public async Task AnalyzeOperationAllActionsAndDisableServiceLogs()
{
TextAnalyticsClient client = GetClient();
TextAnalyticsActions batchActions = new TextAnalyticsActions()
{
ExtractKeyPhrasesActions = new List <ExtractKeyPhrasesAction>()
{
new ExtractKeyPhrasesAction()
{
DisableServiceLogs = true
}
},
RecognizeEntitiesActions = new List <RecognizeEntitiesAction>()
{
new RecognizeEntitiesAction()
{
DisableServiceLogs = true
}
},
RecognizePiiEntitiesActions = new List <RecognizePiiEntitiesAction>()
{
new RecognizePiiEntitiesAction()
{
DisableServiceLogs = false
}
},
RecognizeLinkedEntitiesActions = new List <RecognizeLinkedEntitiesAction>()
{
new RecognizeLinkedEntitiesAction()
{
DisableServiceLogs = true
}
},
AnalyzeSentimentActions = new List <AnalyzeSentimentAction>()
{
new AnalyzeSentimentAction()
{
DisableServiceLogs = true
}
},
};
AnalyzeActionsOperation operation = await client.StartAnalyzeActionsAsync(batchConvenienceDocuments, batchActions);
await operation.WaitForCompletionAsync();
//Take the first page
AnalyzeActionsResult resultCollection = operation.Value.ToEnumerableAsync().Result.FirstOrDefault();
IReadOnlyCollection <ExtractKeyPhrasesActionResult> keyPhrasesActionsResults = resultCollection.ExtractKeyPhrasesActionsResults;
IReadOnlyCollection <RecognizeEntitiesActionResult> entitiesActionsResults = resultCollection.RecognizeEntitiesActionsResults;
IReadOnlyCollection <RecognizePiiEntitiesActionResult> piiActionsResults = resultCollection.RecognizePiiEntitiesActionsResults;
IReadOnlyCollection <RecognizeLinkedEntitiesActionResult> entityLinkingActionsResults = resultCollection.RecognizeLinkedEntitiesActionsResults;
IReadOnlyCollection <AnalyzeSentimentActionResult> analyzeSentimentActionsResults = resultCollection.AnalyzeSentimentActionsResults;
Assert.IsNotNull(keyPhrasesActionsResults);
Assert.AreEqual(2, keyPhrasesActionsResults.FirstOrDefault().Result.Count);
Assert.IsNotNull(entitiesActionsResults);
Assert.AreEqual(2, entitiesActionsResults.FirstOrDefault().Result.Count);
Assert.IsNotNull(piiActionsResults);
Assert.AreEqual(2, piiActionsResults.FirstOrDefault().Result.Count);
Assert.IsNotNull(entityLinkingActionsResults);
Assert.AreEqual(2, entityLinkingActionsResults.FirstOrDefault().Result.Count);
Assert.IsNotNull(analyzeSentimentActionsResults);
Assert.AreEqual(2, analyzeSentimentActionsResults.FirstOrDefault().Result.Count);
}
public async Task RecognizeHealthcareEntitiesTestWithAssertions()
{
TextAnalyticsClient client = GetClient();
IReadOnlyCollection <string> batchDocuments = new List <string>()
{
"Baby not likely to have Meningitis. in case of fever in the mother, consider Penicillin for the baby too."
};
IReadOnlyCollection <string> expectedEntitiesOutput = new List <string>
{
"Baby",
"Meningitis",
"fever",
"mother",
"Penicillin",
"baby"
};
AnalyzeHealthcareEntitiesOperation operation = await client.StartAnalyzeHealthcareEntitiesAsync(batchDocuments);
await operation.WaitForCompletionAsync();
ValidateOperationProperties(operation);
List <AnalyzeHealthcareEntitiesResultCollection> resultInPages = operation.Value.ToEnumerableAsync().Result;
Assert.AreEqual(1, resultInPages.Count);
var resultCollection = resultInPages.FirstOrDefault();
Assert.AreEqual(batchDocuments.Count, resultCollection.Count);
AnalyzeHealthcareEntitiesResult result1 = resultCollection[0];
Assert.AreEqual(expectedEntitiesOutput.Count, result1.Entities.Count);
foreach (HealthcareEntity entity in result1.Entities)
{
Assert.IsTrue(expectedEntitiesOutput.Contains(entity.Text));
if (entity.Text == "Baby")
{
var linksList = new List <string> {
"UMLS", "AOD", "CCPSS", "CHV", "DXP", "LCH", "LCH_NW", "LNC", "MDR", "MSH", "NCI", "NCI_FDA", "NCI_NICHD", "SNOMEDCT_US"
};
foreach (EntityDataSource entityDataSource in entity.DataSources)
{
Assert.IsTrue(linksList.Contains(entityDataSource.Name));
}
Assert.AreEqual("Infant", entity.NormalizedText);
}
if (entity.Text == "Meningitis")
{
Assert.AreEqual(24, entity.Offset);
Assert.AreEqual("Diagnosis", entity.Category);
Assert.AreEqual(10, entity.Length);
Assert.IsNotNull(entity.Assertion);
Assert.AreEqual(EntityCertainty.NegativePossible, entity.Assertion.Certainty.Value);
}
if (entity.Text == "Penicillin")
{
Assert.AreEqual("MedicationName", entity.Category);
Assert.AreEqual(10, entity.Length);
Assert.IsNotNull(entity.Assertion);
Assert.AreEqual(EntityCertainty.NeutralPossible, entity.Assertion.Certainty.Value);
}
}
}
public void AnalyzeHealthcareEntitiesConvenience()
{
// create a text analytics client
string endpoint = TestEnvironment.Endpoint;
string apiKey = TestEnvironment.ApiKey;
var client = new TextAnalyticsClient(new Uri(endpoint), new AzureKeyCredential(apiKey), CreateSampleOptions());
#region Snippet:TextAnalyticsAnalyzeHealthcareEntitiesConvenience
// get input documents
string document1 = @"RECORD #333582770390100 | MH | 85986313 | | 054351 | 2/14/2001 12:00:00 AM | CORONARY ARTERY DISEASE | Signed | DIS | \
Admission Date: 5/22/2001 Report Status: Signed Discharge Date: 4/24/2001 ADMISSION DIAGNOSIS: CORONARY ARTERY DISEASE. \
HISTORY OF PRESENT ILLNESS: The patient is a 54-year-old gentleman with a history of progressive angina over the past several months. \
The patient had a cardiac catheterization in July of this year revealing total occlusion of the RCA and 50% left main disease ,\
with a strong family history of coronary artery disease with a brother dying at the age of 52 from a myocardial infarction and \
another brother who is status post coronary artery bypass grafting. The patient had a stress echocardiogram done on July , 2001 , \
which showed no wall motion abnormalities , but this was a difficult study due to body habitus. The patient went for six minutes with \
minimal ST depressions in the anterior lateral leads , thought due to fatigue and wrist pain , his anginal equivalent. Due to the patient's \
increased symptoms and family history and history left main disease with total occasional of his RCA was referred for revascularization with open heart surgery.";
string document2 = "Prescribed 100mg ibuprofen, taken twice daily.";
// prepare analyze operation input
List <string> batchInput = new List <string>()
{
document1,
document2
};
// start analysis process
AnalyzeHealthcareEntitiesOperation healthOperation = client.StartAnalyzeHealthcareEntities(batchInput);
// wait for completion with manual polling
TimeSpan pollingInterval = new TimeSpan(1000);
while (true)
{
Console.WriteLine($"Status: {healthOperation.Status}");
healthOperation.UpdateStatus();
if (healthOperation.HasCompleted)
{
break;
}
Thread.Sleep(pollingInterval);
}
Console.WriteLine($"AnalyzeHealthcareEntities operation was completed");
#endregion Snippet:TextAnalyticsAnalyzeHealthcareEntitiesConvenience
// view operation status
Console.WriteLine($" Created On : {healthOperation.CreatedOn}");
Console.WriteLine($" Expires On : {healthOperation.ExpiresOn}");
Console.WriteLine($" Status : {healthOperation.Status}");
Console.WriteLine($" Last Modified: {healthOperation.LastModified}");
// view operation results
foreach (AnalyzeHealthcareEntitiesResultCollection documentsInPage in healthOperation.GetValues())
{
Console.WriteLine($"Results of \"Healthcare\" Model, version: \"{documentsInPage.ModelVersion}\"");
Console.WriteLine("");
foreach (AnalyzeHealthcareEntitiesResult result in documentsInPage)
{
if (result.HasError)
{
Console.WriteLine(" Error!");
Console.WriteLine($" Document error code: {result.Error.ErrorCode}.");
Console.WriteLine($" Message: {result.Error.Message}");
}
else
{
Console.WriteLine($" Recognized the following {result.Entities.Count} healthcare entities:");
// view recognized healthcare entities
foreach (HealthcareEntity entity in result.Entities)
{
Console.WriteLine($" Entity: {entity.Text}");
Console.WriteLine($" Category: {entity.Category}");
Console.WriteLine($" Offset: {entity.Offset}");
Console.WriteLine($" Length: {entity.Length}");
Console.WriteLine($" NormalizedText: {entity.NormalizedText}");
Console.WriteLine($" Links:");
// view entity data sources
foreach (EntityDataSource entityDataSource in entity.DataSources)
{
Console.WriteLine($" Entity ID in Data Source: {entityDataSource.EntityId}");
Console.WriteLine($" DataSource: {entityDataSource.Name}");
}
// view assertion
if (entity.Assertion != null)
{
Console.WriteLine($" Assertions:");
if (entity.Assertion?.Association != null)
{
Console.WriteLine($" Association: {entity.Assertion?.Association}");
}
if (entity.Assertion?.Certainty != null)
{
Console.WriteLine($" Certainty: {entity.Assertion?.Certainty}");
}
if (entity.Assertion?.Conditionality != null)
{
Console.WriteLine($" Conditionality: {entity.Assertion?.Conditionality}");
}
}
Console.WriteLine($" We found {result.EntityRelations.Count} relations in the current document:");
Console.WriteLine("");
// view recognized healthcare relations
foreach (HealthcareEntityRelation relations in result.EntityRelations)
{
Console.WriteLine($" Relation: {relations.RelationType}");
Console.WriteLine($" For this relation there are {relations.Roles.Count} roles");
// view relation roles
foreach (HealthcareEntityRelationRole role in relations.Roles)
{
Console.WriteLine($" Role Name: {role.Name}");
Console.WriteLine($" Associated Entity Text: {role.Entity.Text}");
Console.WriteLine($" Associated Entity Category: {role.Entity.Category}");
Console.WriteLine("");
}
Console.WriteLine("");
}
}
Console.WriteLine("");
}
}
}
}
public async Task DetectLanguageBatchAsync()
{
string endpoint = TestEnvironment.Endpoint;
string apiKey = TestEnvironment.ApiKey;
// Instantiate a client that will be used to call the service.
var client = new TextAnalyticsClient(new Uri(endpoint), new AzureKeyCredential(apiKey));
var documents = new List <DetectLanguageInput>
{
new DetectLanguageInput("1", "Hello world")
{
CountryHint = "us",
},
new DetectLanguageInput("2", "Bonjour tout le monde")
{
CountryHint = "fr",
},
new DetectLanguageInput("3", "Hola mundo")
{
CountryHint = "es",
},
new DetectLanguageInput("4", ":) :( :D")
{
CountryHint = DetectLanguageInput.None,
}
};
DetectLanguageResultCollection results = await client.DetectLanguageBatchAsync(documents, new TextAnalyticsRequestOptions { IncludeStatistics = true });
int i = 0;
Console.WriteLine($"Results of Azure Text Analytics \"Detect Language\" Model, version: \"{results.ModelVersion}\"");
Console.WriteLine("");
foreach (DetectLanguageResult result in results)
{
DetectLanguageInput document = documents[i++];
Console.WriteLine($"On document (Id={document.Id}, CountryHint=\"{document.CountryHint}\", Text=\"{document.Text}\"):");
if (result.HasError)
{
Console.WriteLine($" Document error code: {result.Error.Code}.");
Console.WriteLine($" Message: {result.Error.Message}.");
}
else
{
Console.WriteLine($" Detected language {result.PrimaryLanguage.Name} with confidence score {result.PrimaryLanguage.ConfidenceScore}.");
Console.WriteLine($" Document statistics:");
Console.WriteLine($" Character count (in Unicode graphemes): {result.Statistics.CharacterCount}");
Console.WriteLine($" Transaction count: {result.Statistics.TransactionCount}");
Console.WriteLine("");
}
}
Console.WriteLine($"Batch operation statistics:");
Console.WriteLine($" Document count: {results.Statistics.DocumentCount}");
Console.WriteLine($" Valid document count: {results.Statistics.ValidDocumentCount}");
Console.WriteLine($" Invalid document count: {results.Statistics.InvalidDocumentCount}");
Console.WriteLine($" Transaction count: {results.Statistics.TransactionCount}");
Console.WriteLine("");
}
public void AnalyzeSentimentBatchAdvanced()
{
string endpoint = Environment.GetEnvironmentVariable("TEXT_ANALYTICS_ENDPOINT");
string subscriptionKey = Environment.GetEnvironmentVariable("TEXT_ANALYTICS_SUBSCRIPTION_KEY");
// Instantiate a client that will be used to call the service.
var client = new TextAnalyticsClient(new Uri(endpoint), subscriptionKey);
var inputs = new List <DocumentInput>
{
new DocumentInput("1")
{
Language = "en",
Text = "That was the best day of my life!"
},
new DocumentInput("2")
{
Language = "en",
Text = "This food is very bad. Everyone who ate with us got sick."
},
new DocumentInput("3")
{
Language = "en",
Text = "I'm not sure how I feel about this product.",
},
new DocumentInput("4")
{
Language = "en",
Text = "Pike Place Market is my favorite Seattle attraction. We had so much fun there."
