/// <summary>
/// Creates a new environment. You can only create one environment per service instance.An attempt to create another environment
/// will result in an error. The size of the new environment can be controlled by specifying the size parameter.
/// </summary>
/// <param name="callback">The OnAnalyze callback.</param>
/// <param name="parameters">The analyze parameters.</param>
/// <param name="customData">Optional custom data.</param>
/// <returns>True if the call succeeds, false if the call is unsuccessful.</returns>
public bool Analyze(OnAnalyze callback, Parameters parameters, string customData = default(string))
{
if (callback == null)
{
throw new ArgumentNullException("callback");
}
if (parameters == null)
{
throw new ArgumentNullException("parameters");
}
AnalyzeRequest req = new AnalyzeRequest();
req.Callback = callback;
req._Parameters = parameters;
req.Data = customData;
req.OnResponse = OnAnalyzeResponse;
req.Headers["Content-Type"] = "application/json";
req.Headers["Accept"] = "application/json";
req.Parameters["version"] = NaturalLanguageUnderstandingVersion.Version;
fsData data = null;
fsResult r = sm_Serializer.TrySerialize(parameters, out data);
string sendjson = data.ToString();
req.Send = Encoding.UTF8.GetBytes(sendjson);
RESTConnector connector = RESTConnector.GetConnector(SERVICE_ID, SERVICE_ANALYZE);
if (connector == null)
{
return(false);
}
return(connector.Send(req));
}
/// <summary>
/// Delete a specific model by it's ID.
/// </summary>
/// <param name="model_id">The model to delete.</param>
/// <param name="callback">The DeleteModel callback.</param>
/// <returns></returns>
public bool DeleteModel(DeleteModelCallback callback, string model_id)
{
if (string.IsNullOrEmpty(model_id))
{
throw new ArgumentNullException("model_id");
}
if (callback == null)
{
throw new ArgumentNullException("callback");
}
RESTConnector connector = RESTConnector.GetConnector(Credentials, "/v2/models/");
if (connector == null)
{
return(false);
}
DeleteModelReq req = new DeleteModelReq();
req.Callback = callback;
req.Function = WWW.EscapeURL(model_id);
req.OnResponse = DeleteModelResponse;
req.Delete = true;
return(connector.Send(req));
}
/// <summary>
/// Identifies a language from the given text.
/// </summary>
/// <param name="text">The text sample to ID.</param>
/// <param name="callback">The callback to receive the results.</param>
/// <returns></returns>
public bool Identify(string text, IdentifyCallback callback)
{
if (string.IsNullOrEmpty(text))
{
throw new ArgumentNullException("text");
}
if (callback == null)
{
throw new ArgumentNullException("callback");
}
RESTConnector connector = RESTConnector.GetConnector(SERVICE_ID, "/v2/identify");
if (connector == null)
{
return(false);
}
IdentifyReq req = new IdentifyReq();
req.Callback = callback;
req.Send = Encoding.UTF8.GetBytes(text);
req.Headers["Content-Type"] = "text/plain";
req.OnResponse = OnIdentifyResponse;
return(connector.Send(req));
}
/// <summary>
/// Gets a classifier by classifierId.
/// </summary>
/// <returns><c>true</c>, if classifier was gotten, <c>false</c> otherwise.</returns>
/// <param name="classifierId">Classifier identifier.</param>
/// <param name="callback">Callback.</param>
public bool GetClassifier(string classifierId, OnGetClassifier callback)
{
if (string.IsNullOrEmpty(classifierId))
{
throw new ArgumentNullException("classifierId");
}
if (callback == null)
{
throw new ArgumentNullException("callback");
}
if (string.IsNullOrEmpty(mp_ApiKey))
{
mp_ApiKey = Config.Instance.GetAPIKey(SERVICE_ID);
}
if (string.IsNullOrEmpty(mp_ApiKey))
{
throw new WatsonException("GetClassifier - VISUAL_RECOGNITION_API_KEY needs to be defined in config.json");
}
RESTConnector connector = RESTConnector.GetConnector(SERVICE_ID, SERVICE_CLASSIFIERS + "/" + classifierId);
if (connector == null)
{
return(false);
}
GetClassifierReq req = new GetClassifierReq();
req.Callback = callback;
req.Parameters["api_key"] = mp_ApiKey;
req.Parameters["version"] = VisualRecognitionVersion.Version;
req.OnResponse = OnGetClassifierResp;
return(connector.Send(req));
}
/// <summary>
/// Deletes a dialog by ID.
/// </summary>
/// <param name="dialogId">The ID of the dialog to delete.</param>
/// <param name="callback">The callback to invoke on success or failure.</param>
/// <returns>Returns true if request is sent.</returns>
public bool DeleteDialog(string dialogId, OnDialogCallback callback)
{
if (string.IsNullOrEmpty(dialogId))
{
throw new ArgumentNullException("dialogId");
}
if (callback == null)
{
throw new ArgumentNullException("callback");
}
RESTConnector connector = RESTConnector.GetConnector(SERVICE_ID, "/v1/dialogs/" + dialogId);
if (connector == null)
{
return(false);
}
DeleteDialogReq req = new DeleteDialogReq();
req.Callback = callback;
req.OnResponse = OnDeleteDialogResp;
req.Delete = true;
return(connector.Send(req));
}
/// <summary>
/// Deletes the specified classifier.
