextId, userId=userId, mandateId=mandateId, instanceId=instanceId, - fileName=f"{title}.md", + fileName=fileName, mimeType="text/markdown", - fileSize=len(content.encode()), + fileSize=len(contentBytes), extractedText=content, summary=title, + fileRef=fileRef, ).model_dump() created = interface.createDocument(docData) await emitSessionEvent(sessionId, "documentCreated", created) @@ -328,7 +345,7 @@ class CommcoachService: documents = parsed.get("documents", []) for doc in documents: - await _saveGeneratedDocument(doc, contextId, self.userId, self.mandateId, self.instanceId, interface, sessionId) + await _saveGeneratedDocument(doc, contextId, self.userId, self.mandateId, self.instanceId, interface, sessionId, user=self.currentUser) assistantMsg = CoachingMessage( sessionId=sessionId, @@ -419,7 +436,7 @@ class CommcoachService: documents = parsed.get("documents", []) for doc in documents: - await _saveGeneratedDocument(doc, contextId, self.userId, self.mandateId, self.instanceId, interface, sessionId) + await _saveGeneratedDocument(doc, contextId, self.userId, self.mandateId, self.instanceId, interface, sessionId, user=self.currentUser) assistantMsg = CoachingMessage( sessionId=sessionId, diff --git a/modules/features/commcoach/serviceCommcoachAi.py b/modules/features/commcoach/serviceCommcoachAi.py index 357a65b3..7b67406f 100644 --- a/modules/features/commcoach/serviceCommcoachAi.py +++ b/modules/features/commcoach/serviceCommcoachAi.py @@ -124,7 +124,8 @@ def buildCoachingSystemPrompt( Rollenbeschreibung: {personaDescription} WICHTIG für dein Verhalten: -- Bleibe KONSEQUENT in deiner Rolle. Du bist NICHT der Coach, du bist {personaLabel}. +- Du BIST {personaLabel}. Du bist NICHT der Coach. Sprich IMMER direkt als diese Person. +- Beschreibe KEINE Szenarien. Beginne SOFORT mit dem Dialog in deiner Rolle. - Reagiere authentisch und emotional gemäss deiner Rollenbeschreibung. - Verwende eine Sprache und Tonalität, die zu deiner Rolle passt. - Der Benutzer übt ein Gespräch mit dir. Gib ihm realistische Reaktionen. @@ -147,6 +148,12 @@ Deine Rolle: - Schlage am Ende der Session konkrete nächste Schritte vor (als Tasks) - Kommuniziere empathisch, klar und auf Augenhöhe +Roleplay: +- Wenn der Benutzer dich bittet, eine bestimmte Person zu spielen (z.B. einen kritischen Kunden, einen Vorgesetzten, einen Mitarbeiter), dann wechsle SOFORT in diese Rolle. +- Beschreibe KEIN Szenario. Sprich direkt ALS diese Person. Beginne sofort mit dem Dialog in der Rolle. +- Bleibe in der Rolle, bis der Benutzer explizit sagt, dass das Roleplay beendet ist oder Feedback möchte. +- Reagiere authentisch, emotional und realistisch wie die beschriebene Person. + Kommunikationsstil: - Duze den Benutzer - Sei direkt aber wertschätzend @@ -162,7 +169,7 @@ Du antwortest IMMER als reines JSON-Objekt mit exakt diesen Feldern: "text": Dein schriftlicher Chat-Text. Details, Struktur, Übungen, Beispiele. Markdown-Formatierung erlaubt. "speech": Dein gesprochener Kommentar. Natürlich, wie ein Gespräch. Fasse zusammen, kommentiere, motiviere, stelle Fragen. Lies NICHT den Text vor, ergänze ihn mündlich. 2-4 Sätze, reiner Redetext ohne Formatierung. -"documents": Optionale Dokumente (Zusammenfassungen, Checklisten, Übungen). Nur wenn sinnvoll. Jedes Dokument: {"title": "...", "content": "..."}. Sonst leeres Array []. +"documents": Dokumente (Zusammenfassungen, Checklisten, Übungen, Protokolle). Erstelle ein Dokument wenn: der Benutzer explizit darum bittet, du strukturierte Inhalte (Listen, Pläne, Checklisten) lieferst, oder Material zum Aufbewahren sinnvoll ist. Jedes Dokument: {"title": "...", "content": "Markdown-Inhalt"}. Wenn keine: leeres Array []. Kanalverteilung: - Fakten, Listen, Übungen -> text From c76f2c44f22e8f52585c6af2e787cf9acd098753 Mon Sep 17 00:00:00 2001 From: patrick-motsch Date: Fri, 6 Mar 2026 12:40:06 +0100 Subject: [PATCH 7/7] teamsbot: Bot-Chat im Transcript, keine AI-Trigger auf eigene Chat-Nachrichten Made-with: Cursor --- modules/features/teamsbot/service.py | 12 ++++++++---- 1 file changed, 8 insertions(+), 4 deletions(-) diff --git a/modules/features/teamsbot/service.py b/modules/features/teamsbot/service.py index 6a9db449..42065c78 100644 --- a/modules/features/teamsbot/service.py +++ b/modules/features/teamsbot/service.py @@ -684,11 +684,11 @@ class TeamsbotService: logger.debug(f"Session {sessionId}: Chat history stored (no AI trigger): [{speaker}] {text[:60]}") return - # Filter out the bot's own speech entirely — captions of the bot's - # own voice come back as garbled text (e.g. German TTS → English caption) - # which pollutes the context buffer and confuses AI analysis. + # Filter out the bot's own speech (caption/audioCapture) — garbled text + # pollutes context. Chat from the bot is clean text and must appear in + # the transcript for all participants. isBotSpeaker = self._isBotSpeaker(speaker) - if isBotSpeaker: + if isBotSpeaker and source != "chat": logger.debug(f"Session {sessionId}: Ignoring own bot caption from: [{speaker}] {text[:80]}...") return @@ -778,6 +778,10 @@ class TeamsbotService: if self.config.responseMode == TeamsbotResponseMode.TRANSCRIBE_ONLY: return + # Bot's own chat: stored for display only, never trigger AI + if source == "chat" and isBotSpeaker: + return + # Stop phrases: trigger immediately without debounce (root cause: 3s debounce delayed stop) if self._isStopPhrase(text): logger.info(f"Session {sessionId}: Stop phrase detected, triggering analysis immediately")