Improve the frontend 3
This commit is contained in:
Urtzi Alfaro
@@ -231,31 +231,40 @@ async def clone_demo_data(
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base_tenant=str(base_uuid)
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)
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# Calculate date offset to make production recent
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if base_batches:
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max_date = max(batch.planned_start_time for batch in base_batches if batch.planned_start_time)
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today = datetime.now(timezone.utc)
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date_offset = today - max_date
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else:
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date_offset = timedelta(days=0)
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for batch in base_batches:
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new_batch_id = uuid.uuid4()
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batch_id_map[batch.id] = new_batch_id
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# Adjust dates relative to session creation time
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adjusted_planned_start = adjust_date_for_demo(
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batch.planned_start_time, session_time, BASE_REFERENCE_DATE
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) if batch.planned_start_time else None
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adjusted_planned_end = adjust_date_for_demo(
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batch.planned_end_time, session_time, BASE_REFERENCE_DATE
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) if batch.planned_end_time else None
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adjusted_actual_start = adjust_date_for_demo(
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batch.actual_start_time, session_time, BASE_REFERENCE_DATE
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) if batch.actual_start_time else None
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adjusted_actual_end = adjust_date_for_demo(
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batch.actual_end_time, session_time, BASE_REFERENCE_DATE
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) if batch.actual_end_time else None
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adjusted_completed = adjust_date_for_demo(
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batch.completed_at, session_time, BASE_REFERENCE_DATE
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) if batch.completed_at else None
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new_batch = ProductionBatch(
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id=new_batch_id,
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tenant_id=virtual_uuid,
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batch_number=f"BATCH-{uuid.uuid4().hex[:8].upper()}", # New batch number
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product_id=batch.product_id, # Keep product reference
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product_id=batch.product_id, # Keep product reference
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product_name=batch.product_name,
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recipe_id=batch.recipe_id, # Keep recipe reference
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planned_start_time=batch.planned_start_time + date_offset if batch.planned_start_time else None,
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planned_end_time=batch.planned_end_time + date_offset if batch.planned_end_time else None,
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planned_start_time=adjusted_planned_start,
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planned_end_time=adjusted_planned_end,
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planned_quantity=batch.planned_quantity,
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planned_duration_minutes=batch.planned_duration_minutes,
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actual_start_time=batch.actual_start_time + date_offset if batch.actual_start_time else None,
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actual_end_time=batch.actual_end_time + date_offset if batch.actual_end_time else None,
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actual_start_time=adjusted_actual_start,
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actual_end_time=adjusted_actual_end,
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actual_quantity=batch.actual_quantity,
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actual_duration_minutes=batch.actual_duration_minutes,
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status=batch.status,
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@@ -284,9 +293,9 @@ async def clone_demo_data(
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quality_notes=batch.quality_notes,
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delay_reason=batch.delay_reason,
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cancellation_reason=batch.cancellation_reason,
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created_at=datetime.now(timezone.utc),
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updated_at=datetime.now(timezone.utc),
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completed_at=batch.completed_at + date_offset if batch.completed_at else None
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created_at=session_time,
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updated_at=session_time,
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completed_at=adjusted_completed
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)
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db.add(new_batch)
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stats["production_batches"] += 1
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@@ -310,6 +319,11 @@ async def clone_demo_data(
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new_batch_id = batch_id_map.get(check.batch_id, check.batch_id)
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new_template_id = template_id_map.get(check.template_id, check.template_id) if check.template_id else None
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# Adjust check time relative to session creation time
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adjusted_check_time = adjust_date_for_demo(
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check.check_time, session_time, BASE_REFERENCE_DATE
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) if check.check_time else None
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new_check = QualityCheck(
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id=uuid.uuid4(),
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tenant_id=virtual_uuid,
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@@ -317,7 +331,7 @@ async def clone_demo_data(
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template_id=new_template_id,
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check_type=check.check_type,
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process_stage=check.process_stage,
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check_time=check.check_time + date_offset,
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check_time=adjusted_check_time,
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checker_id=check.checker_id,
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quality_score=check.quality_score,
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pass_fail=check.pass_fail,
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@@ -340,8 +354,8 @@ async def clone_demo_data(
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check_notes=check.check_notes,
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photos_urls=check.photos_urls,
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certificate_url=check.certificate_url,
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created_at=datetime.now(timezone.utc),
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updated_at=datetime.now(timezone.utc)
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created_at=session_time,
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updated_at=session_time
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)
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db.add(new_check)
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stats["quality_checks"] += 1
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@@ -359,12 +373,26 @@ async def clone_demo_data(
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)
