merged upstream cli

CHANGELOG.rst

@@ -21,6 +21,7 @@ Added
 - added ``/parse`` endpoint to query for NLU results
 - File based event store
 - ability to configure event store using the endpoints file
+- added ability to use multiple env vars per line in yaml files
 
 Changed
 -------
@@ -34,12 +35,17 @@ Changed
 - configuration key ``store_type`` of the tracker store endpoint configuration
   has been renamed to ``type`` to allow usage accross endpoints
 - renamed ``policy_metadata.json`` to ``metadata.json`` for persisted models
+- ``scores`` array returned by the ``/conversations/{sender_id}/predict``
+  endpoint is now sorted according to the actions' scores.
 
 Removed
 -------
+- removed ``admin_token`` from ``RasaChatInput`` since it wasn't used
 
 Fixed
 -----
+- When a ``fork`` is used in interactive learning, every forked
+  storyline is saved (not just the last)
 
 [0.13.2] - 2019-02-06
 ^^^^^^^^^^^^^^^^^^^^^

README.md

@@ -1,36 +1,16 @@
 # Rasa Core 
 
-
 [![Join the chat on Rasa Community Forum](https://img.shields.io/badge/forum-join%20discussions-brightgreen.svg)](https://forum.rasa.com/?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge)
 [![PyPI version](https://img.shields.io/pypi/v/rasa_core.svg)](https://pypi.python.org/pypi/rasa-core)
 [![Supported Python Versions](https://img.shields.io/pypi/pyversions/rasa_core.svg)](https://pypi.python.org/pypi/rasa_core)
 [![Build Status](https://travis-ci.com/RasaHQ/rasa_core.svg?branch=master)](https://travis-ci.com/RasaHQ/rasa_core)
 [![Coverage Status](https://coveralls.io/repos/github/RasaHQ/rasa_core/badge.svg?branch=master)](https://coveralls.io/github/RasaHQ/rasa_core?branch=master)
 [![Documentation Status](https://img.shields.io/badge/docs-stable-brightgreen.svg)](https://rasa.com/docs/core)
 
-
-- **What do Rasa Core & NLU do? 🤔**
-  [Read About the Rasa Stack](https://rasa.com/products/rasa-stack/)
-
-- **I'd like to read the detailed docs 🤓**
-  [Read The Docs](https://rasa.com/docs/core)
-
-- **I'm ready to install Rasa Core! 🚀**
-  [Installation](https://rasa.com/docs/core/installation.html)
-
-- **I'm ready to start building! 🤖**
-  [Rasa Stack starter-pack](https://github.com/RasaHQ/starter-pack-rasa-stack)
-
-- **I have a question ❓**
-  [Rasa Community Forum](https://forum.rasa.com)
-
-- **I would like to contribute 🤗**
-  [How to contribute](#how-to-contribute)
-
-## Introduction
+<img align="right" height="244" src="https://www.rasa.com/assets/img/sara/sara-open-source-lg.png">
 
 Rasa Core is a framework for building conversational software, which includes
-Chat Bots on:
+chatbots on:
 - Facebook Messenger
 - Slack
 - Microsoft Bot Framework
@@ -51,6 +31,26 @@ Rasa Core lets you do that in a scalable way.
 There's a lot more background information in this
 [blog post](https://medium.com/rasa-blog/a-new-approach-to-conversational-software-2e64a5d05f2a).
 
+---
+- **What do Rasa Core & NLU do? 🤔**
+  [Read About the Rasa Stack](https://rasa.com/products/rasa-stack/)
+
+- **I'd like to read the detailed docs 🤓**
+  [Read The Docs](https://rasa.com/docs/core)
+
+- **I'm ready to install Rasa Core! 🚀**
+  [Installation](https://rasa.com/docs/core/installation/)
+
+- **I'm ready to start building! 🤖**
+  [Rasa Stack starter-pack](https://github.com/RasaHQ/starter-pack-rasa-stack)
+
+- **I have a question ❓**
+  [Rasa Community Forum](https://forum.rasa.com)
+
+- **I would like to contribute 🤗**
+  [How to contribute](#how-to-contribute)
+
+---  
 ## Where to get help
 
 There is extensive documentation:
@@ -65,7 +65,6 @@ Please use [Rasa Community Forum](https://forum.rasa.com) for quick answers to
 questions.
 
 
-
 ### README Contents:
 - [How to contribute](#how-to-contribute)
 - [Development Internals](#development-internals)
@@ -74,7 +73,7 @@ questions.
 ### How to contribute
 We are very happy to receive and merge your contributions. There is
 some more information about the style of the code and docs in the
-[documentation](https://nlu.rasa.com/contribute.html).
+[documentation](https://rasa.com/docs/contributing/).
 
