Merge branch 'master' into combined-entity-intent-model

CHANGELOG.rst

@@ -7,6 +7,7 @@ Rasa Change Log
 All notable changes to this project will be documented in this file.
 This project adheres to `Semantic Versioning`_ starting with version 1.0.
 
+
 [Unreleased 1.5.0a1] - `master`_
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
 
@@ -29,6 +30,24 @@ Fixed
 -----
 - ``MultiProjectImporter`` now imports files in the order of the import statements
 
+[Unreleased 1.4.2]
+~~~~~~~~~~~~~~~~~~
+
+Added
+-----
+
+Changed
+-------
+
+Removed
+-------
+- TensorFlow deprecation warnings are no longer shown when running ``rasa x``
+
+Fixed
+-----
+- Fixed ``'Namespace' object has no attribute 'persist_nlu_data'`` error during
+  interactive learning
+
 [1.4.1] - 2019-10-22
 ^^^^^^^^^^^^^^^^^^^^
 Regression: changes from ``1.2.12`` were missing from ``1.4.0``, readded them

data/test_config/keyword_classifier_config.yml

@@ -0,0 +1,2 @@
+pipeline:
+  - name: "KeywordIntentClassifier"

docs/nlu/components.rst

@@ -272,23 +272,8 @@ CountVectorsFeaturizer
 Intent Classifiers
 ------------------
 
-KeywordIntentClassifier
-~~~~~~~~~~~~~~~~~~~~~~~
 
-:Short: Simple keyword matching intent classifier. Not intended to be used.
-:Outputs: ``intent``
-:Requires: nothing
-:Output-Example:
-
-    .. code-block:: json
-
-        {
-            "intent": {"name": "greet", "confidence": 0.98343}
-        }
 
-:Description:
-    This classifier is mostly used as a placeholder. It is able to recognize `hello` and
-    `goodbye` intents by searching for these keywords in the passed messages.
 
