azure-ai-textanalytics-py

Azure AI Text Analytics SDK for sentiment analysis, entity recognition, key phrases, language detection, PII, and healthcare NLP. Use for natural language processing on text.

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Repository: bouclem/skills
Letzte Quellaktivität: 24. Mai 2026 um 16:04
Erkannte Sprache von SKILL.md: Englisch
Sterne: 7
Forks: 1

Installationsoptionen

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npx skills add https://github.com/bouclem/skills --skill azure-ai-textanalytics-py

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

client = TextAnalyticsClient(
    endpoint=os.environ["AZURE_LANGUAGE_ENDPOINT"],
    credential=DefaultAzureCredential()
)

documents = [
    "I had a wonderful trip to Seattle last week!",
    "The food was terrible and the service was slow."
]

result = client.analyze_sentiment(documents, show_opinion_mining=True)

for doc in result:
    if not doc.is_error:
        print(f"Sentiment: {doc.sentiment}")
        print(f"Scores: pos={doc.confidence_scores.positive:.2f}, "
              f"neg={doc.confidence_scores.negative:.2f}, "
              f"neu={doc.confidence_scores.neutral:.2f}")
        
        # Opinion mining (aspect-based sentiment)
        for sentence in doc.sentences:
            for opinion in sentence.mined_opinions:
                target = opinion.target
                print(f"  Target: '{target.text}' - {target.sentiment}")
                for assessment in opinion.assessments:
                    print(f"    Assessment: '{assessment.text}' - {assessment.sentiment}")

documents = ["Microsoft was founded by Bill Gates and Paul Allen in Albuquerque."]

result = client.recognize_entities(documents)

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"  Subcategory: {entity.subcategory}")
            print(f"  Confidence: {entity.confidence_score:.2f}")

documents = ["My SSN is 123-45-6789 and my email is john@example.com"]

result = client.recognize_pii_entities(documents)

for doc in result:
    if not doc.is_error:
        print(f"Redacted: {doc.redacted_text}")
        for entity in doc.entities:
            print(f"PII: {entity.text} ({entity.category})")

documents = ["Azure AI provides powerful machine learning capabilities for developers."]

result = client.extract_key_phrases(documents)

for doc in result:
    if not doc.is_error:
        print(f"Key phrases: {doc.key_phrases}")

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}")

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}")

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}")

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

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

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

name	azure-ai-textanalytics-py
description	Azure AI Text Analytics SDK for sentiment analysis, entity recognition, key phrases, language detection, PII, and healthcare NLP. Use for natural language processing on text.
risk	unknown
source	community
date_added	2026-02-27

name	azure-ai-textanalytics-py
description	Azure AI Text Analytics SDK for sentiment analysis, entity recognition, key phrases, language detection, PII, and healthcare NLP. Use for natural language processing on text.
risk	unknown
source	community
date_added	2026-02-27

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

azure-ai-textanalytics-py

Installationsoptionen

Quelldateien prüfen

Azure AI Text Analytics SDK for Python

Installation

Environment Variables

Authentication

API Key

Azure AI Text Analytics SDK for Python

Installation

Environment Variables

Authentication

API Key

Entra ID (Recommended)

Sentiment Analysis

Entity Recognition

PII Detection

Key Phrase Extraction

Language Detection

Healthcare Text Analytics

Multiple Analysis (Batch)

Async Client

Client Types

Available Operations

Best Practices

When to Use

Limitations

azure-ai-textanalytics-py

Quellinformationen

Installationsoptionen

Quelldateien prüfen

Mehr aus diesem Repository

Azure AI Text Analytics SDK for Python

Installation

Environment Variables

Authentication

API Key

Mehr aus diesem Repository

Azure AI Text Analytics SDK for Python

Installation

Environment Variables

Authentication

API Key

Entra ID (Recommended)

Sentiment Analysis

Entity Recognition

PII Detection

Key Phrase Extraction

Language Detection

Healthcare Text Analytics

Multiple Analysis (Batch)

Async Client

Client Types

Available Operations

Best Practices

When to Use

Limitations