struai 2.1.0

StruAI Drawing Analysis SDK - AI-powered construction drawing analysis

StruAI SDK (Python + JavaScript)

Official SDKs for the StruAI Drawing Analysis API.

• Python package: struai (PyPI)
• JavaScript package: struai (npm, source in js/)

Install

pip install struai
npm install struai

Environment

export STRUAI_API_KEY=your_api_key
# Optional: defaults to https://api.stru.ai (SDK appends /v1 automatically)
export STRUAI_BASE_URL=https://api.stru.ai

Python Quick Start

import os
from struai import StruAI

client = StruAI(api_key=os.environ["STRUAI_API_KEY"])

# Tier 1: drawings
result = client.drawings.analyze("structural.pdf", page=12)
print(result.id, result.processing_ms)

# Tier 2: projects + docquery
project = client.projects.create(name="Building A", description="Structural set")
job = project.sheets.add(page=12, file_hash=client.drawings.compute_file_hash("structural.pdf"))
sheet = job.wait(timeout=180)

hits = project.docquery.search("beam connection", limit=5)
print(hits.count)

Real Workflow Examples

Python examples (/examples):

# Drawings-only flow (hash, cache probe, analyze, get, optional delete)
python3 examples/test_prod_page12.py --pdf /absolute/path/to/structural.pdf --page 12

# Full projects + docquery workflow
python3 examples/test_prod_page12_full.py --pdf /absolute/path/to/structural.pdf --page 12

# Full workflow + crop demo
python3 examples/test_prod_page12_full.py \
  --pdf /absolute/path/to/structural.pdf --page 12 \
  --crop-image /absolute/path/to/page_context.png \
  --crop-output /absolute/path/to/crop.png

# Optional cleanup after full workflow
python3 examples/test_prod_page12_full.py --pdf /absolute/path/to/structural.pdf --cleanup

# Async workflow
python3 examples/async_projects_workflow.py --pdf /absolute/path/to/structural.pdf --page 12

JavaScript examples (/js/scripts):

cd js
npm install
npm run build

# Drawings-only flow
STRUAI_API_KEY=... STRUAI_BASE_URL=https://api.stru.ai \
STRUAI_PDF=/absolute/path/to/structural.pdf STRUAI_PAGE=12 \
node scripts/drawings_quickstart.mjs

# Full projects + docquery workflow
STRUAI_API_KEY=... STRUAI_BASE_URL=https://api.stru.ai \
STRUAI_PDF=/absolute/path/to/structural.pdf STRUAI_PAGE=12 \
node scripts/projects_workflow.mjs

# Full workflow + crop demo
STRUAI_API_KEY=... STRUAI_BASE_URL=https://api.stru.ai \
STRUAI_PDF=/absolute/path/to/structural.pdf STRUAI_PAGE=12 \
STRUAI_CROP_IMAGE=/absolute/path/to/page_context.png \
STRUAI_CROP_OUTPUT=/absolute/path/to/crop.png \
node scripts/projects_workflow.mjs

Python API Reference

Async API (AsyncStruAI) mirrors the same resource shape and method names; use await.

Client

• StruAI(api_key=None, base_url="https://api.stru.ai", timeout=60, max_retries=2)
• AsyncStruAI(api_key=None, base_url="https://api.stru.ai", timeout=60, max_retries=2)
• client.drawings
• client.projects

Drawings (client.drawings)

• analyze(file=None, page=1, file_hash=None) -> DrawingResult
• check_cache(file_hash) -> DrawingCacheStatus
• get(drawing_id) -> DrawingResult
• delete(drawing_id) -> DrawingDeleteResult
• compute_file_hash(file) -> str

Projects Top-Level (client.projects)

• create(name, description=None) -> ProjectInstance
• list() -> list[Project]
• open(project_id, name=None, description=None) -> ProjectInstance
• delete(project_id) -> ProjectDeleteResult

Project Instance (project)

Properties:

• id, name, description, data
• sheets, docquery

Methods:

• delete() -> ProjectDeleteResult

Sheets (project.sheets)

• add(file=None, page=1|"1,3,5-7"|"all", file_hash=None, source_description=None, on_sheet_exists=None, community_update_mode=None, semantic_index_update_mode=None) -> Job | JobBatch
• delete(sheet_id) -> SheetDeleteResult
• job(job_id, page=None) -> Job

DocQuery (project.docquery)

• node_get(uuid) -> DocQueryNodeGetResult
• sheet_entities(sheet_id, entity_type=None, limit=200) -> DocQuerySheetEntitiesResult
• search(query, index="entity_search", limit=20) -> DocQuerySearchResult
• neighbors(uuid, direction="both", relationship_type=None, limit=50) -> DocQueryNeighborsResult
• cypher(query, params=None, max_rows=500) -> DocQueryCypherResult
• sheet_summary(sheet_id, orphan_limit=10) -> DocQuerySheetSummaryResult
• sheet_list() -> DocQuerySheetListResult
• reference_resolve(uuid, limit=100) -> DocQueryReferenceResolveResult
• crop(output, uuid=None, bbox=None, image=None, page_hash=None, scale=None, scale_x=None, scale_y=None, auto_scale=False, pad=0, clamp=True) -> DocQueryCropResult

CLI parity: project-list maps to client.projects.list(), and the remaining 9 commands map to project.docquery.*, for full 10-command parity.

Python cypher + crop example:

project = client.projects.open("proj_86c0f02e")
rows = project.docquery.cypher(
    "MATCH (n:Entity {project_id:$project_id}) RETURN count(n) AS total",
    params={},
    max_rows=1,
)

crop = project.docquery.crop(
    uuid="entity-uuid-here",
    image="/absolute/path/to/page_context.png",
    output="/absolute/path/to/crop.png",
)
print(rows.records[0]["total"], crop.output_image["path"])

Jobs

Job (single-page ingest result):

• id, page
• status() -> JobStatus
• wait(timeout=120, poll_interval=2) -> SheetResult

JobBatch (multi-page ingest result):

• jobs, ids
• status_all() -> list[JobStatus]
• wait_all(timeout_per_job=120, poll_interval=2) -> list[SheetResult]

HTTP Endpoints Covered

Tier 1:

• POST /v1/drawings
• GET /v1/drawings/{id}
• DELETE /v1/drawings/{id}
• GET /v1/drawings/cache/{file_hash}

Tier 2:

• POST /v1/projects
• GET /v1/projects
• DELETE /v1/projects/{project_id}
• POST /v1/projects/{project_id}/sheets
• DELETE /v1/projects/{project_id}/sheets/{sheet_id}
• GET /v1/projects/{project_id}/jobs/{job_id}
• GET /v1/projects/{project_id}/docquery/node-get
• GET /v1/projects/{project_id}/docquery/sheet-entities
• GET /v1/projects/{project_id}/docquery/search
• GET /v1/projects/{project_id}/docquery/neighbors
• POST /v1/projects/{project_id}/docquery/cypher

JavaScript Reference

See js/README.md for complete JS method signatures and usage patterns.

License

MIT