fixes for chat workflow
This commit is contained in:
ValueOn AG
parent
6d393f9cf3
commit
a48bf06778
31 changed files with 963 additions and 1626 deletions
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M app.py
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A modules/.$DEPENDENCY_DIAGRAM.drawio.bkp
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A modules/AUTOMATION_FEATURE_ANALYSIS.md
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A modules/BIDIRECTIONAL_IMPORTS.md
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A modules/DEPENDENCY_DIAGRAM.drawio
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A modules/FEATURES_TO_INTERFACES_IMPORTS.md
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M modules/connectors/connectorVoiceGoogle.py
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M modules/datamodels/datamodelChat.py
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M modules/datamodels/datamodelPagination.py
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A modules/features/automation/__init__.py
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A modules/features/automation/mainAutomation.py
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A modules/features/automation/subAutomationUtils.py
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D modules/features/chatAlthaus/COMPONENT_DIAGRAM.md
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M modules/features/featuresLifecycle.py
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M modules/interfaces/interfaceAiObjects.py
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M modules/interfaces/interfaceDbAppObjects.py
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M modules/interfaces/interfaceDbChatObjects.py
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M modules/interfaces/interfaceDbComponentObjects.py
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M modules/interfaces/interfaceVoiceObjects.py
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M modules/routes/routeAdminAutomationEvents.py
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M modules/routes/routeVoiceGoogle.py
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M modules/services/__init__.py
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M modules/services/serviceAi/mainServiceAi.py
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M modules/services/serviceAi/subJsonResponseHandling.py
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M modules/services/serviceChat/mainServiceChat.py
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M modules/services/serviceExtraction/mainServiceExtraction.py
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M modules/services/serviceExtraction/subPipeline.py
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M modules/services/serviceExtraction/subPromptBuilderExtraction.py
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M modules/services/serviceGeneration/renderers/rendererXlsx.py
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M modules/services/serviceGeneration/subPromptBuilderGeneration.py
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A modules/services/serviceSecurity/mainServiceSecurity.py
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M modules/services/serviceSharepoint/mainServiceSharepoint.py
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M modules/services/serviceUtils/mainServiceUtils.py
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A modules/shared/callbackRegistry.py
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M modules/shared/debugLogger.py
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M modules/shared/jsonUtils.py
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M modules/workflows/methods/methodAi.py
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M modules/workflows/methods/methodBase.py
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A modules/workflows/methods/methodContext.py
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M modules/workflows/methods/methodOutlook.py
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M modules/workflows/methods/methodSharepoint.py
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M modules/workflows/processing/adaptive/contentValidator.py
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M modules/workflows/processing/core/messageCreator.py
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M modules/workflows/processing/modes/modeAutomation.py
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M modules/workflows/processing/modes/modeDynamic.py
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M modules/workflows/processing/shared/promptGenerationActionsDynamic.py
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M modules/workflows/processing/shared/promptGenerationTaskplan.py
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M modules/workflows/processing/workflowProcessor.py
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M modules/workflows/workflowManager.py
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|
||||
<mxGeometry width="50" height="50" relative="1" as="geometry">
|
||||
<mxPoint x="800" y="800" as="sourcePoint" />
|
||||
<mxPoint x="600" y="450" as="targetPoint" />
|
||||
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|
||||
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|
||||
|
||||
<mxCell id="edge31" value="" style="endArrow=classic;html=1;rounded=0;strokeWidth=2;strokeColor=#880e4f" edge="1" parent="1" source="security" target="datamodels">
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|
||||
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|
||||
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||||
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|
||||
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|
||||
|
||||
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|
||||
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|
||||
<mxPoint x="800" y="800" as="sourcePoint" />
|
||||
<mxPoint x="650" y="300" as="targetPoint" />
|
||||
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|
||||
</mxCell>
|
||||
|
||||
<!-- Legend -->
|
||||
<mxCell id="legend" value="Legend" style="text;html=1;strokeColor=none;fillColor=none;align=center;verticalAlign=middle;whiteSpace=wrap;rounded=0;fontStyle=1;fontSize=14" vertex="1" parent="1">
|
||||
<mxGeometry x="1000" y="100" width="100" height="30" as="geometry" />
|
||||
</mxCell>
|
||||
|
||||
<mxCell id="legend1" value="Foundation Layer" style="rounded=1;whiteSpace=wrap;html=1;fillColor=#e1f5ff;strokeColor=#01579b;strokeWidth=2" vertex="1" parent="1">
|
||||
<mxGeometry x="1000" y="140" width="150" height="30" as="geometry" />
|
||||
</mxCell>
|
||||
|
||||
<mxCell id="legend2" value="Data Access Layer" style="rounded=1;whiteSpace=wrap;html=1;fillColor=#f3e5f5;strokeColor=#4a148c;strokeWidth=2" vertex="1" parent="1">
|
||||
<mxGeometry x="1000" y="180" width="150" height="30" as="geometry" />
|
||||
</mxCell>
|
||||
|
||||
<mxCell id="legend3" value="Business Logic Layer" style="rounded=1;whiteSpace=wrap;html=1;fillColor=#e8f5e9;strokeColor=#1b5e20;strokeWidth=2" vertex="1" parent="1">
|
||||
<mxGeometry x="1000" y="220" width="150" height="30" as="geometry" />
|
||||
</mxCell>
|
||||
|
||||
<mxCell id="legend4" value="Feature Layer" style="rounded=1;whiteSpace=wrap;html=1;fillColor=#fff3e0;strokeColor=#e65100;strokeWidth=2" vertex="1" parent="1">
|
||||
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|
||||
</mxCell>
|
||||
|
||||
<mxCell id="legend5" value="API Layer" style="rounded=1;whiteSpace=wrap;html=1;fillColor=#fce4ec;strokeColor=#880e4f;strokeWidth=2" vertex="1" parent="1">
|
||||
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|
||||
</mxCell>
|
||||
|
||||
<mxCell id="legend6" value="✅ Correct Direction" style="text;html=1;strokeColor=none;fillColor=none;align=left;verticalAlign=middle;whiteSpace=wrap;rounded=0" vertex="1" parent="1">
|
||||
<mxGeometry x="1000" y="350" width="150" height="20" as="geometry" />
|
||||
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|
||||
|
||||
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|
||||
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|
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|
||||
<!-- Status Box -->
|
||||
<mxCell id="status" value="✅ ZERO VIOLATIONS
Perfect Architectural Compliance" style="rounded=1;whiteSpace=wrap;html=1;fillColor=#c8e6c9;strokeColor=#2e7d32;strokeWidth=3;fontStyle=1;fontSize=12" vertex="1" parent="1">
|
||||
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|
||||
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|
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|
||||
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|
||||
</mxGraphModel>
|
||||
</diagram>
|
||||
</mxfile>
|
||||
|
||||
|
|
@ -1,407 +0,0 @@
|
|||
# Automation Feature Analysis: Moving Automation Handler to Features Layer
|
||||
|
||||
## Executive Summary
|
||||
|
||||
**Status: ✅ HIGHLY RECOMMENDED - Architectural Improvement**
|
||||
|
||||
Moving automation workflow handler functionality from `interfaces/interfaceDbChatObjects.py` to a new feature in `features/` is **architecturally correct** and aligns with separation of concerns.
|
||||
|
||||
---
|
||||
|
||||
## Current Architecture Analysis
|
||||
|
||||
### Current Location: `interfaces/interfaceDbChatObjects.py`
|
||||
|
||||
**Automation-related methods:**
|
||||
1. `executeAutomation(automationId: str)` - Executes automation workflow immediately (test mode)
|
||||
2. `syncAutomationEvents()` - Syncs scheduler with all active automations
|
||||
3. `_createAutomationEventHandler(automationId: str)` - Creates event handler for scheduled execution
|
||||
4. `_parseScheduleToCron(schedule: str)` - Parses schedule string to cron kwargs
|
||||
5. `_planToPrompt(plan: Dict)` - Converts plan structure to prompt string
|
||||
6. `_replacePlaceholders(template: str, placeholders: Dict)` - Replaces placeholders in template
|
||||
|
||||
**Dependencies:**
|
||||
- Uses `getAutomationDefinition()` - Database access (should stay in interface)
|
||||
- Uses `chatStart()` from `features.chatPlayground` - Already imports from features
|
||||
- Uses `eventManager` from `shared.eventManagement` - Foundation layer
|
||||
- Creates workflows using `WorkflowModeEnum.WORKFLOW_AUTOMATION`
|
||||
|
||||
---
|
||||
|
||||
## Why This Should Be a Feature
|
||||
|
||||
### 1. **Business Logic vs. Data Access**
|
||||
|
||||
**Current Problem:**
|
||||
- Automation execution logic is **business logic** (orchestration, workflow creation)
|
||||
- It's mixed with **data access** (interface layer)
|
||||
- Interface layer should only provide data access, not business orchestration
|
||||
|
||||
**After Move:**
|
||||
- Interface layer: `getAutomationDefinition()`, `saveAutomationDefinition()` (data access)
|
||||
- Feature layer: `executeAutomation()`, `syncAutomationEvents()` (business logic)
|
||||
|
||||
### 2. **Feature Pattern Consistency**
|
||||
|
||||
**Existing Features Pattern:**
|
||||
- `features/chatPlayground/` - Chat workflow execution
|
||||
- `features/chatAlthaus/` - Scheduled data updates
|
||||
- `features/syncDelta/` - Sync management
|
||||
- `features/neutralizePlayground/` - Neutralization workflows
|
||||
|
||||
**Automation Handler Pattern:**
|
||||
- Scheduled execution (like `chatAlthaus`)
|
||||
- Workflow orchestration (like `chatPlayground`)
|
||||
- Event-driven (like `syncDelta`)
|
||||
|
||||
**Conclusion:** Automation handler fits the feature pattern perfectly.
|
||||
|
||||
### 3. **Dependency Direction**
|
||||
|
||||
**Current Violation:**
|
||||
- `interfaces/` imports from `features/` (line 1927: `from modules.features.chatPlayground.mainChatPlayground import chatStart`)
|
||||
- This creates bidirectional dependency: `interfaces/ ↔ features/`
|
||||
|
||||
**After Move:**
|
||||
- `features/automation/` imports from `interfaces/` (correct direction)
|
||||
- `features/automation/` imports from `features/chatPlayground/` (feature-to-feature)
|
||||
- Eliminates `interfaces/ → features/` import
|
||||
|
||||
### 4. **Separation of Concerns**
|
||||
|
||||
**Interface Layer Should:**
|
||||
- ✅ Provide data access (`getAutomationDefinition`, `saveAutomationDefinition`)
|
||||
- ✅ Handle CRUD operations
|
||||
- ❌ NOT orchestrate workflows
|
||||
- ❌ NOT manage scheduling
|
||||
- ❌ NOT execute business logic
|
||||
|
||||
**Feature Layer Should:**
|
||||
- ✅ Orchestrate workflows
|
||||
- ✅ Manage scheduling
|
||||
- ✅ Execute business logic
|
||||
- ✅ Coordinate between services and interfaces
|
||||
|
||||
---
|
||||
|
||||
## Proposed Architecture
|
||||
|
||||
### New Structure: `features/automation/`
|
||||
|
||||
```
|
||||
features/automation/
|
||||
├── mainAutomation.py # Main automation service
|
||||
│ ├── executeAutomation() # Execute automation workflow
|
||||
│ ├── syncAutomationEvents() # Sync scheduler with automations
|
||||
│ └── _createAutomationEventHandler() # Create event handler
|
||||
└── subAutomationUtils.py # Utility functions
|
||||
├── _parseScheduleToCron() # Parse schedule to cron
|
||||
├── _planToPrompt() # Convert plan to prompt
|
||||
└── _replacePlaceholders() # Replace template placeholders
|
||||
```
|
||||
|
||||
### Interface Layer (Keep)
|
||||
|
||||
```
|
||||
interfaces/interfaceDbChatObjects.py
|
||||
├── getAutomationDefinition() # Data access - KEEP
|
||||
├── saveAutomationDefinition() # Data access - KEEP
|
||||
└── (other CRUD methods) # Data access - KEEP
|
||||
```
|
||||
|
||||
### Feature Lifecycle Integration
|
||||
|
||||
```
|
||||
features/featuresLifecycle.py
|
||||
├── start()
|
||||
│ └── from features.automation import mainAutomation
|
||||
│ mainAutomation.startScheduler(eventUser)
|
||||
└── stop()
|
||||
└── mainAutomation.stopScheduler()
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Detailed Functionality Analysis
|
||||
|
||||
### Functions to Move
|
||||
|
||||
#### 1. `executeAutomation(automationId: str)` → `features/automation/mainAutomation.py`
|
||||
|
||||
**Current Implementation:**
|
||||
- Loads automation definition (calls interface method)
|
||||
- Replaces placeholders in template
|
||||
- Creates UserInputRequest
|
||||
- Calls `chatStart()` from `features.chatPlayground`
|
||||
- Returns ChatWorkflow
|
||||
|
||||
**Dependencies:**
|
||||
- `getAutomationDefinition()` - Interface method (import from interface)
|
||||
- `_replacePlaceholders()` - Utility (move to feature)
|
||||
- `_planToPrompt()` - Utility (move to feature)
|
||||
- `chatStart()` - Feature method (import from feature)
|
||||
- `getInterface()` - Interface factory (import from interface)
|
||||
|
||||
**After Move:**
|
||||
```python
|
||||
# features/automation/mainAutomation.py
|
||||
from modules.interfaces.interfaceDbChatObjects import getInterface as getChatInterface
|
||||
from modules.interfaces.interfaceDbAppObjects import getInterface as getAppInterface
|
||||
from modules.features.chatPlayground.mainChatPlayground import chatStart
|
||||
from .subAutomationUtils import replacePlaceholders, planToPrompt
|
||||
|
||||
async def executeAutomation(automationId: str, chatInterface) -> ChatWorkflow:
|
||||
"""Execute automation workflow immediately."""
|
||||
# Load automation (uses interface)
|
||||
automation = chatInterface.getAutomationDefinition(automationId)
|
||||
# ... rest of logic
|
||||
```
|
||||
|
||||
#### 2. `syncAutomationEvents()` → `features/automation/mainAutomation.py`
|
||||
|
||||
**Current Implementation:**
|
||||
- Gets all automation definitions (calls interface method)
|
||||
- Parses schedules
|
||||
- Registers cron jobs with eventManager
|
||||
- Creates event handlers
|
||||
|
||||
**Dependencies:**
|
||||
- `getRecordset()` - Interface method (via chatInterface)
|
||||
- `_parseScheduleToCron()` - Utility (move to feature)
|
||||
- `_createAutomationEventHandler()` - Handler creation (move to feature)
|
||||
- `eventManager` - Foundation layer (import from shared)
|
||||
|
||||
**After Move:**
|
||||
```python
|
||||
# features/automation/mainAutomation.py
|
||||
from modules.shared.eventManagement import eventManager
|
||||
from modules.interfaces.interfaceDbChatObjects import getInterface as getChatInterface
|
||||
from .subAutomationUtils import parseScheduleToCron
|
||||
|
||||
async def syncAutomationEvents(chatInterface) -> Dict[str, Any]:
|
||||
"""Sync scheduler with all active automations."""
|
||||
# Get automations (uses interface)
|
||||
allAutomations = chatInterface.db.getRecordset(AutomationDefinition)
|
||||
# ... rest of logic
|
||||
```
|
||||
|
||||
#### 3. `_createAutomationEventHandler(automationId: str)` → `features/automation/mainAutomation.py`
|
||||
|
||||
**Current Implementation:**
|
||||
- Creates async handler function
|
||||
- Gets event user
|
||||
- Loads automation
|
||||
- Executes automation with creator user context
|
||||
|
||||
**Dependencies:**
|
||||
- `getRootInterface()` - Interface factory (import from interface)
|
||||
- `getInterface()` - Interface factories (import from interfaces)
|
||||
- `executeAutomation()` - Will be in same module
|
||||
|
||||
**After Move:**
|
||||
```python
|
||||
# features/automation/mainAutomation.py
|
||||
def createAutomationEventHandler(automationId: str):
|
||||
"""Create event handler function for scheduled automation."""
|
||||
async def handler():
|
||||
# Uses interfaces and executeAutomation from same module
|
||||
await executeAutomation(automationId, eventInterface)
|
||||
return handler
|
||||
```
|
||||
|
||||
#### 4. Utility Functions → `features/automation/subAutomationUtils.py`
|
||||
|
||||
**Functions:**
|
||||
- `_parseScheduleToCron(schedule: str)` - Parse schedule to cron kwargs
|
||||
- `_planToPrompt(plan: Dict)` - Convert plan to prompt string
|
||||
- `_replacePlaceholders(template: str, placeholders: Dict)` - Replace placeholders
|
||||
|
||||
**Dependencies:**
|
||||
- No external dependencies (pure utility functions)
|
||||
|
||||
---
|
||||
|
||||
## Migration Plan
|
||||
|
||||
### Phase 1: Create Feature Structure
|
||||
|
||||
1. Create `features/automation/` directory
|
||||
2. Create `features/automation/__init__.py`
|
||||
3. Create `features/automation/mainAutomation.py`
|
||||
4. Create `features/automation/subAutomationUtils.py`
|
||||
|
||||
### Phase 2: Move Functions
|
||||
|
||||
1. Move utility functions to `subAutomationUtils.py`
|
||||
2. Move `executeAutomation()` to `mainAutomation.py`
|
||||
3. Move `syncAutomationEvents()` to `mainAutomation.py`
|
||||
4. Move `_createAutomationEventHandler()` to `mainAutomation.py`
|
||||
|
||||
### Phase 3: Update Dependencies
|
||||
|
||||
1. Update `features/featuresLifecycle.py` to use new feature
|
||||
2. Update `routes/routeAdminAutomationEvents.py` to use new feature
|
||||
3. Update any other call sites
|
||||
|
||||
### Phase 4: Cleanup Interface
|
||||
|
||||
1. Remove moved functions from `interfaceDbChatObjects.py`
|
||||
2. Keep only data access methods (`getAutomationDefinition`, etc.)
|
||||
3. Remove import from `features.chatPlayground` from interface
|
||||
|
||||
### Phase 5: Update Documentation
|
||||
|
||||
1. Update `BIDIRECTIONAL_IMPORTS.md` to reflect resolved dependency
|
||||
2. Document new feature structure
|
||||
|
||||
---
|
||||
|
||||
## Benefits
|
||||
|
||||
### ✅ Architectural Benefits
|
||||
|
||||
1. **Correct Separation of Concerns**
|
||||
- Interface layer: Data access only
|
||||
- Feature layer: Business logic and orchestration
|
||||
|
||||
2. **Resolves Bidirectional Dependency**
|
||||
- Eliminates `interfaces/ → features/` import
|
||||
- Only `features/ → interfaces/` remains (correct direction)
|
||||
|
||||
3. **Consistency with Existing Patterns**
|
||||
- Matches other feature implementations
|
||||
- Follows established architecture
|
||||
|
||||
4. **Better Testability**
|
||||
- Feature logic can be tested independently
|
||||
- Interface layer remains focused
|
||||
|
||||
### ✅ Maintainability Benefits
|
||||
|
||||
1. **Clearer Code Organization**
|
||||
- Automation logic in one place
|
||||
- Easier to find and modify
|
||||
|
||||
2. **Reduced Coupling**
|
||||
- Interface layer doesn't depend on features
|
||||
- Features depend on interfaces (correct direction)
|
||||
|
||||
3. **Easier to Extend**
|
||||
- New automation features can be added to feature module
|
||||
- Interface layer remains stable
|
||||
|
||||
---
|
||||
|
||||
## Risks and Considerations
|
||||
|
||||
### 🟢 Low Risk
|
||||
|
||||
- **Functionality preservation** - Logic doesn't change, only location
|
||||
- **Interface methods remain** - Data access methods stay in interface
|
||||
- **Lazy imports** - Already using lazy imports for event handlers
|
||||
|
||||
### 🟡 Medium Risk
|
||||
|
||||
- **Call site updates** - Need to update routes and lifecycle
|
||||
- **Interface method access** - Feature needs to call interface methods
|
||||
- **Event user context** - Need to ensure proper user context handling
|
||||
|
||||
### 🔴 Potential Issues
|
||||
|
||||
1. **Interface method access** - Feature needs `chatInterface` instance
|
||||
- **Solution:** Pass interface instance as parameter or create in feature
|
||||
|
||||
2. **Event handler context** - Event handlers need interface access
|
||||
- **Solution:** Create interface instances in handler (already doing this)
|
||||
|
||||
3. **Backward compatibility** - Existing code calling `chatInterface.executeAutomation()`
|
||||
- **Solution:** Update all call sites, or create wrapper method in interface (deprecated)
|
||||
|
||||
---
|
||||
|
||||
## Call Sites Analysis
|
||||
|
||||
### Current Call Sites
|
||||
|
||||
1. **`features/featuresLifecycle.py` (line 20)**
|
||||
```python
|
||||
await chatInterface.syncAutomationEvents()
|
||||
```
|
||||
**Update:** Import and call feature directly
|
||||
|
||||
2. **`routes/routeAdminAutomationEvents.py` (line 97)**
|
||||
```python
|
||||
result = await chatInterface.syncAutomationEvents()
|
||||
```
|
||||
**Update:** Import and call feature directly
|
||||
|
||||
3. **`interfaces/interfaceDbChatObjects.py` (lines 1683, 1714, 1744)**
|
||||
```python
|
||||
asyncio.create_task(self.syncAutomationEvents())
|
||||
```
|
||||
**Update:** Remove (will be handled by feature lifecycle)
|
||||
|
||||
4. **`_createAutomationEventHandler()` (line 2105)**
|
||||
```python
|
||||
await creatorInterface.executeAutomation(automationId)
|
||||
```
|
||||
**Update:** Call feature method instead
|
||||
|
||||
### Proposed Call Sites
|
||||
|
||||
1. **`features/featuresLifecycle.py`**
|
||||
```python
|
||||
from modules.features.automation import mainAutomation
|
||||
await mainAutomation.syncAutomationEvents(chatInterface)
|
||||
```
|
||||
|
||||
2. **`routes/routeAdminAutomationEvents.py`**
|
||||
```python
|
||||
from modules.features.automation import mainAutomation
|
||||
result = await mainAutomation.syncAutomationEvents(chatInterface)
|
||||
```
|
||||
|
||||
3. **`features/automation/mainAutomation.py` (event handler)**
|
||||
```python
|
||||
from .mainAutomation import executeAutomation
|
||||
await executeAutomation(automationId, eventInterface)
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Implementation Checklist
|
||||
|
||||
- [ ] Create `features/automation/` directory structure
|
||||
- [ ] Create `features/automation/__init__.py`
|
||||
- [ ] Create `features/automation/mainAutomation.py`
|
||||
- [ ] Create `features/automation/subAutomationUtils.py`
|
||||
- [ ] Move `_parseScheduleToCron()` to `subAutomationUtils.py`
|
||||
- [ ] Move `_planToPrompt()` to `subAutomationUtils.py`
|
||||
- [ ] Move `_replacePlaceholders()` to `subAutomationUtils.py`
|
||||
- [ ] Move `executeAutomation()` to `mainAutomation.py`
|
||||
- [ ] Move `syncAutomationEvents()` to `mainAutomation.py`
|
||||
- [ ] Move `_createAutomationEventHandler()` to `mainAutomation.py`
|
||||
- [ ] Update `features/featuresLifecycle.py` to use feature
|
||||
- [ ] Update `routes/routeAdminAutomationEvents.py` to use feature
|
||||
- [ ] Remove moved functions from `interfaceDbChatObjects.py`
|
||||
- [ ] Remove `features.chatPlayground` import from `interfaceDbChatObjects.py`
|
||||
- [ ] Update `BIDIRECTIONAL_IMPORTS.md`
|
||||
- [ ] Test automation execution (manual)
|
||||
- [ ] Test automation scheduling (scheduled)
|
||||
- [ ] Verify no circular dependencies
|
||||
|
||||
---
|
||||
|
||||
## Conclusion
|
||||
|
||||
**✅ STRONGLY RECOMMENDED: Move to Features Layer**
|
||||
|
||||
This refactoring is:
|
||||
- **Architecturally correct** - Business logic belongs in features, not interfaces
|
||||
- **Resolves dependency violation** - Eliminates `interfaces/ → features/` import
|
||||
- **Consistent with patterns** - Matches existing feature implementations
|
||||
- **Low risk** - Logic doesn't change, only location
|
||||
- **Improves maintainability** - Clearer separation of concerns
|
||||
|
||||
**Recommendation: PROCEED** with moving automation handler functionality to `features/automation/` following the plan above.