/// </summary>
/// <param name="successCallback">The success callback.</param>
/// <param name="failCallback">The fail callback.</param>
/// <param name="classifierId">The ID of the classifier.</param>
/// <returns>Returns false if we failed to submit a request.</returns>
public bool DeleteClassifer(SuccessCallback <bool> successCallback, FailCallback failCallback, string classifierId, Dictionary <string, object> customData = null)
{
if (successCallback == null)
{
throw new ArgumentNullException("successCallback");
}
if (failCallback == null)
{
throw new ArgumentNullException("failCallback");
}
if (string.IsNullOrEmpty(classifierId))
{
throw new ArgumentNullException("classiferId");
}
RESTConnector connector = RESTConnector.GetConnector(Credentials, "/v1/classifiers/" + classifierId);
if (connector == null)
{
return(false);
}
DeleteClassifierReq req = new DeleteClassifierReq();
req.SuccessCallback = successCallback;
req.FailCallback = failCallback;
req.CustomData = customData == null ? new Dictionary <string, object>() : customData;
req.OnResponse = OnDeleteClassifierResp;
req.Delete = true;
return(connector.Send(req));
}
/// <summary>
/// Returns a dilemma that contains the problem and a resolution. The problem contains a set of options and objectives. The resolution
/// contains a set of optimal options, their analytical characteristics, and by default their representation on a two-dimensional space.
/// You can optionally request that the service also return a refined set of preferable options that are most likely to appeal to the
/// greatest number of users
/// </summary>
/// <param name="successCallback">The success callback.</param>
/// <param name="failCallback">The fail callback.</param>
/// <param name="problem">The decision problem.</param>
/// <param name="generateVisualization">Indicates whether to calculate the map visualization. If true, the visualization is returned if
/// the is_objective field is true for at least three columns and at least three options have a status of FRONT in the problem resolution.</param>
/// <param name="customData">Optional custom data.</param>
/// <returns></returns>
public bool GetDilemma(SuccessCallback <DilemmasResponse> successCallback, FailCallback failCallback, Problem problem, Boolean generateVisualization, Dictionary <string, object> customData = null)
{
if (successCallback == null)
{
throw new ArgumentNullException("successCallback");
}
if (failCallback == null)
{
throw new ArgumentNullException("failCallback");
}
RESTConnector connector = RESTConnector.GetConnector(Credentials, DillemaEndpoint);
if (connector == null)
{
return(false);
}
GetDilemmaRequest req = new GetDilemmaRequest();
req.SuccessCallback = successCallback;
req.FailCallback = failCallback;
req.CustomData = customData == null ? new Dictionary <string, object>() : customData;
req.OnResponse = GetDilemmaResponse;
req.Parameters["generate_visualization"] = generateVisualization.ToString();
fsData tempData = null;
_serializer.TrySerialize <Problem>(problem, out tempData);
req.Send = Encoding.UTF8.GetBytes(tempData.ToString());
req.Headers["Content-Type"] = "application/json";
return(connector.Send(req));
}
/// <summary>
/// Classify images.
///
/// Classify images with built-in or custom classifiers.
/// </summary>
/// <param name="callback">The callback function that is invoked when the operation completes.</param>
/// <param name="imagesFile">An image file (.gif, .jpg, .png, .tif) or .zip file with images. Maximum image size
/// is 10 MB. Include no more than 20 images and limit the .zip file to 100 MB. Encode the image and .zip file
/// names in UTF-8 if they contain non-ASCII characters. The service assumes UTF-8 encoding if it encounters
/// non-ASCII characters.
///
/// You can also include an image with the **url** parameter. (optional)</param>
/// <param name="imagesFilename">The filename for imagesFile. (optional)</param>
/// <param name="imagesFileContentType">The content type of imagesFile. (optional)</param>
/// <param name="url">The URL of an image (.gif, .jpg, .png, .tif) to analyze. The minimum recommended pixel
/// density is 32X32 pixels, but the service tends to perform better with images that are at least 224 x 224
/// pixels. The maximum image size is 10 MB.
///
/// You can also include images with the **images_file** parameter. (optional)</param>
/// <param name="threshold">The minimum score a class must have to be displayed in the response. Set the
/// threshold to `0.0` to return all identified classes. (optional)</param>
/// <param name="owners">The categories of classifiers to apply. The **classifier_ids** parameter overrides
/// **owners**, so make sure that **classifier_ids** is empty.
/// - Use `IBM` to classify against the `default` general classifier. You get the same result if both
/// **classifier_ids** and **owners** parameters are empty.
/// - Use `me` to classify against all your custom classifiers. However, for better performance use
/// **classifier_ids** to specify the specific custom classifiers to apply.
/// - Use both `IBM` and `me` to analyze the image against both classifier categories. (optional)</param>
/// <param name="classifierIds">Which classifiers to apply. Overrides the **owners** parameter. You can specify
/// both custom and built-in classifier IDs. The built-in `default` classifier is used if both
/// **classifier_ids** and **owners** parameters are empty.