}
};
SentimentResultCollection results = client.AnalyzeSentiment(inputs, new TextAnalyticsRequestOptions(showStatistics: true)).Value;
int i = 0;
Debug.WriteLine($"Results of Azure Text Analytics \"Sentiment Analysis\" Model, version: \"{results.ModelVersion}\"");
Debug.WriteLine("");
foreach (var result in results)
{
var document = inputs[i++];
Debug.WriteLine($"On document (Id={document.Id}, Language=\"{document.Language}\", Text=\"{document.Text}\"):");
Debug.WriteLine($"Document sentiment is {result.DocumentSentiment.SentimentClass.ToString()}, with scores: ");
Debug.WriteLine($" Positive score: {result.DocumentSentiment.PositiveScore:0.00}.");
Debug.WriteLine($" Neutral score: {result.DocumentSentiment.NeutralScore:0.00}.");
Debug.WriteLine($" Negative score: {result.DocumentSentiment.NegativeScore:0.00}.");
Debug.WriteLine($" Sentence sentiment results:");
foreach (var sentenceSentiment in result.SentenceSentiments)
{
Debug.WriteLine($" On sentence \"{document.Text.Substring(sentenceSentiment.Offset, sentenceSentiment.Length)}\"");
Debug.WriteLine($" Sentiment is {sentenceSentiment.SentimentClass.ToString()}, with scores: ");
Debug.WriteLine($" Positive score: {sentenceSentiment.PositiveScore:0.00}.");
Debug.WriteLine($" Neutral score: {sentenceSentiment.NeutralScore:0.00}.");
Debug.WriteLine($" Negative score: {sentenceSentiment.NegativeScore:0.00}.");
}
Debug.WriteLine($" Document statistics:");
Debug.WriteLine($" Character count: {result.Statistics.CharacterCount}");
Debug.WriteLine($" Transaction count: {result.Statistics.TransactionCount}");
Debug.WriteLine("");
}
Debug.WriteLine($"Batch operation statistics:");
Debug.WriteLine($" Document count: {results.Statistics.DocumentCount}");
Debug.WriteLine($" Valid document count: {results.Statistics.ValidDocumentCount}");
Debug.WriteLine($" Invalid document count:{results.Statistics.InvalidDocumentCount}");
Debug.WriteLine($" Transaction count:{results.Statistics.TransactionCount}");
Debug.WriteLine("");
}
public void AnalyzeSentimentBatch()
{
string endpoint = Environment.GetEnvironmentVariable("TEXT_ANALYTICS_ENDPOINT");
string apiKey = Environment.GetEnvironmentVariable("TEXT_ANALYTICS_API_KEY");
// Instantiate a client that will be used to call the service.
var client = new TextAnalyticsClient(new Uri(endpoint), new AzureKeyCredential(apiKey));
#region Snippet:TextAnalyticsSample2AnalyzeSentimentBatch
var inputs = new List <TextDocumentInput>
{
new TextDocumentInput("1", "That was the best day of my life!")
{
Language = "en",
},
new TextDocumentInput("2", "This food is very bad. Everyone who ate with us got sick.")
{
Language = "en",
},
new TextDocumentInput("3", "I'm not sure how I feel about this product.")
{
Language = "en",
},
new TextDocumentInput("4", "Pike Place Market is my favorite Seattle attraction. We had so much fun there.")
{
Language = "en",
}
};
AnalyzeSentimentResultCollection results = client.AnalyzeSentimentBatch(inputs, new TextAnalyticsRequestOptions {
IncludeStatistics = true
});
#endregion
int i = 0;
Debug.WriteLine($"Results of Azure Text Analytics \"Sentiment Analysis\" Model, version: \"{results.ModelVersion}\"");
Debug.WriteLine("");
foreach (AnalyzeSentimentResult result in results)
{
TextDocumentInput document = inputs[i++];
Debug.WriteLine($"On document (Id={document.Id}, Language=\"{document.Language}\", Text=\"{document.Text}\"):");
if (result.HasError)
{
Debug.WriteLine($" Document error: {result.Error.Code}.");
Debug.WriteLine($" Message: {result.Error.Message}.");
}
else
{
Debug.WriteLine($"Document sentiment is {result.DocumentSentiment.Sentiment}, with confidence scores: ");
Debug.WriteLine($" Positive confidence score: {result.DocumentSentiment.ConfidenceScores.Positive}.");
Debug.WriteLine($" Neutral confidence score: {result.DocumentSentiment.ConfidenceScores.Neutral}.");
Debug.WriteLine($" Negative confidence score: {result.DocumentSentiment.ConfidenceScores.Negative}.");
Debug.WriteLine($" Sentence sentiment results:");
foreach (SentenceSentiment sentenceSentiment in result.DocumentSentiment.Sentences)
{
Debug.WriteLine($" Sentiment is {sentenceSentiment.Sentiment}, with confidence scores: ");
Debug.WriteLine($" Positive confidence score: {sentenceSentiment.ConfidenceScores.Positive}.");
Debug.WriteLine($" Neutral confidence score: {sentenceSentiment.ConfidenceScores.Neutral}.");
Debug.WriteLine($" Negative confidence score: {sentenceSentiment.ConfidenceScores.Negative}.");
}
Debug.WriteLine($" Document statistics:");
Debug.WriteLine($" Character count (in Unicode graphemes): {result.Statistics.GraphemeCount}");
Debug.WriteLine($" Transaction count: {result.Statistics.TransactionCount}");
Debug.WriteLine("");
}
}
Debug.WriteLine($"Batch operation statistics:");
Debug.WriteLine($" Document count: {results.Statistics.DocumentCount}");
Debug.WriteLine($" Valid document count: {results.Statistics.ValidDocumentCount}");
Debug.WriteLine($" Invalid document count: {results.Statistics.InvalidDocumentCount}");
Debug.WriteLine($" Transaction count: {results.Statistics.TransactionCount}");
Debug.WriteLine("");
}
protected override async Task ExecuteAsync(CancellationToken stoppingToken)
{
try
{
var logEntry = new LogEntry();
var options = new JsonSerializerOptions
{
WriteIndented = false
};
options.Converters.Add(new JsonStringEnumConverter(JsonNamingPolicy.CamelCase));
//var configurationBuilder = new ConfigurationBuilder().AddUserSecrets();
// var configuration = configurationBuilder.Build();
var hashTags = _configuration.GetValue <string>("HashTags").Split(",").ToList();
var users = _configuration.GetValue <string>("Users").Split(",").ToList();
var blockedWords = _configuration.GetValue <string>("BlockedWords").Split(",").ToList();
var blockedUsers = _configuration.GetValue <string>("BlockedUsers").Split(",").ToList();
var userCredentials = new TwitterCredentials(
_configuration.GetValue <string>("Twitter:ApiKey"),
_configuration.GetValue <string>("Twitter:ApiSecret"),
_configuration.GetValue <string>("Twitter:AccessToken"),
_configuration.GetValue <string>("Twitter:AccessSecret")
);
var textAnalyticsClient = new TextAnalyticsClient(
new Uri(_configuration.GetValue <string>("Azure:TextAnalyticsURI")),
new AzureKeyCredential(_configuration.GetValue <string>("Azure:TextAnalyticsKey"))
);
var userClient = new TwitterClient(userCredentials);
var stream = userClient.Streams.CreateFilteredStream();
stream.AddLanguageFilter(LanguageFilter.English);
stream.FilterLevel = StreamFilterLevel.Low;
foreach (var hashTag in hashTags)
{
stream.AddTrack(hashTag);
}
foreach (var user in users)
{
var twitterUser = await userClient.Users.GetUserAsync(user);
stream.AddFollow(twitterUser);
}
stream.MatchingTweetReceived += (sender, eventReceived) =>
{
ITweet tweet = eventReceived.Tweet;
string textToAnalyze = tweet.FullText ?? tweet.Text;
foreach (var blockedWord in blockedWords)
{
if (textToAnalyze.ToLower().Contains(blockedWord.ToLower()))
{
return;
}
}
if (blockedUsers.Contains(tweet.CreatedBy.ScreenName))
{
return;
}
foreach (var blockedWord in blockedWords)
{
if (textToAnalyze.ToLower().Contains(blockedWord.ToLower()))
{
return;
}
}
if (eventReceived.Tweet.IsRetweet)
{
return;
}
if (eventReceived.Tweet.CreatedBy.CreatedAt > DateTime.Now.AddMonths(-1))
{
return;
}
if (eventReceived.Tweet.CreatedBy.FollowersCount < 100)
{
return;
}
if (eventReceived.MatchingFollowers.Length > 0 && eventReceived.MatchingFollowers.Contains(tweet.CreatedBy.Id) == false)
{
return;
}
//_logger.LogInformation("Matching tweet: {time}, {text}", DateTimeOffset.Now, textToAnalyze.Replace(Environment.NewLine,""));
var connStr = _configuration.GetConnectionString("DefaultConnection");
var optionsBuilder = new DbContextOptionsBuilder <ApplicationDbContext>();
optionsBuilder.UseSqlServer(connStr);
hashTags = _configuration.GetValue <string>("HashTags").Split(",").ToList();
foreach (var hashTag in hashTags)
{
textToAnalyze = textToAnalyze.Replace(hashTag, "");
}
DocumentSentiment documentSentiment = null;
TweetSentiment tweetSentiment = new TweetSentiment();
List <SentimentDetail> sentimentDetails = new List <SentimentDetail>();
List <TweetEntity> listEntities = new List <TweetEntity>();
List <TweetKeyPhrase> listKeyPhrases = new List <TweetKeyPhrase>();
//_logger.LogInformation("Analyzing sentiment: {time}", DateTimeOffset.Now);
documentSentiment = textAnalyticsClient.AnalyzeSentiment(textToAnalyze);
logEntry.Sentiment = JsonSerializer.Serialize(documentSentiment, options);
//_logger.LogInformation("Sentiment: {time}", documentSentiment.Sentiment);
tweetSentiment = new TweetSentiment
{
IsPositive = (eventReceived.MatchingFollowers.Contains(tweet.CreatedBy.Id) && documentSentiment.Sentiment != TextSentiment.Negative) || (documentSentiment.Sentiment == TextSentiment.Positive) && (!documentSentiment.Sentences.Where(s => s.Sentiment == TextSentiment.Mixed || s.Sentiment == TextSentiment.Negative).Any()),
TweetContent = textToAnalyze,
TweetedBy = 0,
TweetedOn = DateTime.Now,
TweetID = tweet.Id
};
foreach (var sentence in documentSentiment.Sentences)
{
var sentimentDetail = new SentimentDetail()
{
Sentence = sentence.Text,
Positive = sentence.ConfidenceScores.Positive,
Negative = sentence.ConfidenceScores.Negative,
Neutral = sentence.ConfidenceScores.Neutral,
TweetID = tweet.Id,
Sentiment = sentence.Sentiment.ToString()
};
sentimentDetails.Add(sentimentDetail);
}
logEntry.Details = JsonSerializer.Serialize(sentimentDetails, options);
var responseEntities = textAnalyticsClient.RecognizeEntities(textToAnalyze);
foreach (var entity in responseEntities.Value)
{
var tweetEntity = new TweetEntity
{
EntityText = entity.Text,
Category = entity.Category.ToString(),
SubCategory = entity.SubCategory,
Confidence = entity.ConfidenceScore,
TweetID = tweet.Id
};
listEntities.Add(tweetEntity);
}
logEntry.Entities = JsonSerializer.Serialize(listEntities);
var responseKeyPhrases = textAnalyticsClient.ExtractKeyPhrases(textToAnalyze);
foreach (string keyphrase in responseKeyPhrases.Value)
{
var tweetKeyPhrase = new TweetKeyPhrase
{
TweetID = tweet.Id,
KeyPhrase = keyphrase
};
listKeyPhrases.Add(tweetKeyPhrase);
}
logEntry.Phrases = JsonSerializer.Serialize(listKeyPhrases, options);
using (ApplicationDbContext db = new ApplicationDbContext(optionsBuilder.Options))
{
//_logger.LogWarning("Saving tweet: {time}", DateTimeOffset.Now);
db.TweetSentiments.Add(tweetSentiment);
db.SentimentDetails.AddRange(sentimentDetails);
db.TweetEntities.AddRange(listEntities);
db.TweetKeyPhrases.AddRange(listKeyPhrases);
db.SaveChanges();
}
if (tweetSentiment.IsPositive)
{
eventReceived.Tweet.FavoriteAsync();
eventReceived.Tweet.PublishRetweetAsync();
}
_logger.LogInformation(@$ "{logEntry.Sentiment} {logEntry.Details} {logEntry.Entities} {logEntry.Phrases}");
};
stream.StreamStopped += (sender, eventReceived) =>
{
stream.StartMatchingAnyConditionAsync();
};
_ = stream.StartMatchingAnyConditionAsync();
while (!stoppingToken.IsCancellationRequested)
{
await Task.Delay(1000, stoppingToken);
}
}
catch (OperationCanceledException)
{
_logger.LogWarning("Worker process was cancelled");
Environment.ExitCode = 0;
}
catch (Exception ex)
{
_logger.LogError(ex, "Worker process caught exception");
Environment.ExitCode = 0;
}
finally
{
// No matter what happens (success or exception), we need to indicate that it's time to stop the application.
applicationLifetime.StopApplication();
}
}
public async Task RecognizePiiEntitiesBatchConvenienceAsync()
{
string endpoint = TestEnvironment.Endpoint;
string apiKey = TestEnvironment.ApiKey;
// Instantiate a client that will be used to call the service.
var client = new TextAnalyticsClient(new Uri(endpoint), new AzureKeyCredential(apiKey), CreateSampleOptions());
string documentA = @"Parker Doe has repaid all of their loans as of 2020-04-25.
Their SSN is 859-98-0987. To contact them, use their phone number 800-102-1100.
They are originally from Brazil and have document ID number 998.214.865-68";
string documentB = @"Yesterday, Dan Doe was asking where they could find the ABA number. I explained
that it is the first 9 digits in the lower left hand corner of their personal check.