|
||||
|
||||
|
|
@ -1,406 +0,0 @@
|
|||
# Bidirectional Import Analysis
|
||||
|
||||
## Summary
|
||||
|
||||
After refactoring extraction functions and automation handler, **ALL bidirectional dependencies have been RESOLVED**:
|
||||
|
||||
**Current Status:**
|
||||
- ✅ **interfaces/ → services/**: **RESOLVED** (no imports)
|
||||
- ✅ **interfaces/ → features/**: **RESOLVED** (uses callback registry, no direct imports)
|
||||
- ✅ **services/ → interfaces/**: **UNIDIRECTIONAL** (correct dependency direction)
|
||||
- ✅ **services/ → features/**: **NONE** (no imports)
|
||||
- ✅ **features/ → interfaces/**: **UNIDIRECTIONAL** (correct dependency direction)
|
||||
- ✅ **features/ → services/**: **1 lazy import** (correct direction)
|
||||
|
||||
**Result:** ✅ **ZERO VIOLATIONS** - Perfect architectural compliance achieved.
|
||||
|
||||
---
|
||||
|
||||
## Dependency Diagram
|
||||
|
||||
### Mermaid Diagram
|
||||
|
||||
```mermaid
|
||||
graph TB
|
||||
%% Foundation Layer (no dependencies)
|
||||
shared[shared/<br/>Foundation]
|
||||
datamodels[datamodels/<br/>Foundation]
|
||||
aicore[aicore/<br/>Infrastructure]
|
||||
connectors[connectors/<br/>Infrastructure]
|
||||
|
||||
%% Data Layer
|
||||
interfaces[interfaces/<br/>Data Access<br/>✅ No violations]
|
||||
|
||||
%% Business Logic Layer
|
||||
services[services/<br/>Business Logic<br/>✅ Unidirectional]
|
||||
workflows[workflows/<br/>Business Logic]
|
||||
|
||||
%% Feature Layer
|
||||
features[features/<br/>Features<br/>✅ Unidirectional]
|
||||
|
||||
%% API Layer
|
||||
routes[routes/<br/>API Layer]
|
||||
security[security/<br/>Security]
|
||||
|
||||
%% Foundation dependencies
|
||||
datamodels -->|imports| shared
|
||||
aicore -->|imports| datamodels
|
||||
aicore -->|imports| shared
|
||||
connectors -->|imports| datamodels
|
||||
connectors -->|imports| shared
|
||||
|
||||
%% Interface layer (foundation only)
|
||||
interfaces -->|imports| aicore
|
||||
interfaces -->|imports| connectors
|
||||
interfaces -->|imports| datamodels
|
||||
interfaces -.->|callbackRegistry| shared
|
||||
|
||||
%% Service layer (interfaces only)
|
||||
services -->|✅ imports| interfaces
|
||||
services -->|imports| aicore
|
||||
services -->|imports| datamodels
|
||||
services -->|imports| security
|
||||
services -->|imports| shared
|
||||
|
||||
%% Workflow layer
|
||||
workflows -->|imports| aicore
|
||||
workflows -->|imports| datamodels
|
||||
workflows -->|imports| services
|
||||
workflows -->|imports| shared
|
||||
|
||||
%% Feature layer (interfaces + services)
|
||||
features -->|✅ imports| interfaces
|
||||
features -->|✅ imports| services
|
||||
features -->|imports| datamodels
|
||||
features -->|imports| workflows
|
||||
features -->|imports| shared
|
||||
|
||||
%% API layer
|
||||
routes -->|imports| interfaces
|
||||
routes -->|imports| features
|
||||
routes -->|imports| services
|
||||
routes -->|imports| security
|
||||
routes -->|imports| datamodels
|
||||
routes -->|imports| shared
|
||||
|
||||
%% Security layer
|
||||
security -->|imports| interfaces
|
||||
security -->|imports| datamodels
|
||||
security -->|imports| shared
|
||||
|
||||
%% Styling
|
||||
classDef foundation fill:#e1f5ff,stroke:#01579b,stroke-width:2px
|
||||
classDef data fill:#f3e5f5,stroke:#4a148c,stroke-width:3px
|
||||
classDef business fill:#e8f5e9,stroke:#1b5e20,stroke-width:2px
|
||||
classDef feature fill:#fff3e0,stroke:#e65100,stroke-width:2px
|
||||
classDef api fill:#fce4ec,stroke:#880e4f,stroke-width:2px
|
||||
|
||||
class shared,datamodels,aicore,connectors foundation
|
||||
class interfaces data
|
||||
class services,workflows business
|
||||
class features feature
|
||||
class routes,security api
|
||||
```
|
||||
|
||||
### Draw.io Diagram
|
||||
|
||||
A detailed draw.io diagram is available in `DEPENDENCY_DIAGRAM.drawio` with:
|
||||
- Color-coded layers (Foundation, Data, Business Logic, Features, API)
|
||||
- Arrow directions showing import relationships
|
||||
- ✅ markers on correct dependency directions
|
||||
- Dashed line for callback registry pattern
|
||||
- Status box showing zero violations
|
||||
|
||||
**Key Visual Elements:**
|
||||
- **Thick green arrows (✅)**: Correct dependency directions (services→interfaces, features→interfaces, features→services)
|
||||
- **Dashed purple line**: Callback registry pattern (interfaces→shared, decoupled from features)
|
||||
- **Color coding**: Each layer has distinct colors for easy identification
|
||||
- **Status indicators**: ✅ markers show compliance, "No violations" labels confirm architectural correctness
|
||||
|
||||
---
|
||||
|
||||
## Detailed Analysis
|
||||
|
||||
### 1. interfaces/ → services/ ✅ RESOLVED
|
||||
|
||||
**Current State:**
|
||||
- ✅ **No imports from services/** in `interfaces/`
|
||||
- All extraction-related functions moved to `services/serviceExtraction/`
|
||||
- Dependency violations resolved
|
||||
|
||||
**Impact:** Major architectural improvement - interfaces no longer depend on services.
|
||||
|
||||
---
|
||||
|
||||
### 2. interfaces/ → features/ ✅ RESOLVED
|
||||
|
||||
**Previous State:**
|
||||
- `interfaceDbChatObjects.py` (line 1754): Lazy import in `_triggerAutomationSync()` helper method
|
||||
```python
|
||||
from modules.features.automation import syncAutomationEvents
|
||||
```
|
||||
|
||||
**Current State:**
|
||||
- ✅ **No imports from features/** in `interfaces/`
|
||||
- Uses callback registry pattern (`shared.callbackRegistry`) for decoupled notifications
|
||||
- Interface triggers callbacks without knowing which features are listening
|
||||
- Feature registers callback in `featuresLifecycle.py` startup
|
||||
|
||||
**Refactoring:**
|
||||
- Created `shared/callbackRegistry.py` - decoupled event notification system
|
||||
- Interface calls `callbackRegistry.trigger('automation.changed', self)` instead of importing feature
|
||||
- Feature registers callback on startup: `callbackRegistry.register('automation.changed', onAutomationChanged)`
|
||||
|
||||
**Impact:** Perfect separation - interface doesn't know about features, uses shared callback registry.
|
||||
|
||||
---
|
||||
|
||||
### 3. services/ → interfaces/ ✅ CORRECT DIRECTION
|
||||
|
||||
**Current State:**
|
||||
- `serviceAi/mainServiceAi.py`: Imports `AiObjects` from `interfaceAiObjects`
|
||||
- `serviceExtraction/mainServiceExtraction.py`: Lazy import from `interfaceDbComponentObjects`
|
||||
- `serviceUtils/mainServiceUtils.py`: Lazy import from `interfaceDbChatObjects`
|
||||
- `serviceTicket/mainServiceTicket.py`: Imports from `interfaceTicketObjects`
|
||||
- `services/__init__.py`: Lazy imports from multiple interfaces
|
||||
|
||||
**Impact:** This is **correct** - services should use interfaces for data access. This follows the dependency rule: `services/` → `interfaces/` ✅
|
||||
|
||||
**Note:** This is **unidirectional** (services → interfaces), not bidirectional.
|
||||
|
||||
---
|
||||
|
||||
### 4. services/ → features/ ✅ NONE
|
||||
|
||||
**Current State:**
|
||||
- ✅ **No imports from features/** in `services/`
|
||||
|
||||
**Impact:** Services correctly do not depend on features.
|
||||
|
||||
---
|
||||
|
||||
### 5. features/ → interfaces/ ✅ CORRECT DIRECTION
|
||||
|
||||
**Current State:**
|
||||
- `features/automation/mainAutomation.py`: Imports from `interfaceDbChatObjects`, `interfaceDbAppObjects`
|
||||
- `features/featuresLifecycle.py`: Imports from `interfaceDbAppObjects`, `interfaceDbChatObjects` (lazy)
|
||||
|
||||
**Impact:** This is **correct** - features should use interfaces for data access. This follows the dependency rule: `features/` → `interfaces/` ✅
|
||||
|
||||
**Note:** This is **unidirectional** (features → interfaces), not bidirectional.
|
||||
|
||||
---
|
||||
|
||||
### 6. features/ → services/ ✅ CORRECT DIRECTION
|
||||
|
||||
**Current State:**
|
||||
- `features/neutralizePlayground/mainNeutralizePlayground.py` (line 123): Lazy import from `serviceSharepoint`
|
||||
|
||||
**Impact:** This is **correct** - features can use services. This follows the dependency rule: `features/` → `services/` ✅
|
||||
|
||||
---
|
||||
|
||||
## Complete Import Matrix (Fact-Based)
|
||||
|
||||
### aicore/
|
||||
- **Imports from:** `datamodels/`, `shared/`
|
||||
- **Imported by:** `interfaces/`, `services/`, `workflows/`
|
||||
- **Bidirectional:** None ✅
|
||||
|
||||
### connectors/
|
||||
- **Imports from:** `datamodels/`, `shared/`
|
||||
- **Imported by:** `interfaces/`
|
||||
- **Bidirectional:** None ✅
|
||||
|
||||
### datamodels/
|
||||
- **Imports from:** `shared/`
|
||||
- **Imported by:** `aicore/`, `connectors/`, `features/`, `interfaces/`, `routes/`, `security/`, `services/`, `workflows/`
|
||||
- **Bidirectional:** None ✅
|
||||
|
||||
### features/
|
||||
- **Imports from:** `datamodels/`, `interfaces/`, `services/`, `shared/`, `workflows/`
|
||||
- **Imported by:** `routes/`
|
||||
- **✅ UNIDIRECTIONAL:** No longer imported by `interfaces/`
|
||||
|
||||
**Detailed imports:**
|
||||
- From `interfaces/`: `interfaceDbChatObjects`, `interfaceDbAppObjects`
|
||||
- From `services/`: `serviceSharepoint` (lazy, in `neutralizePlayground`)
|
||||
- From `features/`: `chatPlayground` (in `automation`), `syncDelta`, `chatAlthaus` (in `featuresLifecycle`)
|
||||
|
||||
### interfaces/
|
||||
- **Imports from:** `aicore/`, `connectors/`, `datamodels/`, `shared/`
|
||||
- **Imported by:** `features/`, `routes/`, `security/`, `services/`
|
||||
- **✅ RESOLVED:** No longer imports from `services/` or `features/`
|
||||
|
||||
**Detailed imports:**
|
||||
- From `shared/`: `callbackRegistry` (for decoupled event notifications), `eventManagement` (for event removal in delete), `timeUtils`, `configuration`, `debugLogger`
|
||||
- From `interfaces/`: Internal imports (`interfaceDbChatAccess`, `interfaceDbAppAccess`, `interfaceDbComponentAccess`)
|
||||
|
||||
### routes/
|
||||
- **Imports from:** `datamodels/`, `features/`, `interfaces/`, `security/`, `services/`, `shared/`
|
||||
- **Imported by:** None (top-level API layer)
|
||||
- **Bidirectional:** None ✅
|
||||
|
||||
**Detailed imports:**
|
||||
- From `interfaces/`: `interfaceDbChatObjects`, `interfaceDbAppObjects`, `interfaceDbComponentObjects`, `interfaceVoiceObjects`
|
||||
- From `features/**: `features.automation`, `features.chatPlayground`, `features.neutralizePlayground`
|
||||
|
||||
### security/
|
||||
- **Imports from:** `datamodels/`, `interfaces/`, `shared/`
|
||||
- **Imported by:** `routes/`, `services/`
|
||||
- **Bidirectional:** None ✅
|
||||
|
||||
**Detailed imports:**
|
||||
- From `interfaces/**: `interfaceDbAppObjects` (lazy imports)
|
||||
|
||||
### services/
|
||||
- **Imports from:** `aicore/`, `datamodels/`, `interfaces/`, `security/`, `shared/`
|
||||
- **Imported by:** `features/`, `routes/`, `workflows/`
|
||||
- **✅ UNIDIRECTIONAL:** Only imports from `interfaces/` (correct direction)
|
||||
- **✅ RESOLVED:** No longer imported by `interfaces/`
|
||||
|
||||
**Detailed imports:**
|
||||
- From `interfaces/**: `interfaceAiObjects`, `interfaceDbComponentObjects` (lazy), `interfaceDbChatObjects` (lazy), `interfaceTicketObjects`
|
||||
- From `services/**: Internal imports (service-to-service)
|
||||
|
||||
### shared/
|
||||
- **Imports from:** None (foundation layer)
|
||||
- **Imported by:** `aicore/`, `connectors/`, `datamodels/`, `features/`, `interfaces/`, `routes/`, `security/`, `services/`, `workflows/`
|
||||
- **Bidirectional:** None ✅
|
||||
|
||||
### workflows/
|
||||
- **Imports from:** `aicore/`, `datamodels/`, `services/`, `shared/`
|
||||
- **Imported by:** `features/`
|
||||
- **Bidirectional:** None ✅
|
||||
|
||||
**Detailed imports:**
|
||||
- From `services/**: `serviceGeneration` (lazy, in `methodAi.py`)
|
||||
|
||||
---
|
||||
|
||||
## Refactoring Impact Summary
|
||||
|
||||
### Before Refactoring:
|
||||
- ❌ **interfaces/ ↔ services/**: Bidirectional (violations)
|
||||
- `interfaces/` imported from `services/serviceExtraction/` (6 violations)
|
||||
- `services/` imported from `interfaces/` (correct)
|
||||
- ❌ **interfaces/ ↔ features/**: Bidirectional (violation)
|
||||
- `interfaces/` imported from `features.chatPlayground` (1 violation)
|
||||
- `features/` imported from `interfaces/` (correct)
|
||||
|
||||
### After Refactoring:
|
||||
- ✅ **interfaces/ → services/**: RESOLVED (no imports)
|
||||
- ✅ **services/ → interfaces/**: UNIDIRECTIONAL (correct direction)
|
||||
- ✅ **interfaces/ → features/**: RESOLVED (uses callback registry pattern)
|
||||
- ✅ **features/ → interfaces/**: UNIDIRECTIONAL (correct direction)
|
||||
- ✅ **features/ → services/**: CORRECT DIRECTION (1 lazy import)
|
||||
|
||||
---
|
||||
|
||||
## Specific Import Details
|
||||
|
||||
### interfaces/ → features/ ✅ RESOLVED
|
||||
|
||||
**Previous:** `interfaceDbChatObjects.py` (line 1754) had lazy import from `features.automation`
|
||||
```python
|
||||
from modules.features.automation import syncAutomationEvents
|
||||
```
|
||||
|
||||
**Current:** Uses `shared.callbackRegistry` pattern (line 1754):
|
||||
- Interface calls: `callbackRegistry.trigger('automation.changed', self)`
|
||||
- Feature registers callback in `featuresLifecycle.py`: `callbackRegistry.register('automation.changed', onAutomationChanged)`
|
||||
- **Zero direct imports** from features in interfaces
|
||||
- **Verification:** `grep "from modules.features" interfaces/` returns no matches ✅
|
||||
|
||||
### features/ → services/ (1 import, correct direction)
|
||||
|
||||
**File:** `features/neutralizePlayground/mainNeutralizePlayground.py`
|
||||
- **Line:** 123
|
||||
- **Import:** `from modules.services.serviceSharepoint.mainServiceSharepoint import SharepointService`
|
||||
- **Type:** Lazy import (inside method)
|
||||
- **Context:** Used for SharePoint file processing
|
||||
- **Status:** ✅ CORRECT - Features can import from services
|
||||
|
||||
---
|
||||
|
||||
## Recommendations
|
||||
|
||||
### ✅ Completed Improvements
|
||||
1. **Resolved interfaces/ → services/ violations** - Moved extraction functions to `serviceExtraction/`
|
||||
2. **Resolved interfaces/ → features/ violations** - Moved automation handler to `features/automation/`
|
||||
3. **Eliminated ALL bidirectional dependencies** - `interfaces/` no longer imports from `services/` or `features/`
|
||||
4. **Implemented callback registry pattern** - Decoupled event notifications using `shared.callbackRegistry`
|
||||
5. **Follows dependency rules perfectly** - All dependencies now follow correct direction:
|
||||
- `services/` → `interfaces/` ✅
|
||||
- `features/` → `interfaces/` ✅
|
||||
- `features/` → `services/` ✅
|
||||
- `interfaces/` → `shared/` only ✅
|
||||
|
||||
### Best Practices
|
||||
- ✅ Use lazy imports (inside functions) for dependencies when appropriate
|
||||
- ✅ Services correctly depend on interfaces (unidirectional)
|
||||
- ✅ Features correctly depend on interfaces and services (unidirectional)
|
||||
- ✅ Interfaces completely independent (only foundation layers)
|
||||
- ✅ Use callback registry for decoupled event notifications
|
||||
- ✅ Document dependency relationships clearly
|
||||
- ✅ Monitor for circular import errors
|
||||
|
||||
---
|
||||
|
||||
## Dependency Rule Compliance
|
||||
|
||||
### Current Rules:
|
||||
- ✅ **features/** → **services/** ✅ (correct)
|
||||
- ✅ **services/** → **interfaces/** ✅ (correct)
|
||||
- ✅ **features/** → **interfaces/** ✅ (correct)
|
||||
|
||||
### Status:
|
||||
- ✅ **interfaces/** → **services/**: **RESOLVED** (was violation, now compliant)
|
||||
- ✅ **services/** → **interfaces/**: **COMPLIANT** (correct direction)
|
||||
- ✅ **features/** → **interfaces/**: **COMPLIANT** (correct direction)
|
||||
- ✅ **features/** → **services/**: **COMPLIANT** (correct direction)
|
||||
- ✅ **interfaces/** → **features/**: **RESOLVED** (was violation, now uses callback registry)
|
||||
|
||||
---
|
||||
|
||||
## Conclusion
|
||||
|
||||
The refactoring successfully resolved **ALL bidirectional dependencies**:
|
||||
- ✅ **interfaces/ ↔ services/**: RESOLVED
|
||||
- ✅ **interfaces/ ↔ features/**: RESOLVED (using callback registry pattern)
|
||||
|
||||
The architecture now follows the intended dependency rules **perfectly**:
|
||||
- `interfaces/` only imports from foundation layers (`aicore/`, `connectors/`, `datamodels/`, `shared/`)
|
||||
- `services/` imports from `interfaces/` (correct direction)
|
||||
- `features/` imports from `interfaces/` and `services/` (correct direction)
|
||||
- **Zero violations** - perfect architectural compliance achieved through callback registry pattern
|
||||
|
||||
---
|
||||
|
||||
## Architecture Layers
|
||||
|
||||
The codebase follows a clean layered architecture:
|
||||
|
||||
1. **Foundation Layer** (`shared/`, `datamodels/`)
|
||||
- No dependencies on other modules
|
||||
- Used by all layers
|
||||
|
||||
2. **Infrastructure Layer** (`aicore/`, `connectors/`)
|
||||
- Depends only on foundation
|
||||
- Provides core capabilities
|
||||
|
||||
3. **Data Access Layer** (`interfaces/`)
|
||||
- Depends only on foundation and infrastructure
|
||||
- Provides data access abstraction
|
||||
|
||||
4. **Business Logic Layer** (`services/`, `workflows/`)
|
||||
- Depends on interfaces and foundation
|
||||
- Implements business logic
|
||||
|
||||
5. **Feature Layer** (`features/`)
|
||||
- Depends on interfaces, services, and foundation
|
||||
- Implements user-facing features
|
||||
|
||||
6. **API Layer** (`routes/`, `security/`)
|
||||
- Depends on all layers
|
||||
- Provides HTTP API endpoints
|
||||
|
|
@ -1 +0,0 @@
|
|||
<mxfile host="Electron" modified="2025-12-02T16:28:53.356Z" agent="5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) draw.io/20.3.0 Chrome/104.0.5112.114 Electron/20.1.3 Safari/537.36" etag="L77fz7tGmuPPsr8RbEBA" version="20.3.0" type="device"><diagram name="Module Dependencies" id="dependency-diagram">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</diagram></mxfile>
|
||||
|
|
@ -1,199 +0,0 @@
|
|||
# Features → Interfaces Import Analysis
|
||||
|
||||
## Summary
|
||||
|
||||
This document details all imports from `features/` modules to `interfaces/` modules.
