support generic types to avoid typecasting what Decision.get() returns.

Author: panhongx

improveai/src/main/java/ai/improve/Decision.java

@@ -6,12 +6,12 @@
 import ai.improve.log.IMPLog;
 import ai.improve.util.ModelUtils;
 
-public class Decision {
+public class Decision<T> {
     public static final String Tag = "Decision";
 
     private DecisionModel model;
 
-    protected List<?> variants;
+    protected List<T> variants;
 
     protected Map<String, Object> givens;
 
@@ -25,7 +25,7 @@ public class Decision {
      * */
     protected int tracked;
 
-    protected Object best;
+    protected T best;
 
     // The message_id of the tracked decision
     protected String id;
@@ -39,7 +39,7 @@ protected Decision(DecisionModel model) {
      * @return Returns the chosen variant memoized.
      * @throws IllegalStateException Thrown if called before chooseFrom()
      */
-    public Object peek() {
+    public T peek() {
         return best;
     }
 
@@ -49,7 +49,7 @@ public Object peek() {
      * might return null.
      * @throws IllegalStateException Thrown if variants is null or empty.
      * */
-    public synchronized Object get() {
+    public synchronized T get() {
         if(tracked == 0) {
             DecisionTracker tracker = model.getTracker();
             if (tracker != null) {

improveai/src/main/java/ai/improve/DecisionContext.java

@@ -22,7 +22,7 @@ public DecisionContext(DecisionModel decisionModel, Map givens) {
     /**
      * @see ai.improve.DecisionModel#chooseFrom(List)
      */
-    public Decision chooseFrom(List variants) {
+    public <T> Decision<T> chooseFrom(List<T> variants) {
         if(variants == null || variants.size() <= 0) {
             throw new IllegalArgumentException("variants to choose from can't be null or empty");
         }
@@ -43,7 +43,7 @@ public Decision chooseFrom(List variants) {
     /**
      * @see ai.improve.DecisionModel#chooseFrom(List, List)
      */
-    public Decision chooseFrom(List variants, List scores) {
+    public <T> Decision<T> chooseFrom(List<T> variants, List<Double> scores) {
         if(variants == null || scores == null || variants.size() <= 0) {
             throw new IllegalArgumentException("variants and scores can't be null or empty");
         }
@@ -67,7 +67,7 @@ public Decision chooseFrom(List variants, List scores) {
     /**
      * @see ai.improve.DecisionModel#chooseFrom(List)
      */
-    public Decision chooseFirst(List variants) {
+    public <T> Decision<T> chooseFirst(List<T> variants) {
         if(variants == null || variants.size() <= 0) {
             throw new IllegalArgumentException("variants can't be null or empty");
         }
@@ -98,7 +98,7 @@ public Object first(Object... variants) {
     /**
      * @see ai.improve.DecisionModel#chooseRandom(List)
      */
-    public Decision chooseRandom(List variants) {
+    public <T> Decision<T> chooseRandom(List<T> variants) {
         if(variants == null || variants.size() <= 0) {
             throw new IllegalArgumentException("variants can't be null or empty");
         }

improveai/src/main/java/ai/improve/DecisionModel.java

@@ -278,7 +278,7 @@ protected FeatureEncoder getFeatureEncoder() {
      *                booleans.
      * @return an IMPDecision object.
      * */
-    public <T> Decision chooseFrom(List<T> variants) {
+    public <T> Decision<T> chooseFrom(List<T> variants) {
         return given(null).chooseFrom(variants);
     }
 
@@ -291,7 +291,7 @@ public <T> Decision chooseFrom(List<T> variants) {
      * @throws IllegalArgumentException Thrown if variants or scores is null or empty; Thrown if
      * variants.size() != scores.size().
      */
-    public Decision chooseFrom(List variants, List scores) {
+    public <T> Decision<T> chooseFrom(List<T> variants, List<Double> scores) {
         return given(null).chooseFrom(variants, scores);
     }
 
@@ -338,7 +338,7 @@ public Object which(Object... variants) {
      * @param variants See chooseFrom()
      * @return A Decision object which has the first variant as the best.
      */
-    public Decision chooseFirst(List variants) {
+    public <T> Decision<T> chooseFirst(List<T> variants) {
         if(variants == null || variants.size() <= 0) {
             throw new IllegalArgumentException("variants can't be null or empty");
         }
@@ -362,7 +362,7 @@ public Object first(Object... variants) {
      * @return A Decision object containing a random variant as the decision.
      * @throws IllegalArgumentException Thrown if variants is null or empty.
      */
-    public Decision chooseRandom(List variants) {
+    public <T> Decision<T> chooseRandom(List<T> variants) {
         return given(null).chooseRandom(variants);
     }
 