 In general the process is rather simple:
 1. create an issue describing the feature you want to work on (or

docs/_static/spec/server.yml

@@ -343,10 +343,11 @@ paths:
       - Tracker
       summary: Predict the next action
       description: >-
-        Runs the conversations tracker through the models
-        policies to predict the next action. The action is
-        not executed, just returned. The state of the tracker
-        is not modified.
+        Runs the conversations tracker through the model's
+        policies to predict the scores of all actions present
+        in the model's domain. Actions are returned in the
+        'scores' array, sorted on their 'score' values.
+        The state of the tracker is not modified.
       operationId: predictAction
       parameters:
       - $ref: '#/components/parameters/senderId'

docs/migrations.rst

@@ -8,6 +8,20 @@ Migration Guide
 This page contains information about changes between major versions and
 how you can migrate from one version to another.
 
+
+.. _migration-to-0-14-0:
+
+0.13.x to 0.14.0
+----------------
+
+Function Naming
+~~~~~~~~~~~~~~~
+- renamed ``train_dialogue_model`` to ``train``. Please use ``train`` from
+  now on.
+- renamed ``rasa_core.evaluate`` to ``rasa_core.test``. Please use ``test``
+  from now on.
+
+
 .. _migration-to-0-13-0:
 
 0.12.x to 0.13.0

examples/concertbot/train.py

@@ -8,13 +8,11 @@ def train_dialogue(domain_file='domain.yml',
                    stories_file='data/stories.md',
                    model_path='models/dialogue',
                    policy_config='policy_config.yml'):
-    return train.train(domain_file=domain_file,
-                       stories_file=stories_file,
-                       output_path=model_path,
-                       policy_config=policy_config,
-                       kwargs={'augmentation_factor': 50,
-                                              'validation_split': 0.2}
-                       )
+    return train(domain_file=domain_file,
+                 stories_file=stories_file,
+                 output_path=model_path,
+                 policy_config=policy_config,
+                 kwargs={'augmentation_factor': 50, 'validation_split': 0.2})
 
 
 if __name__ == '__main__':

examples/concertbot/train_interactive.py

@@ -7,11 +7,10 @@
 
 
 def train_agent():
-    return train.train(domain_file="domain.yml",
-                       stories_file="data/stories.md",
-                       output_path="models/dialogue",
-                       policy_config='policy_config.yml'
-                       )
+    return train(domain_file="domain.yml",
+                 stories_file="data/stories.md",
+                 output_path="models/dialogue",
+                 policy_config='policy_config.yml')
 
 
 if __name__ == '__main__':

rasa_core/__init__.py

@@ -3,7 +3,7 @@
 import rasa_core.version
 
 from rasa_core.train import train
-from rasa_core.test import test as test
+from rasa_core.test import test
 from rasa_core.visualize import visualize
 
 logging.getLogger(__name__).addHandler(logging.NullHandler())

rasa_core/agent.py

@@ -225,8 +225,7 @@ def __init__(
                 "FormPolicy to your policy ensemble."
             )
 
-        self.interpreter = None
-        self.set_interpreter(interpreter)
+        self.interpreter = NaturalLanguageInterpreter.create(interpreter)
 
         self.nlg = NaturalLanguageGenerator.create(generator, self.domain)
         self.tracker_store = self.create_tracker_store(
@@ -368,7 +367,7 @@ def handle_text(
         message_preprocessor: Optional[Callable[[Text], Text]] = None,
         output_channel: Optional[OutputChannel] = None,
         sender_id: Optional[Text] = UserMessage.DEFAULT_SENDER_ID
-    ) -> Optional[List[Any]]:
+    ) -> Optional[List[Dict[Text, Any]]]:
         """Handle a single message.
 
         If a message preprocessor is passed, the message will be passed to that
@@ -707,21 +706,3 @@ def _form_policy_not_present(self) -> bool:
         return (self.domain and self.domain.form_names and not
                 any(isinstance(p, FormPolicy)
                     for p in self.policy_ensemble.policies))
-
-    def set_interpreter(self,
-                        interpreter: Optional[NaturalLanguageInterpreter]
-                        ) -> None:
-        from rasa_nlu.model import Interpreter
-
-        if not (isinstance(interpreter, NaturalLanguageInterpreter) or
-                isinstance(interpreter, Interpreter)):
-            if interpreter is not None:
-                logger.warning(
-                    "Passing a value for interpreter to an agent "
-                    "where the value is not an interpreter "
-                    "is deprecated. Construct the interpreter, before"
-                    "passing it to the agent, e.g. "
-                    "`interpreter = NaturalLanguageInterpreter.create(nlu)`.")
-
-            interpreter = NaturalLanguageInterpreter.create(interpreter, None)
-        self.interpreter = interpreter

rasa_core/channels/rasa_chat.py

@@ -21,12 +21,10 @@ def from_credentials(cls, credentials):
         if not credentials:
             cls.raise_missing_credentials_exception()
 
