Merge pull request #4627 from ronancummins/add_persist_flag_cli

Add flag to CLI to persist NLU data #4599

CHANGELOG.rst

@@ -12,6 +12,7 @@ This project adheres to `Semantic Versioning`_ starting with version 1.0.
 
 Added
 -----
+- add flag to CLI to persist NLU training data if needed
 - log a warning if the ``Interpreter`` picks up an intent or an entity that does not
   exist in the domain file.
 - added ``DynamoTrackerStore`` to support persistence of agents running on AWS
@@ -20,7 +21,7 @@ Added
 - `CRFEntityExtractor` updated to accept arbitrary token-level features like word
   vectors (issues/4214)
 - `SpacyFeaturizer` updated to add `ner_features` for `CRFEntityExtractor`
-- Sanitizing incoming messages from slack to remove slack formatting like <mailto:xyz@rasa.com|xyz@rasa.com> 
+- Sanitizing incoming messages from slack to remove slack formatting like <mailto:xyz@rasa.com|xyz@rasa.com>
   or <http://url.com|url.com> and substitute it with original content
 - Added the ability to configure the number of Sanic worker processes in the HTTP
   server (``rasa.server``) and input channel server

rasa/cli/arguments/train.py

@@ -22,6 +22,7 @@ def set_train_arguments(parser: argparse.ArgumentParser):
     add_dump_stories_param(parser)
 
     add_model_name_param(parser)
+    add_persist_nlu_data_param(parser)
     add_force_param(parser)
 
 
@@ -50,6 +51,7 @@ def set_train_nlu_arguments(parser: argparse.ArgumentParser):
     add_nlu_data_param(parser, help_text="File or folder containing your NLU data.")
 
     add_model_name_param(parser)
+    add_persist_nlu_data_param(parser)
 
 
 def add_force_param(parser: Union[argparse.ArgumentParser, argparse._ActionsContainer]):
@@ -138,3 +140,13 @@ def add_model_name_param(parser: argparse.ArgumentParser):
         help="If set, the name of the model file/directory will be set to the given "
         "name.",
     )
+
+
+def add_persist_nlu_data_param(
+    parser: Union[argparse.ArgumentParser, argparse._ActionsContainer]
+):
+    parser.add_argument(
+        "--persist-nlu-data",
+        action="store_true",
+        help="Persist the nlu training data in the saved model.",
+    )

rasa/cli/train.py

@@ -72,6 +72,7 @@ def train(args: argparse.Namespace) -> Optional[Text]:
         output=args.out,
         force_training=args.force,
         fixed_model_name=args.fixed_model_name,
+        persist_nlu_training_data=args.persist_nlu_data,
         kwargs=extract_additional_arguments(args),
     )
 
@@ -134,6 +135,7 @@ def train_nlu(
         output=output,
         train_path=train_path,
         fixed_model_name=args.fixed_model_name,
+        persist_nlu_training_data=args.persist_nlu_data,
     )
 
 

rasa/train.py

@@ -26,6 +26,7 @@ def train(
     output: Text = DEFAULT_MODELS_PATH,
     force_training: bool = False,
     fixed_model_name: Optional[Text] = None,
+    persist_nlu_training_data: bool = False,
     kwargs: Optional[Dict] = None,
     loop: Optional[asyncio.AbstractEventLoop] = None,
 ) -> Optional[Text]:
@@ -40,6 +41,7 @@ def train(
             output_path=output,
             force_training=force_training,
             fixed_model_name=fixed_model_name,
+            persist_nlu_training_data=persist_nlu_training_data,
             kwargs=kwargs,
         )
     )
@@ -124,6 +126,8 @@ async def _train_async_internal(
         train_path: Directory in which to train the model.
         output_path: Output path.
         force_training: If `True` retrain model even if data has not changed.
+        persist_nlu_training_data: `True` if the NLU training data should be persisted
+                                   with the model.
         fixed_model_name: Name of model to be stored.
         kwargs: Additional training parameters.
 
@@ -363,6 +367,7 @@ def train_nlu(
     output: Text,
     train_path: Optional[Text] = None,
     fixed_model_name: Optional[Text] = None,
+    persist_nlu_training_data: bool = False,
 ) -> Optional[Text]:
     """Trains an NLU model.
 
