refactored workflow engine
This commit is contained in:
ValueOn AG
parent
1a8cecc50a
commit
9b8510bfd0
31 changed files with 1559 additions and 1575 deletions
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@ -1053,7 +1053,7 @@ class MethodOutlook(MethodBase):
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Parameters:
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connectionReference (str): REQUIRED - Reference to the Microsoft connection (must be a connection label from AVAILABLE_CONNECTIONS list)
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to (str): REQUIRED - Email recipient address
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to (List[str]): REQUIRED - Email recipient addresses
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subject (str): REQUIRED - Email subject line
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body (str): REQUIRED - Email body content
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cc (List[str], optional): CC recipients
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@ -1072,7 +1072,9 @@ class MethodOutlook(MethodBase):
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if not connectionReference or not to or not subject or not body:
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return ActionResult.isFailure(error="connectionReference, to, subject, and body are required")
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# Convert single values to lists
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# Convert single values to lists for all recipient parameters
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if isinstance(to, str):
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to = [to]
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if isinstance(cc, str):
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cc = [cc]
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if isinstance(bcc, str):
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@ -1215,7 +1217,7 @@ class MethodOutlook(MethodBase):
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Parameters:
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connectionReference (str): REQUIRED - Reference to the Microsoft connection (must be a connection label from AVAILABLE_CONNECTIONS list)
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to (str): REQUIRED - Email recipient address
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to (List[str]): REQUIRED - Email recipient addresses
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context (str): REQUIRED - Context information for email composition
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documentList (List[str], optional): Document references to include as context and attachments
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cc (List[str], optional): CC recipients
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@ -1236,7 +1238,9 @@ class MethodOutlook(MethodBase):
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if not connectionReference or not to or not context:
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return ActionResult.isFailure(error="connectionReference, to, and context are required")
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# Convert single values to lists
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# Convert single values to lists for all recipient parameters
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if isinstance(to, str):
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to = [to]
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if isinstance(cc, str):
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cc = [cc]
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if isinstance(bcc, str):
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@ -5,7 +5,7 @@ import logging
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from typing import Dict, Any, List
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from modules.datamodels.datamodelWorkflow import ActionResult, TaskAction, TaskStep
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from modules.datamodels.datamodelChat import ChatWorkflow
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from modules.workflows.processing.shared.promptFactory import methods
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from modules.workflows.processing.shared.methodDiscovery import methods
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logger = logging.getLogger(__name__)
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@ -6,11 +6,11 @@ import logging
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from typing import Dict, Any
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from modules.datamodels.datamodelWorkflow import TaskStep, TaskContext, TaskPlan
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from modules.datamodels.datamodelAi import AiCallOptions, OperationType, ProcessingMode, Priority
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from modules.workflows.processing.shared.promptFactoryPlaceholders import (
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createTaskPlanningPromptTemplate,
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extractUserPrompt,
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extractAvailableDocuments,
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extractWorkflowHistory
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from modules.workflows.processing.shared.promptGenerationTaskplan import (
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createTaskPlanningPromptTemplate
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)
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from modules.workflows.processing.shared.placeholderFactory import (
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extractUserPrompt
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)
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logger = logging.getLogger(__name__)
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@ -1,4 +1,4 @@
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# actionplanMode.py
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# modeActionplan.py
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# Actionplan mode implementation for workflows
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import json
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@ -11,16 +11,19 @@ from modules.datamodels.datamodelWorkflow import (
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)
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from modules.datamodels.datamodelChat import ChatWorkflow
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from modules.datamodels.datamodelAi import AiCallOptions, OperationType, ProcessingMode, Priority
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from modules.workflows.processing.modes.baseMode import BaseMode
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from modules.workflows.processing.modes.modeBase import BaseMode
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from modules.workflows.processing.shared.executionState import TaskExecutionState
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from modules.workflows.processing.shared.promptFactoryPlaceholders import (
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from modules.workflows.processing.shared.promptGenerationActionsActionplan import (
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createActionDefinitionPromptTemplate,
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createResultReviewPromptTemplate,
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createResultReviewPromptTemplate
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)
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from modules.workflows.processing.shared.placeholderFactory import (
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extractUserPrompt,
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extractAvailableDocuments,
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extractWorkflowHistory,
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extractAvailableMethods,
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extractUserLanguage,
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extractAvailableConnections,
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extractReviewContent
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)
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@ -135,8 +138,7 @@ class ActionplanMode(BaseMode):
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availableMethods = extractAvailableMethods(self.services)
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userLanguage = extractUserLanguage(self.services)
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# Action planner also needs connections for parameter generation (like old system)
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availableConnections = self.services.workflow.getConnectionReferenceList()
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availableConnectionsStr = '\n'.join(f"- {conn}" for conn in availableConnections) if availableConnections else "No connections available"
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availableConnectionsStr = extractAvailableConnections(self.services)
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# Create placeholders dictionary
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placeholders = {
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@ -1,4 +1,4 @@
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# baseMode.py
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# modeBase.py
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# Abstract base class for workflow modes
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from abc import ABC, abstractmethod
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@ -1,4 +1,4 @@
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# reactMode.py
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# modeReact.py
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# React mode implementation for workflows
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import json
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@ -13,13 +13,13 @@ from modules.datamodels.datamodelWorkflow import (
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)
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from modules.datamodels.datamodelChat import ChatWorkflow
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from modules.datamodels.datamodelAi import AiCallOptions, OperationType, ProcessingMode, Priority
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from modules.workflows.processing.modes.baseMode import BaseMode
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from modules.workflows.processing.shared.executionState import TaskExecutionState, should_continue
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from modules.workflows.processing.shared.contextAwarePlaceholders import (
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from modules.workflows.processing.modes.modeBase import BaseMode
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from modules.workflows.processing.shared.executionState import TaskExecutionState, shouldContinue
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from modules.workflows.processing.shared.placeholderFactoryReactOnly import (
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ContextAwarePlaceholders,
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WorkflowPhase
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)
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from modules.workflows.processing.shared.reactPromptTemplates import (
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from modules.workflows.processing.shared.promptGenerationActionsReact import (
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createReactPlanSelectionPromptTemplate,
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createReactParametersPromptTemplate,
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createReactRefinementPromptTemplate
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@ -150,8 +150,8 @@ class ReactMode(BaseMode):
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progressState = self.progressTracker.getCurrentProgress()
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shouldContinue = self.progressTracker.shouldContinue(progressState, observation.get('contentValidation', {}))
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if not shouldContinue or not should_continue(observation, lastReviewDict, step, state.max_steps):
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logger.info(f"Stopping at step {step}: shouldContinue={shouldContinue}, should_continue={should_continue(observation, lastReviewDict, step, state.max_steps)}")
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if not shouldContinue or not shouldContinue(observation, lastReviewDict, step, state.max_steps):
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logger.info(f"Stopping at step {step}: shouldContinue={shouldContinue}, shouldContinue={shouldContinue(observation, lastReviewDict, step, state.max_steps)}")
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break
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step += 1
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@ -233,25 +233,8 @@ class ReactMode(BaseMode):
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promptTemplate = createReactParametersPromptTemplate()
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# Get action parameter description (not function signature)
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actionParameters = ""
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from modules.workflows.processing.shared.promptFactory import methods
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if self.services and methodName in methods:
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methodInstance = methods[methodName]['instance']
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if actionName in methodInstance.actions:
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action_info = methodInstance.actions[actionName]
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# Extract parameter descriptions from docstring
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docstring = action_info.get('description', '')
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paramDescriptions, paramTypes = methodInstance._extractParameterDetails(docstring)
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param_list = []
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for paramName, paramDesc in paramDescriptions.items():
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paramType = paramTypes.get(paramName, 'Any')
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if paramDesc:
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param_list.append(f"- {paramName} ({paramType}): {paramDesc}")
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else:
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param_list.append(f"- {paramName} ({paramType})")
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actionParameters = "Required parameters:\n" + "\n".join(param_list)
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from modules.workflows.processing.shared.methodDiscovery import methods, getActionParameterSignature
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actionParameters = getActionParameterSignature(methodName, actionName, methods)
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selectedAction = compoundActionName
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@ -1,397 +0,0 @@
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"""
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Context-aware placeholder service for different workflow phases.
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This module provides different levels of context based on the workflow phase.
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"""
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import json
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import logging
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from typing import Dict, Any, Optional
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from enum import Enum
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logger = logging.getLogger(__name__)
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class WorkflowPhase(Enum):
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"""Different phases of workflow execution requiring different context levels."""
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TASK_PLANNING = "task_planning" # Needs full context for planning
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REACT_PLAN_SELECTION = "react_plan_selection" # Needs minimal context for action selection
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REACT_PARAMETERS = "react_parameters" # Needs full context for parameter generation
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ACTION_PLANNING = "action_planning" # Needs full context for action planning
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RESULT_REVIEW = "result_review" # Needs full context for review
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class ContextAwarePlaceholders:
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"""Context-aware placeholder service that provides different context levels based on workflow phase."""
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def __init__(self, services):
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self.services = services
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async def getPlaceholders(self, phase: WorkflowPhase, context: Any, additional_data: Dict[str, Any] = None) -> Dict[str, str]:
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"""
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Get placeholders based on workflow phase and context.
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Args:
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phase: The workflow phase determining context level
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context: The workflow context object
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additional_data: Additional data for specific phases (e.g., selected action)
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Returns:
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Dictionary of placeholder key-value pairs
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"""
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if phase == WorkflowPhase.TASK_PLANNING:
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return self._getTaskPlanningPlaceholders(context)
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elif phase == WorkflowPhase.REACT_PLAN_SELECTION:
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return self._getReactPlanSelectionPlaceholders(context)
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elif phase == WorkflowPhase.REACT_PARAMETERS:
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return await self._getReactParametersPlaceholders(context, additional_data)
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elif phase == WorkflowPhase.ACTION_PLANNING:
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return self._getActionPlanningPlaceholders(context)
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elif phase == WorkflowPhase.RESULT_REVIEW:
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return self._getResultReviewPlaceholders(context)
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else:
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logger.warning(f"Unknown workflow phase: {phase}")
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return self._getMinimalPlaceholders(context)
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def _getTaskPlanningPlaceholders(self, context: Any) -> Dict[str, str]:
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"""Get full context placeholders for task planning."""
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return {
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"USER_PROMPT": self._extractUserPrompt(context),
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"AVAILABLE_DOCUMENTS": self._getFullDocumentContext(context),
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"WORKFLOW_HISTORY": self._getWorkflowHistory(context),
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"USER_LANGUAGE": self._extractUserLanguage(),
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}
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def _getReactPlanSelectionPlaceholders(self, context: Any) -> Dict[str, str]:
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"""Get minimal context placeholders for React plan selection."""
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return {
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"USER_PROMPT": self._extractUserPrompt(context),
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"AVAILABLE_DOCUMENTS": self._getMinimalDocumentContext(context),
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"USER_LANGUAGE": self._extractUserLanguage(),
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"AVAILABLE_METHODS": self._getAvailableMethods(),
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"AVAILABLE_CONNECTIONS": self._getMinimalConnectionContext(),
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}
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async def _getReactParametersPlaceholders(self, context: Any, additional_data: Dict[str, Any] = None) -> Dict[str, str]:
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"""Get full context placeholders for React parameter generation."""
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# Get both original user prompt and current task objective
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original_prompt = self._extractUserPrompt(context)
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current_task = ""
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if hasattr(context, 'task_step') and context.task_step and context.task_step.objective:
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current_task = context.task_step.objective
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# Combine original prompt and current task for better context
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combined_prompt = f"Original request: {original_prompt}"
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if current_task and current_task != original_prompt:
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combined_prompt += f"\n\nCurrent task: {current_task}"
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# Generate intelligent action objective
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action_objective = await self._generateActionObjective(context, current_task, original_prompt, additional_data)
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placeholders = {
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"USER_PROMPT": combined_prompt,
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"ACTION_OBJECTIVE": action_objective, # AI-generated intelligent objective
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"AVAILABLE_DOCUMENTS": self._getFullDocumentContext(context),
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"USER_LANGUAGE": self._extractUserLanguage(),
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"AVAILABLE_CONNECTIONS": self._getFullConnectionContext(),
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"PREVIOUS_ACTION_RESULTS": self._getPreviousActionResults(context),
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"LEARNINGS_AND_IMPROVEMENTS": self._getLearningsAndImprovements(context),
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"LATEST_REFINEMENT_FEEDBACK": self._getLatestRefinementFeedback(context),
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}
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# Add additional data if provided (e.g., selected action, action signature)
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if additional_data:
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placeholders.update(additional_data)
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return placeholders
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def _getActionPlanningPlaceholders(self, context: Any) -> Dict[str, str]:
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"""Get full context placeholders for action planning."""
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return {
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"USER_PROMPT": self._extractUserPrompt(context),
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"AVAILABLE_DOCUMENTS": self._getFullDocumentContext(context),
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"WORKFLOW_HISTORY": self._getWorkflowHistory(context),
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"AVAILABLE_METHODS": self._getAvailableMethods(),
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"AVAILABLE_CONNECTIONS": self._getFullConnectionContext(),
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"USER_LANGUAGE": self._extractUserLanguage(),
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}
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def _getResultReviewPlaceholders(self, context: Any) -> Dict[str, str]:
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"""Get full context placeholders for result review."""
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return {
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"USER_PROMPT": self._extractUserPrompt(context),
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"REVIEW_CONTENT": self._getReviewContent(context),
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}
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def _getMinimalPlaceholders(self, context: Any) -> Dict[str, str]:
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"""Get minimal placeholders as fallback."""
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return {
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"USER_PROMPT": self._extractUserPrompt(context),
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"USER_LANGUAGE": self._extractUserLanguage(),
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}
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# Helper methods for extracting different context levels
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def _extractUserPrompt(self, context: Any) -> str:
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"""Extract user prompt from context."""
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# Get the current user prompt from services (clean and reliable)
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if self.services and hasattr(self.services, 'currentUserPrompt') and self.services.currentUserPrompt:
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return self.services.currentUserPrompt
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# Fallback to task step objective if no current prompt found
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if hasattr(context, 'task_step') and context.task_step:
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return context.task_step.objective or 'No request specified'
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return 'No request specified'
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def _extractUserLanguage(self) -> str:
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"""Extract user language from service."""
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return self.services.user.language if self.services and self.services.user else 'en'
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def _getMinimalDocumentContext(self, context: Any) -> str:
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"""Get minimal document context (counts only) for React plan selection."""
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try:
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if hasattr(context, 'workflow') and context.workflow:
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# Get document count from workflow
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documents = self.services.workflow.getAvailableDocuments(context.workflow)
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if documents and documents != "No documents available":
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# Count documents by counting docList and docItem references
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doc_count = documents.count("docList:") + documents.count("docItem:")
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return f"{doc_count} documents available from previous tasks"
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else:
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return "No documents available"
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return "No documents available"
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except Exception as e:
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logger.error(f"Error getting minimal document context: {str(e)}")
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return "No documents available"
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def _getFullDocumentContext(self, context: Any) -> str:
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"""Get full document context with detailed references for parameter generation."""
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try:
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if hasattr(context, 'workflow') and context.workflow:
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return self.services.workflow.getAvailableDocuments(context.workflow)
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return "No documents available"
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except Exception as e:
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logger.error(f"Error getting full document context: {str(e)}")
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return "No documents available"
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def _getMinimalConnectionContext(self) -> str:
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"""Get minimal connection context (count only) for React plan selection."""
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try:
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connections = self.services.workflow.getConnectionReferenceList()
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if connections:
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return f"{len(connections)} connections available"
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return "No connections available"
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except Exception as e:
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logger.error(f"Error getting minimal connection context: {str(e)}")
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return "No connections available"
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def _getFullConnectionContext(self) -> str:
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"""Get full connection context with detailed references for parameter generation."""
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try:
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connections = self.services.workflow.getConnectionReferenceList()
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if connections:
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return '\n'.join(f"- {conn}" for conn in connections)
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return "No connections available"
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except Exception as e:
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logger.error(f"Error getting full connection context: {str(e)}")
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return "No connections available"
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def _getWorkflowHistory(self, context: Any) -> str:
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"""Get workflow history for task planning."""
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try:
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if hasattr(context, 'workflow') and context.workflow:
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from modules.workflows.processing.shared.promptFactory import getPreviousRoundContext
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return getPreviousRoundContext(self.services, context.workflow) or "No previous workflow rounds - this is the first round."
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return "No previous workflow rounds - this is the first round."
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except Exception as e:
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logger.error(f"Error getting workflow history: {str(e)}")
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return "No previous workflow rounds - this is the first round."
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def _getAvailableMethods(self) -> str:
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"""Get available methods for action selection and planning using compound action names."""
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try:
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from modules.workflows.processing.shared.promptFactory import methods, discoverMethods
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# Get the methods dictionary
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if not methods:
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discoverMethods(self.services)
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# Create a flat JSON format with compound action names for better AI parsing
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available_actions_json = {}
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for methodName, methodInfo in methods.items():
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# Convert MethodAi -> ai, MethodDocument -> document, etc.
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shortName = methodName.replace('Method', '').lower()
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for actionName, actionInfo in methodInfo['actions'].items():
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# Create compound action name: method.action
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compoundActionName = f"{shortName}.{actionName}"
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# Get the action description
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action_description = actionInfo.get('description', f"Execute {actionName} action")
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available_actions_json[compoundActionName] = action_description
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return json.dumps(available_actions_json, indent=2, ensure_ascii=False)
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except Exception as e:
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logger.error(f"Error extracting available methods: {str(e)}")
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return json.dumps({}, indent=2, ensure_ascii=False)
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def _getReviewContent(self, context: Any) -> str:
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"""Get review content for result validation."""
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try:
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from modules.workflows.processing.shared.promptFactoryPlaceholders import extractReviewContent
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return extractReviewContent(context)
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except Exception as e:
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logger.error(f"Error getting review content: {str(e)}")
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return "No review content available"
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def _getPreviousActionResults(self, context: Any) -> str:
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"""Get previous action results for learning context."""