|
||||
|
||||
**Total Feature Modules:** 6
|
||||
**Modules Importing from Interfaces:** 2 (only `getRootInterface` - system-level function)
|
||||
**Total Interface Imports:** 2 (both for `getRootInterface` only)
|
||||
|
||||
**✅ REFACTORED:** All feature modules now use `services.getInterface()` to access interfaces, following the same pattern as `chatPlayground`. Only `getRootInterface()` remains as a direct import (system-level function, not user-specific).
|
||||
|
||||
---
|
||||
|
||||
## Detailed Import List
|
||||
|
||||
### 1. `features/featuresLifecycle.py`
|
||||
|
||||
**Imports:**
|
||||
- **Line 2:** `from modules.interfaces.interfaceDbAppObjects import getRootInterface`
|
||||
- **Type:** Direct import
|
||||
- **Usage:** Gets root interface to retrieve event user for feature initialization
|
||||
- **Context:** Used in `start()` function to get event user for automation, syncDelta, and chatAlthaus features
|
||||
- **Note:** `getRootInterface()` is a system-level function (no user required), so it remains as direct import
|
||||
|
||||
**Refactored:**
|
||||
- ✅ **Removed:** `from modules.interfaces.interfaceDbChatObjects import getInterface as getChatInterface`
|
||||
- ✅ **Added:** `from modules.services import getInterface as getServices`
|
||||
- ✅ **Changed:** Now uses `services.interfaceDbChat` instead of direct interface import
|
||||
- **Pattern:** `services = getServices(eventUser, None)` then `services.interfaceDbChat`
|
||||
|
||||
**Purpose:** Feature lifecycle management - initializes and manages all features on startup/shutdown.
|
||||
|
||||
---
|
||||
|
||||
### 2. `features/automation/mainAutomation.py`
|
||||
|
||||
**Imports:**
|
||||
- **Line 14:** `from modules.interfaces.interfaceDbAppObjects import getRootInterface`
|
||||
- **Type:** Direct import
|
||||
- **Usage:** Gets root interface to retrieve event user (system-level function)
|
||||
- **Context:** Used in `createAutomationEventHandler()` to get event user
|
||||
- **Note:** `getRootInterface()` is a system-level function (no user required), so it remains as direct import
|
||||
|
||||
**Refactored:**
|
||||
- ✅ **Removed:** `from modules.interfaces.interfaceDbChatObjects import getInterface as getChatInterface`
|
||||
- ✅ **Removed:** `from modules.interfaces.interfaceDbAppObjects import getInterface as getAppInterface`
|
||||
- ✅ **Added:** `from modules.services import getInterface as getServices`
|
||||
- ✅ **Changed:** All interface access now goes through services:
|
||||
- `executeAutomation()`: Uses `services.interfaceDbApp` and `services.interfaceDbChat`
|
||||
- `createAutomationEventHandler()`: Uses `eventServices.interfaceDbChat` and `eventServices.interfaceDbApp`
|
||||
- **Pattern:** `services = getServices(user, None)` then `services.interfaceDbChat` or `services.interfaceDbApp`
|
||||
|
||||
**Purpose:** Automation workflow execution and scheduling - handles automated workflow triggers and event scheduling.
|
||||
|
||||
---
|
||||
|
||||
### 3. `features/chatPlayground/mainChatPlayground.py`
|
||||
|
||||
**Imports:**
|
||||
- ❌ **No imports from interfaces/**
|
||||
- Uses `modules.services.getInterface` instead (indirect access through services layer)
|
||||
|
||||
**Purpose:** Chat playground feature - interactive chat interface.
|
||||
|
||||
---
|
||||
|
||||
### 4. `features/chatAlthaus/mainChatAlthaus.py`
|
||||
|
||||
**Imports:**
|
||||
- ❌ **No imports from interfaces/**
|
||||
- Uses `modules.services.getInterface` instead (indirect access through services layer)
|
||||
|
||||
**Purpose:** Chat Althaus data scheduler - scheduled data updates for Althaus preprocessing.
|
||||
|
||||
---
|
||||
|
||||
### 5. `features/syncDelta/mainSyncDelta.py`
|
||||
|
||||
**Imports:**
|
||||
- ❌ **No imports from interfaces/**
|
||||
- Uses `modules.services.getInterface` instead (indirect access through services layer)
|
||||
|
||||
**Purpose:** Delta Group sync manager - synchronizes tickets to SharePoint.
|
||||
|
||||
---
|
||||
|
||||
### 6. `features/neutralizePlayground/mainNeutralizePlayground.py`
|
||||
|
||||
**Imports:**
|
||||
- ❌ **No imports from interfaces/**
|
||||
- Uses `modules.services.getInterface` instead (indirect access through services layer)
|
||||
|
||||
**Purpose:** Neutralization playground - UI wrapper for data neutralization service.
|
||||
|
||||
---
|
||||
|
||||
## Import Statistics
|
||||
|
||||
### By Interface Module
|
||||
|
||||
**`interfaceDbAppObjects`:**
|
||||
- `getRootInterface`: 2 imports (system-level function, remains as direct import)
|
||||
- `features/featuresLifecycle.py` (line 2)
|
||||
- `features/automation/mainAutomation.py` (line 14)
|
||||
|
||||
**`interfaceDbChatObjects`:**
|
||||
- ✅ **Removed:** All direct imports refactored to use services layer
|
||||
- Now accessed via `services.interfaceDbChat` after calling `getServices(user, None)`
|
||||
|
||||
**`interfaceDbAppObjects.getInterface`:**
|
||||
- ✅ **Removed:** All direct imports refactored to use services layer
|
||||
- Now accessed via `services.interfaceDbApp` after calling `getServices(user, None)`
|
||||
|
||||
### By Import Type
|
||||
|
||||
- **Direct imports:** 2 (only `getRootInterface` - system-level function)
|
||||
- `features/featuresLifecycle.py`: 1
|
||||
- `features/automation/mainAutomation.py`: 1
|
||||
|
||||
- **Services-based access:** All user-specific interface access now goes through services layer
|
||||
- Pattern: `services = getServices(user, None)` then `services.interfaceDbChat` or `services.interfaceDbApp`
|
||||
|
||||
---
|
||||
|
||||
## Architectural Notes
|
||||
|
||||
### ✅ Correct Dependency Direction
|
||||
|
||||
All imports follow the correct architectural direction:
|
||||
- **features/** → **interfaces/** ✅
|
||||
|
||||
This is compliant with the dependency rules:
|
||||
- Features can import from interfaces (correct)
|
||||
- Features can import from services (correct)
|
||||
- Features do NOT import from other features (except internal feature-to-feature imports)
|
||||
|
||||
### Import Patterns
|
||||
|
||||
1. **Direct Interface Access:**
|
||||
- `features/automation/mainAutomation.py` - Directly imports interfaces for automation management
|
||||
- `features/featuresLifecycle.py` - Directly imports `getRootInterface` for feature initialization
|
||||
|
||||
2. **Indirect Access via Services:**
|
||||
- `features/chatPlayground/mainChatPlayground.py`
|
||||
- `features/chatAlthaus/mainChatAlthaus.py`
|
||||
- `features/syncDelta/mainSyncDelta.py`
|
||||
- `features/neutralizePlayground/mainNeutralizePlayground.py`
|
||||
|
||||
These features use `modules.services.getInterface` which provides a service layer abstraction.
|
||||
|
||||
### Usage Context
|
||||
|
||||
**`interfaceDbAppObjects`:**
|
||||
- Used for user management (`getRootInterface`, `getAppInterface`)
|
||||
- Primarily for getting event user and creator user in automation context
|
||||
|
||||
**`interfaceDbChatObjects`:**
|
||||
- Used for chat/automation data access (`getChatInterface`)
|
||||
- Used for automation execution, event syncing, and workflow management
|
||||
|
||||
---
|
||||
|
||||
## Summary Table
|
||||
|
||||
| Feature Module | Interface Imports | Import Type | Purpose |
|
||||
|---------------|-------------------|-------------|---------|
|
||||
| `featuresLifecycle.py` | `interfaceDbAppObjects.getRootInterface` | Direct | Feature initialization (system-level) |
|
||||
| `featuresLifecycle.py` | ✅ Via `services.interfaceDbChat` | Services | Automation event sync |
|
||||
| `automation/mainAutomation.py` | `interfaceDbAppObjects.getRootInterface` | Direct | Event user access (system-level) |
|
||||
| `automation/mainAutomation.py` | ✅ Via `services.interfaceDbChat` | Services | Automation execution |
|
||||
| `automation/mainAutomation.py` | ✅ Via `services.interfaceDbApp` | Services | User management |
|
||||
| `chatPlayground/mainChatPlayground.py` | None | - | Uses services layer |
|
||||
| `chatAlthaus/mainChatAlthaus.py` | None | - | Uses services layer |
|
||||
| `syncDelta/mainSyncDelta.py` | None | - | Uses services layer |
|
||||
| `neutralizePlayground/mainNeutralizePlayground.py` | None | - | Uses services layer |
|
||||
|
||||
---
|
||||
|
||||
## Conclusion
|
||||
|
||||
**Total Interface Imports:** 2 (only `getRootInterface` - system-level function)
|
||||
- 2 direct imports (both for `getRootInterface`)
|
||||
|
||||
**Modules Using Direct Interface Imports:** 2 out of 6 (only for `getRootInterface`)
|
||||
- `features/featuresLifecycle.py`
|
||||
- `features/automation/mainAutomation.py`
|
||||
|
||||
**✅ REFACTORED:** All user-specific interface access now goes through services layer
|
||||
- Pattern: `services = getServices(user, None)` then `services.interfaceDbChat` or `services.interfaceDbApp`
|
||||
- Consistent with other feature modules (`chatPlayground`, `chatAlthaus`, `syncDelta`, `neutralizePlayground`)
|
||||
|
||||
**Architectural Compliance:** ✅ **PERFECT**
|
||||
- All imports follow correct direction (features → interfaces)
|
||||
- Only system-level function (`getRootInterface`) remains as direct import
|
||||
- All user-specific interface access goes through services layer
|
||||
- Clean separation maintained
|
||||
- Consistent pattern across all feature modules
|
||||
|
||||
|
|
@ -62,7 +62,7 @@ class ChatLog(BaseModel):
|
|||
None, description="Performance metrics"
|
||||
)
|
||||
parentId: Optional[str] = Field(
|
||||
None, description="Parent log entry ID for hierarchical display"
|
||||
None, description="Parent operation ID (operationId of parent operation) for hierarchical display"
|
||||
)
|
||||
operationId: Optional[str] = Field(
|
||||
None, description="Operation ID to group related log entries"
|
||||
|
|
@ -828,6 +828,7 @@ class TaskContext(BaseModel):
|
|||
failurePatterns: Optional[list[str]] = Field(default_factory=list)
|
||||
failedActions: Optional[list] = Field(default_factory=list)
|
||||
successfulActions: Optional[list] = Field(default_factory=list)
|
||||
executedActions: Optional[list] = Field(default_factory=list, description="List of executed actions with action name, parameters, and step number")
|
||||
criteriaProgress: Optional[dict] = None
|
||||
|
||||
# Stage 2 context fields (NEW)
|
||||
|
|
|
|||
|
|
@ -570,7 +570,7 @@ class ChatObjects:
|
|||
allWorkflows = self.db.getRecordset(ChatWorkflow)
|
||||
filteredWorkflows = self._uam(ChatWorkflow, allWorkflows)
|
||||
|
||||
# If no pagination requested, return all items
|
||||
# If no pagination requested, return all items (no sorting - frontend handles it)
|
||||
if pagination is None:
|
||||
return filteredWorkflows
|
||||
|
||||
|
|
@ -578,7 +578,7 @@ class ChatObjects:
|
|||
if pagination.filters:
|
||||
filteredWorkflows = self._applyFilters(filteredWorkflows, pagination.filters)
|
||||
|
||||
# Apply sorting (in order of sortFields)
|
||||
# Apply sorting (in order of sortFields) - only if provided by frontend
|
||||
if pagination.sort:
|
||||
filteredWorkflows = self._applySorting(filteredWorkflows, pagination.sort)
|
||||
|
||||
|
|
|
|||
|
|
@ -205,10 +205,8 @@ Respond with ONLY a JSON object in this exact format:
|
|||
documentMetadata = None # Store document metadata (title, filename) from first iteration
|
||||
accumulationState = None # Track accumulation state for string accumulation
|
||||
|
||||
# Get parent log ID for iteration operations
|
||||
parentLogId = None
|
||||
if operationId:
|
||||
parentLogId = self.services.chat.getOperationLogId(operationId)
|
||||
# Get parent operation ID for iteration operations (parentId should be operationId, not log entry ID)
|
||||
parentOperationId = operationId # Use the parent's operationId directly
|
||||
|
||||
while iteration < maxIterations:
|
||||
iteration += 1
|
||||
|
|
@ -222,7 +220,7 @@ Respond with ONLY a JSON object in this exact format:
|
|||
"AI Call",
|
||||
f"Iteration {iteration}",
|
||||
"",
|
||||
parentId=parentLogId
|
||||
parentOperationId=parentOperationId
|
||||
)
|
||||
|
||||
# Build iteration prompt
|
||||
|
|
@ -235,11 +233,14 @@ Respond with ONLY a JSON object in this exact format:
|
|||
logger.warning(f"Iteration {iteration}: No previous response available for continuation!")
