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Posted to commits@nlpcraft.apache.org by ar...@apache.org on 2020/06/02 02:45:10 UTC
[incubator-nlpcraft-website] branch master updated: Doc fixes.
This is an automated email from the ASF dual-hosted git repository.
aradzinski pushed a commit to branch master
in repository https://gitbox.apache.org/repos/asf/incubator-nlpcraft-website.git
The following commit(s) were added to refs/heads/master by this push:
new f4c7a8c Doc fixes.
f4c7a8c is described below
commit f4c7a8c15b1baf715592ee6900019797a39a7ce0
Author: Aaron Radzinzski <ar...@datalingvo.com>
AuthorDate: Mon Jun 1 19:43:57 2020 -0700
Doc fixes.
---
examples/alarm_clock.html | 74 +++++++++++++++++++++++++++++++++-------------
examples/light_switch.html | 55 +++++++++++++++++++++++++++-------
examples/weather_bot.html | 35 +++++++++++++++++-----
3 files changed, 126 insertions(+), 38 deletions(-)
diff --git a/examples/alarm_clock.html b/examples/alarm_clock.html
index ca9d50f..7fbec85 100644
--- a/examples/alarm_clock.html
+++ b/examples/alarm_clock.html
@@ -255,31 +255,42 @@ public class AlarmModel extends NCModelFileAdapter {
</p>
<ul>
<li>
- On <code>line 1</code> our class extends <code>NCModelFileAdapter</code> that allows us to load most
- of the model declaration from the external JSON or YAML file (<code>line 10</code>) and only provide functionality that we
+ On line 9 our class extends <code>NCModelFileAdapter</code> that allows us to load most
+ of the model declaration from the external JSON or YAML file (line 18) and only provide functionality that we
couldn't express in declarative portion in JSON.
</li>
<li>
- <code>Lines 13-16</code> define method <code>onMatch</code> as a callback for intent <code>alarm</code>
+ Lines 21-24 define method <code>onMatch</code> as a callback for intent <code>alarm</code>
when it is detected in the user input. Method parameter <code>numToks</code> will get up to 7 tokens
of type <code>nlpcraft:num</code> (see intent definition above).
</li>
<li>
The rest of the method <code>onMatch</code> implementation is a relatively straight forward Java code
- that calculates timer delay from multiple numeric units and their types. In the end (<code>line 60</code>)
+ that calculates timer delay from multiple numeric units and their types. In the end (line 68)
it schedules a timer to print "BEEP BEEP BEEP" at calculated time. For simplicity, this message will
be printed right in the data probe console.
</li>
<li>
- On the <code>line 73</code> the intent callback simply returns a confirmation message telling
+ On the line 81 the intent callback simply returns a confirmation message telling
for what actual time the alarm clock was set.
</li>
</ul>
</section>
<section id="start_probe">
- <h3 class="section-title">Start Data Probe</h3>
+ <h3 class="section-title">Start Data Probe <sub>optional</sub></h3>
+ <div class="bq warn">
+ <p><b>Embedded Probe</b></p>
+ <p>
+ If you are using the <a href="#testing">unit test</a> that comes with this example you <b>do not</b>
+ need to start the data probe standalone as this unit test uses embedded probe mode. In this mode, the unit
+ test will be automatically start and stop the data probe from within the test itself.
+ </p>
+ <p>
+ <b>If using <a href="#testing">unit test</a> below - skip this step, you only need to start the server.</b>
+ </p>
+ </div>
<p>
- NLPCraft data models get deployed into data probe. Let's start data probe with our newly
+ NLPCraft data models get deployed into data probe. Let's start a standalone data probe with our newly
created data model. To start data probe we need to configure Run Configuration in IDEA with
the following parameters:
</p>
@@ -352,28 +363,39 @@ public class AlarmModel extends NCModelFileAdapter {
<p>
Let's create new Java class <code>AlarmTest.java</code> with the following code:
</p>
- <pre class="brush: java, highlight: [16, 26, 27, 28]">
-import org.junit.jupiter.api.*;
+ <pre class="brush: java, highlight: [20, 24, 32, 37, 38, 39]">
+package org.apache.nlpcraft.examples.alarm;
+
import org.apache.nlpcraft.common.NCException;
-import org.apache.nlpcraft.model.tools.test.*;
+import org.apache.nlpcraft.model.tools.test.NCTestClient;
+import org.apache.nlpcraft.model.tools.test.NCTestClientBuilder;
+import org.apache.nlpcraft.probe.embedded.NCEmbeddedProbe;
+import org.junit.jupiter.api.AfterAll;
+import org.junit.jupiter.api.BeforeAll;
+import org.junit.jupiter.api.Test;
import java.io.IOException;
import static org.junit.jupiter.api.Assertions.assertTrue;
class AlarmTest {
- private NCTestClient cli;
+ static private NCTestClient cli;
+
+ @BeforeAll
+ static void setUp() throws NCException, IOException {
+ NCEmbeddedProbe.start(AlarmModel.class);
- @BeforeEach
- void setUp() throws NCException, IOException {
cli = new NCTestClientBuilder().newBuilder().build();
cli.open("nlpcraft.alarm.ex"); // See alarm_model.json
}
- @AfterEach
- void tearDown() throws NCException, IOException {
- cli.close();
+ @AfterAll
+ static void tearDown() throws NCException, IOException {
+ if (cli != null)
+ cli.close();
+
+ NCEmbeddedProbe.stop();
}
@Test
@@ -382,21 +404,33 @@ class AlarmTest {
assertTrue(cli.ask("Buzz me in an hour and 15mins").isOk());
assertTrue(cli.ask("Set my alarm for 30s").isOk());
}
-} </pre>
+}
+
+ </pre>
<p>
This test is pretty straight forward:
</p>
<ul>
<li>
- On <code>line 16</code> we open the test client with the model ID (see <code>alarm_model.json</code>
+ On line 24 we open the test client with the model ID (see <code>alarm_model.json</code>
file for where we declared it).