After looking at their account they confirmed the number was 111000025";
string documentC = string.Empty;
var documents = new List <string>
{
documentA,
documentB,
documentC
};
Response <RecognizePiiEntitiesResultCollection> response = await client.RecognizePiiEntitiesBatchAsync(documents);
RecognizePiiEntitiesResultCollection entititesPerDocuments = response.Value;
int i = 0;
Console.WriteLine($"Results of \"PII Entity Recognition\" Model, version: \"{entititesPerDocuments.ModelVersion}\"");
Console.WriteLine("");
foreach (RecognizePiiEntitiesResult piiEntititesInDocument in entititesPerDocuments)
{
Console.WriteLine($"On document with Text: \"{documents[i++]}\"");
Console.WriteLine("");
if (piiEntititesInDocument.HasError)
{
Console.WriteLine(" Error!");
Console.WriteLine($" Document error code: {piiEntititesInDocument.Error.ErrorCode}.");
Console.WriteLine($" Message: {piiEntititesInDocument.Error.Message}");
}
else
{
Console.WriteLine($" Redacted Text: {piiEntititesInDocument.Entities.RedactedText}");
Console.WriteLine("");
Console.WriteLine($" Recognized {piiEntititesInDocument.Entities.Count} PII entities:");
foreach (PiiEntity piiEntity in piiEntititesInDocument.Entities)
{
Console.WriteLine($" Text: {piiEntity.Text}");
Console.WriteLine($" Category: {piiEntity.Category}");
if (!string.IsNullOrEmpty(piiEntity.SubCategory))
{
Console.WriteLine($" SubCategory: {piiEntity.SubCategory}");
}
Console.WriteLine($" Confidence score: {piiEntity.ConfidenceScore}");
Console.WriteLine("");
}
}
Console.WriteLine("");
}
}
public static async Task <IActionResult> Run(
[HttpTrigger(AuthorizationLevel.Function, "get", "post", Route = null)] HttpRequest req,
ILogger log)
{
string cognitive_service_key = Environment.GetEnvironmentVariable("cognitive_service_key");
string cognitive_service_endpoint = Environment.GetEnvironmentVariable("cognitive_service_endpoint");
int SentencesToSummarize = 3;
string requestBody = await new StreamReader(req.Body).ReadToEndAsync();
dynamic data = JsonConvert.DeserializeObject(requestBody);
string inputText = data.text;
var credentials = new ApiKeyServiceClientCredentials(cognitive_service_key);
var client = new TextAnalyticsClient(credentials)
{
Endpoint = cognitive_service_endpoint
};
dynamic result = new JObject();
//Detecting language first
var inputDocuments = new LanguageBatchInput(
new List <LanguageInput>
{
new LanguageInput(id: "1", text: inputText)
});
var langResults = await client.DetectLanguageAsync(false, inputDocuments);
string inputLanguage = null;
foreach (var document in langResults.Documents)
{
inputLanguage = document.DetectedLanguages[0].Iso6391Name;
}
result.language = inputLanguage;
log.LogInformation($"{result.ToString()}");
//Detecting sentiment of the input text
var inputDocuments2 = new MultiLanguageBatchInput(
new List <MultiLanguageInput>
{
new MultiLanguageInput(inputLanguage, "1", inputText)
});
var sentimentResult = await client.SentimentAsync(false, inputDocuments2);
double?sentimentScore = 0;
foreach (var document in sentimentResult.Documents)
{
sentimentScore = document.Score;
}
result.sentimentScore = sentimentScore;
log.LogInformation($"{result.ToString()}");
//Detecting entities in the text
var entitiesResult = await client.EntitiesAsync(false, inputDocuments2);
JArray entities = new JArray();
foreach (var document in entitiesResult.Documents)
{
dynamic entityObject = new JObject();
foreach (var entity in document.Entities)
{
entityObject.name = entity.Name;
entityObject.type = entity.Type;
entityObject.subtype = entity.SubType;
foreach (var match in entity.Matches)
{
entityObject.offset = match.Offset;
entityObject.length = match.Length;
entityObject.score = match.EntityTypeScore;
//log.LogInformation($"\t\t\tOffset: {match.Offset},\tLength: {match.Length},\tScore: {match.EntityTypeScore:F3}");
}
entities.Add(entityObject);
}
}
result.entities = entities;
log.LogInformation($"{result.ToString()}");
//Detecting keyphrases
var kpResults = await client.KeyPhrasesAsync(false, inputDocuments2);
JArray keyPhrases = new JArray();
var Phrases = new List <string>();
// Printing keyphrases
foreach (var document in kpResults.Documents)
{
foreach (string keyphrase in document.KeyPhrases)
{
keyPhrases.Add(keyphrase);
Phrases.Add(keyphrase);
}
}
result.keyphrases = keyPhrases;
//Generating text summary
String[] sentences = inputText.Split('!', '.', '?');
List <Match> matchList = new List <Match>();
int counter = 0;
// Take the 10 best words
var topPhrases = Phrases.Take(10);
foreach (var sentence in sentences)
{
double count = 0;
Match match = new Match();
foreach (var phrase in topPhrases)
{
if ((sentence.ToLower().IndexOf(phrase) > -1) &&
(sentence.Length > 20) && (WordCount(sentence) >= 3))
{
count++;
}
;
}
if (count > 0)
{
matchList.Add(new Match {
sentence = counter, total = count
});
}
counter++;
}
var MatchList = matchList.OrderByDescending(y => y.total).Take(SentencesToSummarize).OrderBy(x => x.sentence).ToList();
StringBuilder summary = new StringBuilder();
List <string> SentenceList = new List <string>();
int sentenceCount = 0;
for (int i = 0; i < MatchList.Count; i++)
{
summary.Append(sentences[MatchList[i].sentence] + ".");
sentenceCount++;
}
// If there are no sentences found, just take the first three
if (sentenceCount == 0)
{
for (int i = 0; i < Math.Min(SentencesToSummarize, sentences.Count()); i++)
{
summary.Append(sentences[MatchList[i].sentence] + ".");
}
}
result.summary = summary.ToString();
log.LogInformation($"{result.ToString()}");
return(inputText != null
? (ActionResult) new OkObjectResult($"{result.ToString()}")
: new BadRequestObjectResult("{ \"error\": \"Please pass the text input for the text analytics operations\""));
}
public async Task ExtractEntityLinkingBatchAsync()
{
string endpoint = TestEnvironment.Endpoint;
string apiKey = TestEnvironment.ApiKey;
// Instantiate a client that will be used to call the service.
var client = new TextAnalyticsClient(new Uri(endpoint), new AzureKeyCredential(apiKey));
var documents = new List <TextDocumentInput>
{
new TextDocumentInput("1", "Microsoft was founded by Bill Gates and Paul Allen.")
{
Language = "en",
},
new TextDocumentInput("2", "Text Analytics is one of the Azure Cognitive Services.")
{
Language = "en",
},
new TextDocumentInput("3", "Pike place market is my favorite Seattle attraction.")
{
Language = "en",
}
};
RecognizeLinkedEntitiesResultCollection results = await client.RecognizeLinkedEntitiesBatchAsync(documents, new TextAnalyticsRequestOptions { IncludeStatistics = true });
int i = 0;
Console.WriteLine($"Results of Azure Text Analytics \"Entity Linking\", version: \"{results.ModelVersion}\"");
Console.WriteLine("");
foreach (RecognizeLinkedEntitiesResult result in results)
{
TextDocumentInput document = documents[i++];
Console.WriteLine($"On document (Id={document.Id}, Language=\"{document.Language}\", Text=\"{document.Text}\"):");
if (result.HasError)
{
Console.WriteLine($" Document error code: {result.Error.ErrorCode}.");
Console.WriteLine($" Message: {result.Error.Message}.");
}
else
{
Console.WriteLine($" Extracted the following {result.Entities.Count()} linked entities:");
foreach (LinkedEntity linkedEntity in result.Entities)
{
Console.WriteLine($" Name: \"{linkedEntity.Name}\", Language: {linkedEntity.Language}, Data Source: {linkedEntity.DataSource}, Url: {linkedEntity.Url.ToString()}, Entity Id in Data Source: \"{linkedEntity.DataSourceEntityId}\"");
foreach (LinkedEntityMatch match in linkedEntity.Matches)
{
Console.WriteLine($" Match Text: \"{match.Text}\", Offset (in UTF-16 code units): {match.Offset}");
Console.WriteLine($" Confidence score: {match.ConfidenceScore}");
}
}
Console.WriteLine($" Document statistics:");
Console.WriteLine($" Character count (in Unicode graphemes): {result.Statistics.CharacterCount}");
Console.WriteLine($" Transaction count: {result.Statistics.TransactionCount}");
Console.WriteLine("");
}
}
Console.WriteLine($"Batch operation statistics:");
Console.WriteLine($" Document count: {results.Statistics.DocumentCount}");
Console.WriteLine($" Valid document count: {results.Statistics.ValidDocumentCount}");
Console.WriteLine($" Invalid document count: {results.Statistics.InvalidDocumentCount}");
Console.WriteLine($" Transaction count: {results.Statistics.TransactionCount}");
Console.WriteLine("");
}
public async Task Sample7_AnalyzeHealthcareEntitiesBatchAsync_AutomaticPolling()
{
// create a text analytics client
string endpoint = TestEnvironment.Endpoint;
string apiKey = TestEnvironment.ApiKey;
var client = new TextAnalyticsClient(new Uri(endpoint), new AzureKeyCredential(apiKey));
#region Snippet:RecognizeHealthcareEntitiesAsyncAutomaticPolling
// get input documents
string document1 = @"RECORD #333582770390100 | MH | 85986313 | | 054351 | 2/14/2001 12:00:00 AM | CORONARY ARTERY DISEASE | Signed | DIS | \
Admission Date: 5/22/2001 Report Status: Signed Discharge Date: 4/24/2001 ADMISSION DIAGNOSIS: CORONARY ARTERY DISEASE. \
HISTORY OF PRESENT ILLNESS: The patient is a 54-year-old gentleman with a history of progressive angina over the past several months. \
The patient had a cardiac catheterization in July of this year revealing total occlusion of the RCA and 50% left main disease ,\
with a strong family history of coronary artery disease with a brother dying at the age of 52 from a myocardial infarction and \
another brother who is status post coronary artery bypass grafting. The patient had a stress echocardiogram done on July , 2001 , \
which showed no wall motion abnormalities , but this was a difficult study due to body habitus. The patient went for six minutes with \
minimal ST depressions in the anterior lateral leads , thought due to fatigue and wrist pain , his anginal equivalent. Due to the patient's \
increased symptoms and family history and history left main disease with total occasional of his RCA was referred for revascularization with open heart surgery.";
string document2 = "Prescribed 100mg ibuprofen, taken twice daily.";
// prepare analyze operation input
List <TextDocumentInput> batchInput = new List <TextDocumentInput>()
{
new TextDocumentInput("1", document1)
{
Language = "en"
},
new TextDocumentInput("2", document2)
{
Language = "en"
}
};
AnalyzeHealthcareEntitiesOptions options = new AnalyzeHealthcareEntitiesOptions()
{
IncludeStatistics = true
};
// start analysis process
AnalyzeHealthcareEntitiesOperation healthOperation = await client.StartAnalyzeHealthcareEntitiesAsync(batchInput, options);
// wait for operation completion with automatic polling
TimeSpan pollingInterval = new TimeSpan(1000);
await healthOperation.WaitForCompletionAsync(pollingInterval);
// view operation results
await foreach (AnalyzeHealthcareEntitiesResultCollection documentsInPage in healthOperation.Value)
{
Console.WriteLine($"Results of Azure Text Analytics \"Healthcare Async\" Model, version: \"{documentsInPage.ModelVersion}\"");
Console.WriteLine("");
foreach (AnalyzeHealthcareEntitiesResult result in documentsInPage)
{
Console.WriteLine($" Recognized the following {result.Entities.Count} healthcare entities:");
// view recognized healthcare entities
foreach (HealthcareEntity entity in result.Entities)
{
Console.WriteLine($" Entity: {entity.Text}");
Console.WriteLine($" Category: {entity.Category}");
Console.WriteLine($" Offset: {entity.Offset}");
Console.WriteLine($" Length: {entity.Length}");
Console.WriteLine($" NormalizedText: {entity.NormalizedText}");
Console.WriteLine($" Links:");
// view entity data sources
foreach (EntityDataSource entityDataSource in entity.DataSources)
{
Console.WriteLine($" Entity ID in Data Source: {entityDataSource.EntityId}");
Console.WriteLine($" DataSource: {entityDataSource.Name}");
}
// view assertion
if (entity.Assertion != null)
{
Console.WriteLine($" Assertions:");
if (entity.Assertion?.Association != null)
{
Console.WriteLine($" Association: {entity.Assertion?.Association}");
}
if (entity.Assertion?.Certainty != null)
{
Console.WriteLine($" Certainty: {entity.Assertion?.Certainty}");
}
if (entity.Assertion?.Conditionality != null)
{
Console.WriteLine($" Conditionality: {entity.Assertion?.Conditionality}");
}
}
}
Console.WriteLine($" We found {result.EntityRelations.Count} relations in the current document:");
Console.WriteLine("");
// view recognized healthcare relations
foreach (HealthcareEntityRelation relations in result.EntityRelations)
{
Console.WriteLine($" Relation: {relations.RelationType}");
Console.WriteLine($" For this relation there are {relations.Roles.Count} roles");
// view relation roles
foreach (HealthcareEntityRelationRole role in relations.Roles)
{
Console.WriteLine($" Role Name: {role.Name}");
Console.WriteLine($" Associated Entity Text: {role.Entity.Text}");
Console.WriteLine($" Associated Entity Category: {role.Entity.Category}");
Console.WriteLine("");
}
Console.WriteLine("");
}
// document statistics
Console.WriteLine($" Document statistics:");
Console.WriteLine($" Character count (in Unicode graphemes): {result.Statistics.CharacterCount}");
Console.WriteLine($" Transaction count: {result.Statistics.TransactionCount}");
Console.WriteLine("");
}
// batch operation statistics
Console.WriteLine($"Batch operation statistics:");
Console.WriteLine($" Document count: {documentsInPage.Statistics.DocumentCount}");
Console.WriteLine($" Valid document count: {documentsInPage.Statistics.ValidDocumentCount}");
Console.WriteLine($" Invalid document count: {documentsInPage.Statistics.InvalidDocumentCount}");
Console.WriteLine($" Transaction count: {documentsInPage.Statistics.TransactionCount}");
Console.WriteLine("");
}
}
public async Task RecognizeEntitiesBatchAsync()
{
string endpoint = Environment.GetEnvironmentVariable("TEXT_ANALYTICS_ENDPOINT");
string apiKey = Environment.GetEnvironmentVariable("TEXT_ANALYTICS_API_KEY");
// Instantiate a client that will be used to call the service.
var client = new TextAnalyticsClient(new Uri(endpoint), new AzureKeyCredential(apiKey));
var documents = new List <TextDocumentInput>
{
new TextDocumentInput("1", "Microsoft was founded by Bill Gates and Paul Allen.")
{
Language = "en",
},
new TextDocumentInput("2", "Text Analytics is one of the Azure Cognitive Services.")
{
Language = "en",
},
new TextDocumentInput("3", "A key technology in Text Analytics is Named Entity Recognition (NER).")