|
||||
|
||||
# Filter promptArgs to only include parameters that buildGenerationPrompt accepts
|
||||
# buildGenerationPrompt accepts: outputFormat, userPrompt, title, extracted_content, continuationContext
|
||||
# buildGenerationPrompt accepts: outputFormat, userPrompt, title, extracted_content, continuationContext, services
|
||||
filteredPromptArgs = {
|
||||
k: v for k, v in promptArgs.items()
|
||||
if k in ['outputFormat', 'userPrompt', 'title', 'extracted_content']
|
||||
if k in ['outputFormat', 'userPrompt', 'title', 'extracted_content', 'services']
|
||||
}
|
||||
# Always include services if available
|
||||
if not filteredPromptArgs.get('services') and hasattr(self, 'services'):
|
||||
filteredPromptArgs['services'] = self.services
|
||||
|
||||
# Rebuild prompt with continuation context using the provided prompt builder
|
||||
iterationPrompt = await promptBuilder(**filteredPromptArgs, continuationContext=continuationContext)
|
||||
|
|
@ -266,9 +267,20 @@ Respond with ONLY a JSON object in this exact format:
|
|||
response = await self.callAi(request)
|
||||
result = response.content
|
||||
|
||||
# Update progress after AI call
|
||||
# Track bytes for progress reporting
|
||||
bytesReceived = len(result.encode('utf-8')) if result else 0
|
||||
totalBytesSoFar = sum(len(section.get('content', '').encode('utf-8')) if isinstance(section.get('content'), str) else 0 for section in allSections) + bytesReceived
|
||||
|
||||
# Update progress after AI call with byte information
|
||||
if iterationOperationId:
|
||||
self.services.chat.progressLogUpdate(iterationOperationId, 0.6, "AI response received")
|
||||
# Format bytes for display (kB or MB)
|
||||
if totalBytesSoFar < 1024:
|
||||
bytesDisplay = f"{totalBytesSoFar}B"
|
||||
elif totalBytesSoFar < 1024 * 1024:
|
||||
bytesDisplay = f"{totalBytesSoFar / 1024:.1f}kB"
|
||||
else:
|
||||
bytesDisplay = f"{totalBytesSoFar / (1024 * 1024):.1f}MB"
|
||||
self.services.chat.progressLogUpdate(iterationOperationId, 0.6, f"AI response received ({bytesDisplay})")
|
||||
|
||||
# Write raw AI response to debug file
|
||||
if iteration == 1:
|
||||
|
|
@ -469,8 +481,24 @@ Respond with ONLY a JSON object in this exact format:
|
|||
# The break can occur anywhere - in any section, at any depth
|
||||
allSections = JsonResponseHandler.mergeSectionsIntelligently(allSections, extractedSections, iteration)
|
||||
|
||||
# Log merged sections for debugging
|
||||
# Calculate total bytes in merged content for progress display
|
||||
merged_json_str = json.dumps(allSections, indent=2, ensure_ascii=False)
|
||||
totalBytesGenerated = len(merged_json_str.encode('utf-8'))
|
||||
|
||||
# Update main operation with byte progress
|
||||
if operationId:
|
||||
# Format bytes for display
|
||||
if totalBytesGenerated < 1024:
|
||||
bytesDisplay = f"{totalBytesGenerated}B"
|
||||
elif totalBytesGenerated < 1024 * 1024:
|
||||
bytesDisplay = f"{totalBytesGenerated / 1024:.1f}kB"
|
||||
else:
|
||||
bytesDisplay = f"{totalBytesGenerated / (1024 * 1024):.1f}MB"
|
||||
# Estimate progress based on iterations (rough estimate)
|
||||
estimatedProgress = min(0.9, 0.4 + (iteration * 0.1))
|
||||
self.services.chat.progressLogUpdate(operationId, estimatedProgress, f"Pipeline: {bytesDisplay} (iteration {iteration})")
|
||||
|
||||
# Log merged sections for debugging
|
||||
self.services.utils.writeDebugFile(merged_json_str, f"{debugPrefix}_merged_sections_iteration_{iteration}")
|
||||
|
||||
# Check if we should continue (completion detection)
|
||||
|
|
@ -485,14 +513,40 @@ Respond with ONLY a JSON object in this exact format:
|
|||
if shouldContinue:
|
||||
# Finish iteration operation (will continue with next iteration)
|
||||
if iterationOperationId:
|
||||
# Show byte progress in iteration completion
|
||||
iterBytes = len(result.encode('utf-8')) if result else 0
|
||||
if iterBytes < 1024:
|
||||
iterBytesDisplay = f"{iterBytes}B"
|
||||
elif iterBytes < 1024 * 1024:
|
||||
iterBytesDisplay = f"{iterBytes / 1024:.1f}kB"
|
||||
else:
|
||||
iterBytesDisplay = f"{iterBytes / (1024 * 1024):.1f}MB"
|
||||
self.services.chat.progressLogUpdate(iterationOperationId, 0.95, f"Completed ({iterBytesDisplay})")
|
||||
self.services.chat.progressLogFinish(iterationOperationId, True)
|
||||
continue
|
||||
else:
|
||||
# Done - finish iteration and update main operation
|
||||
if iterationOperationId:
|
||||
# Show final byte count
|
||||
finalBytes = len(merged_json_str.encode('utf-8'))
|
||||
if finalBytes < 1024:
|
||||
finalBytesDisplay = f"{finalBytes}B"
|
||||
elif finalBytes < 1024 * 1024:
|
||||
finalBytesDisplay = f"{finalBytes / 1024:.1f}kB"
|
||||
else:
|
||||
finalBytesDisplay = f"{finalBytes / (1024 * 1024):.1f}MB"
|
||||
self.services.chat.progressLogUpdate(iterationOperationId, 0.95, f"Complete ({finalBytesDisplay})")
|
||||
self.services.chat.progressLogFinish(iterationOperationId, True)
|
||||
if operationId:
|
||||
self.services.chat.progressLogUpdate(operationId, 0.95, f"Generation complete ({iteration} iterations, {len(allSections)} sections)")
|
||||
# Show final size in main operation
|
||||
finalBytes = len(merged_json_str.encode('utf-8'))
|
||||
if finalBytes < 1024:
|
||||
finalBytesDisplay = f"{finalBytes}B"
|
||||
elif finalBytes < 1024 * 1024:
|
||||
finalBytesDisplay = f"{finalBytes / 1024:.1f}kB"
|
||||
else:
|
||||
finalBytesDisplay = f"{finalBytes / (1024 * 1024):.1f}MB"
|
||||
self.services.chat.progressLogUpdate(operationId, 0.95, f"Generation complete: {finalBytesDisplay} ({iteration} iterations, {len(allSections)} sections)")
|
||||
logger.info(f"Generation complete after {iteration} iterations: {len(allSections)} sections")
|
||||
break
|
||||
|
||||
|
|
@ -907,7 +961,7 @@ If no trackable items can be identified, return: {{"kpis": []}}
|
|||
# Debug: persist prompt/response for analysis with context-specific naming
|
||||
debugPrefix = debugType if debugType else "plan"
|
||||
self.services.utils.writeDebugFile(fullPrompt, f"{debugPrefix}_prompt")
|
||||
response = await self.aiObjects.call(request)
|
||||
response = await self.aiObjects.callWithTextContext(request)
|
||||
result = response.content or ""
|
||||
self.services.utils.writeDebugFile(result, f"{debugPrefix}_response")
|
||||
return result
|
||||
|
|
@ -941,10 +995,8 @@ If no trackable items can be identified, return: {{"kpis": []}}
|
|||
workflowId = self.services.workflow.id if self.services.workflow else f"no-workflow-{int(time.time())}"
|
||||
aiOperationId = f"ai_content_{workflowId}_{int(time.time())}"
|
||||
|
||||
# Get parent log ID if parent operation exists
|
||||
parentLogId = None
|
||||
if parentOperationId:
|
||||
parentLogId = self.services.chat.getOperationLogId(parentOperationId)
|
||||
# Use parent operation ID directly (parentId should be operationId, not log entry ID)
|
||||
# parentOperationId is already the operationId of the parent
|
||||
|
||||
# Start progress tracking with parent reference
|
||||
self.services.chat.progressLogStart(
|
||||
|
|
@ -952,7 +1004,7 @@ If no trackable items can be identified, return: {{"kpis": []}}
|
|||
"AI content processing",
|
||||
"Content Processing",
|
||||
f"Format: {outputFormat or 'text'}",
|
||||
parentId=parentLogId
|
||||
parentOperationId=parentOperationId
|
||||
)
|
||||
|
||||
try:
|
||||
|
|
@ -1122,7 +1174,7 @@ If no trackable items can be identified, return: {{"kpis": []}}
|
|||
self.services.utils.writeDebugFile(extractionPrompt, "content_extraction_prompt")
|
||||
|
||||
# Call generic content parts processor - handles images, text, chunking, merging
|
||||
extractionResponse = await self.aiObjects.call(extractionRequest)
|
||||
extractionResponse = await self.callAi(extractionRequest)
|
||||
|
||||
# Write debug file for extraction response
|
||||
if extractionResponse.content:
|
||||
|
|
@ -1153,14 +1205,15 @@ If no trackable items can be identified, return: {{"kpis": []}}
|
|||
from modules.services.serviceGeneration.subPromptBuilderGeneration import buildGenerationPrompt
|
||||
|
||||
generation_prompt = await buildGenerationPrompt(
|
||||
outputFormat, prompt, title, content_for_generation, None
|
||||
outputFormat, prompt, title, content_for_generation, None, self.services
|
||||
)
|
||||
|
||||
promptArgs = {
|
||||
"outputFormat": outputFormat,
|
||||
"userPrompt": prompt,
|
||||
"title": title,
|
||||
"extracted_content": content_for_generation
|
||||
"extracted_content": content_for_generation,
|
||||
"services": self.services
|
||||
}
|
||||
|
||||
self.services.chat.progressLogUpdate(aiOperationId, 0.4, "Calling AI for content generation")
|
||||
|
|
@ -1169,6 +1222,7 @@ If no trackable items can be identified, return: {{"kpis": []}}
|
|||
if promptArgs:
|
||||
userPrompt = promptArgs.get("userPrompt") or promptArgs.get("user_prompt")
|
||||
|
||||
# Track generation progress - the looping function will update with byte progress
|
||||
generated_json = await self._callAiWithLooping(
|
||||
generation_prompt,
|
||||
options,
|
||||
|
|
@ -1179,7 +1233,16 @@ If no trackable items can be identified, return: {{"kpis": []}}
|
|||
userPrompt=userPrompt
|
||||
)
|
||||
|
||||
self.services.chat.progressLogUpdate(aiOperationId, 0.7, "Parsing generated JSON")
|
||||
# Calculate final size for completion message
|
||||
finalSize = len(generated_json.encode('utf-8')) if generated_json else 0
|
||||
if finalSize < 1024:
|
||||
finalSizeDisplay = f"{finalSize}B"
|
||||
elif finalSize < 1024 * 1024:
|
||||
finalSizeDisplay = f"{finalSize / 1024:.1f}kB"
|
||||
else:
|
||||
finalSizeDisplay = f"{finalSize / (1024 * 1024):.1f}MB"
|
||||
|
||||
self.services.chat.progressLogUpdate(aiOperationId, 0.7, f"Parsing generated JSON ({finalSizeDisplay})")
|
||||
try:
|
||||
extracted_json = self.services.utils.jsonExtractString(generated_json)
|
||||
generated_data = json.loads(extracted_json)
|
||||
|
|
@ -1210,13 +1273,13 @@ If no trackable items can be identified, return: {{"kpis": []}}
|
|||
|
||||
# Create separate operation for content rendering
|
||||
renderOperationId = f"{aiOperationId}_render"
|
||||
renderParentLogId = self.services.chat.getOperationLogId(aiOperationId)
|
||||
# Use aiOperationId directly as parentOperationId (operationId, not log entry ID)
|
||||
self.services.chat.progressLogStart(
|
||||
renderOperationId,
|
||||
"Content Rendering",
|
||||
"Rendering",
|
||||
f"Format: {outputFormat}",
|
||||
parentId=renderParentLogId
|
||||
parentOperationId=aiOperationId
|
||||
)
|
||||
|
||||
try:
|
||||
|
|
|
|||
|
|
@ -1015,10 +1015,19 @@ class ChatService:
|
|||
def createProgressLogger(self) -> ProgressLogger:
|
||||
return ProgressLogger(self.services)
|
||||
|
||||
def progressLogStart(self, operationId: str, serviceName: str, actionName: str, context: str = "", parentId: Optional[str] = None):
|
||||
"""Wrapper for ProgressLogger.startOperation"""
|
||||
def progressLogStart(self, operationId: str, serviceName: str, actionName: str, context: str = "", parentOperationId: Optional[str] = None):
|
||||
"""Wrapper for ProgressLogger.startOperation
|
||||
|
||||
Args:
|
||||
operationId: Unique identifier for the operation
|
||||
serviceName: Name of the service
|
||||
actionName: Name of the action
|
||||
context: Additional context information
|
||||
parentOperationId: Optional parent operation ID (operationId of parent operation)
|
||||
The parentId in ChatLog will be set to this parentOperationId
|
||||
"""
|
||||
progressLogger = self._getProgressLogger()
|
||||
return progressLogger.startOperation(operationId, serviceName, actionName, context, parentId)
|
||||
return progressLogger.startOperation(operationId, serviceName, actionName, context, parentOperationId)
|
||||
|
||||
def progressLogUpdate(self, operationId: str, progress: float, statusUpdate: str = ""):
|
||||
"""Wrapper for ProgressLogger.updateOperation"""
|
||||
|
|
|
|||
|
|
@ -34,13 +34,21 @@ class ExtractionService:
|
|||
if model is None or model.calculatePriceUsd is None:
|
||||
raise RuntimeError(f"FATAL: Required internal model '{modelDisplayName}' is not available. Check connector registration.")
|
||||
|
||||
def extractContent(self, documents: List[ChatDocument], options: ExtractionOptions) -> List[ContentExtracted]:
|
||||
def extractContent(
|
||||
self,
|
||||
documents: List[ChatDocument],
|
||||
options: ExtractionOptions,
|
||||
operationId: Optional[str] = None,
|
||||
parentOperationId: Optional[str] = None
|
||||
) -> List[ContentExtracted]:
|
||||
"""
|
||||
Extract content from a list of ChatDocument objects.
|
||||
|
||||
Args:
|
||||
documents: List of ChatDocument objects to extract content from
|
||||
options: Extraction options including maxSize, chunkAllowed, mergeStrategy, etc.
|
||||
operationId: Optional operation ID for progress logging (parent operation)
|
||||
parentOperationId: Optional parent operation ID for hierarchical logging
|
||||
|
||||
Returns:
|
||||
List of ContentExtracted objects, one per input document
|
||||
|
|
@ -52,125 +60,172 @@ class ExtractionService:
|
|||
from modules.interfaces.interfaceDbComponentObjects import getInterface
|
||||
dbInterface = getInterface()
|
||||
|
||||
totalDocs = len(documents)
|
||||
|
||||
for i, doc in enumerate(documents):
|
||||
logger.info(f"=== DOCUMENT {i}: {doc.fileName} ===")
|
||||
logger.info(f"=== DOCUMENT {i + 1}/{totalDocs}: {doc.fileName} ===")
|
||||
logger.info(f"Initial MIME type: {doc.mimeType}")
|
||||
|
||||
# Create child operation for this document if parent operationId is provided
|
||||
docOperationId = None
|
||||
if operationId:
|
||||
workflowId = self.services.workflow.id if self.services.workflow else f"no-workflow-{int(time.time())}"
|
||||
docOperationId = f"{operationId}_doc_{i}"
|
||||
self.services.chat.progressLogStart(
|
||||
docOperationId,
|
||||
"Extracting Document",
|
||||
f"Document {i + 1}/{totalDocs}",
|
||||
doc.fileName[:50] + "..." if len(doc.fileName) > 50 else doc.fileName,
|
||||
parentOperationId=operationId # Use operationId as parent (not parentOperationId)
|
||||
)
|
||||
|
||||
# Start timing for this document
|
||||
startTime = time.time()
|
||||
|
||||
# Resolve raw bytes for this document using interface
|
||||
documentBytes = dbInterface.getFileData(doc.fileId)
|
||||
if not documentBytes:
|
||||
raise ValueError(f"No file data found for fileId={doc.fileId}")
|
||||
|
||||
# Convert ChatDocument to the format expected by runExtraction
|
||||
documentData = {
|
||||
"id": doc.id,
|
||||
"bytes": documentBytes,
|
||||
"fileName": doc.fileName,
|
||||
"mimeType": doc.mimeType
|
||||
}
|
||||
|
||||
ec = runExtraction(
|
||||
extractorRegistry=self._extractorRegistry,
|
||||
chunkerRegistry=self._chunkerRegistry,
|
||||
documentBytes=documentData["bytes"],
|
||||
fileName=documentData["fileName"],
|
||||
mimeType=documentData["mimeType"],
|
||||
options=options
|
||||
)
|
||||
|
||||
# Log content parts metadata
|
||||
logger.debug(f"Content parts: {len(ec.parts)}")
|
||||
for j, part in enumerate(ec.parts):
|
||||
logger.debug(f" Part {j}: {part.typeGroup} ({part.mimeType}) - {len(part.data) if part.data else 0} chars")
|
||||
if part.metadata:
|
||||
logger.debug(f" Metadata: {part.metadata}")
|
||||
|
||||
# Attach document id and MIME type to parts if missing
|
||||
for p in ec.parts:
|
||||
if "documentId" not in p.metadata:
|
||||
p.metadata["documentId"] = documentData["id"] or str(uuid.uuid4())
|
||||
if "documentMimeType" not in p.metadata:
|
||||
p.metadata["documentMimeType"] = documentData["mimeType"]
|
||||
|
||||
# Log chunking information
|
||||
chunkedParts = [p for p in ec.parts if p.metadata.get("chunk", False)]
|
||||
if chunkedParts:
|
||||
logger.debug(f"=== CHUNKING RESULTS ===")
|
||||
logger.debug(f"Total parts: {len(ec.parts)}")
|
||||
logger.debug(f"Chunked parts: {len(chunkedParts)}")
|
||||
for chunk in chunkedParts:
|
||||
logger.debug(f" Chunk: {chunk.label} - {len(chunk.data)} chars (parent: {chunk.parentId})")
|
||||
else:
|
||||
logger.debug(f"No chunking needed - {len(ec.parts)} parts fit within size limits")
|
||||
|
||||
# Calculate timing and emit stats
|
||||
endTime = time.time()
|
||||
processingTime = endTime - startTime
|
||||
bytesSent = len(documentBytes)
|
||||
bytesReceived = sum(len(part.data) if part.data else 0 for part in ec.parts)
|
||||
|
||||
# Emit stats for extraction operation
|
||||
|
||||
# Use internal extraction model for pricing
|
||||
modelDisplayName = "Internal Document Extractor"
|
||||
model = modelRegistry.getModel(modelDisplayName)
|
||||
# Hard fail if model is missing; caller must ensure connectors are registered
|
||||
if model is None or model.calculatePriceUsd is None:
|
||||
raise RuntimeError(f"Pricing model not available: {modelDisplayName}")
|
||||
priceUsd = model.calculatePriceUsd(processingTime, bytesSent, bytesReceived)
|
||||
|
||||
# Create AiCallResponse with real calculation
|
||||
# Use model.name for the response (API identifier), not displayName
|
||||
aiResponse = AiCallResponse(
|
||||
content="", # No content for extraction stats needed
|
||||
modelName=model.name,
|
||||
priceUsd=priceUsd,
|
||||
processingTime=processingTime,
|
||||
bytesSent=bytesSent,
|
||||
bytesReceived=bytesReceived,
|
||||
errorCount=0
|
||||
)
|
||||
|
||||
self.services.chat.storeWorkflowStat(
|
||||
self.services.workflow,
|
||||
aiResponse,
|
||||
f"extraction.process.{doc.mimeType}"
|
||||
)
|
||||
|
||||
# Write extraction results to debug file
|
||||
try:
|
||||
from modules.shared.debugLogger import writeDebugFile
|
||||
import json
|
||||
# Create summary of extraction results for debug
|
||||
extractionSummary = {
|
||||
"documentName": doc.fileName,
|
||||
"documentMimeType": doc.mimeType,
|
||||
"partsCount": len(ec.parts),
|
||||
"parts": []
|
||||
}
|
||||
for part in ec.parts:
|
||||
partSummary = {
|
||||
"typeGroup": part.typeGroup,
|
||||
"mimeType": part.mimeType,
|
||||
"label": part.label,
|
||||
"dataLength": len(part.data) if part.data else 0,
|
||||
"metadata": part.metadata
|
||||
}
|
||||
# Include data preview for small parts (first 500 chars)
|
||||
if part.data and len(part.data) <= 500:
|
||||
partSummary["dataPreview"] = part.data[:500]
|
||||
elif part.data:
|
||||
partSummary["dataPreview"] = f"[Large data: {len(part.data)} chars - truncated]"
|
||||
extractionSummary["parts"].append(partSummary)
|
||||
if docOperationId:
|
||||
self.services.chat.progressLogUpdate(docOperationId, 0.1, "Loading document data")
|
||||
|
||||
writeDebugFile(json.dumps(extractionSummary, indent=2, ensure_ascii=False), f"extraction_result_{doc.fileName}")
|
||||
except Exception as e:
|
||||
logger.debug(f"Failed to write extraction debug file: {str(e)}")
|
||||
# Resolve raw bytes for this document using interface
|
||||
documentBytes = dbInterface.getFileData(doc.fileId)
|
||||
if not documentBytes:
|
||||
if docOperationId:
|
||||
self.services.chat.progressLogFinish(docOperationId, False)
|
||||
raise ValueError(f"No file data found for fileId={doc.fileId}")
|
||||
|
||||
if docOperationId:
|
||||
self.services.chat.progressLogUpdate(docOperationId, 0.2, "Running extraction pipeline")
|
||||
|
||||
# Convert ChatDocument to the format expected by runExtraction
|
||||
documentData = {
|
||||
"id": doc.id,
|
||||
"bytes": documentBytes,
|
||||
"fileName": doc.fileName,
|
||||
"mimeType": doc.mimeType
|
||||
}
|
||||
|
||||
ec = runExtraction(
|
||||
extractorRegistry=self._extractorRegistry,
|
||||
chunkerRegistry=self._chunkerRegistry,
|
||||
documentBytes=documentData["bytes"],
|
||||
fileName=documentData["fileName"],
|
||||
mimeType=documentData["mimeType"],
|
||||
options=options
|
||||
)
|
||||
|
||||
if docOperationId:
|
||||
self.services.chat.progressLogUpdate(docOperationId, 0.7, f"Extracted {len(ec.parts)} parts")
|
||||
|
||||
# Log content parts metadata
|
||||
logger.debug(f"Content parts: {len(ec.parts)}")
|
||||
for j, part in enumerate(ec.parts):
|
||||
logger.debug(f" Part {j + 1}/{len(ec.parts)}: {part.typeGroup} ({part.mimeType}) - {len(part.data) if part.data else 0} chars")
|
||||
if part.metadata:
|
||||
logger.debug(f" Metadata: {part.metadata}")
|
||||
|
||||
results.append(ec)
|
||||
# Attach document id and MIME type to parts if missing
|
||||
for p in ec.parts:
|
||||
if "documentId" not in p.metadata:
|
||||
p.metadata["documentId"] = documentData["id"] or str(uuid.uuid4())
|
||||
if "documentMimeType" not in p.metadata:
|
||||
p.metadata["documentMimeType"] = documentData["mimeType"]
|
||||
|
||||
# Log chunking information
|
||||
chunkedParts = [p for p in ec.parts if p.metadata.get("chunk", False)]
|
||||
if chunkedParts:
|
||||
logger.debug(f"=== CHUNKING RESULTS ===")
|
||||
logger.debug(f"Total parts: {len(ec.parts)}")
|
||||
logger.debug(f"Chunked parts: {len(chunkedParts)}")
|
||||
for chunk in chunkedParts:
|
||||
logger.debug(f" Chunk: {chunk.label} - {len(chunk.data)} chars (parent: {chunk.parentId})")
|
||||
else:
|
||||
logger.debug(f"No chunking needed - {len(ec.parts)} parts fit within size limits")
|
||||
|
||||
if docOperationId:
|
||||
self.services.chat.progressLogUpdate(docOperationId, 0.9, f"Processing complete: {len(ec.parts)} parts extracted")
|
||||
|
||||
# Calculate timing and emit stats
|
||||
endTime = time.time()
|
||||
processingTime = endTime - startTime
|
||||
bytesSent = len(documentBytes)
|
||||
bytesReceived = sum(len(part.data) if part.data else 0 for part in ec.parts)
|
||||
|
||||
# Emit stats for extraction operation
|
||||
|
||||
# Use internal extraction model for pricing
|
||||
modelDisplayName = "Internal Document Extractor"
|
||||
model = modelRegistry.getModel(modelDisplayName)
|
||||
# Hard fail if model is missing; caller must ensure connectors are registered
|
||||
if model is None or model.calculatePriceUsd is None:
|
||||
if docOperationId:
|
||||
self.services.chat.progressLogFinish(docOperationId, False)
|
||||
raise RuntimeError(f"Pricing model not available: {modelDisplayName}")
|
||||
priceUsd = model.calculatePriceUsd(processingTime, bytesSent, bytesReceived)
|
||||
|
||||
# Create AiCallResponse with real calculation
|
||||
# Use model.name for the response (API identifier), not displayName
|
||||
aiResponse = AiCallResponse(
|
||||
content="", # No content for extraction stats needed
|
||||
modelName=model.name,
|
||||
priceUsd=priceUsd,
|
||||
processingTime=processingTime,
|
||||
bytesSent=bytesSent,
|
||||
bytesReceived=bytesReceived,
|
||||
errorCount=0
|
||||
)
|
||||
|
||||
self.services.chat.storeWorkflowStat(
|
||||
self.services.workflow,
|
||||
aiResponse,
|
||||
f"extraction.process.{doc.mimeType}"
|
||||
)
|
||||
|
||||
# Write extraction results to debug file
|
||||
try:
|
||||
from modules.shared.debugLogger import writeDebugFile
|
||||
import json
|
||||
# Create summary of extraction results for debug
|
||||
extractionSummary = {
|
||||
"documentName": doc.fileName,
|
||||
"documentMimeType": doc.mimeType,
|
||||
"partsCount": len(ec.parts),
|
||||
"parts": []
|
||||
}
|
||||
for part in ec.parts:
|
||||
partSummary = {
|
||||
"typeGroup": part.typeGroup,
|
||||
"mimeType": part.mimeType,
|
||||
"label": part.label,
|
||||
"dataLength": len(part.data) if part.data else 0,
|
||||
"metadata": part.metadata
|
||||
}
|
||||
# Include data preview for small parts (first 500 chars)
|
||||
if part.data and len(part.data) <= 500:
|
||||
partSummary["dataPreview"] = part.data[:500]
|
||||
elif part.data:
|
||||
partSummary["dataPreview"] = f"[Large data: {len(part.data)} chars - truncated]"
|
||||
extractionSummary["parts"].append(partSummary)
|
||||
|
||||
writeDebugFile(json.dumps(extractionSummary, indent=2, ensure_ascii=False), f"extraction_result_{doc.fileName}")
|
||||
except Exception as e:
|
||||
logger.debug(f"Failed to write extraction debug file: {str(e)}")
|
||||
|
||||
results.append(ec)
|
||||
|
||||
# Finish document operation successfully
|
||||
if docOperationId:
|
||||
self.services.chat.progressLogFinish(docOperationId, True)
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Error extracting content from document {i + 1}/{totalDocs} ({doc.fileName}): {str(e)}")
|
||||
if docOperationId:
|
||||
try:
|
||||
self.services.chat.progressLogFinish(docOperationId, False)
|
||||
except:
|
||||
pass # Don't fail on progress logging errors
|
||||
# Continue with next document instead of failing completely
|
||||
# This allows parallel processing to continue even if one document fails
|
||||
continue
|
||||
|
||||
return results
|
||||
|
||||
|
|
@ -481,7 +536,8 @@ class ExtractionService:
|
|||
# Extract content WITHOUT chunking
|
||||
if operationId:
|
||||
self.services.chat.progressLogUpdate(operationId, 0.1, f"Extracting content from {len(documents)} documents")
|
||||
extractionResult = self.extractContent(documents, extractionOptions)
|
||||
# Pass operationId as parentOperationId for hierarchical logging
|
||||
extractionResult = self.extractContent(documents, extractionOptions, operationId=operationId, parentOperationId=parentOperationId)
|
||||
|
||||
if not isinstance(extractionResult, list):
|
||||
if operationId:
|
||||
|
|
@ -491,11 +547,9 @@ class ExtractionService:
|
|||
# Process parts (not chunks) with model-aware AI calls
|
||||
if operationId:
|
||||
self.services.chat.progressLogUpdate(operationId, 0.3, f"Processing {len(extractionResult)} extracted content parts")
|
||||
# Get parent log ID for part operations
|
||||
parentLogId = None
|
||||
if operationId:
|
||||
parentLogId = self.services.chat.getOperationLogId(operationId)
|
||||
partResults = await self._processPartsWithMapping(extractionResult, prompt, aiObjects, options, operationId, parentLogId)
|
||||
# Use parent operation ID directly (parentId should be operationId, not log entry ID)
|
||||
parentOperationId = operationId # Use the parent's operationId directly
|
||||
partResults = await self._processPartsWithMapping(extractionResult, prompt, aiObjects, options, operationId, parentOperationId)
|
||||
|
||||
# Merge results using existing merging system
|
||||
if operationId:
|
||||
|
|
@ -522,7 +576,7 @@ class ExtractionService:
|
|||
aiObjects: Any,
|
||||
options: Optional[AiCallOptions] = None,
|
||||
operationId: Optional[str] = None,
|
||||
parentLogId: Optional[str] = None
|
||||
parentOperationId: Optional[str] = None
|
||||
) -> List[PartResult]:
|
||||
"""Process content parts with model-aware chunking and proper mapping."""