@@ -399,7 +399,7 @@ protected Map<String, Object> combinedGivens(Map<String, Object> givens) {
      * @throws IllegalArgumentException Thrown if variants is null or empty.
      * @return scores of the variants
      */
-    public <T> List<Double> score(List<T> variants) {
+    public List<Double> score(List variants) {
         return scoreInternal(variants, combinedGivens(null));
     }
 
@@ -416,12 +416,12 @@ public <T> List<Double> score(List<T> variants) {
      * @throws IllegalArgumentException Thrown if variants is null or empty
      * @return scores of the variants
      */
-    protected  <T> List<Double> scoreInternal(List<T> variants, Map<String, ?> givens) {
+    protected List<Double> scoreInternal(List variants, Map<String, ?> givens) {
         if(variants == null || variants.size() <= 0) {
             throw new IllegalArgumentException("variants can't be null or empty");
         }
 
-        IMPLog.d(Tag, "givens: " + givens);
+//        IMPLog.d(Tag, "givens: " + givens);
 
         if(predictor == null) {
             // When tracking a decision like this:
@@ -516,7 +516,7 @@ public int compare(Integer obj1, Integer obj2) {
             }
         });
 
-        List<T> result = new ArrayList<T>(variants.size());
+        List<T> result = new ArrayList<>(variants.size());
         for(int i = 0; i < indices.length; ++i) {
             result.add(variants.get(indices[i]));
         }

improveai/src/test/java/ai/improve/DecisionContextTest.java

@@ -27,10 +27,14 @@ public static void setUp() {
         DecisionModel.setDefaultTrackURL(Track_URL);
     }
 
-    private List variants() {
+    private List<String> variants() {
         return Arrays.asList("Hello", "Hi", "Hey");
     }
 
+    private List<Double> scores() {
+        return Arrays.asList(0.1, 0.2, 0.3);
+    }
+
     private Map givens() {
         return Map.of("lang", "en");
     }
@@ -43,6 +47,13 @@ public void testChooseFrom() {
         assertNotNull(decision);
     }
 
+    @Test
+    public void testChooseFrom_generic() {
+        DecisionModel decisionModel = new DecisionModel("greetings");
+        String greeting = decisionModel.given(null).chooseFrom(variants()).get();
+        IMPLog.d(Tag, "greeting is " + greeting);
+    }
+
     @Test
     public void testChooseFrom_null_variants() {
         DecisionModel decisionModel = new DecisionModel("greetings");
@@ -81,6 +92,13 @@ public void testChooseFromVaiantsAndScores() {
         assertEquals("en", decision.givens.get("lang"));
     }
 
+    @Test
+    public void testChooseFromVaiantsAndScores_generic() {
+        DecisionModel decisionModel = new DecisionModel("greetings");
+        String greeting = decisionModel.given(null).chooseFrom(variants(), scores()).get();
+        IMPLog.d(Tag, "greeting is " + greeting);
+    }
+
     @Test
     public void testChooseFromVaiantsAndScores_null_variants() {
         Map givens = Map.of("lang", "en");
@@ -130,10 +148,18 @@ public void testChooseFirst() {
         List variants = Arrays.asList("hi", "hello", "hey");
         DecisionModel decisionModel = new DecisionModel("greetings");
         Decision decision = decisionModel.given(givens).chooseFirst(variants);
-        assertEquals(givens, decision.givens);
+        assertEquals(1, decision.givens.size());
+        assertEquals("en", decision.givens.get("lang"));
         assertEquals("hi", decision.get());
     }
 
+    @Test
+    public void testChooseFirst_generic() {
+        DecisionModel decisionModel = new DecisionModel("greetings");
+        String greeting = decisionModel.given(null).chooseFirst(variants()).get();
+        IMPLog.d(Tag, "greeting is " + greeting);
+    }
+
     @Test
     public void testChooseFirst_null_variants() {
         Map givens = Map.of("lang", "en");
@@ -224,6 +250,15 @@ public void testChooseRandom() {
         assertEquals(loop/3, countMap.get("hey"), 100);
     }
 
