revised validation logic
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ValueOn AG
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modules/datamodels/PROPOSAL_CLASS_ENHANCEMENTS.md
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modules/datamodels/PROPOSAL_CLASS_ENHANCEMENTS.md
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@ -0,0 +1,285 @@
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# Pydantic Class Enhancement Proposal
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## Format Tracking & Validation Alignment
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**Date:** 2025-11-02
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**Purpose:** Align validation logic with prompt requirements, enable workflow-level validation, and track expected file formats
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**Simplified Approach:** Use existing document metadata (name, size, format, mimeType) - no summary fields needed
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---
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## Executive Summary
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This proposal addresses:
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1. **Validation alignment**: What prompts ask for matches what validators check
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2. **Workflow-level validation**: Check ALL deliverables from ALL tasks against original user request
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3. **Format tracking**: Track expected formats (list) at workflow and task levels
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4. **Adaptive task planning**: Next task uses ALL workflow data (messages, document metadata) to refine objective
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**Key Simplification:** Actions deliver documents with metadata (as today). No summary fields needed - use existing document metadata.
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---
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## 1. ActionResult Class Changes
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**File:** `gateway/modules/datamodels/datamodelChat.py` (lines 483-521)
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### NO CHANGES NEEDED
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**Current Structure (KEEP ALL - ALL USED):**
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- ✅ `success: bool` - Used by validation
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- ✅ `error: Optional[str]` - Used for error handling
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- ✅ `documents: List[ActionDocument]` - Contains document metadata (name, data, mimeType)
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- ✅ `resultLabel: Optional[str]` - Used for document routing
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**Documents already provide all needed metadata:**
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- `documentName` - File name
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- `documentData` - Content
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- `mimeType` - MIME type (can derive format from this)
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**No summary field needed** - document metadata is sufficient.
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---
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## 2. TaskResult Class Changes
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**File:** `gateway/modules/datamodels/datamodelChat.py` (lines 718-736)
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### NO CHANGES NEEDED
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**Current Structure (KEEP ALL - ALL USED):**
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- ✅ `taskId: str` - Task identification
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- ✅ `status: TaskStatus` - Task status tracking
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- ✅ `success: bool` - Success flag
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- ✅ `feedback: Optional[str]` - Task feedback
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- ✅ `error: Optional[str]` - Error message
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**Document metadata available from workflow:**
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- Can extract delivered formats from documents in workflow messages
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- No need to store separately - use existing document metadata
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---
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## 3. TaskStep Class Changes
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**File:** `gateway/modules/datamodels/datamodelChat.py` (lines 790-825)
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### Modify
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- Change `expectedFormat: Optional[str]` → `expectedFormats: Optional[List[str]]`
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- Keep `dataType` and `qualityRequirements` as-is
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### Modified Class:
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```python
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class TaskStep(BaseModel):
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id: str
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objective: str
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dependencies: Optional[list[str]] = Field(default_factory=list)
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successCriteria: Optional[list[str]] = Field(default_factory=list)
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estimatedComplexity: Optional[str] = None
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userMessage: Optional[str] = Field(
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None, description="User-friendly message in user's language"
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)
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# Format details extracted from intent analysis
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dataType: Optional[str] = Field(
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None, description="Expected data type (text, numbers, documents, etc.)"
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)
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expectedFormats: Optional[List[str]] = Field(
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None, description="Expected output file format extensions (e.g., ['docx', 'pdf', 'xlsx']). Use actual file extensions, not conceptual terms."
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)
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qualityRequirements: Optional[Dict[str, Any]] = Field(
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None, description="Quality requirements and constraints"
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)
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```
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### Register Labels
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Update:
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```python
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"expectedFormats": {"en": "Expected Formats", "fr": "Formats attendus"}
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```
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---
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## 4. ChatWorkflow Class Changes (for Workflow-Level Tracking)
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**File:** `gateway/modules/datamodels/datamodelChat.py` (find ChatWorkflow class)
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### Add (if not exists)
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```python
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expectedFormats: Optional[List[str]] = Field(
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None,
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description="List of expected file format extensions from user request (e.g., ['xlsx', 'pdf']). Extracted during intent analysis."