|
||||
|
||||
|
|
@ -569,7 +623,7 @@ class ExtractionService:
|
|||
"Content Processing",
|
||||
f"Part {part_index + 1}",
|
||||
f"Type: {part.typeGroup}",
|
||||
parentId=parentLogId
|
||||
parentOperationId=parentOperationId
|
||||
)
|
||||
|
||||
try:
|
||||
|
|
|
|||
|
|
@ -99,6 +99,18 @@ async def buildExtractionPrompt(
|
|||
# Parse extraction intent if AI service is available
|
||||
extraction_intent = await _parseExtractionIntent(userPrompt, outputFormat, aiService, services) if aiService else userPrompt
|
||||
|
||||
# Extract user language for document language instruction
|
||||
userLanguage = 'en' # Default fallback
|
||||
if services:
|
||||
try:
|
||||
# Prefer detected language if available
|
||||
if hasattr(services, 'currentUserLanguage') and services.currentUserLanguage:
|
||||
userLanguage = services.currentUserLanguage
|
||||
elif hasattr(services, 'user') and services.user and hasattr(services.user, 'language'):
|
||||
userLanguage = services.user.language
|
||||
except Exception:
|
||||
pass
|
||||
|
||||
# Build base prompt with clear user prompt markers
|
||||
sanitized_user_prompt = services.utils.sanitizePromptContent(userPrompt, 'userinput') if services else userPrompt
|
||||
adaptive_prompt = f"""
|
||||
|
|
@ -114,6 +126,8 @@ You are a document processing assistant that extracts and structures content fro
|
|||
|
||||
TASK: Extract the actual content from the document and organize it into documents. For single documents, create one document entry. For multi-document requests, create multiple document entries.
|
||||
|
||||
LANGUAGE REQUIREMENT: All extracted content must be in the language '{userLanguage}'. Extract and preserve content in this language.
|
||||
|
||||
{extraction_intent}
|
||||
|
||||
REQUIREMENTS:
|
||||
|
|
|
|||
|
|
@ -362,7 +362,7 @@ class BaseRenderer(ABC):
|
|||
self.logger.debug(f"AI Style Template Prompt:")
|
||||
self.logger.debug(f"{styleTemplate}")
|
||||
|
||||
response = await aiService.aiObjects.call(request)
|
||||
response = await aiService.callAi(request)
|
||||
|
||||
# Save styling prompt and response to debug
|
||||
self.services.utils.writeDebugFile(styleTemplate, "renderer_styling_prompt")
|
||||
|
|
|
|||
|
|
@ -205,7 +205,7 @@ Return only the compressed prompt, no explanations.
|
|||
)
|
||||
)
|
||||
|
||||
response = await aiService.aiObjects.call(request)
|
||||
response = await aiService.callAi(request)
|
||||
compressed = response.content.strip()
|
||||
|
||||
# Validate the compressed prompt
|
||||
|
|
|
|||
|
|
@ -227,7 +227,7 @@ class RendererPdf(BaseRenderer):
|
|||
self.logger.warning("AI service not properly configured, using defaults")
|
||||
return default_styles
|
||||
|
||||
response = await ai_service.aiObjects.call(request)
|
||||
response = await ai_service.callAi(request)
|
||||
|
||||
# Check if response is valid
|
||||
if not response:
|
||||
|
|
|
|||
|
|
@ -424,7 +424,7 @@ JSON ONLY. NO OTHER TEXT."""
|
|||
self.logger.warning("AI service not properly configured, using defaults")
|
||||
return default_styles
|
||||
|
||||
response = await aiService.aiObjects.call(request)
|
||||
response = await aiService.callAi(request)
|
||||
|
||||
# Check if response is valid
|
||||
if not response:
|
||||
|
|
|
|||
|
|
@ -346,7 +346,7 @@ class RendererXlsx(BaseRenderer):
|
|||
requestOptions.operationType = OperationTypeEnum.DATA_GENERATE
|
||||
|
||||
request = AiCallRequest(prompt=styleTemplate, context="", options=requestOptions)
|
||||
response = await aiService.aiObjects.call(request)
|
||||
response = await aiService.callAi(request)
|
||||
|
||||
import json
|
||||
import re
|
||||
|
|
|
|||
|
|
@ -16,7 +16,8 @@ async def buildGenerationPrompt(
|
|||
userPrompt: str,
|
||||
title: str,
|
||||
extracted_content: str = None,
|
||||
continuationContext: Dict[str, Any] = None
|
||||
continuationContext: Dict[str, Any] = None,
|
||||
services: Any = None
|
||||
) -> str:
|
||||
"""
|
||||
Build the unified generation prompt using a single JSON template.
|
||||
|
|
@ -28,10 +29,23 @@ async def buildGenerationPrompt(
|
|||
title: Title for the document
|
||||
extracted_content: Optional extracted content from documents to prepend to prompt
|
||||
continuationContext: Optional context from previous generation for continuation
|
||||
services: Optional services instance for accessing user language
|
||||
|
||||
Returns:
|
||||
Complete generation prompt string
|
||||
"""
|
||||
# Extract user language for document language instruction
|
||||
userLanguage = 'en' # Default fallback
|
||||
if services:
|
||||
try:
|
||||
# Prefer detected language if available
|
||||
if hasattr(services, 'currentUserLanguage') and services.currentUserLanguage:
|
||||
userLanguage = services.currentUserLanguage
|
||||
elif hasattr(services, 'user') and services.user and hasattr(services.user, 'language'):
|
||||
userLanguage = services.user.language
|
||||
except Exception:
|
||||
pass
|
||||
|
||||
# Create a template - let AI generate title if not provided
|
||||
titleValue = title if title else "Generated Document"
|
||||
jsonTemplate = jsonTemplateDocument.replace("{{DOCUMENT_TITLE}}", titleValue)
|
||||
|
|
@ -82,6 +96,8 @@ END OF USER REQUEST / USER PROMPT
|
|||
|
||||
⚠️ CONTINUATION MODE: Response was incomplete. Generate ONLY the remaining content.
|
||||
|
||||
LANGUAGE REQUIREMENT: All generated content must be in the language '{userLanguage}'. Generate all text, headings, paragraphs, and content in this language.
|
||||
|
||||
{continuationText}
|
||||
|
||||
JSON structure template:
|
||||
|
|
@ -92,6 +108,7 @@ Rules:
|
|||
- Reference elements shown above are ALREADY DELIVERED - DO NOT repeat them.
|
||||
- Generate ONLY the remaining content that comes AFTER the reference elements.
|
||||
- DO NOT regenerate the entire JSON structure - start directly with what comes next.
|
||||
- All content must be in the language '{userLanguage}'.
|
||||
- Output JSON only; no markdown fences or extra text.
|
||||
|
||||
Continue generating the remaining content now.
|
||||
|
|
@ -124,6 +141,8 @@ EXTRACTED CONTENT FROM DOCUMENTS:
|
|||
END OF EXTRACTED CONTENT
|
||||
{'='*80}
|
||||
|
||||
LANGUAGE REQUIREMENT: All generated content must be in the language '{userLanguage}'. Generate all text, headings, paragraphs, and content in this language. If the extracted content is in a different language, translate it to '{userLanguage}' while preserving the structure and meaning.
|
||||
|
||||
Generate a VALID JSON response using the EXTRACTED CONTENT above as your data source.
|
||||
The JSON structure template below shows ONLY the structure pattern - the example values are NOT real data.
|
||||
You MUST use the actual data from EXTRACTED CONTENT above, NOT the example values from the template.
|
||||
|
|
@ -136,6 +155,7 @@ Instructions:
|
|||
- Do NOT reuse example section IDs; create your own.
|
||||
- CRITICAL: Use the ACTUAL DATA from EXTRACTED CONTENT above, NOT the example values from the template.
|
||||
- Generate complete content based on the user request and the extracted content. Do NOT just give an instruction or comments. Deliver the complete response.
|
||||
- All content must be in the language '{userLanguage}'.
|
||||
- IMPORTANT: Set a meaningful "filename" in each document with appropriate file extension (e.g., "prime_numbers.txt", "report.docx", "data.json"). The filename should reflect the content and task objective.
|
||||
- Output JSON only; no markdown fences or extra text.
|
||||
|
||||
|
|
@ -151,6 +171,8 @@ USER REQUEST / USER PROMPT:
|
|||
END OF USER REQUEST / USER PROMPT
|
||||
{'='*80}
|
||||
|
||||
LANGUAGE REQUIREMENT: All generated content must be in the language '{userLanguage}'. Generate all text, headings, paragraphs, and content in this language.
|
||||
|
||||
Generate a VALID JSON response for the user request. The template below shows ONLY the structure pattern - it is NOT existing content.
|
||||
|
||||
JSON structure template:
|
||||
|
|
@ -160,6 +182,7 @@ Instructions:
|
|||
- Return ONLY valid JSON (strict). No comments. No trailing commas. Use double quotes.
|
||||
- Do NOT reuse example section IDs; create your own.
|
||||
- Generate complete content based on the user request. Do NOT just give an instruction or comments. Deliver the complete response.
|
||||
- All content must be in the language '{userLanguage}'.
|
||||
- IMPORTANT: Set a meaningful "filename" in each document with appropriate file extension (e.g., "prime_numbers.txt", "report.docx", "data.json"). The filename should reflect the content and task objective.
|
||||
- Output JSON only; no markdown fences or extra text.
|
||||
|
||||
|
|
|
|||
|
|
@ -114,16 +114,14 @@ class WebService:
|
|||
self.services.chat.progressLogUpdate(operationId, 0.4, "Initiating")
|
||||
self.services.chat.progressLogUpdate(operationId, 0.6, f"Crawling {len(allUrls)} URLs")
|
||||
|
||||
# Get parent log ID for URL-level operations
|
||||
parentLogId = None
|
||||
if operationId:
|
||||
parentLogId = self.services.chat.getOperationLogId(operationId)
|
||||
# Use parent operation ID directly (parentId should be operationId, not log entry ID)
|
||||
parentOperationId = operationId # Use the parent's operationId directly
|
||||
|
||||
crawlResult = await self._performWebCrawl(
|
||||
instruction=instruction,
|
||||
urls=allUrls,
|
||||
maxDepth=maxDepth,
|
||||
parentLogId=parentLogId
|
||||
parentOperationId=parentOperationId
|
||||
)
|
||||
|
||||
if operationId:
|
||||
|
|
@ -131,18 +129,95 @@ class WebService:
|
|||
self.services.chat.progressLogUpdate(operationId, 0.95, "Completed")
|
||||
self.services.chat.progressLogFinish(operationId, True)
|
||||
|
||||
# Return consolidated result
|
||||
# Calculate statistics about crawl results
|
||||
totalResults = len(crawlResult) if isinstance(crawlResult, list) else 1
|
||||
totalContentLength = 0
|
||||
urlsWithContent = 0
|
||||
|
||||
# Analyze crawl results to gather statistics
|
||||
if isinstance(crawlResult, list):
|
||||
for item in crawlResult:
|
||||
if isinstance(item, dict):
|
||||
if item.get("url"):
|
||||
urlsWithContent += 1
|
||||
content = item.get("content", "")
|
||||
if isinstance(content, str):
|
||||
totalContentLength += len(content)
|
||||
elif isinstance(content, dict):
|
||||
# Estimate size from dict
|
||||
totalContentLength += len(str(content))
|
||||
elif isinstance(crawlResult, dict):
|
||||
if crawlResult.get("url"):
|
||||
urlsWithContent = 1
|
||||
content = crawlResult.get("content", "")
|
||||
if isinstance(content, str):
|
||||
totalContentLength = len(content)
|
||||
elif isinstance(content, dict):
|
||||
totalContentLength = len(str(content))
|
||||
|
||||
# Convert crawl results into sections format for generic validator
|
||||
sections = []
|
||||
if isinstance(crawlResult, list):
|
||||
for idx, item in enumerate(crawlResult):
|
||||
if isinstance(item, dict):
|
||||
section = {
|
||||
"id": f"result_{idx}",
|
||||
"content_type": "paragraph",
|
||||
"title": item.get("url", f"Result {idx + 1}"),
|
||||
"order": idx
|
||||
}
|
||||
# Add content preview
|
||||
content = item.get("content", "")
|
||||
if isinstance(content, str) and content:
|
||||
section["textPreview"] = content[:200] + ("..." if len(content) > 200 else "")
|
||||
sections.append(section)
|
||||
elif isinstance(crawlResult, dict):
|
||||
section = {
|
||||
"id": "result_0",
|
||||
"content_type": "paragraph",
|
||||
"title": crawlResult.get("url", "Research Result"),
|
||||
"order": 0
|
||||
}
|
||||
content = crawlResult.get("content", "")
|
||||
if isinstance(content, str) and content:
|
||||
section["textPreview"] = content[:200] + ("..." if len(content) > 200 else "")
|
||||
sections.append(section)
|
||||
|
||||
# Return consolidated result with metadata in format that generic validator understands
|
||||
result = {
|
||||
"metadata": {
|
||||
"title": suggestedFilename or instruction[:100] if instruction else "Web Research Results",
|
||||
"extraction_method": "web_crawl",
|
||||
"research_depth": finalResearchDepth,
|
||||
"max_depth": maxDepth,
|
||||
"country": countryCode,
|
||||
"language": languageCode,
|
||||
"urls_crawled": allUrls[:20], # First 20 URLs for reference
|
||||
"total_urls": len(allUrls),
|
||||
"urls_with_content": urlsWithContent,
|
||||
"total_content_length": totalContentLength,
|
||||
"crawl_date": self.services.utils.timestampGetUtc() if hasattr(self.services, 'utils') else None
|
||||
},
|
||||
"sections": sections,
|
||||
"statistics": {
|
||||
"sectionCount": len(sections),
|
||||
"total_urls": len(allUrls),
|
||||
"results_count": totalResults,
|
||||
"urls_with_content": urlsWithContent,
|
||||
"total_content_length": totalContentLength
|
||||
},
|
||||
# Keep original structure for backward compatibility
|
||||
"instruction": instruction,
|
||||
"urls_crawled": allUrls,
|
||||
"total_urls": len(allUrls),
|
||||
"results": crawlResult,
|
||||
"total_results": len(crawlResult) if isinstance(crawlResult, list) else 1
|
||||
"total_results": totalResults
|
||||
}
|
||||
|
||||
# Add suggested filename if available
|
||||
if suggestedFilename:
|
||||
result["suggested_filename"] = suggestedFilename
|
||||
result["metadata"]["suggested_filename"] = suggestedFilename
|
||||
|
||||
return result
|
||||
|
||||
|
|
@ -311,7 +386,7 @@ Return ONLY valid JSON, no additional text:
|
|||
instruction: str,
|
||||
urls: List[str],
|
||||
maxDepth: int = 2,
|
||||
parentLogId: Optional[str] = None
|
||||
parentOperationId: Optional[str] = None
|
||||
) -> List[Dict[str, Any]]:
|
||||
"""Perform web crawl on list of URLs - calls plugin for each URL individually."""
|
||||
crawlResults = []
|
||||
|
|
@ -320,7 +395,7 @@ Return ONLY valid JSON, no additional text:
|
|||
for urlIndex, url in enumerate(urls):
|
||||
# Create separate operation for each URL with parent reference
|
||||
urlOperationId = None
|
||||
if parentLogId:
|
||||
if parentOperationId:
|
||||
workflowId = self.services.workflow.id if self.services.workflow else f"no-workflow-{int(time.time())}"
|
||||
urlOperationId = f"web_crawl_url_{workflowId}_{urlIndex}_{int(time.time())}"
|
||||
self.services.chat.progressLogStart(
|
||||
|
|
@ -328,21 +403,23 @@ Return ONLY valid JSON, no additional text:
|
|||
"Web Crawl",
|
||||
f"URL {urlIndex + 1}",
|
||||
url[:50] + "..." if len(url) > 50 else url,
|
||||
parentId=parentLogId
|
||||
parentOperationId=parentOperationId
|
||||
)
|
||||
|
||||
try:
|
||||
logger.info(f"Crawling URL: {url}")
|
||||
logger.info(f"Crawling URL {urlIndex + 1}/{len(urls)}: {url}")
|
||||
|
||||
if urlOperationId:
|
||||
self.services.chat.progressLogUpdate(urlOperationId, 0.3, "Initiating")
|
||||
displayUrl = url[:50] + "..." if len(url) > 50 else url
|
||||
self.services.chat.progressLogUpdate(urlOperationId, 0.2, f"Crawling: {displayUrl}")
|
||||
self.services.chat.progressLogUpdate(urlOperationId, 0.3, "Initiating crawl")
|
||||
|
||||
# Build crawl prompt model for single URL
|
||||
crawlPromptModel = AiCallPromptWebCrawl(
|
||||
instruction=instruction,
|
||||
url=url, # Single URL
|
||||
maxDepth=maxDepth,
|
||||
maxWidth=50
|
||||
maxWidth=5 # Default: 5 pages per level
|
||||
)
|
||||
crawlPrompt = crawlPromptModel.model_dump_json(exclude_none=True, indent=2)
|
||||
|
||||
|
|
@ -356,16 +433,19 @@ Return ONLY valid JSON, no additional text:
|
|||
resultFormat="json"
|
||||
)
|
||||
|
||||
# Use unified callAiContent method
|
||||
if urlOperationId:
|
||||
self.services.chat.progressLogUpdate(urlOperationId, 0.4, "Calling crawl connector")
|
||||
|
||||
# Use unified callAiContent method with parentOperationId for hierarchical logging
|
||||
crawlResponse = await self.services.ai.callAiContent(
|
||||
prompt=crawlPrompt,
|
||||
options=crawlOptions,
|
||||
outputFormat="json"
|
||||
outputFormat="json",
|
||||
parentOperationId=urlOperationId # Pass URL operation ID as parent for sub-URL logging
|
||||
)
|
||||
|
||||
if urlOperationId:
|
||||
self.services.chat.progressLogUpdate(urlOperationId, 0.8, "Completed")
|
||||
self.services.chat.progressLogFinish(urlOperationId, True)
|
||||
self.services.chat.progressLogUpdate(urlOperationId, 0.7, "Processing crawl results")
|
||||
|
||||
# Extract content from AiResponse
|
||||
crawlResult = crawlResponse.content
|
||||
|
|
@ -387,16 +467,30 @@ Return ONLY valid JSON, no additional text:
|
|||
else:
|
||||
crawlData = crawlResult
|
||||
|
||||
# Process crawl results and create hierarchical progress logging for sub-URLs
|
||||
if urlOperationId:
|
||||
self.services.chat.progressLogUpdate(urlOperationId, 0.8, "Processing crawl results")
|
||||
|
||||
# Recursively process crawl results to find nested URLs and create child operations
|
||||
processedResults = self._processCrawlResultsWithHierarchy(crawlData, url, urlOperationId, maxDepth, 0)
|
||||
|
||||
# Count total URLs crawled (including sub-URLs) for progress message
|
||||
totalUrlsCrawled = self._countUrlsInResults(processedResults)
|
||||
|
||||
# Ensure it's a list of results
|
||||
if isinstance(crawlData, list):
|
||||
crawlResults.extend(crawlData)
|
||||
elif isinstance(crawlData, dict):
|
||||
if "results" in crawlData:
|
||||
crawlResults.extend(crawlData["results"])
|
||||
else:
|
||||
crawlResults.append(crawlData)
|
||||
if isinstance(processedResults, list):
|
||||
crawlResults.extend(processedResults)
|
||||
elif isinstance(processedResults, dict):
|
||||
crawlResults.append(processedResults)
|
||||
else:
|
||||
crawlResults.append({"url": url, "content": str(crawlData)})
|
||||
crawlResults.append({"url": url, "content": str(processedResults)})
|
||||
|
||||
if urlOperationId:
|
||||
if totalUrlsCrawled > 1:
|
||||
self.services.chat.progressLogUpdate(urlOperationId, 0.9, f"Crawled {totalUrlsCrawled} URLs (including sub-URLs)")
|
||||
else:
|
||||
self.services.chat.progressLogUpdate(urlOperationId, 0.9, "Crawl completed")
|
||||
self.services.chat.progressLogFinish(urlOperationId, True)
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Error crawling URL {url}: {str(e)}")
|
||||
|
|
@ -405,4 +499,145 @@ Return ONLY valid JSON, no additional text:
|
|||
crawlResults.append({"url": url, "error": str(e)})
|
||||
|
||||
return crawlResults
|
||||
|
||||
def _processCrawlResultsWithHierarchy(
|
||||
self,
|
||||
crawlData: Any,
|
||||
parentUrl: str,
|
||||
parentOperationId: Optional[str],
|
||||
maxDepth: int,
|
||||
currentDepth: int
|
||||
) -> List[Dict[str, Any]]:
|
||||
"""
|
||||
Recursively process crawl results to create hierarchical progress logging for sub-URLs.