{
Language = "en",
}
};
RecognizeEntitiesResultCollection results = await client.RecognizeEntitiesBatchAsync(documents, new TextAnalyticsRequestOptions { IncludeStatistics = true });
int i = 0;
Console.WriteLine($"Results of Azure Text Analytics \"Named Entity Recognition\" Model, version: \"{results.ModelVersion}\"");
Console.WriteLine("");
foreach (RecognizeEntitiesResult result in results)
{
TextDocumentInput document = documents[i++];
Console.WriteLine($"On document (Id={document.Id}, Language=\"{document.Language}\", Text=\"{document.Text}\"):");
if (result.HasError)
{
Console.WriteLine($" Document error code: {result.Error.Code}.");
Console.WriteLine($" Message: {result.Error.Message}.");
}
else
{
Console.WriteLine($" Recognized the following {result.Entities.Count()} entities:");
foreach (CategorizedEntity entity in result.Entities)
{
Console.WriteLine($" Text: {entity.Text}, Category: {entity.Category}, SubCategory: {entity.SubCategory}, Confidence score: {entity.ConfidenceScore}");
}
Console.WriteLine($" Document statistics:");
Console.WriteLine($" Character count (in Unicode graphemes): {result.Statistics.GraphemeCount}");
Console.WriteLine($" Transaction count: {result.Statistics.TransactionCount}");
Console.WriteLine("");
}
}
Console.WriteLine($"Batch operation statistics:");
Console.WriteLine($" Document count: {results.Statistics.DocumentCount}");
Console.WriteLine($" Valid document count: {results.Statistics.ValidDocumentCount}");
Console.WriteLine($" Invalid document count: {results.Statistics.InvalidDocumentCount}");
Console.WriteLine($" Transaction count: {results.Statistics.TransactionCount}");
Console.WriteLine("");
}
public static async Task RunAsync([EventGridTrigger] EventGridEvent eventGridEvent, ILogger log)
{
//Extracting content type and url of the blob triggering the function
var jsondata = JsonConvert.SerializeObject(eventGridEvent.Data);
var tmp = new { contentType = "", url = "" };
var data = JsonConvert.DeserializeAnonymousType(jsondata, tmp);
//Checking if the trigger was iniatiated for a WAV File.
if (data.contentType == "audio/wav")
{
var audioUrl = data.url;
string blobName = audioUrl.Split('/').Last();
string contosoStorageConnectionString = System.Environment.GetEnvironmentVariable("ContosoStorageConnectionString", EnvironmentVariableTarget.Process);
string speechRegion = System.Environment.GetEnvironmentVariable("SpeechRegion", EnvironmentVariableTarget.Process);
string speechKey = System.Environment.GetEnvironmentVariable("SpeechKey", EnvironmentVariableTarget.Process);
string translatorKey = System.Environment.GetEnvironmentVariable("TranslatorKey", EnvironmentVariableTarget.Process);
string translatorEndpoint = System.Environment.GetEnvironmentVariable("TranslatorEndpoint", EnvironmentVariableTarget.Process);
string translatorLocation = System.Environment.GetEnvironmentVariable("TranslatorLocation", EnvironmentVariableTarget.Process);
string cosmosEndpointUrl = System.Environment.GetEnvironmentVariable("CosmosDBEndpointUrl", EnvironmentVariableTarget.Process);
string cosmosPrimaryKey = System.Environment.GetEnvironmentVariable("CosmosDBPrimaryKey", EnvironmentVariableTarget.Process);
string textAnalyticsKey = System.Environment.GetEnvironmentVariable("TextAnalyticsKey", EnvironmentVariableTarget.Process);
string textAnalyticsEndpoint = System.Environment.GetEnvironmentVariable("TextAnalyticsEndpoint", EnvironmentVariableTarget.Process);
// Download audio file to a local temp directory
var tempPath = System.IO.Path.GetTempFileName();
BlobContainerClient container = new BlobContainerClient(contosoStorageConnectionString, "audiorecordings");
BlobClient blob = container.GetBlobClient(blobName);
await blob.DownloadToAsync(tempPath);
var speechConfig = SpeechConfig.FromSubscription(speechKey, speechRegion);
speechConfig.SetProperty(PropertyId.SpeechServiceConnection_SingleLanguageIdPriority, "Latency");
// Audio Language Identification
// Considering only two languages: English and Spanish
// Languages supported for language detection : https://docs.microsoft.com/azure/cognitive-services/speech-service/language-support
var autoDetectSourceLanguageConfig = AutoDetectSourceLanguageConfig.FromLanguages(new string[] { "en-US", "es-MX" });
string languageDetected = "en-US";
using (var audioInput = AudioConfig.FromWavFileInput(tempPath))
{
using (var recognizer = new SourceLanguageRecognizer(speechConfig, autoDetectSourceLanguageConfig, audioInput))
{
var result = await recognizer.RecognizeOnceAsync().ConfigureAwait(false);
if (result.Reason == ResultReason.RecognizedSpeech)
{
var lidResult = AutoDetectSourceLanguageResult.FromResult(result);
languageDetected = lidResult.Language;
}
}
}
speechConfig.SpeechRecognitionLanguage = languageDetected;
// Audio Transcription
StringBuilder sb = new StringBuilder();
using var audioConfig = AudioConfig.FromWavFileInput(tempPath);
{
using var recognizer = new SpeechRecognizer(speechConfig, audioConfig);
{
var stopRecognition = new TaskCompletionSource <int>();
recognizer.SessionStopped += (s, e) =>
{
stopRecognition.TrySetResult(0);
};
recognizer.Canceled += (s, e) =>
{
stopRecognition.TrySetResult(0);
};
recognizer.Recognized += (s, e) =>
{
if (e.Result.Reason == ResultReason.RecognizedSpeech)
{
sb.Append(e.Result.Text);
}
else if (e.Result.Reason == ResultReason.NoMatch)
{
log.LogInformation($"NOMATCH: Speech could not be recognized.");
}
};
await recognizer.StartContinuousRecognitionAsync();
Task.WaitAny(new[] { stopRecognition.Task });
}
}
string transcribedText = sb.ToString();
// If transcription is in Spanish we will translate it to English
if (!languageDetected.Contains("en"))
{
string route = $"/translate?api-version=3.0&to=en";
string textToTranslate = sb.ToString();
object[] body = new object[] { new { Text = textToTranslate } };
var requestBody = JsonConvert.SerializeObject(body);
using (var client = new HttpClient())
using (var request = new HttpRequestMessage())
{
request.Method = HttpMethod.Post;
request.RequestUri = new Uri(translatorEndpoint + route);
request.Content = new StringContent(requestBody, Encoding.UTF8, "application/json");
request.Headers.Add("Ocp-Apim-Subscription-Key", translatorKey);
request.Headers.Add("Ocp-Apim-Subscription-Region", translatorLocation);
HttpResponseMessage response = await client.SendAsync(request).ConfigureAwait(false);
var responseBody = await response.Content.ReadAsStringAsync();
List <Model.TranslatorService.Root> translatedDocuments = JsonConvert.DeserializeObject <List <Model.TranslatorService.Root> >(responseBody);
transcribedText = translatedDocuments.FirstOrDefault().Translations.FirstOrDefault().Text;
}
}
//Azure Text Analytics for Healthcare
List <string> healthDocuments = new List <string>
{
transcribedText
};
var textAnalyticsClient = new TextAnalyticsClient(new Uri(textAnalyticsEndpoint), new AzureKeyCredential(textAnalyticsKey));
AnalyzeHealthcareEntitiesOperation healthOperation = textAnalyticsClient.StartAnalyzeHealthcareEntities(healthDocuments, "en", new AnalyzeHealthcareEntitiesOptions {
});
await healthOperation.WaitForCompletionAsync();
AnalyzeHealthcareEntitiesResult healthcareResult = healthOperation.GetValues().FirstOrDefault().FirstOrDefault();
//Insert documents into CosmosDB
var cosmosClient = new CosmosClient(cosmosEndpointUrl, cosmosPrimaryKey);
var cosmosDatabase = (await cosmosClient.CreateDatabaseIfNotExistsAsync("Contoso")).Database;
var cosmosContainer = (await cosmosDatabase.CreateContainerIfNotExistsAsync("Transcriptions", "/id")).Container;
Model.Transcription newTranscription = new Model.Transcription();
newTranscription.Id = Guid.NewGuid().ToString();
newTranscription.DocumentDate = new DateTime(int.Parse(blobName.Substring(0, 4)),
int.Parse(blobName.Substring(4, 2)), int.Parse(blobName.Substring(6, 2)));
newTranscription.FileName = blobName;
newTranscription.TranscribedText = transcribedText;
foreach (var item in healthcareResult.Entities)
{
newTranscription.HealthcareEntities.Add(new Model.HealthcareEntity()
{
Category = item.Category, Text = item.Text
});
}
try
{
ItemResponse <Model.Transcription> cosmosResponse = await
cosmosContainer.CreateItemAsync(newTranscription, new PartitionKey(newTranscription.Id));
}
catch (CosmosException ex) when(ex.StatusCode == System.Net.HttpStatusCode.Conflict)
{
//Conflicting documents are silently ignored for demo purposes.
}
System.IO.File.Delete(tempPath);
log.LogInformation(eventGridEvent.Data.ToString());
}
}
public static void Run([TimerTrigger("0 30 6 * * *", RunOnStartup = true)] TimerInfo myTimer, ILogger log)
{
log.LogInformation($"C# Timer trigger function executed at: {DateTime.Now}");
// Initialize variables from local.settings.json
string twilioSid = System.Environment.GetEnvironmentVariable("TwilioSid");
string twilioAuthToken = System.Environment.GetEnvironmentVariable("TwilioAuthToken");
string newsApiKey = System.Environment.GetEnvironmentVariable("NewsApiKey");
string fromNumber = System.Environment.GetEnvironmentVariable("TwilioPhoneNumber");
string toNumber = System.Environment.GetEnvironmentVariable("MyPhoneNumber");
TextAnalyticsApiKeyCredential textAnalyticsCredentials = new TextAnalyticsApiKeyCredential(System.Environment.GetEnvironmentVariable("TextAnalyticsApiKeyCredential"));
Uri textAnalyticsEndpoint = new Uri(System.Environment.GetEnvironmentVariable("CognitiveServicesEndpoint"));
// Incase URL of article image is null, we will use this royalty free stock photo.
string newspaperImageURL = "https://images.unsplash.com/photo-1504711331083-9c895941bf81?ixlib=rb-1.2.1&ixid=eyJhcHBfaWQiOjEyMDd9&auto=format&fit=crop&w=2550&q=80";
// NEWS API Search parameters and URL
string searchKeyword = "Covid";
string sortBy = "relevancy";
string pageSize = "100";
string searchLanguage = "en";
string fromDate = DateTime.Today.AddDays(-1).ToString("yyyy-MM-dd");
double imageFileSize = 0.0;
var newAPIEndpointURL = $"https://newsapi.org/v2/everything?from={fromDate}&sortBy={sortBy}&pageSize={pageSize}&language={searchLanguage}&q={searchKeyword}&apiKey={newsApiKey}";
// 1. Get json
string jsonFromAPI = GetNewsFromAPI(newAPIEndpointURL);
// 2. Deserialize into objects
News news = JsonConvert.DeserializeObject <News> (jsonFromAPI);
// 3. Initialize TextAnalyticsClient for sentiment detection, TwilioClient to send the message
TextAnalyticsClient textAnalyticsClient = new TextAnalyticsClient(textAnalyticsEndpoint, textAnalyticsCredentials);
TwilioClient.Init(twilioSid, twilioAuthToken);
// 4. Perform sentiment detection on article titles
string sentimentLabel = "negative";
if (news.status.Equals("ok"))
{
foreach (var article in news.articles)
{
sentimentLabel = SentimentDetection(textAnalyticsClient, article.title);
// 5. Once a a news article with positive sentiment is found, send via text and break out of foreach loop.
if (sentimentLabel.Equals("Positive"))
{
log.LogInformation("Found positive story: " + article.url);
// Checks if there is a url for image of article, if there isn't it will default to newspaperImageURL.
article.urlToImage = !String.IsNullOrEmpty(article.urlToImage) ? article.urlToImage : newspaperImageURL;
// If article image was changes to newspaperImageURL, no need to check size because newspaperImageURL is only 321KB
if (!(article.urlToImage.Equals(newspaperImageURL)))
{
// Gets image file size and logs to console.
imageFileSize = GetMediaFileSize(article.urlToImage);
log.LogInformation("The image size is: " + imageFileSize);
// MMS size limit is 5 MB.
if ((imageFileSize > 4.9))
{
article.urlToImage = newspaperImageURL;
}
}
SendMessage(fromNumber, toNumber, article.url, article.title, article.urlToImage);
break;
}
}
}
else
{
log.LogInformation("Error with NEWS API call");
}
}
public void DetectLanguageBatch()
{
string endpoint = Environment.GetEnvironmentVariable("TEXT_ANALYTICS_ENDPOINT");
string subscriptionKey = Environment.GetEnvironmentVariable("TEXT_ANALYTICS_SUBSCRIPTION_KEY");
var client = new TextAnalyticsClient(new Uri(endpoint), subscriptionKey);
#region Snippet:TextAnalyticsSample1DetectLanguagesBatch
var inputs = new List <DetectLanguageInput>
{
new DetectLanguageInput("1", "Hello world")
{
CountryHint = "us",
},
new DetectLanguageInput("2", "Bonjour tout le monde")
{
CountryHint = "fr",
},
new DetectLanguageInput("3", "Hola mundo")
{
CountryHint = "es",
},
new DetectLanguageInput("4", ":) :( :D")
{
CountryHint = "us",
}
};
DetectLanguageResultCollection results = client.DetectLanguages(inputs, new TextAnalyticsRequestOptions {
IncludeStatistics = true
});
#endregion
int i = 0;
Debug.WriteLine($"Results of Azure Text Analytics \"Detect Language\" Model, version: \"{results.ModelVersion}\"");
Debug.WriteLine("");
foreach (DetectLanguageResult result in results)
{
DetectLanguageInput document = inputs[i++];
Debug.WriteLine($"On document (Id={document.Id}, CountryHint=\"{document.CountryHint}\", Text=\"{document.Text}\"):");
if (result.ErrorMessage != default)
{
Debug.WriteLine($" Document error: {result.ErrorMessage}.");
}
else
{
Debug.WriteLine($" Detected language {result.PrimaryLanguage.Name} with confidence {result.PrimaryLanguage.Score:0.00}.");
Debug.WriteLine($" Document statistics:");
Debug.WriteLine($" Character count: {result.Statistics.CharacterCount}");
Debug.WriteLine($" Transaction count: {result.Statistics.TransactionCount}");
Debug.WriteLine("");
}
}
Debug.WriteLine($"Batch operation statistics:");
Debug.WriteLine($" Document count: {results.Statistics.DocumentCount}");
Debug.WriteLine($" Valid document count: {results.Statistics.ValidDocumentCount}");
Debug.WriteLine($" Invalid document count: {results.Statistics.InvalidDocumentCount}");
Debug.WriteLine($" Transaction count: {results.Statistics.TransactionCount}");
Debug.WriteLine("");
}
public void RecognizeEntitiesBatch()
{
string endpoint = TestEnvironment.Endpoint;
string apiKey = TestEnvironment.ApiKey;
// Instantiate a client that will be used to call the service.
var client = new TextAnalyticsClient(new Uri(endpoint), new AzureKeyCredential(apiKey));
#region Snippet:TextAnalyticsSample4RecognizeEntitiesBatch
var documents = new List <TextDocumentInput>
{
new TextDocumentInput("1", "Microsoft was founded by Bill Gates and Paul Allen.")