///
/// The following built-in classifier IDs require no training:
/// - `default`: Returns classes from thousands of general tags.
/// - `food`: Enhances specificity and accuracy for images of food items.
/// - `explicit`: Evaluates whether the image might be pornographic. (optional)</param>
/// <param name="acceptLanguage">The desired language of parts of the response. See the response for details.
/// (optional, default to en)</param>
/// <returns><see cref="ClassifiedImages" />ClassifiedImages</returns>
public bool Classify(Callback <ClassifiedImages> callback, System.IO.MemoryStream imagesFile = null, string imagesFilename = null, string imagesFileContentType = null, string url = null, float?threshold = null, List <string> owners = null, List <string> classifierIds = null, string acceptLanguage = null)
{
if (callback == null)
{
throw new ArgumentNullException("`callback` is required for `Classify`");
}
RequestObject <ClassifiedImages> req = new RequestObject <ClassifiedImages>
{
Callback = callback,
HttpMethod = UnityWebRequest.kHttpVerbPOST,
DisableSslVerification = DisableSslVerification
};
foreach (KeyValuePair <string, string> kvp in customRequestHeaders)
{
req.Headers.Add(kvp.Key, kvp.Value);
}
ClearCustomRequestHeaders();
foreach (KeyValuePair <string, string> kvp in Common.GetSdkHeaders("watson_vision_combined", "V3", "Classify"))
{
req.Headers.Add(kvp.Key, kvp.Value);
}
req.Parameters["version"] = VersionDate;
req.Forms = new Dictionary <string, RESTConnector.Form>();
if (imagesFile != null)
{
req.Forms["images_file"] = new RESTConnector.Form(imagesFile, imagesFilename, imagesFileContentType);
}
if (!string.IsNullOrEmpty(url))
{
req.Forms["url"] = new RESTConnector.Form(url);
}
if (threshold != null)
{
req.Forms["threshold"] = new RESTConnector.Form(threshold.ToString());
}
if (owners != null && owners.Count > 0)
{
req.Forms["owners"] = new RESTConnector.Form(string.Join(", ", owners.ToArray()));
}
if (classifierIds != null && classifierIds.Count > 0)
{
req.Forms["classifier_ids"] = new RESTConnector.Form(string.Join(", ", classifierIds.ToArray()));
}
req.OnResponse = OnClassifyResponse;
RESTConnector connector = RESTConnector.GetConnector(Credentials, "/v3/classify");
if (connector == null)
{
return(false);
}
return(connector.Send(req));
}
private bool GetTranslation(SuccessCallback <Translations> successCallback, FailCallback failCallback, string json, Dictionary <string, object> customData = null)
{
if (successCallback == null)
{
throw new ArgumentNullException("successCallback");
}
if (failCallback == null)
{
throw new ArgumentNullException("failCallback");
}
if (string.IsNullOrEmpty(json))
{
throw new ArgumentNullException("json");
}
RESTConnector connector = RESTConnector.GetConnector(Credentials, "/v2/translate");
if (connector == null)
{
return(false);
}
TranslateReq req = new TranslateReq();
req.SuccessCallback = successCallback;
req.FailCallback = failCallback;
req.CustomData = customData == null ? new Dictionary <string, object>() : customData;
req.OnResponse = TranslateResponse;
req.Send = Encoding.UTF8.GetBytes(json);
req.Headers["accept"] = "application/json";
req.Headers["Content-Type"] = "application/json";
return(connector.Send(req));
}
/// <summary>
/// Message the specified workspaceId, input and callback.
/// </summary>
/// <param name="workspaceId">Workspace identifier.</param>
/// <param name="input">Input.</param>
/// <param name="callback">Callback.</param>
public bool Message(string workspaceId, string input, OnMessage callback)
{
if (string.IsNullOrEmpty(workspaceId))
{
throw new ArgumentNullException("workspaceId");
}
if (string.IsNullOrEmpty(input))
{
throw new ArgumentNullException("input");
}
if (callback == null)
{
throw new ArgumentNullException("callback");
}
RESTConnector connector = RESTConnector.GetConnector(SERVICE_ID, "/v2/rest/workspaces");
if (connector == null)
{
return(false);
}
string reqJson = "{{\"input\": {{\"text\": \"{0}\"}}}}";
string reqString = string.Format(reqJson, input);
MessageReq req = new MessageReq();
req.Callback = callback;
req.Headers["Content-Type"] = "application/json";
req.Function = "/" + workspaceId + "/message";
req.Send = Encoding.UTF8.GetBytes(reqString);
req.OnResponse = MessageResp;
return(connector.Send(req));
}
private bool RequestToken(Callback <CloudPakForDataTokenResponse> callback)
{
if (callback == null)
{
throw new ArgumentNullException("successCallback");
}
RESTConnector connector = new RESTConnector();
connector.URL = Url;
if (connector == null)
{
return(false);
}
RequestCloudPakForDataTokenRequest req = new RequestCloudPakForDataTokenRequest();
req.HttpMethod = UnityWebRequest.kHttpVerbGET;
req.Callback = callback;
req.Headers.Add("Content-type", "application/x-www-form-urlencoded");
req.Headers.Add("Authorization", Utility.CreateAuthorization(Username, Password));
req.OnResponse = OnRequestCloudPakForDataTokenResponse;
req.DisableSslVerification = DisableSslVerification;
return(connector.Send(req));
}
/// <summary>
/// Deletes the specified classifier.
