from azure.ai.textanalytics import TextAnalyticsClient
from azure.core.credentials import AzureKeyCredential

client = TextAnalyticsClient(
    endpoint="https://<resource>.cognitiveservices.azure.com/",
    credential=AzureKeyCredential("<key>")
)

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

result = client.recognize_entities(documents)
for doc in result:
    for entity in doc.entities:
        print(f"{entity.text} ({entity.category})")

result = client.recognize_pii_entities(
    documents=["My SSN is 123-45-6789 and my email is [email protected]"],
    language="en"
)

for doc in result:
    for entity in doc.entities:
        print(f"PII: {entity.text} ({entity.category})")
    print(f"Redacted: {doc.redacted_text}")

result = client.analyze_sentiment(
    documents=["The food was excellent but the service was slow."],
    show_opinion_mining=True
)

for doc in result:
    print(f"Document sentiment: {doc.sentiment}")
    print(f"Positive: {doc.confidence_scores.positive}")
    print(f"Negative: {doc.confidence_scores.negative}")
    
    for sentence in doc.sentences:
        print(f"  Sentence: {sentence.text}")
        print(f"  Sentiment: {sentence.sentiment}")
        
        for opinion in sentence.mined_opinions:
            print(f"    Target: {opinion.target.text} ({opinion.target.sentiment})")

result = client.extract_key_phrases(
    documents=["Azure Language provides powerful NLP capabilities for analyzing text."]
)

for doc in result:
    print("Key phrases:")
    for phrase in doc.key_phrases:
        print(f"  - {phrase}")

result = client.detect_language(
    documents=["Bonjour, comment allez-vous?"]
)

for doc in result:
    print(f"Language: {doc.primary_language.name}")
    print(f"ISO code: {doc.primary_language.iso6391_name}")
    print(f"Confidence: {doc.primary_language.confidence_score}")

from azure.ai.textanalytics import ExtractiveSummaryAction

poller = client.begin_analyze_actions(
    documents=[long_document],
    actions=[ExtractiveSummaryAction(max_sentence_count=3)]
)

for result in poller.result():
    for summary_result in result:
        for sentence in summary_result.sentences:
            print(sentence.text)

from azure.ai.textanalytics import AbstractiveSummaryAction

poller = client.begin_analyze_actions(
    documents=[long_document],
    actions=[AbstractiveSummaryAction()]
)

for result in poller.result():
    for summary_result in result:
        for summary in summary_result.summaries:
            print(summary.text)

result = client.recognize_linked_entities(
    documents=["Microsoft was founded in Albuquerque."]
)

for doc in result:
    for entity in doc.entities:
        print(f"Name: {entity.name}")
        print(f"URL: {entity.url}")
        print(f"Data source: {entity.data_source}")

from azure.ai.textanalytics import HealthcareEntityRelation

poller = client.begin_analyze_healthcare_entities(
    documents=["Patient prescribed 50mg of ibuprofen for headache."]
)

for result in poller.result():
    for doc in result:
        for entity in doc.entities:
            print(f"{entity.text} ({entity.category})")
        
        for relation in doc.entity_relations:
            print(f"Relation: {relation.relation_type}")

from azure.ai.textanalytics import RecognizeCustomEntitiesAction

poller = client.begin_analyze_actions(
    documents=["Order #12345 shipped to warehouse A."],
    actions=[
        RecognizeCustomEntitiesAction(
            project_name="my-project",
            deployment_name="production"
        )
    ]
)

for result in poller.result():
    for entity_result in result:
        for entity in entity_result.entities:
            print(f"{entity.text} ({entity.category})")

from azure.ai.textanalytics import SingleLabelClassifyAction

poller = client.begin_analyze_actions(
    documents=["Customer requesting refund for damaged product."],
    actions=[
        SingleLabelClassifyAction(
            project_name="ticket-classifier",
            deployment_name="production"
        )
    ]
)

for result in poller.result():
    for classification_result in result:
        for classification in classification_result.classifications:
            print(f"Category: {classification.category}")
            print(f"Confidence: {classification.confidence_score}")

from azure.ai.language.conversations import ConversationAnalysisClient

clu_client = ConversationAnalysisClient(endpoint, credential)

result = clu_client.analyze_conversation(
    task={
        "kind": "Conversation",
        "analysisInput": {
            "conversationItem": {
                "text": "Book a flight to Seattle for next Friday",
                "id": "1",
                "participantId": "user"
            }
        },
        "parameters": {
            "projectName": "travel-assistant",
            "deploymentName": "production"
        }
    }
)

print(f"Intent: {result['result']['prediction']['topIntent']}")
for entity in result['result']['prediction']['entities']:
    print(f"Entity: {entity['category']} = {entity['text']}")

from azure.ai.language.questionanswering import QuestionAnsweringClient

qa_client = QuestionAnsweringClient(endpoint, credential)

response = qa_client.get_answers(
    question="What is Azure Language?",
    project_name="product-faq",
    deployment_name="production"
)

for answer in response.answers:
    print(f"Answer: {answer.answer}")
    print(f"Confidence: {answer.confidence}")