</li>
<li>
- <code>Line 26, 27, and 28</code> is where we issue our test sentences and we should see
+ Line 37, 38, and 39 is where we issue our test sentences and we should see
the confirmation messages and eventually "BEEP BEEP BEEP" print outs in the data probe
console.
</li>
</ul>
+ <div class="bq info">
+ <p><b>Embedded Prove</b></p>
+ <p>
+ This test uses <a href="/tools/embedded_probe.html">embedded probe</a> which automatically
+ start and stops the data probe from within the tests itself. See lines 20 and 32 for details.
+ </p>
+ <p>
+ <b>NOTE:</b> when using test you don't need to start data probe standalone in a previous step.
+ </p>
+ </div>
<p>
Right click on this class in the project view and run it. You should be getting standard output in
JUnit panel as well as the output in the data probe console.
@@ -418,7 +452,7 @@ class AlarmTest {
<li><a href="#add_nlpcraft">Add NLPCraft</a></li>
<li><a href="#model">Data Model</a></li>
<li><a href="#code">Model Class</a></li>
- <li><a href="#start_probe">Start Probe</a></li>
+ <li><a href="#start_probe">Start Probe <sub>opt</sub></a></li>
<li><a href="#start_server">Start Server</a></li>
{% include quick-links.html %}
</ul>
diff --git a/examples/light_switch.html b/examples/light_switch.html
index 6a9161c..317deff 100644
--- a/examples/light_switch.html
+++ b/examples/light_switch.html
@@ -231,7 +231,18 @@ class LightSwitchModel extends NCModelFileAdapter("org/apache/nlpcraft/examples/
</ul>
</section>
<section id="start_probe">
- <h3 class="section-title">Start Data Probe</h3>
+ <h3 class="section-title">Start Data Probe <sub>optional</sub></h3>
+ <div class="bq warn">
+ <p><b>Embedded Probe</b></p>
+ <p>
+ If you are using the <a href="#testing">unit test</a> that comes with this example you <b>do not</b>
+ need to start the data probe standalone as this unit test uses embedded probe mode. In this mode, the unit
+ test will be automatically start and stop the data probe from within the test itself.
+ </p>
+ <p>
+ <b>If using <a href="#testing">unit test</a> below - skip this step, you only need to start the server.</b>
+ </p>
+ </div>
<p>
NLPCraft data models get deployed into data probe. Let's start data probe with our newly
created data model. To start data probe we need to configure Run Configuration in IDEA with
@@ -315,19 +326,28 @@ class LightSwitchModel extends NCModelFileAdapter("org/apache/nlpcraft/examples/
<p>
Let's create new Java class <code>LightSwitchTest.java</code> with the following code:
</p>
- <pre class="brush: java, highlight: [15, 24]">
-import org.junit.jupiter.api.*;
-import org.apache.nlpcraft.common.*;
-import org.apache.nlpcraft.model.tools.test.*;
-import java.io.*;
+ <pre class="brush: java, highlight: [20, 24, 32, 36]">
+package org.apache.nlpcraft.examples.lightswitch;
+
+import org.apache.nlpcraft.common.NCException;
+import org.apache.nlpcraft.model.tools.test.NCTestClient;
+import org.apache.nlpcraft.model.tools.test.NCTestClientBuilder;
+import org.apache.nlpcraft.probe.embedded.NCEmbeddedProbe;
+import org.junit.jupiter.api.AfterEach;
+import org.junit.jupiter.api.BeforeEach;
+import org.junit.jupiter.api.Test;
-import static org.junit.jupiter.api.Assertions.*;
+import java.io.IOException;
+
+import static org.junit.jupiter.api.Assertions.assertTrue;
class LightSwitchTest {
private NCTestClient cli;
@BeforeEach
void setUp() throws NCException, IOException {
+ NCEmbeddedProbe.start(LightSwitchModel.class);
+
cli = new NCTestClientBuilder().newBuilder().build();
cli.open("nlpcraft.lightswitch.ex");
@@ -335,7 +355,10 @@ class LightSwitchTest {
@AfterEach
void tearDown() throws NCException, IOException {
- cli.close();
+ if (cli != null)
+ cli.close();
+
+ NCEmbeddedProbe.stop();
}
@Test
@@ -359,14 +382,24 @@ class LightSwitchTest {
</p>
<ul>
<li>
- On <code>line 15</code> we open the test client with the model ID (see <code>lightswitch_model.yaml</code>
+ On <code>line 24</code> we open the test client with the model ID (see <code>lightswitch_model.yaml</code>
file for where we declared it).
