internal void TranscribeAndExtractTagsForAGivenFile()
{
HelperFunctions.PromptForConfirmationAndExecute(
"Press Y to Continue with single file contigous transciption or any key to skip...",
() =>
{
string inputPath = HelperFunctions.GetSampleDataFullPath(customSettings.SampleDataFolders.VoiceMemosFolder);
string inputFile = Path.Combine(inputPath, customSettings.SampleIndividualFiles.SampleVoiceMemoFile);
// transcribing speech - a single file case scenario
IndividualFileTranscribe.TranscribeSpeechFileAsync(
customSettings.SpeechConfigSettings.Key, customSettings.SpeechConfigSettings.Region,
inputFile,
HelperFunctions.GetSampleDataFullPath(customSettings.SampleDataFolders.TranscribedFileFolder)).Wait();
});
HelperFunctions.PromptForConfirmationAndExecute(
"Press Y to Continue to extract tags from a single file or any key to skip...",
() =>
{
string outPath = HelperFunctions.GetSampleDataFullPath(customSettings.SampleDataFolders.TranscribedFileFolder);
string outFile = Path.Combine(outPath, customSettings.SampleIndividualFiles.SampleVoiceMemoFile) + ".txt";
TextAnalyticsClient textClient = TextAnalytics.GetClient(
customSettings.TextAnalyticsSettings.Key,
customSettings.TextAnalyticsSettings.Endpoint);
var tags = TextAnalytics.GetTags(textClient, outFile).ConfigureAwait(false).GetAwaiter().GetResult();
Console.WriteLine(string.Join(", ", tags));
});
}
private static async Task SurveyReceivedAsync(IDialogContext context, IAwaitable <object> result)
{
var activity = await result as Activity;
var text = activity?.Text;
var textAnalisysService = new TextAnalytics();
var score = await textAnalisysService.MakeRequest(text);
if (score < 50)
{
var message = context.MakeMessage();
message.AttachmentLayout = AttachmentLayoutTypes.Carousel;
var card = new ThumbnailCard
{
Title = "Sorry for not help you, but you can enter in contact through our other channels",
Subtitle = "Click on the buttons below to talk to our agents through phone or chat",
Buttons = new List <CardAction>
{
new CardAction("call", $"Call", null, $"tel:1149029052"),
new CardAction(ActionTypes.OpenUrl, $"Chat", null,
"http://www.gndi.com.br/web/guest/atendimento-em-saude")
}
};
message.Attachments.Add(card.ToAttachment());
await context.PostAsync(message);
}
else
{
await context.PostAsync("Thanks for your answer, I'll be here if you need anything else");
}
InsightUtils.TrackEvent(MenuOptions.Survey);
context.Done <object>(null);
}
private async Task MessageReceivedAsync(IDialogContext context, IAwaitable <object> result)
{
var activity = await result as Activity;
var message = context.MakeMessage();
message.Text = activity.Text;
await context.PostAsync("about to call text analytics");
TextAnalytics textAnalytics = new TextAnalytics();
string response = await textAnalytics.Start(activity.Text);
await context.PostAsync(response);
await context.PostAsync("about to call qna");
QnAMaker qna = new QnAMaker();
response = await qna.TryQuery(activity.Text);
await context.PostAsync(response);
if (response.Contains("Fall Back Response"))
{
await context.PostAsync("about to call luis");
await context.Forward(new LUIS(), AfterLuis, activity, System.Threading.CancellationToken.None);
context.Done(true);
}
}
public async Task <IActionResult> Post([FromBody] string value)
{
var ta = new TextAnalytics();
var prop = await ta.MakeRequestAsync(value);
return(new OkObjectResult(lib.getEmojiForSentiment(prop)));
}
// This method is to get the feedback from the user and generated the Score base on the Text Analytics API
private async Task feedback(IDialogContext context, IAwaitable <string> result)
{
var score = await TextAnalytics.TextAnalysis(await result);
await context.PostAsync($"You rate us as {double.Parse(score)*100}%. \r\n {await TextAnalytics.Sentiment(score)}");
context.Wait(MessageReceived);
}
public IHttpActionResult Post([FromBody] Activity activity)
{
if (string.IsNullOrEmpty(activity.Text))
{
return(NotFound());
}
string reply = "";
if (activity.Type == ActivityTypes.Message)
{
// calculate something for us to return
int length = (activity.Text ?? string.Empty).Length;
var keyPhrases = TextAnalytics.GetKeyPhrases(activity.Text, activity.Id);
//MessageDB.MessagesList.Add(message);
var keys = _keyWords_manager.FindKeyWords(activity.Text, _question_manager.CurrentTopic);
if (keys.Count == 0)
{
var topic = _keyWords_manager.RecognizeTopic(activity.Text);
if (topic != Topic.None)
{
reply = _question_manager.GetQuestion(topic);
