google-cloud-documentai
Google Cloud Documentai API client library
Decision gist · record as of 2026-08-14
Yes, if you have a Google Cloud project with Document AI enabled and need to process documents programmatically. The library is production-stable, actively maintained, has no known vulnerabilities, and integrates seamlessly with Google Cloud authentication. The main prerequisite is a working Google Cloud setup and a deployed processor; without those, the library alone is not useful.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Google Cloud project with Document AI enabled, valid credentials (via GOOGLE_APPLICATION_CREDENTIALS or Application Default Credentials), and a deployed Document AI processor.
- Python >= 3.10 required.
- Low install friction with a pure-Python wheel distribution.
License · maintenance · safety
Apache-2.0 (permissive) — Apache-2.0 permissive license allows use in commercial and open-source projects with minimal restrictions; you must include a copy of the license and note any modifications.
last release 2026-06-03 (72 days) · last repo commit 2026-08-14 · 5,373 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 3,878,766 downloads/mo, #2,466 on PyPI
Alternatives
Verify before relying
pip install google-cloud-documentai
from google.cloud import documentai_v1
client = documentai_v1.DocumentProcessorServiceClient()
name = client.processor_path(project_id, location, processor_id)
response = client.process_document(request={"name": name, "raw_document": raw_document})- Specific supported document types and formats beyond the general 'unstructured or semi-structured' claim
- Performance characteristics or throughput limits for batch processing
- Whether the library supports all Document AI processor types or only a subset
What it is and what it does
This is the official Python client for Google Cloud Document AI, a managed service that uses machine learning to extract and classify information from documents. It wraps Google's REST and gRPC APIs, allowing you to send documents to pre-trained or custom Document AI processors and receive structured data back. The library handles authentication, request serialization, and response parsing, so you work with Python objects rather than raw JSON.
The package is built on standard Google Cloud infrastructure (grpcio, protobuf, google-api-core, google-auth) and requires an active Google Cloud project with Document AI enabled and at least one deployed processor. It's intended for developers integrating document processing into applications—extracting invoices, forms, contracts, or other business documents at scale.
Use it for
- Extract line items, totals, and vendor details from invoices and receipts automatically
- Parse form responses and structured fields from application forms or surveys
- Classify and extract key information from contracts or legal documents
- Batch process large volumes of documents to populate databases or data warehouses
- Build document intake workflows that route documents based on extracted metadata
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you have a Google Cloud project with Document AI enabled and need to process documents programmatically.
The library is production-stable, actively maintained, has no known vulnerabilities, and integrates seamlessly with Google Cloud authentication. The main prerequisite is a working Google Cloud setup and a deployed processor; without those, the library alone is not useful.
Install
google-cloud-documentai on PyPI
Before you install
Low install friction with a pure-Python wheel distribution. Active maintenance with a release 72 days ago. Depends on standard Google Cloud libraries (grpcio, protobuf, google-api-core, google-auth, proto-plus), all widely used and well-maintained.
Requires Google Cloud project with Document AI enabled, valid credentials (via GOOGLE_APPLICATION_CREDENTIALS or Application Default Credentials), and a deployed Document AI processor. Python >= 3.10 required.
License in practice
Apache-2.0 permissive license allows use in commercial and open-source projects with minimal restrictions; you must include a copy of the license and note any modifications.
Quickstart
pip install google-cloud-documentai
from google.cloud import documentai_v1
client = documentai_v1.DocumentProcessorServiceClient()
name = client.processor_path(project_id, location, processor_id)
response = client.process_document(request={"name": name, "raw_document": raw_document})Verify before relying
- Specific supported document types and formats beyond the general 'unstructured or semi-structured' claim
- Performance characteristics or throughput limits for batch processing
- Whether the library supports all Document AI processor types or only a subset
Package facts
| License | Apache-2.0 permissive |
| Python support | Supports the current Python release >=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 5 packagesgrpcioproto-plusprotobufgoogle-api-coregoogle-auth |
| Maintenance | Actively maintained 72 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 3,878,766 / month, #2,466 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 5 - Production/StableIntended Audience :: DevelopersLicense :: OSI Approved :: Apache Software LicenseOperating System :: OS IndependentProgramming Language :: PythonProgramming Language :: Python :: 3Programming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14Topic :: Internet |
Evidence: google_cloud_documentai-3.15.0-py3-none-any.whl
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See also google-cloud-automl · google-cloud-documentai-toolbox · google-cloud-vision · google-cloud-firestore · google-cloud-language · google-cloud-workflows · google-cloud-translate · google-cloud-recommendations-ai · unstructured-client · google-cloud-videointelligence