/// </summary>
/// <param name="classifierId">The ID of the classifier.</param>
/// <param name="callback">The callback to invoke with the results.</param>
/// <returns>Returns false if we failed to submit a request.</returns>
public bool DeleteClassifer(string classifierId, OnDeleteClassifier callback)
{
if (string.IsNullOrEmpty(classifierId))
{
throw new ArgumentNullException("classiferId");
}
if (callback == null)
{
throw new ArgumentNullException("callback");
}
RESTConnector connector = RESTConnector.GetConnector(SERVICE_ID, "/v1/classifiers/" + classifierId);
if (connector == null)
{
return(false);
}
DeleteClassifierReq req = new DeleteClassifierReq();
req.Callback = callback;
req.OnResponse = OnDeleteClassifierResp;
req.Delete = true;
return(connector.Send(req));
}
/// <summary>
/// Retrieve the translation models with optional filters.
/// </summary>
/// <param name="successCallback">The success callback.</param>
/// <param name="failCallback">The fail callback.</param>
/// <param name="sourceFilter">Optional source language filter.</param>
/// <param name="targetFilter">Optional target language filter.</param>
/// <param name="defaults">Controls if we get default, non-default, or all models.</param>
/// <returns>Returns a true on success, false if it failed to submit the request.</returns>
public bool GetModels(SuccessCallback <TranslationModels> successCallback,
FailCallback failCallback,
string sourceFilter = null,
string targetFilter = null,
TypeFilter defaults = TypeFilter.ALL,
Dictionary <string, object> customData = null)
{
if (successCallback == null)
{
throw new ArgumentNullException("successCallback");
}
if (failCallback == null)
{
throw new ArgumentNullException("failCallback");
}
RESTConnector connector = RESTConnector.GetConnector(Credentials, "/v3/models");
if (connector == null)
{
return(false);
}
GetModelsReq req = new GetModelsReq();
req.Parameters["version"] = VersionDate;
req.SuccessCallback = successCallback;
req.FailCallback = failCallback;
req.HttpMethod = UnityWebRequest.kHttpVerbGET;
req.DisableSslVerification = DisableSslVerification;
req.CustomData = customData == null ? new Dictionary <string, object>() : customData;
if (req.CustomData.ContainsKey(Constants.String.CUSTOM_REQUEST_HEADERS))
{
foreach (KeyValuePair <string, string> kvp in req.CustomData[Constants.String.CUSTOM_REQUEST_HEADERS] as Dictionary <string, string> )
{
req.Headers.Add(kvp.Key, kvp.Value);
}
}
req.OnResponse = GetModelsResponse;
req.Headers["X-IBMCloud-SDK-Analytics"] = "service_name=language_translator;service_version=v3;operation_id=GetModels";
if (!string.IsNullOrEmpty(sourceFilter))
{
req.Parameters["source"] = sourceFilter;
}
if (!string.IsNullOrEmpty(targetFilter))
{
req.Parameters["target"] = targetFilter;
}
if (defaults == TypeFilter.DEFAULT)
{
req.Parameters["default"] = "true";
}
else if (defaults == TypeFilter.NON_DEFAULT)
{
req.Parameters["default"] = "false";
}
return(connector.Send(req));
}
/// <summary>
/// Deletes the specified model.
/// </summary>
/// <param name="callback">The callback.</param>
/// <param name="modelId">The model identifier.</param>
/// <param name="customData">Optional custom data.</param>
/// <returns>True if the call succeeds, false if the call is unsuccessful.</returns>
public bool DeleteModel(OnDeleteModel callback, string modelId, string customData = default(string))
{
if (callback == null)
{
throw new ArgumentNullException("callback");
}
if (string.IsNullOrEmpty(modelId))
{
throw new ArgumentNullException("modelId");
}
DeleteModelRequest req = new DeleteModelRequest();
req.Callback = callback;
req.ModelId = modelId;
req.Data = customData;
req.Parameters["version"] = NaturalLanguageUnderstandingVersion.Version;
req.OnResponse = OnDeleteModelResponse;
req.Delete = true;
RESTConnector connector = RESTConnector.GetConnector(Credentials, string.Format(ModelEndpoint, modelId));
if (connector == null)
{
return(false);
}
return(connector.Send(req));
}
/// <summary>
/// Request an IAM token using an API key.