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)
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```
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Note: `_workflowIntent` is already stored as a dict (not a model field), so `expectedFormats` can be extracted from there, but having it as an explicit field makes it easier to query.
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---
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## 5. ActionItem Class Review
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**File:** `gateway/modules/datamodels/datamodelChat.py` (lines 652-715)
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### Current Structure (ALL USED - KEEP):
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- ✅ `id: str` - Used for action identification
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- ✅ `execMethod: str` - Used for action execution
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- ✅ `execAction: str` - Used for action execution
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- ✅ `execParameters: Dict[str, Any]` - Used for action execution
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- ✅ `execResultLabel: Optional[str]` - Used for document routing
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- ✅ `expectedDocumentFormats: Optional[List[Dict[str, str]]]` - Used by action planning
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- ✅ `userMessage: Optional[str]` - Used for user communication
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- ✅ `status: TaskStatus` - Used for tracking
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- ✅ `error: Optional[str]` - Used for error handling
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- ✅ `retryCount: int` - Used for retry logic
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- ✅ `retryMax: int` - Used for retry logic
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- ✅ `processingTime: Optional[float]` - Used for performance tracking
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- ✅ `timestamp: float` - Used for ordering/auditing
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- ✅ `result: Optional[str]` - Used to store action result text
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**NO CHANGES NEEDED** - All attributes are used
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---
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## 6. Summary of Changes
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### Classes to Modify:
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1. ✅ **TaskStep** - Change `expectedFormat` (str) → `expectedFormats` (List[str])
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2. ✅ **ChatWorkflow** - Add `expectedFormats` (optional, for explicit tracking)
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### Classes to Review (NO CHANGES):
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- ✅ **ActionResult** - Keep as-is, documents already have metadata
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- ✅ **TaskResult** - Keep as-is, no summary needed
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- ✅ **ActionDocument** - Already correct (documentName, documentData, mimeType)
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- ✅ **ActionItem** - All attributes used
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- ✅ **Observation** - Already has contentValidation field
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- ✅ **TaskItem** - Used for database storage, separate from TaskStep
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---
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## 7. Implementation Impact
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### Files That Will Need Updates:
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1. **datamodelChat.py** - Class definitions (this proposal)
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- Change `expectedFormat` → `expectedFormats` in TaskStep
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- Add `expectedFormats` to ChatWorkflow (optional)
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2. **taskPlanner.py** - Populate `expectedFormats` list instead of single `expectedFormat`
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- **Adaptive planning:** Use ALL workflow data (messages, document metadata) to refine next task objective
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- Extract delivered formats from workflow documents
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- Compare what was delivered vs. what was planned
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3. **contentValidator.py** - Use `expectedFormats` list for validation
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- **Action-level validation:** Check action results against task objective (already exists)
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- **Task-level validation:** Validate THIS task's deliverables against THIS task's expectations
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- Uses document metadata (name, size, format, mimeType) - no summaries needed
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4. **intentAnalyzer.py** - Fix prompt to ask for actual file format extensions
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- Change from conceptual terms ("raw_data", "formatted") to actual extensions ("pdf", "docx", "xlsx")
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5. **promptGenerationTaskplan.py** - Ask for `expectedFormats` in task planning
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- **Adaptive planning:** Include ALL workflow data (messages, document names/sizes/formats/metadata) when planning next task
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- Show what was actually delivered to help refine objective
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6. **workflowManager.py** - Pass ALL workflow data to next task planning
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- Messages (text content)
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- Document metadata (names, sizes, formats, mimeTypes)
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- Validation results
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### Key Implementation Points:
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- **No summary fields:** Use existing document metadata (name, size, format, mimeType)
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- **Adaptive task planning:** Next task receives ALL workflow data (messages + document metadata) to refine objective
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- **Validation scope:** Task validation checks ONLY that task's actions, not all workflow actions
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- **After each action:** Validate against task objective → decide if complete or next action needed
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---
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## 8. Validation Logic Alignment
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### Action-Level Validation (Within Task):
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- **When:** After each action execution within a task
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- **Checks:** Action results against task objective
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- **Against:** Action documents (name, size, format, mimeType metadata)
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- **Purpose:** Decide if task is complete or next action needed
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- **Triggers:** Continue to next action if incomplete, complete task if done
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### Task Planning (Adaptive - Uses ALL Workflow Data):
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- **Input:** ALL workflow data available:
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- All messages (text content)
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- All document metadata (names, sizes, formats/extensions, mimeTypes)