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try:
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if not hasattr(context, 'previous_action_results') or not context.previous_action_results:
|
||||
return "No previous actions executed yet"
|
||||
|
||||
results = []
|
||||
for i, result in enumerate(context.previous_action_results[-5:], 1): # Last 5 results
|
||||
if hasattr(result, 'resultLabel') and hasattr(result, 'status'):
|
||||
status = "SUCCESS" if result.status == "completed" else "FAILED"
|
||||
results.append(f"Action {i}: {result.resultLabel} - {status}")
|
||||
if hasattr(result, 'error') and result.error:
|
||||
results.append(f" Error: {result.error}")
|
||||
|
||||
return "\n".join(results) if results else "No previous actions executed yet"
|
||||
except Exception as e:
|
||||
logger.error(f"Error getting previous action results: {str(e)}")
|
||||
return "No previous actions executed yet"
|
||||
|
||||
def _getLearningsAndImprovements(self, context: Any) -> str:
|
||||
"""Get learnings and improvements from previous actions."""
|
||||
try:
|
||||
learnings = []
|
||||
|
||||
# Get improvements from context
|
||||
if hasattr(context, 'improvements') and context.improvements and isinstance(context.improvements, list):
|
||||
learnings.append("IMPROVEMENTS:")
|
||||
for improvement in context.improvements[-3:]: # Last 3 improvements
|
||||
learnings.append(f"- {improvement}")
|
||||
|
||||
# Get failure patterns
|
||||
if hasattr(context, 'failure_patterns') and context.failure_patterns and isinstance(context.failure_patterns, list):
|
||||
learnings.append("FAILURE PATTERNS TO AVOID:")
|
||||
for pattern in context.failure_patterns[-3:]: # Last 3 patterns
|
||||
learnings.append(f"- {pattern}")
|
||||
|
||||
# Get successful actions
|
||||
if hasattr(context, 'successful_actions') and context.successful_actions and isinstance(context.successful_actions, list):
|
||||
learnings.append("SUCCESSFUL APPROACHES:")
|
||||
for action in context.successful_actions[-3:]: # Last 3 successful
|
||||
learnings.append(f"- {action}")
|
||||
|
||||
return "\n".join(learnings) if learnings else "No learnings available yet"
|
||||
except Exception as e:
|
||||
logger.error(f"Error getting learnings and improvements: {str(e)}")
|
||||
return "No learnings available yet"
|
||||
|
||||
def _getLatestRefinementFeedback(self, context: Any) -> str:
|
||||
"""Get the latest refinement feedback to influence next action planning."""
|
||||
try:
|
||||
if not hasattr(context, 'previous_review_result') or not context.previous_review_result or not isinstance(context.previous_review_result, list):
|
||||
return "No previous refinement feedback available"
|
||||
|
||||
# Get the most recent refinement decision
|
||||
latest_decision = context.previous_review_result[-1]
|
||||
if not isinstance(latest_decision, dict):
|
||||
return "No previous refinement feedback available"
|
||||
|
||||
feedback_parts = []
|
||||
|
||||
# Add decision and reason
|
||||
decision = 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}")
|
||||
|
||||
# Add any specific feedback or suggestions
|
||||
if 'feedback' in latest_decision:
|
||||
feedback_parts.append(f"Feedback: {latest_decision['feedback']}")
|
||||
|
||||
if 'suggestions' in latest_decision:
|
||||
feedback_parts.append(f"Suggestions: {latest_decision['suggestions']}")
|
||||
|
||||
return "\n".join(feedback_parts)
|
||||
except Exception as e:
|
||||
logger.error(f"Error getting latest refinement feedback: {str(e)}")
|
||||
return "No previous refinement feedback available"
|
||||
|
||||
async def _generateActionObjective(self, context: Any, current_task: str, original_prompt: str, additional_data: Dict[str, Any] = None) -> str:
|
||||
"""Generate intelligent, context-aware action objective using AI."""
|
||||
try:
|
||||
# Get the selected action from additional_data
|
||||
selected_action = additional_data.get('SELECTED_ACTION', '') if additional_data else ''
|
||||
|
||||
# Build context for AI objective generation
|
||||
context_info = {
|
||||
"original_prompt": original_prompt,
|
||||
"current_task": current_task,
|
||||
"selected_action": selected_action,
|
||||
"available_documents": self._getFullDocumentContext(context),
|
||||
"available_connections": self._getFullConnectionContext(),
|
||||
"previous_results": self._getPreviousActionResults(context),
|
||||
"learnings": self._getLearningsAndImprovements(context),
|
||||
"refinement_feedback": self._getLatestRefinementFeedback(context),
|
||||
"user_language": self._extractUserLanguage()
|
||||
}
|
||||
|
||||
# Create AI prompt for objective generation
|
||||
objective_prompt = f"""Generate a specific, actionable objective for the selected action.
|
||||
|
||||
CONTEXT:
|
||||
- Original User Request: {context_info['original_prompt']}
|
||||
- Current Task: {context_info['current_task']}
|
||||
- Selected Action: {context_info['selected_action']}
|
||||
- Available Documents: {context_info['available_documents']}
|
||||
- Available Connections: {context_info['available_connections']}
|
||||
- Previous Action Results: {context_info['previous_results']}
|
||||
- Learnings and Improvements: {context_info['learnings']}
|
||||
- Latest Refinement Feedback: {context_info['refinement_feedback']}
|
||||
- User Language: {context_info['user_language']}
|
||||
|
||||
REQUIREMENTS:
|
||||
1. Create a SPECIFIC objective that tells the action exactly what to accomplish
|
||||
2. Include relevant details about documents, connections, recipients, etc.
|
||||
3. Learn from previous attempts and refinement feedback
|
||||
4. Make it actionable and concrete
|
||||
5. Focus on the user's actual intent, not just the task description
|
||||
6. If this is a retry, incorporate learnings from previous failures
|
||||
|
||||
RESPONSE FORMAT:
|
||||
Return ONLY the objective text, no explanations or formatting.
|
||||
|
||||
OBJECTIVE:"""
|
||||
|
||||
# Call AI to generate the objective
|
||||
if self.services and hasattr(self.services, 'ai'):
|
||||
from modules.datamodels.datamodelAi import AiCallOptions, OperationType, Priority, ProcessingMode
|
||||
|
||||
options = AiCallOptions(
|
||||
operationType=OperationType.ANALYSE_CONTENT,
|
||||
priority=Priority.BALANCED,
|
||||
compressPrompt=False,
|
||||
compressContext=False,
|
||||
processingMode=ProcessingMode.ADVANCED,
|
||||
maxCost=0.01,
|
||||
maxProcessingTime=10
|
||||
)
|
||||
|
||||
response = await self.services.ai.callAi(
|
||||
prompt=objective_prompt,
|
||||
placeholders={},
|
||||
options=options
|
||||
)
|
||||
|
||||
# Extract objective from response
|
||||
if response and response.strip():
|
||||
return response.strip()
|
||||
|
||||
# Fallback to current task if AI fails
|
||||
return current_task or original_prompt
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Error generating action objective: {str(e)}")
|
||||
# Fallback to current task
|
||||
return current_task or original_prompt
|
||||
|
|
@ -58,7 +58,7 @@ class TaskExecutionState:
|
|||
patterns.append("permission_issues")
|
||||
return list(set(patterns))
|
||||
|
||||
def should_continue(observation, review=None, current_step: int = 0, max_steps: int = 5) -> bool:
|
||||
def shouldContinue(observation, review=None, current_step: int = 0, max_steps: int = 5) -> bool:
|
||||
"""Helper to decide if the iterative loop should continue
|
||||
- Stop if review indicates 'stop' or success criteria are met
|
||||
- Stop on failure with no retry path
|
||||
|
|
|
|||
130
modules/workflows/processing/shared/methodDiscovery.py
Normal file
130
modules/workflows/processing/shared/methodDiscovery.py
Normal file
|
|
@ -0,0 +1,130 @@
|
|||
# methodDiscovery.py
|
||||
# Method discovery and management for workflow execution
|
||||
|
||||
import json
|
||||
import logging
|
||||
import importlib
|
||||
import pkgutil
|
||||
import inspect
|
||||
from typing import Any, Dict, List
|
||||
from modules.datamodels.datamodelWorkflow import TaskContext, ReviewContext, DocumentExchange
|
||||
from modules.workflows.methods.methodBase import MethodBase
|
||||
|
||||
# Set up logger
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
# Global methods catalog - moved from serviceCenter
|
||||
methods = {}
|
||||
|
||||
def discoverMethods(serviceCenter):
|
||||
"""Dynamically discover all method classes and their actions in modules methods package"""
|
||||
try:
|
||||
# Import the methods package
|
||||
methodsPackage = importlib.import_module('modules.workflows.methods')
|
||||
|
||||
# Discover all modules in the package
|
||||
for _, name, isPkg in pkgutil.iter_modules(methodsPackage.__path__):
|
||||
if not isPkg and name.startswith('method'):
|
||||
try:
|
||||
# Import the module
|
||||
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):
|
||||
# Instantiate the method
|
||||
methodInstance = item(serviceCenter)
|
||||
|
||||
# Use the actions property from MethodBase which handles @action decorator
|
||||
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
|
||||
shortName = itemName.replace('Method', '').lower()
|
||||
methods[shortName] = methodInfo
|
||||
|
||||
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 {len(methods)} method entries total")
|
||||
|
||||
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 getActionParameterSignature(methodName: str, actionName: str, methods: Dict[str, Any]) -> str:
|
||||
"""Get action parameter signature from method docstring for AI parameter generation"""
|
||||
try:
|
||||
if not methods or methodName not in methods:
|
||||
return ""
|
||||
|
||||
methodInstance = methods[methodName]['instance']
|
||||
if actionName not in methodInstance.actions:
|
||||
return ""
|
||||
|
||||
action_info = methodInstance.actions[actionName]
|
||||
# Extract parameter descriptions from docstring
|
||||
docstring = action_info.get('description', '')
|
||||
paramDescriptions, paramTypes = methodInstance._extractParameterDetails(docstring)
|
||||
|
||||
param_list = []
|
||||
for paramName, paramDesc in paramDescriptions.items():
|
||||
paramType = paramTypes.get(paramName, 'Any')
|
||||
if paramDesc:
|
||||
param_list.append(f"- {paramName} ({paramType}): {paramDesc}")
|
||||
else:
|
||||
param_list.append(f"- {paramName} ({paramType})")
|
||||
|
||||
return "Required parameters:\n" + "\n".join(param_list)
|
||||
except Exception as e:
|
||||
logger.error(f"Error getting action parameter signature for {methodName}.{actionName}: {str(e)}")
|
||||
return ""
|
||||
|
||||
633
modules/workflows/processing/shared/placeholderFactory.py
Normal file
633
modules/workflows/processing/shared/placeholderFactory.py
Normal file
|
|
@ -0,0 +1,633 @@
|
|||
"""
|
||||
Placeholder Factory
|
||||
Centralized placeholder extraction functions for all workflow modes.
|
||||
Each function corresponds to a {{KEY:PLACEHOLDER_NAME}} in prompt templates.
|
||||
|
||||
NAMING CONVENTION:
|
||||
- All functions follow pattern: extract{PlaceholderName}()
|
||||
- Placeholder names are in UPPER_CASE with underscores
|
||||
- Function names are in camelCase
|
||||
|
||||
MAPPING TABLE:
|
||||
{{KEY:USER_PROMPT}} -> extractUserPrompt()
|
||||
{{KEY:AVAILABLE_DOCUMENTS}} -> extractAvailableDocuments()
|
||||
{{KEY:WORKFLOW_HISTORY}} -> extractWorkflowHistory()
|
||||
{{KEY:AVAILABLE_METHODS}} -> extractAvailableMethods()
|
||||
{{KEY:AVAILABLE_CONNECTIONS}} -> extractAvailableConnections()
|
||||
{{KEY:USER_LANGUAGE}} -> extractUserLanguage()
|
||||
{{KEY:REVIEW_CONTENT}} -> extractReviewContent()
|
||||
{{KEY:ACTION_OBJECTIVE}} -> extractActionObjective()
|
||||
{{KEY:PREVIOUS_ACTION_RESULTS}} -> extractPreviousActionResults()
|
||||
{{KEY:LEARNINGS_AND_IMPROVEMENTS}} -> extractLearningsAndImprovements()
|
||||
{{KEY:LATEST_REFINEMENT_FEEDBACK}} -> extractLatestRefinementFeedback()
|
||||
{{KEY:SELECTED_ACTION}} -> extractSelectedAction()
|
||||
{{KEY:ACTION_SIGNATURE}} -> extractActionSignature()
|
||||
{{KEY:ENHANCED_DOCUMENTS}} -> extractEnhancedDocumentContext()
|
||||
"""
|
||||
|
||||
import json
|
||||
import logging
|
||||
from typing import Dict, Any, List
|
||||
from modules.datamodels.datamodelChat import ChatDocument
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
from modules.workflows.processing.shared.methodDiscovery import (
|
||||
getAvailableDocuments,
|
||||
getMethodsList,
|
||||
methods,
|
||||
discoverMethods
|
||||
)
|
||||
|
||||
|
||||
# ============================================================================
|
||||
# CORE PLACEHOLDER EXTRACTION FUNCTIONS
|
||||
# ============================================================================
|
||||
|
||||
def extractUserPrompt(context: Any) -> str:
|
||||
"""Extract user prompt from context. Maps to {{KEY:USER_PROMPT}}"""
|
||||
if hasattr(context, 'task_step') and context.task_step:
|
||||
return context.task_step.objective or 'No request specified'
|
||||
return 'No request specified'
|
||||
|
||||
|
||||
def extractAvailableDocuments(context: Any) -> str:
|
||||
"""Extract available documents from context. Maps to {{KEY:AVAILABLE_DOCUMENTS}}"""
|
||||
if hasattr(context, 'available_documents') and context.available_documents:
|
||||
return context.available_documents
|
||||
return "No documents available"
|
||||
|
||||
|
||||
def extractWorkflowHistory(service: Any, context: Any) -> str:
|
||||
"""Extract workflow history from context. Maps to {{KEY:WORKFLOW_HISTORY}}"""
|
||||
if hasattr(context, 'workflow') and context.workflow:
|
||||
return getPreviousRoundContext(service, context.workflow) or "No previous workflow rounds - this is the first round."
|
||||
return "No previous workflow rounds - this is the first round."
|
||||
|
||||
|
||||
def extractAvailableMethods(service: Any) -> str:
|
||||
"""Extract available methods for action planning. Maps to {{KEY:AVAILABLE_METHODS}}"""
|
||||
try:
|
||||
# Get the methods dictionary directly from the global methods variable
|
||||
if not methods:
|
||||
discoverMethods(service)
|
||||
|
||||
# Create a flat JSON format with compound action names for better AI parsing
|
||||
available_actions_json = {}
|
||||
for methodName, methodInfo in methods.items():