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for schedule in base_schedules:
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# Adjust schedule dates relative to session creation time
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adjusted_schedule_date = adjust_date_for_demo(
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schedule.schedule_date, session_time, BASE_REFERENCE_DATE
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) if schedule.schedule_date else None
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adjusted_shift_start = adjust_date_for_demo(
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schedule.shift_start, session_time, BASE_REFERENCE_DATE
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) if schedule.shift_start else None
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adjusted_shift_end = adjust_date_for_demo(
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schedule.shift_end, session_time, BASE_REFERENCE_DATE
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) if schedule.shift_end else None
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adjusted_finalized = adjust_date_for_demo(
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schedule.finalized_at, session_time, BASE_REFERENCE_DATE
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) if schedule.finalized_at else None
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new_schedule = ProductionSchedule(
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id=uuid.uuid4(),
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tenant_id=virtual_uuid,
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schedule_date=schedule.schedule_date + date_offset,
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shift_start=schedule.shift_start + date_offset,
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shift_end=schedule.shift_end + date_offset,
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schedule_date=adjusted_schedule_date,
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shift_start=adjusted_shift_start,
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shift_end=adjusted_shift_end,
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total_capacity_hours=schedule.total_capacity_hours,
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planned_capacity_hours=schedule.planned_capacity_hours,
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actual_capacity_hours=schedule.actual_capacity_hours,
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@@ -383,9 +411,9 @@ async def clone_demo_data(
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on_time_completion_rate=schedule.on_time_completion_rate,
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schedule_notes=schedule.schedule_notes,
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schedule_adjustments=schedule.schedule_adjustments,
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created_at=datetime.now(timezone.utc),
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updated_at=datetime.now(timezone.utc),
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finalized_at=schedule.finalized_at + date_offset if schedule.finalized_at else None
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created_at=session_time,
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updated_at=session_time,
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finalized_at=adjusted_finalized
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)
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db.add(new_schedule)
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stats["production_schedules"] += 1
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@@ -397,15 +425,29 @@ async def clone_demo_data(
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base_capacity = result.scalars().all()
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for capacity in base_capacity:
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# Adjust capacity dates relative to session creation time
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adjusted_date = adjust_date_for_demo(
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capacity.date, session_time, BASE_REFERENCE_DATE
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) if capacity.date else None
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adjusted_start_time = adjust_date_for_demo(
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capacity.start_time, session_time, BASE_REFERENCE_DATE
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) if capacity.start_time else None
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adjusted_end_time = adjust_date_for_demo(
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capacity.end_time, session_time, BASE_REFERENCE_DATE
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) if capacity.end_time else None
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adjusted_last_maintenance = adjust_date_for_demo(
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capacity.last_maintenance_date, session_time, BASE_REFERENCE_DATE
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) if capacity.last_maintenance_date else None
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new_capacity = ProductionCapacity(
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id=uuid.uuid4(),
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tenant_id=virtual_uuid,
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resource_type=capacity.resource_type,
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resource_id=capacity.resource_id,
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resource_name=capacity.resource_name,
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date=capacity.date + date_offset,
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start_time=capacity.start_time + date_offset,
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end_time=capacity.end_time + date_offset,
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date=adjusted_date,
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start_time=adjusted_start_time,
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end_time=adjusted_end_time,
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total_capacity_units=capacity.total_capacity_units,
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allocated_capacity_units=capacity.allocated_capacity_units,
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remaining_capacity_units=capacity.remaining_capacity_units,
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@@ -419,11 +461,11 @@ async def clone_demo_data(
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cleanup_time_minutes=capacity.cleanup_time_minutes,
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efficiency_rating=capacity.efficiency_rating,
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maintenance_status=capacity.maintenance_status,
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last_maintenance_date=capacity.last_maintenance_date + date_offset if capacity.last_maintenance_date else None,
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last_maintenance_date=adjusted_last_maintenance,
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notes=capacity.notes,
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restrictions=capacity.restrictions,
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created_at=datetime.now(timezone.utc),
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updated_at=datetime.now(timezone.utc)
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created_at=session_time,
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updated_at=session_time
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)
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db.add(new_capacity)
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stats["production_capacity"] += 1
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@@ -437,8 +479,8 @@ async def clone_demo_data(
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stats["alerts_generated"] = 0
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# Calculate total from non-alert stats
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total_records = (stats["equipment"] + stats["batches"] + stats["schedules"] +
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stats["quality_templates"] + stats["quality_checks"] +
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total_records = (stats["equipment"] + stats["production_batches"] + stats["production_schedules"] +
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stats["quality_check_templates"] + stats["quality_checks"] +
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stats["production_capacity"])
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duration_ms = int((datetime.now(timezone.utc) - start_time).total_seconds() * 1000)