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- Previous task validation results
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- **Process:**
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- Extract delivered formats from all workflow documents
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- Compare what was ACTUALLY delivered vs. what was PLANNED
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- Refine next task objective:
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- Deliver MORE if previous tasks delivered less than expected
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- Deliver LESS if previous tasks already delivered more
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- Adapt to actual workflow progress
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### Task-Level Validation (Task Completion):
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- **When:** After ALL actions in a task complete
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- **Checks:** Task objective, task `expectedFormats`, task `successCriteria`
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- **Against:** Documents from THIS task only (extract formats from document metadata)
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- **Purpose:** Verify THIS task delivered what was expected for THIS task scope
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- **Output:** Validation result (used in workflow data for next task planning)
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### Workflow-Level Validation (Final):
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- **When:** After ALL tasks complete
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- **Checks:** Original user request, workflow `expectedFormats`, workflow success criteria
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- **Against:** ALL documents from ALL tasks (extract formats from document metadata)
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- **Purpose:** Final verification that complete workflow delivered what user requested
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- **Triggers:** New compensatory task if validation fails (missing deliverables)
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---
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## 9. Next Steps
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1. **Review and approve this proposal**
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2. **Implement class changes** in datamodelChat.py
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3. **Update intent analyzer prompt** to request actual file format extensions
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4. **Update task planning prompt** to request `expectedFormats` list
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5. **Update AI generation prompts** to include summary instruction
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6. **Implement aggregation logic** for summaries at task/workflow levels
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7. **Implement workflow-level validation** method
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8. **Update all references** from `expectedFormat` to `expectedFormats`
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---
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## Questions Answered
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✅ **Document metadata:** Use existing document fields (name, size, format from mimeType/extensions) - no summaries needed
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✅ **Format extraction:** Extract formats from document metadata (mimeType or file extensions)
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✅ **Task validation scope:** Task validation checks ONLY actions in that task, not all workflow actions
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✅ **Adaptive planning:** Next task uses ALL workflow data (messages + document metadata) to refine objective
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✅ **After each action:** Validate against task objective → decide complete or next action needed
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---
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## 10. Validation Flow Clarification
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### Simplified Flow:
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1. **Within Task (Action-by-Action):**
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- Action executes → delivers documents with metadata
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- Validate action results against task objective
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- If incomplete → next action needed
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- If complete → task done
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2. **Task Planning (Adaptive):**
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- Receives: ALL workflow data (messages, document metadata from all previous tasks)
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- Extracts: Delivered formats from document metadata (file extensions/mimeTypes)
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- Compares: What was actually delivered vs. what was planned
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- Refines: Next task objective (may need more/less based on actual progress)
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3. **Task Completion:**
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- Validate: THIS task's documents (extract formats from metadata) against THIS task's expectations
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- Result: Used in workflow data for next task planning
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4. **Workflow Completion:**
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- Final validation: All documents (extract formats from metadata) meet original user request
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- If missing: Create compensatory task
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---
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**Status:** Ready for implementation after approval
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@ -417,6 +417,13 @@ class ChatWorkflow(BaseModel):
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frontend_readonly=False,
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frontend_required=False,
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)
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expectedFormats: Optional[List[str]] = Field(
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None,
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description="List of expected file format extensions from user request (e.g., ['xlsx', 'pdf']). Extracted during intent analysis.",
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frontend_type="text",
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frontend_readonly=True,
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frontend_required=False,
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)
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registerModelLabels(
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@ -440,6 +447,7 @@ registerModelLabels(
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"tasks": {"en": "Tasks", "fr": "Tâches"},
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"workflowMode": {"en": "Workflow Mode", "fr": "Mode de workflow"},
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"maxSteps": {"en": "Max Steps", "fr": "Étapes max"},
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"expectedFormats": {"en": "Expected Formats", "fr": "Formats attendus"},
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},
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)
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@ -800,8 +808,8 @@ class TaskStep(BaseModel):
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dataType: Optional[str] = Field(
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None, description="Expected data type (text, numbers, documents, etc.)"
