public void AnalyzeSentimentBatchConvenience()
{
string endpoint = Environment.GetEnvironmentVariable("TEXT_ANALYTICS_ENDPOINT");
string subscriptionKey = Environment.GetEnvironmentVariable("TEXT_ANALYTICS_SUBSCRIPTION_KEY");
var client = new TextAnalyticsClient(new Uri(endpoint), subscriptionKey);
var inputs = new List <string>
{
"That was the best day of my life!",
"This food is very bad.",
"I'm not sure how I feel about this product.",
"Pike place market is my favorite Seattle attraction.",
};
Debug.WriteLine($"Analyzing sentiment for inputs:");
foreach (string input in inputs)
{
Debug.WriteLine($" {input}");
}
#region Snippet:TextAnalyticsSample2AnalyzeSentimentConvenience
AnalyzeSentimentResultCollection results = client.AnalyzeSentiment(inputs);
#endregion
Debug.WriteLine($"Predicted sentiments are:");
foreach (AnalyzeSentimentResult result in results)
{
TextSentiment sentiment = result.DocumentSentiment;
Debug.WriteLine($"Document sentiment is {sentiment.SentimentClass.ToString()}, with scores: ");
Debug.WriteLine($" Positive score: {sentiment.PositiveScore:0.00}.");
Debug.WriteLine($" Neutral score: {sentiment.NeutralScore:0.00}.");
Debug.WriteLine($" Negative score: {sentiment.NegativeScore:0.00}.");
}
}
public static DocumentSentiment ToDocumentSentiment(JObject input)
{
var ti = typeof(DocumentSentiment).GetTypeInfo().DeclaredConstructors.First();
Type[] paramTypes = new Type[] {
typeof(TextSentiment),
typeof(double),
typeof(double),
typeof(double),
typeof(List<SentenceSentiment>)
};
var score = ToSentimentConfidenceScores(input);
var sentences = input.Value<JArray>("Sentences")
.Select(s => ToSentenceSentiment((JObject)s)).ToList();
TextSentiment ts = TextSentiment.Neutral;
#region GetDocumentOverall Sentiment
int sentencesPositive = sentences.Count(s =>
GetSentenceTextSentiment(s) == TextSentiment.Positive);
int sentencesNegative = sentences.Count(s =>
GetSentenceTextSentiment(s) == TextSentiment.Negative);
int sentencesNeutral = sentences.Count(s =>
GetSentenceTextSentiment(s) == TextSentiment.Neutral);
if ((sentencesPositive > 0) && (sentencesNegative > 0))
{
ts = TextSentiment.Mixed;
}
else if (sentencesPositive > 0)
{
ts = TextSentiment.Positive;
}
else if (sentencesNegative > 0)
{
ts = TextSentiment.Negative;
}
#endregion
object[] paramValues = new object[] {
ts,
score.Positive,
score.Neutral,
score.Negative,
sentences
};
DocumentSentiment instance = null;
try
{
instance = TypeHelpers.Construct<DocumentSentiment>(
paramTypes, paramValues);
}
catch (Exception)
{
}
return instance;
}
internal DocumentSentimentInternal(string id, TextSentiment sentiment, TextDocumentStatistics?statistics, SentimentConfidenceScores confidenceScores, IEnumerable <SentenceSentimentInternal> sentences, IEnumerable <TextAnalyticsWarningInternal> warnings)
{
if (id == null)
{
throw new ArgumentNullException(nameof(id));
}
if (confidenceScores == null)
{
throw new ArgumentNullException(nameof(confidenceScores));
}
if (sentences == null)
{
throw new ArgumentNullException(nameof(sentences));
}
if (warnings == null)
{
throw new ArgumentNullException(nameof(warnings));
}
Id = id;
Sentiment = sentiment;
Statistics = statistics;
ConfidenceScores = confidenceScores;
Sentences = sentences.ToList();
Warnings = warnings.ToList();
}
internal SentenceSentiment(TextSentiment sentiment, double positiveScore, double neutralScore, double negativeScore, int offset, int length)
{
Sentiment = sentiment;
ConfidenceScores = new SentimentConfidenceScores(positiveScore, neutralScore, negativeScore);
GraphemeOffset = offset;
GraphemeLength = length;
}
internal static SentimentResponseDocumentsItem DeserializeSentimentResponseDocumentsItem(JsonElement element)
{
TextSentiment sentiment = default;
SentimentConfidenceScores confidenceScores = default;
IList <SentenceSentimentInternal> sentences = default;
string id = default;
IList <DocumentWarning> warnings = default;
