rasa train nlu accepts domain

data/test_config/config_defaults.yml

@@ -1,4 +1,23 @@
 language: en
 pipeline: []
+# # No configuration for the NLU pipeline was provided. The following default pipeline was used to train your model.
+# # If you'd like to customize it, uncomment and adjust the pipeline.
+# # See https://rasa.com/docs/rasa/tuning-your-model for more information.
+#   - name: WhitespaceTokenizer
+#   - name: RegexFeaturizer
+#   - name: LexicalSyntacticFeaturizer
+#   - name: CountVectorsFeaturizer
+#   - name: CountVectorsFeaturizer
+#     analyzer: char_wb
+#     min_ngram: 1
+#     max_ngram: 4
+#   - name: DIETClassifier
+#     epochs: 100
+#   - name: EntitySynonymMapper
+#   - name: ResponseSelector
+#     epochs: 100
+#   - name: FallbackClassifier
+#     threshold: 0.3
+#     ambiguity_threshold: 0.1
 
 data:

data/test_config/config_response_selector_minimal.yml

@@ -0,0 +1,6 @@
+language: en
+pipeline:
+   - name: WhitespaceTokenizer
+   - name: CountVectorsFeaturizer
+   - name: ResponseSelector
+     epochs: 1

data/test_nlu_no_responses/domain_with_only_responses.yml

@@ -0,0 +1,10 @@
+responses:
+  utter_chitchat/ask_name:
+    - image: "https://i.imgur.com/zTvA58i.jpeg"
+      text: hello, my name is retrieval bot.
+    - text: Oh yeah, I am called the retrieval bot.
+
+  utter_chitchat/ask_weather:
+    - text: Oh, it does look sunny right now in Berlin.
+      image: "https://i.imgur.com/vwv7aHN.png"
+    - text: I am not sure of the whole week but I can see the sun is out today.

data/test_nlu_no_responses/nlu_no_responses.yml

@@ -0,0 +1,16 @@
+version: "2.0"
+
+nlu:
+- intent: chitchat/ask_name
+  examples: |
+    - What is your name?
+    - May I know your name?
+    - What do people call you?
+    - Do you have a name for yourself?
+
+- intent: chitchat/ask_weather
+  examples: |
+    - What's the weather like today?
+    - Does it look sunny outside today?
+    - Oh, do you mind checking the weather for me please?
+    - I like sunny days in Berlin.

rasa/cli/arguments/default_arguments.py

@@ -49,13 +49,14 @@ def add_nlu_data_param(
 
 
 def add_domain_param(
-    parser: Union[argparse.ArgumentParser, argparse._ActionsContainer]
+    parser: Union[argparse.ArgumentParser, argparse._ActionsContainer],
+    default: Optional[Text] = DEFAULT_DOMAIN_PATH,
 ) -> None:
     parser.add_argument(
         "-d",
         "--domain",
         type=str,
-        default=DEFAULT_DOMAIN_PATH,
+        default=default,
         help="Domain specification. This can be a single YAML file, or a directory "
         "that contains several files with domain specifications in it. The content "
         "of these files will be read and merged together.",

rasa/cli/arguments/train.py

@@ -46,6 +46,7 @@ def set_train_core_arguments(parser: argparse.ArgumentParser):
 
 def set_train_nlu_arguments(parser: argparse.ArgumentParser):
     add_config_param(parser)
+    add_domain_param(parser, default=None)
     add_out_param(parser, help_text="Directory where your models should be stored.")
 
     add_nlu_data_param(parser, help_text="File or folder containing your NLU data.")

rasa/cli/train.py

@@ -143,6 +143,11 @@ def train_nlu(
         args.nlu, "nlu", DEFAULT_DATA_PATH, none_is_valid=True
     )
 
