Merge branch 'master' into random_seed_split

changelog/4925.bugfix.rst

@@ -0,0 +1 @@
+"rasa init" will ask if user wants to train a model

docs/user-guide/evaluating-models.rst

@@ -35,7 +35,7 @@ If you've done this, you can see how well your NLU model predicts the test cases
 
 .. code-block:: bash
 
-   rasa test nlu -u test_set.md --model models/nlu-20180323-145833.tar.gz
+   rasa test nlu -u train_test_split/test_data.md --model models/nlu-20180323-145833.tar.gz
 
 
 If you don't want to create a separate test set, you can

rasa/cli/scaffold.py

@@ -36,9 +36,11 @@ def print_train_or_instructions(args: argparse.Namespace, path: Text) -> None:
 
     print_success("Finished creating project structure.")
 
-    should_train = questionary.confirm(
-        "Do you want to train an initial model? 💪🏽"
-    ).skip_if(args.no_prompt, default=True)
+    should_train = (
+        questionary.confirm("Do you want to train an initial model? 💪🏽")
+        .skip_if(args.no_prompt, default=True)
+        .ask()
+    )
 
     if should_train:
         print_success("Training an initial model...")

tests/cli/conftest.py

@@ -13,6 +13,15 @@ def do_run(*args):
     return do_run
 
 
+@pytest.fixture
+def run_with_stdin(testdir: Testdir) -> Callable[..., RunResult]:
+    def do_run(*args, stdin):
+        args = ["rasa"] + list(args)
+        return testdir.run(*args, stdin=stdin)
+
+    return do_run
+
+
 @pytest.fixture
 def run_in_default_project(testdir: Testdir) -> Callable[..., RunResult]:
     os.environ["LOG_LEVEL"] = "ERROR"

tests/cli/test_rasa_init.py

@@ -22,3 +22,8 @@ def test_init_help(run: Callable[..., RunResult]):
     assert (
         output.outlines[0] == "usage: rasa init [-h] [-v] [-vv] [--quiet] [--no-prompt]"
     )
+
+
+def test_user_asked_to_train_model(run_with_stdin: Callable[..., RunResult]):
+    run_with_stdin("init", stdin=b"\nYN")
+    assert not os.path.exists("models")