Merge pull request #80 from snipsco/release/0.60.0

Release 0.60.0

.appveyor.yml

@@ -19,7 +19,6 @@ install:
   - echo "snips-nlu-ffi", >> Cargo.toml
   - echo "snips-nlu-ffi/python/snips-nlu-python-ffi", >> Cargo.toml
   - echo "snips-nlu-lib", >> Cargo.toml
-  - echo "snips-nlu-cli", >> Cargo.toml
   - echo ] >> Cargo.toml
   - ps: (Get-Content snips-nlu-ffi/python/snips-nlu-python-ffi/Cargo.toml) | ForEach-Object { $_ -replace "^snips-nlu-ffi = .*$", "snips-nlu-ffi = { path = `"../..`" }" } | Set-Content snips-nlu-ffi/python/snips-nlu-python-ffi/Cargo.toml
 

.travis/install.sh

@@ -8,8 +8,7 @@ echo '
 members=[
     "snips-nlu-ffi",
     "snips-nlu-ffi/python/snips-nlu-python-ffi",
-    "snips-nlu-lib",
-    "snips-nlu-cli"
+    "snips-nlu-lib"
 ]' > Cargo.toml
 
 echo "Replacing snips-nlu-ffi url for local version"

CHANGELOG.md

@@ -1,6 +1,17 @@
 # Changelog
 All notable changes to this project will be documented in this file.
 
+## [0.60.0] - 2018-10-05
+### Added
+- Support for 3 new builtin entities in French: `snips/musicAlbum`, `snips/musicArtist` and `snips/musicTrack`
+
+### Changed
+- model version `0.16.0` => `0.17.0`
+- Replace `snips-nlu-cli` crate with Rust example
+
+### Fixed
+- Bug with entity feature name in intent classification
+
 ## [0.59.0] - 2018-09-26
 ### Added
 - Limited support for Italian by bumping the `snips-nlu-ontology` to `0.58.0` and `snips-nlu-utils` to `0.7.0`
@@ -97,6 +108,7 @@ being statically hardcoded, reducing the binary size by 31Mb.
 - Improve support for japanese
 - Rename python package to `snips_nlu_rust`
 
+[0.60.0]: https://github.com/snipsco/snips-nlu-rs/compare/0.59.0...0.60.0
 [0.59.0]: https://github.com/snipsco/snips-nlu-rs/compare/0.58.3...0.59.0
 [0.58.3]: https://github.com/snipsco/snips-nlu-rs/compare/0.58.2...0.58.3
 [0.58.2]: https://github.com/snipsco/snips-nlu-rs/compare/0.58.1...0.58.2

README.rst

@@ -4,7 +4,7 @@ Snips NLU Rust
 .. image:: https://travis-ci.org/snipsco/snips-nlu-rs.svg?branch=develop
    :target: https://travis-ci.org/snipsco/snips-nlu-rs
 
-.. image:: https://ci.appveyor.com/api/projects/status/github/snipsco/snips-nlu-rs?branch=develop&svg=true
+.. image:: https://ci.appveyor.com/api/projects/status/rsf27a9txeomic8o/branch/develop?svg=true
    :target: https://ci.appveyor.com/project/snipsco/snips-nlu-rs
 
 Installation
@@ -64,18 +64,18 @@ This repository only contains the inference part, in order to produce trained mo
 the `Snips NLU python library <https://github.com/snipsco/snips-nlu>`_.
 
 
-Interactive CLI and API Usage
------------------------------
+Example and API Usage
+---------------------
 
-The `rust interactive cli <snips-nlu-cli>`_ is a good example of to how to use ``snips-nlu-rs``.
+The `interactive parsing CLI <snips-nlu-lib/examples/interactive_parsing_cli>`_  is a good example
+of to how to use ``snips-nlu-rs``.
 
-Here is how you can run the interactive parsing cli:
+Here is how you can run the CLI example:
 
 .. code-block:: bash
 
    $ git clone https://github.com/snipsco/snips-nlu-rs
-   $ cd snips-nlu-rs/snips-nlu-cli
-   $ cargo run ../data/tests/models/trained_engine
+   $ cargo run -p snips-nlu-lib --example interactive_parsing_cli data/tests/models/nlu_engine
 
 Here we used a sample trained engine, which consists in two intents: ``MakeCoffee`` and ``MakeTea``.
 Thus, it will be able to parse queries like ``"Make me two cups of coffee please"`` or ``"I'd like a hot tea"``.

data/tests/models/nlu_engine/builtin_entity_parser/metadata.json

@@ -0,0 +1,4 @@
+{
+  "language": "en",
+  "gazetteer_parser": null
+}

data/tests/models/nlu_engine/custom_entity_parser/metadata.json

@@ -0,0 +1,4 @@
+{
+  "language": "en",
+  "parser_directory": "parser"
+}

data/tests/models/nlu_engine/custom_entity_parser/parser/metadata.json

@@ -0,0 +1,8 @@
+{
+  "parsers_metadata": [
+    {
+      "entity_identifier": "Temperature",
+      "entity_parser": "parser_1"
+    }
+  ]
+}

data/tests/models/nlu_engine/custom_entity_parser/parser/parser_1/metadata.json

@@ -0,0 +1 @@
+{"version":"0.5.0-SNAPSHOT","parser_filename":"parser","threshold":1.0,"stop_words":[],"edge_cases":[]}

data/tests/models/trained_engine/deterministic_intent_parser/intent_parser.json → data/tests/models/nlu_engine/deterministic_intent_parser/intent_parser.json