-        return cls(credentials.get("url"),
-                   credentials.get("admin_token"))
+        return cls(credentials.get("url"))
 
-    def __init__(self, url, admin_token=None):
+    def __init__(self, url):
         self.base_url = url
-        self.admin_token = admin_token
 
     def _check_token(self, token):
         url = "{}/users/me".format(self.base_url)

rasa_core/cli/__init__.py

@@ -3,12 +3,3 @@
 import rasa_core.cli.run
 import rasa_core.cli.train
 import rasa_core.cli.visualization
-
-
-def stories_from_cli_args(cmdline_arguments):
-    from rasa_core import utils
-
-    if cmdline_arguments.url:
-        return utils.download_file_from_url(cmdline_arguments.url)
-    else:
-        return cmdline_arguments.stories

rasa_core/cli/train.py

@@ -102,3 +102,12 @@ def add_general_args(parser):
              "file called `story_blocks_connections.html`.")
 
     arguments.add_logging_option_arguments(parser)
+
+
+def stories_from_cli_args(cmdline_arguments):
+    from rasa_core import utils
+
+    if cmdline_arguments.url:
+        return utils.download_file_from_url(cmdline_arguments.url)
+    else:
+        return cmdline_arguments.stories

rasa_core/constants.py

@@ -4,7 +4,7 @@
 
 DEFAULT_SERVER_URL = DEFAULT_SERVER_FORMAT.format(DEFAULT_SERVER_PORT)
 
-MINIMUM_COMPATIBLE_VERSION = "0.13.0a6"
+MINIMUM_COMPATIBLE_VERSION = "0.14.0a1"
 
 DOCS_BASE_URL = "https://rasa.com/docs/core"
 

rasa_core/evaluate.py

@@ -1,10 +1,10 @@
 import logging
 
-import rasa_core.test as test
+from rasa_core.test import main
 
 logger = logging.getLogger(__name__)
 
 if __name__ == '__main__':  # pragma: no cover
     logger.warning("Calling `rasa_core.evaluate` is deprecated. "
                    "Please use `rasa_core.test` instead.")
-    test.main()
+    main()

rasa_core/interpreter.py

@@ -21,7 +21,10 @@ def parse(self, text):
 
     @staticmethod
     def create(obj, endpoint=None):
-        if isinstance(obj, NaturalLanguageInterpreter):
+        from rasa_nlu.model import Interpreter
+
+        if (isinstance(obj, NaturalLanguageInterpreter) or
+                isinstance(obj, Interpreter)):
             return obj
 
         if not isinstance(obj, str):

rasa_core/server.py

@@ -406,6 +406,9 @@ def predict(sender_id):
         try:
             # Fetches the appropriate bot response in a json format
             responses = agent.predict_next(sender_id)
+            responses['scores'] = sorted(responses['scores'],
+                                         key = lambda k: (-k['score'],
+                                                          k['action']))
             return jsonify(responses)
 
         except Exception as e:

rasa_core/test.py

@@ -10,6 +10,7 @@
 import rasa_core.cli.arguments
 from typing import List, Optional, Any, Text, Dict, Tuple
 
+import rasa_core.cli.train
 from rasa_core import training, cli
 from rasa_core import utils
 from rasa_core.events import ActionExecuted, UserUttered
@@ -615,7 +616,7 @@ def main():
 
         _agent = Agent.load(cmdline_arguments.core, interpreter=_interpreter)
 
-        stories = cli.stories_from_cli_args(cmdline_arguments)
+        stories = rasa_core.cli.train.stories_from_cli_args(cmdline_arguments)
 
         test(stories, _agent, cmdline_arguments.max_stories,
              cmdline_arguments.output,

rasa_core/train.py

@@ -4,6 +4,7 @@
 import tempfile
 from typing import Text, Dict, Optional
 
+import rasa_core.cli.train
 from rasa_core import config, cli
 from rasa_core import utils
 from rasa_core.broker import PikaProducer
@@ -243,7 +244,8 @@ def do_interactive_learning(cmdline_args, stories, additional_arguments=None):
 
     utils.configure_colored_logging(cmdline_arguments.loglevel)
 
-    training_stories = cli.stories_from_cli_args(cmdline_arguments)
+    training_stories = rasa_core.cli.train.stories_from_cli_args(
+        cmdline_arguments)
 
     if cmdline_arguments.mode == 'default':
         do_default_training(cmdline_arguments,