/// </summary>
/// <param name="callback">The request callback.</param>
/// <param name="error"> The request error.</param>
/// <returns></returns>
override protected bool RequestToken(Callback <TokenData> callback)
{
if (callback == null)
{
throw new ArgumentNullException("successCallback");
}
RESTConnector connector = new RESTConnector();
connector.URL = url;
if (connector == null)
{
return(false);
}
RequestIamTokenRequest req = new RequestIamTokenRequest();
req.Callback = callback;
req.HttpMethod = UnityWebRequest.kHttpVerbGET;
req.Headers.Add("Content-type", "application/x-www-form-urlencoded");
req.Headers.Add("Authorization", Utility.CreateAuthorization(iamClientId, iamClientSecret));
req.OnResponse = OnRequestIamTokenResponse;
req.DisableSslVerification = disableSslVerification;
req.Forms = new Dictionary <string, RESTConnector.Form>();
req.Forms["grant_type"] = new RESTConnector.Form("urn:ibm:params:oauth:grant-type:apikey");
req.Forms["apikey"] = new RESTConnector.Form(iamApikey);
req.Forms["response_type"] = new RESTConnector.Form("cloud_iam");
return(connector.Send(req));
}
/// <summary>
/// Delete a specific model by it's ID.
/// </summary>
/// <param name="successCallback">The success callback.</param>
/// <param name="failCallback">The fail callback.</param>
/// <param name="model_id">The model to delete.</param>
/// <returns></returns>
public bool DeleteModel(SuccessCallback <DeleteModelResult> successCallback, FailCallback failCallback, string model_id, Dictionary <string, object> customData = null)
{
if (successCallback == null)
{
throw new ArgumentNullException("successCallback");
}
if (failCallback == null)
{
throw new ArgumentNullException("failCallback");
}
if (string.IsNullOrEmpty(model_id))
{
throw new ArgumentNullException("model_id");
}
RESTConnector connector = RESTConnector.GetConnector(Credentials, "/v2/models/");
if (connector == null)
{
return(false);
}
DeleteModelReq req = new DeleteModelReq();
req.SuccessCallback = successCallback;
req.FailCallback = failCallback;
req.CustomData = customData == null ? new Dictionary <string, object>() : customData;
req.Function = WWW.EscapeURL(model_id);
req.OnResponse = DeleteModelResponse;
req.Delete = true;
return(connector.Send(req));
}
/// <summary>
/// Returns an array of all classifiers to the callback function.
/// </summary>
/// <param name="successCallback">The success callback.</param>
/// <param name="failCallback">The fail callback.</param>
/// <returns>Returns true if the request is submitted.</returns>
public bool GetClassifiers(SuccessCallback <Classifiers> successCallback, FailCallback failCallback, Dictionary <string, object> customData = null)
{
if (successCallback == null)
{
throw new ArgumentNullException("successCallback");
}
if (failCallback == null)
{
throw new ArgumentNullException("failCallback");
}
RESTConnector connector = RESTConnector.GetConnector(Credentials, "/v1/classifiers");
if (connector == null)
{
return(false);
}
GetClassifiersReq req = new GetClassifiersReq();
req.SuccessCallback = successCallback;
req.FailCallback = failCallback;
req.CustomData = customData == null ? new Dictionary <string, object>() : customData;
req.OnResponse = OnGetClassifiersResp;
return(connector.Send(req));
}
/// <summary>
/// Identifies a language from the given text.
/// </summary>
/// <param name="successCallback">The success callback.</param>
/// <param name="failCallback">The fail callback.</param>
/// <param name="text">The text sample to ID.</param>
/// <returns></returns>
public bool Identify(SuccessCallback <IdentifiedLanguages> successCallback, FailCallback failCallback, string text, Dictionary <string, object> customData = null)
{
if (successCallback == null)
{
throw new ArgumentNullException("successCallback");
}
if (failCallback == null)
{
throw new ArgumentNullException("failCallback");
}
if (string.IsNullOrEmpty(text))
{
throw new ArgumentNullException("text");
}
RESTConnector connector = RESTConnector.GetConnector(Credentials, "/v2/identify");
if (connector == null)
{
return(false);
}
IdentifyReq req = new IdentifyReq();
req.SuccessCallback = successCallback;
req.FailCallback = failCallback;
req.CustomData = customData == null ? new Dictionary <string, object>() : customData;
req.Send = Encoding.UTF8.GetBytes(text);
req.Headers["Content-Type"] = "text/plain";
req.Headers["Accept"] = "application/json";
req.OnResponse = OnIdentifyResponse;
return(connector.Send(req));
}
/// <summary>
/// Lists available models for Relations and Entities features, including Watson Knowledge Studio
/// custom models that you have created and linked to your Natural Language Understanding service.