|
||||
|
||||
Args:
|
||||
crawlData: Crawl result data (dict, list, or other)
|
||||
parentUrl: Parent URL being crawled
|
||||
parentOperationId: Parent operation ID for hierarchical logging
|
||||
maxDepth: Maximum crawl depth
|
||||
currentDepth: Current depth in the crawl tree
|
||||
|
||||
Returns:
|
||||
List of processed crawl results
|
||||
"""
|
||||
import time
|
||||
results = []
|
||||
|
||||
# Handle list of results
|
||||
if isinstance(crawlData, list):
|
||||
for idx, item in enumerate(crawlData):
|
||||
if isinstance(item, dict):
|
||||
# Check if this item has sub-URLs or nested results
|
||||
itemUrl = item.get("url") or item.get("source") or parentUrl
|
||||
|
||||
# Create child operation for sub-URL if we're not at max depth
|
||||
if currentDepth < maxDepth and parentOperationId:
|
||||
# Check if this item has nested results or children
|
||||
hasNestedResults = "results" in item or "children" in item or "subUrls" in item
|
||||
|
||||
if hasNestedResults or (itemUrl != parentUrl and currentDepth > 0):
|
||||
# This is a sub-URL - create child operation
|
||||
workflowId = self.services.workflow.id if self.services.workflow else f"no-workflow-{int(time.time())}"
|
||||
subUrlOperationId = f"{parentOperationId}_sub_{idx}_{int(time.time())}"
|
||||
self.services.chat.progressLogStart(
|
||||
subUrlOperationId,
|
||||
"Crawling Sub-URL",
|
||||
f"Depth {currentDepth + 1}",
|
||||
itemUrl[:50] + "..." if len(itemUrl) > 50 else itemUrl,
|
||||
parentOperationId=parentOperationId
|
||||
)
|
||||
|
||||
try:
|
||||
# Process nested results recursively
|
||||
if "results" in item:
|
||||
nestedResults = self._processCrawlResultsWithHierarchy(
|
||||
item["results"], itemUrl, subUrlOperationId, maxDepth, currentDepth + 1
|
||||
)
|
||||
item["results"] = nestedResults
|
||||
elif "children" in item:
|
||||
nestedResults = self._processCrawlResultsWithHierarchy(
|
||||
item["children"], itemUrl, subUrlOperationId, maxDepth, currentDepth + 1
|
||||
)
|
||||
item["children"] = nestedResults
|
||||
elif "subUrls" in item:
|
||||
nestedResults = self._processCrawlResultsWithHierarchy(
|
||||
item["subUrls"], itemUrl, subUrlOperationId, maxDepth, currentDepth + 1
|
||||
)
|
||||
item["subUrls"] = nestedResults
|
||||
|
||||
self.services.chat.progressLogUpdate(subUrlOperationId, 0.9, "Completed")
|
||||
self.services.chat.progressLogFinish(subUrlOperationId, True)
|
||||
except Exception as e:
|
||||
logger.error(f"Error processing sub-URL {itemUrl}: {str(e)}")
|
||||
if subUrlOperationId:
|
||||
self.services.chat.progressLogFinish(subUrlOperationId, False)
|
||||
|
||||
results.append(item)
|
||||
else:
|
||||
results.append(item)
|
||||
|
||||
# Handle dict with results array
|
||||
elif isinstance(crawlData, dict):
|
||||
if "results" in crawlData:
|
||||
# Process nested results
|
||||
nestedResults = self._processCrawlResultsWithHierarchy(
|
||||
crawlData["results"], parentUrl, parentOperationId, maxDepth, currentDepth
|
||||
)
|
||||
crawlData["results"] = nestedResults
|
||||
results.append(crawlData)
|
||||
elif "children" in crawlData:
|
||||
# Process children
|
||||
nestedResults = self._processCrawlResultsWithHierarchy(
|
||||
crawlData["children"], parentUrl, parentOperationId, maxDepth, currentDepth
|
||||
)
|
||||
crawlData["children"] = nestedResults
|
||||
results.append(crawlData)
|
||||
elif "subUrls" in crawlData:
|
||||
# Process sub-URLs
|
||||
nestedResults = self._processCrawlResultsWithHierarchy(
|
||||
crawlData["subUrls"], parentUrl, parentOperationId, maxDepth, currentDepth
|
||||
)
|
||||
crawlData["subUrls"] = nestedResults
|
||||
results.append(crawlData)
|
||||
else:
|
||||
# Single result dict
|
||||
results.append(crawlData)
|
||||
else:
|
||||
# Other types - wrap in dict
|
||||
results.append({"url": parentUrl, "content": str(crawlData)})
|
||||
|
||||
return results
|
||||
|
||||
def _countUrlsInResults(self, results: Any) -> int:
|
||||
"""
|
||||
Recursively count total URLs in crawl results (including nested sub-URLs).
|
||||
|
||||
Args:
|
||||
results: Crawl results (dict, list, or other)
|
||||
|
||||
Returns:
|
||||
Total count of URLs found
|
||||
"""
|
||||
count = 0
|
||||
|
||||
if isinstance(results, list):
|
||||
for item in results:
|
||||
count += self._countUrlsInResults(item)
|
||||
elif isinstance(results, dict):
|
||||
# Count this URL if it has a url field
|
||||
if "url" in results or "source" in results:
|
||||
count += 1
|
||||
# Recursively count nested results
|
||||
if "results" in results:
|
||||
count += self._countUrlsInResults(results["results"])
|
||||
if "children" in results:
|
||||
count += self._countUrlsInResults(results["children"])
|
||||
if "subUrls" in results:
|
||||
count += self._countUrlsInResults(results["subUrls"])
|
||||
elif isinstance(results, str):
|
||||
# Single URL string
|
||||
count = 1
|
||||
|
||||
return count
|
||||
|
||||
|
|
|
|||
|
|
@ -24,7 +24,7 @@ class ProgressLogger:
|
|||
self.finishedOperations = set() # Track finished operations to avoid repeated warnings
|
||||
self.operationLogIds = {} # Map operationId to the log entry ID for parent reference
|
||||
|
||||
def startOperation(self, operationId: str, serviceName: str, actionName: str, context: str = "", parentId: Optional[str] = None):
|
||||
def startOperation(self, operationId: str, serviceName: str, actionName: str, context: str = "", parentOperationId: Optional[str] = None):
|
||||
"""Start a new long-running operation.
|
||||
|
||||
Args:
|
||||
|
|
@ -32,7 +32,8 @@ class ProgressLogger:
|
|||
serviceName: Name of the service (e.g., "Extract", "AI", "Generate")
|
||||
actionName: Name of the action being performed
|
||||
context: Additional context information
|
||||
parentId: Optional parent log entry ID for hierarchical display
|
||||
parentOperationId: Optional parent operation ID (operationId of parent operation) for hierarchical display
|
||||
The parentId in ChatLog will be set to this parentOperationId
|
||||
"""
|
||||
# Remove from finished operations if it was there (for restart scenarios)
|
||||
self.finishedOperations.discard(operationId)
|
||||
|
|
@ -42,9 +43,10 @@ class ProgressLogger:
|
|||
'action': actionName,
|
||||
'context': context,
|
||||
'startTime': time.time(),
|
||||
'parentId': parentId
|
||||
'parentOperationId': parentOperationId # Store parent's operationId, not log entry ID
|
||||
}
|
||||
logId = self._logProgress(operationId, 0.0, f"Starting {actionName}", parentId=parentId)
|
||||
# Use parentOperationId as parentId in ChatLog (parentId should be the operationId of parent)
|
||||
logId = self._logProgress(operationId, 0.0, f"Starting {actionName}", parentOperationId=parentOperationId)
|
||||
if logId:
|
||||
self.operationLogIds[operationId] = logId
|
||||
logger.debug(f"Started operation {operationId}: {serviceName} - {actionName}")
|
||||
|
|
@ -70,9 +72,9 @@ class ProgressLogger:
|
|||
|
||||
op = self.activeOperations[operationId]
|
||||
context = f"{op['context']} {statusUpdate}".strip()
|
||||
# Use the same parentId as the start operation - all logs (start/update/finish) share the same parent
|
||||
parentId = op.get('parentId')
|
||||
self._logProgress(operationId, progress, context, parentId=parentId)
|
||||
# Use the same parentOperationId as the start operation - all logs (start/update/finish) share the same parent
|
||||
parentOperationId = op.get('parentOperationId')
|
||||
self._logProgress(operationId, progress, context, parentOperationId=parentOperationId)
|
||||
logger.debug(f"Updated operation {operationId}: {progress:.2f} - {context}")
|
||||
|
||||
def finishOperation(self, operationId: str, success: bool = True):
|
||||
|
|
@ -93,11 +95,11 @@ class ProgressLogger:
|
|||
finalProgress = 1.0 if success else 0.0
|
||||
status = "Done" if success else "Failed"
|
||||
|
||||
# Use the same parentId as the start operation - all logs (start/update/finish) share the same parent
|
||||
parentId = op.get('parentId')
|
||||
# Use the same parentOperationId as the start operation - all logs (start/update/finish) share the same parent
|
||||
parentOperationId = op.get('parentOperationId')
|
||||
|
||||
# Create completion log BEFORE removing from activeOperations
|
||||
self._logProgress(operationId, finalProgress, status, parentId=parentId)
|
||||
self._logProgress(operationId, finalProgress, status, parentOperationId=parentOperationId)
|
||||
|
||||
# Log completion time
|
||||
duration = time.time() - op['startTime']
|
||||
|
|
@ -111,14 +113,15 @@ class ProgressLogger:
|
|||
# Mark as finished to prevent repeated warnings from updateOperation calls
|
||||
self.finishedOperations.add(operationId)
|
||||
|
||||
def _logProgress(self, operationId: str, progress: float, status: str, parentId: Optional[str] = None) -> Optional[str]:
|
||||
def _logProgress(self, operationId: str, progress: float, status: str, parentOperationId: Optional[str] = None) -> Optional[str]:
|
||||
"""Create standardized ChatLog entry.
|
||||
|
||||
Args:
|
||||
operationId: Unique identifier for the operation
|
||||
progress: Progress value between 0.0 and 1.0
|
||||
status: Status information for the log entry
|
||||
parentId: Optional parent log entry ID for hierarchical display
|
||||
parentOperationId: Optional parent operation ID (operationId of parent operation) for hierarchical display
|
||||
This will be set as parentId in ChatLog (parentId = operationId of parent)
|
||||
|
||||
Returns:
|
||||
The created log entry ID, or None if creation failed
|
||||
|
|
@ -134,6 +137,7 @@ class ProgressLogger:
|
|||
logger.warning(f"Cannot log progress: no workflow available")
|
||||
return None
|
||||
|
||||
# parentId in ChatLog should be the operationId of the parent operation, not the log entry ID
|
||||
logData = {
|
||||
"workflowId": workflow.id,
|
||||
"message": message,
|
||||
|
|
@ -141,7 +145,7 @@ class ProgressLogger:
|
|||
"status": status,
|
||||
"progress": progress,
|
||||
"operationId": operationId,
|
||||
"parentId": parentId
|
||||
"parentId": parentOperationId # Set to parent's operationId, not log entry ID
|
||||
}
|
||||
|
||||
try:
|
||||
|
|
|
|||
|
|
@ -130,8 +130,9 @@ class MethodAi(MethodBase):
|
|||
processDocumentsIndividually=True
|
||||
)
|
||||
|
||||
# Extract content using extraction service
|
||||
extractedResults = self.services.extraction.extractContent(chatDocuments, extractionOptions)
|
||||
# Extract content using extraction service with hierarchical progress logging
|
||||
# Pass operationId for per-document progress tracking
|
||||
extractedResults = self.services.extraction.extractContent(chatDocuments, extractionOptions, operationId=operationId)
|
||||
|
||||
# Combine all ContentParts from all extracted results
|
||||
contentParts = []
|
||||
|
|
|
|||
|
|
@ -297,13 +297,11 @@ class MethodContext(MethodBase):
|
|||
processDocumentsIndividually=True
|
||||
)
|
||||
|
||||
# Get parent log ID for document-level operations
|
||||
parentLogId = self.services.chat.getOperationLogId(operationId)
|
||||
|
||||
# Call extraction service
|
||||
# Call extraction service with hierarchical progress logging
|
||||
self.services.chat.progressLogUpdate(operationId, 0.4, "Initiating")
|
||||
self.services.chat.progressLogUpdate(operationId, 0.5, f"Extracting content from {len(chatDocuments)} documents")
|
||||
extractedResults = self.services.extraction.extractContent(chatDocuments, extractionOptions)
|
||||
# Pass operationId for hierarchical per-document progress logging
|
||||
extractedResults = self.services.extraction.extractContent(chatDocuments, extractionOptions, operationId=operationId)
|
||||
|
||||
# Build ActionDocuments from ContentExtracted results
|
||||
self.services.chat.progressLogUpdate(operationId, 0.8, "Building result documents")
|
||||
|
|
|
|||
|
|
@ -326,7 +326,21 @@ class MethodOutlook(MethodBase):
|
|||
- filter (str, optional): Sender, query operators, or subject text.
|
||||
- outputMimeType (str, optional): MIME type for output file. Options: "application/json" (default), "text/plain", "text/csv". Default: "application/json".
|
||||
"""
|
||||
import time
|
||||
operationId = None
|
||||
try:
|
||||
# Init progress logger
|
||||
workflowId = self.services.workflow.id if self.services.workflow else f"no-workflow-{int(time.time())}"
|
||||
operationId = f"outlook_read_{workflowId}_{int(time.time())}"
|
||||
|
||||
# Start progress tracking
|
||||
self.services.chat.progressLogStart(
|
||||
operationId,
|
||||
"Read Emails",
|
||||
"Outlook Email Reading",
|
||||
f"Folder: {parameters.get('folder', 'Inbox')}"
|
||||
)
|
||||
|
||||
connectionReference = parameters.get("connectionReference")
|
||||
folder = parameters.get("folder", "Inbox")
|
||||
limit = parameters.get("limit", 10)
|
||||
|
|
@ -334,8 +348,12 @@ class MethodOutlook(MethodBase):
|
|||
outputMimeType = parameters.get("outputMimeType", "application/json")
|
||||
|
||||
if not connectionReference:
|
||||
if operationId:
|
||||
self.services.chat.progressLogFinish(operationId, False)
|
||||
return ActionResult.isFailure(error="Connection reference is required")
|
||||
|
||||
self.services.chat.progressLogUpdate(operationId, 0.2, "Validating parameters")
|
||||
|
||||
# Validate limit parameter
|
||||
if limit <= 0:
|
||||
limit = 1000
|
||||
|
|
@ -351,11 +369,14 @@ class MethodOutlook(MethodBase):
|
|||
|
||||
|
||||
# Get Microsoft connection
|
||||
self.services.chat.progressLogUpdate(operationId, 0.3, "Getting Microsoft connection")
|
||||
connection = self._getMicrosoftConnection(connectionReference)
|
||||
if not connection:
|
||||
self.services.chat.progressLogFinish(operationId, False)
|
||||
return ActionResult.isFailure(error="No valid Microsoft connection found for the provided connection reference")
|
||||
|
||||
# Read emails using Microsoft Graph API
|
||||
self.services.chat.progressLogUpdate(operationId, 0.4, "Reading emails from Microsoft Graph API")
|
||||
try:
|
||||
# Microsoft Graph API endpoint for messages
|
||||
graph_url = "https://graph.microsoft.com/v1.0"
|
||||
|
|
@ -387,6 +408,11 @@ class MethodOutlook(MethodBase):
|
|||
# If using $search, remove $orderby as they can't be combined
|
||||
if "$search" in params:
|
||||
params.pop("$orderby", None)
|
||||
|
||||
# If using $filter with contains(), remove $orderby as they can't be combined
|
||||
# Microsoft Graph API doesn't support contains() with orderby
|
||||
if "$filter" in params and "contains(" in params["$filter"].lower():
|
||||
params.pop("$orderby", None)
|
||||
|
||||
# Filter applied
|
||||
|
||||
|
|
@ -403,6 +429,7 @@ class MethodOutlook(MethodBase):
|
|||
|
||||
response.raise_for_status()
|
||||
|
||||
self.services.chat.progressLogUpdate(operationId, 0.7, "Processing email data")
|
||||
emails_data = response.json()
|
||||
email_data = {
|
||||
"emails": emails_data.get("value", []),
|
||||
|
|
@ -420,22 +447,34 @@ class MethodOutlook(MethodBase):
|
|||
|
||||
except ImportError:
|
||||
logger.error("requests module not available")
|
||||
if operationId:
|
||||
self.services.chat.progressLogFinish(operationId, False)
|
||||
return ActionResult.isFailure(error="requests module not available")
|
||||
except requests.exceptions.HTTPError as e:
|
||||
if e.response.status_code == 400:
|
||||
logger.error(f"Bad Request (400) - Invalid filter or parameter: {e.response.text}")
|
||||
if operationId:
|
||||
self.services.chat.progressLogFinish(operationId, False)
|
||||
return ActionResult.isFailure(error=f"Invalid filter syntax. Please check your filter parameter. Error: {e.response.text}")
|
||||
elif e.response.status_code == 401:
|
||||
logger.error("Unauthorized (401) - Access token may be expired or invalid")
|
||||
if operationId:
|
||||
self.services.chat.progressLogFinish(operationId, False)
|
||||
return ActionResult.isFailure(error="Authentication failed. Please check your connection and try again.")
|
||||
elif e.response.status_code == 403:
|
||||
logger.error("Forbidden (403) - Insufficient permissions to access emails")
|
||||
if operationId:
|
||||
self.services.chat.progressLogFinish(operationId, False)
|
||||
return ActionResult.isFailure(error="Insufficient permissions to read emails from this folder.")
|
||||
else:
|
||||
logger.error(f"HTTP Error {e.response.status_code}: {e.response.text}")
|
||||
if operationId:
|
||||
self.services.chat.progressLogFinish(operationId, False)
|
||||
return ActionResult.isFailure(error=f"HTTP Error {e.response.status_code}: {e.response.text}")
|
||||
except Exception as e:
|
||||
logger.error(f"Error reading emails from Microsoft Graph API: {str(e)}")
|
||||
if operationId:
|
||||
self.services.chat.progressLogFinish(operationId, False)
|
||||
return ActionResult.isFailure(error=f"Failed to read emails: {str(e)}")
|
||||
|
||||
# Determine output format based on MIME type
|
||||
|
|
@ -475,6 +514,9 @@ class MethodOutlook(MethodBase):
|
|||
"outputMimeType": outputMimeType
|
||||
}
|
||||
|
||||
self.services.chat.progressLogUpdate(operationId, 0.9, f"Found {email_data.get('count', 0)} emails")
|
||||
self.services.chat.progressLogFinish(operationId, True)
|
||||
|
||||
return ActionResult.isSuccess(
|
||||
documents=[ActionDocument(
|
||||
documentName=f"outlook_emails_{self._format_timestamp_for_filename()}.json",
|
||||
|
|
@ -486,6 +528,11 @@ class MethodOutlook(MethodBase):
|
|||
|
||||
except Exception as e:
|
||||
logger.error(f"Error reading emails: {str(e)}")
|
||||
if operationId:
|
||||
try:
|
||||
self.services.chat.progressLogFinish(operationId, False)
|
||||
except:
|
||||
pass # Don't fail on progress logging errors
|
||||
return ActionResult.isFailure(
|
||||
error=str(e)
|
||||
)
|
||||
|
|
@ -1491,14 +1538,32 @@ Return JSON:
|
|||
- connectionReference (str, required): Microsoft connection label.
|
||||
- documentList (list, required): Document reference(s) to draft emails in JSON format (outputs from outlook.composeAndDraftEmailWithContext function).
