Adding option input for the Bot Engine.

examples/fake_bot.py

@@ -1,4 +1,5 @@
 from kadot.bot_engine import Agent
+from kadot.classifiers import FuzzyClassifier
 from kadot.models import CRFExtractor
 import random
 
@@ -15,6 +16,21 @@
     crf_filename='.crf_city_extractor_city'
 )
 
+yes_no = FuzzyClassifier({
+    "yes": 'y',
+    "yep": 'y',
+    "of course": 'y',
+    "affirmative": 'y',
+    "ok": 'y',
+    "continue": 'y',
+    "nope": 'n',
+    "no": 'n',
+    "nay": 'n',
+    "negative": 'n',
+    "end": 'n',
+    }
+)
+
 bot = Agent()
 bot.add_entity('place', places_extractor)
 
@@ -53,17 +69,25 @@ def weather(raw, context):
         context.event_flag = 'should_continue'
         return answer, context
     else:
-        return bot.prompt("In which city ?", key='place', callback=weather, context=context)
+        return bot.prompt("In which city ?", key='place',
+                          callback=weather, context=context)
 
 
 @bot.hidden_intent()
 def should_continue(raw, context):
     if context['continue']:
-        answer = "For now, I can't understand if you want to continue or not..."
+        if context['continue'] == 'y':
+            answer = "Ok, fine."
+        else:  # context['continue'] == 'n'
+            answer = "Ok bye bye"
+
         del context['continue']
         return answer, context
+
     else:
-        return bot.prompt("Do you want to continue ?", key='continue', callback=should_continue, context=context)
+        return bot.option("Do you want to continue ?", key='continue',
+                          classifier=yes_no, callback=should_continue,
+                          context=context)
 
 
 bot.train()

kadot/bot_engine.py

@@ -125,6 +125,34 @@ def _prompt(raw, ctx):
 
         return message, context
 
+    def option(self,
+                 message: Any,
+                 key: str,
+                 classifier,
+                 callback: Callable[[str, Context], Any],
+                 context: Context):
+
+        def _option(raw, ctx):
+            """
+            An intent to retrieve the user's input and put it's
+            classification in the context.
+            """
+
+            best_class, best_proba = '', 0
+
+            for e_class, e_proba in classifier.predict(raw).items():
+                if e_proba >= best_proba:
+                    best_class, best_proba = e_class, e_proba
+
+            ctx[key] = best_class
+
+            return callback(raw, ctx)
+
+        self.intents['_option'] = Intent(name='_option', func=_option)
+        context.intent_flag = '_option'
+
+        return message, context
+
     def _get_training_dataset(self):
         training_dataset = {}
 
@@ -172,6 +200,8 @@ def predict(self, text: str, conversation: Optional[Any] = None):
         while context.event_flag:
             intent = context.event_flag
             context.event_flag = None
+
+            logger.info("Event flag for {}.".format(intent))
             event_output, context = self.intents[intent].run(text, context)
             context.step()