 MitieIntentClassifier
 ~~~~~~~~~~~~~~~~~~~~~
@@ -482,6 +467,41 @@ EmbeddingIntentClassifier
               See `starspace paper <https://arxiv.org/abs/1709.03856>`_ for details.
 
 
+.. _keyword_intent_classifier:
+
+KeywordIntentClassifier
+~~~~~~~~~~~~~~~~~~~~~~~
+
+:Short: Simple keyword matching intent classifier, intended for small, short-term projects.
+:Outputs: ``intent``
+:Requires: nothing
+
+:Output-Example:
+
+    .. code-block:: json
+
+        {
+            "intent": {"name": "greet", "confidence": 1.0}
+        }
+
+:Description:
+    This classifier works by searching a message for keywords.
+    The matching is case sensitive by default and searches only for exact matches of the keyword-string in the user message.
+    The keywords for an intent are the examples of that intent in the NLU training data.
+    This means the entire example is the keyword, not the individual words in the example.
+
+    .. note:: This classifier is intended only for small projects or to get started. If
+              you have few NLU training data you can use one of our pipelines
+              :ref:`choosing-a-pipeline`.
+
+:Configuration:
+
+    .. code-block:: yaml
+
+        pipeline:
+        - name: "KeywordIntentClassifier"
+          case_sensitive: True
+
 Selectors
 ----------
 
@@ -493,6 +513,7 @@ Response Selector
 :Short: Response Selector
 :Outputs: A dictionary with key as ``direct_response_intent`` and value containing ``response`` and ``ranking``
 :Requires: A featurizer
+
 :Output-Example:
 
     .. code-block:: json

examples/moodbot/data/nlu.md

@@ -14,11 +14,11 @@
 - good afternoon
 
 ## intent:goodbye
+- good afternoon
 - cu
 - good by
 - cee you later
 - good night
-- good afternoon
 - bye
 - goodbye
 - have a nice day
@@ -42,7 +42,6 @@
 
 ## intent:mood_great
 - perfect
-- very good
 - great
 - amazing
 - feeling like a king
@@ -51,7 +50,7 @@
 - I am great
 - I am amazing
 - I am going to save the world
-- super
+- super stoked
 - extremely good
 - so so perfect
 - so good
@@ -67,7 +66,7 @@
 - sad
 - very sad
 - unhappy
-- not so good
+- not good
 - not very good
 - extremly sad
 - so saad

rasa/cli/arguments/interactive.py

@@ -14,6 +14,7 @@
     add_debug_plots_param,
     add_dump_stories_param,
     add_augmentation_param,
+    add_persist_nlu_data_param,
 )
 
 
@@ -38,6 +39,7 @@ def set_interactive_arguments(parser: argparse.ArgumentParser):
     add_debug_plots_param(train_arguments)
     add_dump_stories_param(train_arguments)
     add_force_param(train_arguments)
+    add_persist_nlu_data_param(train_arguments)
 
 
 def set_interactive_core_arguments(parser: argparse.ArgumentParser):

rasa/cli/interactive.py

@@ -52,8 +52,7 @@ def add_subparser(
 
 
 def interactive(args: argparse.Namespace):
-    args.fixed_model_name = None
-    args.store_uncompressed = False
+    _set_not_required_args(args)
 
     if args.model is None:
         check_training_data(args)
@@ -64,10 +63,14 @@ def interactive(args: argparse.Namespace):
     perform_interactive_learning(args, zipped_model)
 
 
-def interactive_core(args: argparse.Namespace):
+def _set_not_required_args(args: argparse.Namespace) -> None:
     args.fixed_model_name = None
     args.store_uncompressed = False
 
+
+def interactive_core(args: argparse.Namespace):
+    _set_not_required_args(args)
+
     if args.model is None:
         zipped_model = train.train_core(args)
     else:

rasa/cli/x.py

@@ -59,11 +59,11 @@ def _rasa_service(
 ):
     """Starts the Rasa application."""
     from rasa.core.run import serve_application
+    import rasa.utils.common
 
     # needs separate logging configuration as it is started in its own process
-    logging.basicConfig(level=args.loglevel)
+    rasa.utils.common.set_log_level(args.loglevel)
     io_utils.configure_colored_logging(args.loglevel)
-    logging.getLogger("apscheduler").setLevel(logging.WARNING)
 
     if not credentials_path:
         credentials_path = _prepare_credentials_for_rasa_x(

rasa/core/lock_store.py

@@ -2,7 +2,7 @@
 import json
 import logging
 import os
-from typing import Text, Optional, Union, AsyncGenerator, Coroutine
+from typing import Text, Optional, Union, AsyncGenerator
 
 from async_generator import asynccontextmanager
 

rasa/core/policies/embedding_policy.py

@@ -1,4 +1,3 @@
-from collections import namedtuple
 import copy
 import json
 import logging
@@ -10,7 +9,6 @@
 from typing import Any, List, Optional, Text, Dict, Tuple
 
 import rasa.utils.io
-from rasa.core import utils
 from rasa.core.domain import Domain
 from rasa.core.featurizers import (
     TrackerFeaturizer,

rasa/core/policies/form_policy.py

@@ -1,6 +1,6 @@
 import logging
 import typing
-from typing import List, Optional, Dict, Text, Optional
+from typing import List, Dict, Text, Optional
 
 from rasa.core.actions.action import ACTION_LISTEN_NAME
 from rasa.core.domain import PREV_PREFIX, ACTIVE_FORM_PREFIX, Domain, InvalidDomain

rasa/core/policies/keras_policy.py

@@ -9,7 +9,6 @@
 
 import rasa.utils.io
 
-from rasa.core import utils
 from rasa.core.domain import Domain
 from rasa.core.featurizers import (
     MaxHistoryTrackerFeaturizer,

rasa/core/policies/mapping_policy.py

@@ -6,7 +6,6 @@
 
 import rasa.utils.io
 
-from rasa.core import utils
 from rasa.core.actions.action import (
     ACTION_BACK_NAME,
     ACTION_LISTEN_NAME,

rasa/core/policies/memoization.py

@@ -9,7 +9,6 @@
 
 import rasa.utils.io
 
-from rasa.core import utils
 from rasa.core.domain import Domain
 from rasa.core.events import ActionExecuted
 from rasa.core.featurizers import TrackerFeaturizer, MaxHistoryTrackerFeaturizer

rasa/core/policies/sklearn_policy.py

@@ -15,7 +15,6 @@
 from typing import Optional, Any, List, Text, Dict, Callable
 
 import rasa.utils.io
-from rasa.core import utils
 from rasa.core.domain import Domain
 from rasa.core.featurizers import TrackerFeaturizer, MaxHistoryTrackerFeaturizer
 from rasa.core.policies.policy import Policy

rasa/core/policies/two_stage_fallback.py

@@ -5,7 +5,6 @@
 from typing import List, Text, Optional
 
 import rasa.utils.io
-from rasa.core import utils
 from rasa.core.actions.action import (
     ACTION_REVERT_FALLBACK_EVENTS_NAME,
     ACTION_DEFAULT_FALLBACK_NAME,

rasa/core/training/visualization.py

@@ -1,7 +1,6 @@
 from collections import defaultdict, deque
 
 import random
-import re
 from typing import Any, Text, List, Dict, Optional, TYPE_CHECKING
 
 from rasa.core.actions.action import ACTION_LISTEN_NAME

rasa/core/validator.py

@@ -1,5 +1,4 @@
 import logging
-import asyncio
 from collections import defaultdict
 from typing import List, Set, Text
 from rasa.core.domain import Domain
@@ -13,7 +12,7 @@
 logger = logging.getLogger(__name__)
 
 
-class Validator(object):
+class Validator:
     """A class used to verify usage of intents and utterances."""
 
     def __init__(self, domain: Domain, intents: TrainingData, stories: List[StoryStep]):

rasa/jupyter.py

@@ -4,7 +4,6 @@
 from typing import Any, Dict, Text, Optional
 from rasa.cli.utils import print_success, print_error
 from rasa.core.interpreter import NaturalLanguageInterpreter, RasaNLUInterpreter
-import rasa.model as model
 
 if typing.TYPE_CHECKING:
     from rasa.core.agent import Agent

rasa/nlu/classifiers/embedding_intent_classifier.py

@@ -724,8 +724,8 @@ def load(
 
             graph = tf.Graph()
             with graph.as_default():
-                session = tf.Session(config=_tf_config)
-                saver = tf.train.import_meta_graph(checkpoint + ".meta")
+                session = tf.compat.v1.Session(config=_tf_config)
+                saver = tf.compat.v1.train.import_meta_graph(checkpoint + ".meta")
 
                 saver.restore(session, checkpoint)