/// </summary>
/// <param name="successCallback">The success callback.</param>
/// <param name="failCallback">The fail callback.</param>
/// <param name="customData">Optional custom data.</param>
/// <returns>True if the call succeeds, false if the call is unsuccessful.</returns>
public bool GetModels(SuccessCallback <ListModelsResults> successCallback, FailCallback failCallback, Dictionary <string, object> customData = null)
{
if (successCallback == null)
{
throw new ArgumentNullException("successCallback");
}
if (failCallback == null)
{
throw new ArgumentNullException("failCallback");
}
GetModelsRequest req = new GetModelsRequest();
req.SuccessCallback = successCallback;
req.FailCallback = failCallback;
req.CustomData = customData == null ? new Dictionary <string, object>() : customData;
if (req.CustomData.ContainsKey(Constants.String.CUSTOM_REQUEST_HEADERS))
{
foreach (KeyValuePair <string, string> kvp in req.CustomData[Constants.String.CUSTOM_REQUEST_HEADERS] as Dictionary <string, string> )
{
req.Headers.Add(kvp.Key, kvp.Value);
}
}
req.Parameters["version"] = NaturalLanguageUnderstandingVersion.Version;
req.OnResponse = OnGetModelsResponse;
RESTConnector connector = RESTConnector.GetConnector(Credentials, ModelsEndpoint);
if (connector == null)
{
return(false);
}
return(connector.Send(req));
}
public bool GetDilemma(OnDilemma callback, Problem problem, Boolean generateVisualization, string customData = default(string))
{
if (callback == null)
{
throw new ArgumentNullException("callback");
}
RESTConnector connector = RESTConnector.GetConnector(Credentials, DillemaEndpoint);
if (connector == null)
{
return(false);
}
GetDilemmaRequest req = new GetDilemmaRequest();
req.Callback = callback;
req.OnResponse = GetDilemmaResponse;
req.Data = customData;
req.Parameters["generate_visualization"] = generateVisualization.ToString();
fsData tempData = null;
_serializer.TrySerialize <Problem>(problem, out tempData);
req.Send = Encoding.UTF8.GetBytes(tempData.ToString());
req.Headers["Content-Type"] = "application/json";
return(connector.Send(req));
}
private bool Classify(string imagePath, byte[] imageData, OnClassify callback, string[] owners = default(string[]), string[] classifierIDs = default(string[]), float threshold = default(float), string acceptLanguage = "en")
{
RESTConnector connector = RESTConnector.GetConnector(SERVICE_ID, SERVICE_CLASSIFY);
if (connector == null)
{
return(false);
}
ClassifyReq req = new ClassifyReq();
req.Callback = callback;
req.Timeout = REQUEST_TIMEOUT;
req.OnResponse = OnClassifyResp;
req.AcceptLanguage = acceptLanguage;
req.Parameters["api_key"] = mp_ApiKey;
req.Parameters["version"] = VisualRecognitionVersion.Version;
req.Headers["Content-Type"] = "application/x-www-form-urlencoded";
req.Headers["Accept-Language"] = acceptLanguage;
if (imageData != null)
{
req.Send = imageData;
}
return(connector.Send(req));
}
/// <summary>
/// Refresh an IAM token using a refresh token.
/// </summary>
/// <param name="successCallback">The success callback.</param>
/// <param name="failCallback">The fail callback.</param>
/// <param name="customData">Dictionary of custom data.</param>
/// <returns></returns>
public bool RefreshIamToken(SuccessCallback<IamTokenData> successCallback, FailCallback failCallback, Dictionary<string, object> customData = null)
{
if (successCallback == null)
throw new ArgumentNullException("successCallback");
if (failCallback == null)
throw new ArgumentNullException("failCallback");
RESTConnector connector = new RESTConnector();
connector.URL = _iamUrl;
if (connector == null)
return false;
RefreshIamTokenRequest req = new RefreshIamTokenRequest();
req.SuccessCallback = successCallback;
req.FailCallback = failCallback;
req.Headers.Add("Content-type", "application/x-www-form-urlencoded");
req.Headers.Add("Authorization", "Basic Yng6Yng=");
req.OnResponse = OnRefreshIamTokenResponse;
req.CustomData = customData == null ? new Dictionary<string, object>() : customData;
if (req.CustomData.ContainsKey(Constants.String.CUSTOM_REQUEST_HEADERS))
{
foreach (KeyValuePair<string, string> kvp in req.CustomData[Constants.String.CUSTOM_REQUEST_HEADERS] as Dictionary<string, string>)
{
req.Headers.Add(kvp.Key, kvp.Value);
}
}
req.Forms = new Dictionary<string, RESTConnector.Form>();
req.Forms["grant_type"] = new RESTConnector.Form("refresh_token");
req.Forms["refresh_token"] = new RESTConnector.Form(_iamTokenData.RefreshToken);
return connector.Send(req);
}
public bool GetDilemma(OnDilemma callback, Problem problem, Boolean generateVisualization)
{
if (callback == null)
{
throw new ArgumentNullException("callback");
}
RESTConnector connector = RESTConnector.GetConnector(SERVICE_ID, FUNCTION_DILEMMA);
if (connector == null)
{
return(false);
}
GetDilemmaRequest req = new GetDilemmaRequest();
req.Callback = callback;
req.OnResponse = GetDilemmaResponse;
req.Parameters["generate_visualization"] = generateVisualization.ToString();
fsData tempData = null;
sm_Serializer.TrySerialize <Problem>(problem, out tempData);
Log.Status("GetDilemma", "JSON: {0}", tempData.ToString());
req.Send = Encoding.UTF8.GetBytes(tempData.ToString());
req.Headers["Content-Type"] = "application/json";
return(connector.Send(req));
}
/// <summary>
/// Gets the tone analyze.