{
Language = "en",
},
new TextDocumentInput("2", "Text Analytics is one of the Azure Cognitive Services.")
{
Language = "en",
},
new TextDocumentInput("3", "A key technology in Text Analytics is Named Entity Recognition (NER).")
{
Language = "en",
}
};
RecognizeEntitiesResultCollection results = client.RecognizeEntitiesBatch(documents, new TextAnalyticsRequestOptions {
IncludeStatistics = true
});
#endregion
int i = 0;
Debug.WriteLine($"Results of Azure Text Analytics \"Named Entity Recognition\" Model, version: \"{results.ModelVersion}\"");
Debug.WriteLine("");
foreach (RecognizeEntitiesResult result in results)
{
TextDocumentInput document = documents[i++];
Debug.WriteLine($"On document (Id={document.Id}, Language=\"{document.Language}\", Text=\"{document.Text}\"):");
if (result.HasError)
{
Debug.WriteLine($" Document error code: {result.Error.ErrorCode}.");
Debug.WriteLine($" Message: {result.Error.Message}.");
}
else
{
Debug.WriteLine($" Recognized the following {result.Entities.Count()} entities:");
foreach (CategorizedEntity entity in result.Entities)
{
Debug.WriteLine($" Text: {entity.Text}, Offset (in UTF-16 code units): {entity.Offset}, Length (in UTF-16 code units): {entity.Length}");
Debug.WriteLine($" Text: {entity.Text}, Category: {entity.Category}, SubCategory: {entity.SubCategory}, Confidence score: {entity.ConfidenceScore}");
}
Debug.WriteLine($" Document statistics:");
Debug.WriteLine($" Character count (in Unicode graphemes): {result.Statistics.CharacterCount}");
Debug.WriteLine($" Transaction count: {result.Statistics.TransactionCount}");
Debug.WriteLine("");
}
}
Debug.WriteLine($"Batch operation statistics:");
Debug.WriteLine($" Document count: {results.Statistics.DocumentCount}");
Debug.WriteLine($" Valid document count: {results.Statistics.ValidDocumentCount}");
Debug.WriteLine($" Invalid document count: {results.Statistics.InvalidDocumentCount}");
Debug.WriteLine($" Transaction count: {results.Statistics.TransactionCount}");
Debug.WriteLine("");
}
public void ExtractEntityLinkingBatchAdvanced()
{
string endpoint = Environment.GetEnvironmentVariable("TEXT_ANALYTICS_ENDPOINT");
string subscriptionKey = Environment.GetEnvironmentVariable("TEXT_ANALYTICS_SUBSCRIPTION_KEY");
// Instantiate a client that will be used to call the service.
var client = new TextAnalyticsClient(new Uri(endpoint), subscriptionKey);
var inputs = new List <DocumentInput>
{
new DocumentInput("1")
{
Language = "en",
Text = "Microsoft was founded by Bill Gates and Paul Allen."
},
new DocumentInput("2")
{
Language = "en",
Text = "Text Analytics is one of the Azure Cognitive Services."
},
new DocumentInput("3")
{
Language = "en",
Text = "Pike place market is my favorite Seattle attraction."
}
};
var resultCollection = client.ExtractEntityLinking(inputs, new TextAnalyticsRequestOptions(showStatistics: true)).Value;
int i = 0;
Debug.WriteLine($"Results of Azure Text Analytics \"Entity Linking\", version: \"{resultCollection.ModelVersion}\"");
Debug.WriteLine("");
foreach (var result in resultCollection)
{
var document = inputs[i++];
Debug.WriteLine($"On document (Id={document.Id}, Language=\"{document.Language}\", Text=\"{document.Text}\"):");
Debug.WriteLine($" Extracted the following {result.Count()} linked entities:");
foreach (var linkedEntity in result)
{
Debug.WriteLine($" Name: \"{linkedEntity.Name}\", Id: \"{linkedEntity.Id}\", Language: {linkedEntity.Language}, Data Source: {linkedEntity.DataSource}, Uri: {linkedEntity.Uri.ToString()}");
foreach (LinkedEntityMatch match in linkedEntity.Matches)
{
Debug.WriteLine($" Match Text: \"{match.Text}\", Score: {match.Score:0.00}, Offset: {match.Offset}, Length: {match.Length}.");
}
}
Debug.WriteLine($" Document statistics:");
Debug.WriteLine($" Character count: {result.Statistics.CharacterCount}");
Debug.WriteLine($" Transaction count: {result.Statistics.TransactionCount}");
Debug.WriteLine("");
}
Debug.WriteLine($"Batch operation statistics:");
Debug.WriteLine($" Document count: {resultCollection.Statistics.DocumentCount}");
Debug.WriteLine($" Valid document count: {resultCollection.Statistics.ValidDocumentCount}");
Debug.WriteLine($" Invalid document count:{resultCollection.Statistics.InvalidDocumentCount}");
Debug.WriteLine($" Transaction count:{resultCollection.Statistics.TransactionCount}");
Debug.WriteLine("");
}
public async Task AnalyzeOperationConvenienceAsync()
{
string endpoint = TestEnvironment.Endpoint;
string apiKey = TestEnvironment.ApiKey;
var client = new TextAnalyticsClient(new Uri(endpoint), new AzureKeyCredential(apiKey));
#region Snippet:AnalyzeOperationConvenienceAsync
string documentA = @"We love this trail and make the trip every year. The views are breathtaking and well
worth the hike! Yesterday was foggy though, so we missed the spectacular views.
We tried again today and it was amazing. Everyone in my family liked the trail although
it was too challenging for the less athletic among us.";
string documentB = @"Last week we stayed at Hotel Foo to celebrate our anniversary. The staff knew about
our anniversary so they helped me organize a little surprise for my partner.
The room was clean and with the decoration I requested. It was perfect!";
var batchDocuments = new List <string>
{
documentA,
documentB
};
TextAnalyticsActions actions = new TextAnalyticsActions()
{
ExtractKeyPhrasesActions = new List <ExtractKeyPhrasesAction>()
{
new ExtractKeyPhrasesAction()
},
RecognizeEntitiesActions = new List <RecognizeEntitiesAction>()
{
new RecognizeEntitiesAction()
},
RecognizePiiEntitiesActions = new List <RecognizePiiEntitiesAction>()
{
new RecognizePiiEntitiesAction()
},
RecognizeLinkedEntitiesActions = new List <RecognizeLinkedEntitiesAction>()
{
new RecognizeLinkedEntitiesAction()
},
AnalyzeSentimentActions = new List <AnalyzeSentimentAction>()
{
new AnalyzeSentimentAction()
},
DisplayName = "AnalyzeOperationSample"
};
AnalyzeActionsOperation operation = await client.StartAnalyzeActionsAsync(batchDocuments, actions);
await operation.WaitForCompletionAsync();
Console.WriteLine($"Status: {operation.Status}");
Console.WriteLine($"Created On: {operation.CreatedOn}");
Console.WriteLine($"Expires On: {operation.ExpiresOn}");
Console.WriteLine($"Last modified: {operation.LastModified}");
if (!string.IsNullOrEmpty(operation.DisplayName))
{
Console.WriteLine($"Display name: {operation.DisplayName}");
}
Console.WriteLine($"Total actions: {operation.ActionsTotal}");
Console.WriteLine($" Succeeded actions: {operation.ActionsSucceeded}");
Console.WriteLine($" Failed actions: {operation.ActionsFailed}");
Console.WriteLine($" In progress actions: {operation.ActionsInProgress}");
await foreach (AnalyzeActionsResult documentsInPage in operation.Value)
{
IReadOnlyCollection <ExtractKeyPhrasesActionResult> keyPhrasesActionsResults = documentsInPage.ExtractKeyPhrasesActionsResults;
IReadOnlyCollection <RecognizeEntitiesActionResult> entitiesActionsResults = documentsInPage.RecognizeEntitiesActionsResults;
IReadOnlyCollection <RecognizePiiEntitiesActionResult> piiActionsResults = documentsInPage.RecognizePiiEntitiesActionsResults;
IReadOnlyCollection <RecognizeLinkedEntitiesActionResult> entityLinkingActionsResults = documentsInPage.RecognizeLinkedEntitiesActionsResults;
IReadOnlyCollection <AnalyzeSentimentActionResult> analyzeSentimentActionsResults = documentsInPage.AnalyzeSentimentActionsResults;
Console.WriteLine("Recognized Entities");
int docNumber = 1;
foreach (RecognizeEntitiesActionResult entitiesActionResults in entitiesActionsResults)
{
foreach (RecognizeEntitiesResult result in entitiesActionResults.Result)
{
Console.WriteLine($" Document #{docNumber++}");
Console.WriteLine($" Recognized the following {result.Entities.Count} entities:");
foreach (CategorizedEntity entity in result.Entities)
{
Console.WriteLine($" Entity: {entity.Text}");
Console.WriteLine($" Category: {entity.Category}");
Console.WriteLine($" Offset: {entity.Offset}");
Console.WriteLine($" Length: {entity.Length}");
Console.WriteLine($" ConfidenceScore: {entity.ConfidenceScore}");
Console.WriteLine($" SubCategory: {entity.SubCategory}");
}
Console.WriteLine("");
}
}
Console.WriteLine("Recognized PII Entities");
docNumber = 1;
foreach (RecognizePiiEntitiesActionResult piiActionResults in piiActionsResults)
{
foreach (RecognizePiiEntitiesResult result in piiActionResults.Result)
{
Console.WriteLine($" Document #{docNumber++}");
Console.WriteLine($" Recognized the following {result.Entities.Count} PII entities:");
foreach (PiiEntity entity in result.Entities)
{
Console.WriteLine($" Entity: {entity.Text}");
Console.WriteLine($" Category: {entity.Category}");
Console.WriteLine($" Offset: {entity.Offset}");
Console.WriteLine($" Length: {entity.Length}");
Console.WriteLine($" ConfidenceScore: {entity.ConfidenceScore}");
Console.WriteLine($" SubCategory: {entity.SubCategory}");
}
Console.WriteLine("");
}
}
Console.WriteLine("Key Phrases");
docNumber = 1;
foreach (ExtractKeyPhrasesActionResult keyPhrasesActionResult in keyPhrasesActionsResults)
{
foreach (ExtractKeyPhrasesResult result in keyPhrasesActionResult.Result)
{
Console.WriteLine($" Document #{docNumber++}");
Console.WriteLine($" Recognized the following {result.KeyPhrases.Count} Keyphrases:");
foreach (string keyphrase in result.KeyPhrases)
{
Console.WriteLine($" {keyphrase}");
}
Console.WriteLine("");
}
}
Console.WriteLine("Recognized Linked Entities");
docNumber = 1;
foreach (RecognizeLinkedEntitiesActionResult linkedEntitiesActionResults in entityLinkingActionsResults)
{
foreach (RecognizeLinkedEntitiesResult result in linkedEntitiesActionResults.Result)
{
Console.WriteLine($" Document #{docNumber++}");
Console.WriteLine($" Recognized the following {result.Entities.Count} linked entities:");
foreach (LinkedEntity entity in result.Entities)
{
Console.WriteLine($" Entity: {entity.Name}");
Console.WriteLine($" DataSource: {entity.DataSource}");
Console.WriteLine($" DataSource EntityId: {entity.DataSourceEntityId}");
Console.WriteLine($" Language: {entity.Language}");
Console.WriteLine($" DataSource Url: {entity.Url}");
Console.WriteLine($" Total Matches: {entity.Matches.Count()}");
foreach (LinkedEntityMatch match in entity.Matches)
{
Console.WriteLine($" Match Text: {match.Text}");
Console.WriteLine($" ConfidenceScore: {match.ConfidenceScore}");
Console.WriteLine($" Offset: {match.Offset}");
Console.WriteLine($" Length: {match.Length}");
}
Console.WriteLine("");
}
Console.WriteLine("");
}
}
Console.WriteLine("Analyze Sentiment");
docNumber = 1;
foreach (AnalyzeSentimentActionResult analyzeSentimentActionsResult in analyzeSentimentActionsResults)
{
foreach (AnalyzeSentimentResult result in analyzeSentimentActionsResult.Result)
{
Console.WriteLine($" Document #{docNumber++}");
Console.WriteLine($" Sentiment is {result.DocumentSentiment.Sentiment}, with confidence scores: ");
Console.WriteLine($" Positive confidence score: {result.DocumentSentiment.ConfidenceScores.Positive}.");
Console.WriteLine($" Neutral confidence score: {result.DocumentSentiment.ConfidenceScores.Neutral}.");
Console.WriteLine($" Negative confidence score: {result.DocumentSentiment.ConfidenceScores.Negative}.");
Console.WriteLine("");
}
}
}
}
public async Task HealthcareBatch()
{
string endpoint = TestEnvironment.Endpoint;
string apiKey = TestEnvironment.ApiKey;
var client = new TextAnalyticsClient(new Uri(endpoint), new AzureKeyCredential(apiKey));
#region Snippet:TextAnalyticsSampleHealthcareBatch
string document = @"RECORD #333582770390100 | MH | 85986313 | | 054351 | 2/14/2001 12:00:00 AM | CORONARY ARTERY DISEASE | Signed | DIS | \
Admission Date: 5/22/2001 Report Status: Signed Discharge Date: 4/24/2001 ADMISSION DIAGNOSIS: CORONARY ARTERY DISEASE. \
HISTORY OF PRESENT ILLNESS: The patient is a 54-year-old gentleman with a history of progressive angina over the past several months. \
The patient had a cardiac catheterization in July of this year revealing total occlusion of the RCA and 50% left main disease ,\
with a strong family history of coronary artery disease with a brother dying at the age of 52 from a myocardial infarction and \
another brother who is status post coronary artery bypass grafting. The patient had a stress echocardiogram done on July , 2001 , \
which showed no wall motion abnormalities , but this was a difficult study due to body habitus. The patient went for six minutes with \
minimal ST depressions in the anterior lateral leads , thought due to fatigue and wrist pain , his anginal equivalent. Due to the patient's \
increased symptoms and family history and history left main disease with total occasional of his RCA was referred for revascularization with open heart surgery.";
List <string> batchInput = new List <string>()
{
document,
document,
};
AnalyzeHealthcareEntitiesOptions options = new AnalyzeHealthcareEntitiesOptions()
{
IncludeStatistics = true
};
AnalyzeHealthcareEntitiesOperation healthOperation = client.StartAnalyzeHealthcareEntities(batchInput, "en", options);
await healthOperation.WaitForCompletionAsync();
foreach (AnalyzeHealthcareEntitiesResultCollection documentsInPage in healthOperation.GetValues())
{
Console.WriteLine($"Results of Azure Text Analytics \"Healthcare\" Model, version: \"{documentsInPage.ModelVersion}\"");
Console.WriteLine("");
foreach (AnalyzeHealthcareEntitiesResult result in documentsInPage)
{
Console.WriteLine($" Recognized the following {result.Entities.Count} healthcare entities:");
foreach (HealthcareEntity entity in result.Entities)
{
Console.WriteLine($" Entity: {entity.Text}");
Console.WriteLine($" Category: {entity.Category}");
Console.WriteLine($" Offset: {entity.Offset}");
Console.WriteLine($" Length: {entity.Length}");
Console.WriteLine($" Links:");
foreach (EntityDataSource entityDataSource in entity.DataSources)
{
Console.WriteLine($" Entity ID in Data Source: {entityDataSource.EntityId}");
Console.WriteLine($" DataSource: {entityDataSource.Name}");
}
}
Console.WriteLine($" Document statistics:");
Console.WriteLine($" Character count (in Unicode graphemes): {result.Statistics.CharacterCount}");
Console.WriteLine($" Transaction count: {result.Statistics.TransactionCount}");
Console.WriteLine("");
}
Console.WriteLine($"Request statistics:");
Console.WriteLine($" Document Count: {documentsInPage.Statistics.DocumentCount}");
Console.WriteLine($" Valid Document Count: {documentsInPage.Statistics.ValidDocumentCount}");
Console.WriteLine($" Transaction Count: {documentsInPage.Statistics.TransactionCount}");
Console.WriteLine($" Invalid Document Count: {documentsInPage.Statistics.InvalidDocumentCount}");
Console.WriteLine("");
}
}
public void AnalyzeOperation()
{
string endpoint = TestEnvironment.Endpoint;
string apiKey = TestEnvironment.ApiKey;
var client = new TextAnalyticsClient(new Uri(endpoint), new AzureKeyCredential(apiKey));
string documentA = @"We love this trail and make the trip every year. The views are breathtaking and well
worth the hike! Yesterday was foggy though, so we missed the spectacular views.