Optional <TextDocumentStatistics> statistics = default;
foreach (var property in element.EnumerateObject())
{
if (property.NameEquals("sentiment"))
{
sentiment = property.Value.GetString().ToTextSentiment();
continue;
}
if (property.NameEquals("confidenceScores"))
{
confidenceScores = SentimentConfidenceScores.DeserializeSentimentConfidenceScores(property.Value);
continue;
}
if (property.NameEquals("sentences"))
{
List <SentenceSentimentInternal> array = new List <SentenceSentimentInternal>();
foreach (var item in property.Value.EnumerateArray())
{
array.Add(SentenceSentimentInternal.DeserializeSentenceSentimentInternal(item));
}
sentences = array;
continue;
}
if (property.NameEquals("id"))
{
id = property.Value.GetString();
continue;
}
if (property.NameEquals("warnings"))
{
List <DocumentWarning> array = new List <DocumentWarning>();
foreach (var item in property.Value.EnumerateArray())
{
array.Add(DocumentWarning.DeserializeDocumentWarning(item));
}
warnings = array;
continue;
}
if (property.NameEquals("statistics"))
{
if (property.Value.ValueKind == JsonValueKind.Null)
{
property.ThrowNonNullablePropertyIsNull();
continue;
}
statistics = TextDocumentStatistics.DeserializeTextDocumentStatistics(property.Value);
continue;
}
}
return(new SentimentResponseDocumentsItem(id, warnings, Optional.ToNullable(statistics), sentiment, confidenceScores, sentences));
}
public void MergeFrom(AnnotationPayload other)
{
if (other == null)
{
return;
}
if (other.AnnotationSpecId.Length != 0)
{
AnnotationSpecId = other.AnnotationSpecId;
}
if (other.DisplayName.Length != 0)
{
DisplayName = other.DisplayName;
}
switch (other.DetailCase)
{
case DetailOneofCase.Translation:
if (Translation == null)
{
Translation = new global::Google.Cloud.AutoML.V1.TranslationAnnotation();
}
Translation.MergeFrom(other.Translation);
break;
case DetailOneofCase.Classification:
if (Classification == null)
{
Classification = new global::Google.Cloud.AutoML.V1.ClassificationAnnotation();
}
Classification.MergeFrom(other.Classification);
break;
case DetailOneofCase.ImageObjectDetection:
if (ImageObjectDetection == null)
{
ImageObjectDetection = new global::Google.Cloud.AutoML.V1.ImageObjectDetectionAnnotation();
}
ImageObjectDetection.MergeFrom(other.ImageObjectDetection);
break;
case DetailOneofCase.TextExtraction:
if (TextExtraction == null)
{
TextExtraction = new global::Google.Cloud.AutoML.V1.TextExtractionAnnotation();
}
TextExtraction.MergeFrom(other.TextExtraction);
break;
case DetailOneofCase.TextSentiment:
if (TextSentiment == null)
{
TextSentiment = new global::Google.Cloud.AutoML.V1.TextSentimentAnnotation();
}
TextSentiment.MergeFrom(other.TextSentiment);
break;
}
_unknownFields = pb::UnknownFieldSet.MergeFrom(_unknownFields, other._unknownFields);
}
/// <summary>
/// 分析結果をコンソールに出力
/// </summary>
/// <param name="text"></param>
/// <param name="sentiment"></param>
/// <param name="scores"></param>
private void ConsoleOutput(string text, TextSentiment sentiment, SentimentConfidenceScores scores)
{
Console.WriteLine($"\tText: \"{text}\"");
Console.WriteLine($"\tSentence sentiment: {sentiment}");
Console.WriteLine($"\tPositive score: {scores.Positive:0.00}");
Console.WriteLine($"\tNegative score: {scores.Negative:0.00}");
Console.WriteLine($"\tNeutral score: {scores.Neutral:0.00}\n");
}
internal DocumentSentimentInternal(string id, TextSentiment sentiment, TextDocumentStatistics?statistics, SentimentConfidenceScores confidenceScores, IReadOnlyList <SentenceSentimentInternal> sentences, IReadOnlyList <TextAnalyticsWarningInternal> warnings)
{
Id = id;
Sentiment = sentiment;
Statistics = statistics;
ConfidenceScores = confidenceScores;
Sentences = sentences;
Warnings = warnings;
}
public async Task AnalyzeSentimentWithLanguageTest()
{
TextAnalyticsClient client = GetClient();
string input = "El mejor test del mundo!";
AnalyzeSentimentResult result = await client.AnalyzeSentimentAsync(input, "es");