/// </summary>
/// <returns><c>true</c>, if tone analyze was gotten, <c>false</c> otherwise.</returns>
/// <param name="callback">Callback.</param>
/// <param name="text">Text.</param>
/// <param name="data">Data.</param>
public bool GetToneAnalyze(OnGetToneAnalyzed callback, string text, string data = null)
{
if (callback == null)
{
throw new ArgumentNullException("callback");
}
RESTConnector connector = RESTConnector.GetConnector(Credentials, ToneEndpoint);
if (connector == null)
{
return(false);
}
GetToneAnalyzerRequest req = new GetToneAnalyzerRequest();
req.Callback = callback;
req.OnResponse = GetToneAnalyzerResponse;
Dictionary <string, string> upload = new Dictionary <string, string>();
upload["text"] = "\"" + text + "\"";
req.Send = Encoding.UTF8.GetBytes(Json.Serialize(upload));
req.Data = data;
req.Headers["Content-Type"] = "application/json";
req.Parameters["version"] = VersionDate;
req.Parameters["sentences"] = "true";
return(connector.Send(req));
}
/// <summary>
/// Converse with the dialog system.
/// </summary>
/// <param name="dialogId">The dialog ID of the dialog to use.</param>
/// <param name="input">The text input.</param>
/// <param name="callback">The callback for receiving the responses.</param>
/// <param name="conversation_id">The conversation ID to use, if 0 then a new conversation will be started.</param>
/// <param name="client_id">The client ID of the user.</param>
/// <returns>Returns true if the request was submitted to the back-end.</returns>
public bool Converse(string dialogId, string input, OnConverse callback, int conversation_id = 0, int client_id = 0)
{
if (string.IsNullOrEmpty(dialogId))
{
throw new ArgumentNullException("dialogId");
}
if (string.IsNullOrEmpty(input))
{
throw new ArgumentNullException("input");
}
if (callback == null)
{
throw new ArgumentNullException("callback");
}
RESTConnector connector = new RESTConnector();
connector.URL = "http://aiaas.pandorabots.com/talk/1409612821373/rosie?user_key=ce95ff63dbe2ece138f3ffec7695db2b";
if (connector == null)
{
return(false);
}
ConverseReq req = new ConverseReq();
req.Callback = callback;
req.OnResponse = ConverseResp;
req.Forms = new Dictionary <string, RESTConnector.Form>();
req.Forms["input"] = new RESTConnector.Form(input);
return(connector.Send(req));
}
/// <summary>
/// Returns an array of all classifiers to the callback function.
/// </summary>
/// <param name="successCallback">The success callback.</param>
/// <param name="failCallback">The fail callback.</param>
/// <returns>Returns true if the request is submitted.</returns>
public bool GetClassifiers(SuccessCallback <Classifiers> successCallback, FailCallback failCallback, Dictionary <string, object> customData = null)
{
if (successCallback == null)
{
throw new ArgumentNullException("successCallback");
}
if (failCallback == null)
{
throw new ArgumentNullException("failCallback");
}
RESTConnector connector = RESTConnector.GetConnector(Credentials, "/v1/classifiers");
if (connector == null)
{
return(false);
}
GetClassifiersReq req = new GetClassifiersReq();
req.SuccessCallback = successCallback;
req.FailCallback = failCallback;
req.CustomData = customData == null ? new Dictionary <string, object>() : customData;
if (req.CustomData.ContainsKey(Constants.String.CUSTOM_REQUEST_HEADERS))
{
foreach (KeyValuePair <string, string> kvp in req.CustomData[Constants.String.CUSTOM_REQUEST_HEADERS] as Dictionary <string, string> )
{
req.Headers.Add(kvp.Key, kvp.Value);
}
}
req.OnResponse = OnGetClassifiersResp;
return(connector.Send(req));
}
/// <summary>
/// Get a specific model by it's ID.
/// </summary>
/// <param name="model_id"></param>
/// <param name="callback"></param>
/// <returns></returns>
public bool GetModel(string model_id, GetModelCallback callback)
{
if (string.IsNullOrEmpty(model_id))
{
throw new ArgumentNullException("model_id");
}
if (callback == null)
{
throw new ArgumentNullException("callback");
}
RESTConnector connector = RESTConnector.GetConnector(SERVICE_ID, "/v2/models/");
if (connector == null)
{
return(false);
}
GetModelReq req = new GetModelReq();
req.Callback = callback;
req.Function = WWW.EscapeURL(model_id);
req.OnResponse = GetModelResponse;
return(connector.Send(req));
}
/// <summary>
/// Refresh an IAM token using a refresh token.
/// </summary>
/// <param name="callback">The success callback.</param>
/// <param name="failCallback">The fail callback.</param>
/// <returns></returns>
public bool RefreshIamToken(Callback <IamTokenData> callback)
{
if (callback == null)
{
throw new ArgumentNullException("callback");
}
RESTConnector connector = new RESTConnector();
connector.URL = _iamUrl;
if (connector == null)
{
return(false);
}
RefreshIamTokenRequest req = new RefreshIamTokenRequest();
req.Callback = callback;
req.HttpMethod = UnityWebRequest.kHttpVerbGET;
req.Headers.Add("Content-type", "application/x-www-form-urlencoded");
req.Headers.Add("Authorization", "Basic Yng6Yng=");
req.OnResponse = OnRefreshIamTokenResponse;
req.DisableSslVerification = DisableSslVerification;
req.Forms = new Dictionary <string, RESTConnector.Form>();
req.Forms["grant_type"] = new RESTConnector.Form("refresh_token");
req.Forms["refresh_token"] = new RESTConnector.Form(_iamTokenData.RefreshToken);
return(connector.Send(req));
}
/// <summary>
/// Create model.
