LangChain Motor Control Center Configuration Agent with LangGraph
Engineering custom Motor Control Center (MCC) wiring and components manually creates delivery bottlenecks of over 50 weeks. Construct a stateful configuration assistant using LangChain and LangGraph to generate validated electrical schematics and bill-of-materials from natural language requirements. The system must reduce schematic generation time from hours to under 30 seconds.
What you are building
The core problem, expected build, and operating context for this challenge.
Build a stateful LangGraph agent using LangChain tool nodes to automatically translate MCC requirements into verified bill-of-materials and wiring schematics.
How work is evaluated
Evaluates MCC component sizing accuracy, BOM compliance, and generation time.
Challenge datasets
Public datasets, plus the private datasets you have access to.
How submissions are scored
These dimensions define what the evaluator checks and which criteria separate a passable run from a strong one.
electrical_safety_sizing
Ensures breaker sizing satisfies NEC 430 motor circuit requirements
This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.
bom_accuracy
Percentage of correctly selected components in BOM • target: 0.98 • range: 0-1
This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.
What you should walk away with
Design a stateful graph workflow using LangGraph for multi-step MCC configuration
Implement LangChain tool tools for starter selection, overload sizing, and breaker matching
Validate generated Bill of Materials (BOM) against NEMA/IEC electrical safety standards
Produce CAD-compatible JSON output for electrical schematic drafting
Reference links and supporting material
NEMA and IEC motor full-load current (FLA) reference charts and MCC manufacturer component catalog data.
Challenge setup
Evaluates MCC component sizing accuracy, BOM compliance, and generation time.
Challenge input
JSON specifying motor_hp, voltage, phase, starter_type, environment_rating
LangChain
Assigned framework for building tool-using agents.
LangGraph
Assigned workflow engine for cyclic stateful control loops.
Evaluated output
JSON with breaker_rating_amps (int), overload_range (string), enclosure (string), bom_valid (bool)
- Ensures breaker sizing satisfies NEC 430 motor circuit requirements
- Percentage of correctly selected components in BOM • target: 0.98 • range: 0-1
- Benchmark: Electrical Systems CAD Configuration Benchmark
- Bom Accuracy target: 0.98
- 1 public reference case
- Python execution harness
- Python sandbox (unavailable on Versalist)
Summary shows the first task, up to three tools, and up to three evidence items. Open the technical recipe to view all configured items.
View technical recipe
Configured tools
- LangGraph · Required
- Langchain · Optional
- LangChain · Optional
- LangGraph · Required
- Langchain · Optional
- LangChain · Optional
Evaluation contract
- electrical_safety_sizing · Weight 1
- bom_accuracy · Weight 1
Metrics
- bom_accuracy · Target 0.98
Benchmarks
- Electrical Systems CAD Configuration Benchmark
- general
Reference cases
- 1 public reference case
Workflow tasks
- Task 1
Input: JSON specifying motor_hp, voltage, phase, starter_type, environment_rating
Output: JSON with breaker_rating_amps (int), overload_range (string), enclosure (string), bom_valid (bool)
Execution harness: Python
Evaluation tools
- LangChain · LLM Integration Library
- LangGraph · Stateful Orchestration Engine
Recipe freeze marker
No recipe freeze time is recorded.