8000 docs: update classification sample to use v2 model by wizeng23 · Pull Request #378 · googleapis/python-language · GitHub
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docs: update classification sample to use v2 model #378

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Sep 27, 2022
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docs: update classification sample to use v2 model #378

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eaee856
docs: update classification sample to use v2 model
wizeng23 Sep 23, 2022
692fae6
fix: update classification test to use v2 model
wizeng23 Sep 23, 2022
d080d58
Merge branch 'main' into classification-v2
parthea Sep 26, 2022
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15 changes: 12 additions & 3 deletions samples/v1/language_classify_text.py
8000
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Original file line number Diff line number Diff line change
Expand Up @@ -32,12 +32,12 @@ def sample_classify_text(text_content):
Classifying Content in a String

Args:
text_content The text content to analyze. Must include at least 20 words.
text_content The text content to analyze.
"""

client = language_v1.LanguageServiceClient()

# text_content = 'That actor on TV makes movies in Hollywood and also stars in a variety of popular new TV shows.'
# text_content = "That actor on TV makes movies in Hollywood and also stars in a variety of popular new TV shows."

# Available types: PLAIN_TEXT, HTML
type_ = language_v1.Document.Type.PLAIN_TEXT
Expand All @@ -48,7 +48,16 @@ def sample_classify_text(text_content):
language = "en"
document = {"content": text_content, "type_": type_, "language": language}

response = client.classify_text(request = {'document': document})
content_categories_version = (
language_v1.ClassificationModelOptions.V2Model.ContentCategoriesVersion.V2)
response = client.classify_text(request = {
"document": document,
"classification_model_options": {
"v2_model": {
"content_categories_version": content_categories_version
}
}
})
# Loop through classified categories returned from the API
for category in response.categories:
# Get the name of the category representing the document.
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10 changes: 5 additions & 5 deletions samples/v1/test/classifying_content.test.yaml
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Expand Up @@ -16,15 +16,15 @@ test:

- name: language_classify_text - Classifying Content of a text string (*custom value*)
spec:
# Custom value: "Let's drink coffee and eat bagels at a coffee shop. I want muffins, croisants, coffee and baked goods."
# Custom value: "Dungeons and dragons and loot, oh my!"
- call:
sample: language_classify_text
params:
text_content: {literal: "Let's drink coffee and eat bagels at a coffee shop. I want muffins, croisants, coffee and baked goods."}
text_content: {literal: "Dungeons and dragons and loot, oh my!"}
- assert_contains_any:
- {literal: "Food"}
- {literal: "Drink"}
- {literal: "Coffee"}
- {literal: "Games"}
- {literal: "Roleplaying"}
- {literal: "Computer"}

- name: language_classify_gcs - Classifying Content of text file in GCS (default value)
spec:
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