@@ -373,7 +378,9 @@ def train_nlu(
         train_path: If `None` the model will be trained in a temporary
             directory, otherwise in the provided directory.
         fixed_model_name: Name of the model to be stored.
-        uncompress: If `True` the model will not be compressed.
+        persist_nlu_training_data: `True` if the NLU training data should be persisted
+                                   with the model.
+
 
     Returns:
         If `train_path` is given it returns the path to the model archive,
@@ -383,7 +390,14 @@ def train_nlu(
 
     loop = asyncio.get_event_loop()
     return loop.run_until_complete(
-        _train_nlu_async(config, nlu_data, output, train_path, fixed_model_name)
+        _train_nlu_async(
+            config,
+            nlu_data,
+            output,
+            train_path,
+            fixed_model_name,
+            persist_nlu_training_data,
+        )
     )
 
 

tests/cli/test_rasa_train.py

@@ -5,7 +5,8 @@
 import pytest
 
 from rasa import model
-
+from rasa.nlu.model import Metadata
+from rasa.nlu.training_data import training_data
 from rasa.cli.train import _get_valid_config
 from rasa.constants import (
     CONFIG_MANDATORY_KEYS_CORE,
@@ -36,6 +37,44 @@ def test_train(run_in_default_project):
     files = io_utils.list_files(os.path.join(temp_dir, "train_models"))
     assert len(files) == 1
     assert os.path.basename(files[0]) == "test-model.tar.gz"
+    model_dir = model.get_model("train_models")
+    assert model_dir is not None
+    metadata = Metadata.load(os.path.join(model_dir, "nlu"))
+    assert metadata.get("training_data") is None
+    assert not os.path.exists(
+        os.path.join(model_dir, "nlu", training_data.DEFAULT_TRAINING_DATA_OUTPUT_PATH)
+    )
+
+
+def test_train_persist_nlu_data(run_in_default_project):
+    temp_dir = os.getcwd()
+
+    run_in_default_project(
+        "train",
+        "-c",
+        "config.yml",
+        "-d",
+        "domain.yml",
+        "--data",
+        "data",
+        "--out",
+        "train_models",
+        "--fixed-model-name",
+        "test-model",
+        "--persist-nlu-data",
+    )
+
+    assert os.path.exists(os.path.join(temp_dir, "train_models"))
+    files = io_utils.list_files(os.path.join(temp_dir, "train_models"))
+    assert len(files) == 1
+    assert os.path.basename(files[0]) == "test-model.tar.gz"
+    model_dir = model.get_model("train_models")
+    assert model_dir is not None
+    metadata = Metadata.load(os.path.join(model_dir, "nlu"))
+    assert metadata.get("training_data") is not None
+    assert os.path.exists(
+        os.path.join(model_dir, "nlu", training_data.DEFAULT_TRAINING_DATA_OUTPUT_PATH)
+    )
 
 
 def test_train_core_compare(run_in_default_project):
@@ -257,6 +296,39 @@ def test_train_nlu(run_in_default_project):
     files = io_utils.list_files("train_models")
     assert len(files) == 1
     assert os.path.basename(files[0]).startswith("nlu-")
+    model_dir = model.get_model("train_models")
+    assert model_dir is not None
+    metadata = Metadata.load(os.path.join(model_dir, "nlu"))
+    assert metadata.get("training_data") is None
+    assert not os.path.exists(
+        os.path.join(model_dir, "nlu", training_data.DEFAULT_TRAINING_DATA_OUTPUT_PATH)
+    )
+
+
+def test_train_nlu_persist_nlu_data(run_in_default_project):
+    run_in_default_project(
+        "train",
+        "nlu",
+        "-c",
+        "config.yml",
+        "--nlu",
+        "data/nlu.md",
+        "--out",
+        "train_models",
+        "--persist-nlu-data",
+    )
+
+    assert os.path.exists("train_models")
+    files = io_utils.list_files("train_models")
+    assert len(files) == 1
+    assert os.path.basename(files[0]).startswith("nlu-")
+    model_dir = model.get_model("train_models")
+    assert model_dir is not None
+    metadata = Metadata.load(os.path.join(model_dir, "nlu"))
+    assert metadata.get("training_data") is not None
+    assert os.path.exists(
+        os.path.join(model_dir, "nlu", training_data.DEFAULT_TRAINING_DATA_OUTPUT_PATH)
+    )
 
 
 def test_train_nlu_temp_files(run_in_default_project):
@@ -272,7 +344,7 @@ def test_train_help(run):
                   [-c CONFIG] [-d DOMAIN] [--out OUT]
                   [--augmentation AUGMENTATION] [--debug-plots]
                   [--dump-stories] [--fixed-model-name FIXED_MODEL_NAME]
-                  [--force]
+                  [--persist-nlu-data] [--force]
                   {core,nlu} ..."""
 
     lines = help_text.split("\n")
@@ -285,7 +357,8 @@ def test_train_nlu_help(run):
     output = run("train", "nlu", "--help")
 
     help_text = """usage: rasa train nlu [-h] [-v] [-vv] [--quiet] [-c CONFIG] [--out OUT]
-                      [-u NLU] [--fixed-model-name FIXED_MODEL_NAME]"""
+                      [-u NLU] [--fixed-model-name FIXED_MODEL_NAME]
+                      [--persist-nlu-data]"""
 
     lines = help_text.split("\n")