Review comments.

examples/formbot/Makefile

@@ -1,20 +1,35 @@
 help:
 	@echo "    train"
 	@echo "        Train a stacked model using Rasa Ccore and NLU."
+	@echo "    train-core"
+	@echo "        Train a dialogue model using Rasa core."
+	@echo "    run-core"
+	@echo "        Spin up the core server on the command line"
+	@echo "    run-actions"
+	@echo "        Spin up the action server"
 	@echo "    run"
 	@echo "        Spin up both core and the action server"
 	@echo "    visualize"
 	@echo "        Show your stories as a graph"
 
+run:
+	make run-actions&
+	make run-core
+
+run-core:
+	rasa shell core -m models --verbose --endpoints endpoints.yml
+
+run-actions:
+	python -m rasa_core_sdk.endpoint --actions actions
 
 train:
 	rasa train --debug
 
-run:
-	rasa shell core -m models --verbose --endpoints endpoints.yml
+train-core:
+	rasa train core -s data/stories.md --debug
 
 train-interactive:
-	rasa interactive core -d domain.yml -m models -c config.yml --data data --verbose --endpoints endpoints.yml
+	rasa interactive -d domain.yml -m models -c config.yml --data data --verbose --endpoints endpoints.yml
 
 visualize:
 	rasa show stories

examples/formbot/README.md

@@ -25,13 +25,12 @@ Using this example you can build an actual assistant which demonstrates the
 functionality of the FormAction. You can use the example using the following 
 steps:
 
-1. Train the Rasa NLU and Rasa Core model by running:  
-```make train```  
-This will train the Rasa NLU model and Rasa Core model.
-The models will be stored in the `/models` directory.
+1. Train a stacked model containing the Rasa NLU and Rasa Core models by running:
+```make train```
+The model will be stored in the `/models` directory as a zipped file.
 
-2. Test the assistant by running:  
-```make run```  
+2. Test the assistant by running:
+```make run```
 This will load the assistant in your command line for you to chat.
 
 

examples/restaurantbot/Makefile

@@ -6,7 +6,7 @@ help:
 	@echo "    run-core"
 	@echo "        Runs the core server."
 	@echo "    train"
-	@echo "        Train a stacked model using Rasa core & NLU."
+	@echo "        Train a stacked model using Rasa Core & NLU."
 
 run:
 	make run-actions&

examples/restaurantbot/run.py

@@ -89,7 +89,7 @@ def train_nlu(
     parse_parser = subparser.add_parser("parse", help="parse any text")
 
     parse_parser.add_argument(
-        "--nlu-model", default="models/nlu", help="Path to the nlu model."
+        "--nlu-model", default=None, help="Path to the nlu model."
     )
     parse_parser.add_argument(
         "--core-model", default="models/core", help="Path to the core model."

tests/core/test_examples.py

@@ -88,14 +88,18 @@ async def test_formbot_example():
 
 async def test_restaurantbot_example():
     sys.path.append("examples/restaurantbot/")
-    from run import train_core, parse
+    from run import train_core, train_nlu, parse
 
     p = "examples/restaurantbot/"
     stories = os.path.join("data", "test_stories", "stories_babi_small.md")
+    nlu_data = os.path.join(p, "data", "nlu.md")
     core_model_path = await train_core(
         os.path.join(p, "domain.yml"), os.path.join(p, "models", "core"), stories
     )
+    nlu_model_path = train_nlu(
+        os.path.join(p, "config.yml"), os.path.join(p, "models", "nlu"), nlu_data
+    )
 
-    responses = await parse("/greet", core_model_path)
+    responses = await parse("hello", core_model_path, nlu_model_path)
 
     assert responses[0]["text"] == "how can I help you?"