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docs(samples): new Doc AI samples for v1beta3 (#44)
* batch_process_sample. changing from async to synchronous * add quick start and process_document samples and tests * add test and sample for batch_process * add test and sample for batch_process * resolve formatting * use os.environ * remove os.path.join * move tests * descriptive variable * specific Exception, formatting * parse all pages in process_document * add more helpful comments * remove unused imports * better exception handling * rename test files * ran linter, removed nested function in batch predict * refactor tests * format imports * format imports * format imports * serialize as Document object * extract get_text helper function * fix file path * delete test bucket * Update samples/snippets/batch_process_documents_sample_v1beta3_test.py Co-authored-by: Leah E. Cole <6719667+leahecole@users.noreply.github.com> * Update samples/snippets/batch_process_documents_sample_v1beta3_test.py Co-authored-by: Leah E. Cole <6719667+leahecole@users.noreply.github.com> * add more specific assertion in batch_process * add more specific assertion in process_document and quickstart * fix output_uri name * Apply suggestions from code review to resolve exception Co-authored-by: Leah E. Cole <6719667+leahecole@users.noreply.github.com> * resolve exception * lint Co-authored-by: Leah E. Cole <6719667+leahecole@users.noreply.github.com>
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documentai/snippets/batch_process_documents_sample_v1beta3.py
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# Copyright 2020 Google LLC | ||
# | ||
# Licensed under the Apache License, Version 2.0 (the "License"); | ||
# you may not use this file except in compliance with the License. | ||
# You may obtain a copy of the License at | ||
# | ||
# http://www.apache.org/licenses/LICENSE-2.0 | ||
# | ||
# Unless required by applicable law or agreed to in writing, software | ||
# distributed under the License is distributed on an "AS IS" BASIS, | ||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
# See the License for the specific language governing permissions and | ||
# limitations under the License. | ||
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# [START documentai_batch_process_document] | ||
import re | ||
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from google.cloud import documentai_v1beta3 as documentai | ||
from google.cloud import storage | ||
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# TODO(developer): Uncomment these variables before running the sample. | ||
# project_id= 'YOUR_PROJECT_ID' | ||
# location = 'YOUR_PROJECT_LOCATION' # Format is 'us' or 'eu' | ||
# processor_id = 'YOUR_PROCESSOR_ID' # Create processor in Cloud Console | ||
# input_uri = "YOUR_INPUT_URI" | ||
# gcs_output_uri = "YOUR_OUTPUT_BUCKET_URI" | ||
# gcs_output_uri_prefix = "YOUR_OUTPUT_URI_PREFIX" | ||
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def batch_process_documents( | ||
project_id, | ||
location, | ||
processor_id, | ||
gcs_input_uri, | ||
gcs_output_uri, | ||
gcs_output_uri_prefix, | ||
): | ||
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client = documentai.DocumentProcessorServiceClient() | ||
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destination_uri = f"{gcs_output_uri}/{gcs_output_uri_prefix}/" | ||
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# 'mime_type' can be 'application/pdf', 'image/tiff', | ||
# and 'image/gif', or 'application/json' | ||
input_config = documentai.types.document_processor_service.BatchProcessRequest.BatchInputConfig( | ||
gcs_source=gcs_input_uri, mime_type="application/pdf" | ||
) | ||
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# Where to write results | ||
output_config = documentai.types.document_processor_service.BatchProcessRequest.BatchOutputConfig( | ||
gcs_destination=destination_uri | ||
) | ||
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# Location can be 'us' or 'eu' | ||
name = f"projects/{project_id}/locations/{location}/processors/{processor_id}" | ||
request = documentai.types.document_processor_service.BatchProcessRequest( | ||
name=name, | ||
input_configs=[input_config], | ||
output_config=output_config, | ||
) | ||
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operation = client.batch_process_documents(request) | ||
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# Wait for the operation to finish | ||
operation.result() | ||
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# Results are written to GCS. Use a regex to find | ||
# output files | ||
match = re.match(r"gs://([^/]+)/(.+)", destination_uri) | ||
output_bucket = match.group(1) | ||
prefix = match.group(2) | ||
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storage_client = storage.Client() | ||
bucket = storage_client.get_bucket(output_bucket) | ||
blob_list = list(bucket.list_blobs(prefix=prefix)) | ||
print("Output files:") | ||
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for i, blob in enumerate(blob_list): | ||