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)
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expectedFormat: Optional[str] = Field(
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None, description="Expected output format (json, csv, markdown, etc.)"
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expectedFormats: Optional[List[str]] = Field(
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None, description="Expected output file format extensions (e.g., ['docx', 'pdf', 'xlsx']). Use actual file extensions, not conceptual terms."
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)
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qualityRequirements: Optional[Dict[str, Any]] = Field(
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None, description="Quality requirements and constraints"
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@ -821,6 +829,7 @@ registerModelLabels(
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"fr": "Complexité estimée",
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},
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"userMessage": {"en": "User Message", "fr": "Message utilisateur"},
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"expectedFormats": {"en": "Expected Formats", "fr": "Formats attendus"},
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},
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)
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@ -263,22 +263,22 @@ class ContentValidator:
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# Use taskStep format fields if available, otherwise fall back to intent
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dataType = None
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expectedFormat = None
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expectedFormats = None
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if taskStep:
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if hasattr(taskStep, 'dataType') and taskStep.dataType:
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dataType = taskStep.dataType
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elif isinstance(taskStep, dict):
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dataType = taskStep.get('dataType')
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if hasattr(taskStep, 'expectedFormat') and taskStep.expectedFormat:
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expectedFormat = taskStep.expectedFormat
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if hasattr(taskStep, 'expectedFormats') and taskStep.expectedFormats:
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expectedFormats = taskStep.expectedFormats
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elif isinstance(taskStep, dict):
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expectedFormat = taskStep.get('expectedFormat')
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expectedFormats = taskStep.get('expectedFormats')
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# Fallback to intent if taskStep format fields not available
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if not dataType:
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dataType = intent.get('dataType', 'unknown')
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if not expectedFormat:
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expectedFormat = intent.get('expectedFormat', 'unknown')
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if not expectedFormats:
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expectedFormats = intent.get('expectedFormats', [])
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# Determine objective text and label
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objectiveText = taskObjective if taskObjective else intent.get('primaryGoal', 'Unknown')
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@ -299,7 +299,7 @@ class ContentValidator:
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{objectiveLabel}: '{objectiveText}'
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EXPECTED DATA TYPE: {dataType}
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EXPECTED FORMAT: {expectedFormat}
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EXPECTED FORMATS: {expectedFormats if expectedFormats else ['any']}
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SUCCESS CRITERIA ({criteriaCount} items): {successCriteria}
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VALIDATION RULES:
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@ -50,8 +50,10 @@ You are an intent analyzer. Analyze the user's request to understand what they w
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Analyze the user's intent and determine:
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1. What type of data/content they want (numbers, text, documents, analysis, code, etc.)
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2. What format they expect (raw data, formatted, structured, visual, etc.)