|
||||
# Convert MethodAi -> ai, MethodDocument -> document, etc.
|
||||
shortName = methodName.replace('Method', '').lower()
|
||||
|
||||
for actionName, actionInfo in methodInfo['actions'].items():
|
||||
# Create compound action name: method.action
|
||||
compoundActionName = f"{shortName}.{actionName}"
|
||||
# Get the action description
|
||||
action_description = actionInfo.get('description', f"Execute {actionName} action")
|
||||
available_actions_json[compoundActionName] = action_description
|
||||
|
||||
return json.dumps(available_actions_json, indent=2, ensure_ascii=False)
|
||||
except Exception as e:
|
||||
logger.error(f"Error extracting available methods: {str(e)}")
|
||||
return json.dumps({}, indent=2, ensure_ascii=False)
|
||||
|
||||
|
||||
def extractUserLanguage(service: Any) -> str:
|
||||
"""Extract user language from service. Maps to {{KEY:USER_LANGUAGE}}"""
|
||||
return service.user.language if service and service.user else 'en'
|
||||
|
||||
|
||||
def extractAvailableConnections(service: Any) -> str:
|
||||
"""Extract available connections. Maps to {{KEY:AVAILABLE_CONNECTIONS}}"""
|
||||
try:
|
||||
connections = getConnectionReferenceList(service)
|
||||
if connections:
|
||||
return '\n'.join(f"- {conn}" for conn in connections)
|
||||
return "No connections available"
|
||||
except Exception as e:
|
||||
logger.error(f"Error extracting available connections: {str(e)}")
|
||||
return "No connections available"
|
||||
|
||||
|
||||
def getConnectionReferenceList(services) -> List[str]:
|
||||
"""Get list of available connections"""
|
||||
try:
|
||||
# Get connections from the database
|
||||
if hasattr(services, 'interfaceDbApp') and hasattr(services, 'user'):
|
||||
userId = services.user.id
|
||||
connections = services.interfaceDbApp.getUserConnections(userId)
|
||||
if connections:
|
||||
# Format connections as reference strings
|
||||
connectionRefs = []
|
||||
for conn in connections:
|
||||
# Create reference string in format: conn_{authority}_{id}
|
||||
ref = f"conn_{conn.authority.value}_{conn.id}"
|
||||
connectionRefs.append(ref)
|
||||
return connectionRefs
|
||||
|
||||
return []
|
||||
except Exception as e:
|
||||
logger.error(f"Error getting connection reference list: {str(e)}")
|
||||
return []
|
||||
|
||||
|
||||
def getPreviousRoundContext(services, context: Any) -> str:
|
||||
"""Get previous round context for prompt"""
|
||||
try:
|
||||
if not context or not hasattr(context, 'workflow_id'):
|
||||
return "No previous round context available"
|
||||
|
||||
workflowId = context.workflow_id
|
||||
if not workflowId:
|
||||
return "No previous round context available"
|
||||
|
||||
# Get previous round results
|
||||
previousResults = getattr(context, 'previous_results', [])
|
||||
if not previousResults:
|
||||
return "No previous round context available"
|
||||
|
||||
contextList = []
|
||||
for i, result in enumerate(previousResults, 1):
|
||||
if hasattr(result, 'success') and hasattr(result, 'resultLabel'):
|
||||
status = "Success" if result.success else "Failed"
|
||||
contextList.append(f"{i}. {result.resultLabel} - {status}")
|
||||
elif isinstance(result, dict):
|
||||
status = "Success" if result.get('success', False) else "Failed"
|
||||
label = result.get('resultLabel', 'Unknown')
|
||||
contextList.append(f"{i}. {label} - {status}")
|
||||
else:
|
||||
contextList.append(f"{i}. {str(result)}")
|
||||
|
||||
return "\n".join(contextList) if contextList else "No previous round context available"
|
||||
except Exception as e:
|
||||
logger.error(f"Error getting previous round context: {str(e)}")
|
||||
return "Error retrieving previous round context"
|
||||
|
||||
|
||||
def extractReviewContent(context: Any) -> str:
|
||||
"""Extract review content for result validation. Maps to {{KEY:REVIEW_CONTENT}}"""
|
||||
try:
|
||||
if hasattr(context, 'action_results') and context.action_results:
|
||||
# Build result summary
|
||||
result_summary = ""
|
||||
for i, result in enumerate(context.action_results):
|
||||
result_summary += f"\nRESULT {i+1}:\n"
|
||||
result_summary += f" Success: {result.success}\n"
|
||||
if result.error:
|
||||
result_summary += f" Error: {result.error}\n"
|
||||
|
||||
if result.documents:
|
||||
result_summary += f" Documents: {len(result.documents)} document(s)\n"
|
||||
for doc in result.documents:
|
||||
# Extract all available metadata without content
|
||||
doc_metadata = {
|
||||
"name": getattr(doc, 'documentName', 'Unknown'),
|
||||
"mimeType": getattr(doc, 'mimeType', 'Unknown'),
|
||||
"size": getattr(doc, 'size', 'Unknown'),
|
||||
"created": getattr(doc, 'created', 'Unknown'),
|
||||
"modified": getattr(doc, 'modified', 'Unknown'),
|
||||
"typeGroup": getattr(doc, 'typeGroup', 'Unknown'),
|
||||
"documentId": getattr(doc, 'documentId', 'Unknown'),
|
||||
"reference": getattr(doc, 'reference', 'Unknown')
|
||||
}
|
||||
# Remove 'Unknown' values to keep it clean
|
||||
doc_metadata = {k: v for k, v in doc_metadata.items() if v != 'Unknown'}
|
||||
result_summary += f" - {json.dumps(doc_metadata, indent=6, ensure_ascii=False)}\n"
|
||||
else:
|
||||
result_summary += f" Documents: None\n"
|
||||
|
||||
return result_summary
|
||||
elif hasattr(context, 'observation') and context.observation:
|
||||
# For observation data, show full content but handle documents specially
|
||||
if isinstance(context.observation, dict):
|
||||
# Create a copy to modify
|
||||
obs_copy = context.observation.copy()
|
||||
|
||||
# If there are previews with documents, show only metadata
|
||||
if 'previews' in obs_copy and isinstance(obs_copy['previews'], list):
|
||||
for preview in obs_copy['previews']:
|
||||
if isinstance(preview, dict) and 'snippet' in preview:
|
||||
# Replace snippet with metadata indicator
|
||||
preview['snippet'] = f"[Content: {len(preview.get('snippet', ''))} characters]"
|
||||
|
||||
return json.dumps(obs_copy, indent=2, ensure_ascii=False)
|
||||
else:
|
||||
return json.dumps(context.observation, ensure_ascii=False)
|
||||
elif hasattr(context, 'step_result') and context.step_result and 'observation' in context.step_result:
|
||||
# For observation data in step_result, show full content but handle documents specially
|
||||
observation = context.step_result['observation']
|
||||
if isinstance(observation, dict):
|
||||
# Create a copy to modify
|
||||
obs_copy = observation.copy()
|
||||
|
||||
# If there are previews with documents, show only metadata
|
||||
if 'previews' in obs_copy and isinstance(obs_copy['previews'], list):
|
||||
for preview in obs_copy['previews']:
|
||||
if isinstance(preview, dict) and 'snippet' in preview:
|
||||
# Replace snippet with metadata indicator
|
||||
preview['snippet'] = f"[Content: {len(preview.get('snippet', ''))} characters]"
|
||||
|
||||
return json.dumps(obs_copy, indent=2, ensure_ascii=False)
|
||||
else:
|
||||
return json.dumps(observation, ensure_ascii=False)
|
||||
else:
|
||||
return "No review content available"
|
||||
except Exception as e:
|
||||
logger.error(f"Error extracting review content: {str(e)}")
|
||||
return "No review content available"
|
||||
|
||||
|
||||
# ============================================================================
|
||||
# REACT MODE SPECIFIC PLACEHOLDERS
|
||||
# ============================================================================
|
||||
|
||||
def extractActionObjective(context: Any, current_task: str, original_prompt: str, additional_data: Dict[str, Any] = None) -> str:
|
||||
"""Extract action objective for React mode. Maps to {{KEY:ACTION_OBJECTIVE}}"""
|
||||
# This is a placeholder - the actual implementation will be in placeholderFactoryReactOnly
|
||||
# since it requires AI generation
|
||||
return current_task or original_prompt
|
||||
|
||||
|
||||
def extractPreviousActionResults(context: Any) -> str:
|
||||
"""Extract previous action results for learning context. Maps to {{KEY:PREVIOUS_ACTION_RESULTS}}"""
|
||||
try:
|
||||
if not hasattr(context, 'previous_action_results') or not context.previous_action_results:
|
||||
return "No previous actions executed yet"
|
||||
|
||||
results = []
|
||||
for i, result in enumerate(context.previous_action_results[-5:], 1): # Last 5 results
|
||||
if hasattr(result, 'resultLabel') and hasattr(result, 'status'):
|
||||
status = "SUCCESS" if result.status == "completed" else "FAILED"
|
||||
results.append(f"Action {i}: {result.resultLabel} - {status}")
|
||||
if hasattr(result, 'error') and result.error:
|
||||
results.append(f" Error: {result.error}")
|
||||
|
||||
return "\n".join(results) if results else "No previous actions executed yet"
|
||||
except Exception as e:
|
||||
logger.error(f"Error extracting previous action results: {str(e)}")
|
||||
return "No previous actions executed yet"
|
||||
|
||||
|
||||
def extractLearningsAndImprovements(context: Any) -> str:
|
||||
"""Extract learnings and improvements from previous actions. Maps to {{KEY:LEARNINGS_AND_IMPROVEMENTS}}"""
|
||||
try:
|
||||
learnings = []
|
||||
|
||||
# Get improvements from context
|
||||
if hasattr(context, 'improvements') and context.improvements and isinstance(context.improvements, list):
|
||||
learnings.append("IMPROVEMENTS:")
|
||||
for improvement in context.improvements[-3:]: # Last 3 improvements
|
||||
learnings.append(f"- {improvement}")
|
||||
|
||||
# Get failure patterns
|
||||
if hasattr(context, 'failure_patterns') and context.failure_patterns and isinstance(context.failure_patterns, list):
|
||||
learnings.append("FAILURE PATTERNS TO AVOID:")
|
||||
for pattern in context.failure_patterns[-3:]: # Last 3 patterns
|
||||
learnings.append(f"- {pattern}")
|
||||
|
||||
# Get successful actions
|
||||
if hasattr(context, 'successful_actions') and context.successful_actions and isinstance(context.successful_actions, list):
|
||||
learnings.append("SUCCESSFUL APPROACHES:")
|
||||
for action in context.successful_actions[-3:]: # Last 3 successful
|
||||
learnings.append(f"- {action}")
|
||||
|
||||
return "\n".join(learnings) if learnings else "No learnings available yet"
|
||||
except Exception as e:
|
||||
logger.error(f"Error extracting learnings and improvements: {str(e)}")
|
||||
return "No learnings available yet"
|
||||
|
||||
|
||||
def extractLatestRefinementFeedback(context: Any) -> str:
|
||||
"""Extract the latest refinement feedback. Maps to {{KEY:LATEST_REFINEMENT_FEEDBACK}}"""
|
||||
try:
|
||||
if not hasattr(context, 'previous_review_result') or not context.previous_review_result or not isinstance(context.previous_review_result, list):
|
||||
return "No previous refinement feedback available"
|
||||
|
||||
# Get the most recent refinement decision
|
||||
latest_decision = context.previous_review_result[-1]
|
||||
if not isinstance(latest_decision, dict):
|
||||
return "No previous refinement feedback available"
|
||||
|
||||
feedback_parts = []
|
||||
|
||||
# Add decision and reason
|
||||
decision = 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}")
|
||||
|
||||
# Add any specific feedback or suggestions
|
||||
if 'feedback' in latest_decision:
|
||||
feedback_parts.append(f"Feedback: {latest_decision['feedback']}")
|
||||
|
||||
if 'suggestions' in latest_decision:
|
||||
feedback_parts.append(f"Suggestions: {latest_decision['suggestions']}")
|
||||
|
||||
return "\n".join(feedback_parts)
|
||||
except Exception as e:
|
||||
logger.error(f"Error extracting latest refinement feedback: {str(e)}")
|
||||
return "No previous refinement feedback available"
|
||||
|
||||
|
||||
def extractSelectedAction(additional_data: Dict[str, Any]) -> str:
|
||||
"""Extract selected action from additional data. Maps to {{KEY:SELECTED_ACTION}}"""
|
||||
return additional_data.get('SELECTED_ACTION', '') if additional_data else ''
|
||||
|
||||
|
||||
def extractActionSignature(additional_data: Dict[str, Any]) -> str:
|
||||
"""Extract action signature from additional data. Maps to {{KEY:ACTION_SIGNATURE}}"""
|
||||
return additional_data.get('ACTION_SIGNATURE', '') if additional_data else ''
|
||||
|
||||
|
||||
# ============================================================================
|
||||
# CONTEXT-AWARE PLACEHOLDER FUNCTIONS (for React mode)
|
||||
# ============================================================================
|
||||
|
||||
def extractMinimalDocumentContext(service: Any, context: Any) -> str:
|
||||
"""Extract minimal document context (counts only) for React plan selection."""
|
||||
try:
|
||||
if hasattr(context, 'workflow') and context.workflow:
|
||||
# Get document count from workflow
|
||||
documents = service.workflow.getAvailableDocuments(context.workflow)
|
||||
if documents and documents != "No documents available":
|
||||
# Count documents by counting docList and docItem references
|
||||
doc_count = documents.count("docList:") + documents.count("docItem:")
|
||||
return f"{doc_count} documents available from previous tasks"
|
||||
else:
|
||||
return "No documents available"
|
||||
return "No documents available"
|
||||
except Exception as e:
|
||||
logger.error(f"Error getting minimal document context: {str(e)}")
|
||||
return "No documents available"
|
||||
|
||||
|
||||
def extractFullDocumentContext(service: Any, context: Any) -> str:
|
||||
"""Extract full document context with detailed references for parameter generation."""
|
||||
try:
|
||||
if hasattr(context, 'workflow') and context.workflow:
|
||||
return service.workflow.getAvailableDocuments(context.workflow)
|
||||
return "No documents available"
|
||||
except Exception as e:
|
||||
logger.error(f"Error getting full document context: {str(e)}")
|
||||
return "No documents available"
|
||||
|
||||
|
||||
def extractMinimalConnectionContext(service: Any) -> str:
|
||||
"""Extract minimal connection context (count only) for React plan selection."""
|
||||
try:
|
||||
connections = getConnectionReferenceList(service)
|
||||
if connections:
|
||||
return f"{len(connections)} connections available"
|
||||
return "No connections available"
|
||||
except Exception as e:
|
||||
logger.error(f"Error getting minimal connection context: {str(e)}")
|
||||
return "No connections available"
|
||||
|
||||
|
||||
def extractFullConnectionContext(service: Any) -> str:
|
||||
"""Extract full connection context with detailed references for parameter generation."""
|
||||
try:
|
||||
connections = getConnectionReferenceList(service)
|
||||
if connections:
|
||||
return '\n'.join(f"- {conn}" for conn in connections)
|
||||
return "No connections available"
|
||||
except Exception as e:
|
||||
logger.error(f"Error getting full connection context: {str(e)}")
|
||||
return "No connections available"
|
||||
|
||||
|
||||
def extractUserPromptFromService(service: Any) -> str:
|
||||
"""Extract user prompt from service (clean and reliable)."""
|
||||
# Get the current user prompt from services (clean and reliable)
|
||||
if service and hasattr(service, 'currentUserPrompt') and service.currentUserPrompt:
|
||||
return service.currentUserPrompt
|
||||
|
||||
# Fallback to task step objective if no current prompt found
|
||||
return 'No request specified'
|
||||
|
||||
|
||||
def extractUserLanguageFromService(service: Any) -> str:
|
||||
"""Extract user language from service."""
|
||||
return service.user.language if service and service.user else 'en'
|
||||
|
||||
|
||||
# ============================================================================
|
||||
# ADDITIONAL PLACEHOLDER EXTRACTION FUNCTIONS (moved from methodDiscovery.py)
|
||||
# ============================================================================
|
||||
|
||||
def extractAvailableDocumentsFromList(context: Any) -> str:
|
||||
"""Extract available documents from context list. Maps to {{KEY:AVAILABLE_DOCUMENTS}} (alternative implementation)"""
|
||||
try:
|
||||
if not context or not hasattr(context, 'available_documents') or not context.available_documents:
|
||||
return "No documents available"
|
||||
|
||||
documents = context.available_documents
|
||||
if not isinstance(documents, list):
|
||||
return "No documents available"
|
||||
|
||||
docList = []
|
||||
for i, doc in enumerate(documents, 1):
|
||||
if isinstance(doc, ChatDocument):
|
||||
docInfo = f"{i}. **{doc.fileName}**"
|
||||
if hasattr(doc, 'mimeType') and doc.mimeType:
|
||||
docInfo += f" ({doc.mimeType})"
|
||||
if hasattr(doc, 'size') and doc.size:
|
||||
docInfo += f" - {doc.size} bytes"
|
||||
docList.append(docInfo)
|
||||
elif isinstance(doc, dict):
|
||||
docInfo = f"{i}. **{doc.get('fileName', 'Unknown')}**"
|
||||
if doc.get('mimeType'):
|
||||
docInfo += f" ({doc['mimeType']})"
|
||||
if doc.get('size'):
|
||||
docInfo += f" - {doc['size']} bytes"
|
||||
docList.append(docInfo)
|
||||
else:
|
||||
docList.append(f"{i}. {str(doc)}")
|
||||
|
||||
return "\n".join(docList) if docList else "No documents available"
|
||||
except Exception as e:
|
||||
logger.error(f"Error getting available documents: {str(e)}")
|
||||
return "Error retrieving documents"
|
||||
|
||||
|
||||
def extractWorkflowHistoryFromMessages(services: Any, context: Any) -> str:
|
||||
"""Extract workflow history from messages. Maps to {{KEY:WORKFLOW_HISTORY}} (alternative implementation)"""
|
||||
try:
|
||||
if not context or not hasattr(context, 'workflow_id'):
|
||||
return "No workflow history available"
|
||||
|
||||
workflowId = context.workflow_id
|
||||
if not workflowId:
|
||||
return "No workflow history available"
|
||||
|
||||
# Get workflow messages
|
||||
messages = services.interfaceDbChat.getWorkflowMessages(workflowId)
|
||||
if not messages:
|
||||
return "No workflow history available"
|
||||
|
||||
# Filter for relevant messages (last 10)
|
||||
recentMessages = messages[-10:] if len(messages) > 10 else messages
|
||||
|
||||
historyList = []
|
||||
for msg in recentMessages:
|
||||
if hasattr(msg, 'role') and hasattr(msg, 'message'):
|
||||
role = "User" if msg.role == "user" else "Assistant"
|
||||
message = msg.message[:200] + "..." if len(msg.message) > 200 else msg.message
|
||||
historyList.append(f"**{role}**: {message}")
|
||||
|
||||
return "\n".join(historyList) if historyList else "No workflow history available"
|
||||
except Exception as e:
|
||||
logger.error(f"Error getting workflow history: {str(e)}")
|
||||
return "Error retrieving workflow history"
|
||||
|
||||
|
||||
def extractAvailableMethodsFromList(services: Any) -> str:
|
||||
"""Extract available methods as formatted list. Maps to {{KEY:AVAILABLE_METHODS}} (alternative implementation)"""
|
||||
try:
|
||||
if not methods:
|
||||
discoverMethods(services)
|
||||
|
||||
return getMethodsList(services)
|
||||
except Exception as e:
|
||||
logger.error(f"Error getting available methods: {str(e)}")
|
||||
return "Error retrieving available methods"
|
||||
|
||||
|
||||
def extractUserLanguageFromServices(services: Any) -> str:
|
||||
"""Extract user language from services. Maps to {{KEY:USER_LANGUAGE}} (alternative implementation)"""
|
||||
try:
|
||||
if hasattr(services, 'user') and hasattr(services.user, 'language'):
|
||||
return services.user.language or 'en'
|
||||
return 'en'
|
||||
except Exception as e:
|
||||
logger.error(f"Error getting user language: {str(e)}")
|
||||
return 'en'
|
||||
|
||||
|
||||
def extractReviewContentFromObservation(context: Any) -> str:
|
||||
"""Extract review content from observation. Maps to {{KEY:REVIEW_CONTENT}} (alternative implementation)"""
|
||||
try:
|
||||
if not context or not hasattr(context, 'observation'):
|
||||
return "No review content available"
|
||||
|
||||
observation = context.observation
|
||||
if not isinstance(observation, dict):
|
||||
return "No review content available"
|
||||
|
||||
reviewParts = []
|
||||
|
||||
# Add success status
|
||||
if 'success' in observation:
|
||||
reviewParts.append(f"Success: {observation['success']}")
|
||||
|
||||
# Add documents count
|
||||
if 'documentsCount' in observation:
|
||||
reviewParts.append(f"Documents generated: {observation['documentsCount']}")
|
||||
|
||||
# Add previews
|
||||
if 'previews' in observation and observation['previews']:
|
||||
reviewParts.append("Document previews:")
|
||||
for preview in observation['previews']:
|
||||
if isinstance(preview, dict):
|
||||
name = preview.get('name', 'Unknown')
|
||||
mimeType = preview.get('mimeType', 'Unknown')
|
||||
size = preview.get('contentSize', 'Unknown size')
|
||||
reviewParts.append(f" - {name} ({mimeType}) - {size}")
|
||||
|
||||
# Add notes
|
||||
if 'notes' in observation and observation['notes']:
|
||||
reviewParts.append("Notes:")
|
||||
for note in observation['notes']:
|
||||
reviewParts.append(f" - {note}")
|
||||
|
||||
return "\n".join(reviewParts) if reviewParts else "No review content available"
|
||||
except Exception as e:
|
||||
logger.error(f"Error getting review content: {str(e)}")
|
||||
return "Error retrieving review content"
|
||||
|
||||
|
||||
def extractEnhancedDocumentContext(services: Any) -> str:
|
||||
"""Extract enhanced document context with full metadata. Maps to {{KEY:ENHANCED_DOCUMENTS}}"""
|
||||
try:
|
||||
# Get all documents from the current workflow
|
||||
workflow = getattr(services, 'currentWorkflow', None)
|
||||
if not workflow or not hasattr(workflow, 'id'):
|
||||
return "No workflow context available"
|
||||
|
||||
# Get workflow documents from messages
|
||||
if not hasattr(workflow, 'messages') or not workflow.messages:
|
||||
return "No documents available"
|
||||
|
||||
# Collect all documents from all messages
|
||||
all_documents = []
|
||||
for message in workflow.messages:
|
||||
if hasattr(message, 'documents') and message.documents:
|
||||
all_documents.extend(message.documents)
|
||||
|
||||
if not all_documents:
|
||||
return "No documents available"
|
||||
|
||||
# Group documents by round/task/action for better organization
|
||||
docGroups = {}
|
||||
for message in workflow.messages:
|
||||
if hasattr(message, 'documents') and message.documents:
|
||||
round_num = getattr(message, 'roundNumber', 0)
|
||||
task_num = getattr(message, 'taskNumber', 0)
|
||||
action_num = getattr(message, 'actionNumber', 0)
|
||||
label = getattr(message, 'documentsLabel', 'results')
|
||||
|
||||
group_key = f"round{round_num}_task{task_num}_action{action_num}_{label}"
|
||||
if group_key not in docGroups:
|
||||
docGroups[group_key] = []
|
||||
docGroups[group_key].extend(message.documents)
|
||||
|
||||
# Format documents by groups with proper docList references
|
||||
docList = []
|
||||
for group_key, group_docs in docGroups.items():
|
||||
# Find the message that contains these documents to get the message ID
|
||||
message_id = None
|
||||
for message in workflow.messages:
|
||||
if hasattr(message, 'documents') and message.documents:
|
||||
round_num = getattr(message, 'roundNumber', 0)
|
||||
task_num = getattr(message, 'taskNumber', 0)
|
||||
action_num = getattr(message, 'actionNumber', 0)
|
||||
label = getattr(message, 'documentsLabel', 'results')
|
||||
msg_group_key = f"round{round_num}_task{task_num}_action{action_num}_{label}"
|
||||
|
||||
if msg_group_key == group_key:
|
||||
message_id = str(message.id)
|
||||
break
|
||||
|
||||
# Generate proper docList reference
|
||||
if message_id:
|
||||
docListRef = f"docList:{message_id}:{group_key}"
|
||||
else:
|
||||
# Fallback to direct label reference
|
||||
docListRef = group_key
|
||||
|
||||
docList.append(f"\n**{group_key}:**")
|
||||
docList.append(f"Reference: {docListRef}")
|
||||
for i, doc in enumerate(group_docs, 1):
|
||||
if isinstance(doc, ChatDocument):
|
||||
docInfo = f" {i}. **{doc.fileName}**"
|
||||
if hasattr(doc, 'mimeType') and doc.mimeType:
|
||||
docInfo += f" ({doc.mimeType})"
|
||||
if hasattr(doc, 'size') and doc.size:
|
||||
docInfo += f" - {doc.size} bytes"
|
||||
if hasattr(doc, 'created') and doc.created:
|
||||
docInfo += f" - Created: {doc.created}"
|
||||
docList.append(docInfo)
|
||||
elif isinstance(doc, dict):
|
||||
docInfo = f" {i}. **{doc.get('fileName', 'Unknown')}**"
|
||||
if doc.get('mimeType'):
|
||||
docInfo += f" ({doc['mimeType']})"
|
||||
if doc.get('size'):
|
||||
docInfo += f" - {doc['size']} bytes"
|
||||
if doc.get('created'):
|
||||
docInfo += f" - Created: {doc['created']}"
|
||||
docList.append(docInfo)
|
||||
else:
|
||||
docList.append(f" {i}. {str(doc)}")
|
||||
|
||||
return "\n".join(docList) if docList else "No documents available"
|
||||
except Exception as e:
|
||||
logger.error(f"Error getting enhanced document context: {str(e)}")
|
||||
return "Error retrieving document context"
|
||||
|
|
@ -0,0 +1,189 @@
|
|||
"""
|
||||
Context-aware placeholder service for different workflow phases.