+    if args.domain:
+        args.domain = rasa.cli.utils.get_validated_path(
+            args.domain, "domain", DEFAULT_DOMAIN_PATH, none_is_valid=True
+        )
+
     return train_nlu(
         config=config,
         nlu_data=nlu_data,
@@ -151,6 +156,7 @@ def train_nlu(
         fixed_model_name=args.fixed_model_name,
         persist_nlu_training_data=args.persist_nlu_data,
         additional_arguments=extract_nlu_additional_arguments(args),
+        domain=args.domain,
     )
 
 

rasa/train.py

@@ -434,6 +434,7 @@ def train_nlu(
     fixed_model_name: Optional[Text] = None,
     persist_nlu_training_data: bool = False,
     additional_arguments: Optional[Dict] = None,
+    domain: Optional[Union[Domain, Text]] = None,
 ) -> Optional[Text]:
     """Trains an NLU model.
 
@@ -448,6 +449,7 @@ def train_nlu(
                                    with the model.
         additional_arguments: Additional training parameters which will be passed to
                               the `train` method of each component.
+        domain: Path to the optional domain file/Domain object.
 
 
     Returns:
@@ -465,6 +467,7 @@ def train_nlu(
             fixed_model_name,
             persist_nlu_training_data,
             additional_arguments,
+            domain=domain,
         )
     )
 
@@ -477,6 +480,7 @@ async def _train_nlu_async(
     fixed_model_name: Optional[Text] = None,
     persist_nlu_training_data: bool = False,
     additional_arguments: Optional[Dict] = None,
+    domain: Optional[Union[Domain, Text]] = None,
 ):
     if not nlu_data:
         print_error(
@@ -487,7 +491,7 @@ async def _train_nlu_async(
 
     # training NLU only hence the training files still have to be selected
     file_importer = TrainingDataImporter.load_nlu_importer_from_config(
-        config, training_data_paths=[nlu_data]
+        config, domain, training_data_paths=[nlu_data]
     )
 
     training_data = await file_importer.get_nlu_data()

tests/test_train.py

@@ -14,6 +14,8 @@
 import rasa.core
 import rasa.shared.importers.autoconfig as autoconfig
 from rasa.core.interpreter import RasaNLUInterpreter
+from rasa.shared.core.domain import Domain
+from rasa.shared.importers.importer import TrainingDataImporter
 
 from rasa.train import train_core, train_nlu, train
 from tests.conftest import DEFAULT_CONFIG_PATH, DEFAULT_NLU_DATA
@@ -164,6 +166,52 @@ def test_train_nlu_wrong_format_error_message(
     assert "Please verify the data format" in captured.out
 
 
+def test_train_nlu_with_responses_no_domain_warns(
+    tmp_path: Path, monkeypatch: MonkeyPatch,
+):
+    (tmp_path / "training").mkdir()
+    (tmp_path / "models").mkdir()
+
+    data_path = "data/test_nlu_no_responses/nlu_no_responses.yml"
+
+    with pytest.warns(UserWarning) as records:
+        train_nlu(
+            "data/test_config/config_response_selector_minimal.yml",
+            data_path,
+            output=str(tmp_path / "models"),
+        )
+
+    assert any(
+        "You either need to add a response phrase or correct the intent"
+        in record.message.args[0]
+        for record in records
+    )
+
+
+def test_train_nlu_with_responses_and_domain_no_warns(
+    tmp_path: Path, monkeypatch: MonkeyPatch,
+):
+    (tmp_path / "training").mkdir()
+    (tmp_path / "models").mkdir()
+
+    data_path = "data/test_nlu_no_responses/nlu_no_responses.yml"
+    domain_path = "data/test_nlu_no_responses/domain_with_only_responses.yml"
+
+    with pytest.warns(None) as records:
+        train_nlu(
+            "data/test_config/config_response_selector_minimal.yml",
+            data_path,
+            output=str(tmp_path / "models"),
+            domain=domain_path,
+        )
+
+    assert not any(
+        "You either need to add a response phrase or correct the intent"
+        in record.message.args[0]
+        for record in records
+    )
+
+
 def test_train_nlu_no_nlu_file_error_message(
     capsys: CaptureFixture,
     tmp_path: Text,