azure-ai-textanalytics-py non-hero scenarios

These scenarios are intentionally separate from hero flows in SKILL.md. They cover secondary/advanced patterns typically used after the primary end-to-end path is working.

Language Detection

documents = ["Ce document est en francais.", "This is written in English."]

result = client.detect_language(documents)

for doc in result:
    if not doc.is_error:
        print(f"Language: {doc.primary_language.name} ({doc.primary_language.iso6391_name})")
        print(f"Confidence: {doc.primary_language.confidence_score:.2f}")

Healthcare Text Analytics

documents = ["Patient has diabetes and was prescribed metformin 500mg twice daily."]

poller = client.begin_analyze_healthcare_entities(documents)
result = poller.result()

for doc in result:
    if not doc.is_error:
        for entity in doc.entities:
            print(f"Entity: {entity.text}")
            print(f"  Category: {entity.category}")
            print(f"  Normalized: {entity.normalized_text}")
            
            # Entity links (UMLS, etc.)
            for link in entity.data_sources:
                print(f"  Link: {link.name} - {link.entity_id}")

Multiple Analysis (Batch)

from azure.ai.textanalytics import (
    RecognizeEntitiesAction,
    ExtractKeyPhrasesAction,
    AnalyzeSentimentAction
)

documents = ["Microsoft announced new Azure AI features at Build conference."]

poller = client.begin_analyze_actions(
    documents,
    actions=[
        RecognizeEntitiesAction(),
        ExtractKeyPhrasesAction(),
        AnalyzeSentimentAction()
    ]
)

results = poller.result()
for doc_results in results:
    for result in doc_results:
        if result.kind == "EntityRecognition":
            print(f"Entities: {[e.text for e in result.entities]}")
        elif result.kind == "KeyPhraseExtraction":
            print(f"Key phrases: {result.key_phrases}")
        elif result.kind == "SentimentAnalysis":
            print(f"Sentiment: {result.sentiment}")

Async Client

from azure.ai.textanalytics.aio import TextAnalyticsClient
from azure.identity.aio import DefaultAzureCredential

async def analyze():
    async with DefaultAzureCredential() as credential:
        async with TextAnalyticsClient(
            endpoint=endpoint,
            credential=credential
        ) as client:
            result = await client.analyze_sentiment(documents)
            # Process results...

Client Types

Client	Purpose
TextAnalyticsClient	All text analytics operations
TextAnalyticsClient (aio)	Async version

Available Operations

Method	Description
analyze_sentiment	Sentiment analysis with opinion mining
recognize_entities	Named entity recognition
recognize_pii_entities	PII detection and redaction
recognize_linked_entities	Entity linking to Wikipedia
extract_key_phrases	Key phrase extraction
detect_language	Language detection
begin_analyze_healthcare_entities	Healthcare NLP (long-running)
begin_analyze_actions	Multiple analyses in batch