///
/// Uploads Translation Memory eXchange (TMX) files to customize a translation model.
///
/// You can either customize a model with a forced glossary or with a corpus that contains parallel sentences.
/// To create a model that is customized with a parallel corpus <b>and</b> a forced glossary, proceed in two
/// steps: customize with a parallel corpus first and then customize the resulting model with a glossary.
/// Depending on the type of customization and the size of the uploaded corpora, training can range from minutes
/// for a glossary to several hours for a large parallel corpus. You can upload a single forced glossary file
/// and this file must be less than <b>10 MB</b>. You can upload multiple parallel corpora tmx files. The
/// cumulative file size of all uploaded files is limited to <b>250 MB</b>. To successfully train with a
/// parallel corpus you must have at least <b>5,000 parallel sentences</b> in your corpus.
///
/// You can have a <b>maximum of 10 custom models per language pair</b>.
/// </summary>
/// <param name="callback">The callback function that is invoked when the operation completes.</param>
/// <param name="baseModelId">The model ID of the model to use as the base for customization. To see available
/// models, use the `List models` method. Usually all IBM provided models are customizable. In addition, all
/// your models that have been created via parallel corpus customization, can be further customized with a
/// forced glossary.</param>
/// <param name="forcedGlossary">A TMX file with your customizations. The customizations in the file completely
/// overwrite the domain translaton data, including high frequency or high confidence phrase translations. You
/// can upload only one glossary with a file size less than 10 MB per call. A forced glossary should contain
/// single words or short phrases. (optional)</param>
/// <param name="parallelCorpus">A TMX file with parallel sentences for source and target language. You can
/// upload multiple parallel_corpus files in one request. All uploaded parallel_corpus files combined, your
/// parallel corpus must contain at least 5,000 parallel sentences to train successfully. (optional)</param>
/// <param name="name">An optional model name that you can use to identify the model. Valid characters are
/// letters, numbers, dashes, underscores, spaces and apostrophes. The maximum length is 32 characters.
/// (optional)</param>
/// <returns><see cref="TranslationModel" />TranslationModel</returns>
public bool CreateModel(Callback <TranslationModel> callback, string baseModelId, System.IO.MemoryStream forcedGlossary = null, System.IO.MemoryStream parallelCorpus = null, string name = null)
{
if (callback == null)
{
throw new ArgumentNullException("`callback` is required for `CreateModel`");
}
if (string.IsNullOrEmpty(baseModelId))
{
throw new ArgumentNullException("`baseModelId` is required for `CreateModel`");
}
RequestObject <TranslationModel> req = new RequestObject <TranslationModel>
{
Callback = callback,
HttpMethod = UnityWebRequest.kHttpVerbPOST,
DisableSslVerification = DisableSslVerification
};
foreach (KeyValuePair <string, string> kvp in customRequestHeaders)
{
req.Headers.Add(kvp.Key, kvp.Value);
}
ClearCustomRequestHeaders();
foreach (KeyValuePair <string, string> kvp in Common.GetSdkHeaders("language_translator", "V3", "CreateModel"))
{
req.Headers.Add(kvp.Key, kvp.Value);
}
req.Parameters["version"] = VersionDate;
req.Forms = new Dictionary <string, RESTConnector.Form>();
if (forcedGlossary != null)
{
req.Forms["forced_glossary"] = new RESTConnector.Form(forcedGlossary, "filename", "application/octet-stream");
}
if (parallelCorpus != null)
{
req.Forms["parallel_corpus"] = new RESTConnector.Form(parallelCorpus, "filename", "application/octet-stream");
}
if (!string.IsNullOrEmpty(baseModelId))
{
req.Parameters["base_model_id"] = baseModelId;
}
if (!string.IsNullOrEmpty(name))
{
req.Parameters["name"] = name;
}
req.OnResponse = OnCreateModelResponse;
RESTConnector connector = RESTConnector.GetConnector(Credentials, "/v3/models");
if (connector == null)
{
return(false);
}
return(connector.Send(req));
}
/// <summary>
/// Returns a specific classifer.
/// </summary>
/// <param name="classifierId">The ID of the classifier to get.</param>
/// <param name="callback">The callback to invoke with the Classifier object.</param>
/// <returns>Returns true if the request is submitted.</returns>
public bool GetClassifier(string classifierId, OnGetClassifier callback)
{
if (string.IsNullOrEmpty(classifierId))
{
throw new ArgumentNullException("classifierId");
}
if (callback == null)
{
throw new ArgumentNullException("callback");
}
RESTConnector connector = RESTConnector.GetConnector(Credentials, "/v1/classifiers/" + classifierId);
if (connector == null)
{
return(false);
}
GetClassifierReq req = new GetClassifierReq();
req.Callback = callback;
req.OnResponse = OnGetClassifierResp;
return(connector.Send(req));
}