|
||||
"""
|
||||
import time
|
||||
operationId = None
|
||||
try:
|
||||
# Init progress logger
|
||||
workflowId = self.services.workflow.id if self.services.workflow else f"no-workflow-{int(time.time())}"
|
||||
operationId = f"outlook_send_{workflowId}_{int(time.time())}"
|
||||
|
||||
# Start progress tracking
|
||||
self.services.chat.progressLogStart(
|
||||
operationId,
|
||||
"Send Draft Email",
|
||||
"Outlook Email Sending",
|
||||
f"Processing {len(parameters.get('documentList', []))} draft(s)"
|
||||
)
|
||||
|
||||
connectionReference = parameters.get("connectionReference")
|
||||
documentList = parameters.get("documentList", [])
|
||||
|
||||
if not connectionReference:
|
||||
if operationId:
|
||||
self.services.chat.progressLogFinish(operationId, False)
|
||||
return ActionResult.isFailure(error="Connection reference is required")
|
||||
|
||||
if not documentList:
|
||||
if operationId:
|
||||
self.services.chat.progressLogFinish(operationId, False)
|
||||
return ActionResult.isFailure(error="documentList is required and cannot be empty")
|
||||
|
||||
# Convert single value to list if needed
|
||||
|
|
@ -1506,16 +1571,21 @@ Return JSON:
|
|||
documentList = [documentList]
|
||||
|
||||
# Get Microsoft connection
|
||||
self.services.chat.progressLogUpdate(operationId, 0.2, "Getting Microsoft connection")
|
||||
connection = self._getMicrosoftConnection(connectionReference)
|
||||
if not connection:
|
||||
self.services.chat.progressLogFinish(operationId, False)
|
||||
return ActionResult.isFailure(error="No valid Microsoft connection found for the provided connection reference")
|
||||
|
||||
# Check permissions
|
||||
self.services.chat.progressLogUpdate(operationId, 0.3, "Checking permissions")
|
||||
permissions_ok = await self._checkPermissions(connection)
|
||||
if not permissions_ok:
|
||||
self.services.chat.progressLogFinish(operationId, False)
|
||||
return ActionResult.isFailure(error="Connection lacks necessary permissions for Outlook operations")
|
||||
|
||||
# Read draft email JSON documents from documentList
|
||||
self.services.chat.progressLogUpdate(operationId, 0.4, "Reading draft email documents")
|
||||
draftEmails = []
|
||||
for docRef in documentList:
|
||||
try:
|
||||
|
|
@ -1586,8 +1656,11 @@ Return JSON:
|
|||
continue
|
||||
|
||||
if not draftEmails:
|
||||
self.services.chat.progressLogFinish(operationId, False)
|
||||
return ActionResult.isFailure(error="No valid draft email JSON documents found in documentList")
|
||||
|
||||
self.services.chat.progressLogUpdate(operationId, 0.6, f"Found {len(draftEmails)} draft email(s) to send")
|
||||
|
||||
# Send all draft emails
|
||||
graph_url = "https://graph.microsoft.com/v1.0"
|
||||
headers = {
|
||||
|
|
@ -1598,7 +1671,8 @@ Return JSON:
|
|||
sentResults = []
|
||||
failedResults = []
|
||||
|
||||
for draftEmail in draftEmails:
|
||||
self.services.chat.progressLogUpdate(operationId, 0.7, "Sending emails")
|
||||
for idx, draftEmail in enumerate(draftEmails):
|
||||
draftEmailJson = draftEmail["draftEmailJson"]
|
||||
draftId = draftEmail["draftId"]
|
||||
sourceDocument = draftEmail["sourceDocument"]
|
||||
|
|
@ -1628,6 +1702,7 @@ Return JSON:
|
|||
"sourceDocument": sourceDocument
|
||||
})
|
||||
logger.info(f"Email sent successfully. Draft ID: {draftId}, Subject: {subject}")
|
||||
self.services.chat.progressLogUpdate(operationId, 0.7 + (idx + 1) * 0.2 / len(draftEmails), f"Sent {idx + 1}/{len(draftEmails)}: {subject}")
|
||||
else:
|
||||
errorResult = {
|
||||
"status": "error",
|
||||
|
|
@ -1674,7 +1749,9 @@ Return JSON:
|
|||
}
|
||||
|
||||
# Determine overall success status
|
||||
self.services.chat.progressLogUpdate(operationId, 0.9, f"Sent {successfulEmails}/{totalEmails} email(s)")
|
||||
if successfulEmails == 0:
|
||||
self.services.chat.progressLogFinish(operationId, False)
|
||||
validationMetadata = {
|
||||
"actionType": "outlook.sendDraftEmail",
|
||||
"connectionReference": connectionReference,
|
||||
|
|
@ -1703,6 +1780,7 @@ Return JSON:
|
|||
"failedEmails": failedEmails,
|
||||
"status": "partial_success"
|
||||
}
|
||||
self.services.chat.progressLogFinish(operationId, True)
|
||||
return ActionResult(
|
||||
success=True,
|
||||
documents=[ActionDocument(
|
||||
|
|
@ -1723,6 +1801,7 @@ Return JSON:
|
|||
"failedEmails": failedEmails,
|
||||
"status": "all_successful"
|
||||
}
|
||||
self.services.chat.progressLogFinish(operationId, True)
|
||||
return ActionResult(
|
||||
success=True,
|
||||
documents=[ActionDocument(
|
||||
|
|
|
|||
|
|
@ -1120,7 +1120,21 @@ class MethodSharepoint(MethodBase):
|
|||
- documentData: Base64-encoded content (binary files) or plain text (text files)
|
||||
- mimeType: MIME type (e.g., application/pdf, text/plain)
|
||||
"""
|
||||
import time
|
||||
operationId = None
|
||||
try:
|
||||
# Init progress logger
|
||||
workflowId = self.services.workflow.id if self.services.workflow else f"no-workflow-{int(time.time())}"
|
||||
operationId = f"sharepoint_read_{workflowId}_{int(time.time())}"
|
||||
|
||||
# Start progress tracking
|
||||
self.services.chat.progressLogStart(
|
||||
operationId,
|
||||
"Read Documents",
|
||||
"SharePoint Document Reading",
|
||||
f"Path: {parameters.get('pathQuery', parameters.get('pathObject', '*'))}"
|
||||
)
|
||||
|
||||
documentList = parameters.get("documentList")
|
||||
if isinstance(documentList, str):
|
||||
documentList = [documentList]
|
||||
|
|
@ -1131,11 +1145,16 @@ class MethodSharepoint(MethodBase):
|
|||
|
||||
# Validate connection reference
|
||||
if not connectionReference:
|
||||
if operationId:
|
||||
self.services.chat.progressLogFinish(operationId, False)
|
||||
return ActionResult.isFailure(error="Connection reference is required")
|
||||
|
||||
# Get connection first - needed for both pathObject and documentList approaches
|
||||
self.services.chat.progressLogUpdate(operationId, 0.2, "Getting Microsoft connection")
|
||||
connection = self._getMicrosoftConnection(connectionReference)
|
||||
if not connection:
|
||||
if operationId:
|
||||
self.services.chat.progressLogFinish(operationId, False)
|
||||
return ActionResult.isFailure(error="No valid Microsoft connection found for the provided connection reference")
|
||||
|
||||
# If pathObject is provided, extract SharePoint file IDs and read them directly
|
||||
|
|
@ -1150,6 +1169,8 @@ class MethodSharepoint(MethodBase):
|
|||
from modules.datamodels.datamodelDocref import DocumentReferenceList
|
||||
pathObjectDocuments = self.services.chat.getChatDocumentsFromDocumentList(DocumentReferenceList.from_string_list([pathObject]))
|
||||
if not pathObjectDocuments or len(pathObjectDocuments) == 0:
|
||||
if operationId:
|
||||
self.services.chat.progressLogFinish(operationId, False)
|
||||
return ActionResult.isFailure(error=f"No document list found for reference: {pathObject}")
|
||||
|
||||
# Get the first document's content (which should be the JSON from findDocumentPath)
|
||||
|
|
@ -1267,8 +1288,10 @@ class MethodSharepoint(MethodBase):
|
|||
readResults = []
|
||||
siteId = sites[0]['id']
|
||||
|
||||
for fileId in sharePointFileIds:
|
||||
self.services.chat.progressLogUpdate(operationId, 0.5, f"Reading {len(sharePointFileIds)} file(s) from SharePoint")
|
||||
for idx, fileId in enumerate(sharePointFileIds):
|
||||
try:
|
||||
self.services.chat.progressLogUpdate(operationId, 0.5 + (idx * 0.3 / len(sharePointFileIds)), f"Reading file {idx + 1}/{len(sharePointFileIds)}")
|
||||
# Get file info from SharePoint
|
||||
endpoint = f"sites/{siteId}/drive/items/{fileId}"
|
||||
fileInfo = await self._makeGraphApiCall(endpoint)
|
||||
|
|
@ -1314,11 +1337,13 @@ class MethodSharepoint(MethodBase):
|
|||
continue
|
||||
|
||||
if not readResults:
|
||||
self.services.chat.progressLogFinish(operationId, False)
|
||||
return ActionResult.isFailure(error="No files could be read from pathObject")
|
||||
|
||||
# Convert read results to ActionDocument objects
|
||||
# IMPORTANT: For binary files (PDFs), store Base64-encoded content directly in documentData
|
||||
# The system will create FileData and ChatDocument automatically
|
||||
self.services.chat.progressLogUpdate(operationId, 0.8, f"Processing {len(readResults)} document(s)")
|
||||
from modules.datamodels.datamodelChat import ActionDocument
|
||||
import base64
|
||||
|
||||
|
|
@ -1413,6 +1438,8 @@ class MethodSharepoint(MethodBase):
|
|||
actionDocuments.append(actionDoc)
|
||||
|
||||
# Return success with action documents
|
||||
self.services.chat.progressLogUpdate(operationId, 0.9, f"Read {len(actionDocuments)} document(s)")
|
||||
self.services.chat.progressLogFinish(operationId, True)
|
||||
return ActionResult.isSuccess(documents=actionDocuments)
|
||||
|
||||
# Fallback: Use documentList parameter (for backward compatibility)
|
||||
|
|
@ -1643,6 +1670,11 @@ class MethodSharepoint(MethodBase):
|
|||
)
|
||||
except Exception as e:
|
||||
logger.error(f"Error reading SharePoint documents: {str(e)}")
|
||||
if operationId:
|
||||
try:
|
||||
self.services.chat.progressLogFinish(operationId, False)
|
||||
except:
|
||||
pass # Don't fail on progress logging errors
|
||||
return ActionResult(
|
||||
success=False,
|
||||
error=str(e)
|
||||
|
|
|
|||
|
|
@ -139,14 +139,11 @@ class ContentValidator:
|
|||
"statistics": {}
|
||||
}
|
||||
|
||||
# Extract metadata
|
||||
# Extract metadata - include ALL metadata fields (generic for all action types)
|
||||
metadata = jsonData.get("metadata", {})
|
||||
if metadata:
|
||||
summary["metadata"] = {
|
||||
"title": metadata.get("title"),
|
||||
"split_strategy": metadata.get("split_strategy"),
|
||||
"extraction_method": metadata.get("extraction_method")
|
||||
}
|
||||
if metadata and isinstance(metadata, dict):
|
||||
# Include all metadata fields, not just specific ones
|
||||
summary["metadata"] = dict(metadata)
|
||||
|
||||
# Extract documents array (if present)
|
||||
documents = jsonData.get("documents", [])
|
||||
|
|
@ -195,6 +192,17 @@ class ContentValidator:
|
|||
text = textElement.get("text", "")
|
||||
if text:
|
||||
sectionSummary["textPreview"] = text[:100] + ("..." if len(text) > 100 else "")
|
||||
# Also check for textPreview directly in section (for web crawl results)
|
||||
if section.get("textPreview"):
|
||||
sectionSummary["textPreview"] = section.get("textPreview")
|
||||
|
||||
# Include any additional fields from section (generic approach)
|
||||
# This ensures all action-specific fields are preserved
|
||||
for key, value in section.items():
|
||||
if key not in sectionSummary and key not in ["elements"]: # Skip elements as they're processed separately
|
||||
# Include simple types (str, int, float, bool, list of primitives)
|
||||
if isinstance(value, (str, int, float, bool)) or (isinstance(value, list) and len(value) <= 10):
|
||||
sectionSummary[key] = value
|
||||
|
||||
summary["sections"].append(sectionSummary)
|
||||
else:
|
||||
|
|
@ -206,7 +214,8 @@ class ContentValidator:
|
|||
sectionSummary = {
|
||||
"id": section.get("id"),
|
||||
"content_type": section.get("content_type"),
|
||||
"title": section.get("title")
|
||||
"title": section.get("title"),
|
||||
"order": section.get("order")
|
||||
}
|
||||
|
||||
if section.get("content_type") == "table":
|
||||
|
|
@ -220,8 +229,21 @@ class ContentValidator:
|
|||
sectionSummary["rowCount"] = len(rows)
|
||||
sectionSummary["headers"] = headers
|
||||
|
||||
# Include any additional fields from section (generic approach)
|
||||
for key, value in section.items():
|
||||
if key not in sectionSummary and key not in ["elements"]: # Skip elements as they're processed separately
|
||||
# Include simple types (str, int, float, bool, list of primitives)
|
||||
if isinstance(value, (str, int, float, bool)) or (isinstance(value, list) and len(value) <= 10):
|
||||
sectionSummary[key] = value
|
||||
|
||||
summary["sections"].append(sectionSummary)
|
||||
|
||||
# Extract statistics from root level (generic - include all statistics fields)
|
||||
rootStatistics = jsonData.get("statistics", {})
|
||||
if rootStatistics and isinstance(rootStatistics, dict):
|
||||
# Merge root statistics into summary statistics
|
||||
summary["statistics"].update(rootStatistics)
|
||||
|
||||
return summary
|
||||
|
||||
except Exception as e:
|
||||
|
|
|
|||
|
|
@ -28,11 +28,21 @@ class TaskPlanner:
|
|||
|
||||
logger.info(f"=== STARTING TASK PLAN GENERATION ===")
|
||||
logger.info(f"Workflow ID: {workflow.id}")
|
||||
logger.info(f"User Input: {userInput}")
|
||||
# Log normalized request instead of raw user input for security
|
||||
normalizedPrompt = getattr(self.services, 'currentUserPromptNormalized', None) if self.services else None
|
||||
if normalizedPrompt:
|
||||
logger.info(f"Normalized Request: {normalizedPrompt}")
|
||||
else:
|
||||
logger.info(f"Normalized Request: {userInput}")
|
||||
|
||||
# Use stored user prompt if available, otherwise use the input
|
||||
actualUserPrompt = self.services.currentUserPrompt if self.services and hasattr(self.services, 'currentUserPrompt') and self.services.currentUserPrompt else userInput
|
||||
logger.info(f"Actual User Prompt: {actualUserPrompt}")
|
||||
# Use normalized request if available, otherwise fallback to currentUserPrompt, then userInput
|
||||
actualUserPrompt = None
|
||||
if self.services and hasattr(self.services, 'currentUserPromptNormalized') and self.services.currentUserPromptNormalized:
|
||||
actualUserPrompt = self.services.currentUserPromptNormalized
|
||||
elif self.services and hasattr(self.services, 'currentUserPrompt') and self.services.currentUserPrompt:
|
||||
actualUserPrompt = self.services.currentUserPrompt
|
||||
else:
|
||||
actualUserPrompt = userInput
|
||||
|
||||
# Check workflow status before calling AI service
|
||||
checkWorkflowStopped(self.services)
|
||||
|
|
|
|||
|
|
@ -96,6 +96,10 @@ class DynamicMode(BaseMode):
|
|||
# NEW: Reset progress tracking for new task
|
||||
self.progressTracker.reset()
|
||||
|
||||
# Initialize executed actions tracking for this task
|
||||
if not hasattr(context, 'executedActions') or context.executedActions is None:
|
||||
context.executedActions = []
|
||||
|
||||
# Update workflow object before executing task
|
||||
self._updateWorkflowBeforeExecutingTask(taskIndex)
|
||||
|
||||
|
|
@ -104,7 +108,8 @@ class DynamicMode(BaseMode):
|
|||
|
||||
state = TaskExecutionState(taskStep)
|
||||
# Dynamic mode uses max_steps instead of max_retries
|
||||
state.max_steps = max(1, int(getattr(workflow, 'maxSteps', 10)))
|
||||
# maxSteps is set in workflowManager.py when workflow is created
|
||||
state.max_steps = int(getattr(workflow, 'maxSteps', 1))
|
||||
logger.info(f"Using Dynamic mode execution with max_steps: {state.max_steps}")
|
||||
|
||||
step = 1
|
||||
|
|
@ -128,6 +133,19 @@ class DynamicMode(BaseMode):
|
|||
observation = self._observeBuild(result)
|
||||
# Note: resultLabel is already set correctly in _observeBuild from actionResult.resultLabel
|
||||
|
||||
# Store executed action in context for action history
|
||||
if not hasattr(context, 'executedActions') or context.executedActions is None:
|
||||
context.executedActions = []
|
||||
actionName = selection.get('action', 'unknown')
|
||||
actionParameters = selection.get('parameters', {}) or {}
|
||||
# Filter out documentList for clarity in history
|
||||
relevantParams = {k: v for k, v in actionParameters.items() if k not in ['documentList', 'connections']}
|
||||
context.executedActions.append({
|
||||
'action': actionName,
|
||||
'parameters': relevantParams,
|
||||
'step': step
|
||||
})
|
||||
|
||||
# Content validation (against original cleaned user prompt / workflow intent)
|
||||
if getattr(self, 'workflowIntent', None) and result.documents:
|
||||
# Pass ALL documents to validator - validator decides what to validate (generic approach)
|
||||
|
|
@ -883,9 +901,20 @@ class DynamicMode(BaseMode):
|
|||
elif progressState['nextActionsSuggested']:
|
||||
enhancedReviewContent += f"Next Action Suggestions: {', '.join(progressState['nextActionsSuggested'])}\n"
|
||||
|
||||
# NEW: Add action history to review content
|
||||
# NEW: Add action history to review content - use all executed actions
|
||||
actionHistory = []
|
||||
|
||||
# First, add all executed actions from the current task
|
||||
if hasattr(context, 'executedActions') and context.executedActions:
|
||||
for executedAction in context.executedActions:
|
||||
action = executedAction.get('action', 'unknown')
|
||||
params = executedAction.get('parameters', {}) or {}
|
||||
paramsStr = json.dumps(params, ensure_ascii=False) if params else "{}"
|
||||
step = executedAction.get('step', 0)
|
||||
actionHistory.append(f"Step {step}: {action} {paramsStr}")
|
||||
|
||||
# Also include refinement decisions for completeness (these show what was planned)
|
||||
if hasattr(context, 'previousReviewResult') and context.previousReviewResult:
|
||||
actionHistory = []
|
||||
for i, prevDecision in enumerate(context.previousReviewResult, 1):
|
||||
if prevDecision and hasattr(prevDecision, 'nextAction') and prevDecision.nextAction:
|
||||
action = prevDecision.nextAction
|
||||
|
|
@ -895,21 +924,27 @@ class DynamicMode(BaseMode):
|
|||
paramsStr = json.dumps(relevantParams, ensure_ascii=False) if relevantParams else "{}"
|
||||
quality = getattr(prevDecision, 'qualityScore', None)
|
||||
qualityStr = f" (quality: {quality:.2f})" if quality is not None else ""
|
||||
actionHistory.append(f"Round {i}: {action} {paramsStr}{qualityStr}")
|
||||
|
||||
if actionHistory:
|
||||
enhancedReviewContent += f"\nACTION HISTORY:\n"
|
||||
enhancedReviewContent += "\n".join(f"- {entry}" for entry in actionHistory)
|
||||
# Detect repeated actions
|
||||
actionCounts = {}
|
||||
for entry in actionHistory:
|
||||
# Extract action name (before first space or {)
|
||||
actionName = entry.split()[1] if len(entry.split()) > 1 else "unknown"
|
||||
# Only add if not already in executedActions (avoid duplicates)
|
||||
actionEntry = f"Refinement {i}: {action} {paramsStr}{qualityStr}"
|
||||
if actionEntry not in actionHistory:
|
||||
actionHistory.append(actionEntry)
|
||||
|
||||
if actionHistory:
|
||||
enhancedReviewContent += f"\nACTION HISTORY:\n"
|
||||
enhancedReviewContent += "\n".join(f"- {entry}" for entry in actionHistory)
|
||||
# Detect repeated actions
|
||||
actionCounts = {}
|
||||
for entry in actionHistory:
|
||||
# Extract action name (after first space, before next space or {)
|
||||
parts = entry.split()
|
||||
if len(parts) > 1:
|
||||
# Skip "Step", "Refinement" prefixes and get the action name
|
||||
actionName = parts[1] if parts[0] in ['Step', 'Refinement'] else parts[0]
|
||||
actionCounts[actionName] = actionCounts.get(actionName, 0) + 1
|
||||
|
||||
repeatedActions = [action for action, count in actionCounts.items() if count >= 2]
|
||||
if repeatedActions:
|
||||
enhancedReviewContent += f"\nWARNING: Repeated actions detected: {', '.join(repeatedActions)}. Consider a fundamentally different approach.\n"
|
||||
|
||||
repeatedActions = [action for action, count in actionCounts.items() if count >= 2]
|
||||
if repeatedActions:
|
||||
enhancedReviewContent += f"\nWARNING: Repeated actions detected: {', '.join(repeatedActions)}. Consider a fundamentally different approach.\n"
|
||||
|
||||
# Update placeholders with enhanced review content
|
||||
placeholders["REVIEW_CONTENT"] = enhancedReviewContent
|
||||
|
|
|
|||
|
|
@ -19,7 +19,7 @@ class TaskExecutionState:
|
|||
self.max_retries = 3
|
||||
# Iterative loop (dynamic mode)
|
||||
self.current_step = 0
|
||||
self.max_steps = 5
|
||||
self.max_steps = 0 # Will be overridden by workflow.maxSteps from workflowManager.py
|
||||
|
||||
def addSuccessfulAction(self, action_result: ActionResult):
|
||||
"""Add a successful action to the state"""
|
||||
|
|
@ -56,7 +56,7 @@ class TaskExecutionState:
|
|||
patterns.append("permission_issues")
|
||||
return list(set(patterns))
|
||||
|
||||
def shouldContinue(observation: Optional[Observation], review=None, current_step: int = 0, max_steps: int = 5) -> bool:
|
||||
def shouldContinue(observation: Optional[Observation], review=None, current_step: int = 0, max_steps: int = 1) -> bool:
|
||||
"""Helper to decide if the iterative loop should continue
|
||||
|
||||
Args:
|
||||
|
|
|
|||
|
|
@ -61,6 +61,7 @@ Break down user requests into logical, executable task steps.
