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improve docs and samples for glossaries and custom models (Azure#18587)
* update the readme * update readme file * added custom translation samples * fix 'no-locale' thing in links * update glossary docs * update glossaries * link to sample glossaries instead of writing code in readme * update custom model sample linking * remove relative linking in readme * make subheadings in bold text to be more readable * conform with 'Document Translation' naming * disambiguate container sas url * capitaliz Azure name * remove misplaced period * update samples -> custom model * update async sample -> custom model * remove localization from url * update readme with new file types for glossaries * adding sample glossaries -> xlf * white space * use simplified single input method * update 'job' terminology * update azure-core naming * update glossary blob file reference name * link to supported glossaries table * remove locale from url
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sdk/translation/azure-ai-translation-document/samples/assets/glossary_sample.csv
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|---|---|---|
| @@ -0,0 +1,4 @@ | ||
| skull,le crâne | ||
| body,corps | ||
| heart,cœur | ||
| lungs,poumons |
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sdk/translation/azure-ai-translation-document/samples/assets/glossary_sample.tsv
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| skull le crâne | ||
| body corps | ||
| heart cœur | ||
| lungs poumons |
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sdk/translation/azure-ai-translation-document/samples/assets/glossary_sample.xlf
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| <?xml version="1.0" encoding="UTF-8"?> | ||
| <xliff xmlns="urn:oasis:names:tc:xliff:document:1.2" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" version="1.2" xsi:schemaLocation="urn:oasis:names:tc:xliff:document:1.2 http://docs.oasis-open.org/xliff/v1.2/os/xliff-core-1.2-strict.xsd"> | ||
| <file original="EN-TA.tmx" source-language="en-US" target-language="fr-FR" datatype="xml"> | ||
| <body> | ||
| <trans-unit id="1" datatype="plaintext"> | ||
| <source>skull</source> | ||
| <target state="translated">le crâne</target> | ||
| </trans-unit> | ||
| <trans-unit id="2" datatype="plaintext"> | ||
| <source>body</source> | ||
| <target state="translated">corps</target> | ||
| </trans-unit> | ||
| <trans-unit id="3" datatype="plaintext"> | ||
| <source>heart</source> | ||
| <target state="translated">cœur</target> | ||
| </trans-unit> | ||
| <trans-unit id="4" datatype="plaintext"> | ||
| <source>lungs</source> | ||
| <target state="translated">poumons</target> | ||
| </trans-unit> | ||
| </body> | ||
| </file> | ||
| </xliff> |
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...-translation-document/samples/async_samples/sample_translation_with_custom_model_async.py
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| # coding=utf-8 | ||
| # ------------------------------------ | ||
| # Copyright (c) Microsoft Corporation. | ||
| # Licensed under the MIT License. | ||
| # ------------------------------------ | ||
|
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| """ | ||
| FILE: sample_translation_with_custom_model_async.py | ||
| DESCRIPTION: | ||
| This sample demonstrates how to create a translation operation and apply custom azure translation model when doing the translation. | ||
| To set up your containers for translation and generate SAS tokens to your containers (or files) | ||
| with the appropriate permissions, see the README. | ||
| USAGE: | ||
| python sample_translation_with_custom_model_async.py | ||
| Set the environment variables with your own values before running the sample: | ||
| 1) AZURE_DOCUMENT_TRANSLATION_ENDPOINT - the endpoint to your Document Translation resource. | ||
| 2) AZURE_DOCUMENT_TRANSLATION_KEY - your Document Translation API key. | ||
| 3) AZURE_SOURCE_CONTAINER_URL - the container SAS URL to your source container which has the documents | ||
| to be translated. | ||
| 4) AZURE_TARGET_CONTAINER_URL - the container SAS URL to your target container where the translated documents | ||
| will be written. | ||
| 5) AZURE_CUSTOM_MODEL_ID - the URL to your Azure custom translation model. | ||
| """ | ||
|
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| import asyncio | ||
|
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| async def sample_translation_with_custom_model_async(): | ||
| import os | ||
| from azure.core.credentials import AzureKeyCredential | ||
| from azure.ai.translation.document.aio import DocumentTranslationClient | ||
|
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| endpoint = os.environ["AZURE_DOCUMENT_TRANSLATION_ENDPOINT"] | ||
| key = os.environ["AZURE_DOCUMENT_TRANSLATION_KEY"] | ||
| source_container_url = os.environ["AZURE_SOURCE_CONTAINER_URL"] | ||
| target_container_url = os.environ["AZURE_TARGET_CONTAINER_URL"] | ||
| custom_model_id = os.environ["AZURE_CUSTOM_MODEL_ID"] | ||
|
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| client = DocumentTranslationClient(endpoint, AzureKeyCredential(key)) | ||
|
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| async with client: | ||
| poller = await client.begin_translation( | ||
| source_container_url, | ||
| target_container_url, | ||
| "es", | ||
| category_id=custom_model_id | ||
| ) | ||
| result = await poller.result() | ||
