Update conf files location (#1358)

docker-compose-transformers.yml

@@ -16,7 +16,7 @@ services:
       context: ./presidio-analyzer
       args:
         - NAME=presidio-analyzer
-        - NLP_CONF_FILE=conf/transformers.yaml
+        - NLP_CONF_FILE=presidio_analyzer/conf/transformers.yaml
       dockerfile: Dockerfile.transformers
     environment:
       - PORT=5001

docs/analyzer/adding_recognizers.md

@@ -83,7 +83,7 @@ print(results)
 
 For pattern based recognizers, it is possible to change the regex flags, either for
 one recognizer or for all.
-For one recognizer, use the `global_regex_flags` parameter 
+For one recognizer, use the `global_regex_flags` parameter
 in the `PatternRecognizer` constructor.
 For all recognizers, use the `global_regex_flags` parameter in the `RecognizerRegistry` constructor:
 
@@ -98,7 +98,6 @@ engine = AnalyzerEngine(registry=registry)
 engine.analyze(...)
 ```
 
-
 ### Creating a new `EntityRecognizer` in code
 
 To create a new recognizer via code:
@@ -219,7 +218,7 @@ Additional examples can be found in the [OpenAPI spec](../api-docs/api-docs.html
 ### Reading pattern recognizers from YAML
 
 Recognizers can be loaded from a YAML file, which allows users to add recognition logic without writing code.
-An example YAML file can be found [here](https://github.com/microsoft/presidio/blob/main/presidio-analyzer/conf/example_recognizers.yaml).
+An example YAML file can be found [here](https://github.com/microsoft/presidio/blob/main/presidio-analyzer/presidio_analyzer/conf/example_recognizers.yaml).
 
 Once the YAML file is created, it can be loaded into the `RecognizerRegistry` instance.
 

docs/analyzer/customizing_nlp_models.md

@@ -50,7 +50,7 @@ Configuration can be done in two ways:
     print(results_english)
     ```
 
-- **Via configuration**: Set up the models which should be used in the [default `conf` file](https://github.com/microsoft/presidio/blob/main/presidio-analyzer/conf/default.yaml).
+- **Via configuration**: Set up the models which should be used in the [default `conf` file](https://github.com/microsoft/presidio/blob/main/presidio-analyzer/presidio_analyzer/conf/default.yaml).
 
     An example Conf file:
 
@@ -86,7 +86,7 @@ Configuration can be done in two ways:
   - `low_confidence_score_multiplier`: A multiplier to apply to the score of entities with low confidence.
   - `low_score_entity_names`: A list of entity types to apply the low confidence score multiplier to.
 
-    The [default conf file](https://github.com/microsoft/presidio/blob/main/presidio-analyzer/conf/default.yaml) is read during the default initialization of the `AnalyzerEngine`. Alternatively, the path to a custom configuration file can be passed to the `NlpEngineProvider`:
+    The [default conf file](https://github.com/microsoft/presidio/blob/main/presidio-analyzer/presidio_analyzer/conf/default.yaml) is read during the default initialization of the `AnalyzerEngine`. Alternatively, the path to a custom configuration file can be passed to the `NlpEngineProvider`:
 
     ```python
     from presidio_analyzer import AnalyzerEngine, RecognizerRegistry

docs/analyzer/languages.md

@@ -70,8 +70,8 @@ Link to LANGUAGES_CONFIG_FILE=[languages-config.yml](https://github.com/microsof
 
 When packaging the code into a Docker container, NLP models are automatically installed.
 To define which models should be installed,
-update the [conf/default.yaml](https://github.com/microsoft/presidio/blob/main/presidio-analyzer/conf/default.yaml) file. This file is read during