TextSentiment sentiment = result.DocumentSentiment;
Assert.AreEqual("Positive", sentiment.SentimentClass.ToString());
}
internal static DocumentSentimentInternal DeserializeDocumentSentimentInternal(JsonElement element)
{
string id = default;
TextSentiment sentiment = default;
Optional <TextDocumentStatistics> statistics = default;
SentimentConfidenceScores confidenceScores = default;
IReadOnlyList <SentenceSentimentInternal> sentences = default;
IReadOnlyList <TextAnalyticsWarningInternal> warnings = default;
foreach (var property in element.EnumerateObject())
{
if (property.NameEquals("id"))
{
id = property.Value.GetString();
continue;
}
if (property.NameEquals("sentiment"))
{
sentiment = property.Value.GetString().ToTextSentiment();
continue;
}
if (property.NameEquals("statistics"))
{
statistics = TextDocumentStatistics.DeserializeTextDocumentStatistics(property.Value);
continue;
}
if (property.NameEquals("confidenceScores"))
{
confidenceScores = SentimentConfidenceScores.DeserializeSentimentConfidenceScores(property.Value);
continue;
}
if (property.NameEquals("sentences"))
{
List <SentenceSentimentInternal> array = new List <SentenceSentimentInternal>();
foreach (var item in property.Value.EnumerateArray())
{
array.Add(SentenceSentimentInternal.DeserializeSentenceSentimentInternal(item));
}
sentences = array;
continue;
}
if (property.NameEquals("warnings"))
{
List <TextAnalyticsWarningInternal> array = new List <TextAnalyticsWarningInternal>();
foreach (var item in property.Value.EnumerateArray())
{
array.Add(TextAnalyticsWarningInternal.DeserializeTextAnalyticsWarningInternal(item));
}
warnings = array;
continue;
}
}
return(new DocumentSentimentInternal(id, sentiment, Optional.ToNullable(statistics), confidenceScores, sentences, warnings));
}
private static string ConvertSentimentToEmoji(TextSentiment sentiment)
{
string x = sentiment switch
{
TextSentiment.Positive => "🙂",
TextSentiment.Neutral => "😐",
TextSentiment.Negative => "🙁",
TextSentiment.Mixed => "😖",
_ => "❓",
};
return(x);
}
private static TextSentiment GetSentiment(string usertext, ILogger log)
{
AzureKeyCredential credentials = new AzureKeyCredential(Environment.GetEnvironmentVariable("COG_KEY"));
Uri endpoint = new Uri(Environment.GetEnvironmentVariable("COG_EP"));
var client = new TextAnalyticsClient(endpoint, credentials);
log.LogInformation($" gor sentence to analyze: {usertext}");
DocumentSentiment documentSentiment = client.AnalyzeSentiment(usertext);
TextSentiment ts = documentSentiment.Sentiment;
log.LogInformation($"CreateRating:Sentiment Score is: {ts}");
return(ts);
}
public override int GetHashCode()
{
int hash = 1;
if (detailCase_ == DetailOneofCase.Translation)
{
hash ^= Translation.GetHashCode();
}
if (detailCase_ == DetailOneofCase.Classification)
{
hash ^= Classification.GetHashCode();
}
if (detailCase_ == DetailOneofCase.ImageObjectDetection)
{
hash ^= ImageObjectDetection.GetHashCode();
}
if (detailCase_ == DetailOneofCase.VideoClassification)
{
hash ^= VideoClassification.GetHashCode();
}
if (detailCase_ == DetailOneofCase.VideoObjectTracking)
{
hash ^= VideoObjectTracking.GetHashCode();
}
if (detailCase_ == DetailOneofCase.TextExtraction)
{
hash ^= TextExtraction.GetHashCode();
}
if (detailCase_ == DetailOneofCase.TextSentiment)
{
hash ^= TextSentiment.GetHashCode();
}
if (detailCase_ == DetailOneofCase.Tables)
{
hash ^= Tables.GetHashCode();
}
if (AnnotationSpecId.Length != 0)
{
hash ^= AnnotationSpecId.GetHashCode();
}
if (DisplayName.Length != 0)
{
hash ^= DisplayName.GetHashCode();
}
hash ^= (int)detailCase_;
if (_unknownFields != null)
{
hash ^= _unknownFields.GetHashCode();
}
return(hash);
}
public static async Task <IActionResult> Run(
[HttpTrigger(AuthorizationLevel.Function, "post", Route = null)] HttpRequest req,
ILogger log)
{
log.LogInformation("CreateRating function processed a request.");
string DatabaseName = Environment.GetEnvironmentVariable("COSMOS_DB_NAME");