</li>
<li>
- Test on <code>line 24</code> is where we issue our test sentences and we should see
+ Test on <code>line 36</code> is where we issue our test sentences and we should see
the confirmation messages in our test console output.
</li>
</ul>
+ <div class="bq info">
+ <p><b>Embedded Prove</b></p>
+ <p>
+ This test uses <a href="/tools/embedded_probe.html">embedded probe</a> which automatically
+ start and stops the data probe from within the tests itself. See lines 20 and 32 for details.
+ </p>
+ <p>
+ <b>NOTE:</b> when using test you don't need to start data probe standalone in a previous step.
+ </p>
+ </div>
<p>
Right click on this class in the project view and run it. You should be getting standard output in
JUnit panel as well as the output in the data probe console.
@@ -388,7 +421,7 @@ class LightSwitchTest {
<li><a href="#add_nlpcraft">Add NLPCraft</a></li>
<li><a href="#model">Data Model</a></li>
<li><a href="#code">Model Class</a></li>
- <li><a href="#start_probe">Start Probe</a></li>
+ <li><a href="#start_probe">Start Probe <sub>opt</sub></a></li>
<li><a href="#start_server">Start Server</a></li>
<li><a href="#testing">Testing</a></li>
{% include quick-links.html %}
diff --git a/examples/weather_bot.html b/examples/weather_bot.html
index afb9e86..079d706 100644
--- a/examples/weather_bot.html
+++ b/examples/weather_bot.html
@@ -269,7 +269,7 @@ id: weather_bot
<li>
Two optional terms (their IDs are <code>city</code> and <code>date</code>) define
optional city and date for the weather report. If not provided, their will be taken
- from either conversation context or assume the default value (current geo location
+ from either conversation context or assume the default value (current IP geo location
and current time, if available).
</li>
</ul>
@@ -310,9 +310,20 @@ id: weather_bot
</ul>
</section>
<section id="start_probe">
- <h3 class="section-title">Start Data Probe</h3>
+ <h3 class="section-title">Start Data Probe <sub>optional</sub></h3>
+ <div class="bq warn">
+ <p><b>Embedded Probe</b></p>
+ <p>
+ If you are using the <a href="#testing">unit test</a> that comes with this example you <b>do not</b>
+ need to start the data probe standalone as this unit test uses embedded probe mode. In this mode, the unit
+ test will be automatically start and stop the data probe from within the test itself.
+ </p>
+ <p>
+ <b>If using <a href="#testing">unit test</a> below - skip this step, you only need to start the server.</b>
+ </p>
+ </div>
<p>
- NLPCraft data models get deployed into data probe. Let's start data probe with our newly
+ NLPCraft data models get deployed into data probe. Let's start a standalone data probe with our newly
created data model. To start data probe we need to configure Run Configuration in IDEA with
the following parameters:
</p>
@@ -387,7 +398,7 @@ id: weather_bot
<p>
Let's create new Java class <code>WeatherTest.java</code> with the following code:
</p>
- <pre class="brush: java, highlight: [15, 24]">
+ <pre class="brush: java, highlight: [47, 43, 55, 59]">
package org.apache.nlpcraft.examples.weather;
import com.google.gson.Gson;
@@ -472,14 +483,24 @@ class WeatherTest {
</p>
<ul>
<li>
- On <code>line 15</code> we open the test client with the model ID (see <code>lightswitch_model.yaml</code>
+ On line 47 we open the test client with the model ID (see <code>weather_model.yaml</code>
file for where we declared it).
</li>
<li>
- Test on <code>line 24</code> is where we issue our test sentences and we should see
+ Test on line 59 is where we issue our test sentences and we should see
the confirmation messages in our test console output.
</li>
</ul>
+ <div class="bq info">
+ <p><b>Embedded Prove</b></p>
+ <p>
+ This test uses <a href="/tools/embedded_probe.html">embedded probe</a> which automatically
+ start and stops the data probe from within the tests itself. See lines 43 and 55 for details.
+ </p>
+ <p>
+ <b>NOTE:</b> when using test you don't need to start data probe standalone in a previous step.
+ </p>
+ </div>
<p>
Right click on this class in the project view and run it. You should be getting standard output in
JUnit panel as well as the output in the data probe console.
@@ -502,7 +523,7 @@ class WeatherTest {
<li><a href="#model">Data Model</a></li>
<li><a href="#code">Model Class</a></li>
<li><a href="#tools">External Tools</a></li>
- <li><a href="#start_probe">Start Probe</a></li>
+ <li><a href="#start_probe">Start Probe <sub>opt</sub></a></li>
<li><a href="#start_server">Start Server</a></li>
<li><a href="#testing">Testing</a></li>
{% include quick-links.html %}