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cadling — Usage

cadling’s processing flow is: DocumentConverter → Backend → Pipeline (Build → Assemble → Enrich) → CADlingDocument → Chunking / SDG / Export.

Python API

Section titled “Python API”

Basic conversion

Section titled “Basic conversion”
from cadling import DocumentConverter, ConversionStatus


converter = DocumentConverter()
result = converter.convert("part.step")


if result.status == ConversionStatus.SUCCESS:
    doc = result.document
    print(f"Parsed {len(doc.items)} items")


    json_data = doc.export_to_json()
    markdown = doc.export_to_markdown()

With format options

Section titled “With format options”
from cadling import DocumentConverter, FormatOption, InputFormat
from cadling.backend.step.step_backend import STEPBackend
from cadling.pipeline.hybrid_pipeline import HybridPipeline


converter = DocumentConverter(
    allowed_formats=[InputFormat.STEP],
    format_options={
        InputFormat.STEP: FormatOption(
            backend=STEPBackend,
            pipeline_cls=HybridPipeline,
        )
    },
)
result = converter.convert("assembly.step")

Chunking for RAG

Section titled “Chunking for RAG”
from cadling import DocumentConverter
from cadling.chunker.hybrid_chunker import CADHybridChunker


result = DocumentConverter().convert("part.step")


chunker = CADHybridChunker(max_tokens=512, overlap_tokens=50)
for chunk in chunker.chunk(result.document):
    print(f"Chunk {chunk.chunk_id}: {len(chunk.meta.entity_ids)} entities")
    # chunk.text  → text representation
    # chunk.meta  → entity types, topology subgraph, embeddings, bbox

Synthetic data generation (SDG)

Section titled “Synthetic data generation (SDG)”
from pathlib import Path
from cadling.sdg.qa import (
    CADPassageSampler, CADGenerator, CADJudge,
    CADSampleOptions, CADGenerateOptions, CADCritiqueOptions, LlmProvider,
)


# 1. Sample passages from CAD files
sampler = CADPassageSampler(CADSampleOptions(sample_file=Path("samples.jsonl")))
sampler.sample([Path("part.step"), Path("assembly.step")])


# 2. Generate Q&A pairs
gen = CADGenerator(CADGenerateOptions(
    provider=LlmProvider.OPENAI, model_id="gpt-4o",
    generated_file=Path("generated.jsonl"),
))
gen.generate(Path("samples.jsonl"))


# 3. Critique and improve
judge = CADJudge(CADCritiqueOptions(
    provider=LlmProvider.OPENAI, model_id="gpt-4o",
    critiqued_file=Path("critiqued.jsonl"),
))
judge.critique(Path("generated.jsonl"))

CLI

Section titled “CLI”

cadling (main)

Section titled “cadling (main)”
Terminal window
cadling convert part.step --format json --pretty -o part.json
cadling chunk part.step --max-tokens 512 --overlap 50 -o chunks.jsonl
cadling generate-qa part.step -n 100 -m gpt-4 -o qa.jsonl
cadling info part.step

cadling-sdg

Section titled “cadling-sdg”
Terminal window
cadling-sdg qa sample part.step assembly.step --chunker hybrid -o samples.jsonl
cadling-sdg qa generate samples.jsonl -p openai -m gpt-4o -o generated.jsonl
cadling-sdg qa critique generated.jsonl -p openai -m gpt-4o --rewrite -o critiqued.jsonl

The layers

Section titled “The layers”
LayerWhereRole
Backendscadling/backend/Format-specific parsing. DeclarativeCADBackend (text) and RenderableCADBackend (vision). STEP and STL are dual-mode.
Pipelinescadling/pipeline/Orchestrate Build → Assemble → Enrich. SimpleCADPipeline, STEPPipeline, STLPipeline, VisionPipeline, VlmPipeline, HybridPipeline.
Enrichment modelscadling/models/Optional post-processing: geometry analysis, topology validation, mesh quality, surface analysis, interference, GNN segmentation.
Chunkerscadling/chunker/RAG chunking: CADHybridChunker, CADHierarchicalChunker, format-specific.
SDGcadling/sdg/CADPassageSampler → CADGenerator → CADJudge (+ CADConceptualGenerator).

Core data models

Section titled “Core data models”
InputFormat       # STEP | STL | BREP | IGES | CAD_IMAGE
ConversionStatus  # SUCCESS | PARTIAL | FAILURE
CADlingDocument   # items, topology, segments, embeddings
CADItem           # STEPEntityItem | MeshItem | AssemblyItem | AnnotationItem
TopologyGraph     # entity reference graph (adjacency list)
Section titled “Related”