Industry Templates

Pre-built agent workforces for Manufacturing, Energy, Healthcare, Agriculture, and Transportation — ready to run in minutes.

Five production-ready agent pipelines built on the SRAO Framework, each targeting a specific industry with typed I/O schemas, SLA targets, and graceful fallback strategies.

Five production-ready agent pipelines built on the SRAO Framework, each targeting a specific industry with typed I/O schemas, SLA targets, and graceful fallback strategies.

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

agent = Agent(name="ops-lead", instructions="Route industry template workflows.")
result = manufacturing_workflow(
    "Customer ABC needs 100 units of Product-XYZ by March 15th, high priority"
)
print(result)

The user picks an industry template; agents parse the request and return a structured operations report.

Quick Start

1. Pick an industry and run

   Each template ships a single workflow function you can call immediately:

   from praisonaiagents import Agent, tool
   
   # Manufacturing: order → inventory → schedule → quality
   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)
   
2. Customise with IndustryAgentPattern

   Every template exposes IndustryAgentPattern — a base class you can mix into any domain:

   from examples.cookbooks.Industry_Templates.manufacturing_template import IndustryAgentPattern
   
   # Build a domain-specific parser in one line
   parser = IndustryAgentPattern.create_data_parser(
       name="CustomParser",
       domain="pharmaceutical batch records",
       sla_seconds=20
   )
   
   result = parser.start("Parse batch record BR-2024-001")
   print(result)
   

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Which Template Should I Use?

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Templates at a Glance

Industry	Key Agents	Highlights
Manufacturing	ParseOrder, CheckInventory, OptimizeSchedule, DefectDetect	Multi-format order processing, real-time inventory, production optimisation, quality inspection
Energy	SCADAReader, VibrationAnalyzer, PowerForecaster, MaintenanceScheduler	Wind-farm monitoring, vibration-based fault detection, power forecasting, predictive maintenance
Healthcare	VitalSignsCapture, EMRRetrieval, TriageRecommendation, ResourceAllocator	Emergency triage workflow, HIPAA-compliant data handling, ESI-based triage, resource allocation
Agriculture	MultispectralAnalyzer, DiseaseIdentifier, SprayRecommender, YieldPredictor	Drone/satellite multispectral analysis, pest/disease detection, targeted spraying, yield forecasting
Transportation	LiDARFusion, DisplacementCalculator, HeatmapGenerator, MaintenancePlanner	Tunnel/bridge LiDAR analysis, displacement tracking, safety heatmaps, predictive maintenance

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How It Works

All five templates share the same SRAO architecture — only the domain logic differs.

Every step includes a fallback strategy — if an agent fails, the workflow degrades gracefully rather than crashing.

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Cross-Industry Reuse with IndustryAgentPattern

IndustryAgentPattern provides four factory methods that power ~70 % of every template:

from examples.cookbooks.Industry_Templates.manufacturing_template import IndustryAgentPattern

# Generic parser — works for any domain
parser    = IndustryAgentPattern.create_data_parser("MyParser", "logistics data", sla_seconds=15)

# Generic availability checker
checker   = IndustryAgentPattern.create_resource_checker("BedChecker", "hospital bed", sla_seconds=3)

# Generic optimiser
optimizer = IndustryAgentPattern.create_optimizer("IrrigationOpt", "water usage", sla_minutes=5)

# Generic inspector
inspector = IndustryAgentPattern.create_inspector("TunnelInspect", "structural integrity", sla_minutes=2)

Method	Purpose	SLA param
create_data_parser(name, domain, sla_seconds)	Extract/structure raw inputs	sla_seconds=30
create_resource_checker(name, resource_type, sla_seconds)	Verify availability	sla_seconds=5
create_optimizer(name, optimization_target, sla_minutes)	Find optimal solution	sla_minutes=2
create_inspector(name, inspection_type, sla_minutes)	Analyse quality/safety	sla_minutes=1

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Pydantic I/O Schemas

Every template uses Pydantic models to enforce typed data between agents:

Industry	Input Schema	Output Schema
Manufacturing	OrderDetails	QualityReport
Energy	TurbineData	MaintenancePlan
Healthcare	VitalSigns	ResourceAllocation
Agriculture	MultispectralData	YieldForecast
Transportation	LiDARScan	MaintenanceSchedule

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Common Patterns

Add a custom tool to any agent

from praisonaiagents import Agent, tool

@tool
def my_erp_lookup(order_id: str) -> dict:
    """Look up order in ERP system"""
    return {"erp_status": "confirmed", "order_id": order_id}

from examples.cookbooks.Industry_Templates.manufacturing_template import order_parser

order_parser.tools.append(my_erp_lookup)
result = order_parser.start("Parse order ORD-999")

Override the fallback strategy

def custom_fallback(error: Exception) -> dict:
    return {"status": "queued_for_review", "error": str(error)}

try:
    result = manufacturing_workflow("urgent order text")
except Exception as e:
    result = custom_fallback(e)

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Best Practices

Start with the prebuilt workflow function

Call manufacturing_workflow(), energy_monitoring_workflow(), etc. before customising. These functions already wire up all agents and fallbacks in the correct order.

Use Pydantic schemas for typed hand-offs

Pass structured Pydantic objects (e.g. OrderDetails, VitalSigns) between agents instead of raw strings. This catches type errors early and makes pipelines easier to test.

Respect SLA targets per agent

Each agent declares its SLA in its instructions. Keep custom tools within those bounds — e.g. inventory checks must complete in ≤ 5 seconds to not block downstream agents.

Attribution: SRAO Framework

These templates are based on the SRAO Framework (MIT). The IndustryAgentPattern class provides the shared 70 % reuse layer.

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Related

Manufacturing Template

Order processing, inventory, scheduling, and quality control agents.

Energy Template

Wind-farm monitoring, vibration analysis, and predictive maintenance agents.

Healthcare Template

Emergency triage, EMR retrieval, and resource allocation agents.

Agriculture Template

Multispectral analysis, disease detection, and yield prediction agents.