- detector name validation + samples

CHANGELOG.md

@@ -15,6 +15,10 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ### Fixed
 
+## [2.3.0] - 2021-05-05
+
+* Disabled mandatory validation for detectors' names to allow for [Writeprint detection](https://docs.expert.ai/nlapi/latest/guide/detectors/#writeprint-detector)
+
 ## [2.2.0] - 2021-03-15
 
 * Added support for [information detection](https://docs.expert.ai/nlapi/latest/guide/detection)

expertai/nlapi/cloud/validate.py

@@ -1,54 +1,54 @@
-# Copyright (c) 2020 original authors
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-# https://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an \"AS IS\" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-
-from expertai.nlapi.common import constants
-from expertai.nlapi.common.errors import ParameterError
-
-
-class ExpertAiValidation:
-    """
-    To be consistent, every new method added to verify a value should be
-    name according this pattern: [value_name]_value_is_correct
-    """
-
-    def language_value_is_correct(self, language):
-        return language in constants.LANGUAGES.keys()
-    def detector_value_is_correct(self, detector):
-        return detector in constants.DETECTORS.keys()
-
-    def resource_value_is_correct(self, resource):
-        return resource in constants.RESOURCES_NAMES
-
-    def context_value_is_correct(self, context):
-        return True
-
-    def taxonomy_value_is_correct(self, taxonomy):
-        return True
-
-    def check_name(self, param_name):
-        if param_name not in constants.PARAMETER_NAMES:
-            raise ParameterError("{} - invalid name".format(param_name))
-
-    def check_value(self, param_name, value):
-        method_name = "{}_value_is_correct".format(param_name)
-        method = getattr(self, method_name)
-        if not method(**{param_name: value}):
-            raise ParameterError(
-                "{} - invalid value: {}".format(param_name, value)
-            )
-
-    def check_parameters(self, params):
-        for p_name, p_value in params.items():
-            self.check_name(p_name)
-            self.check_value(p_name, p_value)
+# Copyright (c) 2020 original authors
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# https://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an \"AS IS\" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from expertai.nlapi.common import constants
+from expertai.nlapi.common.errors import ParameterError
+
+
+class ExpertAiValidation:
+    """
+    To be consistent, every new method added to verify a value should be
+    name according this pattern: [value_name]_value_is_correct
+    """
+
+    def language_value_is_correct(self, language):
+        return language in constants.LANGUAGES.keys()
+    def detector_value_is_correct(self, detector):
+        return True;
+
+    def resource_value_is_correct(self, resource):
+        return resource in constants.RESOURCES_NAMES
+
+    def context_value_is_correct(self, context):
+        return True
+
+    def taxonomy_value_is_correct(self, taxonomy):
+        return True
+
+    def check_name(self, param_name):
+        if param_name not in constants.PARAMETER_NAMES:
+            raise ParameterError("{} - invalid name".format(param_name))
+
+    def check_value(self, param_name, value):
+        method_name = "{}_value_is_correct".format(param_name)
+        method = getattr(self, method_name)
+        if not method(**{param_name: value}):
+            raise ParameterError(
+                "{} - invalid value: {}".format(param_name, value)
+            )
+
+    def check_parameters(self, params):
+        for p_name, p_value in params.items():
+            self.check_name(p_name)
+            self.check_value(p_name, p_value)