|
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||
| print("Operation status: {}".format(result.status)) | ||
| print("Operation created on: {}".format(result.created_on)) | ||
| print("Operation last updated on: {}".format(result.last_updated_on)) | ||
| print("Total number of translations on documents: {}".format(result.documents_total_count)) | ||
|
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| print("\nOf total documents...") | ||
| print("{} failed".format(result.documents_failed_count)) | ||
| print("{} succeeded".format(result.documents_succeeded_count)) | ||
|
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| doc_results = client.list_all_document_statuses(result.id) | ||
| async for document in doc_results: | ||
| print("Document ID: {}".format(document.id)) | ||
| print("Document status: {}".format(document.status)) | ||
| if document.status == "Succeeded": | ||
| print("Source document location: {}".format(document.source_document_url)) | ||
| print("Translated document location: {}".format(document.translated_document_url)) | ||
| print("Translated to language: {}\n".format(document.translate_to)) | ||
| else: | ||
| print("Error Code: {}, Message: {}\n".format(document.error.code, document.error.message)) | ||
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| async def main(): | ||
| await sample_translation_with_custom_model_async() | ||
|
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| if __name__ == '__main__': | ||
| loop = asyncio.get_event_loop() | ||
| loop.run_until_complete(main()) |
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...translation/azure-ai-translation-document/samples/sample_translation_with_custom_model.py
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| # coding=utf-8 | ||
| # ------------------------------------ | ||
| # Copyright (c) Microsoft Corporation. | ||
| # Licensed under the MIT License. | ||
| # ------------------------------------ | ||
|
|
||
| """ | ||
| FILE: sample_translation_with_custom_model.py | ||
| DESCRIPTION: | ||
| This sample demonstrates how to create a translation operation and apply custom azure translation model when doing the translation. | ||
| To set up your containers for translation and generate SAS tokens to your containers (or files) | ||
| with the appropriate permissions, see the README. | ||
| USAGE: | ||
| python sample_translation_with_custom_model.py | ||
| Set the environment variables with your own values before running the sample: | ||
| 1) AZURE_DOCUMENT_TRANSLATION_ENDPOINT - the endpoint to your Document Translation resource. | ||
| 2) AZURE_DOCUMENT_TRANSLATION_KEY - your Document Translation API key. | ||
| 3) AZURE_SOURCE_CONTAINER_URL - the container SAS URL to your source container which has the documents | ||
| to be translated. | ||
| 4) AZURE_TARGET_CONTAINER_URL - the container SAS URL to your target container where the translated documents | ||
| will be written. | ||
| 5) AZURE_CUSTOM_MODEL_ID - the URL to your Azure custom translation model. | ||
| """ | ||
|
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| def sample_translation_with_custom_model(): | ||
| import os | ||
| from azure.core.credentials import AzureKeyCredential | ||
| from azure.ai.translation.document import ( | ||
| DocumentTranslationClient | ||
| ) | ||
|
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| endpoint = os.environ["AZURE_DOCUMENT_TRANSLATION_ENDPOINT"] | ||
| key = os.environ["AZURE_DOCUMENT_TRANSLATION_KEY"] | ||
| source_container_url = os.environ["AZURE_SOURCE_CONTAINER_URL"] | ||
| target_container_url = os.environ["AZURE_TARGET_CONTAINER_URL"] | ||
| custom_model_id = os.environ["AZURE_CUSTOM_MODEL_ID"] | ||
|
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| client = DocumentTranslationClient(endpoint, AzureKeyCredential(key)) | ||
|
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| poller = client.begin_translation( | ||
| source_container_url, | ||
| target_container_url, | ||
| "es", | ||
| category_id=custom_model_id | ||
| ) | ||
| result = poller.result() | ||
|
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| print("Operation status: {}".format(result.status)) | ||
| print("Operation created on: {}".format(result.created_on)) | ||
| print("Operation last updated on: {}".format(result.last_updated_on)) | ||
| print("Total number of translations on documents: {}".format(result.documents_total_count)) | ||
|
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| print("\nOf total documents...") | ||
| print("{} failed".format(result.documents_failed_count)) | ||
| print("{} succeeded".format(result.documents_succeeded_count)) | ||
|
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| doc_results = client.list_all_document_statuses(result.id) | ||
| for document in doc_results: | ||
| print("Document ID: {}".format(document.id)) | ||
| print("Document status: {}".format(document.status)) | ||
| if document.status == "Succeeded": | ||
| print("Source document location: {}".format(document.source_document_url)) | ||
| print("Translated document location: {}".format(document.translated_document_url)) | ||
| print("Translated to language: {}\n".format(document.translate_to)) | ||
| else: | ||
| print("Error Code: {}, Message: {}\n".format(document.error.code, document.error.message)) | ||
|
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| if __name__ == '__main__': | ||
| sample_translation_with_custom_model() |