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solve RoutingSpeeder path issue #139

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Merged
merged 2 commits into from
Sep 13, 2023
Merged

solve RoutingSpeeder path issue #139

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eaab096
solve RoutingSpeeder path issue
Sep 11, 2023
043980d
Modify the functions
Sep 12, 2023
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10 changes: 9 additions & 1 deletion src/Plugins/BotSharp.Plugin.RoutingSpeeder/Controllers/RoutingSpeederController.cs
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Original file line number Diff line number Diff line change
Expand Up @@ -3,6 +3,7 @@
using System.Diagnostics;
using System.Text;
using System.Threading.Tasks;
using BotSharp.Abstraction.Conversations.Models;
using BotSharp.Plugin.RoutingSpeeder.Providers;
using BotSharp.Plugin.RoutingSpeeder.Providers.Models;
using Microsoft.AspNetCore.Authorization;
Expand All @@ -24,9 +25,16 @@ public RoutingSpeederController(IServiceProvider service)
public IActionResult TrainIntentClassifier(TrainingParams trainingParams)
{
var intentClassifier = _service.GetRequiredService<IntentClassifier>();
intentClassifier.InitClassifer(trainingParams.Inference);
intentClassifier.Train(trainingParams);
return Ok(intentClassifier.Labels);
}

[HttpPost("/routing-speeder/classifier/inference")]
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Is this API for train or inference?
The function name doesn't match with endpoint.

public IActionResult InferenceIntentClassifier([FromBody] DialoguePredictionModel message)
{
var intentClassifier = _service.GetRequiredService<IntentClassifier>();
var vector = intentClassifier.GetTextEmbedding(message.Text);
var predText = intentClassifier.Predict(vector);
return Ok(predText);
}
}
89 changes: 52 additions & 37 deletions src/Plugins/BotSharp.Plugin.RoutingSpeeder/Providers/IntentClassifier.cs
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Expand Up @@ -15,33 +15,33 @@
using System.Linq;
using Tensorflow.Keras;
using BotSharp.Abstraction.Agents;
using Microsoft.Extensions.Logging;

namespace BotSharp.Plugin.RoutingSpeeder.Providers;

public class IntentClassifier
{
private readonly IServiceProvider _services;
private readonly ILogger _logger;
private KnowledgeBaseSettings _knowledgeBaseSettings;
Model _model;
public Model model => _model;
private bool _isModelReady;
public bool isModelReady => _isModelReady;
private ClassifierSetting _settings;
private bool _inferenceMode = true;
private string[] _labels;
public string[] Labels => GetLabels();
private int _numLabels
{
get
{
return Labels.Length;
}
}
public string[] Labels => _labels == null ? GetLabels() : _labels;

public IntentClassifier(IServiceProvider services, ClassifierSetting settings, KnowledgeBaseSettings knowledgeBaseSettings)
public IntentClassifier(IServiceProvider services,
ClassifierSetting settings,
KnowledgeBaseSettings knowledgeBaseSettings,
ILogger logger)
{
_services = services;
_settings = settings;
_knowledgeBaseSettings = knowledgeBaseSettings;
_logger = logger;
}

private void Reset()
Expand All @@ -65,15 +65,14 @@ private void Build()
keras.layers.InputLayer((vector.Dimension), name: "Input"),
keras.layers.Dense(256, activation:"relu"),
keras.layers.Dense(256, activation:"relu"),
keras.layers.Dense(_numLabels, activation: keras.activations.Softmax)
keras.layers.Dense(GetLabels().Length, activation: keras.activations.Softmax)
};
_model = keras.Sequential(layers);

#if DEBUG
Console.WriteLine();
_model.summary();
#endif
_isModelReady = true;
}

private void Fit(NDArray x, NDArray y, TrainingParams trainingParams)
Expand All @@ -97,7 +96,7 @@ private void Fit(NDArray x, NDArray y, TrainingParams trainingParams)
earlyStop
};

var weights = LoadWeights(trainingParams.Inference);
var weights = LoadWeights();

