use of com.ibm.watson.developer_cloud.http.RequestBuilder in project java-sdk by watson-developer-cloud.
the class SpeechToText method deleteCorpus.
/**
* Deletes a corpus from a custom language model.
*
* Deletes an existing corpus from a custom language model. The service removes any out-of-vocabulary (OOV) words
* associated with the corpus from the custom model's words resource unless they were also added by another corpus or
* they have been modified in some way with the `POST /v1/customizations/{customization_id}/words` or `PUT
* /v1/customizations/{customization_id}/words/{word_name}` method. Removing a corpus does not affect the custom model
* until you train the model with the `POST /v1/customizations/{customization_id}/train` method. You must use
* credentials for the instance of the service that owns a model to delete its corpora.
*
* @param deleteCorpusOptions the {@link DeleteCorpusOptions} containing the options for the call
* @return a {@link ServiceCall} with a response type of Void
*/
public ServiceCall<Void> deleteCorpus(DeleteCorpusOptions deleteCorpusOptions) {
Validator.notNull(deleteCorpusOptions, "deleteCorpusOptions cannot be null");
String[] pathSegments = { "v1/customizations", "corpora" };
String[] pathParameters = { deleteCorpusOptions.customizationId(), deleteCorpusOptions.corpusName() };
RequestBuilder builder = RequestBuilder.delete(RequestBuilder.constructHttpUrl(getEndPoint(), pathSegments, pathParameters));
return createServiceCall(builder.build(), ResponseConverterUtils.getVoid());
}
use of com.ibm.watson.developer_cloud.http.RequestBuilder in project java-sdk by watson-developer-cloud.
the class SpeechToText method addCorpus.
/**
* Adds a corpus text file to a custom language model.
*
* Adds a single corpus text file of new training data to a custom language model. Use multiple requests to submit
* multiple corpus text files. You must use credentials for the instance of the service that owns a model to add a
* corpus to it. Note that adding a corpus does not affect the custom language model until you train the model for the
* new data by using the `POST /v1/customizations/{customization_id}/train` method. Submit a plain text file that
* contains sample sentences from the domain of interest to enable the service to extract words in context. The more
* sentences you add that represent the context in which speakers use words from the domain, the better the service's
* recognition accuracy. For guidelines about adding a corpus text file and for information about how the service
* parses a corpus file, see [Preparing a corpus text
* file](https://console.bluemix.net/docs/services/speech-to-text/language-resource.html#prepareCorpus). The call
* returns an HTTP 201 response code if the corpus is valid. The service then asynchronously processes the contents of
* the corpus and automatically extracts new words that it finds. This can take on the order of a minute or two to
* complete depending on the total number of words and the number of new words in the corpus, as well as the current
* load on the service. You cannot submit requests to add additional corpora or words to the custom model, or to train
* the model, until the service's analysis of the corpus for the current request completes. Use the `GET
* /v1/customizations/{customization_id}/corpora/{corpus_name}` method to check the status of the analysis. The
* service auto-populates the model's words resource with any word that is not found in its base vocabulary; these are
* referred to as out-of-vocabulary (OOV) words. You can use the `GET /v1/customizations/{customization_id}/words`
* method to examine the words resource, using other words method to eliminate typos and modify how words are
* pronounced as needed. To add a corpus file that has the same name as an existing corpus, set the allow_overwrite
* query parameter to true; otherwise, the request fails. Overwriting an existing corpus causes the service to process
* the corpus text file and extract OOV words anew. Before doing so, it removes any OOV words associated with the
* existing corpus from the model's words resource unless they were also added by another corpus or they have been
* modified in some way with the `POST /v1/customizations/{customization_id}/words` or `PUT
* /v1/customizations/{customization_id}/words/{word_name}` method. The service limits the overall amount of data that
* you can add to a custom model to a maximum of 10 million total words from all corpora combined. Also, you can add
* no more than 30 thousand new custom words to a model; this includes words that the service extracts from corpora
* and words that you add directly.
