merge base

CHANGELOG.rst

@@ -7,7 +7,23 @@ Rasa Change Log
 All notable changes to this project will be documented in this file.
 This project adheres to `Semantic Versioning`_ starting with version 1.0.
 
-[1.3.4] - 2019-09-19
+
+[1.3.6] - 2019-09-21
+^^^^^^^^^^^^^^^^^^^^
+
+Added
+-----
+- Added the ability for users to specify a conversation id to send a message to when
+  using the ``RasaChat`` input channel.
+
+[1.3.5] - 2019-09-20
+^^^^^^^^^^^^^^^^^^^^
+
+Fixed
+-----
+- Fixed issue where ``rasa init`` would fail without spaCy being installed
+
+[1.3.4] - 2019-09-20
 ^^^^^^^^^^^^^^^^^^^^
 
 Added
@@ -27,6 +43,14 @@ Fixed
   ``Doc``-objects. The resulting lists are merged with their preserved order and
   properly returned.
 
+Changed
+-------
+- The endpoint ``POST /model/train`` no longer supports specifying an output directory
+  for the trained model using the field ``out``. Instead you can choose whether you
+  want to save the trained model in the default model directory (``models``)
+  (default behavior) or in a temporary directory by specifying the
+  ``save_to_default_model_directory`` field in the training request.
+
 [1.3.3] - 2019-09-13
 ^^^^^^^^^^^^^^^^^^^^
 
@@ -57,6 +81,7 @@ Changed
 -------
 - Pin gast to == 0.2.2
 
+
 [1.3.0] - 2019-09-05
 ^^^^^^^^^^^^^^^^^^^^
 
@@ -150,7 +175,7 @@ Removed
 
 Fixed
 -----
-- Correctly pass SSL flag values to x CLI command
+- Correctly pass SSL flag values to x CLI command (backport of
 
 
 [1.2.8] - 2019-09-10
@@ -159,7 +184,8 @@ Fixed
 Fixed
 -----
 - SQL tracker events are retrieved ordered by timestamps. This fixes interactive
-  learning events being shown in the wrong order.
+  learning events being shown in the wrong order. Backport of ``1.3.2`` patch
+  (PR #4427).
 
 
 [1.2.7] - 2019-09-02

docs/_static/spec/rasa.yml

@@ -1228,15 +1228,16 @@ components:
           $ref: '#/components/schemas/NLUTrainingData'
         stories:
           $ref: '#/components/schemas/StoriesTrainingData'
-        out:
-          type: string
-          description: Output directory
-          example: models
         force:
           type: boolean
           description: >-
             Force a model training even if the data has not changed
           example: false
+        save_to_default_model_directory:
+          type: boolean
+          description:  >-
+            If `true` (default) the trained model will be saved in the default model
+            directory, if `false` it will be saved in a temporary directory
       required: ["config"]
 
     NLUTrainingData:

rasa/core/channels/rasa_chat.py

@@ -13,6 +13,10 @@
 
 logger = logging.getLogger(__name__)
 
+CONVERSATION_ID_KEY = "conversation_id"
+JWT_USERNAME_KEY = "username"
+INTERACTIVE_LEARNING_PERMISSION = "clientEvents:create"
+
 
 class RasaChatInput(RestInput):
     """Chat input channel for Rasa X"""
@@ -88,15 +92,39 @@ async def _decode_bearer_token(self, bearer_token: Text) -> Optional[Dict]:
             logger.exception("Failed to decode bearer token.")
 
     async def _extract_sender(self, req: Request) -> Optional[Text]:
-        """Fetch user from the Rasa X Admin API"""
+        """Fetch user from the Rasa X Admin API."""
 
+        jwt_payload = None
         if req.headers.get("Authorization"):
-            user = await self._decode_bearer_token(req.headers["Authorization"])
-            if user:
-                return user["username"]
-
-        user = await self._decode_bearer_token(req.args.get("token", default=None))
-        if user:
-            return user["username"]
-
-        abort(401)
+            jwt_payload = await self._decode_bearer_token(req.headers["Authorization"])
+
+        if not jwt_payload:
+            jwt_payload = await self._decode_bearer_token(req.args.get("token"))
+
+        if not jwt_payload:
+            abort(401)
+
+        if CONVERSATION_ID_KEY in req.json:
+            if self._has_user_permission_to_send_messages_to_conversation(
+                jwt_payload, req.json
+            ):
+                return req.json[CONVERSATION_ID_KEY]
+            else:
+                logger.error(
+                    "User '{}' does not have permissions to send messages to "
+                    "conversation '{}'.".format(
+                        jwt_payload[JWT_USERNAME_KEY], req.json[CONVERSATION_ID_KEY]
+                    )
+                )
+                abort(401)
+
+        return jwt_payload[JWT_USERNAME_KEY]
+
+    @staticmethod
+    def _has_user_permission_to_send_messages_to_conversation(
+        jwt_payload: Dict, message: Dict
+    ) -> bool:
+        user_scopes = jwt_payload.get("scopes", [])
+        return INTERACTIVE_LEARNING_PERMISSION in user_scopes or message[
+            CONVERSATION_ID_KEY
+        ] == jwt_payload.get(JWT_USERNAME_KEY)

rasa/nlu/utils/spacy_utils.py

@@ -2,7 +2,6 @@
 import typing
 from typing import Any, Dict, List, Optional, Text, Tuple
 
-from spacy.tokens import Doc
 from rasa.nlu.components import Component
 from rasa.nlu.config import RasaNLUModelConfig, override_defaults
 from rasa.nlu.training_data import Message, TrainingData
@@ -185,6 +184,8 @@ def process_non_content_bearing_samples(
     ) -> List[Tuple[int, "Doc"]]:
         """Creates empty Doc-objects from zero-lengthed training samples strings."""
 