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240
services/production/app/api/orchestrator.py
Normal file
240
services/production/app/api/orchestrator.py
Normal file
@@ -0,0 +1,240 @@
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# ================================================================
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# services/production/app/api/orchestrator.py
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# ================================================================
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"""
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Production Orchestrator API - Endpoints for orchestrated production scheduling
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Called by the Orchestrator Service to generate production schedules from forecast data
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"""
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from fastapi import APIRouter, Depends, HTTPException, Path
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from typing import Optional, Dict, Any, List
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from datetime import date
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from uuid import UUID
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from pydantic import BaseModel, Field
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import structlog
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from shared.routing import RouteBuilder
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from app.services.production_service import ProductionService
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from app.schemas.production import ProductionScheduleResponse
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from app.core.config import settings
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logger = structlog.get_logger()
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route_builder = RouteBuilder('production')
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router = APIRouter(tags=["production-orchestrator"])
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def get_production_service() -> ProductionService:
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"""Dependency injection for production service"""
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from app.core.database import database_manager
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return ProductionService(database_manager, settings)
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# ================================================================
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# REQUEST/RESPONSE SCHEMAS
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# ================================================================
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class GenerateScheduleRequest(BaseModel):
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"""
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Request to generate production schedule (called by Orchestrator)
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The Orchestrator calls Forecasting Service first, then passes forecast data here.
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Production Service uses this data to determine what to produce.
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NEW: Accepts cached data snapshots from Orchestrator to eliminate duplicate API calls.
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"""
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forecast_data: Dict[str, Any] = Field(..., description="Forecast data from Forecasting Service")
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target_date: Optional[date] = Field(None, description="Target production date")
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planning_horizon_days: int = Field(default=1, ge=1, le=7, description="Planning horizon in days")
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# NEW: Cached data from Orchestrator
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inventory_data: Optional[Dict[str, Any]] = Field(None, description="Cached inventory snapshot from Orchestrator")
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recipes_data: Optional[Dict[str, Any]] = Field(None, description="Cached recipes snapshot from Orchestrator")
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class Config:
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json_schema_extra = {
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"example": {
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"forecast_data": {
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"forecasts": [
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{
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"product_id": "uuid-here",
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"predicted_demand": 100.0,
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"confidence_score": 0.85
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}
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],
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"forecast_id": "uuid-here",
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"generated_at": "2025-01-30T10:00:00Z"
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},
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"target_date": "2025-01-31",
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"planning_horizon_days": 1
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}
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}
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class GenerateScheduleResponse(BaseModel):
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"""Response from generate_schedule endpoint"""
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success: bool
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message: str
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schedule_id: Optional[UUID] = None
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schedule_number: Optional[str] = None
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batches_created: int = 0
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total_planned_quantity: float = 0.0
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warnings: List[str] = []
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errors: List[str] = []
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class Config:
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json_schema_extra = {
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"example": {
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"success": True,
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"message": "Production schedule generated successfully",
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"schedule_id": "uuid-here",
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"schedule_number": "PROD-2025-01-30-001",
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"batches_created": 5,
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"total_planned_quantity": 500.0,
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"warnings": [],
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"errors": []
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}
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}
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# ================================================================
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# ORCHESTRATOR ENTRY POINT
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# ================================================================
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@router.post(
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route_builder.build_nested_resource_route("", None, "generate-schedule"),
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response_model=GenerateScheduleResponse
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)
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async def generate_production_schedule(
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tenant_id: UUID = Path(...),
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request_data: GenerateScheduleRequest = ...,
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production_service: ProductionService = Depends(get_production_service)
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):
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"""
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Generate production schedule from forecast data (called by Orchestrator)
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This is the main entry point for orchestrated production planning.
