This project is used to support Watson training sessions at various clients conductcd by IBM Developer Advocates. Because this is a public repo, it contains no client specific information. Note however that the content may be updated over time to support different training sessions. It is therefore recommended that you clone the project at the time of your training session so the material will match the agenda of your session.
The Watson Services Guide for Developers is a summary of the information presented at the training session. It contains links to relevant information and resources and has a one page summary of each Watson API.
These are the instructions and all supporting files for the hands-on-lab exercises.
The hands on lab exercises are:
In this lab, you will familiarize yourself with the Watson Visual Recognition service by learning how to use the REST API to classify, detect faces in, and recognize text in an image, and how to create, train and then use a custom classifier. Note: This lab requires the free Postman REST client that is available for Mac, Windows and Linux.
Use the Discovery tooling to run various queries against Discovery News - an existing dataset of English-language news sources that is updated continuously, with approximately 300,000 new articles and blogs added daily.
In this lab, you will familiarize yourself with the Watson Assitant service tooling by starting to develop a sample restaurant chatbot that handles reservations for a restaurant. This lab utilizes the slots feature in the Assistant service that enables you to gather multiple pieces of information in a single dialog node and allow users of the chatbot to provide required information proactively.
This section has various code snippets relevant to participants' interests that are not easily found in the Watson API document
Note: This must be compiled with the Watson Java SDK
import com.ibm.watson.developer_cloud.natural_language_understanding.v1.NaturalLanguageUnderstanding;
import com.ibm.watson.developer_cloud.natural_language_understanding.v1.model.AnalysisResults;
import com.ibm.watson.developer_cloud.natural_language_understanding.v1.model.AnalyzeOptions;
import com.ibm.watson.developer_cloud.natural_language_understanding.v1.model.EntitiesOptions;
import com.ibm.watson.developer_cloud.natural_language_understanding.v1.model.Features;
public class CallNLUViaProxy {
public static void main(String[] args) {
// Set proxy here
System.setProperty("https.proxyHost", "nnn.nnn.nnn.nnn");
System.setProperty("https.proxyPort", "nnnn");
// Set your own NLU credentails here
NaturalLanguageUnderstanding service = new NaturalLanguageUnderstanding(
NaturalLanguageUnderstanding.VERSION_DATE_2017_02_27, "username", "password");
Map<String, String> headers = new HashMap<String, String>();
headers.put(HttpHeaders.X_WATSON_LEARNING_OPT_OUT, "True");
service.setDefaultHeaders(headers);
EntitiesOptions entities = new EntitiesOptions.Builder().sentiment(true).limit(1).build();
Features features = new Features.Builder().entities(entities).build();
AnalyzeOptions parameters = new AnalyzeOptions.Builder().url("www.cnn.com").features(features).build();
AnalysisResults results = service.analyze(parameters).execute();
System.out.println("Results\n" + results.toString());
}
}Note: This must be compiled with the Jackson JSON API
package com.ibm.demo;
import java.io.BufferedReader;
import java.io.IOException;
import java.io.InputStreamReader;
import java.net.URL;
import java.util.Base64;
import javax.net.ssl.HttpsURLConnection;
import com.fasterxml.jackson.databind.ObjectMapper;
public class CallNLURESTViaProxy {
public static void main(String[] args) throws IOException {
String baseURL = "https://gateway.watsonplatform.net/natural-language-understanding/api/v1/analyze";
// Set proxy here
System.setProperty("https.proxyHost", "nnn.nnn.nnn.nnn");
System.setProperty("https.proxyPort", "nnnn");
// Set up query parameters
StringBuilder queryParams = new StringBuilder("?version=2017-02-27");
queryParams.append("&url=www.cnn.com");
queryParams.append("&features=entities");
queryParams.append("&entities.sentiment=true");
// Set up GET request
URL url = new URL(baseURL + queryParams.toString());
HttpsURLConnection connection = (HttpsURLConnection) url.openConnection();
connection.setRequestMethod("GET");
connection.setRequestProperty("X-Watson-Learning-Opt-Out", "True");
// Set your NLU username and password below
String authStr = Base64.getEncoder()
.encodeToString("username:password".getBytes());
//setting Authorization header
connection.setRequestProperty("Authorization", "Basic " + authStr);
// Send request
int responseCode = connection.getResponseCode();
System.out.println("Sending 'GET' request to URL : " + url);
System.out.println("Response Code : " + responseCode);
// Read returned JSON as a String
BufferedReader in = new BufferedReader(
new InputStreamReader(connection.getInputStream()));
String inputLine;
StringBuilder response = new StringBuilder();
while ((inputLine = in.readLine()) != null) {
response.append(inputLine);
}
in.close();
// Use Jackson JSON lib to pretty print returned JSON
ObjectMapper mapper = new ObjectMapper();
Object json = mapper.readValue(response.toString(), Object.class);
String formattedJSON = mapper.writerWithDefaultPrettyPrinter().writeValueAsString(json);
System.out.println("JSON returned");
System.out.println(formattedJSON);
}
}import json
import os
from watson_developer_cloud import NaturalLanguageUnderstandingV1
import watson_developer_cloud.natural_language_understanding.features.v1 as Features
# set proxy in env var so it can be read by the underling Requests lib used by
# the Watson SDK
os.environ["HTTPS_PROXY"] = "https://nnn.nnn.nnn.nnn:nnnn"
# Note: if proxy requires authentication, use the following format
# os.environ["HTTPS_PROXY"] = "https://user_id:pass@proxy:port"
# Substitute your NLU credentials below
natural_language_understanding = NaturalLanguageUnderstandingV1(
version='2017-02-27',
username='username',
password='password')
response = natural_language_understanding.analyze(
url='www.cnn.com',
features = [Features.Entities(), Features.Sentiment(True)])
# Pretty print the returned JSON
print(json.dumps(response, indent=2))import json
import os
import requests
from requests.auth import HTTPBasicAuth
# set proxy in env var so it can be read by the underling Requests lib used by
# the Watson SDK
os.environ["HTTPS_PROXY"] = "https://nnn.nnn.nnn.nnn:nnnn"
# Note: if proxy requires authentication, use the following format
# os.environ["HTTPS_PROXY"] = "https://user_id:pass@proxy:port"
# Request parameters
requestParams = {'version': '2017-02-27', 'url': 'www.cnn.com', 'features': 'entities',
'entities.sentiment': 'true'}
requestURL = "https://gateway.watsonplatform.net/natural-language-understanding/api/v1/analyze"
# Substitute your NLU credentials below
username="username"
password="password"
myheader = {'X-Watson-Learning-Opt-Out': 'True'}
response = requests.get(requestURL, auth=HTTPBasicAuth(username,password), params=requestParams, headers=myheader)
# Pretty print returned JSON
print(json.dumps(response.json(), indent=2))