We tried again today and it was amazing. Everyone in my family liked the trail although
it was too challenging for the less athletic among us.";
string documentB = @"Last week we stayed at Hotel Foo to celebrate our anniversary. The staff knew about
our anniversary so they helped me organize a little surprise for my partner.
The room was clean and with the decoration I requested. It was perfect!";
var batchDocuments = new List <TextDocumentInput>
{
new TextDocumentInput("1", documentA)
{
Language = "en",
},
new TextDocumentInput("2", documentB)
{
Language = "en",
}
};
TextAnalyticsActions actions = new TextAnalyticsActions()
{
ExtractKeyPhrasesActions = new List <ExtractKeyPhrasesAction>()
{
new ExtractKeyPhrasesAction()
},
RecognizeEntitiesActions = new List <RecognizeEntitiesAction>()
{
new RecognizeEntitiesAction()
},
DisplayName = "AnalyzeOperationSample"
};
AnalyzeActionsOperation operation = client.StartAnalyzeActions(batchDocuments, actions);
TimeSpan pollingInterval = new TimeSpan(1000);
while (!operation.HasCompleted)
{
Thread.Sleep(pollingInterval);
operation.UpdateStatus();
Console.WriteLine($"Status: {operation.Status}");
//If operation has not started, all other fields are null
if (operation.Status != TextAnalyticsOperationStatus.NotStarted)
{
Console.WriteLine($"Expires On: {operation.ExpiresOn}");
Console.WriteLine($"Last modified: {operation.LastModified}");
if (!string.IsNullOrEmpty(operation.DisplayName))
{
Console.WriteLine($"Display name: {operation.DisplayName}");
}
Console.WriteLine($"Total actions: {operation.ActionsTotal}");
Console.WriteLine($" Succeeded actions: {operation.ActionsSucceeded}");
Console.WriteLine($" Failed actions: {operation.ActionsFailed}");
Console.WriteLine($" In progress actions: {operation.ActionsInProgress}");
}
}
foreach (AnalyzeActionsResult documentsInPage in operation.GetValues())
{
IReadOnlyCollection <ExtractKeyPhrasesActionResult> keyPhrasesResults = documentsInPage.ExtractKeyPhrasesResults;
IReadOnlyCollection <RecognizeEntitiesActionResult> entitiesResults = documentsInPage.RecognizeEntitiesResults;
Console.WriteLine("Recognized Entities");
int docNumber = 1;
foreach (RecognizeEntitiesActionResult entitiesActionResults in entitiesResults)
{
Console.WriteLine($" Action name: {entitiesActionResults.ActionName}");
foreach (RecognizeEntitiesResult documentResults in entitiesActionResults.DocumentsResults)
{
Console.WriteLine($" Document #{docNumber++}");
Console.WriteLine($" Recognized the following {documentResults.Entities.Count} entities:");
foreach (CategorizedEntity entity in documentResults.Entities)
{
Console.WriteLine($" Entity: {entity.Text}");
Console.WriteLine($" Category: {entity.Category}");
Console.WriteLine($" Offset: {entity.Offset}");
Console.WriteLine($" Length: {entity.Length}");
Console.WriteLine($" ConfidenceScore: {entity.ConfidenceScore}");
Console.WriteLine($" SubCategory: {entity.SubCategory}");
}
Console.WriteLine("");
}
}
Console.WriteLine("Key Phrases");
docNumber = 1;
foreach (ExtractKeyPhrasesActionResult keyPhrasesActionResult in keyPhrasesResults)
{
foreach (ExtractKeyPhrasesResult documentResults in keyPhrasesActionResult.DocumentsResults)
{
Console.WriteLine($" Document #{docNumber++}");
Console.WriteLine($" Recognized the following {documentResults.KeyPhrases.Count} Keyphrases:");
foreach (string keyphrase in documentResults.KeyPhrases)
{
Console.WriteLine($" {keyphrase}");
}
Console.WriteLine("");
}
}
}
}
static void Main(string[] args)
{
// Create a client.
ITextAnalyticsClient client = new TextAnalyticsClient(new ApiKeyServiceClientCredentials())
{
Endpoint = "https://centralindia.api.cognitive.microsoft.com"
}; //Replace 'westus' with the correct region for your Text Analytics subscription
Console.OutputEncoding = System.Text.Encoding.UTF8;
// Extracting language
Console.WriteLine("===== LANGUAGE EXTRACTION ======");
var result = client.DetectLanguageAsync(new BatchInput(
new List <Input>()
{
new Input("1", "This is a document written in English."),
new Input("2", "Este es un document escrito en Español."),
new Input("3", "这是一个用中文写的文件")
})).Result;
// Printing language results.
foreach (var document in result.Documents)
{
Console.WriteLine($"Document ID: {document.Id} , Language: {document.DetectedLanguages[0].Name}");
}
// Getting key-phrases
Console.WriteLine("\n\n===== KEY-PHRASE EXTRACTION ======");
KeyPhraseBatchResult result2 = client.KeyPhrasesAsync(new MultiLanguageBatchInput(
new List <MultiLanguageInput>()
{
new MultiLanguageInput("ja", "1", "猫は幸せ"),
new MultiLanguageInput("de", "2", "Fahrt nach Stuttgart und dann zum Hotel zu Fu."),
new MultiLanguageInput("en", "3", "My cat is stiff as a rock."),
new MultiLanguageInput("es", "4", "A mi me encanta el fútbol!")
})).Result;
// Printing keyphrases
foreach (var document in result2.Documents)
{
Console.WriteLine($"Document ID: {document.Id} ");
Console.WriteLine("\t Key phrases:");
foreach (string keyphrase in document.KeyPhrases)
{
Console.WriteLine($"\t\t{keyphrase}");
}
}
// Extracting sentiment
Console.WriteLine("\n\n===== SENTIMENT ANALYSIS ======");
SentimentBatchResult result3 = client.SentimentAsync(
new MultiLanguageBatchInput(
new List <MultiLanguageInput>()
{
new MultiLanguageInput("en", "0", "I had the best day of my life."),
new MultiLanguageInput("en", "1", "This was a waste of my time. The speaker put me to sleep."),
new MultiLanguageInput("es", "2", "No tengo dinero ni nada que dar..."),
new MultiLanguageInput("it", "3", "L'hotel veneziano era meraviglioso. È un bellissimo pezzo di architettura."),
})).Result;
// Printing sentiment results
foreach (var document in result3.Documents)
{
Console.WriteLine($"Document ID: {document.Id} , Sentiment Score: {document.Score:0.00}");
}
// Identify entities
Console.WriteLine("\n\n===== ENTITIES ======");
EntitiesBatchResultV2dot1 result4 = client.EntitiesAsync(
new MultiLanguageBatchInput(
new List <MultiLanguageInput>()
{
new MultiLanguageInput("en", "0", "The Great Depression began in 1929. By 1933, the GDP in America fell by 25%.")
})).Result;
// Printing entities results
foreach (var document in result4.Documents)
{
Console.WriteLine($"Document ID: {document.Id} ");
Console.WriteLine("\t Entities:");
foreach (EntityRecordV2dot1 entity in document.Entities)
{
Console.WriteLine($"\t\t{entity.Name}\t\t{entity.WikipediaUrl}\t\t{entity.Type}\t\t{entity.SubType}");
}
}
Console.ReadLine();
}
public TextAnalyseClient(IConfiguration configuration)
{
_configuration = configuration;
_textAnalyticsClient = new TextAnalyticsClient(new ApiKeyServiceClientCredentials(_configuration["TEXT_KEY"]));
_textAnalyticsClient.Endpoint = _configuration["TEXT_ENDPOINT"];
}
public void ExtractEntityLinkingBatch()
{
string endpoint = Environment.GetEnvironmentVariable("TEXT_ANALYTICS_ENDPOINT");
string apiKey = Environment.GetEnvironmentVariable("TEXT_ANALYTICS_API_KEY");
// Instantiate a client that will be used to call the service.
var client = new TextAnalyticsClient(new Uri(endpoint), new TextAnalyticsApiKeyCredential(apiKey));
#region Snippet:TextAnalyticsSample6RecognizeLinkedEntitiesBatch
var inputs = new List <TextDocumentInput>
{
new TextDocumentInput("1", "Microsoft was founded by Bill Gates and Paul Allen.")
{
Language = "en",
},
new TextDocumentInput("2", "Text Analytics is one of the Azure Cognitive Services.")
{
Language = "en",
},
new TextDocumentInput("3", "Pike place market is my favorite Seattle attraction.")
{
Language = "en",
}
};
RecognizeLinkedEntitiesResultCollection results = client.RecognizeLinkedEntitiesBatch(inputs, new TextAnalyticsRequestOptions {
IncludeStatistics = true
});
#endregion
int i = 0;
Debug.WriteLine($"Results of Azure Text Analytics \"Entity Linking\", version: \"{results.ModelVersion}\"");
Debug.WriteLine("");
foreach (RecognizeLinkedEntitiesResult result in results)
{
TextDocumentInput document = inputs[i++];
Debug.WriteLine($"On document (Id={document.Id}, Language=\"{document.Language}\", Text=\"{document.Text}\"):");
if (result.HasError)
{
Debug.WriteLine($" Document error code: {result.Error.Code}.");
Debug.WriteLine($" Message: {result.Error.Message}.");
}
else
{
Debug.WriteLine($" Extracted the following {result.Entities.Count()} linked entities:");
foreach (LinkedEntity linkedEntity in result.Entities)
{
Debug.WriteLine($" Name: \"{linkedEntity.Name}\", Language: {linkedEntity.Language}, Data Source: {linkedEntity.DataSource}, Url: {linkedEntity.Url.ToString()}, Entity Id in Data Source: \"{linkedEntity.DataSourceEntityId}\"");
foreach (LinkedEntityMatch match in linkedEntity.Matches)
{
Debug.WriteLine($" Match Text: \"{match.Text}\", Score: {match.Score:0.00}, Offset: {match.Offset}, Length: {match.Length}.");
}
}
Debug.WriteLine($" Document statistics:");
Debug.WriteLine($" Character count: {result.Statistics.CharacterCount}");
Debug.WriteLine($" Transaction count: {result.Statistics.TransactionCount}");
Debug.WriteLine("");
}
}
Debug.WriteLine($"Batch operation statistics:");
Debug.WriteLine($" Document count: {results.Statistics.DocumentCount}");
Debug.WriteLine($" Valid document count: {results.Statistics.ValidDocumentCount}");
Debug.WriteLine($" Invalid document count: {results.Statistics.InvalidDocumentCount}");
Debug.WriteLine($" Transaction count: {results.Statistics.TransactionCount}");
Debug.WriteLine("");
}
public void DetectLanguageBatch()
{
string endpoint = TestEnvironment.Endpoint;
string apiKey = TestEnvironment.ApiKey;
// Instantiate a client that will be used to call the service.
var client = new TextAnalyticsClient(new Uri(endpoint), new AzureKeyCredential(apiKey), CreateSampleOptions());
#region Snippet:TextAnalyticsSample1DetectLanguageBatch
string documentA = @"Este documento está escrito en un idioma diferente al Inglés. Tiene como objetivo demostrar
cómo invocar el método de Detección de idioma del servicio de Text Analytics en Microsoft Azure.
También muestra cómo acceder a la información retornada por el servicio. Esta capacidad es útil
para los sistemas de contenido que recopilan texto arbitrario, donde el idioma es desconocido.