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The Orchestrator calls Forecasting Service first, then passes forecast data here.
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Flow:
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1. Receive forecast data from orchestrator
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2. Parse forecast to extract product demands
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3. Check inventory levels for each product
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4. Calculate production quantities needed
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5. Create production schedule and batches
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6. Return schedule summary
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Args:
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tenant_id: Tenant UUID
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request_data: Schedule generation request with forecast data
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Returns:
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GenerateScheduleResponse with schedule details and created batches
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"""
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try:
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logger.info("Generate production schedule endpoint called",
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tenant_id=str(tenant_id),
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has_forecast_data=bool(request_data.forecast_data))
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target_date = request_data.target_date or date.today()
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forecast_data = request_data.forecast_data
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# Parse forecast data from orchestrator
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forecasts = _parse_forecast_data(forecast_data)
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if not forecasts:
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return GenerateScheduleResponse(
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success=False,
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message="No forecast data provided",
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errors=["Forecast data is empty or invalid"]
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)
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# Generate production schedule using the service (with cached data if available)
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result = await production_service.generate_production_schedule_from_forecast(
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tenant_id=tenant_id,
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target_date=target_date,
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forecasts=forecasts,
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planning_horizon_days=request_data.planning_horizon_days,
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inventory_data=request_data.inventory_data, # NEW: Pass cached inventory
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recipes_data=request_data.recipes_data # NEW: Pass cached recipes
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)
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logger.info("Production schedule generated successfully",
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tenant_id=str(tenant_id),
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schedule_id=str(result.get('schedule_id')) if result.get('schedule_id') else None,
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batches_created=result.get('batches_created', 0))
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return GenerateScheduleResponse(
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success=True,
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message="Production schedule generated successfully",
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schedule_id=result.get('schedule_id'),
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schedule_number=result.get('schedule_number'),
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batches_created=result.get('batches_created', 0),
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total_planned_quantity=result.get('total_planned_quantity', 0.0),
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warnings=result.get('warnings', []),
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errors=[]
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)
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except Exception as e:
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logger.error("Error generating production schedule",
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error=str(e), tenant_id=str(tenant_id))
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return GenerateScheduleResponse(
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success=False,
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message="Failed to generate production schedule",
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errors=[str(e)]
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)
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# ================================================================
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# HELPER FUNCTIONS
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# ================================================================
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def _parse_forecast_data(forecast_data: Dict[str, Any]) -> List[Dict[str, Any]]:
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"""
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Parse forecast data received from orchestrator
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Expected format from Forecasting Service via Orchestrator:
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{
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"forecasts": [
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{
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"product_id": "uuid",
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"inventory_product_id": "uuid", # Alternative field name
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"predicted_demand": 100.0,
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"predicted_value": 100.0, # Alternative field name
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"confidence_score": 0.85,
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...
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}
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],
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"forecast_id": "uuid",
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"generated_at": "2025-01-30T10:00:00Z"
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}
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"""
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forecasts = []
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forecast_list = forecast_data.get('forecasts', [])
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for forecast_item in forecast_list:
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# Extract product ID (try multiple field names)
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product_id = (
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forecast_item.get('product_id') or
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forecast_item.get('inventory_product_id') or
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forecast_item.get('item_id')
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)
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# Extract predicted demand (try multiple field names)
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predicted_demand = (
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forecast_item.get('predicted_demand') or
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forecast_item.get('predicted_value') or
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forecast_item.get('demand') or
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0
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)
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if product_id and predicted_demand > 0:
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forecasts.append({
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'product_id': product_id,
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'predicted_demand': float(predicted_demand),
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'confidence_score': forecast_item.get('confidence_score', 0.8),
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'lower_bound': forecast_item.get('lower_bound', 0),
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'upper_bound': forecast_item.get('upper_bound', 0),
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'forecast_id': forecast_data.get('forecast_id'),
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})
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return forecasts
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Reference in New Issue
Block a user