refactor: Remove TEXT fields and use only reasoning_data for i18n
Completed the migration to structured reasoning_data for multilingual
dashboard support. Removed hardcoded TEXT fields (reasoning, consequence)
and updated all related code to use JSONB reasoning_data.
Changes:
1. Models Updated (removed TEXT fields):
- PurchaseOrder: Removed reasoning, consequence TEXT columns
- ProductionBatch: Removed reasoning TEXT column
- Both now use only reasoning_data (JSONB/JSON)
2. Dashboard Service Updated:
- Changed to return reasoning_data instead of TEXT fields
- Creates default reasoning_data if missing
- PO actions: reasoning_data with type and parameters
- Production timeline: reasoning_data for each batch
3. Unified Schemas Updated (no separate migration):
- services/procurement/migrations/001_unified_initial_schema.py
- services/production/migrations/001_unified_initial_schema.py
- Removed reasoning/consequence columns from table definitions
- Updated comments to reflect i18n approach
Database Schema:
- purchase_orders: Only reasoning_data (JSONB)
- production_batches: Only reasoning_data (JSON)
Backend now generates:
{
"type": "low_stock_detection",
"parameters": {
"supplier_name": "Harinas del Norte",
"days_until_stockout": 3,
...
},
"consequence": {
"type": "stockout_risk",
"severity": "high"
}
}
Next Steps:
- Frontend: Create i18n translation keys
- Frontend: Update components to translate reasoning_data
- Test multilingual support (ES, EN, CA)
This commit is contained in:
@@ -367,14 +367,23 @@ class DashboardService:
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# Calculate urgency based on required delivery date
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urgency = self._calculate_po_urgency(po)
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# Get reasoning_data or create default
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reasoning_data = po.get("reasoning_data") or {
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"type": "low_stock_detection",
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"parameters": {
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"supplier_name": po.get('supplier_name', 'Unknown'),
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"product_names": ["Items"],
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"days_until_stockout": 7
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}
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}
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actions.append({
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"id": po["id"],
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"type": ActionType.APPROVE_PO,
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"urgency": urgency,
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"title": f"Purchase Order {po.get('po_number', 'N/A')}",
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"subtitle": f"Supplier: {po.get('supplier_name', 'Unknown')}",
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"reasoning": po.get("reasoning") or "Low stock levels detected",
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"consequence": po.get("consequence") or "Order needed to maintain inventory levels",
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"reasoning_data": reasoning_data, # NEW: Structured data for i18n
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"amount": po.get("total_amount", 0),
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"currency": po.get("currency", "EUR"),
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"actions": [
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@@ -490,6 +499,16 @@ class DashboardService:
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status_icon = "⏰"
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status_text = "PENDING"
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# Get reasoning_data or create default
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reasoning_data = batch.get("reasoning_data") or {
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"type": "forecast_demand",
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"parameters": {
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"product_name": batch.get("product_name", "Product"),
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"predicted_demand": batch.get("planned_quantity", 0),
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"confidence_score": 85
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}
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}
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timeline.append({
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"id": batch["id"],
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"batchNumber": batch.get("batch_number"),
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@@ -505,7 +524,7 @@ class DashboardService:
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"progress": progress,
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"readyBy": planned_end.isoformat() if planned_end else None,
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"priority": batch.get("priority", "MEDIUM"),
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"reasoning": batch.get("reasoning") or "Based on demand forecast"
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"reasoning_data": reasoning_data # NEW: Structured data for i18n
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})
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# Sort by planned start time
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@@ -119,17 +119,30 @@ class PurchaseOrder(Base):
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internal_notes = Column(Text, nullable=True) # Not shared with supplier
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terms_and_conditions = Column(Text, nullable=True)
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# JTBD Dashboard: Reasoning and consequences for user transparency
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# Deferred loading to prevent breaking queries when columns don't exist yet
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reasoning = deferred(Column(Text, nullable=True)) # Why this PO was created (e.g., "Low flour stock (2 days left)")
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consequence = deferred(Column(Text, nullable=True)) # What happens if not approved (e.g., "Stock out risk in 48 hours")
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reasoning_data = deferred(Column(JSONB, nullable=True)) # Structured reasoning data
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# reasoning_data structure: {
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# "trigger": "low_stock" | "forecast_demand" | "manual",
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# "ingredients_affected": [{"id": "uuid", "name": "Flour", "current_stock": 10, "days_remaining": 2}],
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# "orders_impacted": [{"id": "uuid", "product": "Baguette", "quantity": 100}],
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# "urgency_score": 0-100,
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# "estimated_stock_out_date": "2025-11-10T00:00:00Z"
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# JTBD Dashboard: Structured reasoning data for i18n support
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# Backend stores structured data, frontend translates using i18n
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reasoning_data = Column(JSONB, nullable=True) # Structured reasoning data for multilingual support
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# reasoning_data structure (see shared/schemas/reasoning_types.py):
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# {
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# "type": "low_stock_detection" | "forecast_demand" | "safety_stock_replenishment" | etc.,
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# "parameters": {
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# "supplier_name": "Harinas del Norte",
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# "product_names": ["Flour Type 55", "Flour Type 45"],
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# "days_until_stockout": 3,
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# "current_stock": 45.5,
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# "required_stock": 200
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# },
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# "consequence": {
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# "type": "stockout_risk",
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# "severity": "high",
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# "impact_days": 3,
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# "affected_products": ["Baguette", "Croissant"]
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# },
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# "metadata": {
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# "trigger_source": "orchestrator_auto",
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# "forecast_confidence": 0.85,
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# "ai_assisted": true
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# }
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# }
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# Audit fields
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@@ -6,7 +6,7 @@ Create Date: 2025-11-07
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Complete procurement service schema including:
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- Procurement plans and requirements
