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StruAI Drawing Analysis SDK - AI-powered construction drawing analysis

Project description

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(len(hits.hits))

Real Workflow Examples

Python examples (/examples):

# Drawings-only flow (hash, cache probe, analyze)
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-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

Page-12 cookbook with all 10 operations (including cypher and crop):

  • examples/PAGE12_COOKBOOK.md

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_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
  • 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, mode="both", direction="both", relationship_type=None, radius=200.0, 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, page_hash=None) -> 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",
    output="/absolute/path/to/crop.png",
)
print(rows.records[0]["total"], crop.output_path, crop.bytes_written)

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/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}/node-get
  • GET /v1/projects/{project_id}/sheet-entities
  • GET /v1/projects/{project_id}/search
  • GET /v1/projects/{project_id}/neighbors
  • POST /v1/projects/{project_id}/cypher
  • POST /v1/projects/{project_id}/crop

JavaScript Reference

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

License

MIT

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