@@ -22,17 +22,17 @@
   "language_code": "en",
   "patterns": {
     "MakeCoffee": [
-      "^\\s*Make\\s*me\\s*(?P<group_5>%SNIPSNUMBER%)\\s*cup\\s*of\\s*coffee\\s*$",
-      "^\\s*give\\s*me\\s*(?P<group_4>%SNIPSNUMBER%)\\s*coffees\\s*please\\s*$",
       "^\\s*Make\\s*me\\s*(?P<group_0>%SNIPSNUMBER%)\\s*cups\\s*of\\s*coffee\\s*$",
       "^\\s*Brew\\s*(?P<group_3>%SNIPSNUMBER%)\\s*coffee\\s*cups\\s*$",
+      "^\\s*give\\s*me\\s*(?P<group_4>%SNIPSNUMBER%)\\s*coffees\\s*please\\s*$",
       "^\\s*make\\s*me\\s*(?P<group_2>%SNIPSNUMBER%)\\s*cups\\s*of\\s*coffee\\s*$",
-      "^\\s*Brew\\s*me\\s*(?P<group_1>%SNIPSNUMBER%)\\s*coffee\\s*cups\\s*$"
+      "^\\s*Brew\\s*me\\s*(?P<group_1>%SNIPSNUMBER%)\\s*coffee\\s*cups\\s*$",
+      "^\\s*Make\\s*me\\s*(?P<group_5>%SNIPSNUMBER%)\\s*cup\\s*of\\s*coffee\\s*$"
     ],
     "MakeTea": [
-      "^\\s*Prepare\\s*(?P<group_10>%SNIPSNUMBER%)\\s*cups\\s*of\\s*(?P<group_11>boiling|iced|cold|hot)\\s*tea\\s*$",
-      "^\\s*Please\\s*can\\s*I\\s*get\\s*(?P<group_8>%SNIPSNUMBER%)\\s*(?P<group_9>boiling|iced|cold|hot)\\s*teas\\s*\\?\\s*$",
       "^\\s*Make\\s*(?P<group_6>%SNIPSNUMBER%)\\s*(?P<group_7>boiling|iced|cold|hot)\\s*teas\\s*$",
+      "^\\s*Please\\s*can\\s*I\\s*get\\s*(?P<group_8>%SNIPSNUMBER%)\\s*(?P<group_9>boiling|iced|cold|hot)\\s*teas\\s*\\?\\s*$",
+      "^\\s*Prepare\\s*(?P<group_10>%SNIPSNUMBER%)\\s*cups\\s*of\\s*(?P<group_11>boiling|iced|cold|hot)\\s*tea\\s*$",
       "^\\s*Make\\s*me\\s*(?P<group_12>%SNIPSNUMBER%)\\s*tea\\s*$"
     ]
   },
@@ -44,6 +44,5 @@
       "beverage_temperature": "Temperature",
       "number_of_cups": "snips/number"
     }
-  },
-  "unit_name": "deterministic_intent_parser"
+  }
 }

data/tests/models/trained_engine/nlu_engine.json → data/tests/models/nlu_engine/nlu_engine.json

@@ -1,4 +1,5 @@
 {
+  "builtin_entity_parser": "builtin_entity_parser",
   "config": {
     "intent_parsers_configs": [
       {
@@ -18,6 +19,7 @@
           "featurizer_config": {
             "pvalue_threshold": 0.4,
             "sublinear_tf": false,
+            "use_stemming": true,
             "word_clusters_name": null
           },
           "random_seed": null,
@@ -140,6 +142,19 @@
                 -1,
                 0
               ]
+            },
+            {
+              "args": {
+                "cluster_name": "brown_clusters",
+                "use_stemming": false
+              },
+              "factory_name": "word_cluster",
+              "offsets": [
+                -2,
+                -1,
+                0,
+                1
+              ]
             }
           ],
           "random_seed": null,
@@ -151,20 +166,11 @@
     ],
     "unit_name": "nlu_engine"
   },
+  "custom_entity_parser": "custom_entity_parser",
   "dataset_metadata": {
     "entities": {
       "Temperature": {
-        "automatically_extensible": true,
-        "utterances": {
-          "Boiling": "hot",
-          "Cold": "cold",
-          "Hot": "hot",
-          "Iced": "cold",
-          "boiling": "hot",
-          "cold": "cold",
-          "hot": "hot",
-          "iced": "cold"
-        }
+        "automatically_extensible": true
       }
     },
     "language_code": "en",
@@ -182,7 +188,7 @@
     "deterministic_intent_parser",
     "probabilistic_intent_parser"
   ],
-  "model_version": "0.16.0",
-  "training_package_version": "0.15.1",
+  "model_version": "0.17.0",
+  "training_package_version": "0.17.0",
   "unit_name": "nlu_engine"
-}
+}