|
|||
## 📋 Context
|
||||
|
||||
### User Request
|
||||
The following is the user's normalized request:
|
||||
{{KEY:USER_PROMPT}}
|
||||
|
||||
### Workflow Intent
|
||||
|
|
|
|||
|
|
@ -64,21 +64,30 @@ class WorkflowProcessor:
|
|||
logger.info(f"=== STARTING TASK PLAN GENERATION ===")
|
||||
logger.info(f"Using user language: {self.services.currentUserLanguage}")
|
||||
logger.info(f"Workflow ID: {workflow.id}")
|
||||
logger.info(f"User Input: {userInput}")
|
||||
# Log normalized request instead of raw user input for security
|
||||
normalizedPrompt = getattr(self.services, 'currentUserPromptNormalized', None) or userInput
|
||||
logger.info(f"Normalized Request: {normalizedPrompt}")
|
||||
modeValue = workflow.workflowMode.value if hasattr(workflow.workflowMode, 'value') else workflow.workflowMode
|
||||
logger.info(f"Workflow Mode: {modeValue}")
|
||||
|
||||
# Update progress - generating task plan
|
||||
self.services.chat.progressLogUpdate(operationId, 0.3, "Analyzing input")
|
||||
|
||||
# Use normalized request instead of raw userInput for security
|
||||
normalizedPrompt = getattr(self.services, 'currentUserPromptNormalized', None) or userInput
|
||||
|
||||
# Delegate to the appropriate mode
|
||||
taskPlan = await self.mode.generateTaskPlan(userInput, workflow)
|
||||
taskPlan = await self.mode.generateTaskPlan(normalizedPrompt, workflow)
|
||||
|
||||
# Update progress - creating task plan message
|
||||
self.services.chat.progressLogUpdate(operationId, 0.8, "Creating plan")
|
||||
|
||||
# Create task plan message
|
||||
await self.mode.createTaskPlanMessage(taskPlan, workflow)
|
||||
# Create task plan message only if there are 2+ tasks
|
||||
# Single-task workflows don't need a task plan message
|
||||
if taskPlan.tasks and len(taskPlan.tasks) >= 2:
|
||||
await self.mode.createTaskPlanMessage(taskPlan, workflow)
|
||||
else:
|
||||
logger.info(f"Skipping task plan message creation - only {len(taskPlan.tasks) if taskPlan.tasks else 0} task(s)")
|
||||
|
||||
# Complete progress tracking
|
||||
self.services.chat.progressLogFinish(operationId, True)
|
||||
|
|
@ -315,12 +324,16 @@ class WorkflowProcessor:
|
|||
|
||||
# Fast Path Implementation
|
||||
|
||||
async def detectComplexity(self, prompt: str, documents: Optional[List[ChatDocument]] = None) -> str:
|
||||
async def detectComplexity(self, prompt: str, documents: Optional[List[ChatDocument]] = None) -> tuple[str, bool, Optional[str]]:
|
||||
"""
|
||||
Detect request complexity using AI-based semantic understanding.
|
||||
Also detects user language for fast path responses.
|
||||
|
||||
Returns:
|
||||
"simple" | "moderate" | "complex"
|
||||
Tuple of (complexity: str, needsWorkflowHistory: bool, detectedLanguage: Optional[str])
|
||||
complexity: "simple" | "moderate" | "complex"
|
||||
needsWorkflowHistory: True if request needs previous workflow rounds/history
|
||||
detectedLanguage: ISO 639-1 language code (e.g., "de", "en") or None
|
||||
|
||||
Simple: Single question, no documents, straightforward answer (5-15s)
|
||||
Moderate: Multiple steps, some documents, structured response (30-60s)
|
||||
|
|
@ -330,38 +343,47 @@ class WorkflowProcessor:
|
|||
# Ensure AI service is initialized
|
||||
await self.services.ai.ensureAiObjectsInitialized()
|
||||
|
||||
# Build complexity detection prompt (language-agnostic, semantic)
|
||||
# Build complexity detection prompt (includes language detection)
|
||||
# JSON template comes BEFORE user input for security
|
||||
complexityPrompt = (
|
||||
"You are a complexity analyzer. Analyze the user's request and determine its complexity level.\n\n"
|
||||
"You are a complexity analyzer. Analyze the user's request and determine its complexity level and language.\n\n"
|
||||
"Consider:\n"
|
||||
"- Number of distinct tasks or steps required\n"
|
||||
"- Amount and type of documents provided\n"
|
||||
"- Need for external research or web search\n"
|
||||
"- Need for document analysis or extraction\n"
|
||||
"- Need for content generation (reports, summaries, etc.)\n"
|
||||
"- Need for multi-step reasoning or planning\n\n"
|
||||
"- Need for multi-step reasoning or planning\n"
|
||||
"- Need for previous workflow rounds/history (e.g., 'continue', 'retry', 'fix', 'improve', 'update', 'modify', 'based on previous', 'build on', references to earlier work)\n"
|
||||
"- Language: Detect the ISO 639-1 language code (e.g., de, en, fr, it) from the user's request\n\n"
|
||||
"Complexity levels:\n"
|
||||
"- 'simple': Single question, no documents or minimal documents, straightforward answer that can be provided in one AI response (5-15s)\n"
|
||||
"- 'moderate': Multiple steps, some documents, structured response requiring some processing (30-60s)\n"
|
||||
"- 'complex': Multi-task workflow, many documents, research needed, content generation required, multi-step planning (60-120s)\n\n"
|
||||
f"User request:\n{prompt}\n\n"
|
||||
"Return ONLY a JSON object with this exact structure:\n"
|
||||
"{\n"
|
||||
' "complexity": "simple" | "moderate" | "complex",\n'
|
||||
' "reasoning": "Brief explanation of why this complexity level",\n'
|
||||
' "needsWorkflowHistory": true|false,\n'
|
||||
' "detectedLanguage": "de|en|fr|it|..." (ISO 639-1 language code)\n'
|
||||
"}\n\n"
|
||||
"################ USER INPUT START #################\n"
|
||||
)
|
||||
|
||||
# Add sanitized user input with clear delimiters
|
||||
# Escape curly braces for f-string safety, but preserve format (no quote wrapping)
|
||||
sanitizedPrompt = prompt.replace('{', '{{').replace('}', '}}') if prompt else ""
|
||||
complexityPrompt += f"{sanitizedPrompt}\n"
|
||||
|
||||
complexityPrompt += "################ USER INPUT FINISH #################\n\n"
|
||||
|
||||
if documents and len(documents) > 0:
|
||||
complexityPrompt += f"\nDocuments provided: {len(documents)} document(s)\n"
|
||||
complexityPrompt += f"Documents provided: {len(documents)} document(s)\n"
|
||||
# Add document types
|
||||
docTypes = [doc.mimeType for doc in documents if hasattr(doc, 'mimeType')]
|
||||
if docTypes:
|
||||
complexityPrompt += f"Document types: {', '.join(set(docTypes))}\n"
|
||||
|
||||
complexityPrompt += (
|
||||
"\nReturn ONLY a JSON object with this exact structure:\n"
|
||||
"{\n"
|
||||
' "complexity": "simple" | "moderate" | "complex",\n'
|
||||
' "reasoning": "Brief explanation of why this complexity level"\n'
|
||||
"}\n"
|
||||
)
|
||||
|
||||
# Call AI for complexity detection (planning call - no documents needed)
|
||||
aiResponse = await self.services.ai.callAiPlanning(
|
||||
prompt=complexityPrompt,
|
||||
|
|
@ -371,6 +393,8 @@ class WorkflowProcessor:
|
|||
|
||||
# Parse response
|
||||
complexity = "moderate" # Default fallback
|
||||
needsWorkflowHistory = False # Default fallback
|
||||
detectedLanguage = None # Default fallback
|
||||
try:
|
||||
# callAiPlanning returns a string directly, not an object
|
||||
responseContent = str(aiResponse) if aiResponse else ""
|
||||
|
|
@ -384,19 +408,21 @@ class WorkflowProcessor:
|
|||
if jsonStr:
|
||||
parsed = json.loads(jsonStr)
|
||||
complexity = parsed.get("complexity", "moderate")
|
||||
needsWorkflowHistory = parsed.get("needsWorkflowHistory", False)
|
||||
detectedLanguage = parsed.get("detectedLanguage") or None
|
||||
reasoning = parsed.get("reasoning", "")
|
||||
logger.info(f"Complexity detected: {complexity} - {reasoning}")
|
||||
logger.info(f"Complexity detected: {complexity}, needsWorkflowHistory: {needsWorkflowHistory}, language: {detectedLanguage} - {reasoning}")
|
||||
else:
|
||||
logger.warning("Could not parse complexity detection response, defaulting to 'moderate'")
|
||||
except Exception as e:
|
||||
logger.warning(f"Error parsing complexity detection: {str(e)}, defaulting to 'moderate'")
|
||||
|
||||
return complexity
|
||||
return (complexity, needsWorkflowHistory, detectedLanguage)
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Error in detectComplexity: {str(e)}")
|
||||
# Default to moderate on error (safe fallback)
|
||||
return "moderate"
|
||||
return ("moderate", False, None)
|
||||
|
||||
async def fastPathExecute(self, prompt: str, documents: Optional[List[ChatDocument]] = None, userLanguage: Optional[str] = None) -> ActionResult:
|
||||
"""
|
||||
|
|
@ -416,9 +442,12 @@ class WorkflowProcessor:
|
|||
await self.services.ai.ensureAiObjectsInitialized()
|
||||
|
||||
# Build fast path prompt (understand + execute + deliver in one call)
|
||||
# Clearly separate user prompt for security
|
||||
fastPathPrompt = (
|
||||
"You are a helpful assistant. Answer the user's question directly and comprehensively.\n\n"
|
||||
f"User question:\n{prompt}\n\n"
|
||||
"## User Question\n"
|
||||
"The following is the user's request:\n\n"
|
||||
f"{prompt}\n\n"
|
||||
)
|
||||
|
||||
# Add user language context if available
|
||||
|
|
@ -443,7 +472,7 @@ class WorkflowProcessor:
|
|||
)
|
||||
|
||||
# Call AI directly (no document generation - just plain text response)
|
||||
# Use aiObjects.call() instead of callAiContent() to avoid document generation path
|
||||
# Use callWithTextContext() for text-only calls
|
||||
aiRequest = AiCallRequest(
|
||||
prompt=fastPathPrompt,
|
||||
context="",
|
||||
|
|
@ -451,7 +480,7 @@ class WorkflowProcessor:
|
|||
contentParts=None # Fast path doesn't process documents
|
||||
)
|
||||
|
||||
aiCallResponse = await self.services.ai.aiObjects.call(aiRequest)
|
||||
aiCallResponse = await self.services.ai.aiObjects.callWithTextContext(aiRequest)
|
||||
|
||||
# Extract response content (AiCallResponse.content is a string)
|
||||
responseText = aiCallResponse.content if aiCallResponse.content else ""
|
||||
|
|
|
|||
|
|
@ -97,7 +97,7 @@ class WorkflowManager:
|
|||
"mandateId": self.services.user.mandateId,
|
||||
"messageIds": [],
|
||||
"workflowMode": workflowMode,
|
||||
"maxSteps": 5 if workflowMode == WorkflowModeEnum.WORKFLOW_DYNAMIC else 1, # Set maxSteps for Dynamic mode
|
||||
"maxSteps": 10 , # Set maxSteps
|
||||
}
|
||||
|
||||
workflow = self.services.chat.createWorkflow(workflowData)
|
||||
|
|
@ -160,6 +160,9 @@ class WorkflowManager:
|
|||
# Reset progress logger for new workflow
|
||||
self.services.chat._progressLogger = None
|
||||
|
||||
# Reset workflow history flag at start of each workflow
|
||||
setattr(self.services, '_needsWorkflowHistory', False)
|
||||
|
||||
self.workflowProcessor = WorkflowProcessor(self.services)
|
||||
|
||||
# Get workflow mode to determine if complexity detection is needed
|
||||
|
|
@ -169,6 +172,8 @@ class WorkflowManager:
|
|||
if skipComplexityDetection:
|
||||
logger.info("Skipping complexity detection for AUTOMATION mode - using predefined plan")
|
||||
complexity = "moderate" # Default for automation workflows
|
||||
needsWorkflowHistory = False # Automation workflows don't need history
|
||||
detectedLanguage = None # No language detection in automation mode
|
||||
else:
|
||||
# Process user-uploaded documents from userInput for complexity detection
|
||||
# This is the correct way: use the input data directly, not workflow state
|
||||
|
|
@ -180,24 +185,27 @@ class WorkflowManager:
|
|||
logger.warning(f"Failed to process user fileIds for complexity detection: {e}")
|
||||
|
||||
# Detect complexity (AI-based semantic understanding) using user input documents
|
||||
complexity = await self.workflowProcessor.detectComplexity(userInput.prompt, documents)
|
||||
logger.info(f"Request complexity detected: {complexity}")
|
||||
# Also detects language for fast path responses
|
||||
complexity, needsWorkflowHistory, detectedLanguage = await self.workflowProcessor.detectComplexity(userInput.prompt, documents)
|
||||
logger.info(f"Request complexity detected: {complexity}, needsWorkflowHistory: {needsWorkflowHistory}, language: {detectedLanguage}")
|
||||
|
||||
# Set detected language for fast path (if detected)
|
||||
if detectedLanguage and isinstance(detectedLanguage, str):
|
||||
self._setUserLanguage(detectedLanguage)
|
||||
try:
|
||||
setattr(self.services, 'currentUserLanguage', detectedLanguage)
|
||||
except Exception:
|
||||
pass
|
||||
|
||||
# Now send the first message (which will also process the documents again, but that's fine)
|
||||
await self._sendFirstMessage(userInput)
|
||||
|
||||
# Check if workflow history is needed before deciding on fast path
|
||||
# Use AI intention analysis result only (no keyword matching)
|
||||
needsHistory = getattr(self.services, '_needsWorkflowHistory', False)
|
||||
hasHistory = self._checkIfHistoryAvailable()
|
||||
|
||||
# Route to fast path for simple requests (skip for automation mode and if history is needed)
|
||||
if not skipComplexityDetection and complexity == "simple" and not (needsHistory and hasHistory):
|
||||
# Route to fast path for simple requests if history is not needed
|
||||
# Skip fast path for automation mode or if history is needed
|
||||
if complexity == "simple" and not needsWorkflowHistory:
|
||||
logger.info("Routing to fast path for simple request")
|
||||
await self._executeFastPath(userInput, documents)
|
||||
return # Fast path completes the workflow
|
||||
elif needsHistory and hasHistory:
|
||||
logger.info(f"Skipping fast path - workflow history is needed (from AI intention analysis) and available")
|
||||
|
||||
# Now send the first message (which will also process the documents again, but that's fine)
|
||||
await self._sendFirstMessage(userInput)
|
||||
|
||||
# Route to full workflow for moderate/complex requests or automation mode
|
||||
logger.info(f"Routing to full workflow for {complexity} request" + (" (automation mode)" if skipComplexityDetection else ""))
|
||||
|
|
@ -222,9 +230,10 @@ class WorkflowManager:
|
|||
# Get user language if available
|
||||
userLanguage = getattr(self.services, 'currentUserLanguage', None)
|
||||
|
||||
# Execute fast path
|
||||
# Execute fast path - use normalizedRequest if available, otherwise use raw prompt
|
||||
normalizedPrompt = getattr(self.services, 'currentUserPromptNormalized', None) or userInput.prompt
|
||||
result = await self.workflowProcessor.fastPathExecute(
|
||||
prompt=userInput.prompt,
|
||||
prompt=normalizedPrompt,
|
||||
documents=documents,
|
||||
userLanguage=userLanguage
|
||||
)
|
||||
|
|
@ -279,12 +288,20 @@ class WorkflowManager:
|
|||
}
|
||||
chatDocuments.append(chatDoc)
|
||||
|
||||
# Mark workflow as completed BEFORE storing message (so UI polling stops)
|
||||
workflow.status = "completed"
|
||||
workflow.lastActivity = self.services.utils.timestampGetUtc()
|
||||
self.services.chat.updateWorkflow(workflow.id, {
|
||||
"status": "completed",
|
||||
"lastActivity": workflow.lastActivity
|
||||
})
|
||||
|
||||
# Create ChatMessage with fast path response (in user's language)
|
||||
messageData = {
|
||||
"workflowId": workflow.id,
|
||||
"role": "assistant",
|
||||
"message": responseText or "Fast path response completed",
|
||||
"status": "last", # Fast path completes the workflow
|
||||
"status": "last", # Fast path completes the workflow - UI polling stops on this
|
||||
"sequenceNr": len(workflow.messages) + 1,
|
||||
"publishedAt": self.services.utils.timestampGetUtc(),
|
||||
"documentsLabel": "fast_path_response",
|
||||
|
|
@ -301,14 +318,6 @@ class WorkflowManager:
|
|||
# Store message with documents
|
||||
self.services.chat.storeMessageWithDocuments(workflow, messageData, chatDocuments)
|
||||
|
||||
# Mark workflow as completed
|
||||
workflow.status = "completed"
|
||||
workflow.lastActivity = self.services.utils.timestampGetUtc()
|
||||
self.services.chat.updateWorkflow(workflow.id, {
|
||||
"status": "completed",
|
||||
"lastActivity": workflow.lastActivity
|
||||
})
|
||||
|
||||
logger.info(f"Fast path completed successfully, response length: {len(responseText)} chars")
|
||||
|
||||
except Exception as e:
|
||||
|
|
@ -405,7 +414,11 @@ class WorkflowManager:
|
|||
" \"successCriteria\": [\"specific criterion 1\", \"specific criterion 2\"],\n"
|
||||
" \"needsWorkflowHistory\": true|false\n"
|
||||
"}\n\n"
|
||||
f"User message:\n{self.services.utils.sanitizePromptContent(userInput.prompt, 'userinput')}"
|
||||
"## User Message\n"
|
||||
"The following is the user's original input message. Extract intent, normalize the request, and identify any large context blocks that should be moved to separate documents:\n\n"
|
||||
"################ USER INPUT START #################\n"
|
||||
f"{userInput.prompt.replace('{', '{{').replace('}', '}}') if userInput.prompt else ''}\n"
|
||||
"################ USER INPUT FINISH #################"
|
||||
)
|
||||
|
||||
# Call AI analyzer (planning call - will use static parameters)
|
||||
|
|
@ -446,8 +459,8 @@ class WorkflowManager:
|
|||
|
||||
# Store needsWorkflowHistory in services for fast path decision
|
||||
needsHistoryFromIntention = parsed.get('needsWorkflowHistory', False)
|
||||
if isinstance(needsHistoryFromIntention, bool):
|
||||
setattr(self.services, '_needsWorkflowHistory', needsHistoryFromIntention)
|
||||
# Always set the value - default to False if not a boolean
|
||||
setattr(self.services, '_needsWorkflowHistory', bool(needsHistoryFromIntention) if isinstance(needsHistoryFromIntention, bool) else False)
|
||||
|
||||
# Store workflowIntent in workflow object for reuse
|
||||
if hasattr(self.services, 'workflow') and self.services.workflow:
|
||||
|
|
@ -455,6 +468,8 @@ class WorkflowManager:
|
|||
except Exception:
|
||||
contextItems = []
|
||||
workflowIntent = None
|
||||
# Ensure needsWorkflowHistory is False if parsing fails
|
||||
setattr(self.services, '_needsWorkflowHistory', False)
|
||||
|
||||
# Update services state
|
||||
if detectedLanguage and isinstance(detectedLanguage, str):
|
||||
|
|
@ -531,7 +546,9 @@ class WorkflowManager:
|
|||
workflow = self.services.workflow
|
||||
handling = self.workflowProcessor
|
||||
# Generate task plan first (shared for both modes)
|
||||
taskPlan = await handling.generateTaskPlan(userInput.prompt, workflow)
|
||||
# Use normalizedRequest instead of raw userInput.prompt for security
|
||||
normalizedPrompt = getattr(self.services, 'currentUserPromptNormalized', None) or userInput.prompt
|
||||
taskPlan = await handling.generateTaskPlan(normalizedPrompt, workflow)
|
||||
if not taskPlan or not taskPlan.tasks:
|
||||
raise Exception("No tasks generated in task plan.")
|
||||
workflowMode = getattr(workflow, 'workflowMode')
|
||||
|
|
|
|||
Loading…
Reference in a new issue