CAD Exploded View Assembly BOM Extraction Agent with Pydantic AI
Extracting structured Bill of Materials (BOM) from complex 3D CAD exploded views is prone to manual line-item omission. Build a type-safe extraction agent using Pydantic AI that converts CAD assembly hierarchy trees into strictly typed nested Pydantic BOM objects. Achieve 100% schema validation and 95% line-item part number accuracy.
What you are building
The core problem, expected build, and operating context for this challenge.
Implement a type-safe CAD assembly metadata extraction agent using Pydantic AI and validated Pydantic model schemas.
How work is evaluated
Evaluates schema compliance and accuracy of parsed CAD assembly BOM items.
Shared data for this challenge
Review public datasets and any private uploads tied to your build.
How submissions are scored
These dimensions define what the evaluator checks and which criteria separate a passable run from a strong one.
schema_pass
Ensure zero Pydantic validation errors
This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.
item_extraction_recall
Proportion of individual part numbers correctly extracted • target: 0.95 • 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
Define nested Pydantic models representing BOM items, quantities, and material specs
Instantiate a Pydantic AI agent configured to parse unstructured CAD tree text into BOM models
Ensure total structural schema validation across multi-level assembly hierarchies
Reference links and supporting material
Dataset of 30 CAD assembly structure text trees and verified reference BOM representations.
How this agent runs
Evaluates schema compliance and accuracy of parsed CAD assembly BOM items.
Challenge input
Unstructured CAD tree text document
Pydantic AI
Provides strict type-safe output guarantees for structured engineering data.
Evaluated output
Pydantic validated JSON conforming to AssemblyBOM schema
- Ensure zero Pydantic validation errors
- Proportion of individual part numbers correctly extracted • target: 0.95 • range: 0-1
- Benchmark: CAD BOM Extraction Suite (CAD-BOM-2025)
- Item Extraction Recall target: 0.95
- 1 public reference case
- Python execution harness
- Python sandbox (unavailable on Versalist)
View technical recipe
Configured tools
- Pydantic AI · Required
- Pydantic AI · Required
Evaluation contract
- schema_pass · Weight 1
- item_extraction_recall · Weight 1
Recipe state
This is a preview. The configuration can change before the evaluation recipe is locked.