+        from spacy.tokens import Doc
+
         n_docs = [
             (empty_sample[0], doc)
             for empty_sample, doc in zip(

rasa/server.py

@@ -670,6 +670,11 @@ async def train(request: Request):
             domain_path = os.path.join(temp_dir, "domain.yml")
             dump_obj_as_str_to_file(domain_path, rjs["domain"])
 
+        if rjs.get("save_to_default_model_directory", True) is True:
+            model_output_directory = DEFAULT_MODELS_PATH
+        else:
+            model_output_directory = tempfile.gettempdir()
+
         try:
             with app.active_training_processes.get_lock():
                 app.active_training_processes.value += 1
@@ -678,7 +683,7 @@ async def train(request: Request):
                 domain=domain_path,
                 config=config_path,
                 training_files=temp_dir,
-                output_path=rjs.get("out", DEFAULT_MODELS_PATH),
+                output_path=model_output_directory,
                 force_training=rjs.get("force", False),
             )
 

rasa/train.py

@@ -61,6 +61,8 @@ async def train_async(
         output_path: Output path.
         force_training: If `True` retrain model even if data has not changed.
         fixed_model_name: Name of model to be stored.
+        persist_nlu_training_data: `True` if the NLU training data should be persisted
+                                   with the model.
         kwargs: Additional training parameters.
 
     Returns:
@@ -115,11 +117,8 @@ async def _train_async_internal(
     """Trains a Rasa model (Core and NLU). Use only from `train_async`.
 
     Args:
-        domain: Path to the domain file.
-        config: Path to the config for Core and NLU.
+        file_importer: `TrainingDataImporter` which supplies the training data.
         train_path: Directory in which to train the model.
-        nlu_data_directory: Path to NLU training files.
-        story_directory: Path to Core training files.
         output_path: Output path.
         force_training: If `True` retrain model even if data has not changed.
         fixed_model_name: Name of model to be stored.

rasa/version.py

@@ -1 +1 @@
-__version__ = "1.3.4"
+__version__ = "1.3.6"

tests/core/test_channels.py

@@ -1,5 +1,6 @@
 import json
 import logging
+from typing import Dict
 from unittest.mock import patch, MagicMock
 
 import pytest
@@ -9,7 +10,13 @@
 
 import rasa.core.run
 from rasa.core import utils
+from rasa.core.channels import RasaChatInput
 from rasa.core.channels.channel import UserMessage
+from rasa.core.channels.rasa_chat import (
+    JWT_USERNAME_KEY,
+    CONVERSATION_ID_KEY,
+    INTERACTIVE_LEARNING_PERMISSION,
+)
 from rasa.core.channels.telegram import TelegramOutput
 from rasa.utils.endpoints import EndpointConfig
 from tests.core import utilities
@@ -822,3 +829,40 @@ async def test_rasa_chat_input():
         await rasa_chat_input._fetch_public_key()
         assert rasa_chat_input.jwt_key == public_key
         assert rasa_chat_input.jwt_algorithm == jwt_algorithm
+
+
+@pytest.mark.parametrize(
+    "jwt, message",
+    [
+        ({JWT_USERNAME_KEY: "abc"}, {CONVERSATION_ID_KEY: "abc"}),
+        (
+            {
+                JWT_USERNAME_KEY: "abc",
+                "scopes": ["a", "b", INTERACTIVE_LEARNING_PERMISSION],
+            },
+            {CONVERSATION_ID_KEY: "test"},
+        ),
+    ],
+)
+def test_has_user_permission_to_send_messages_to_conversation(jwt: Dict, message: Dict):
+    assert RasaChatInput._has_user_permission_to_send_messages_to_conversation(
+        jwt, message
+    )
+
+
+@pytest.mark.parametrize(
+    "jwt, message",
+    [
+        ({JWT_USERNAME_KEY: "abc"}, {CONVERSATION_ID_KEY: "xyz"}),
+        (
+            {JWT_USERNAME_KEY: "abc", "scopes": ["a", "b"]},
+            {CONVERSATION_ID_KEY: "test"},
+        ),
+    ],
+)
+def test_has_user_permission_to_send_messages_to_conversation_without_permission(
+    jwt: Dict, message: Dict
+):
+    assert not RasaChatInput._has_user_permission_to_send_messages_to_conversation(
+        jwt, message
+    )