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- Purchase orders and items (with reasoning fields for JTBD dashboard)
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- Purchase orders and items (with reasoning_data for i18n JTBD dashboard)
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- Deliveries and delivery items
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- Supplier invoices
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- Replenishment planning
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@@ -207,7 +207,7 @@ def upgrade() -> None:
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# PURCHASE ORDER TABLES
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# ========================================================================
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# Create purchase_orders table (with JTBD dashboard reasoning fields)
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# Create purchase_orders table (with reasoning_data for i18n)
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op.create_table('purchase_orders',
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sa.Column('id', postgresql.UUID(as_uuid=True), nullable=False),
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sa.Column('tenant_id', postgresql.UUID(as_uuid=True), nullable=False),
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@@ -242,9 +242,7 @@ def upgrade() -> None:
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sa.Column('notes', sa.Text(), nullable=True),
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sa.Column('internal_notes', sa.Text(), nullable=True),
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sa.Column('terms_and_conditions', sa.Text(), nullable=True),
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# JTBD Dashboard fields
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sa.Column('reasoning', sa.Text(), nullable=True),
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sa.Column('consequence', sa.Text(), nullable=True),
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# JTBD Dashboard: Structured reasoning for i18n support
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sa.Column('reasoning_data', postgresql.JSONB(astext_type=sa.Text()), nullable=True),
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sa.Column('created_at', sa.DateTime(timezone=True), server_default=sa.text('now()'), nullable=False),
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sa.Column('updated_at', sa.DateTime(timezone=True), server_default=sa.text('now()'), onupdate=sa.text('now()'), nullable=False),
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@@ -133,16 +133,29 @@ class ProductionBatch(Base):
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delay_reason = Column(String(255), nullable=True)
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cancellation_reason = Column(String(255), nullable=True)
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# JTBD Dashboard: Reasoning and context for user transparency
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# Deferred loading to prevent breaking queries when columns don't exist yet
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reasoning = deferred(Column(Text, nullable=True)) # Why this batch was scheduled (e.g., "Based on wedding order #1234")
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reasoning_data = deferred(Column(JSON, nullable=True)) # Structured reasoning data
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# reasoning_data structure: {
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# "trigger": "forecast" | "order" | "inventory" | "manual",
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# "forecast_id": "uuid",
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# "orders_fulfilled": [{"id": "uuid", "customer": "Maria's Bakery", "quantity": 100}],
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# "demand_score": 0-100,
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# "scheduling_priority_reason": "High demand + VIP customer"
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# JTBD Dashboard: Structured reasoning data for i18n support
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# Backend stores structured data, frontend translates using i18n
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reasoning_data = Column(JSON, nullable=True) # Structured reasoning data for multilingual support
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# reasoning_data structure (see shared/schemas/reasoning_types.py):
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# {
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# "type": "forecast_demand" | "customer_order" | "stock_replenishment" | etc.,
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# "parameters": {
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# "product_name": "Croissant",
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# "predicted_demand": 500,
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# "current_stock": 120,
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# "production_needed": 380,
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# "confidence_score": 87
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# },
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# "urgency": {
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# "level": "normal",
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# "ready_by_time": "08:00",
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# "customer_commitment": false
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# },
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# "metadata": {
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# "trigger_source": "orchestrator_auto",
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# "forecast_id": "uuid-here",
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# "ai_assisted": true
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# }
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# }
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# Timestamps
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@@ -191,7 +204,6 @@ class ProductionBatch(Base):
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"quality_notes": self.quality_notes,
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"delay_reason": self.delay_reason,
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"cancellation_reason": self.cancellation_reason,
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"reasoning": self.reasoning,
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"reasoning_data": self.reasoning_data,
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"created_at": self.created_at.isoformat() if self.created_at else None,
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"updated_at": self.updated_at.isoformat() if self.updated_at else None,
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@@ -5,7 +5,7 @@ Revises:
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Create Date: 2025-11-07
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Complete production service schema including:
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- Production batches (with reasoning fields for JTBD dashboard and waste tracking)
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- Production batches (with reasoning_data for i18n JTBD dashboard and waste tracking)
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- Production schedules
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- Production capacity
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- Equipment
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@@ -90,7 +90,7 @@ def upgrade() -> None:
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)
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op.create_index(op.f('ix_equipment_tenant_id'), 'equipment', ['tenant_id'], unique=False)
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# Create production_batches table (with all fields including reasoning and waste tracking)
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# Create production_batches table (with reasoning_data for i18n and waste tracking)
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op.create_table('production_batches',
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sa.Column('id', sa.UUID(), nullable=False),
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sa.Column('tenant_id', sa.UUID(), nullable=False),
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@@ -135,8 +135,7 @@ def upgrade() -> None:
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sa.Column('quality_notes', sa.Text(), nullable=True),
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sa.Column('delay_reason', sa.String(length=255), nullable=True),
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sa.Column('cancellation_reason', sa.String(length=255), nullable=True),
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# JTBD Dashboard fields (from 20251107 migration)
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sa.Column('reasoning', sa.Text(), nullable=True),
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# JTBD Dashboard: Structured reasoning for i18n support
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sa.Column('reasoning_data', sa.JSON(), nullable=True),
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sa.Column('created_at', sa.DateTime(timezone=True), server_default=sa.text('now()'), nullable=True),
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sa.Column('updated_at', sa.DateTime(timezone=True), server_default=sa.text('now()'), nullable=True),
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