|
||||
This module provides different levels of context based on the workflow phase.
|
||||
"""
|
||||
|
||||
import json
|
||||
import logging
|
||||
from typing import Dict, Any, Optional
|
||||
from enum import Enum
|
||||
from modules.workflows.processing.shared.placeholderFactory import (
|
||||
extractUserPromptFromService, extractFullDocumentContext,
|
||||
extractWorkflowHistory, extractUserLanguageFromService,
|
||||
extractMinimalDocumentContext, extractAvailableMethods,
|
||||
extractMinimalConnectionContext, extractFullConnectionContext,
|
||||
extractReviewContent, extractPreviousActionResults,
|
||||
extractLearningsAndImprovements, extractLatestRefinementFeedback
|
||||
)
|
||||
from modules.datamodels.datamodelAi import AiCallOptions, OperationType, Priority, ProcessingMode
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
class WorkflowPhase(Enum):
|
||||
"""Different phases of workflow execution requiring different context levels."""
|
||||
TASK_PLANNING = "task_planning" # Needs full context for planning
|
||||
REACT_PLAN_SELECTION = "react_plan_selection" # Needs minimal context for action selection
|
||||
REACT_PARAMETERS = "react_parameters" # Needs full context for parameter generation
|
||||
ACTION_PLANNING = "action_planning" # Needs full context for action planning
|
||||
RESULT_REVIEW = "result_review" # Needs full context for review
|
||||
|
||||
class ContextAwarePlaceholders:
|
||||
"""Context-aware placeholder service that provides different context levels based on workflow phase."""
|
||||
|
||||
def __init__(self, services):
|
||||
self.services = services
|
||||
|
||||
async def getPlaceholders(self, phase: WorkflowPhase, context: Any, additional_data: Dict[str, Any] = None) -> Dict[str, str]:
|
||||
"""
|
||||
Get placeholders based on workflow phase and context.
|
||||
|
||||
Args:
|
||||
phase: The workflow phase determining context level
|
||||
context: The workflow context object
|
||||
additional_data: Additional data for specific phases (e.g., selected action)
|
||||
|
||||
Returns:
|
||||
Dictionary of placeholder key-value pairs
|
||||
"""
|
||||
if phase == WorkflowPhase.TASK_PLANNING:
|
||||
return {
|
||||
"USER_PROMPT": extractUserPromptFromService(self.services),
|
||||
"AVAILABLE_DOCUMENTS": extractFullDocumentContext(self.services, context),
|
||||
"WORKFLOW_HISTORY": extractWorkflowHistory(self.services, context),
|
||||
"USER_LANGUAGE": extractUserLanguageFromService(self.services),
|
||||
}
|
||||
elif phase == WorkflowPhase.REACT_PLAN_SELECTION:
|
||||
return {
|
||||
"USER_PROMPT": extractUserPromptFromService(self.services),
|
||||
"AVAILABLE_DOCUMENTS": extractMinimalDocumentContext(self.services, context),
|
||||
"USER_LANGUAGE": extractUserLanguageFromService(self.services),
|
||||
"AVAILABLE_METHODS": extractAvailableMethods(self.services),
|
||||
"AVAILABLE_CONNECTIONS": extractMinimalConnectionContext(self.services),
|
||||
}
|
||||
elif phase == WorkflowPhase.REACT_PARAMETERS:
|
||||
# Get both original user prompt and current task objective
|
||||
original_prompt = extractUserPromptFromService(self.services)
|
||||
current_task = ""
|
||||
if hasattr(context, 'task_step') and context.task_step and context.task_step.objective:
|
||||
current_task = context.task_step.objective
|
||||
|
||||
# Combine original prompt and current task for better context
|
||||
combined_prompt = f"Original request: {original_prompt}"
|
||||
if current_task and current_task != original_prompt:
|
||||
combined_prompt += f"\n\nCurrent task: {current_task}"
|
||||
|
||||
# Generate intelligent action objective
|
||||
action_objective = await self._generateActionObjective(context, current_task, original_prompt, additional_data)
|
||||
|
||||
placeholders = {
|
||||
"USER_PROMPT": combined_prompt,
|
||||
"ACTION_OBJECTIVE": action_objective, # AI-generated intelligent objective
|
||||
"AVAILABLE_DOCUMENTS": extractFullDocumentContext(self.services, context),
|
||||
"USER_LANGUAGE": extractUserLanguageFromService(self.services),
|
||||
"AVAILABLE_CONNECTIONS": extractFullConnectionContext(self.services),
|
||||
"PREVIOUS_ACTION_RESULTS": extractPreviousActionResults(context),
|
||||
"LEARNINGS_AND_IMPROVEMENTS": extractLearningsAndImprovements(context),
|
||||
"LATEST_REFINEMENT_FEEDBACK": extractLatestRefinementFeedback(context),
|
||||
}
|
||||
|
||||
# Add additional data if provided (e.g., selected action, action signature)
|
||||
if additional_data:
|
||||
placeholders.update(additional_data)
|
||||
|
||||
return placeholders
|
||||
elif phase == WorkflowPhase.ACTION_PLANNING:
|
||||
return {
|
||||
"USER_PROMPT": extractUserPromptFromService(self.services),
|
||||
"AVAILABLE_DOCUMENTS": extractFullDocumentContext(self.services, context),
|
||||
"WORKFLOW_HISTORY": extractWorkflowHistory(self.services, context),
|
||||
"AVAILABLE_METHODS": extractAvailableMethods(self.services),
|
||||
"AVAILABLE_CONNECTIONS": extractFullConnectionContext(self.services),
|
||||
"USER_LANGUAGE": extractUserLanguageFromService(self.services),
|
||||
}
|
||||
elif phase == WorkflowPhase.RESULT_REVIEW:
|
||||
return {
|
||||
"USER_PROMPT": extractUserPromptFromService(self.services),
|
||||
"REVIEW_CONTENT": extractReviewContent(context),
|
||||
}
|
||||
else:
|
||||
logger.warning(f"Unknown workflow phase: {phase}")
|
||||
return {
|
||||
"USER_PROMPT": extractUserPromptFromService(self.services),
|
||||
"USER_LANGUAGE": extractUserLanguageFromService(self.services),
|
||||
}
|
||||
|
||||
async def _generateActionObjective(self, context: Any, current_task: str, original_prompt: str, additional_data: Dict[str, Any] = None) -> str:
|
||||
"""Generate intelligent, context-aware action objective using AI."""
|
||||
try:
|
||||
# Get the selected action from additional_data
|
||||
selected_action = additional_data.get('SELECTED_ACTION', '') if additional_data else ''
|
||||
|
||||
# Build context for AI objective generation
|
||||
context_info = {
|
||||
"original_prompt": original_prompt,
|
||||
"current_task": current_task,
|
||||
"selected_action": selected_action,
|
||||
"available_documents": extractFullDocumentContext(self.services, context),
|
||||
"available_connections": extractFullConnectionContext(self.services),
|
||||
"previous_results": extractPreviousActionResults(context),
|
||||
"learnings": extractLearningsAndImprovements(context),
|
||||
"refinement_feedback": extractLatestRefinementFeedback(context),
|
||||
"user_language": extractUserLanguageFromService(self.services)
|
||||
}
|
||||
|
||||
# Create AI prompt for objective generation
|
||||
objective_prompt = f"""Generate a specific, actionable objective for the selected action.
|
||||
|
||||
CONTEXT:
|
||||
- Original User Request: {context_info['original_prompt']}
|
||||
- Current Task: {context_info['current_task']}
|
||||
- Selected Action: {context_info['selected_action']}
|
||||
- Available Documents: {context_info['available_documents']}
|
||||
- Available Connections: {context_info['available_connections']}
|
||||
- Previous Action Results: {context_info['previous_results']}
|
||||
- Learnings and Improvements: {context_info['learnings']}
|
||||
- Latest Refinement Feedback: {context_info['refinement_feedback']}
|
||||
- User Language: {context_info['user_language']}
|
||||
|
||||
REQUIREMENTS:
|
||||
1. Create a SPECIFIC objective that tells the action exactly what to accomplish
|
||||
2. Include relevant details about documents, connections, recipients, etc.
|
||||
3. Learn from previous attempts and refinement feedback
|
||||
4. Make it actionable and concrete
|
||||
5. Focus on the user's actual intent, not just the task description
|
||||
6. If this is a retry, incorporate learnings from previous failures
|
||||
|
||||
RESPONSE FORMAT:
|
||||
Return ONLY the objective text, no explanations or formatting.