+    @Test
+    public void testChooseRandom_generic() {
+        Map givens = Map.of("lang", "en");
+        List<String> variants = Arrays.asList("hi", "hello", "hey");
+        DecisionModel decisionModel = new DecisionModel("greetings");
+        String greeting = decisionModel.given(givens).chooseRandom(variants).get();
+        IMPLog.d(Tag, "greeting is " + greeting);
+    }
+
     @Test
     public void testChooseRandom_null_variants() {
         DecisionModel decisionModel = new DecisionModel("greetings");

improveai/src/test/java/ai/improve/DecisionModelTest.java

@@ -43,6 +43,14 @@ public class DecisionModelTest {
         DecisionModel.setDefaultTrackApiKey(Track_Api_Key);
     }
 
+    private List<String> variants() {
+        return Arrays.asList("Hello", "Hi", "Hey");
+    }
+
+    private List<Double> scores() {
+        return Arrays.asList(0.1, 0.2, 0.3);
+    }
+
     @BeforeEach
     public void setUp() throws Exception {
         IMPLog.d(Tag, "setUp");
@@ -319,6 +327,16 @@ public void testRankInvalid_largerScores() {
         fail("An IndexOutOfBoundException should have been thrown, we should never reach here");
     }
 
+    @Test
+    public void testRank_generic() {
+        List<String> variants = Arrays.asList("hi", "hello", "hey");
+        List<Double> scores = Arrays.asList(0.1, 0.2, 0.3);
+        // test that we don't have to do type cast here like:
+        // String greeting = (String) DecisionModel.rank(variants, scores).get(0);
+        String greeting = DecisionModel.rank(variants, scores).get(0);
+        assertEquals("hey", greeting);
+    }
+
     @Test
     public void testTopScoringVariant() {
         int count = 100;
@@ -469,6 +487,13 @@ public void testChooseFrom() {
 //        product = IMPDecisionModel.lo(modelUrl).chooseFrom(["clutch", "dress", "jacket"]).get()
     }
 
+    @Test
+    public void testChooseFrom_generic() {
+        DecisionModel decisionModel = new DecisionModel("greetings");
+        String greeting = decisionModel.chooseFrom(variants()).get();
+        IMPLog.d(Tag, "greetings is " + greeting);
+    }
+
     @Test
     public void testChooseFromVariantsAndScores() {
         List variants = Arrays.asList("hi", "hello", "Hey");
@@ -481,6 +506,13 @@ public void testChooseFromVariantsAndScores() {
         assertEquals(variants, decision.variants);
     }
 
+    @Test
+    public void testChooseFromVariantsAndScores_generic() {
+        DecisionModel decisionModel = new DecisionModel("greetings");
+        String greeting = decisionModel.chooseFrom(variants(), scores()).get();
+        IMPLog.d(Tag, "greetings is " + greeting);
+    }
+
     @Test
     public void testChooseFromVariantsAndScores_empty_variants() {
         List variants = new ArrayList();
@@ -720,6 +752,13 @@ public void testChooseFirst() {
         assertEquals(variants.size(), decision.scores.size());
     }
 
+    @Test
+    public void testChooseFirst_generic() {
+        DecisionModel decisionModel = new DecisionModel("greetings");
+        String greeting = decisionModel.chooseFirst(variants()).get();
+        IMPLog.d(Tag, "greetings is " + greeting);
+    }
+
     @Test
     public void testChooseFirst_null_variants() {
         List variants = null;
@@ -831,6 +870,13 @@ public void testChooseRandom() {
         assertEquals(loop/3, countMap.get("hey"), 100);
     }
 
+    @Test
+    public void testChooseRandom_generic() {
+        DecisionModel decisionModel = new DecisionModel("greetings");
+        String greeting = decisionModel.chooseRandom(variants()).get();
+        IMPLog.d(Tag, "greetings is " + greeting);
+    }
+
     @Test
     public void testChooseRandom_empty_variants() {
         List variants = new ArrayList();

improveai/src/test/java/ai/improve/DecisionTest.java

@@ -162,4 +162,22 @@ public void testAddReward_negative_infinity() {
         }
         fail(DefaultFailMessage);
     }
+
+    @Test
+    public void testGet_generic() {
+        List<String> variants = Arrays.asList("hi", "hello", "Hey");
+        DecisionModel decisionModel = new DecisionModel("greetings");
+        // Unit test that no type cast needed here
+        String greeting = decisionModel.chooseFrom(variants).get();
+        assertEquals("hi", greeting);
+    }
+
+    @Test
+    public void testPeek_generic() {
+        List<String> variants = Arrays.asList("hi", "hello", "Hey");
+        DecisionModel decisionModel = new DecisionModel("greetings");
+        // Unit test that no type cast needed here
+        String greeting = decisionModel.chooseFrom(variants).peek();
+        assertEquals("hi", greeting);
+    }
 }