# Download the contents of this blob as a bytes object. | ||
blob_as_bytes = blob.download_as_bytes() | ||
document = documentai.types.Document.from_json(blob_as_bytes) | ||
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print(f"Fetched file {i + 1}") | ||
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# For a full list of Document object attributes, please reference this page: https://googleapis.dev/python/documentai/latest/_modules/google/cloud/documentai_v1beta3/types/document.html#Document | ||
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# Read the text recognition output from the processor | ||
for page in document.pages: | ||
for form_field in page.form_fields: | ||
field_name = get_text(form_field.field_name, document) | ||
field_value = get_text(form_field.field_value, document) | ||
print("Extracted key value pair:") | ||
print(f"\t{field_name}, {field_value}") | ||
for paragraph in document.pages: | ||
paragraph_text = get_text(paragraph.layout, document) | ||
print(f"Paragraph text:\n{paragraph_text}") | ||
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# Extract shards from the text field | ||
def get_text(doc_element: dict, document: dict): | ||
""" | ||
Document AI identifies form fields by their offsets | ||
in document text. This function converts offsets | ||
to text snippets. | ||
""" | ||
response = "" | ||
# If a text segment spans several lines, it will | ||
# be stored in different text segments. | ||
for segment in doc_element.text_anchor.text_segments: | ||
start_index = ( | ||
int(segment.start_index) | ||
if "start_index" in doc_element.text_anchor.__dict__ | ||
else 0 | ||
) | ||
end_index = int(segment.end_index) | ||
response += document.text[start_index:end_index] | ||
return response | ||
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# [END documentai_batch_process_document] |
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documentai/snippets/batch_process_documents_sample_v1beta3_test.py
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# Copyright 2020 Google LLC | ||
# | ||
# Licensed under the Apache License, Version 2.0 (the "License"); | ||
# you may not use this file except in compliance with the License. | ||
# You may obtain a copy of the License at | ||
# | ||
# http://www.apache.org/licenses/LICENSE-2.0 | ||
# | ||
# Unless required by applicable law or agreed to in writing, software | ||
# distributed under the License is distributed on an "AS IS" BASIS, | ||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
# See the License for the specific language governing permissions and | ||
# limitations under the License. | ||
# | ||
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import os | ||
from uuid import uuid4 | ||
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from google.cloud import storage | ||
from google.cloud.exceptions import NotFound | ||
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import pytest | ||
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from samples.snippets import batch_process_documents_sample_v1beta3 | ||
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location = "us" | ||
project_id = os.environ["GOOGLE_CLOUD_PROJECT"] | ||
processor_id = "90484cfdedb024f6" | ||
gcs_input_uri = "gs://cloud-samples-data/documentai/invoice.pdf" | ||
gcs_output_uri_prefix = uuid4() | ||
BUCKET_NAME = f"document-ai-python-{uuid4()}" | ||
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@pytest.fixture(scope="module") | ||
def test_bucket(): | ||
storage_client = storage.Client() | ||
bucket = storage_client.create_bucket(BUCKET_NAME) | ||
yield bucket.name | ||
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try: | ||
blobs = list(bucket.list_blobs()) | ||
for blob in blobs: | ||
blob.delete() | ||
bucket.delete() | ||
except NotFound: | ||
print("Bucket already deleted.") | ||
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def test_batch_process_documents(capsys, test_bucket): | ||
batch_process_documents_sample_v1beta3.batch_process_documents( | ||
project_id=project_id, | ||
location=location, | ||
processor_id=processor_id, | ||
gcs_input_uri=gcs_input_uri, | ||
gcs_output_uri=f"gs://{test_bucket}", | ||
gcs_output_uri_prefix=gcs_output_uri_prefix, | ||
) | ||
out, _ = capsys.readouterr() | ||
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assert "Extracted" in out | ||
assert "Paragraph" in out | ||
assert "Invoice" in out |
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# Copyright 2020 Google LLC | ||
# | ||
# Licensed under the Apache License, Version 2.0 (the "License"); | ||
# you may not use this file except in compliance with the License. | ||
# You may obtain a copy of the License at | ||
# | ||
# http://www.apache.org/licenses/LICENSE-2.0 | ||
# | ||
# Unless required by applicable law or agreed to in writing, software | ||
# distributed under the License is distributed on an "AS IS" BASIS, | ||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
# See the License for the specific language governing permissions and | ||
# limitations under the License. | ||
# | ||
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from google.cloud import documentai_v1beta3 as documentai | ||
