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aradzinski pushed a commit to branch master
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The following commit(s) were added to refs/heads/master by this push:
new 556eef6 WIP.
556eef6 is described below
commit 556eef6c4948afd8375c7acf1f8d5ee225c972fc
Author: Aaron Radzinski <[email protected]>
AuthorDate: Thu Aug 20 12:23:04 2020 -0700
WIP.
---
examples/alarm_clock.html | 8 +--
examples/light_switch.html | 147 ++++++++++++++++-----------------------------
2 files changed, 55 insertions(+), 100 deletions(-)
diff --git a/examples/alarm_clock.html b/examples/alarm_clock.html
index a4e605c..c7dfa1c 100644
--- a/examples/alarm_clock.html
+++ b/examples/alarm_clock.html
@@ -262,17 +262,17 @@ public class AlarmModel extends NCModelFileAdapter {
</p>
<ul>
<li>
- On line 10 our class extends <code>NCModelFileAdapter</code>
that allows us to load most
+ On <code>line 10</code> 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>
- Line 27 defines method <code>onMatch</code> as a callback for
intent <code>alarm</code>
+ <code>Line 27</code> defines 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>
- Note the line 22 where we use <a target="javadoc"
href="/apis/latest/org/apache/nlpcraft/model/NCIntentSample.html">@NCIntentSample</a>
+ Note the <code>line 22</code> where we use <a target="javadoc"
href="/apis/latest/org/apache/nlpcraft/model/NCIntentSample.html">@NCIntentSample</a>
annotation to provide samples of the user input that this
intent should match. Apart from documentation
purpose these samples will be used when we will be <a
href="#testing">testing out model below.</a>
</li>
@@ -283,7 +283,7 @@ public class AlarmModel extends NCModelFileAdapter {
be printed right in the data probe console.
</li>
<li>
- On the line 82 the intent callback simply returns a
confirmation message telling
+ On the <code>line 82</code> the intent callback simply returns
a confirmation message telling
for what actual time the alarm clock was set.
</li>
</ul>
diff --git a/examples/light_switch.html b/examples/light_switch.html
index d69d07c..e03c951 100644
--- a/examples/light_switch.html
+++ b/examples/light_switch.html
@@ -106,19 +106,14 @@ id: light_switch
<h3 class="section-title">Data Model</h3>
<p>
We are going to start with declaring the static part of our
semantic model using YAML which we will later load using
- <code>NCModelFileAdapter</code> in our Sccla-based model
implementation. Create new <code>lightswitch_model.yaml</code>
+ <code>NCModelFileAdapter</code> in our Scala-based model
implementation. Create new <code>lightswitch_model.yaml</code>
file and add the following model declaration into it:
</p>
- <pre class="brush: js, highlight: [10, 19, 26, 34, 42]">
+ <pre class="brush: js, highlight: [5, 14, 21, 29, 37]">
id: "nlpcraft.lightswitch.ex"
name: "Light Switch Example Model"
version: "1.0"
description: "NLI-powered light switch example model."
-examples:
- - "Set the lights on in the entire house."
- - "Turn the lights off in the guest bedroom."
- - "Could you please switch off all the lights?"
- - "Dial off illumination on the 2nd floor."
macros:
- name: "<ACTION>"
macro: "{turn|switch|dial|control|let|set|get|put}"
@@ -126,7 +121,7 @@ macros:
macro: "{entire|full|whole|total|*}"
- name: "<LIGHT>"
macro: "{all|*} {it|them|light|illumination|lamp|lamplight}"
-enabledBuiltInTokens: [] # Don't use any built-in tokens.
+enabledBuiltInTokens: [] # This example doesn't use any built-in tokens.
elements:
- id: "ls:loc"
description: "Location of lights."
