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Turn an unstructured order (email, PDF, API payload) into a quality-checked production schedule with a single function call.

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Quick Start

1

Run the prebuilt workflow

from praisonaiagents import Agent, tool
from examples.cookbooks.Industry_Templates.manufacturing_template import manufacturing_workflow

result = manufacturing_workflow(
    "Customer ABC needs 100 units of Product-XYZ by March 15th, high priority"
)
print(result)
result is a dict with keys order, inventory, schedule, and quality.
2

Build a custom agent with IndustryAgentPattern

from examples.cookbooks.Industry_Templates.manufacturing_template import IndustryAgentPattern

custom_parser = IndustryAgentPattern.create_data_parser(
    name="XMLOrderParser",
    domain="XML purchase orders",
    sla_seconds=15
)

order_data = custom_parser.start("Parse <order><id>999</id><qty>50</qty></order>")
print(order_data)

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How It Works

AgentResponsibilitySLA
ParseOrderExtract structured order info from any format≤ 30 s
CheckInventoryValidate material availability and reorder levels≤ 5 s
OptimizeScheduleGenerate optimal production schedule≤ 2 min
DefectDetectAutomated quality inspection per batch≤ 1 min

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Configuration Options

Pydantic I/O schemas used by this template:
SchemaFields
OrderDetailsorder_id, customer_id, product_id, quantity, priority, due_date, requirements
InventoryStatusmaterial_id, available_quantity, reorder_level, supplier_lead_time, location
ProductionScheduleschedule_id, production_line, start_time, end_time, assigned_workers, estimated_completion, bottleneck_analysis
QualityReportbatch_id, inspection_time, defect_rate, defect_types, passed, recommendations

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Common Patterns

Plug a custom ERP tool into ParseOrder 
from praisonaiagents import tool
from examples.cookbooks.Industry_Templates.manufacturing_template import order_parser

@tool
def erp_order_lookup(order_ref: str) -> dict:
    """Fetch order details from ERP system"""
    return {"erp_confirmed": True, "order_ref": order_ref, "priority": "high"}

order_parser.tools.append(erp_order_lookup)
result = order_parser.start("Look up order ORD-2024-555 in ERP")
print(result)
Swap the fallback strategy for inventory 
from examples.cookbooks.Industry_Templates.manufacturing_template import (
    manufacturing_workflow, inventory_checker
)

def conservative_inventory(order_text: str) -> dict:
    try:
        return manufacturing_workflow(order_text)
    except Exception:
        return {
            "status": "manual_review_required",
            "reason": "inventory_system_unavailable"
        }

result = conservative_inventory("Rush order: 200 units PART-999")
Scale with IndustryAgentPattern 
from examples.cookbooks.Industry_Templates.manufacturing_template import IndustryAgentPattern

optimizer = IndustryAgentPattern.create_optimizer(
    name="ShiftOptimizer",
    optimization_target="shift scheduling across 3 production lines",
    sla_minutes=5
)
schedule = optimizer.start("Optimize night shift for lines A, B, C with 80% capacity")

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Best Practices

The OptimizeSchedule agent sorts by priority (urgent > high > normal). Ensure ParseOrder correctly extracts the priority field — incorrect priorities cascade into suboptimal schedules.
CheckInventory must respond within 5 seconds to avoid blocking production scheduling. Any custom inventory tool you attach should query a cache or pre-indexed store rather than a slow ERP endpoint.
When CheckInventory cannot find stock, the built-in fallback returns an alternative-supplier flag. Extend this by attaching a @tool that queries a supplier API before escalating to manual review.
DefectDetect returns a defect_rate even when passed=True. Log these rates over time to catch drift in machine calibration before it causes real rejections.

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