*
* @param addCorpusOptions the {@link AddCorpusOptions} containing the options for the call
* @return a {@link ServiceCall} with a response type of Void
*/
public ServiceCall<Void> addCorpus(AddCorpusOptions addCorpusOptions) {
Validator.notNull(addCorpusOptions, "addCorpusOptions cannot be null");
String[] pathSegments = { "v1/customizations", "corpora" };
String[] pathParameters = { addCorpusOptions.customizationId(), addCorpusOptions.corpusName() };
RequestBuilder builder = RequestBuilder.post(RequestBuilder.constructHttpUrl(getEndPoint(), pathSegments, pathParameters));
if (addCorpusOptions.allowOverwrite() != null) {
builder.query("allow_overwrite", String.valueOf(addCorpusOptions.allowOverwrite()));
}
MultipartBody.Builder multipartBuilder = new MultipartBody.Builder();
multipartBuilder.setType(MultipartBody.FORM);
RequestBody corpusFileBody = RequestUtils.inputStreamBody(addCorpusOptions.corpusFile(), addCorpusOptions.corpusFileContentType());
multipartBuilder.addFormDataPart("corpus_file", addCorpusOptions.corpusFilename(), corpusFileBody);
builder.body(multipartBuilder.build());
return createServiceCall(builder.build(), ResponseConverterUtils.getVoid());
}
use of com.ibm.watson.developer_cloud.http.RequestBuilder in project java-sdk by watson-developer-cloud.
the class PersonalityInsights method profile.
/**
* Generates a personality profile based on input text.
*
* Derives personality insights for up to 20 MB of input content written by an author, though the service requires
* much less text to produce an accurate profile; for more information, see [Providing sufficient
* input](https://console.bluemix.net/docs/services/personality-insights/input.html#sufficient). Accepts input in
* Arabic, English, Japanese, Korean, or Spanish and produces output in one of eleven languages. Provide plain text,
* HTML, or JSON content, and receive results in JSON or CSV format.
*
* @param profileOptions the {@link ProfileOptions} containing the options for the call
* @return a {@link ServiceCall} with a response type of {@link Profile}
*/
public ServiceCall<Profile> profile(ProfileOptions profileOptions) {
Validator.notNull(profileOptions, "profileOptions cannot be null");
String[] pathSegments = { "v3/profile" };
RequestBuilder builder = RequestBuilder.post(RequestBuilder.constructHttpUrl(getEndPoint(), pathSegments));
builder.query(VERSION, versionDate);
builder.header("Content-Type", profileOptions.contentType());
if (profileOptions.contentLanguage() != null) {
builder.header("Content-Language", profileOptions.contentLanguage());
}
if (profileOptions.acceptLanguage() != null) {
builder.header("Accept-Language", profileOptions.acceptLanguage());
}
if (profileOptions.rawScores() != null) {
builder.query("raw_scores", String.valueOf(profileOptions.rawScores()));
}
if (profileOptions.consumptionPreferences() != null) {
builder.query("consumption_preferences", String.valueOf(profileOptions.consumptionPreferences()));
}
if (profileOptions.contentType().equalsIgnoreCase(ProfileOptions.ContentType.APPLICATION_JSON)) {
builder.bodyJson(GsonSingleton.getGson().toJsonTree(profileOptions.content()).getAsJsonObject());
} else {
builder.bodyContent(profileOptions.body(), profileOptions.contentType());
}
return createServiceCall(builder.build(), ResponseConverterUtils.getObject(Profile.class));
}
use of com.ibm.watson.developer_cloud.http.RequestBuilder in project java-sdk by watson-developer-cloud.
the class VisualRecognition method updateClassifier.
/**
* Update a classifier.
*
* Update a custom classifier by adding new positive or negative classes (examples) or by adding new images to
* existing classes. You must supply at least one set of positive or negative examples. For details, see [Updating
* custom
* classifiers]
* (https://console.bluemix.net/docs/services/visual-recognition/customizing.html#updating-custom-classifiers).
* Encode all names in UTF-8 if they contain non-ASCII characters (.zip and image file names, and classifier and class
* names). The service assumes UTF-8 encoding if it encounters non-ASCII characters. **Important:** You can't update a
* custom classifier with an API key for a Lite plan. To update a custom classifier on a Lite plan, create another
* service instance on a Standard plan and re-create your custom classifier. **Tip:** Don't make retraining calls on a
* classifier until the status is ready. When you submit retraining requests in parallel, the last request overwrites
* the previous requests. The retrained property shows the last time the classifier retraining finished.