@@ -182,12 +177,26 @@ intents:
<p>
Let's create new Scala class in
<code>LightSwitchModel.scala</code> with the following code:
</p>
- <pre class="brush: java, highlight: [4, 5, 6, 7, 8, 20]">
-import org.apache.nlpcraft.model._
-import org.apache.nlpcraft.model.NCIntentTerm
+ <pre class="brush: java, highlight: [5, 6, 7, 21, 22, 34]">
+package org.apache.nlpcraft.examples.lightswitch
+
+import org.apache.nlpcraft.model.{NCIntentTerm, _}
class LightSwitchModel extends
NCModelFileAdapter("org/apache/nlpcraft/examples/lightswitch/lightswitch_model.yaml")
{
@NCIntentRef("ls")
+ @NCIntentSample(Array(
+ "Turn the lights off in the entire house.",
+ "Switch on the illumination in the master bedroom closet.",
+ "Get the lights on.",
+ "Please, put the light out in the upstairs bedroom.",
+ "Set the lights on in the entire house.",
+ "Turn the lights off in the guest bedroom.",
+ "Could you please switch off all the lights?",
+ "Dial off illumination on the 2nd floor.",
+ "Please, no lights!",
+ "Kill off all the lights now!",
+ "No lights in the bedroom, please."
+ ))
def onMatch(
@NCIntentTerm("act") actTok: NCToken,
@NCIntentTerm("loc") locToks: List[NCToken]
@@ -213,20 +222,25 @@ class LightSwitchModel extends
NCModelFileAdapter("org/apache/nlpcraft/examples/
</p>
<ul>
<li>
- On <code>line 4</code> our class extends
<code>NCModelFileAdapter</code> that allows us to load most
+ On <code>line 5</code> our class extends
<code>NCModelFileAdapter</code> that allows us to load most
of the model declaration from the external YAML file and only
provide functionality that we
couldn't express in declarative portion in JSON.
</li>
<li>
- <code>Line 5</code> annotates method <code>onMatch</code> as a
callback for the intent <code>ls</code>
+ <code>Line 6</code> annotates method <code>onMatch</code> as a
callback for the intent <code>ls</code>
when it is detected in the user input.
</li>
<li>
- <code>Lines 7 and 8</code> map terms from detected intent to
the formal method parameters of the
+ Note the line 7 where we use <a target="javadoc"
href="/apis/latest/org/apache/nlpcraft/model/NCIntentSample.html">@NCIntentSample</a>
+ annotation to provide samples of the user input that this
intent should match. Apart from documentation
+ purpose these samples will be used when we will be <a
href="#testing">testing out model below.</a>
+ </li>
+ <li>
+ <code>Lines 21 and 22</code> map terms from detected intent to
the formal method parameters of the
<code>onMatch</code> method.
</li>
<li>
- On the <code>line 20</code> the intent callback simply returns
a confirmation message.
+ On the <code>line 34</code> the intent callback simply returns
a confirmation message.
</li>
</ul>
</section>
@@ -302,114 +316,55 @@ class LightSwitchModel extends
NCModelFileAdapter("org/apache/nlpcraft/examples/
<section id="testing">
<h3 class="section-title">Testing</h3>
<p>
- NLPCraft comes with easy to use <a
href="/tools/test_framework.html">test framework</a> for
- data models that can be used with
- any unit testing framework like JUnit or ScalaTest. It is
essentially a simplified
- version of Java REST client that is custom designed for data model
testing.
+ Let's develop a unit test for our model. Remember the <a
target="javadoc"
href="/apis/latest/org/apache/nlpcraft/model/NCIntentSample.html">@NCIntentSample</a>
+ annotation we have used in our code next to intent definition?
Auto-testing utility is relying on it.
</p>
<p>
- We would like to test with following user requests:
+ Part of the <a href="/tools/test_framework.html">test
framework</a>, the auto-validator class <a
+ target="javadoc"
+
href="/apis/latest/org/apache/nlpcraft/model/tools/test/NCTestAutoModelValidator.html">NCTestAutoModelValidator</a>
takes one or more model IDs
+ (or class names) and performs validation. Validation consists of
starting an embedded probe with a given model,
+ scanning for <a target="javadoc"
href="/apis/latest/org/apache/nlpcraft/model/NCIntentSample.html">@NCIntentSample</a>
annotations
+ and their corresponding callback methods, submitting each sample
input
+ sentences from <a target="javadoc"
href="/apis/latest/org/apache/nlpcraft/model/NCIntentSample.html">@NCIntentSample</a>
+ annotation and checking that resulting intent matches the intent
the sample was attached to.