|
||||
|
||||
OBJECTIVE:"""
|
||||
|
||||
# Call AI to generate the objective
|
||||
if self.services and hasattr(self.services, 'ai'):
|
||||
options = AiCallOptions(
|
||||
operationType=OperationType.ANALYSE_CONTENT,
|
||||
priority=Priority.BALANCED,
|
||||
compressPrompt=False,
|
||||
compressContext=False,
|
||||
processingMode=ProcessingMode.ADVANCED,
|
||||
maxCost=0.01,
|
||||
maxProcessingTime=10
|
||||
)
|
||||
|
||||
response = await self.services.ai.callAi(
|
||||
prompt=objective_prompt,
|
||||
placeholders={},
|
||||
options=options
|
||||
)
|
||||
|
||||
# Extract objective from response
|
||||
if response and response.strip():
|
||||
return response.strip()
|
||||
|
||||
# Fallback to current task if AI fails
|
||||
return current_task or original_prompt
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Error generating action objective: {str(e)}")
|
||||
# Fallback to current task
|
||||
return current_task or original_prompt
|
||||
|
|
@ -1,371 +0,0 @@
|
|||
# promptFactory.py
|
||||
# Enhanced prompt factory with reusable functions
|
||||
|
||||
import json
|
||||
import logging
|
||||
import importlib
|
||||
import pkgutil
|
||||
import inspect
|
||||
from typing import Any, Dict, List
|
||||
from modules.datamodels.datamodelWorkflow import TaskContext, ReviewContext, DocumentExchange
|
||||
from modules.datamodels.datamodelChat import ChatDocument
|
||||
from modules.services.serviceGeneration.subDocumentUtility import getFileExtension
|
||||
from modules.workflows.methods.methodBase import MethodBase
|
||||
|
||||
# Set up logger
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
# Global methods catalog - moved from serviceCenter
|
||||
methods = {}
|
||||
|
||||
def discoverMethods(serviceCenter):
|
||||
"""Dynamically discover all method classes and their actions in modules methods package"""
|
||||
try:
|
||||
# Import the methods package
|
||||
methodsPackage = importlib.import_module('modules.workflows.methods')
|
||||
|
||||
# Discover all modules in the package
|
||||
for _, name, isPkg in pkgutil.iter_modules(methodsPackage.__path__):
|
||||
if not isPkg and name.startswith('method'):
|
||||
try:
|
||||
# Import the module
|
||||
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):
|
||||
# Instantiate the method
|
||||
methodInstance = item(serviceCenter)
|
||||
|
||||
# Use the actions property from MethodBase which handles @action decorator
|
||||
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
|
||||
shortName = itemName.replace('Method', '').lower()
|
||||
methods[shortName] = methodInfo
|
||||
|
||||
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 {len(methods)} method entries total")
|
||||
|
||||
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)
|
||||
|
||||
# Reusable prompt element functions
|
||||
def getAvailableDocuments(context: Any) -> str:
|
||||
"""Get available documents for prompt context"""
|
||||
try:
|
||||
if not context or not hasattr(context, 'available_documents') or not context.available_documents:
|
||||
return "No documents available"
|
||||
|
||||
documents = context.available_documents
|
||||
if not isinstance(documents, list):
|
||||
return "No documents available"
|
||||
|
||||
docList = []
|
||||
for i, doc in enumerate(documents, 1):
|
||||
if isinstance(doc, ChatDocument):
|
||||
docInfo = f"{i}. **{doc.fileName}**"
|
||||
if hasattr(doc, 'mimeType') and doc.mimeType:
|
||||
docInfo += f" ({doc.mimeType})"
|
||||
if hasattr(doc, 'size') and doc.size:
|
||||
docInfo += f" - {doc.size} bytes"
|
||||
docList.append(docInfo)
|
||||
elif isinstance(doc, dict):
|
||||
docInfo = f"{i}. **{doc.get('fileName', 'Unknown')}**"
|
||||
if doc.get('mimeType'):
|
||||
docInfo += f" ({doc['mimeType']})"
|
||||
if doc.get('size'):
|
||||
docInfo += f" - {doc['size']} bytes"
|
||||
docList.append(docInfo)
|
||||
else:
|
||||
docList.append(f"{i}. {str(doc)}")
|
||||
|
||||
return "\n".join(docList) if docList else "No documents available"
|
||||
except Exception as e:
|
||||
logger.error(f"Error getting available documents: {str(e)}")
|
||||
return "Error retrieving documents"
|
||||
|
||||
def getWorkflowHistory(services, context: Any) -> str:
|
||||
"""Get workflow history for prompt context"""
|
||||
try:
|
||||
if not context or not hasattr(context, 'workflow_id'):
|
||||
return "No workflow history available"
|
||||
|
||||
workflowId = context.workflow_id
|
||||
if not workflowId:
|
||||
return "No workflow history available"
|
||||
|
||||
# Get workflow messages
|
||||
messages = services.interfaceDbChat.getWorkflowMessages(workflowId)
|
||||
if not messages:
|
||||
return "No workflow history available"
|
||||
|
||||
# Filter for relevant messages (last 10)
|
||||
recentMessages = messages[-10:] if len(messages) > 10 else messages
|
||||
|
||||
historyList = []
|
||||
for msg in recentMessages:
|
||||
if hasattr(msg, 'role') and hasattr(msg, 'message'):
|
||||
role = "User" if msg.role == "user" else "Assistant"
|
||||
message = msg.message[:200] + "..." if len(msg.message) > 200 else msg.message
|
||||
historyList.append(f"**{role}**: {message}")
|
||||
|
||||
return "\n".join(historyList) if historyList else "No workflow history available"
|
||||
except Exception as e:
|
||||
logger.error(f"Error getting workflow history: {str(e)}")
|
||||
return "Error retrieving workflow history"
|
||||
|
||||
def getAvailableMethods(services) -> str:
|
||||
"""Get available methods for prompt context"""
|
||||
try:
|
||||
if not methods:
|
||||
discoverMethods(services)
|
||||
|
||||
return getMethodsList(services)
|
||||
except Exception as e:
|
||||
logger.error(f"Error getting available methods: {str(e)}")
|
||||
return "Error retrieving available methods"
|
||||
|
||||
def getEnhancedDocumentContext(services) -> str:
|
||||
"""Get enhanced document context with full metadata"""
|
||||
try:
|
||||
# Get all documents from the current workflow
|
||||
workflow = getattr(services, 'currentWorkflow', None)
|
||||
if not workflow or not hasattr(workflow, 'id'):
|
||||
return "No workflow context available"
|
||||
|
||||
# Get workflow documents from messages
|
||||
if not hasattr(workflow, 'messages') or not workflow.messages:
|
||||
return "No documents available"
|
||||
|
||||
# Collect all documents from all messages
|
||||
all_documents = []
|
||||
for message in workflow.messages:
|
||||
if hasattr(message, 'documents') and message.documents:
|
||||
all_documents.extend(message.documents)
|
||||
|
||||
if not all_documents:
|
||||
return "No documents available"
|
||||
|
||||
# Group documents by round/task/action for better organization
|
||||
docGroups = {}
|
||||
for message in workflow.messages:
|
||||
if hasattr(message, 'documents') and message.documents:
|
||||
round_num = getattr(message, 'roundNumber', 0)
|
||||
task_num = getattr(message, 'taskNumber', 0)
|
||||
action_num = getattr(message, 'actionNumber', 0)
|
||||
label = getattr(message, 'documentsLabel', 'results')
|
||||
|
||||
group_key = f"round{round_num}_task{task_num}_action{action_num}_{label}"
|
||||
if group_key not in docGroups:
|
||||
docGroups[group_key] = []
|
||||
docGroups[group_key].extend(message.documents)
|
||||
|
||||
# Format documents by groups with proper docList references
|
||||
docList = []
|
||||
for group_key, group_docs in docGroups.items():
|
||||
# Find the message that contains these documents to get the message ID
|
||||
message_id = None
|
||||
for message in workflow.messages:
|
||||
if hasattr(message, 'documents') and message.documents:
|
||||
round_num = getattr(message, 'roundNumber', 0)
|
||||
task_num = getattr(message, 'taskNumber', 0)
|
||||
action_num = getattr(message, 'actionNumber', 0)
|
||||
label = getattr(message, 'documentsLabel', 'results')
|
||||
msg_group_key = f"round{round_num}_task{task_num}_action{action_num}_{label}"
|
||||
|
||||
if msg_group_key == group_key:
|
||||
message_id = str(message.id)
|
||||
break
|
||||
|
||||
# Generate proper docList reference
|
||||
if message_id:
|
||||
docListRef = f"docList:{message_id}:{group_key}"
|
||||
else:
|
||||
# Fallback to direct label reference
|
||||
docListRef = group_key
|
||||
|
||||
docList.append(f"\n**{group_key}:**")
|
||||
docList.append(f"Reference: {docListRef}")
|
||||
for i, doc in enumerate(group_docs, 1):
|
||||
if isinstance(doc, ChatDocument):
|
||||
docInfo = f" {i}. **{doc.fileName}**"
|
||||
if hasattr(doc, 'mimeType') and doc.mimeType:
|
||||
docInfo += f" ({doc.mimeType})"
|
||||
if hasattr(doc, 'size') and doc.size:
|
||||
docInfo += f" - {doc.size} bytes"
|
||||
if hasattr(doc, 'created') and doc.created:
|
||||
docInfo += f" - Created: {doc.created}"
|
||||
docList.append(docInfo)
|
||||
elif isinstance(doc, dict):
|
||||
docInfo = f" {i}. **{doc.get('fileName', 'Unknown')}**"
|
||||
if doc.get('mimeType'):
|
||||
docInfo += f" ({doc['mimeType']})"
|
||||
if doc.get('size'):
|
||||
docInfo += f" - {doc['size']} bytes"
|
||||
if doc.get('created'):
|
||||
docInfo += f" - Created: {doc['created']}"
|
||||
docList.append(docInfo)
|
||||
else:
|
||||
docList.append(f" {i}. {str(doc)}")
|
||||
|
||||
return "\n".join(docList) if docList else "No documents available"
|
||||
except Exception as e:
|
||||
logger.error(f"Error getting enhanced document context: {str(e)}")
|
||||
return "Error retrieving document context"
|
||||
|
||||
def getConnectionReferenceList(services) -> List[str]:
|
||||
"""Get list of available connections"""
|
||||
try:
|
||||
# Get connections from the database
|
||||
if hasattr(services, 'interfaceDbApp') and hasattr(services, 'user'):
|
||||
userId = services.user.id
|
||||
connections = services.interfaceDbApp.getUserConnections(userId)
|
||||
if connections:
|
||||
# Format connections as reference strings
|
||||
connectionRefs = []
|
||||
for conn in connections:
|
||||
# Create reference string in format: conn_{authority}_{id}
|
||||
ref = f"conn_{conn.authority.value}_{conn.id}"
|
||||
connectionRefs.append(ref)
|
||||
return connectionRefs
|
||||
|
||||
return []
|
||||
except Exception as e:
|
||||
logger.error(f"Error getting connection reference list: {str(e)}")
|
||||
return []
|
||||
|
||||
def getUserLanguage(services) -> str:
|
||||
"""Get user language from services"""
|
||||
try:
|
||||
if hasattr(services, 'user') and hasattr(services.user, 'language'):
|
||||
return services.user.language or 'en'
|
||||
return 'en'
|
||||
except Exception as e:
|
||||
logger.error(f"Error getting user language: {str(e)}")
|
||||
return 'en'
|
||||
|
||||
def getReviewContent(context: Any) -> str:
|
||||
"""Get review content for prompt context"""
|
||||
try:
|
||||
if not context or not hasattr(context, 'observation'):
|
||||
return "No review content available"
|
||||
|
||||
observation = context.observation
|
||||
if not isinstance(observation, dict):
|
||||
return "No review content available"
|
||||
|
||||
reviewParts = []
|
||||
|
||||
# Add success status
|
||||
if 'success' in observation:
|
||||
reviewParts.append(f"Success: {observation['success']}")
|
||||
|
||||
# Add documents count
|
||||
if 'documentsCount' in observation:
|
||||
reviewParts.append(f"Documents generated: {observation['documentsCount']}")
|
||||
|
||||
# Add previews
|
||||
if 'previews' in observation and observation['previews']:
|
||||
reviewParts.append("Document previews:")
|
||||
for preview in observation['previews']:
|
||||
if isinstance(preview, dict):
|
||||
name = preview.get('name', 'Unknown')
|
||||
mimeType = preview.get('mimeType', 'Unknown')
|
||||
size = preview.get('contentSize', 'Unknown size')
|
||||
reviewParts.append(f" - {name} ({mimeType}) - {size}")
|
||||
|
||||
# Add notes
|
||||
if 'notes' in observation and observation['notes']:
|
||||
reviewParts.append("Notes:")
|
||||
for note in observation['notes']:
|
||||
reviewParts.append(f" - {note}")
|
||||
|
||||
return "\n".join(reviewParts) if reviewParts else "No review content available"
|
||||
except Exception as e:
|
||||
logger.error(f"Error getting review content: {str(e)}")
|
||||
return "Error retrieving review content"
|
||||
|
||||
def getPreviousRoundContext(services, context: Any) -> str:
|
||||
"""Get previous round context for prompt"""
|
||||
try:
|
||||
if not context or not hasattr(context, 'workflow_id'):
|
||||
return "No previous round context available"
|
||||
|
||||
workflowId = context.workflow_id
|
||||
if not workflowId:
|
||||
return "No previous round context available"
|
||||
|
||||
# Get previous round results
|
||||
previousResults = getattr(context, 'previous_results', [])
|
||||
if not previousResults:
|
||||
return "No previous round context available"
|
||||
|
||||
contextList = []
|
||||
for i, result in enumerate(previousResults, 1):
|
||||
if hasattr(result, 'success') and hasattr(result, 'resultLabel'):
|
||||
status = "Success" if result.success else "Failed"
|
||||
contextList.append(f"{i}. {result.resultLabel} - {status}")
|
||||
elif isinstance(result, dict):
|
||||
status = "Success" if result.get('success', False) else "Failed"
|
||||
label = result.get('resultLabel', 'Unknown')
|
||||
contextList.append(f"{i}. {label} - {status}")
|
||||
else:
|
||||
contextList.append(f"{i}. {str(result)}")
|
||||
|
||||
return "\n".join(contextList) if contextList else "No previous round context available"
|
||||
except Exception as e:
|
||||
logger.error(f"Error getting previous round context: {str(e)}")
|
||||
return "Error retrieving previous round context"
|
||||
|
|
@ -1,673 +0,0 @@
|
|||
"""
|
||||
Placeholder-based prompt factory for dynamic AI calls.
|
||||
This module provides prompt templates with placeholders that can be filled dynamically.
|
||||
"""
|
||||
|
||||
import json
|
||||
import logging
|
||||
from typing import Dict, Any
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
from modules.workflows.processing.shared.promptFactory import (
|
||||
getAvailableDocuments,
|
||||
getPreviousRoundContext,
|
||||
getMethodsList,
|
||||
getEnhancedDocumentContext,
|
||||
getConnectionReferenceList,
|
||||
methods,
|
||||
discoverMethods
|
||||
)
|
||||
|
||||
|
||||
def createTaskPlanningPromptTemplate() -> str:
|
||||
"""Create task planning prompt template with placeholders."""
|
||||
return """# Task Planning
|
||||
|
||||
Break down user requests into logical, executable task steps.
|
||||
|
||||
## 📋 Context
|
||||
|
||||
### User Request
|
||||
{{KEY:USER_PROMPT}}
|
||||
|
||||
### Available Documents
|
||||
{{KEY:AVAILABLE_DOCUMENTS}}
|
||||
|
||||
### Previous Workflow Rounds
|
||||
{{KEY:WORKFLOW_HISTORY}}
|
||||
|
||||
## 📝 Task Planning Rules
|
||||
|
||||
### Strategic Task Grouping
|
||||
- **GROUP RELATED ACTIONS** - Combine all actions for the same business topic into ONE task
|
||||
- **ONE TOPIC PER TASK** - Each task should handle one complete business objective
|
||||
- **HIGH-LEVEL FOCUS** - Plan strategic outcomes, not implementation steps
|
||||
- **AVOID MICRO-TASKS** - Don't create separate tasks for each small action
|
||||
|
||||
### Task Grouping Examples
|
||||
- **Research + Analysis + Report** → ONE task: "Web research report"
|
||||
- **Data Collection + Processing + Visualization** → ONE task: "Collect and present data"
|
||||
- **Different topics** (email + flowers) → SEPARATE tasks: "Send formal email..." + "Order flowers from Fleurop for delivery to 123 Main St, include card message"
|
||||
|
||||
### Retry Handling
|
||||
- **If retry request**: Analyze previous rounds to understand what failed
|
||||
- **Learn from mistakes**: Improve the plan based on previous failures
|
||||
|
||||
## 📊 Required JSON Structure
|
||||
|
||||
```json
|
||||
{
|
||||
"overview": "Brief description of the overall plan",
|
||||
"languageUserDetected": "en",
|
||||
"userMessage": "User-friendly message explaining the task plan",
|
||||
"tasks": [
|
||||
{
|
||||
"id": "task_1",
|
||||
"objective": "Clear business objective focusing on what to deliver",
|
||||
"dependencies": ["task_0"],
|
||||
"success_criteria": ["measurable criteria 1", "measurable criteria 2"],
|
||||
"estimated_complexity": "low|medium|high",
|
||||
"userMessage": "What this task will accomplish"
|
||||
}
|
||||
]
|
||||
}
|
||||
```
|
||||
|
||||
## 🎯 Task Structure Guidelines
|
||||
|
||||
### Task ID Format
|
||||
- Use sequential numbering: `task_1`, `task_2`, `task_3`
|
||||
- Keep IDs simple and clear
|
||||
|
||||
### Objective Writing
|
||||
- **Be VERY SPECIFIC** - Include exact details needed for action planning
|
||||
- **Include all requirements** - recipient, attachments, format, recipients, etc.
|
||||
- **State the complete deliverable** - What exactly will be produced
|
||||
- **Include context and constraints** - When, where, how, with what
|
||||
- **Make it actionable** - Clear enough to plan specific actions
|
||||
|
||||
### Specific Objective Examples
|
||||
- **Good**: "Send formal email to ceo and board of directors with annual report as attachment"
|
||||
- **Bad**: "Handle email communication"
|
||||
- **Good**: "Order flowers from Fleurop for delivery to 123 Main St, include card message 'Happy Birthday', deliver on March 15th"
|
||||
- **Bad**: "Order flowers"
|
||||
|
||||
### Action Planning Requirements
|
||||
- **Include all necessary details** - The objective must contain everything needed to plan actions
|
||||
- **Specify recipients and destinations** - Who should receive what
|
||||
- **Include file names and formats** - What documents to use/create
|
||||
- **State timing and deadlines** - When things need to be done
|
||||
- **Include context and constraints** - Any special requirements or limitations
|
||||
|
||||
### Success Criteria
|
||||
- **Make them measurable** - specific, quantifiable outcomes
|
||||
- **Focus on deliverables** - what the user will receive
|
||||
- **Keep criteria realistic** - achievable within the task scope
|
||||
- **Include all related actions** - success means completing the entire business objective
|
||||
- **Be specific about requirements** - Include exact details like recipients, formats, deadlines
|
||||
- **State clear completion criteria** - How to know the task is fully done
|
||||
|
||||
### Complexity Estimation
|
||||
- **Low**: Simple, single-action tasks (1-2 actions)
|
||||
- **Medium**: Multi-action tasks for one topic (3-5 actions)
|
||||
- **High**: Complex strategic tasks (6+ actions)
|
||||
|
||||
## 🚀 Response Format
|
||||
Return ONLY the JSON object."""
|
||||
|
||||
|
||||
def createActionDefinitionPromptTemplate() -> str:
|
||||
"""Create action definition prompt template with placeholders."""
|
||||
return """# Action Definition
|
||||
|
||||
Generate the next action to advance toward completing the task objective.
|
||||
|
||||
## 📋 Context
|
||||
|
||||
### Task Objective
|
||||
{{KEY:USER_PROMPT}}
|
||||
|
||||
### Available Documents
|
||||
{{KEY:AVAILABLE_DOCUMENTS}}
|
||||
|
||||
### Workflow History
|
||||
{{KEY:WORKFLOW_HISTORY}}
|
||||
|
||||
### Available Methods
|
||||
{{KEY:AVAILABLE_METHODS}}
|
||||
|
||||
### Available Connections
|
||||
{{KEY:AVAILABLE_CONNECTIONS}}
|
||||
|
||||
### User Language
|
||||
{{KEY:USER_LANGUAGE}}
|
||||
|
||||
## ⚠️ RULES
|
||||
|
||||
### Action Names
|
||||
- **Use EXACT compound action names** from AVAILABLE_METHODS (e.g., "ai.process", "document.extract", "web.search")
|
||||
- **DO NOT create** new action names - only use those listed in AVAILABLE_METHODS
|
||||
- **DO NOT separate** method and action names - use the full compound name
|
||||
|
||||
### Parameter Guidelines
|
||||
- **Use exact document references** from AVAILABLE_DOCUMENTS
|
||||
- **Use exact connection references** from AVAILABLE_CONNECTIONS
|
||||
- **Include user language** if relevant
|
||||
- **Avoid unnecessary fields** - host applies defaults
|
||||
|
||||
## 📊 Required JSON Structure
|
||||
|
||||
```json
|
||||
{
|
||||
"actions": [
|
||||
{
|
||||
"action": "method.action_name",
|
||||
"parameters": {},
|
||||
"resultLabel": "round{current_round}_task{current_task}_action{action_number}_{descriptive_label}",
|
||||
"description": "What this action accomplishes",
|
||||
"userMessage": "User-friendly message in {{KEY:USER_LANGUAGE}}"
|
||||
}
|
||||
]
|
||||
}
|
||||
```
|
||||
|
||||
## ✅ Correct Example
|
||||
|
||||
```json
|
||||
{
|
||||
"actions": [
|
||||
{
|
||||
"action": "document.extract",
|
||||
"parameters": {"documentList": ["docList:msg_123:results"]},
|
||||
"resultLabel": "round1_task1_action1_extract_results",
|
||||
"description": "Extract data from documents",
|
||||
"userMessage": "Extracting data from documents"
|
||||
}
|
||||
]
|
||||
}
|
||||
```
|
||||
|
||||
|
||||
## 🎯 Action Planning Guidelines
|
||||
|
||||
### Method Selection
|
||||
- **Choose appropriate method** based on task requirements
|
||||
- **Consider available resources** (documents, connections)
|
||||
- **Match method capabilities** to task objectives
|
||||
|
||||
### Parameter Design
|
||||
- **Use ACTION SIGNATURE** to understand required parameters
|
||||
- **Convert objective** into appropriate parameter values
|
||||
- **Include all required parameters** for the action
|
||||
|
||||
### Result Labeling
|
||||
- **Use descriptive labels** that explain what the action produces
|
||||
- **Follow naming convention**: `round{round}_task{task}_action{action}_{label}`
|
||||
- **Make labels meaningful** for future reference
|
||||
|
||||
### User Messages
|
||||
- **Write in user language** ({{KEY:USER_LANGUAGE}})
|
||||
- **Explain what's happening** in user-friendly terms
|
||||
- **Keep messages concise** but informative
|
||||
|
||||
## 🚀 Response Format
|
||||
Return ONLY the JSON object."""