_model.fit(x, y,
batch_size: trainingParams.BatchSize,
Expand All @@ -110,24 +109,25 @@ private void Fit(NDArray x, NDArray y, TrainingParams trainingParams)
_isModelReady = true;
}

public string LoadWeights(bool inference = true)
public string LoadWeights()
{
var agentService = _services.CreateScope()
.ServiceProvider
.GetRequiredService<IAgentService>();

var weightsFile = Path.Combine(agentService.GetDataDir(), _settings.MODEL_DIR, $"intent-classifier.h5");
var weightsFile = Path.Combine(agentService.GetDataDir(), _settings.MODEL_DIR, _settings.WEIGHT_FILE_NAME);

if (File.Exists(weightsFile) && inference)
if (File.Exists(weightsFile) && _inferenceMode)
{
_model.load_weights(weightsFile);
_isModelReady = true;
Console.WriteLine($"Successfully load the weights!");
}
else
{
var logInfo = inference ? "No available weights." : "Will implement model training process and write trained weights into local";
Console.WriteLine(logInfo);
var logInfo = _inferenceMode ? "No available weights." : "Will implement model training process and write trained weights into local";
_isModelReady = false;
_logger.LogInformation(logInfo);
}

return weightsFile;
Expand Down Expand Up @@ -159,7 +159,14 @@ public NDArray GetTextEmbedding(string text)

if (!Directory.Exists(rootDirectory))
{
throw new Exception($"No training data found! Please put training data in this path: {rootDirectory}");
Directory.CreateDirectory(rootDirectory);
}

int numFiles = Directory.GetFiles(rootDirectory).Length;

if (numFiles == 0)
{
throw new Exception($"No dialogue data found in {rootDirectory} folder! Please put dialogue data in this path: {rootDirectory}");
}

// Do embedding and store results
Expand Down Expand Up @@ -214,25 +221,32 @@ public string[] GetFiles(string prefix = "")

public string[] GetLabels()
{
if (_labels == null)
var agentService = _services.CreateScope()
.ServiceProvider
.GetRequiredService<IAgentService>();
string labelPath = Path.Combine(
agentService.GetDataDir(),
_settings.MODEL_DIR,
_settings.LABEL_FILE_NAME);

if (_inferenceMode)
{
var agentService = _services.CreateScope()
.ServiceProvider
.GetRequiredService<IAgentService>();

string[] labels = GetFiles()
if (_labels == null)
{
if (!File.Exists(labelPath))
{
throw new Exception($"Label file doesn't exist. Please training model first or move label.txt to {labelPath}");
}
_labels = File.ReadAllLines(labelPath);
}
}
else
{
_labels = GetFiles()
.Select(x => Path.GetFileName(x).Split(".")[^2])
.OrderBy(x => x)
.ToArray();

string writePath = Path.Combine(
agentService.GetDataDir(),
_settings.MODEL_DIR,
_settings.LABEL_FILE_NAME);

_labels = labels.OrderBy(x => x).ToArray();

// Write labels into the local txt file
File.WriteAllLines(writePath, _labels);
File.WriteAllLines(labelPath, _labels);
}
return _labels;
}
Expand All @@ -248,24 +262,25 @@ public string Predict(NDArray vector, float confidenceScore = 0.9f)
var prob = _model.predict(vector).numpy();
var probLabel = tf.arg_max(prob, -1).numpy().ToArray<long>();
prob = np.squeeze(prob, axis: 0);
var labelIndex = probLabel[0];

if (prob[probLabel[0]] < confidenceScore)
{
return string.Empty;
}

var labelIndex = probLabel[0];
return _labels[labelIndex];
}
public void InitClassifer(bool inference = true)
public void InitClassifer()
{
Reset();
Build();
LoadWeights(inference);
LoadWeights();
}

public void Train(TrainingParams trainingParams)
{
_inferenceMode = false;
Reset();
(var x, var y) = PrepareLoadData();
Build();
Expand Down
6 changes: 3 additions & 3 deletions src/Plugins/BotSharp.Plugin.RoutingSpeeder/Providers/Models/DialoguePredictionModel.cs
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Expand Up @@ -7,7 +7,7 @@ namespace BotSharp.Plugin.RoutingSpeeder.Providers.Models;
public class DialoguePredictionModel
{
public int Id { get; set; }
public string text { get; set; }
public string? label { get; set; }
public string? prediction { get; set; }
public string Text { get; set; }
public string? Label { get; set; }
public string? Prediction { get; set; }
}
11 changes: 6 additions & 5 deletions src/Plugins/BotSharp.Plugin.RoutingSpeeder/Settings/classifierSetting.cs
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Expand Up @@ -7,13 +7,14 @@ namespace BotSharp.Plugin.RoutingSpeeder.Settings;
public class ClassifierSetting
{
public Dictionary<string, float> LabelMappingDict { get; set; } = new Dictionary<string, float>()
{
{"goodbye", 0f},
{"greeting", 1f},
{"other", 2f}
};
{
{"goodbye", 0f},
{"greeting", 1f},
{"other", 2f}
};

public string RAW_DATA_DIR { get; set; } = "raw_data";
public string MODEL_DIR { get; set; } = "models";
public string LABEL_FILE_NAME { get; set; } = "label.txt";
public string WEIGHT_FILE_NAME { get; set; } = "intent-classifier.h5";
}