+update the [conf/default.yaml](https://github.com/microsoft/presidio/blob/main/presidio-analyzer/presidio_analyzer/conf/default.yaml) file. This file is read during
 the `docker build` phase and the models defined in it are installed automatically.
 
-For `transformers` based models, the configuration [can be found here](https://github.com/microsoft/presidio/blob/main/presidio-analyzer/conf/transformers.yaml). 
+For `transformers` based models, the configuration [can be found here](https://github.com/microsoft/presidio/blob/main/presidio-analyzer/presidio_analyzer/conf/transformers.yaml). 
 A docker file supporting transformers models [can be found here](https://github.com/microsoft/presidio/blob/main/presidio-analyzer/Dockerfile.transformers).

docs/tutorial/08_no_code.md

@@ -7,7 +7,7 @@ No-code pattern recognizers can be helpful in two scenarios:
 
 Regular expression or deny-list based recognizers can be written in a YAML file, and added to the list of recognizers in Presidio.
 
-An example YAML file can be found [here](https://github.com/microsoft/presidio/blob/main/presidio-analyzer/conf/example_recognizers.yaml).
+An example YAML file can be found [here](https://github.com/microsoft/presidio/blob/main/presidio-analyzer/presidio_analyzer/conf/example_recognizers.yaml).
 
 For more information on the schema, see the `PatternRecognizer` definition on the [API Docs](https://microsoft.github.io/presidio/api-docs/api-docs.html#tag/Analyzer)).
 

e2e-tests/tests/test_analyzer.py

@@ -1,5 +1,4 @@
 import pytest
-
 from common.assertions import equal_json_strings
 from common.methods import analyze, analyzer_supported_entities
 

presidio-analyzer/Dockerfile

@@ -1,7 +1,7 @@
 FROM python:3.9-slim
 
 ARG NAME
-ARG NLP_CONF_FILE=conf/default.yaml
+ARG NLP_CONF_FILE=presidio_analyzer/conf/default.yaml
 ENV PIPENV_VENV_IN_PROJECT=1
 ENV PIP_NO_CACHE_DIR=1
 WORKDIR /usr/bin/${NAME}
@@ -16,4 +16,4 @@ RUN pipenv run python install_nlp_models.py --conf_file ${NLP_CONF_FILE}
 
 COPY . /usr/bin/${NAME}/
 EXPOSE ${PORT}
-CMD pipenv run python app.py --host 0.0.0.0
+CMD pipenv run python app.py --host 0.0.0.0

presidio-analyzer/Dockerfile.transformers

@@ -1,7 +1,7 @@
 FROM python:3.9-slim
 
 ARG NAME
-ARG NLP_CONF_FILE=conf/transformers.yaml
+ARG NLP_CONF_FILE=presidio_analyzer/conf/transformers.yaml
 ENV PIPENV_VENV_IN_PROJECT=1
 ENV PIP_NO_CACHE_DIR=1
 WORKDIR /usr/bin/${NAME}
@@ -19,4 +19,4 @@ RUN pipenv run python install_nlp_models.py --conf_file ${NLP_CONF_FILE}
 
 COPY . /usr/bin/${NAME}/
 EXPOSE ${PORT}
-CMD pipenv run python app.py --host 0.0.0.0
+CMD pipenv run python app.py --host 0.0.0.0

presidio-analyzer/Dockerfile.windows

@@ -1,6 +1,6 @@
 FROM python:3.9-windowsservercore
 
-ARG NLP_CONF_FILE=conf/default.yaml
+ARG NLP_CONF_FILE=presidio_analyzer/conf/default.yaml
 ENV PIPENV_VENV_IN_PROJECT=1
 ENV PIP_NO_CACHE_DIR=1
 WORKDIR /app

presidio-analyzer/install_nlp_models.py

@@ -102,7 +102,7 @@ def _install_transformers_spacy_models(model_name: Dict[str, str]) -> None:
     parser.add_argument(
         "--conf_file",
         required=False,
-        default="conf/default.yaml",
+        default="presidio_analyzer/conf/default.yaml",
         help="Location of nlp configuration yaml file. Default: conf/default.yaml",
     )
     args = parser.parse_args()

presidio-analyzer/conf/transformers.yaml → presidio-analyzer/presidio_analyzer/conf/transformers.yaml

@@ -1,44 +1,44 @@