|
||||
|
||||
|
||||
def createActionSelectionPromptTemplate() -> str:
|
||||
"""Create action selection prompt template with placeholders."""
|
||||
return """# Action Selection
|
||||
|
||||
Select exactly one action to advance the task.
|
||||
|
||||
## 📋 Context
|
||||
|
||||
### Objective
|
||||
{{KEY:USER_PROMPT}}
|
||||
|
||||
### Available Documents
|
||||
{{KEY:AVAILABLE_DOCUMENTS}}
|
||||
|
||||
### User Language
|
||||
{{KEY:USER_LANGUAGE}}
|
||||
|
||||
### Available Methods
|
||||
{{KEY:AVAILABLE_METHODS}}
|
||||
|
||||
## ⚠️ CRITICAL RULES
|
||||
|
||||
### Selection Requirements
|
||||
- **Return ONLY the compound action name**
|
||||
- **Do NOT include parameters or prompts**
|
||||
- **Use EXACT compound action names** from AVAILABLE_METHODS above
|
||||
- **DO NOT create** new action names
|
||||
|
||||
### Action Format
|
||||
- **Compound action names**: Use exact names from AVAILABLE_METHODS (e.g., "ai.process", "document.extract", "web.search")
|
||||
- **Single field format**: Use the full compound action name as a single string
|
||||
|
||||
## 📝 Required JSON Format
|
||||
|
||||
```json
|
||||
{"action":"method.action_name"}
|
||||
```
|
||||
|
||||
## ✅ Correct Examples
|
||||
|
||||
```json
|
||||
{"action":"ai.process"}
|
||||
{"action":"document.extract"}
|
||||
{"action":"web.search"}
|
||||
```
|
||||
|
||||
|
||||
## 🎯 Selection Guidelines
|
||||
|
||||
### Choose Appropriate Action
|
||||
- **Match action to objective** - select the most relevant action
|
||||
- **Consider available resources** - ensure required documents/connections are available
|
||||
- **Think about the next step** - what action will advance the task
|
||||
|
||||
### Method Selection
|
||||
- **AI methods**: For processing, analysis, or generation tasks
|
||||
- **Document methods**: For document operations (extract, generate, etc.)
|
||||
- **Web methods**: For web searches or external data retrieval
|
||||
- **Other methods**: Based on specific requirements
|
||||
|
||||
## 🚀 Response Format
|
||||
Return ONLY the JSON object."""
|
||||
|
||||
|
||||
def createActionParameterPromptTemplate() -> str:
|
||||
"""Create action parameter prompt template with placeholders."""
|
||||
return """# Action Parameter Generation
|
||||
|
||||
You are an AI assistant tasked with generating parameters for a selected action.
|
||||
|
||||
## 🎯 Your Goal
|
||||
Provide the EXACT parameters required by the ACTION SIGNATURE, using information from the OBJECTIVE, AVAILABLE DOCUMENTS, and AVAILABLE CONNECTIONS.
|
||||
|
||||
## ⚠️ CRITICAL RULES
|
||||
- **MUST respond with a JSON object**
|
||||
- **All parameters MUST be wrapped in a "parameters" object**
|
||||
- **ONLY include parameters listed in the ACTION SIGNATURE**
|
||||
- **Do NOT use code blocks or markdown in your response**
|
||||
- **Return ONLY the JSON object**
|
||||
|
||||
## 📋 Document & Connection References
|
||||
- **Document references**: Copy the EXACT reference string from AVAILABLE DOCUMENTS (e.g., `docList:msg_UUID:label`)
|
||||
- **Connection references**: Copy the EXACT reference string from AVAILABLE CONNECTIONS (e.g., `connection:msft:user@domain.com:uuid [status:active, token:valid]`)
|
||||
- **Do NOT invent, shorten, or modify any references**
|
||||
- **If unsure**: Use "UNCLEAR_REFERENCE" or "UNCLEAR_OBJECTIVE" and explain in a comment
|
||||
|
||||
## 📝 Input Context
|
||||
|
||||
### Selected Action
|
||||
{{KEY:SELECTED_ACTION}}
|
||||
|
||||
### Objective
|
||||
{{KEY:USER_PROMPT}}
|
||||
|
||||
### Available Documents
|
||||
{{KEY:AVAILABLE_DOCUMENTS}}
|
||||
|
||||
### Available Connections
|
||||
{{KEY:AVAILABLE_CONNECTIONS}}
|
||||
|
||||
### User Language
|
||||
{{KEY:USER_LANGUAGE}}
|
||||
|
||||
### Action Requirements
|
||||
{{KEY:ACTION_SIGNATURE}}
|
||||
|
||||
## 📚 Reference Types
|
||||
|
||||
### Document References
|
||||
- **docItem**: Reference to a single document (e.g., "docItem:uuid:filename.pdf")
|
||||
- **docList**: Reference to a group of documents (e.g., "docList:msg_123:AnalysisResults")
|
||||
- **Use EXACT reference strings** shown in AVAILABLE_DOCUMENTS
|
||||
|
||||
### Connection References
|
||||
- **Use exact connection references** from AVAILABLE CONNECTIONS
|
||||
- **Examples**: "connection:msft:user@domain.com:uuid [status:active, token:valid]", "connection:sp:user@domain.com:uuid [status:active, token:valid]"
|
||||
|
||||
## 💡 Basic Examples
|
||||
|
||||
```json
|
||||
{"parameters":{"aiPrompt": "Summarize the document"}}
|
||||
{"parameters":{"documentList": ["docList:msg_UUID:label"]}}
|
||||
{"parameters":{"connectionReference": "connection:msft:user@domain.com:uuid [status:active, token:valid]"}}
|
||||
```
|
||||
|
||||
## ❌ Wrong Format (DO NOT USE)
|
||||
|
||||
```json
|
||||
{"aiPrompt": "Your prompt here"}
|
||||
```
|
||||
|
||||
```json
|
||||
{"parameters":{"aiPrompt": "Your prompt here"}}
|
||||
```
|
||||
|
||||
## 🎯 Parameter Guidelines
|
||||
|
||||
### Required Parameters
|
||||
- **Use ACTION SIGNATURE** to understand what parameters are required
|
||||
- **Convert objective** into appropriate parameter values
|
||||
- **Include user language** if relevant
|
||||
- **Avoid unnecessary fields** - host applies defaults
|
||||
|
||||
### Document Reference Rules
|
||||
- **ONLY use exact document reference strings** from AVAILABLE_DOCUMENTS
|
||||
- **DO NOT add file paths** or individual filenames to document references
|
||||
- **For documentList parameters**: Use the EXACT reference strings shown in AVAILABLE_DOCUMENTS
|
||||
|
||||
### Connection Reference Rules
|
||||
- **ONLY use exact connection references** from AVAILABLE CONNECTIONS
|
||||
- **For connectionReference parameters**: Use the exact connection reference from AVAILABLE CONNECTIONS
|
||||
|
||||
## 🚀 Response Format
|
||||
Return your JSON response immediately after this prompt."""
|
||||
|
||||
|
||||
def createRefinementPromptTemplate() -> str:
|
||||
"""Create refinement prompt template with placeholders."""
|
||||
return """# Workflow Refinement Decision
|
||||
|
||||
Decide the next step based on the observation.
|
||||
|
||||
## 📋 Context
|
||||
|
||||
### Objective
|
||||
{{KEY:USER_PROMPT}}
|
||||
|
||||
### Observation
|
||||
{{KEY:REVIEW_CONTENT}}
|
||||
|
||||
## ⚠️ CRITICAL RULES
|
||||
|
||||
### Data Requirements
|
||||
- **If user wants DATA** (numbers, lists, calculations): Ensure AI delivers the actual data, not code
|
||||
- **If user wants DOCUMENTS** (Word, PDF, Excel): Ensure appropriate method is used to create the document
|
||||
- **If user wants ANALYSIS**: Ensure AI analyzes and delivers insights
|
||||
- **NEVER accept code when user wants data** - demand the actual data
|
||||
- **NEVER accept algorithms when user wants results** - demand the actual results
|
||||
|
||||
## 🤔 Decision Rules
|
||||
|
||||
### Continue Conditions
|
||||
- The objective is **NOT fulfilled** (user didn't get what they asked for)
|
||||
- More data or processing is needed
|
||||
- The current result is incomplete
|
||||
|
||||
### Stop Conditions
|
||||
- The objective is **fulfilled** (user got what they asked for)
|
||||
- All required data has been delivered
|
||||
- The task is complete
|
||||
|
||||
### Focus
|
||||
- Focus on what the user actually wants, not what was delivered
|
||||
- Consider the user's original request carefully
|
||||
|
||||
## 📝 Response Format
|
||||
|
||||
```json
|
||||
{"decision":"continue","reason":"Need more data"}
|
||||
```
|
||||
|
||||
### Decision Options
|
||||
- `"continue"` - Keep working on the objective
|
||||
- `"stop"` - Objective has been fulfilled
|
||||
|
||||
### Reason Examples
|
||||
- `"Need more data"`
|
||||
- `"Objective fulfilled"`
|
||||
- `"User got the requested document"`
|
||||
- `"Analysis complete"`
|
||||
|
||||
## 🎯 Decision Guidelines
|
||||
|
||||
### When to Continue
|
||||
- **Incomplete results** - User didn't get what they asked for
|
||||
- **Missing data** - Need to gather more information
|
||||
- **Partial success** - Some but not all requirements met
|
||||
- **Technical issues** - Action failed and needs retry
|
||||
|
||||
### When to Stop
|
||||
- **Complete success** - User got exactly what they asked for
|
||||
- **All criteria met** - Success criteria have been achieved
|
||||
- **Document created** - Required document has been generated
|
||||
- **Data delivered** - All requested data has been provided
|
||||
|
||||
### Quality Assessment
|
||||
- **Check completeness** - Is the result complete?
|
||||
- **Verify accuracy** - Is the data correct?
|
||||
- **Assess usefulness** - Does it meet the user's needs?
|
||||
- **Consider format** - Is it in the requested format?
|
||||
|
||||
## 🚀 Response Format
|
||||
Return your JSON response immediately after this prompt."""
|
||||
|
||||
|
||||
def createResultReviewPromptTemplate() -> str:
|
||||
"""Create result review prompt template with placeholders."""
|
||||
return """# Result Review & Validation
|
||||
|
||||
Review task execution outcomes and determine success, retry needs, or failure.
|
||||
|
||||
## 📋 Context
|
||||
|
||||
### Task Objective
|
||||
{{KEY:USER_PROMPT}}
|
||||
|
||||
### Execution Results
|
||||
{{KEY:REVIEW_CONTENT}}
|
||||
|
||||
## 🔍 Validation Criteria
|
||||
|
||||
### Action Assessment
|
||||
- **Review each action's success/failure status**
|
||||
- **Check if required documents were produced**
|
||||
- **Validate document quality and completeness**
|
||||
- **Assess if success criteria were met**
|
||||
- **Identify any missing or incomplete outputs**
|
||||
|
||||
### Decision Making
|
||||
- **Determine if retry would help** or if task should be marked as failed
|
||||
- **Consider business value** and user satisfaction
|
||||
- **Evaluate technical execution** and results quality
|
||||
|
||||
## 📊 Required JSON Structure
|
||||
|
||||
```json
|
||||
{
|
||||
"status": "success|retry|failed",
|
||||
"reason": "Detailed explanation of the validation decision",
|
||||
"improvements": ["specific improvement 1", "specific improvement 2"],
|
||||
"quality_score": 8,
|
||||
"met_criteria": ["criteria1", "criteria2"],
|
||||
"unmet_criteria": ["criteria3", "criteria4"],
|
||||
"confidence": 0.85,
|
||||
"userMessage": "User-friendly message explaining the validation result"
|
||||
}
|
||||
```
|
||||
|
||||
## 🎯 Validation Principles
|
||||
|
||||
### Assessment Approach
|
||||
- **Be thorough but fair** in assessment
|
||||
- **Focus on business value** and outcomes
|
||||
- **Consider both technical execution** and business results
|
||||
- **Provide specific, actionable** improvement suggestions
|
||||
|
||||
### Quality Scoring
|
||||
- **Use quality scores** to track progress across retries
|
||||
- **Scale 1-10**: 1 = Poor, 5 = Average, 10 = Excellent
|
||||
- **Consider completeness, accuracy, and usefulness**
|
||||
|
||||
### Criteria Evaluation
|
||||
- **Clearly identify** which success criteria were met vs. unmet
|
||||
- **List specific criteria** that were achieved
|
||||
- **Note missing requirements** that need attention
|
||||
|
||||
### Confidence Levels
|
||||
- **Set appropriate confidence levels** based on evidence quality
|
||||
- **Scale 0.0-1.0**: 0.0 = No confidence, 1.0 = Complete confidence
|
||||
- **Consider data quality** and result reliability
|
||||
|
||||
## 📝 Status Definitions
|
||||
|
||||
### Success
|
||||
- **All objectives met** - User got what they asked for
|
||||
- **Quality standards met** - Results are complete and accurate
|
||||
- **No retry needed** - Task is fully complete
|
||||
|
||||
### Retry
|
||||
- **Partial success** - Some but not all objectives met
|
||||
- **Improvement possible** - Retry could lead to better results
|
||||
- **Technical issues** - Action failures that can be resolved
|
||||
|
||||
### Failed
|
||||
- **No progress made** - Objectives not achieved
|
||||
- **Technical limitations** - Cannot be resolved with retry
|
||||
- **Resource constraints** - Missing required inputs
|
||||
|
||||
## 💡 Improvement Suggestions
|
||||
|
||||
### Actionable Improvements
|
||||
- **Be specific** - Don't just say "improve quality"
|
||||
- **Focus on process** - How to do better next time
|
||||
- **Consider resources** - What additional inputs might help
|
||||
- **Technical fixes** - Address specific technical issues
|
||||
|
||||
### Examples
|
||||
- "Use more specific document references from AVAILABLE_DOCUMENTS"
|
||||
- "Include user language parameter for better localization"
|
||||
- "Break down complex objective into smaller, focused actions"
|
||||
- "Verify document references before processing"
|
||||
|
||||
## 🚀 Response Format
|
||||
Return ONLY the JSON object. Do not include any explanatory text."""
|
||||
|
||||
|
||||
# Helper functions to extract content for placeholders
|
||||
|
||||
def extractUserPrompt(context) -> str:
|
||||
"""Extract user prompt from context."""
|
||||
if hasattr(context, 'task_step') and context.task_step:
|
||||
return context.task_step.objective or 'No request specified'
|
||||
return 'No request specified'
|
||||
|
||||
|
||||
def extractAvailableDocuments(context) -> str:
|
||||
"""Extract available documents from context."""
|
||||
if hasattr(context, 'available_documents') and context.available_documents:
|
||||
return context.available_documents
|
||||
return "No documents available"
|
||||
|
||||
|
||||
def extractWorkflowHistory(service, context) -> str:
|
||||
"""Extract workflow history from context."""
|
||||
if hasattr(context, 'workflow') and context.workflow:
|
||||
return getPreviousRoundContext(service, context.workflow) or "No previous workflow rounds - this is the first round."
|
||||
return "No previous workflow rounds - this is the first round."
|
||||
|
||||
|
||||
def extractAvailableMethods(service) -> str:
|
||||
"""Extract available methods for action planning using compound action names."""
|
||||
try:
|
||||
# Get the methods dictionary directly from the global methods variable
|
||||
if not methods:
|
||||
discoverMethods(service)
|
||||
|
||||
# Create a flat JSON format with compound action names for better AI parsing
|
||||
available_actions_json = {}
|
||||
for methodName, methodInfo in methods.items():
|
||||
# Convert MethodAi -> ai, MethodDocument -> document, etc.
|
||||
shortName = methodName.replace('Method', '').lower()
|
||||
|
||||
for actionName, actionInfo in methodInfo['actions'].items():
|
||||
# Create compound action name: method.action
|
||||
compoundActionName = f"{shortName}.{actionName}"
|
||||
# Get the action description
|
||||
action_description = actionInfo.get('description', f"Execute {actionName} action")
|
||||
available_actions_json[compoundActionName] = action_description
|
||||
|
||||
return json.dumps(available_actions_json, indent=2, ensure_ascii=False)
|
||||
except Exception as e:
|
||||
logger.error(f"Error extracting available methods: {str(e)}")
|
||||
return json.dumps({}, indent=2, ensure_ascii=False)
|
||||
|
||||
|
||||
def extractUserLanguage(service) -> str:
|
||||
"""Extract user language from service."""
|
||||
return service.user.language if service and service.user else 'en'
|
||||
|
||||
|
||||
def extractReviewContent(context) -> str:
|
||||
"""Extract review content from context with full document metadata."""