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3. What quality requirements they have (accuracy, completeness, format)
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2. What file format(s) they expect - provide matching file format extensions list
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- If multiple formats requested, list all of them (e.g., ["xlsx", "pdf"])
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- If format is unclear or not specified, use empty list []
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3. What quality requirements they have (accuracy, completeness)
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4. What specific success criteria define completion
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5. What language the user is communicating in (detect from the user request)
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@ -60,11 +62,10 @@ CRITICAL: Respond with ONLY the JSON object below. Do not include any explanator
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{{
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"primaryGoal": "The main objective the user wants to achieve",
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"dataType": "numbers|text|documents|analysis|code|unknown",
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"expectedFormat": "raw_data|formatted|structured|visual|unknown",
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"expectedFormats": ["pdf", "docx", "xlsx", "txt", "json", "csv", "html", "md"],
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"qualityRequirements": {{
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"accuracyThreshold": 0.0-1.0,
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"completenessThreshold": 0.0-1.0,
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"formatRequirement": "any|formatted|raw|structured"
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"completenessThreshold": 0.0-1.0
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}},
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"successCriteria": ["specific criterion 1", "specific criterion 2"],
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"languageUserDetected": "en",
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@ -116,53 +116,56 @@ class LearningEngine:
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def _getStrategyKey(self, intent: Dict[str, Any]) -> str:
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"""Gets strategy key based on intent"""
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dataType = intent.get('dataType', 'unknown')
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expectedFormat = intent.get('expectedFormat', 'unknown')
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return f"{dataType}_{expectedFormat}"
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expectedFormats = intent.get('expectedFormats', [])
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formatKey = '_'.join(expectedFormats) if expectedFormats else 'unknown'
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return f"{dataType}_{formatKey}"
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def _createDefaultStrategy(self, intent: Dict[str, Any]) -> Dict[str, Any]:
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"""Creates a default strategy for the intent"""
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dataType = intent.get('dataType', 'unknown')
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expectedFormat = intent.get('expectedFormat', 'unknown')
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expectedFormats = intent.get('expectedFormats', [])
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formatStr = ', '.join(expectedFormats) if expectedFormats else 'any'
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formatKey = '_'.join(expectedFormats) if expectedFormats else 'unknown'
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# Create strategy based on intent type
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if dataType == 'numbers':
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return {
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'strategyId': f"numbers_{expectedFormat}",
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'strategyId': f"numbers_{formatKey}",
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'successfulActions': [],
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'failedActions': [],
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'successRate': 0.5,
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'lastModified': datetime.now(timezone.utc).timestamp(),
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'recommendedPrompt': f"Deliver {dataType} data in {expectedFormat} format. Provide actual numbers, not code to generate them.",
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'recommendedPrompt': f"Deliver {dataType} data in {formatStr} format. Provide actual numbers, not code to generate them.",
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'avoidPrompt': "Do not ask AI to write code when user wants data. Deliver the data directly."
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}
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elif dataType == 'text':
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return {
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'strategyId': f"text_{expectedFormat}",
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'strategyId': f"text_{formatKey}",
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||||
'successfulActions': [],
|
||||
'failedActions': [],
|
||||
'successRate': 0.5,
|
||||
'lastModified': datetime.now(timezone.utc).timestamp(),
|
||||
'recommendedPrompt': f"Generate {dataType} content in {expectedFormat} format.",
|
||||
'recommendedPrompt': f"Generate {dataType} content in {formatStr} format.",
|
||||
'avoidPrompt': "Ensure content is readable and well-structured."
|
||||
}
|
||||
elif dataType == 'documents':
|
||||
return {
|
||||
'strategyId': f"documents_{expectedFormat}",
|
||||
'strategyId': f"documents_{formatKey}",
|
||||
'successfulActions': [],
|
||||
'failedActions': [],
|
||||
'successRate': 0.5,
|
||||
'lastModified': datetime.now(timezone.utc).timestamp(),
|
||||
'recommendedPrompt': f"Create {dataType} in {expectedFormat} format with proper structure.",
|
||||
'recommendedPrompt': f"Create {dataType} in {formatStr} format with proper structure.",
|
||||
'avoidPrompt': "Ensure document is properly formatted and organized."
|
||||
}
|
||||
else:
|
||||
return {
|
||||
'strategyId': f"unknown_{expectedFormat}",
|
||||
'strategyId': f"unknown_{formatKey}",
|
||||
'successfulActions': [],
|
||||
'failedActions': [],
|
||||
'successRate': 0.5,
|
||||
'lastModified': datetime.now(timezone.utc).timestamp(),
|
||||
'recommendedPrompt': f"Deliver {dataType} content in {expectedFormat} format.",
|
||||
'recommendedPrompt': f"Deliver {dataType} content in {formatStr} format.",
|
||||
'avoidPrompt': "Ensure content matches user requirements."