La característica Detección de idioma puede detectar una amplia gama de idiomas, variantes,
dialectos y algunos idiomas regionales o culturales.";
string documentB = @"This document is written in a language different than Spanish. It's objective is to demonstrate
how to call the Detect Language method from the Microsoft Azure Text Analytics service.
It also shows how to access the information returned from the service. This capability is useful
for content stores that collect arbitrary text, where language is unknown.
The Language Detection feature can detect a wide range of languages, variants, dialects, and some
regional or cultural languages.";
string documentC = @"Ce document est rédigé dans une langue différente de l'espagnol. Son objectif est de montrer comment
appeler la méthode Detect Language à partir du service Microsoft Azure Text Analytics.
Il montre également comment accéder aux informations renvoyées par le service. Cette capacité est
utile pour les magasins de contenu qui collectent du texte arbitraire dont la langue est inconnue.
La fonctionnalité Détection de langue peut détecter une grande variété de langues, de variantes,
de dialectes, et certaines langues régionales ou de culture.";
var documents = new List <DetectLanguageInput>
{
new DetectLanguageInput("1", documentA)
{
CountryHint = "es",
},
new DetectLanguageInput("2", documentB)
{
CountryHint = "us",
},
new DetectLanguageInput("3", documentC)
{
CountryHint = "fr",
},
new DetectLanguageInput("4", ":) :( :D")
{
CountryHint = DetectLanguageInput.None,
},
new DetectLanguageInput("5", "")
};
var options = new TextAnalyticsRequestOptions {
IncludeStatistics = true
};
Response <DetectLanguageResultCollection> response = client.DetectLanguageBatch(documents, options);
DetectLanguageResultCollection documentsLanguage = response.Value;
int i = 0;
Console.WriteLine($"Results of Azure Text Analytics \"Detect Language\" Model, version: \"{documentsLanguage.ModelVersion}\"");
Console.WriteLine("");
foreach (DetectLanguageResult documentLanguage in documentsLanguage)
{
DetectLanguageInput document = documents[i++];
Console.WriteLine($"On document (Id={document.Id}, CountryHint=\"{document.CountryHint}\"):");
if (documentLanguage.HasError)
{
Console.WriteLine(" Error!");
Console.WriteLine($" Document error code: {documentLanguage.Error.ErrorCode}.");
Console.WriteLine($" Message: {documentLanguage.Error.Message}");
}
else
{
Console.WriteLine($" Detected language: {documentLanguage.PrimaryLanguage.Name}");
Console.WriteLine($" Confidence score: {documentLanguage.PrimaryLanguage.ConfidenceScore}");
Console.WriteLine($" Document statistics:");
Console.WriteLine($" Character count: {documentLanguage.Statistics.CharacterCount}");
Console.WriteLine($" Transaction count: {documentLanguage.Statistics.TransactionCount}");
}
Console.WriteLine("");
}
Console.WriteLine($"Batch operation statistics:");
Console.WriteLine($" Document count: {documentsLanguage.Statistics.DocumentCount}");
Console.WriteLine($" Valid document count: {documentsLanguage.Statistics.ValidDocumentCount}");
Console.WriteLine($" Invalid document count: {documentsLanguage.Statistics.InvalidDocumentCount}");
Console.WriteLine($" Transaction count: {documentsLanguage.Statistics.TransactionCount}");
#endregion
}
public async Task RecognizeCustomEntitiesConvenienceAsync()
{
// Create a text analytics client.
string endpoint = TestEnvironment.Endpoint;
string apiKey = TestEnvironment.ApiKey;
var client = new TextAnalyticsClient(new Uri(endpoint), new AzureKeyCredential(apiKey), CreateSampleOptions());
// Create input documents.
string documentA = @"We love this trail and make the trip every year. The views are breathtaking and well
worth the hike! Yesterday was foggy though, so we missed the spectacular views.
We tried again today and it was amazing. Everyone in my family liked the trail although
it was too challenging for the less athletic among us.";
string documentB = @"Last week we stayed at Hotel Foo to celebrate our anniversary. The staff knew about
our anniversary so they helped me organize a little surprise for my partner.
The room was clean and with the decoration I requested. It was perfect!";
var batchDocuments = new List <string>
{
documentA,
documentB
};
// Set project and deployment names of the target model
// To train a model to recognize your custom entities, see https://aka.ms/azsdk/textanalytics/customentityrecognition
string projectName = TestEnvironment.RecognizeCustomEntitiesProjectName;
string deploymentName = TestEnvironment.RecognizeCustomEntitiesDeploymentName;
var recognizeCustomEntitiesAction = new RecognizeCustomEntitiesAction(projectName, deploymentName);
// prepare actions.
var actions = new TextAnalyticsActions()
{
RecognizeCustomEntitiesActions = new List <RecognizeCustomEntitiesAction>()
{
recognizeCustomEntitiesAction
}
};
AnalyzeActionsOperation operation = await client.StartAnalyzeActionsAsync(batchDocuments, actions);
await operation.WaitForCompletionAsync();
await foreach (AnalyzeActionsResult documentsInPage in operation.Value)
{
IReadOnlyCollection <RecognizeCustomEntitiesActionResult> customEntitiesActionResults = documentsInPage.RecognizeCustomEntitiesResults;
foreach (RecognizeCustomEntitiesActionResult customEntitiesActionResult in customEntitiesActionResults)
{
Console.WriteLine($" Action name: {customEntitiesActionResult.ActionName}");
int docNumber = 1;
foreach (RecognizeEntitiesResult documentResults in customEntitiesActionResult.DocumentsResults)
{
Console.WriteLine($" Document #{docNumber++}");
Console.WriteLine($" Recognized the following {documentResults.Entities.Count} entities:");
foreach (CategorizedEntity entity in documentResults.Entities)
{
Console.WriteLine($" Entity: {entity.Text}");
Console.WriteLine($" Category: {entity.Category}");
Console.WriteLine($" Offset: {entity.Offset}");
Console.WriteLine($" Length: {entity.Length}");
Console.WriteLine($" ConfidenceScore: {entity.ConfidenceScore}");
Console.WriteLine($" SubCategory: {entity.SubCategory}");
}
Console.WriteLine("");
}
}
}
}
public void AnalyzeOperationBatchConvenience()
{
string endpoint = TestEnvironment.Endpoint;
string apiKey = TestEnvironment.ApiKey;
var client = new TextAnalyticsClient(new Uri(endpoint), new AzureKeyCredential(apiKey));
#region Snippet:AnalyzeOperationBatchConvenience
string documentA = @"We love this trail and make the trip every year. The views are breathtaking and well
worth the hike! Yesterday was foggy though, so we missed the spectacular views.
We tried again today and it was amazing. Everyone in my family liked the trail although
it was too challenging for the less athletic among us.
Not necessarily recommended for small children.
A hotel close to the trail offers services for childcare in case you want that.";
string documentB = @"Last week we stayed at Hotel Foo to celebrate our anniversary. The staff knew about
our anniversary so they helped me organize a little surprise for my partner.
The room was clean and with the decoration I requested. It was perfect!";
string documentC = @"That was the best day of my life! We went on a 4 day trip where we stayed at Hotel Foo.
They had great amenities that included an indoor pool, a spa, and a bar.
The spa offered couples massages which were really good.
The spa was clean and felt very peaceful. Overall the whole experience was great.
We will definitely come back.";
var batchDocuments = new List <string>
{
documentA,
documentB,
documentC
};
TextAnalyticsActions actions = new TextAnalyticsActions()
{
ExtractKeyPhrasesOptions = new List <ExtractKeyPhrasesOptions>()
{
new ExtractKeyPhrasesOptions()
},
RecognizeEntitiesOptions = new List <RecognizeEntitiesOptions>()
{
new RecognizeEntitiesOptions()
},
RecognizePiiEntitiesOptions = new List <RecognizePiiEntitiesOptions>()
{
new RecognizePiiEntitiesOptions()
},
RecognizeLinkedEntitiesOptions = new List <RecognizeLinkedEntitiesOptions>()
{
new RecognizeLinkedEntitiesOptions()
},
DisplayName = "AnalyzeOperationSample"
};
AnalyzeBatchActionsOperation operation = client.StartAnalyzeBatchActions(batchDocuments, actions);
TimeSpan pollingInterval = new TimeSpan(1000);
while (!operation.HasCompleted)
{
Thread.Sleep(pollingInterval);
operation.UpdateStatus();
Console.WriteLine($"Status: {operation.Status}");
//If operation has not started, all other fields are null
if (operation.Status != TextAnalyticsOperationStatus.NotStarted)
{
Console.WriteLine($"Expires On: {operation.ExpiresOn}");
Console.WriteLine($"Last modified: {operation.LastModified}");
if (!string.IsNullOrEmpty(operation.DisplayName))
{
Console.WriteLine($"Display name: {operation.DisplayName}");
}
Console.WriteLine($"Total actions: {operation.TotalActions}");
Console.WriteLine($" Succeeded actions: {operation.ActionsSucceeded}");
Console.WriteLine($" Failed actions: {operation.ActionsFailed}");
Console.WriteLine($" In progress actions: {operation.ActionsInProgress}");
}
}
foreach (AnalyzeBatchActionsResult documentsInPage in operation.GetValues())
{
RecognizeEntitiesResultCollection entitiesResult = documentsInPage.RecognizeEntitiesActionsResults.FirstOrDefault().Result;
ExtractKeyPhrasesResultCollection keyPhrasesResult = documentsInPage.ExtractKeyPhrasesActionsResults.FirstOrDefault().Result;
RecognizePiiEntitiesResultCollection piiResult = documentsInPage.RecognizePiiEntitiesActionsResults.FirstOrDefault().Result;
RecognizeLinkedEntitiesResultCollection linkedEntitiesResult = documentsInPage.RecognizeLinkedEntitiesActionsResults.FirstOrDefault().Result;
Console.WriteLine("Recognized Entities");
foreach (RecognizeEntitiesResult result in entitiesResult)
{
Console.WriteLine($" Recognized the following {result.Entities.Count} entities:");
foreach (CategorizedEntity entity in result.Entities)
{
Console.WriteLine($" Entity: {entity.Text}");
Console.WriteLine($" Category: {entity.Category}");
Console.WriteLine($" Offset: {entity.Offset}");
Console.WriteLine($" Length: {entity.Length}");
Console.WriteLine($" ConfidenceScore: {entity.ConfidenceScore}");
Console.WriteLine($" SubCategory: {entity.SubCategory}");
}
Console.WriteLine("");
}
Console.WriteLine("Recognized PII Entities");
foreach (RecognizePiiEntitiesResult result in piiResult)
{
Console.WriteLine($" Recognized the following {result.Entities.Count} PII entities:");
foreach (PiiEntity entity in result.Entities)
{
Console.WriteLine($" Entity: {entity.Text}");
Console.WriteLine($" Category: {entity.Category}");
Console.WriteLine($" Offset: {entity.Offset}");
Console.WriteLine($" Length: {entity.Length}");
Console.WriteLine($" ConfidenceScore: {entity.ConfidenceScore}");
Console.WriteLine($" SubCategory: {entity.SubCategory}");
}
Console.WriteLine("");
}
Console.WriteLine("Key Phrases");
foreach (ExtractKeyPhrasesResult result in keyPhrasesResult)
{
Console.WriteLine($" Recognized the following {result.KeyPhrases.Count} Keyphrases:");
foreach (string keyphrase in result.KeyPhrases)
{
Console.WriteLine($" {keyphrase}");
}
Console.WriteLine("");
}
Console.WriteLine("Recognized Linked Entities");
foreach (RecognizeLinkedEntitiesResult result in linkedEntitiesResult)
{
Console.WriteLine($" Recognized the following {result.Entities.Count} linked entities:");
foreach (LinkedEntity entity in result.Entities)
{
Console.WriteLine($" Entity: {entity.Name}");
Console.WriteLine($" DataSource: {entity.DataSource}");
Console.WriteLine($" DataSource EntityId: {entity.DataSourceEntityId}");
Console.WriteLine($" Language: {entity.Language}");
Console.WriteLine($" DataSource Url: {entity.Url}");
Console.WriteLine($" Total Matches: {entity.Matches.Count()}");
foreach (LinkedEntityMatch match in entity.Matches)
{
Console.WriteLine($" Match Text: {match.Text}");
Console.WriteLine($" ConfidenceScore: {match.ConfidenceScore}");
Console.WriteLine($" Offset: {match.Offset}");
Console.WriteLine($" Length: {match.Length}");
}
Console.WriteLine("");
}
Console.WriteLine("");
}
}
}
public async Task RecognizeHealthcareEntitiesTest()
{
TextAnalyticsClient client = GetClient();
AnalyzeHealthcareEntitiesOperation operation = await client.StartAnalyzeHealthcareEntitiesAsync(s_batchDocuments);
await operation.WaitForCompletionAsync();
ValidateOperationProperties(operation);
List <AnalyzeHealthcareEntitiesResultCollection> resultInPages = operation.Value.ToEnumerableAsync().Result;
Assert.AreEqual(1, resultInPages.Count);
//Take the first page
var resultCollection = resultInPages.FirstOrDefault();
Assert.AreEqual(s_batchDocuments.Count, resultCollection.Count);
AnalyzeHealthcareEntitiesResult result1 = resultCollection[0];
Assert.AreEqual(s_document1ExpectedEntitiesOutput.Count, result1.Entities.Count);
Assert.IsNotNull(result1.Id);
Assert.AreEqual("1", result1.Id);
foreach (HealthcareEntity entity in result1.Entities)
{
Assert.IsTrue(s_document1ExpectedEntitiesOutput.Contains(entity.Text));
if (entity.Text == "ibuprofen")
{
var linksList = new List <string> {
"UMLS", "AOD", "ATC", "CCPSS", "CHV", "CSP", "DRUGBANK", "GS", "LCH_NW", "LNC", "MEDCIN", "MMSL", "MSH", "MTHSPL", "NCI", "NCI_CTRP", "NCI_DCP", "NCI_DTP", "NCI_FDA", "NCI_NCI-GLOSS", "NDDF", "PDQ", "RCD", "RXNORM", "SNM", "SNMI", "SNOMEDCT_US", "USP", "USPMG", "VANDF"
};
foreach (EntityDataSource entityDataSource in entity.DataSources)
{
Assert.IsTrue(linksList.Contains(entityDataSource.Name));
}
}
if (entity.Text == "100mg")
{
Assert.AreEqual(18, entity.Offset);
Assert.AreEqual("Dosage", entity.Category);
Assert.AreEqual(5, entity.Length);
}
}
Assert.AreEqual(2, result1.EntityRelations.Count());
foreach (HealthcareEntityRelation relation in result1.EntityRelations)
{
if (relation.RelationType == "DosageOfMedication")
{
var role = relation.Roles.ElementAt(0);
Assert.IsNotNull(relation.Roles);
Assert.AreEqual(2, relation.Roles.Count());
Assert.AreEqual("Dosage", role.Name);
Assert.AreEqual("100mg", role.Entity.Text);
Assert.AreEqual(18, role.Entity.Offset);
Assert.AreEqual("Dosage", role.Entity.Category);
Assert.AreEqual(5, role.Entity.Length);
}
}
}
public void ExtractSummary()
{
// Create a text analytics client.
string endpoint = TestEnvironment.Endpoint;
string apiKey = TestEnvironment.ApiKey;
var client = new TextAnalyticsClient(new Uri(endpoint), new AzureKeyCredential(apiKey));
// Get input document.
string document = @"Windows 365 was in the works before COVID-19 sent companies around the world on a scramble to secure solutions to support employees suddenly forced to work from home, but “what really put the firecracker behind it was the pandemic, it accelerated everything,” McKelvey said. She explained that customers were asking, “’How do we create an experience for people that makes them still feel connected to the company without the physical presence of being there?”