expertai/nlapi/common/constants.py

@@ -1,89 +1,86 @@
-# Copyright (c) 2020 original authors
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-# https://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an \"AS IS\" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-
-BASE_API_URL = "https://nlapi.expert.ai/v2"
-BASE_EDGE_URL = "https://edgeapi.expert.ai"
-
-OAUTH2_TOKEN_URL = "https://developer.expert.ai/oauth2/token"
-
-USERNAME_ENV_VARIABLE = "EAI_USERNAME"
-PASSWORD_ENV_VARIABLE = "EAI_PASSWORD"
-TOKEN_ENV_VARIABLE = "AUTH_TOKEN"
-AUTH_HEADER_KEY = "Authorization"
-AUTH_HEADER_VALUE = "Bearer {}"
-
-TK_TIMESTAMP_FILENAME = ".timestamp"
-
-# No leading slash
-FULL_ANALYSIS_PATH = "analyze/{context}/{language}"
-ANALYSIS_PATH = "analyze/{context}/{language}/{resource}"
-CLASSIFICATION_PATH = "categorize/{taxonomy}/{language}"
-EXECUTION_KEY_PATH = "edge/key/{footprint}"
-DETECTION_PATH = "detect/{detector}/{language}"
-
-CONTEXTS_PATH = "contexts"
-DETECTORS_PATH = "detectors"
-TAXONOMIES_PATH = "taxonomies"
-TAXONOMY_PATH = "taxonomies/{taxonomy}/{language}"
-
-CONTENT_TYPE_HEADER = {"Content-Type": "application/json"}
-
-URLS_AND_METHODS = (
-    (FULL_ANALYSIS_PATH, "POST"),
-    (ANALYSIS_PATH, "POST"),
-    (CLASSIFICATION_PATH, "POST"),
-    (CONTEXTS_PATH, "GET"),
-    (TAXONOMIES_PATH, "GET"),
-    (TAXONOMY_PATH, "GET"),
-    (EXECUTION_KEY_PATH, "GET"),        
-    (DETECTION_PATH, "POST"),
-    (DETECTORS_PATH, "GET"),
-)
-
-HTTP_GET = "GET"
-HTTP_SUCCESSFUL = 200
-HTTP_BAD_REQUEST = 400
-HTTP_UNAUTHORIZED = 401
-HTTP_FORBIDDEN = 403
-HTTP_NOT_FOUND = 404
-HTTP_INTERNAL_SERVER_ERROR = 500
-
-# Strings used when print out the status of a EaiResponse
-HTTP_ERRORS = {
-    HTTP_UNAUTHORIZED: "UNAUTHORIZED",
-    HTTP_FORBIDDEN: "FORBIDDEN",
-    HTTP_NOT_FOUND: "NOT FOUND",
-    HTTP_INTERNAL_SERVER_ERROR: "INTERNAL SERVER ERROR",
-}
-
-UNKNOWN = "UNKNOWN_STATUS"
-SUCCESSFUL = "SUCCESSFUL"
-BAD_REQUEST = "BAD REQUEST"
-
-PARAMETER_NAMES = ["language", "resource", "context", "taxonomy", "footprint","detector"]
-
-LANGUAGES = {
-    "de": "German",
-    "en": "English",
-    "es": "Spanish",
-    "fr": "French",
-    "it": "Italian",
-}
-DETECTORS = {
-    "pii": "Protected Information"
-}
-
-RESOURCES_NAMES = ["disambiguation", "relevants", "entities", "relations", "sentiment"]
-
-RESPONSE_KEYS_TO_IGNORE = ["language", "version", "content"]
+# Copyright (c) 2020 original authors
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# https://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an \"AS IS\" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+BASE_API_URL = "https://nlapi.expert.ai/v2"
+BASE_EDGE_URL = "https://edgeapi.expert.ai"
+
+OAUTH2_TOKEN_URL = "https://developer.expert.ai/oauth2/token"
+
+USERNAME_ENV_VARIABLE = "EAI_USERNAME"
+PASSWORD_ENV_VARIABLE = "EAI_PASSWORD"
+TOKEN_ENV_VARIABLE = "AUTH_TOKEN"
+AUTH_HEADER_KEY = "Authorization"
+AUTH_HEADER_VALUE = "Bearer {}"
+
+TK_TIMESTAMP_FILENAME = ".timestamp"
+
+# No leading slash
+FULL_ANALYSIS_PATH = "analyze/{context}/{language}"
+ANALYSIS_PATH = "analyze/{context}/{language}/{resource}"
+CLASSIFICATION_PATH = "categorize/{taxonomy}/{language}"
+EXECUTION_KEY_PATH = "edge/key/{footprint}"
+DETECTION_PATH = "detect/{detector}/{language}"
+
+CONTEXTS_PATH = "contexts"
+DETECTORS_PATH = "detectors"
+TAXONOMIES_PATH = "taxonomies"
+TAXONOMY_PATH = "taxonomies/{taxonomy}/{language}"
+
+CONTENT_TYPE_HEADER = {"Content-Type": "application/json"}
+
+URLS_AND_METHODS = (
+    (FULL_ANALYSIS_PATH, "POST"),
+    (ANALYSIS_PATH, "POST"),
+    (CLASSIFICATION_PATH, "POST"),
+    (CONTEXTS_PATH, "GET"),
+    (TAXONOMIES_PATH, "GET"),
+    (TAXONOMY_PATH, "GET"),
+    (EXECUTION_KEY_PATH, "GET"),        
+    (DETECTION_PATH, "POST"),
+    (DETECTORS_PATH, "GET"),
+)
+
+HTTP_GET = "GET"
+HTTP_SUCCESSFUL = 200
+HTTP_BAD_REQUEST = 400
+HTTP_UNAUTHORIZED = 401
+HTTP_FORBIDDEN = 403
+HTTP_NOT_FOUND = 404
+HTTP_INTERNAL_SERVER_ERROR = 500
+
+# Strings used when print out the status of a EaiResponse
+HTTP_ERRORS = {
+    HTTP_UNAUTHORIZED: "UNAUTHORIZED",
+    HTTP_FORBIDDEN: "FORBIDDEN",
+    HTTP_NOT_FOUND: "NOT FOUND",
+    HTTP_INTERNAL_SERVER_ERROR: "INTERNAL SERVER ERROR",
+}
+
+UNKNOWN = "UNKNOWN_STATUS"
+SUCCESSFUL = "SUCCESSFUL"
+BAD_REQUEST = "BAD REQUEST"
+
+PARAMETER_NAMES = ["language", "resource", "context", "taxonomy", "footprint","detector"]
+
+LANGUAGES = {
+    "de": "German",
+    "en": "English",
+    "es": "Spanish",
+    "fr": "French",
+    "it": "Italian",
+}
+
+RESOURCES_NAMES = ["disambiguation", "relevants", "entities", "relations", "sentiment"]
+
+RESPONSE_KEYS_TO_IGNORE = ["language", "version", "content"]