|
||||
}
|
||||
|
||||
|
|
|
|||
|
|
@ -163,8 +163,8 @@ class TaskPlanner:
|
|||
if isinstance(workflowIntent, dict):
|
||||
if 'dataType' in workflowIntent and 'dataType' not in taskDict:
|
||||
taskDict['dataType'] = workflowIntent.get('dataType')
|
||||
if 'expectedFormat' in workflowIntent and 'expectedFormat' not in taskDict:
|
||||
taskDict['expectedFormat'] = workflowIntent.get('expectedFormat')
|
||||
if 'expectedFormats' in workflowIntent and 'expectedFormats' not in taskDict:
|
||||
taskDict['expectedFormats'] = workflowIntent.get('expectedFormats')
|
||||
if 'qualityRequirements' in workflowIntent and 'qualityRequirements' not in taskDict:
|
||||
taskDict['qualityRequirements'] = workflowIntent.get('qualityRequirements')
|
||||
|
||||
|
|
|
|||
|
|
@ -242,12 +242,12 @@ class ActionplanMode(BaseMode):
|
|||
self.workflowIntent = await self.intentAnalyzer.analyzeUserIntent(originalPrompt, context)
|
||||
logger.warning(f"Workflow intent not found in workflow object, analyzed fresh")
|
||||
|
||||
# Task-level intent is NOT needed - use task.objective + task format fields (dataType, expectedFormat, qualityRequirements)
|
||||
# Task-level intent is NOT needed - use task.objective + task format fields (dataType, expectedFormats, qualityRequirements)
|
||||
# These format fields are populated from workflow intent during task planning
|
||||
self.taskIntent = None # Removed redundant task-level intent analysis
|
||||
logger.info(f"Workflow intent: {self.workflowIntent}")
|
||||
if taskStep.dataType or taskStep.expectedFormat or taskStep.qualityRequirements:
|
||||
logger.info(f"Task format info: dataType={taskStep.dataType}, expectedFormat={taskStep.expectedFormat}")
|
||||
if taskStep.dataType or taskStep.expectedFormats or taskStep.qualityRequirements:
|
||||
logger.info(f"Task format info: dataType={taskStep.dataType}, expectedFormats={taskStep.expectedFormats}")
|
||||
|
||||
# Reset progress tracking for new task
|
||||
self.progressTracker.reset()
|
||||
|
|
|
|||
|
|
@ -61,12 +61,12 @@ class DynamicMode(BaseMode):
|
|||
self.workflowIntent = await self.intentAnalyzer.analyzeUserIntent(original_prompt, context)
|
||||
logger.warning(f"Workflow intent not found in workflow object, analyzed fresh")
|
||||
|
||||
# Task-level intent is NOT needed - use task.objective + task format fields (dataType, expectedFormat, qualityRequirements)
|
||||
# Task-level intent is NOT needed - use task.objective + task format fields (dataType, expectedFormats, qualityRequirements)
|
||||
# These format fields are populated from workflow intent during task planning
|
||||
self.taskIntent = None # Removed redundant task-level intent analysis
|
||||
logger.info(f"Workflow intent: {self.workflowIntent}")
|
||||
if taskStep.dataType or taskStep.expectedFormat or taskStep.qualityRequirements:
|
||||
logger.info(f"Task format info: dataType={taskStep.dataType}, expectedFormat={taskStep.expectedFormat}")
|
||||
if taskStep.dataType or taskStep.expectedFormats or taskStep.qualityRequirements:
|
||||
logger.info(f"Task format info: dataType={taskStep.dataType}, expectedFormats={taskStep.expectedFormats}")
|
||||
|
||||
# NEW: Reset progress tracking for new task
|
||||
self.progressTracker.reset()
|
||||
|
|
|
|||
|
|
@ -82,7 +82,8 @@ Break down user requests into logical, executable task steps.
|
|||
"dependencies": ["task_0"],
|
||||
"successCriteria": ["measurable criteria 1", "measurable criteria 2"],
|
||||
"estimatedComplexity": "low|medium|high",
|
||||
"userMessage": "What this task will accomplish in language '{{KEY:USER_LANGUAGE}}'"
|
||||
"userMessage": "What this task will accomplish in language '{{KEY:USER_LANGUAGE}}'",
|
||||
"expectedFormats": ["pdf", "docx", "xlsx", "txt", "json", "csv", "html", "md",...]
|
||||
}}
|
||||
],
|
||||
}}
|
||||
|
|
|
|||
Loading…
Reference in a new issue