In this new world of Windows 365, remote workers flip the lid on their laptop, bootup the family workstation or clip a keyboard onto a tablet, launch a native app or modern web browser and login to their Windows 365 account.From there, their Cloud PC appears with their background, apps, settings and content just as they left it when they last were last there – in the office, at home or a coffee shop.
And then, when you’re done, you’re done.You won’t have any issues around security because you’re not saving anything on your device,” McKelvey said, noting that all the data is stored in the cloud.
The ability to login to a Cloud PC from anywhere on any device is part of Microsoft’s larger strategy around tailoring products such as Microsoft Teams and Microsoft 365 for the post-pandemic hybrid workforce of the future, she added. It enables employees accustomed to working from home to continue working from home; it enables companies to hire interns from halfway around the world; it allows startups to scale without requiring IT expertise.
“I think this will be interesting for those organizations who, for whatever reason, have shied away from virtualization.This is giving them an opportunity to try it in a way that their regular, everyday endpoint admin could manage,” McKelvey said.
The simplicity of Windows 365 won over Dean Wells, the corporate chief information officer for the Government of Nunavut. His team previously attempted to deploy a traditional virtual desktop infrastructure and found it inefficient and unsustainable given the limitations of low-bandwidth satellite internet and the constant need for IT staff to manage the network and infrastructure.
We didn’t run it for very long,” he said. “It didn’t turn out the way we had hoped.So, we actually had terminated the project and rolled back out to just regular PCs.”
He re-evaluated this decision after the Government of Nunavut was hit by a ransomware attack in November 2019 that took down everything from the phone system to the government’s servers. Microsoft helped rebuild the system, moving the government to Teams, SharePoint, OneDrive and Microsoft 365. Manchester’s team recruited the Government of Nunavut to pilot Windows 365. Wells was intrigued, especially by the ability to manage the elastic workforce securely and seamlessly.
“The impact that I believe we are finding, and the impact that we’re going to find going forward, is being able to access specialists from outside the territory and organizations outside the territory to come in and help us with our projects, being able to get people on staff with us to help us deliver the day-to-day expertise that we need to run the government,” he said.
“Being able to improve healthcare, being able to improve education, economic development is going to improve the quality of life in the communities.”";
// Prepare analyze operation input. You can add multiple documents to this list and perform the same
// operation to all of them.
var batchDocuments = new List <TextDocumentInput>
{
new TextDocumentInput("1", document)
{
Language = "en",
}
};
var summaryAction = new ExtractSummaryAction()
{
MaxSentenceCount = 5,
OrderBy = SummarySentencesOrder.Rank
};
TextAnalyticsActions actions = new TextAnalyticsActions()
{
ExtractSummaryActions = new List <ExtractSummaryAction>()
{
summaryAction
}
};
// Start analysis process.
AnalyzeActionsOperation operation = client.StartAnalyzeActions(batchDocuments, actions);
// Wait for completion with manual polling.
TimeSpan pollingInterval = new TimeSpan(1000);
while (true)
{
Console.WriteLine($"Status: {operation.Status}");
operation.UpdateStatus();
if (operation.HasCompleted)
{
break;
}
Thread.Sleep(pollingInterval);
}
// View operation status.
Console.WriteLine($"AnalyzeActions operation has completed");
Console.WriteLine();
Console.WriteLine($"Created On : {operation.CreatedOn}");
Console.WriteLine($"Expires On : {operation.ExpiresOn}");
Console.WriteLine($"Id : {operation.Id}");
Console.WriteLine($"Status : {operation.Status}");
Console.WriteLine($"Last Modified: {operation.LastModified}");
Console.WriteLine();
// View operation results.
foreach (AnalyzeActionsResult documentsInPage in operation.GetValues())
{
IReadOnlyCollection <ExtractSummaryActionResult> summaryResults = documentsInPage.ExtractSummaryResults;
foreach (ExtractSummaryActionResult summaryActionResults in summaryResults)
{
if (summaryActionResults.HasError)
{
Console.WriteLine($" Error!");
Console.WriteLine($" Action error code: {summaryActionResults.Error.ErrorCode}.");
Console.WriteLine($" Message: {summaryActionResults.Error.Message}");
continue;
}
foreach (ExtractSummaryResult documentResults in summaryActionResults.DocumentsResults)
{
if (documentResults.HasError)
{
Console.WriteLine($" Error!");
Console.WriteLine($" Document error code: {documentResults.Error.ErrorCode}.");
Console.WriteLine($" Message: {documentResults.Error.Message}");
continue;
}
Console.WriteLine($" Extracted the following {documentResults.Sentences.Count} sentence(s):");
Console.WriteLine();
foreach (SummarySentence sentence in documentResults.Sentences)
{
Console.WriteLine($" Sentence: {sentence.Text}");
Console.WriteLine($" Rank Score: {sentence.RankScore}");
Console.WriteLine($" Offset: {sentence.Offset}");
Console.WriteLine($" Length: {sentence.Length}");
Console.WriteLine();
}
}
}
}
}
static public (string identifiedLanguage, string keyPhrases, double sentiment) EvaluateUtterance(TextAnalyticsClient textAnalyticsClient, string utterance)
{
string identifiedLanguage = null;
string keyPhrases = null;
double sentiment = Int32.MinValue;
var detectLanguageResult = textAnalyticsClient.DetectLanguageAsync(new BatchInput(
new List <Input>()
{
new Input("1", utterance),
})).Result;
if (detectLanguageResult != null && detectLanguageResult.Errors.Count == 0)
{
identifiedLanguage = detectLanguageResult.Documents[0].DetectedLanguages[0].Name;
string identfiedIsoLanguage = detectLanguageResult.Documents[0].DetectedLanguages[0].Iso6391Name;
KeyPhraseBatchResult keyPhraseResult = textAnalyticsClient.KeyPhrasesAsync(new MultiLanguageBatchInput(
new List <MultiLanguageInput>()
{
new MultiLanguageInput(identfiedIsoLanguage, "1", utterance)
})).Result;
if (keyPhraseResult != null && keyPhraseResult.Errors.Count == 0)
{
// Collapse keyphrases into one space delimited string
keyPhrases = String.Join(" ", keyPhraseResult.Documents[0].KeyPhrases.Select(x => x.ToString()).ToArray());
SentimentBatchResult sentimentResult = textAnalyticsClient.SentimentAsync(
new MultiLanguageBatchInput(
new List <MultiLanguageInput>()
{
new MultiLanguageInput(identfiedIsoLanguage, "0", utterance)
})).Result;
if (sentimentResult != null && sentimentResult.Errors.Count == 0)
{
sentiment = sentimentResult.Documents[0].Score.Value;
}
}
}
return(identifiedLanguage, keyPhrases, sentiment);
}
public async Task AnalyzeOperationWithMultipleActions()
{
TextAnalyticsClient client = GetClient();
var batchDocuments = new List <TextDocumentInput>
{
new TextDocumentInput("1", "Microsoft was founded by Bill Gates and Paul Allen.")
{
Language = "en",
},
new TextDocumentInput("2", "Mi perro y mi gato tienen que ir al veterinario.")
{
Language = "es",
}
};
TextAnalyticsActions batchActions = new TextAnalyticsActions()
{
ExtractKeyPhrasesActions = new List <ExtractKeyPhrasesAction>()
{
new ExtractKeyPhrasesAction()
},
RecognizeEntitiesActions = new List <RecognizeEntitiesAction>()
{
new RecognizeEntitiesAction()
},
RecognizePiiEntitiesActions = new List <RecognizePiiEntitiesAction>()
{
new RecognizePiiEntitiesAction()
},
RecognizeLinkedEntitiesActions = new List <RecognizeLinkedEntitiesAction>()
{
new RecognizeLinkedEntitiesAction()
},
AnalyzeSentimentActions = new List <AnalyzeSentimentAction>()
{
new AnalyzeSentimentAction()
},
DisplayName = "AnalyzeOperationWithMultipleTasks"
};
AnalyzeActionsOperation operation = await client.StartAnalyzeActionsAsync(batchDocuments, batchActions);
Assert.AreEqual(0, operation.ActionsFailed);
Assert.AreEqual(0, operation.ActionsSucceeded);
Assert.AreEqual(0, operation.ActionsInProgress);
Assert.AreEqual(0, operation.ActionsTotal);
await operation.WaitForCompletionAsync();
Assert.AreEqual(0, operation.ActionsFailed);
Assert.AreEqual(5, operation.ActionsSucceeded);
Assert.AreEqual(0, operation.ActionsInProgress);
Assert.AreEqual(5, operation.ActionsTotal);
Assert.AreNotEqual(new DateTimeOffset(), operation.CreatedOn);
Assert.AreNotEqual(new DateTimeOffset(), operation.LastModified);
Assert.AreNotEqual(new DateTimeOffset(), operation.ExpiresOn);
//Take the first page
AnalyzeActionsResult resultCollection = operation.Value.ToEnumerableAsync().Result.FirstOrDefault();
IReadOnlyCollection <RecognizeEntitiesActionResult> entitiesActionsResults = resultCollection.RecognizeEntitiesActionsResults;
IReadOnlyCollection <ExtractKeyPhrasesActionResult> keyPhrasesActionsResults = resultCollection.ExtractKeyPhrasesActionsResults;
IReadOnlyCollection <RecognizePiiEntitiesActionResult> piiActionsResults = resultCollection.RecognizePiiEntitiesActionsResults;
IReadOnlyCollection <RecognizeLinkedEntitiesActionResult> entityLinkingActionsResults = resultCollection.RecognizeLinkedEntitiesActionsResults;
IReadOnlyCollection <AnalyzeSentimentActionResult> analyzeSentimentActionsResults = resultCollection.AnalyzeSentimentActionsResults;
Assert.IsNotNull(keyPhrasesActionsResults);
Assert.IsNotNull(entitiesActionsResults);
Assert.IsNotNull(piiActionsResults);
Assert.IsNotNull(entityLinkingActionsResults);
Assert.AreEqual("AnalyzeOperationWithMultipleTasks", operation.DisplayName);
// Keyphrases
ExtractKeyPhrasesResultCollection keyPhrasesResults = keyPhrasesActionsResults.FirstOrDefault().Result;
Assert.AreEqual(2, keyPhrasesResults.Count);
var keyPhrasesListId1 = new List <string> {
"Bill Gates", "Paul Allen", "Microsoft"
};
var keyPhrasesListId2 = new List <string> {
"gato", "perro", "veterinario"
};
foreach (string keyphrase in keyPhrasesResults[0].KeyPhrases)
{
Assert.IsTrue(keyPhrasesListId1.Contains(keyphrase));
}
foreach (string keyphrase in keyPhrasesResults[1].KeyPhrases)
{
Assert.IsTrue(keyPhrasesListId2.Contains(keyphrase));
}
// Entities
RecognizeEntitiesResultCollection entitiesResult = entitiesActionsResults.FirstOrDefault().Result;
Assert.AreEqual(2, entitiesResult.Count);
Assert.AreEqual(3, entitiesResult[0].Entities.Count);
var entitiesList = new List <string> {
"Bill Gates", "Microsoft", "Paul Allen"
};
foreach (CategorizedEntity entity in entitiesResult[0].Entities)
{
Assert.IsTrue(entitiesList.Contains(entity.Text));
Assert.IsNotNull(entity.Category);
Assert.IsNotNull(entity.Offset);
Assert.IsNotNull(entity.ConfidenceScore);
}
// PII
RecognizePiiEntitiesResultCollection piiResult = piiActionsResults.FirstOrDefault().Result;
Assert.AreEqual(2, piiResult.Count);
Assert.AreEqual(3, piiResult[0].Entities.Count);
Assert.IsNotNull(piiResult[0].Id);
Assert.IsNotNull(piiResult[0].Entities);
Assert.IsNotNull(piiResult[0].Error);
// Entity Linking
RecognizeLinkedEntitiesResultCollection entityLinkingResult = entityLinkingActionsResults.FirstOrDefault().Result;
Assert.AreEqual(2, entityLinkingResult.Count);
Assert.AreEqual(3, entityLinkingResult[0].Entities.Count);
Assert.IsNotNull(entityLinkingResult[0].Id);
Assert.IsNotNull(entityLinkingResult[0].Entities);
Assert.IsNotNull(entityLinkingResult[0].Error);
foreach (LinkedEntity entity in entityLinkingResult[0].Entities)
{
if (entity.Name == "Bill Gates")
{
Assert.AreEqual("Bill Gates", entity.DataSourceEntityId);
Assert.AreEqual("Wikipedia", entity.DataSource);
}
if (entity.Name == "Microsoft")
{
Assert.AreEqual("Microsoft", entity.DataSourceEntityId);
Assert.AreEqual("Wikipedia", entity.DataSource);
}
}
// Analyze sentiment
AnalyzeSentimentResultCollection analyzeSentimentResult = analyzeSentimentActionsResults.FirstOrDefault().Result;
Assert.AreEqual(2, analyzeSentimentResult.Count);
Assert.AreEqual(TextSentiment.Neutral, analyzeSentimentResult[0].DocumentSentiment.Sentiment);
Assert.AreEqual(TextSentiment.Neutral, analyzeSentimentResult[1].DocumentSentiment.Sentiment);
}