}
}
_question_manager.AllowToNextQuestion = keys.Count > 0;
if (String.IsNullOrEmpty(reply))
{
if (_question_manager.CurrentTopic == Topic.Experience)
{
if (_question_manager.CurrentTopic == Topic.Experience)
{
string txt = "";
foreach (var key in keyPhrases.Result.documents)
{
txt += key + ", ";
}
txt += " seems cool!";
}
}
reply = _question_manager.GetQuestion();
}
// connector.Conversations.ReplyToActivityAsync(reply);
}
else
{
HandleSystemMessage(activity);
}
//var response = Request.CreateResponse(HttpStatusCode.OK);
//response.Content =
//return response;
return(Ok(reply));
}
static void Main(string[] args)
{
//1 - using LUIS
//var task1 = LUISMakerShowClient.ParseUserInput("What can you tell me about an arduino?");
//task1.Wait();
//2 - Tuple, calling text analytics
var task2 = TextAnalytics.ProcessLanguage();
task2.Wait();
Console.WriteLine(task2.Result.keyPhrases);
//3 - Face API with SDK (this is .net core so copied classes manually into my project)
BlurFaces.Process();
//4 -
TopicDetection.MakeRequest();
}
public async Task <ActionResult> Text([FromBody] InputModel inputModel)
{
if (inputModel.Document.HasContent())
{
// Get settings from cache
var settingHelper = new SettingHelper(_memoryCache);
var keys = $"{SettingKeys.TextAnalyticsEndpoint},{SettingKeys.TextAnalyticsSecret}";
Dictionary <string, string> settings = settingHelper.GetCachedSettingValuesByKeys(keys);
// Text analytics
var textAnalytics = new TextAnalytics(settings[SettingKeys.TextAnalyticsEndpoint], settings[SettingKeys.TextAnalyticsSecret]);
var response = await textAnalytics.ProcessText(inputModel.Document);
return(Ok(response));
}
// If it reaches here document has no content return HTTP 400 Bad Request
return(BadRequest(new { Message = "Document cannot be empty" }));
}
/// <summary>
/// Get Ask Question Results from Bing Web Search Result
/// </summary>
public static async Task <string[]> GetTopics(string question, string[] currentTopics)
{
// Run keyphrases extraction
TextAnalyticsResult <TextAnalyticsKeyPhrasesResult> textAnalyticsResult =
await TextAnalytics.AnalyzeKeyPhrasesAsync(question);
string[] topics = currentTopics;
if (textAnalyticsResult.Results?.Count() > 0 == true)
{
topics = textAnalyticsResult.Results.Select(r => r.KeyPhrases).FirstOrDefault();
}
if (topics?.Count() > 0)
{
topics = topics.Select(t => t.ToLower()).ToArray();
}
return(topics);
}
public TextAnalyticsTest()
{
var configuration = new ConfigurationBuilder()
.SetBasePath(Directory.GetCurrentDirectory())
.AddJsonFile("appsettings.json")
.Build();
SQLHelperConfig.ConnectionConfig = configuration.GetConnectionString("ContentderAIConnection");
var provider = new ServiceCollection()
.AddMemoryCache()
.BuildServiceProvider();
var memoryCache = provider.GetService <IMemoryCache>();
var settingHelper = new SettingHelper(memoryCache);
settingHelper.CacheAllSettings();
var keys = $"{SettingKeys.TextAnalyticsEndpoint},{SettingKeys.TextAnalyticsSecret}";
Dictionary <string, string> settings = settingHelper.GetCachedSettingValuesByKeys(keys);
_textAnalytics = new TextAnalytics(settings[SettingKeys.TextAnalyticsEndpoint], settings[SettingKeys.TextAnalyticsSecret]);
}
public async Task <ActionResult <IList> > PostKeyPhraseAsync([FromBody] DocsWithTime json)
{
Docs jsonDoc = JsonSerializer.Deserialize <Docs>(JsonSerializer.Serialize(json));
//string result = await CallTextAnalyticsAPI(jsonDoc);
string result = await TextAnalticsAPI.CallTextAnalyticsAPI(json : jsonDoc, RequestType : "keyphrases", azure_key : _configuration["azure_key"]);
TextAnalytics textanalyticsresponse = JsonSerializer.Deserialize <TextAnalytics>(result);
var p = textanalyticsresponse.documents; //.GroupBy(i => i.keyPhrases);
var allphrases = p.SelectMany(s => s.keyPhrases).ToList();
var allPhrasesCount = allphrases.GroupBy(x => x)
.Where(g => g.Count() > 1)
.Select(y => new { word = y.Key, count = y.Count() })
.ToList();
return(allPhrasesCount.ToList());
}
internal async Task ReadImageOcrTextAndTranslate(string toLanguage = "en-US")
{
string inputImageFilePath = Path.Combine(
HelperFunctions.GetSampleDataFullPath(customSettings.SampleDataFolders.PhotosToAnalyzeFolder),
customSettings.SampleIndividualFiles.PhotoFileToProcess
);
string fileNamePrefix = Path.GetFileName(inputImageFilePath);
string outFolder = HelperFunctions.GetSampleDataFullPath(customSettings.SampleDataFolders.AnalyzedImagesFolder);