</p>
- <ul>
- <li><code>"Turn the lights off in the entire house."</code></li>
- <li><code>"Switch on the illumination in the master bedroom
closet."</code></li>
- <li><code>"Get the lights on."</code></li>
- <li><code>"Please, put the light out in the upstairs
bedroom."</code></li>
- <li><code>"Set the lights on in the entire house."</code></li>
- <li><code>"Turn the lights off in the guest bedroom."</code></li>
- <li><code>"Could you please switch off all the lights?"</code></li>
- <li><code>"Dial off illumination on the 2nd floor."</code></li>
- <li><code>"Please, no lights!"</code></li>
- <li><code>"Kill off all the lights now!"</code></li>
- <li><code>"No lights in the bedroom, please."</code></li>
- </ul>
<p>
- Let's create new Java class <code>LightSwitchTest.java</code> with
the following code:
+ Note that auto-testing does not require any additional code to be
written - the class gathers all required information from the model
+ itself.
</p>
- <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 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");
- }
-
- @AfterEach
- void tearDown() throws NCException, IOException {
- if (cli != null)
- cli.close();
-
- NCEmbeddedProbe.stop();
- }
-
- @Test
- void test() throws NCException, IOException {
- assertTrue(cli.ask("Turn the lights off in the entire house.").isOk());
- assertTrue(cli.ask("Switch on the illumination in the master bedroom
closet.").isOk());
- assertTrue(cli.ask("Get the lights on.").isOk());
- assertTrue(cli.ask("Please, put the light out in the upstairs
bedroom.").isOk());
- assertTrue(cli.ask("Set the lights on in the entire house.").isOk());
- assertTrue(cli.ask("Turn the lights off in the guest
bedroom.").isOk());
- assertTrue(cli.ask("Could you please switch off all the
lights?").isOk());
- assertTrue(cli.ask("Dial off illumination on the 2nd floor.").isOk());
- assertTrue(cli.ask("Please, no lights!").isOk());
- assertTrue(cli.ask("Kill off all the lights now!").isOk());
- assertTrue(cli.ask("No lights in the bedroom, please.").isOk());
- }
-}
- </pre>
<p>
- This test is pretty straight forward:
+ Let's configure IDEA Runtime Configuration (remember - there's no
need to write any additional code here):
</p>
<ul>
<li>
- 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).
+ <b>Main class:</b>
<code>org.apache.nlpcraft.model.tools.test.NCTestAutoModelValidator</code>
</li>
<li>
- 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.
+ <b>VM options: </b>
<code>-DNLPCRAFT_TEST_MODELS=org.apache.nlpcraft.examples.lightswitch.LightSwitchModel</code>
</li>
</ul>
<div class="bq info">
<p><b>Embedded Probe</b></p>
<p>
- This test uses <a href="/tools/embedded_probe.html">embedded
probe</a> which automatically
- starts and stops the data probe from within the tests itself.
See lines 20 and 32 for details.
+ This test (as well as manual test client from <a
href="/tools/test_framework.html">test framework</a>) use
+ <a href="/tools/embedded_probe.html">embedded probe</a> which
automatically
+ starts and stops the data probe from within the tests itself.
However, when not testing you will need
+ to start data probe separately.
</p>
<p>
- <b>NOTE:</b> when using this test you don't need to start data
probe standalone in a previous step.
+ <b>NOTE:</b> when using this test you don't need to start data
probe standalone.
</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.
+ Start this Runtime Configuration and you should be getting
standard log in the output console.
</p>
</section>
<section>
<h2 class="section-title">Done! 👌</h2>
<p>
You've created NLI-power light switch data model, deployed it into
the data probe, started the
- REST server and tested this model using JUnit 5 and the built-in
test framework.
+ REST server and tested this model using the built-in test
framework.
</p>
</section>
</div>