samples/cloud natural language api/document classification/behavioral-traits.py

@@ -0,0 +1,15 @@
+# Demonstrates the IPTC Media Topics document classification capability of the (Cloud based) expert.ai Natural Language API
+
+from expertai.nlapi.cloud.client import ExpertAiClient
+client = ExpertAiClient()
+
+text = "Michael Jordan was one of the best basketball players of all time. Scoring was Jordan's stand-out skill, but he still holds a defensive NBA record, with eight steals in a half."
+taxonomy = 'iptc'
+language= 'en'
+
+output = client.classification(body={"document": {"text": text}}, params={'taxonomy': taxonomy, 'language': language})
+
+print("Tab separated list of categories:")
+
+for category in output.categories:
+    print(category.id_, category.hierarchy, sep="\t")

samples/cloud natural language api/document classification/emotional-traits.py

@@ -0,0 +1,15 @@
+# Demonstrates the IPTC Media Topics document classification capability of the (Cloud based) expert.ai Natural Language API
+
+from expertai.nlapi.cloud.client import ExpertAiClient
+client = ExpertAiClient()
+
+text = "I experience a mix of conflicting emotions: the approach of the fateful date scares me, but at the same time I can't wait for it to arrive. I have moments of elation and others of pure panic, but I would say that I am mostly happy."
+taxonomy = 'emotional-traits'
+language= 'en'
+
+output = client.classification(body={"document": {"text": text}}, params={'taxonomy': taxonomy, 'language': language})
+
+print("Tab separated list of categories:")
+
+for category in output.categories:
+    print(category.id_, category.hierarchy, sep="\t")

samples/cloud natural language api/information detection/writeprint.py

@@ -0,0 +1,16 @@
+# Demonstrates the Writeprint detection capability of the expert.ai (Cloud based) Natural Language API
+
+import json
+from expertai.nlapi.cloud.client import ExpertAiClient
+client = ExpertAiClient()
+
+text = "My dear Bagginses and Boffins, Tooks and Brandybucks, Grubbs, Chubbs, Hornblowers, Bolgers, Bracegirdles and Proudfoots. Today is my one hundred and eleventh birthday! Alas, eleventy-one years is far too short a time to live among such excellent and admirable hobbits. I don't know half of you half as well as I should like, and I like less than half of you half as well as you deserve."
+
+detector = 'writeprint'
+language= 'en'
+
+output = client.detection(body={"document": {"text": text}}, params={'detector': detector, 'language': language})
+
+# Output extra data containing the JSON-LD object
+
+print("extra_data: ",json.dumps(output.extra_data, indent=4, sort_keys=True))