string outBaseFilePath = Path.Combine(outFolder, fileNamePrefix);
// ensure destination Path exists
Directory.CreateDirectory(outFolder);
// OCR - text extraction
// Get vision client
Console.WriteLine($"Extracting Text using Vision OCR from {inputImageFilePath}...");
ComputerVisionClient visionClient = ComputerVision.Authenticate(
customSettings.ComputerVisionSettings.Endpoint,
customSettings.ComputerVisionSettings.Key);
string ocrFilePath = outBaseFilePath + "-ReadOcrResults.txt";
var ocrResult = await ComputerVision.RecognizeTextFromImageLocal(visionClient, inputImageFilePath, false);
var ocrLineTexts = ComputerVisionHelper.GetOcrResultLineTexts(ocrResult);
await File.WriteAllLinesAsync(ocrFilePath, ocrLineTexts);
Console.WriteLine($"Generated OCR output file {ocrFilePath}.");
Console.WriteLine();
// Detect Languages using Text Analytics Api
TextAnalyticsClient textClient = TextAnalytics.GetClient(
customSettings.TextAnalyticsSettings.Key,
customSettings.TextAnalyticsSettings.Endpoint
);
Console.WriteLine("Detect the language from generated OCR text using TextAnalytics...");
IEnumerable <string> sourceLanguages = await TextAnalytics.DetectLanguageBatchAsync(textClient, ocrLineTexts);
//Console.WriteLine($"Detected languages Count: {sourceLanguages.Count()}");
//Console.WriteLine($"Detected Languages: {string.Join(", ", sourceLanguages)}");
Console.WriteLine();
// Now translate the extracted text (OCR) to output language (here default is English)
Console.WriteLine($"Now translate the generated OCR file to English {toLanguage}...");
string ocrText = await File.ReadAllTextAsync(ocrFilePath);
string translatedText = await JournalHelper.Translator.Translate.TranslateTextRequestAsync(
customSettings.TranslatorConfigSettings.Key,
customSettings.TranslatorConfigSettings.Endpoint,
toLanguage,
ocrText
);
string outTranslatedFilePath = outBaseFilePath + "-translated-" + toLanguage + ".json";
if (!translatedText.StartsWith("["))
{
Console.WriteLine($"Storing the generated translation output to file: {outTranslatedFilePath}... ");
var json = JObject.Parse(translatedText);
Helper.WriteToJsonFile <JObject>(outTranslatedFilePath, json);
if (json.ContainsKey("error"))
{
Console.WriteLine($"\t\t\tTRANSLATOR ERROR: {json["error"]["code"]}");
Console.WriteLine($"\t\t\tMESSAGE: {json["error"]["message"]}");
return;
}
}
string txtFile = outTranslatedFilePath + ".txt";
Console.WriteLine($"Generating txt file with translated texts - {txtFile}");
IEnumerable <string> texts = JournalHelper.Translator.Translate.GetTranslatedTexts(translatedText);
await File.WriteAllLinesAsync(txtFile, texts);
Console.WriteLine();
}
public async Task <IActionResult> GetCommentsAnalyse([FromRoute] Guid eventId)
{
var model = new List <CommentAnalyticsDTO>();
var comments = await _commentRepo.Comments(eventId);
if (!comments.IsNullOrEmpty())
{
var inputs = new List <Input>();
foreach (var comment in comments)
{
inputs.Add(new Input()
{
Id = comment.Id.ToString(),
Text = comment.Content
});
model.Add(new CommentAnalyticsDTO()
{
CommentId = comment.Id,
Content = comment.Content,
CreatedAt = comment.CreatedAt
});
}
TextAnalytics _textAnalytics = new TextAnalytics();
var multiLanguageInputs = new List <MultiLanguageInput>();
var languageResult = _textAnalytics.DetectLanguage(inputs);
if (languageResult != null)
{
for (int i = 0; i < languageResult.Documents.Count; i++)
{
foreach (var item in model)
{
if (item.CommentId.ToString() == languageResult.Documents[i].Id)
{
item.Language = languageResult.Documents[i].DetectedLanguages[0].Name;
item.LanguageCode = languageResult.Documents[i].DetectedLanguages[0].Iso6391Name;
}
}
multiLanguageInputs.Add(new MultiLanguageInput()
{
Id = model[i].CommentId.ToString(),
Language = model[i].LanguageCode,
Text = model[i].Content
});
}
var keyPhrases = _textAnalytics.GetKeyPhrases(multiLanguageInputs);
if (keyPhrases != null)
{
for (int i = 0; i < keyPhrases.Documents.Count; i++)
{
foreach (var item in model)
{
if (item.CommentId.ToString() == keyPhrases.Documents[i].Id)
{
item.KeyPhrases = keyPhrases.Documents[i].KeyPhrases.ToList();
}
}
}
}
var sentimentResult = _textAnalytics.GetSentiment(multiLanguageInputs);
if (sentimentResult != null)
{
for (int i = 0; i < sentimentResult.Documents.Count; i++)
{
foreach (var item in model)
{
if (item.CommentId.ToString() == sentimentResult.Documents[i].Id)
{
item.Sentiment = sentimentResult.Documents[i].Score.ToString();
}
}
}
}
}
}
return(Ok(model));
}
