Examples with Builder okhttp3.HttpUrl.Builder used on opensource projects

Example 76 with Builder

use of okhttp3.HttpUrl.Builder in project androidthings-deskclock by leinardi.

the class NetworkModule method provideOkHttpClient.

@Provides
@Singleton
public OkHttpClient provideOkHttpClient(@Named(NETWORK_TIMEOUT) Long networkTimeout) {
    OkHttpClient.Builder builder = new OkHttpClient.Builder();
    if (BuildConfig.DEBUG) {
        HttpLoggingInterceptor logging = new HttpLoggingInterceptor();
        logging.setLevel(HttpLoggingInterceptor.Level.BODY);
        builder.addInterceptor(logging);
    }
    return builder.connectTimeout(networkTimeout, TimeUnit.SECONDS).readTimeout(networkTimeout, TimeUnit.SECONDS).writeTimeout(networkTimeout, TimeUnit.SECONDS).build();
}

Example 77 with Builder

use of okhttp3.HttpUrl.Builder in project java-sdk by watson-developer-cloud.

the class SpeechToText method recognizeUsingWebSocket.

/**
 * Sends audio and returns transcription results for recognition requests over a WebSocket connection. Requests and
 * responses are enabled over a single TCP connection that abstracts much of the complexity of the request to offer
 * efficient implementation, low latency, high throughput, and an asynchronous response. By default, only final
 * results are returned for any request; to enable interim results, set the interimResults parameter to true.
 *
 * The service imposes a data size limit of 100 MB per utterance (per recognition request). You can send multiple
 * utterances over a single WebSocket connection. The service automatically detects the endianness of the incoming
 * audio and, for audio that includes multiple channels, downmixes the audio to one-channel mono during transcoding.
 * (For the audio/l16 format, you can specify the endianness.)
 *
 * @param recognizeOptions the recognize options
 * @param callback the {@link RecognizeCallback} instance where results will be sent
 * @return the {@link WebSocket}
 */
public WebSocket recognizeUsingWebSocket(RecognizeOptions recognizeOptions, RecognizeCallback callback) {
    Validator.notNull(recognizeOptions, "recognizeOptions cannot be null");
    Validator.notNull(recognizeOptions.audio(), "audio cannot be null");
    Validator.notNull(callback, "callback cannot be null");
    HttpUrl.Builder urlBuilder = HttpUrl.parse(getEndPoint() + "/v1/recognize").newBuilder();
    if (recognizeOptions.model() != null) {
        urlBuilder.addQueryParameter("model", recognizeOptions.model());
    }
    if (recognizeOptions.customizationId() != null) {
        urlBuilder.addQueryParameter("customization_id", recognizeOptions.customizationId());
    }
    if (recognizeOptions.acousticCustomizationId() != null) {
        urlBuilder.addQueryParameter("acoustic_customization_id", recognizeOptions.acousticCustomizationId());
    }
    if (recognizeOptions.version() != null) {
        urlBuilder.addQueryParameter("version", recognizeOptions.version());
    }
    if (recognizeOptions.customizationWeight() != null) {
        urlBuilder.addQueryParameter("customization_weight", String.valueOf(recognizeOptions.customizationWeight()));
    }
    String url = urlBuilder.toString().replace("https://", "wss://");
    Request.Builder builder = new Request.Builder().url(url);
    setAuthentication(builder);
    setDefaultHeaders(builder);
    OkHttpClient client = configureHttpClient();
    return client.newWebSocket(builder.build(), new SpeechToTextWebSocketListener(recognizeOptions, callback));
}

Example 78 with Builder

use of okhttp3.HttpUrl.Builder 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());
}

Example 79 with Builder

use of okhttp3.HttpUrl.Builder 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));
}

Example 80 with Builder

use of okhttp3.HttpUrl.Builder 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));
}