string CollectionName = Environment.GetEnvironmentVariable("COSMOS_COLLECTION");
string ConnectionStringSetting = Environment.GetEnvironmentVariable("COSMOS_CS");
CosmosClient cosmosClient = new CosmosClient(ConnectionStringSetting);
Container cosmosContainer = cosmosClient.GetContainer(DatabaseName, CollectionName);
// string name = req.Query["name"];
var aRating = new Rating();
string requestBody = await new StreamReader(req.Body).ReadToEndAsync();
log.LogInformation($"CreateRating : got string data: {requestBody}");
dynamic data = JsonConvert.DeserializeObject(requestBody);
log.LogInformation("CreateRating : got dynamic data");
aRating.userId = data?.userId;
aRating.productId = data?.productId;
aRating.locationName = data?.locationName;
string s_rating = data?.rating;
aRating.rating = (string.IsNullOrEmpty(s_rating))? 0: int.Parse(s_rating);
aRating.userNotes = data?.userNotes;
aRating.timestamp = new DateTime();
aRating.id = Guid.NewGuid().ToString();
Boolean ValidUser = await ValidateUserId(aRating.userId, log);
Boolean ValidProduct = await ValidateProductId(aRating.productId, log);
if (!ValidUser || !ValidProduct || !ValidateRating(aRating.rating))
{
string errorresponse = "One or more items does not exist, please try again";
return(new NotFoundObjectResult(errorresponse));
}
TextSentiment score = GetSentiment(aRating.userNotes, log);
aRating.Sentiment = score.ToString();
string okresponse = JsonConvert.SerializeObject(aRating);
ItemResponse <Rating> ratingResponse = await cosmosContainer.CreateItemAsync <Rating>(aRating, new PartitionKey(aRating.id));
return(new OkObjectResult(okresponse));
}
public async Task AnalyzeSentimentTest()
{
TextAnalyticsClient client = GetClient();
string input = "That was the best day of my life!";
AnalyzeSentimentResult result = await client.AnalyzeSentimentAsync(input);
TextSentiment sentiment = result.DocumentSentiment;
Assert.AreEqual("Positive", sentiment.SentimentClass.ToString());
Assert.IsNotNull(sentiment.PositiveScore);
Assert.IsNotNull(sentiment.NeutralScore);
Assert.IsNotNull(sentiment.NegativeScore);
Assert.IsNotNull(sentiment.Offset);
}
public void AnalyzeSentiment()
{
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);
string input = "That was the best day of my life!";
Debug.WriteLine($"Analyzing sentiment for input: \"{input}\"");
AnalyzeSentimentResult result = client.AnalyzeSentiment(input).Value;
TextSentiment sentiment = result.DocumentSentiment;
Debug.WriteLine($"Sentiment was {sentiment.SentimentClass.ToString()}, with scores: ");
Debug.WriteLine($" Positive score: {sentiment.PositiveScore:0.00}.");
Debug.WriteLine($" Neutral score: {sentiment.NeutralScore:0.00}.");
Debug.WriteLine($" Negative score: {sentiment.NeutralScore:0.00}.");
}
public void AnalyzeSentiment()
{
string endpoint = Environment.GetEnvironmentVariable("TEXT_ANALYTICS_ENDPOINT");
string subscriptionKey = Environment.GetEnvironmentVariable("TEXT_ANALYTICS_SUBSCRIPTION_KEY");
#region Snippet:TextAnalyticsSample2CreateClient
var client = new TextAnalyticsClient(new Uri(endpoint), new TextAnalyticsSubscriptionKeyCredential(subscriptionKey));
#endregion
#region Snippet:AnalyzeSentiment
string input = "That was the best day of my life!";
AnalyzeSentimentResult result = client.AnalyzeSentiment(input);
TextSentiment sentiment = result.DocumentSentiment;
Console.WriteLine($"Sentiment was {sentiment.SentimentClass.ToString()}, with scores: ");
Console.WriteLine($" Positive score: {sentiment.PositiveScore:0.00}.");
Console.WriteLine($" Neutral score: {sentiment.NeutralScore:0.00}.");
Console.WriteLine($" Negative score: {sentiment.NegativeScore:0.00}.");
#endregion
}
public static async Task <IActionResult> Run(
[HttpTrigger(AuthorizationLevel.Anonymous, "post", Route = null)] HttpRequest req
)
{
string TextInput = await DeserializerRequest(req);
if (TextInput.Length < 3)
{