|
||||
if hasattr(context, 'action_results') and context.action_results:
|
||||
# Build result summary
|
||||
result_summary = ""
|
||||
for i, result in enumerate(context.action_results):
|
||||
result_summary += f"\nRESULT {i+1}:\n"
|
||||
result_summary += f" Success: {result.success}\n"
|
||||
if result.error:
|
||||
result_summary += f" Error: {result.error}\n"
|
||||
|
||||
if result.documents:
|
||||
result_summary += f" Documents: {len(result.documents)} document(s)\n"
|
||||
for doc in result.documents:
|
||||
# Extract all available metadata without content
|
||||
doc_metadata = {
|
||||
"name": getattr(doc, 'documentName', 'Unknown'),
|
||||
"mimeType": getattr(doc, 'mimeType', 'Unknown'),
|
||||
"size": getattr(doc, 'size', 'Unknown'),
|
||||
"created": getattr(doc, 'created', 'Unknown'),
|
||||
"modified": getattr(doc, 'modified', 'Unknown'),
|
||||
"typeGroup": getattr(doc, 'typeGroup', 'Unknown'),
|
||||
"documentId": getattr(doc, 'documentId', 'Unknown'),
|
||||
"reference": getattr(doc, 'reference', 'Unknown')
|
||||
}
|
||||
# Remove 'Unknown' values to keep it clean
|
||||
doc_metadata = {k: v for k, v in doc_metadata.items() if v != 'Unknown'}
|
||||
result_summary += f" - {json.dumps(doc_metadata, indent=6, ensure_ascii=False)}\n"
|
||||
else:
|
||||
result_summary += f" Documents: None\n"
|
||||
|
||||
return result_summary
|
||||
elif hasattr(context, 'observation') and context.observation:
|
||||
# For observation data, show full content but handle documents specially
|
||||
if isinstance(context.observation, dict):
|
||||
# Create a copy to modify
|
||||
obs_copy = context.observation.copy()
|
||||
|
||||
# If there are previews with documents, show only metadata
|
||||
if 'previews' in obs_copy and isinstance(obs_copy['previews'], list):
|
||||
for preview in obs_copy['previews']:
|
||||
if isinstance(preview, dict) and 'snippet' in preview:
|
||||
# Replace snippet with metadata indicator
|
||||
preview['snippet'] = f"[Content: {len(preview.get('snippet', ''))} characters]"
|
||||
|
||||
return json.dumps(obs_copy, indent=2, ensure_ascii=False)
|
||||
else:
|
||||
return json.dumps(context.observation, ensure_ascii=False)
|
||||
elif hasattr(context, 'step_result') and context.step_result and 'observation' in context.step_result:
|
||||
# For observation data in step_result, show full content but handle documents specially
|
||||
observation = context.step_result['observation']
|
||||
if isinstance(observation, dict):
|
||||
# Create a copy to modify
|
||||
obs_copy = observation.copy()
|
||||
|
||||
# If there are previews with documents, show only metadata
|
||||
if 'previews' in obs_copy and isinstance(obs_copy['previews'], list):
|
||||
for preview in obs_copy['previews']:
|
||||
if isinstance(preview, dict) and 'snippet' in preview:
|
||||
# Replace snippet with metadata indicator
|
||||
preview['snippet'] = f"[Content: {len(preview.get('snippet', ''))} characters]"
|
||||
|
||||
return json.dumps(obs_copy, indent=2, ensure_ascii=False)
|
||||
else:
|
||||
return json.dumps(observation, ensure_ascii=False)
|
||||
else:
|
||||
return "No review content available"
|
||||
|
|
@ -0,0 +1,208 @@
|
|||
"""
|
||||
Actionplan Mode Prompt Generation
|
||||
Handles prompt templates and extraction functions for actionplan mode action handling.
|
||||
"""
|
||||
|
||||
import json
|
||||
import logging
|
||||
from typing import Dict, Any
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
def createActionDefinitionPromptTemplate() -> str:
|
||||
"""Create action definition prompt template with placeholders."""
|
||||
return """# Action Definition
|
||||
|
||||
Generate the next action to advance toward completing the task objective.
|
||||
|
||||
## 📋 Context
|
||||
|
||||
### Task Objective
|
||||
{{KEY:USER_PROMPT}}
|
||||
|
||||
### Available Documents
|
||||
{{KEY:AVAILABLE_DOCUMENTS}}
|
||||
|
||||
### Workflow History
|
||||
{{KEY:WORKFLOW_HISTORY}}
|
||||
|
||||
### Available Methods
|
||||
{{KEY:AVAILABLE_METHODS}}
|
||||
|
||||
### Available Connections
|
||||
{{KEY:AVAILABLE_CONNECTIONS}}
|
||||
|
||||
### User Language
|
||||
{{KEY:USER_LANGUAGE}}
|
||||
|
||||
## ⚠️ RULES
|
||||
|
||||
### Action Names
|
||||
- **Use EXACT compound action names** from AVAILABLE_METHODS (e.g., "ai.process", "document.extract", "web.search")
|
||||
- **DO NOT create** new action names - only use those listed in AVAILABLE_METHODS
|
||||
- **DO NOT separate** method and action names - use the full compound name
|
||||
|
||||
### Parameter Guidelines
|
||||
- **Use exact document references** from AVAILABLE_DOCUMENTS
|
||||
- **Use exact connection references** from AVAILABLE_CONNECTIONS
|
||||
- **Include user language** if relevant
|
||||
- **Avoid unnecessary fields** - host applies defaults
|
||||
|
||||
## 📊 Required JSON Structure
|
||||
|
||||
```json
|
||||
{
|
||||
"actions": [
|
||||
{
|
||||
"action": "method.action_name",
|
||||
"parameters": {},
|
||||
"resultLabel": "round{current_round}_task{current_task}_action{action_number}_{descriptive_label}",
|
||||
"description": "What this action accomplishes",
|
||||
"userMessage": "User-friendly message in {{KEY:USER_LANGUAGE}}"
|
||||
}
|
||||
]
|
||||
}
|
||||
```
|
||||
|
||||
## ✅ Correct Example
|
||||
|
||||
```json
|
||||
{
|
||||
"actions": [
|
||||
{
|
||||
"action": "document.extract",
|
||||
"parameters": {"documentList": ["docList:msg_123:results"]},
|
||||
"resultLabel": "round1_task1_action1_extract_results",
|
||||
"description": "Extract data from documents",
|
||||
"userMessage": "Extracting data from documents"
|
||||
}
|
||||
]
|
||||
}
|
||||
```
|
||||
|
||||
|
||||
## 🎯 Action Planning Guidelines
|
||||
|
||||
### Method Selection
|
||||
- **Choose appropriate method** based on task requirements
|
||||
- **Consider available resources** (documents, connections)
|
||||
- **Match method capabilities** to task objectives
|
||||
|
||||
### Parameter Design
|
||||
- **Use ACTION SIGNATURE** to understand required parameters
|
||||
- **Convert objective** into appropriate parameter values
|
||||
- **Include all required parameters** for the action
|
||||
|
||||
### Result Labeling
|
||||
- **Use descriptive labels** that explain what the action produces
|
||||
- **Follow naming convention**: `round{round}_task{task}_action{action}_{label}`
|
||||
- **Make labels meaningful** for future reference
|
||||
|
||||
### User Messages
|
||||
- **Write in user language** ({{KEY:USER_LANGUAGE}})
|
||||
- **Explain what's happening** in user-friendly terms
|
||||
- **Keep messages concise** but informative
|
||||
|
||||
## 🚀 Response Format
|
||||
Return ONLY the JSON object."""
|
||||
|
||||
def createResultReviewPromptTemplate() -> str:
|
||||
"""Create result review prompt template with placeholders."""
|
||||
return """# Result Review & Validation
|
||||
|
||||
Review task execution outcomes and determine success, retry needs, or failure.
|
||||
|
||||
## 📋 Context
|
||||
|
||||
### Task Objective
|
||||
{{KEY:USER_PROMPT}}
|
||||
|
||||
### Execution Results
|
||||
{{KEY:REVIEW_CONTENT}}
|
||||
|
||||
## 🔍 Validation Criteria
|
||||
|
||||
### Action Assessment
|
||||
- **Review each action's success/failure status**
|
||||
- **Check if required documents were produced**
|
||||
- **Validate document quality and completeness**
|
||||
- **Assess if success criteria were met**
|
||||
- **Identify any missing or incomplete outputs**
|
||||
|
||||
### Decision Making
|
||||
- **Determine if retry would help** or if task should be marked as failed
|
||||
- **Consider business value** and user satisfaction
|
||||
- **Evaluate technical execution** and results quality
|
||||
|
||||
## 📊 Required JSON Structure
|
||||
|
||||
```json
|
||||
{
|
||||
"status": "success|retry|failed",
|
||||
"reason": "Detailed explanation of the validation decision",
|
||||
"improvements": ["specific improvement 1", "specific improvement 2"],
|
||||
"quality_score": 8,
|
||||
"met_criteria": ["criteria1", "criteria2"],
|
||||
"unmet_criteria": ["criteria3", "criteria4"],
|
||||
"confidence": 0.85,
|
||||
"userMessage": "User-friendly message explaining the validation result"
|
||||
}
|
||||
```
|
||||
|
||||
## 🎯 Validation Principles
|
||||
|
||||
### Assessment Approach
|
||||
- **Be thorough but fair** in assessment
|
||||
- **Focus on business value** and outcomes
|
||||
- **Consider both technical execution** and business results
|
||||
- **Provide specific, actionable** improvement suggestions
|
||||
|
||||
### Quality Scoring
|
||||
- **Use quality scores** to track progress across retries
|
||||
- **Scale 1-10**: 1 = Poor, 5 = Average, 10 = Excellent
|
||||
- **Consider completeness, accuracy, and usefulness**
|
||||
|
||||
### Criteria Evaluation
|
||||
- **Clearly identify** which success criteria were met vs. unmet
|
||||
- **List specific criteria** that were achieved
|
||||
- **Note missing requirements** that need attention
|
||||
|
||||
### Confidence Levels
|
||||
- **Set appropriate confidence levels** based on evidence quality
|
||||
- **Scale 0.0-1.0**: 0.0 = No confidence, 1.0 = Complete confidence
|
||||
- **Consider data quality** and result reliability
|
||||
|
||||
## 📝 Status Definitions
|
||||
|
||||
### Success
|
||||
- **All objectives met** - User got what they asked for
|
||||
- **Quality standards met** - Results are complete and accurate
|
||||
- **No retry needed** - Task is fully complete
|
||||
|
||||
### Retry
|
||||
- **Partial success** - Some but not all objectives met
|
||||
- **Improvement possible** - Retry could lead to better results
|
||||
- **Technical issues** - Action failures that can be resolved
|
||||
|
||||
### Failed
|
||||
- **No progress made** - Objectives not achieved
|
||||
- **Technical limitations** - Cannot be resolved with retry
|
||||
- **Resource constraints** - Missing required inputs
|
||||
|
||||
## 💡 Improvement Suggestions
|
||||
|
||||
### Actionable Improvements
|
||||
- **Be specific** - Don't just say "improve quality"
|
||||
- **Focus on process** - How to do better next time
|
||||
- **Consider resources** - What additional inputs might help
|
||||
- **Technical fixes** - Address specific technical issues
|
||||
|
||||
### Examples
|
||||
- "Use more specific document references from AVAILABLE_DOCUMENTS"
|
||||
- "Include user language parameter for better localization"
|
||||
- "Break down complex objective into smaller, focused actions"
|
||||
- "Verify document references before processing"
|
||||
|
||||
## 🚀 Response Format
|
||||
Return ONLY the JSON object. Do not include any explanatory text."""
|
||||
|
||||
|
|
@ -0,0 +1,108 @@
|
|||
"""
|
||||
React Mode Prompt Generation
|
||||
Handles prompt templates for react mode action handling.
|
||||
"""
|
||||
|
||||
def createReactPlanSelectionPromptTemplate() -> str:
|
||||
"""Create action selection prompt template for React mode with minimal placeholders."""
|
||||
return """Select one action to advance the task.
|
||||
|
||||
OBJECTIVE:
|
||||
{{KEY:USER_PROMPT}}
|
||||
|
||||
AVAILABLE_DOCUMENTS:
|
||||
{{KEY:AVAILABLE_DOCUMENTS}}
|
||||
|
||||
AVAILABLE_METHODS:
|
||||
{{KEY:AVAILABLE_METHODS}}
|
||||
|
||||
REPLY: Return only a JSON object with the selected action:
|
||||
{{
|
||||
"action": "method.action_name"
|
||||
}}
|
||||
|
||||
RULES:
|
||||
1. Use EXACT action names from AVAILABLE_METHODS
|
||||
2. Return ONLY JSON - no other text
|
||||
3. Do NOT use markdown code blocks
|
||||
4. Do NOT add explanations
|
||||
"""
|
||||
|
||||
def createReactParametersPromptTemplate() -> str:
|
||||
"""Create comprehensive action parameter prompt template for React mode with all available context."""
|
||||
return """Generate parameters for this action.
|
||||
|
||||
ACTION_OBJECTIVE (the objective for this action to fulfill):
|
||||
{{KEY:ACTION_OBJECTIVE}}
|
||||
|
||||
ACTION_SIGNATURE (the signature of the action to generate parameters for):
|
||||
{{KEY:ACTION_SIGNATURE}}
|
||||
|
||||
AVAILABLE_DOCUMENTS:
|
||||
{{KEY:AVAILABLE_DOCUMENTS}}
|
||||
|
||||
AVAILABLE_CONNECTIONS:
|
||||
{{KEY:AVAILABLE_CONNECTIONS}}
|
||||
|
||||
USER_REQUEST (final user prompt to deliver):
|
||||
{{KEY:USER_PROMPT}}
|
||||
|
||||
USER_LANGUAGE:
|
||||
{{KEY:USER_LANGUAGE}}
|
||||
|
||||
PREVIOUS_ACTION_RESULTS:
|
||||
{{KEY:PREVIOUS_ACTION_RESULTS}}
|
||||
|
||||
LEARNINGS_AND_IMPROVEMENTS:
|
||||
{{KEY:LEARNINGS_AND_IMPROVEMENTS}}
|
||||
|
||||
LATEST_REFINEMENT_FEEDBACK:
|
||||
{{KEY:LATEST_REFINEMENT_FEEDBACK}}
|
||||
|
||||
SELECTED_ACTION:
|
||||
{{KEY:SELECTED_ACTION}}
|
||||
|
||||
REPLY: Return only a JSON object with the parameters according to the ACTION_SIGNATURE without any comments in the structure below:
|
||||
{{
|
||||
"parameters": {{
|
||||
"parameter": "value",
|
||||
}},
|
||||
"signature": [List of all signatures, you see in the ACTION_SIGNATURE]
|
||||
}}
|
||||
|
||||
RULES:
|
||||
1. Use ONLY parameter names from ACTION_SIGNATURE
|
||||
2. Use exact connection references from AVAILABLE_CONNECTIONS for connectionReference parameters
|
||||
3. Use exact document references from AVAILABLE_DOCUMENTS for documentList parameters
|
||||
4. Learn from PREVIOUS_ACTION_RESULTS and LEARNINGS_AND_IMPROVEMENTS to avoid repeating mistakes
|
||||
5. Consider LATEST_REFINEMENT_FEEDBACK when generating parameters
|
||||
6. Use the ACTION_OBJECTIVE to understand the specific goal for this action
|
||||
7. Generate parameters that align with the USER_LANGUAGE when applicable
|
||||
8. Return ONLY JSON - no other text
|
||||
9. Do NOT use markdown code blocks
|
||||
10. Do NOT add explanations
|
||||
"""
|
||||
|
||||
def createReactRefinementPromptTemplate() -> str:
|
||||
"""Create refinement prompt template for React mode with full context placeholders."""
|
||||
return """Decide the next step based on the observation.
|
||||
|
||||
OBJECTIVE:
|
||||
{{KEY:USER_PROMPT}}
|
||||
|
||||
OBSERVATION:
|
||||
{{KEY:REVIEW_CONTENT}}
|
||||
|
||||
REPLY: Return only a JSON object with your decision:
|
||||
{{
|
||||
"decision": "continue|stop",
|
||||
"reason": "brief explanation"
|
||||
}}
|
||||
|
||||
RULES:
|
||||
1. Use "continue" if objective NOT fulfilled
|
||||
2. Use "stop" if objective fulfilled
|
||||
3. Return ONLY JSON - no other text
|
||||
4. Do NOT use markdown code blocks
|
||||
5. Do NOT add explanations
|
||||
"""
|
||||
107
modules/workflows/processing/shared/promptGenerationTaskplan.py
Normal file
107
modules/workflows/processing/shared/promptGenerationTaskplan.py
Normal file
|
|
@ -0,0 +1,107 @@
|
|||
"""
|
||||
Task Planning Prompt Generation
|
||||
Handles prompt templates and extraction functions for task planning phase.
|
||||
"""
|
||||
|
||||
import json
|
||||
import logging
|
||||
from typing import Dict, Any
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
def createTaskPlanningPromptTemplate() -> str:
|
||||
"""Create task planning prompt template with placeholders."""
|
||||
return """# Task Planning
|
||||
|
||||
Break down user requests into logical, executable task steps.