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# [START documentai_process_document] | ||
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# TODO(developer): Uncomment these variables before running the sample. | ||
# project_id= 'YOUR_PROJECT_ID'; | ||
# location = 'YOUR_PROJECT_LOCATION'; // Format is 'us' or 'eu' | ||
# processor_id = 'YOUR_PROCESSOR_ID'; // Create processor in Cloud Console | ||
# file_path = '/path/to/local/pdf'; | ||
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def process_document_sample( | ||
project_id: str, location: str, processor_id: str, file_path: str | ||
): | ||
# Instantiates a client | ||
client = documentai.DocumentProcessorServiceClient() | ||
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# The full resource name of the processor, e.g.: | ||
# projects/project-id/locations/location/processor/processor-id | ||
# You must create new processors in the Cloud Console first | ||
name = f"projects/{project_id}/locations/{location}/processors/{processor_id}" | ||
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with open(file_path, "rb") as image: | ||
image_content = image.read() | ||
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# Read the file into memory | ||
document = {"content": image_content, "mime_type": "application/pdf"} | ||
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# Configure the process request | ||
request = {"name": name, "document": document} | ||
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# Recognizes text entities in the PDF document | ||
result = client.process_document(request=request) | ||
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document = result.document | ||
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print("Document processing complete.") | ||
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# For a full list of Document object attributes, please reference this page: https://googleapis.dev/python/documentai/latest/_modules/google/cloud/documentai_v1beta3/types/document.html#Document | ||
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document_pages = document.pages | ||
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# Read the text recognition output from the processor | ||
print("The document contains the following paragraphs:") | ||
for page in document_pages: | ||
paragraphs = page.paragraphs | ||
for paragraph in paragraphs: | ||
paragraph_text = get_text(paragraph.layout, document) | ||
print(f"Paragraph text: {paragraph_text}") | ||
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# Extract shards from the text field | ||
def get_text(doc_element: dict, document: dict): | ||
""" | ||
Document AI identifies form fields by their offsets | ||
in document text. This function converts offsets | ||
to text snippets. | ||
""" | ||
response = "" | ||
# If a text segment spans several lines, it will | ||
# be stored in different text segments. | ||
for segment in doc_element.text_anchor.text_segments: | ||
start_index = ( | ||
int(segment.start_index) | ||
if segment.start_index in doc_element.text_anchor.text_segments | ||
else 0 | ||
) | ||
end_index = int(segment.end_index) | ||
response += document.text[start_index:end_index] | ||
return response | ||
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# [END documentai_process_document] |
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documentai/snippets/process_document_sample_v1beta3_test.py
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# # Copyright 2020 Google LLC | ||
# | ||
# Licensed under the Apache License, Version 2.0 (the "License"); | ||
# you may not use this file except in compliance with the License. | ||
# You may obtain a copy of the License at | ||
# | ||
# http://www.apache.org/licenses/LICENSE-2.0 | ||
# | ||
# Unless required by applicable law or agreed to in writing, software | ||
# distributed under the License is distributed on an "AS IS" BASIS, | ||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
# See the License for the specific language governing permissions and | ||
# limitations under the License. | ||
# | ||
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import os | ||
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from samples.snippets import process_document_sample_v1beta3 | ||
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location = "us" | ||
project_id = os.environ["GOOGLE_CLOUD_PROJECT"] | ||
processor_id = "90484cfdedb024f6" | ||
file_path = "resources/invoice.pdf" | ||
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def test_process_documents(capsys): | ||
process_document_sample_v1beta3.process_document_sample( | ||
project_id=project_id, | ||
location=location, | ||
processor_id=processor_id, | ||
file_path=file_path, | ||
) | ||
out, _ = capsys.readouterr() | ||
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assert "Paragraph" in out | ||
assert "Invoice" in out |
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