*
* @param updateClassifierOptions the {@link UpdateClassifierOptions} containing the options for the call
* @return a {@link ServiceCall} with a response type of {@link Classifier}
*/
public ServiceCall<Classifier> updateClassifier(UpdateClassifierOptions updateClassifierOptions) {
Validator.notNull(updateClassifierOptions, "updateClassifierOptions cannot be null");
Validator.isTrue((updateClassifierOptions.classNames().size() > 0) || (updateClassifierOptions.negativeExamples() != null), "At least one of classnamePositiveExamples or negativeExamples must be supplied.");
String[] pathSegments = { "v3/classifiers" };
String[] pathParameters = { updateClassifierOptions.classifierId() };
RequestBuilder builder = RequestBuilder.post(RequestBuilder.constructHttpUrl(getEndPoint(), pathSegments, pathParameters));
builder.query(VERSION, versionDate);
MultipartBody.Builder multipartBuilder = new MultipartBody.Builder();
multipartBuilder.setType(MultipartBody.FORM);
// Classes
for (String className : updateClassifierOptions.classNames()) {
String dataName = className + "_positive_examples";
File positiveExamples = updateClassifierOptions.positiveExamplesByClassName(className);
RequestBody body = RequestUtils.fileBody(positiveExamples, "application/octet-stream");
multipartBuilder.addFormDataPart(dataName, positiveExamples.getName(), body);
}
if (updateClassifierOptions.negativeExamples() != null) {
RequestBody negativeExamplesBody = RequestUtils.inputStreamBody(updateClassifierOptions.negativeExamples(), "application/octet-stream");
multipartBuilder.addFormDataPart("negative_examples", updateClassifierOptions.negativeExamplesFilename(), negativeExamplesBody);
}
builder.body(multipartBuilder.build());
return createServiceCall(builder.build(), ResponseConverterUtils.getObject(Classifier.class));
}
use of com.ibm.watson.developer_cloud.http.RequestBuilder in project java-sdk by watson-developer-cloud.
the class VisualRecognition method detectFaces.
/**
* Detect faces in images.
*
* **Important:** On April 2, 2018, the identity information in the response to calls to the Face model was removed.
* The identity information refers to the `name` of the person, `score`, and `type_hierarchy` knowledge graph. For
* details about the enhanced Face model, see the [Release
* notes](https://console.bluemix.net/docs/services/visual-recognition/release-notes.html#2april2018). Analyze and get
* data about faces in images. Responses can include estimated age and gender. This feature uses a built-in model, so
* no training is necessary. The Detect faces method does not support general biometric facial recognition. Supported
* image formats include .gif, .jpg, .png, and .tif. The maximum image size is 10 MB. The minimum recommended pixel
* density is 32X32 pixels per inch.
*
* @param detectFacesOptions the {@link DetectFacesOptions} containing the options for the call
* @return a {@link ServiceCall} with a response type of {@link DetectedFaces}
*/
public ServiceCall<DetectedFaces> detectFaces(DetectFacesOptions detectFacesOptions) {
Validator.notNull(detectFacesOptions, "detectFacesOptions cannot be null");
Validator.isTrue((detectFacesOptions.imagesFile() != null) || (detectFacesOptions.url() != null) || (detectFacesOptions.parameters() != null), "At least one of imagesFile, url, or parameters must be supplied.");
String[] pathSegments = { "v3/detect_faces" };
RequestBuilder builder = RequestBuilder.post(RequestBuilder.constructHttpUrl(getEndPoint(), pathSegments));
builder.query(VERSION, versionDate);
MultipartBody.Builder multipartBuilder = new MultipartBody.Builder();
multipartBuilder.setType(MultipartBody.FORM);
if (detectFacesOptions.imagesFile() != null) {
RequestBody imagesFileBody = RequestUtils.inputStreamBody(detectFacesOptions.imagesFile(), detectFacesOptions.imagesFileContentType());
multipartBuilder.addFormDataPart("images_file", detectFacesOptions.imagesFilename(), imagesFileBody);
}
if (detectFacesOptions.parameters() != null) {
multipartBuilder.addFormDataPart("parameters", detectFacesOptions.parameters());
}
if (detectFacesOptions.url() != null) {
multipartBuilder.addFormDataPart("url", detectFacesOptions.url());
}
builder.body(multipartBuilder.build());
return createServiceCall(builder.build(), ResponseConverterUtils.getObject(DetectedFaces.class));
}
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