|
||||
|
||||
## 📋 Context
|
||||
|
||||
### User Request
|
||||
{{KEY:USER_PROMPT}}
|
||||
|
||||
### Available Documents
|
||||
{{KEY:AVAILABLE_DOCUMENTS}}
|
||||
|
||||
### Previous Workflow Rounds
|
||||
{{KEY:WORKFLOW_HISTORY}}
|
||||
|
||||
## 📝 Task Planning Rules
|
||||
|
||||
### Strategic Task Grouping
|
||||
- **GROUP RELATED ACTIONS** - Combine all actions for the same business topic into ONE task
|
||||
- **ONE TOPIC PER TASK** - Each task should handle one complete business objective
|
||||
- **HIGH-LEVEL FOCUS** - Plan strategic outcomes, not implementation steps
|
||||
- **AVOID MICRO-TASKS** - Don't create separate tasks for each small action
|
||||
|
||||
### Task Grouping Examples
|
||||
- **Research + Analysis + Report** → ONE task: "Web research report"
|
||||
- **Data Collection + Processing + Visualization** → ONE task: "Collect and present data"
|
||||
- **Different topics** (email + flowers) → SEPARATE tasks: "Send formal email..." + "Order flowers from Fleurop for delivery to 123 Main St, include card message"
|
||||
|
||||
### Retry Handling
|
||||
- **If retry request**: Analyze previous rounds to understand what failed
|
||||
- **Learn from mistakes**: Improve the plan based on previous failures
|
||||
|
||||
## 📊 Required JSON Structure
|
||||
|
||||
```json
|
||||
{
|
||||
"overview": "Brief description of the overall plan",
|
||||
"languageUserDetected": "en",
|
||||
"userMessage": "User-friendly message explaining the task plan",
|
||||
"tasks": [
|
||||
{
|
||||
"id": "task_1",
|
||||
"objective": "Clear business objective focusing on what to deliver",
|
||||
"dependencies": ["task_0"],
|
||||
"success_criteria": ["measurable criteria 1", "measurable criteria 2"],
|
||||
"estimated_complexity": "low|medium|high",
|
||||
"userMessage": "What this task will accomplish"
|
||||
}
|
||||
]
|
||||
}
|
||||
```
|
||||
|
||||
## 🎯 Task Structure Guidelines
|
||||
|
||||
### Task ID Format
|
||||
- Use sequential numbering: `task_1`, `task_2`, `task_3`
|
||||
- Keep IDs simple and clear
|
||||
|
||||
### Objective Writing
|
||||
- **Be VERY SPECIFIC** - Include exact details needed for action planning
|
||||
- **Include all requirements** - recipient, attachments, format, recipients, etc.
|
||||
- **State the complete deliverable** - What exactly will be produced
|
||||
- **Include context and constraints** - When, where, how, with what
|
||||
- **Make it actionable** - Clear enough to plan specific actions
|
||||
|
||||
### Specific Objective Examples
|
||||
- **Good**: "Send formal email to ceo and board of directors with annual report as attachment"
|
||||
- **Bad**: "Handle email communication"
|
||||
- **Good**: "Order flowers from Fleurop for delivery to 123 Main St, include card message 'Happy Birthday', deliver on March 15th"
|
||||
- **Bad**: "Order flowers"
|
||||
|
||||
### Action Planning Requirements
|
||||
- **Include all necessary details** - The objective must contain everything needed to plan actions
|
||||
- **Specify recipients and destinations** - Who should receive what
|
||||
- **Include file names and formats** - What documents to use/create
|
||||
- **State timing and deadlines** - When things need to be done
|
||||
- **Include context and constraints** - Any special requirements or limitations
|
||||
|
||||
### Success Criteria
|
||||
- **Make them measurable** - specific, quantifiable outcomes
|
||||
- **Focus on deliverables** - what the user will receive
|
||||
- **Keep criteria realistic** - achievable within the task scope
|
||||
- **Include all related actions** - success means completing the entire business objective
|
||||
- **Be specific about requirements** - Include exact details like recipients, formats, deadlines
|
||||
- **State clear completion criteria** - How to know the task is fully done
|
||||
|
||||
### Complexity Estimation
|
||||
- **Low**: Simple, single-action tasks (1-2 actions)
|
||||
- **Medium**: Multi-action tasks for one topic (3-5 actions)
|
||||
- **High**: Complex strategic tasks (6+ actions)
|
||||
|
||||
## 🚀 Response Format
|
||||
Return ONLY the JSON object."""
|
||||
|
|
@ -1,87 +0,0 @@
|
|||
"""
|
||||
React-specific prompt templates for dynamic AI calls.
|
||||
These templates are tailored for the React mode's iterative process.
|
||||
"""
|
||||
|
||||
def createReactPlanSelectionPromptTemplate() -> str:
|
||||
"""Create action selection prompt template for React mode with minimal placeholders."""
|
||||
return """Select one action to advance the task.
|
||||
|
||||
OBJECTIVE:
|
||||
{{KEY:USER_PROMPT}}
|
||||
|
||||
AVAILABLE_DOCUMENTS:
|
||||
{{KEY:AVAILABLE_DOCUMENTS}}
|
||||
|
||||
AVAILABLE_METHODS:
|
||||
{{KEY:AVAILABLE_METHODS}}
|
||||
|
||||
REPLY: Return only a JSON object with the selected action:
|
||||
{{
|
||||
"action": "method.action_name"
|
||||
}}
|
||||
|
||||
RULES:
|
||||
1. Use EXACT action names from AVAILABLE_METHODS
|
||||
2. Return ONLY JSON - no other text
|
||||
3. Do NOT use markdown code blocks
|
||||
4. Do NOT add explanations
|
||||
"""
|
||||
|
||||
|
||||
def createReactParametersPromptTemplate() -> str:
|
||||
"""Create ultra-simple action parameter prompt template for React mode."""
|
||||
return """Generate parameters for this action.
|
||||
|
||||
ACTION_SIGNATURE:
|
||||
{{KEY:ACTION_SIGNATURE}}
|
||||
|
||||
AVAILABLE_DOCUMENTS:
|
||||
{{KEY:AVAILABLE_DOCUMENTS}}
|
||||
|
||||
AVAILABLE_CONNECTIONS:
|
||||
{{KEY:AVAILABLE_CONNECTIONS}}
|
||||
|
||||
USER_REQUEST:
|
||||
{{KEY:USER_PROMPT}}
|
||||
|
||||
REPLY: Return only a JSON object with the parameters according to the ACTION_SIGNATURE without any comments in the structure below:
|
||||
{{
|
||||
"parameters": {{
|
||||
"parameter": "value",
|
||||
}},
|
||||
"signature": [List of all signatures, you see in the ACTION_SIGNATURE]
|
||||
}}
|
||||
|
||||
RULES:
|
||||
1. Use ONLY parameter names from ACTION_SIGNATURE
|
||||
2. Use exact connection references from AVAILABLE_CONNECTIONS for connectionReference parameters
|
||||
3. Use exact document references from AVAILABLE_DOCUMENTS for documentList parameters
|
||||
4. Return ONLY JSON - no other text
|
||||
5. Do NOT use markdown code blocks
|
||||
6. Do NOT add explanations
|
||||
"""
|
||||
|
||||
def createReactRefinementPromptTemplate() -> str:
|
||||
"""Create refinement prompt template for React mode with full context placeholders."""
|
||||
return """Decide the next step based on the observation.
|
||||
|
||||
OBJECTIVE:
|
||||
{{KEY:USER_PROMPT}}
|
||||
|
||||
OBSERVATION:
|
||||
{{KEY:REVIEW_CONTENT}}
|
||||
|
||||
REPLY: Return only a JSON object with your decision:
|
||||
{{
|
||||
"decision": "continue|stop",
|
||||
"reason": "brief explanation"
|
||||
}}
|
||||
|
||||
RULES:
|
||||
1. Use "continue" if objective NOT fulfilled
|
||||
2. Use "stop" if objective fulfilled
|
||||
3. Return ONLY JSON - no other text
|
||||
4. Do NOT use markdown code blocks
|
||||
5. Do NOT add explanations
|
||||
"""
|
||||
|
|
@ -5,9 +5,9 @@ import logging
|
|||
from typing import Dict, Any, Optional, List
|
||||
from modules.datamodels.datamodelWorkflow import TaskStep, TaskContext, TaskPlan, TaskResult, ReviewResult
|
||||
from modules.datamodels.datamodelChat import ChatWorkflow
|
||||
from modules.workflows.processing.modes.baseMode import BaseMode
|
||||
from modules.workflows.processing.modes.actionplanMode import ActionplanMode
|
||||
from modules.workflows.processing.modes.reactMode import ReactMode
|
||||
from modules.workflows.processing.modes.modeBase import BaseMode
|
||||
from modules.workflows.processing.modes.modeActionplan import ActionplanMode
|
||||
from modules.workflows.processing.modes.modeReact import ReactMode
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
|
|
|||
19
test-chat/obj/m20251005-100001_2_0_0/message.json
Normal file
19
test-chat/obj/m20251005-100001_2_0_0/message.json
Normal file
|
|
@ -0,0 +1,19 @@
|
|||
{
|
||||
"id": "msg_4fce3b47-1595-4190-a09a-7b8c2483d9dd",
|
||||
"workflowId": "8630c862-d9f3-4332-9d6c-6664a39edd73",
|
||||
"parentMessageId": null,
|
||||
"message": "Sende eine formelle E-Mail an peter.muster@domain.com von meinem valueon account aus, um meinen Termin von 10 Uhr auf Freitag zu scheiben. lege diese datei im mail als anhang bei und erfasse eine zusammenfasung im mail.",
|
||||
"role": "user",
|
||||
"status": "first",
|
||||
"sequenceNr": 7,
|
||||
"publishedAt": 1759651201.5949264,
|
||||
"roundNumber": 2,
|
||||
"taskNumber": 0,
|
||||
"actionNumber": 0,
|
||||
"documentsLabel": "round2_task0_action0_context",
|
||||
"actionId": null,
|
||||
"actionMethod": null,
|
||||
"actionName": null,
|
||||
"success": null,
|
||||
"documents": []
|
||||
}
|
||||
1
test-chat/obj/m20251005-100001_2_0_0/message_text.txt
Normal file
1
test-chat/obj/m20251005-100001_2_0_0/message_text.txt
Normal file
|
|
@ -0,0 +1 @@
|
|||
Sende eine formelle E-Mail an peter.muster@domain.com von meinem valueon account aus, um meinen Termin von 10 Uhr auf Freitag zu scheiben. lege diese datei im mail als anhang bei und erfasse eine zusammenfasung im mail.
|
||||
19
test-chat/obj/m20251005-100006_2_1_0/message.json
Normal file
19
test-chat/obj/m20251005-100006_2_1_0/message.json
Normal file
|
|
@ -0,0 +1,19 @@
|
|||
{
|
||||
"id": "msg_b85c3e84-c119-4634-ad19-11a735e1039d",
|
||||
"workflowId": "8630c862-d9f3-4332-9d6c-6664a39edd73",
|
||||
"parentMessageId": null,
|
||||
"message": "📋 **Task Plan**\n\nI will help you send a formal email to reschedule your appointment, including the specified file and a summary.\n\n💬 I will compose and send a formal email to reschedule your appointment, ensuring all required elements are included.\n\n",
|
||||
"role": "assistant",
|
||||
"status": "step",
|
||||
"sequenceNr": 8,
|
||||
"publishedAt": 1759651206.7063708,
|
||||
"roundNumber": 2,
|
||||
"taskNumber": 1,
|
||||
"actionNumber": 0,
|
||||
"documentsLabel": "task_plan",
|
||||
"actionId": null,
|
||||
"actionMethod": null,
|
||||
"actionName": null,
|
||||
"success": null,
|
||||
"documents": []
|
||||
}
|
||||
6
test-chat/obj/m20251005-100006_2_1_0/message_text.txt
Normal file
6
test-chat/obj/m20251005-100006_2_1_0/message_text.txt
Normal file
|
|
@ -0,0 +1,6 @@
|
|||
📋 **Task Plan**
|
||||
|
||||
I will help you send a formal email to reschedule your appointment, including the specified file and a summary.
|
||||
|
||||
💬 I will compose and send a formal email to reschedule your appointment, ensuring all required elements are included.
|
||||
|
||||
19
test-chat/obj/m20251005-100007_2_1_0/message.json
Normal file
19
test-chat/obj/m20251005-100007_2_1_0/message.json
Normal file
|
|
@ -0,0 +1,19 @@
|
|||
{
|
||||
"id": "msg_cb9e3372-52b5-4254-98e6-7552efb2b248",
|
||||
"workflowId": "8630c862-d9f3-4332-9d6c-6664a39edd73",
|
||||
"parentMessageId": null,
|
||||
"message": "🚀 **Task 1/1**\n\n💬 I will compose and send a formal email to reschedule your appointment, ensuring all required elements are included.",
|
||||
"role": "assistant",
|
||||
"status": "step",
|
||||
"sequenceNr": 9,
|
||||
"publishedAt": 1759651207.017333,
|
||||
"roundNumber": 2,
|
||||
"taskNumber": 1,
|
||||
"actionNumber": 0,
|
||||
"documentsLabel": "task_1_start",
|
||||
"actionId": null,
|
||||
"actionMethod": null,
|
||||
"actionName": null,
|
||||
"success": null,
|
||||
"documents": []
|
||||
}
|
||||
3
test-chat/obj/m20251005-100007_2_1_0/message_text.txt
Normal file
3
test-chat/obj/m20251005-100007_2_1_0/message_text.txt
Normal file
|
|
@ -0,0 +1,3 @@
|
|||
🚀 **Task 1/1**
|
||||
|
||||
💬 I will compose and send a formal email to reschedule your appointment, ensuring all required elements are included.
|
||||
19
test-chat/obj/m20251005-100020_2_1_1/message.json
Normal file
19
test-chat/obj/m20251005-100020_2_1_1/message.json
Normal file
|
|
@ -0,0 +1,19 @@
|
|||
{
|
||||
"id": "msg_dafc2f81-528f-4c61-991e-53fbb863a9a8",
|
||||
"workflowId": "8630c862-d9f3-4332-9d6c-6664a39edd73",
|
||||
"parentMessageId": null,
|
||||
"message": "**Action 1/1 (outlook.composeAndSendEmailWithContext)**\n\n✅ Compose and send formal email from valueon account to peter.muster@domain.com to reschedule 10am appointment to Friday, including file attachment and appointment summary\n\n",
|
||||
"role": "assistant",
|
||||
"status": "step",
|
||||
"sequenceNr": 10,
|
||||
"publishedAt": 1759651220.387675,
|
||||
"roundNumber": 2,
|
||||
"taskNumber": 1,
|
||||
"actionNumber": 1,
|
||||
"documentsLabel": "round2_task1_action1_results",
|
||||
"actionId": "action_4a3eb40f-a97d-4043-94c3-4fedfc5b1c8d",
|
||||
"actionMethod": "outlook",
|
||||
"actionName": "composeAndSendEmailWithContext",
|
||||
"success": null,
|
||||
"documents": []
|
||||
}
|
||||
4
test-chat/obj/m20251005-100020_2_1_1/message_text.txt
Normal file
4
test-chat/obj/m20251005-100020_2_1_1/message_text.txt
Normal file
|
|
@ -0,0 +1,4 @@
|
|||
**Action 1/1 (outlook.composeAndSendEmailWithContext)**
|
||||
|
||||
✅ Compose and send formal email from valueon account to peter.muster@domain.com to reschedule 10am appointment to Friday, including file attachment and appointment summary
|
||||
|
||||
|
|
@ -0,0 +1,12 @@
|
|||
{
|
||||
"id": "94fc49c9-55e5-4b03-a437-e79c26483651",
|
||||
"messageId": "msg_dafc2f81-528f-4c61-991e-53fbb863a9a8",
|
||||
"fileId": "a0196528-6ba3-4bc9-abef-7ae25aad0c76",
|
||||
"fileName": "ai_generated_email_draft_20251005-080020.json",
|
||||
"fileSize": 1173,
|
||||
"mimeType": "application/json",
|
||||
"roundNumber": 2,
|
||||
"taskNumber": 1,
|
||||
"actionNumber": 1,
|
||||
"actionId": "action_4a3eb40f-a97d-4043-94c3-4fedfc5b1c8d"
|
||||
}
|
||||
19
test-chat/obj/m20251005-100021_2_0_0/message.json
Normal file
19
test-chat/obj/m20251005-100021_2_0_0/message.json
Normal file
|
|
@ -0,0 +1,19 @@
|
|||
{
|
||||
"id": "msg_998654a7-b4b3-444a-9d25-ecabd0117735",
|
||||
"workflowId": "8630c862-d9f3-4332-9d6c-6664a39edd73",
|
||||
"parentMessageId": null,
|
||||
"message": "Workflow completed.\n\nProcessed 2 user inputs and generated 9 responses.\nWorkflow status: running",
|
||||
"role": "assistant",
|
||||
"status": "last",
|
||||
"sequenceNr": 12,
|
||||
"publishedAt": 1759651221.848871,
|
||||
"roundNumber": 2,
|
||||
"taskNumber": 0,
|
||||
"actionNumber": 0,
|
||||
"documentsLabel": "workflow_feedback",
|
||||
"actionId": null,
|
||||
"actionMethod": null,
|
||||
"actionName": null,
|
||||
"success": null,
|
||||
"documents": []
|
||||
}
|
||||
4
test-chat/obj/m20251005-100021_2_0_0/message_text.txt
Normal file
4
test-chat/obj/m20251005-100021_2_0_0/message_text.txt
Normal file
|
|
@ -0,0 +1,4 @@
|
|||
Workflow completed.
|
||||
|
||||
Processed 2 user inputs and generated 9 responses.
|
||||
Workflow status: running
|
||||
19
test-chat/obj/m20251005-100021_2_1_0/message.json
Normal file
19
test-chat/obj/m20251005-100021_2_1_0/message.json
Normal file
|
|
@ -0,0 +1,19 @@
|
|||
{
|
||||
"id": "msg_402e3653-1500-441f-adf0-d4ea90980d4e",
|
||||
"workflowId": "8630c862-d9f3-4332-9d6c-6664a39edd73",
|
||||
"parentMessageId": null,
|
||||
"message": "🎯 **Task 1/1**\n\n✅ Email draft successfully created with attachment and summary as requested\n📊 Score 8/10",
|
||||
"role": "assistant",
|
||||
"status": "step",
|
||||
"sequenceNr": 11,
|
||||
"publishedAt": 1759651221.6639369,
|
||||
"roundNumber": 2,
|
||||
"taskNumber": 1,
|
||||
"actionNumber": 0,
|
||||
"documentsLabel": "task_1_completion",
|
||||
"actionId": null,
|
||||
"actionMethod": null,
|
||||
"actionName": null,
|
||||
"success": null,
|
||||
"documents": []
|
||||
}
|
||||
4
test-chat/obj/m20251005-100021_2_1_0/message_text.txt
Normal file
4
test-chat/obj/m20251005-100021_2_1_0/message_text.txt
Normal file
|
|
@ -0,0 +1,4 @@
|
|||
🎯 **Task 1/1**
|
||||
|
||||
✅ Email draft successfully created with attachment and summary as requested
|
||||
📊 Score 8/10
|
||||
Loading…
Reference in a new issue