return(new BadRequestObjectResult("Input Text is too short (min is 3) "));
}
if (TextInput.Length > 5000)
{
return(new BadRequestObjectResult("Input Text is too long ! (Max is 5000) "));
}
List <string> TextSplitIntoList = new List <string>();
TextSplitIntoList.AddRange(TextInput.Split('\n'));
TextSplitIntoList.RemoveAll(x => string.IsNullOrEmpty(x));
if (TextSplitIntoList.Count > 10)
{
return(new BadRequestObjectResult("Input text has too many lines (Maximum of 10 Lines)"));
}
string[] TextSplitIntoLines = TextSplitIntoList.ToArray();
TextSentiment Sentiment = await GetSentiment(TextInput);
String[] TalkingPoints = await TextAnalisis(TextInput);
String SentimentEmoji = ConvertSentimentToEmoji(Sentiment);
LinesSentiment[] SentimentsBreakdown = await GetSentimentLines(TextSplitIntoLines);
FunctionResult result = new FunctionResult(SentimentEmoji, TalkingPoints, SentimentsBreakdown);
return(new OkObjectResult(JsonConvert.SerializeObject(result)));
}
public static SentenceSentiment ToSentenceSentiment(JObject input)
{
var ti = typeof(SentenceSentiment).GetTypeInfo().DeclaredConstructors.First();
Type[] paramTypes = new Type[] {
typeof(TextSentiment),
typeof(double),
typeof(double),
typeof(double),
typeof(int),
typeof(int)
};
TextSentiment ts = (TextSentiment)input.Value<int>("Sentiment");
var score = ToSentimentConfidenceScores(input.Value<JObject>("ConfidenceScores"));
object[] paramValues = new object[] {
ts,
score.Positive,
score.Neutral,
score.Negative,
input.Value<int>("GraphemeOffset"),
input.Value<int>("GraphemeLength")
};
SentenceSentiment instance = default(SentenceSentiment);
try
{
instance = TypeHelpers.Construct<SentenceSentiment>(
paramTypes, paramValues);
}
catch (Exception)
{
}
return instance;
}
public SentimentDocumentResult(string id, IEnumerable <DocumentWarning> warnings, TextSentiment sentiment, SentimentConfidenceScores confidenceScores, IEnumerable <SentenceSentimentInternal> sentences) : base(id, warnings)
{
if (id == null)
{
throw new ArgumentNullException(nameof(id));
}
if (warnings == null)
{
throw new ArgumentNullException(nameof(warnings));
}
if (confidenceScores == null)
{
throw new ArgumentNullException(nameof(confidenceScores));
}
if (sentences == null)
{
throw new ArgumentNullException(nameof(sentences));
}
Sentiment = sentiment;
ConfidenceScores = confidenceScores;
Sentences = sentences.ToList();
}
internal SentenceSentiment(TextSentiment sentiment, string text, double positiveScore, double neutralScore, double negativeScore)
{
Sentiment = sentiment;
Text = text;
ConfidenceScores = new SentimentConfidenceScores(positiveScore, neutralScore, negativeScore);
}
public SentimentResponseDocumentsItem(string id, IEnumerable <DocumentWarning> warnings, TextSentiment sentiment, SentimentConfidenceScores confidenceScores, IEnumerable <SentenceSentimentInternal> sentences) : base(id, warnings, sentiment, confidenceScores, sentences)
{
if (id == null)
{
throw new ArgumentNullException(nameof(id));
}
if (warnings == null)
{
throw new ArgumentNullException(nameof(warnings));
}
if (confidenceScores == null)
{
throw new ArgumentNullException(nameof(confidenceScores));
}
if (sentences == null)
{
throw new ArgumentNullException(nameof(sentences));
}
}
internal SentimentResponseDocumentsItem(string id, IList <DocumentWarning> warnings, TextDocumentStatistics?statistics, TextSentiment sentiment, SentimentConfidenceScores confidenceScores, IList <SentenceSentimentInternal> sentences) : base(id, warnings, statistics, sentiment, confidenceScores, sentences)
{
}
internal SentimentDocumentResult(string id, IList <DocumentWarning> warnings, TextDocumentStatistics?statistics, TextSentiment sentiment, SentimentConfidenceScores confidenceScores, IList <SentenceSentimentInternal> sentences) : base(id, warnings, statistics)
{
Sentiment = sentiment;
ConfidenceScores = confidenceScores;
Sentences = sentences;
}
public void SetSentiment(TextSentiment value)
{
textSentiment = value;
}