-nlp_engine_name: transformers
-models:
-  -
-    lang_code: en
-    model_name:
-      spacy: en_core_web_sm
-      transformers: StanfordAIMI/stanford-deidentifier-base
-
-ner_model_configuration:
-  labels_to_ignore:
-  - O
-  aggregation_strategy: max # "simple", "first", "average", "max"
-  stride: 16                # If stride >= 0, process long texts in
-                            # overlapping windows of the model max
-                            # length. The value is the length of the
-                            # window overlap in transformer tokenizer
-                            # tokens, NOT the length of the stride.
-  alignment_mode: expand # "strict", "contract", "expand"
-  model_to_presidio_entity_mapping:
-    PER: PERSON
-    PERSON: PERSON
-    LOC: LOCATION
-    LOCATION: LOCATION
-    GPE: LOCATION
-    ORG: ORGANIZATION
-    ORGANIZATION: ORGANIZATION
-    NORP: NRP
-    AGE: AGE
-    ID: ID
-    EMAIL: EMAIL
-    PATIENT: PERSON
-    STAFF: PERSON
-    HOSP: ORGANIZATION
-    PATORG: ORGANIZATION
-    DATE: DATE_TIME
-    TIME: DATE_TIME
-    PHONE: PHONE_NUMBER
-    HCW: PERSON
-    HOSPITAL: ORGANIZATION
-    FACILITY: LOCATION
-
-  low_confidence_score_multiplier: 0.4
-  low_score_entity_names:
-  - ID
+nlp_engine_name: transformers
+models:
+  -
+    lang_code: en
+    model_name:
+      spacy: en_core_web_sm
+      transformers: StanfordAIMI/stanford-deidentifier-base
+
+ner_model_configuration:
+  labels_to_ignore:
+  - O
+  aggregation_strategy: max # "simple", "first", "average", "max"
+  stride: 16                # If stride >= 0, process long texts in
+                            # overlapping windows of the model max
+                            # length. The value is the length of the
+                            # window overlap in transformer tokenizer
+                            # tokens, NOT the length of the stride.
+  alignment_mode: expand # "strict", "contract", "expand"
+  model_to_presidio_entity_mapping:
+    PER: PERSON
+    PERSON: PERSON
+    LOC: LOCATION
+    LOCATION: LOCATION
+    GPE: LOCATION
+    ORG: ORGANIZATION
+    ORGANIZATION: ORGANIZATION
+    NORP: NRP
+    AGE: AGE
+    ID: ID
+    EMAIL: EMAIL
+    PATIENT: PERSON
+    STAFF: PERSON
+    HOSP: ORGANIZATION
+    PATORG: ORGANIZATION
+    DATE: DATE_TIME
+    TIME: DATE_TIME
+    PHONE: PHONE_NUMBER
+    HCW: PERSON
+    HOSPITAL: ORGANIZATION
+    FACILITY: LOCATION
+
+  low_confidence_score_multiplier: 0.4
+  low_score_entity_names:
+  - ID

presidio-analyzer/presidio_analyzer/nlp_engine/nlp_engine_provider.py

@@ -135,4 +135,4 @@ def _get_full_conf_path(
         default_conf_file: Union[Path, str] = "default.yaml"
     ) -> Path:
         """Return a Path to the default conf file."""
-        return Path(Path(__file__).parent.parent.parent, "conf", default_conf_file)
+        return Path(Path(__file__).parent.parent, "conf", default_conf_file)

presidio-analyzer/presidio_analyzer/recognizer_registry.py

@@ -287,7 +287,7 @@ def add_recognizers_from_yaml(self, yml_path: Union[str, Path]) -> None:
         Read YAML file and load recognizers into the recognizer registry.
 
         See example yaml file here:
-        https://github.com/microsoft/presidio/blob/main/presidio-analyzer/conf/example_recognizers.yaml
+        https://github.com/microsoft/presidio/blob/main/presidio-analyzer/presidio_analyzer/conf/example_recognizers.yaml
 
         :example:
         >>> yaml_file = "recognizers.yaml"