docs: sync Core Integrations API reference (presidio) on Docusaurus (#11187)

Co-authored-by: sjrl <10526848+sjrl@users.noreply.github.com>

Author: HaystackBot

docs-website/reference/integrations-api/presidio.md

@@ -36,28 +36,49 @@ print(result["documents"][0].meta["entities"])
 #  {"entity_type": "EMAIL_ADDRESS", "start": 17, "end": 34, "score": 1.0}]
 ```
 
+#### SPACY_DEFAULT_MODELS
+
+```python
+SPACY_DEFAULT_MODELS: dict[str, str] = _SPACY_DEFAULT_MODELS
+```
+
+Mapping from ISO 639-1 language code to the largest available spaCy model for that language.
+
+Used to automatically select an NLP model when `models` is not specified.
+See [spaCy documentation](https://spacy.io/models) for the full list of available spaCy models.
+
 #### __init__
 
 ```python
 __init__(
     *,
     language: str = "en",
     entities: list[str] | None = None,
-    score_threshold: float = 0.35
+    score_threshold: float = 0.35,
+    models: list[dict[str, str]] | None = None
 ) -> None
 ```
 
 Initializes the PresidioEntityExtractor.
 
 **Parameters:**
 
-- **language** (<code>str</code>) – Language code for PII detection. Defaults to `"en"`.
+- **language** (<code>str</code>) – ISO 639-1 language code for PII detection. Defaults to `"en"`.
+  For languages in the built-in mapping (e.g. `"de"`, `"fr"`, `"es"`), the appropriate
+  spaCy model is loaded automatically at warm-up time — no need to set `models`.
+  For unsupported languages, use the `models` parameter to configure a custom model.
   See [Presidio supported languages](https://microsoft.github.io/presidio/analyzer/languages/).
 - **entities** (<code>list\[str\] | None</code>) – List of PII entity types to detect (e.g. `["PERSON", "EMAIL_ADDRESS"]`).
   If `None`, all supported entity types are detected.
   See [Presidio supported entities](https://microsoft.github.io/presidio/supported_entities/).
 - **score_threshold** (<code>float</code>) – Minimum confidence score (0-1) for a detected entity to be included. Defaults to `0.35`.
   See [Presidio analyzer documentation](https://microsoft.github.io/presidio/analyzer/).
+- **models** (<code>list\[dict\[str, str\]\] | None</code>) – Advanced override: list of spaCy model configurations.
+  Each entry must contain `"lang_code"` and `"model_name"` keys,
+  e.g. `[{"lang_code": "fr", "model_name": "fr_core_news_md"}]`.
+  Use this only when you need a specific model variant or a language not covered by the
+  built-in mapping. If `None`, the model is selected automatically from `SPACY_DEFAULT_MODELS`
+  based on `language`.
 
 #### warm_up
 
@@ -114,28 +135,49 @@ print(result["documents"][0].content)
 # My name is <PERSON> and my email is <EMAIL_ADDRESS>
 ```
 
+#### SPACY_DEFAULT_MODELS
+
+```python
+SPACY_DEFAULT_MODELS: dict[str, str] = _SPACY_DEFAULT_MODELS
+```
+
+Mapping from ISO 639-1 language code to the largest available spaCy model for that language.
+
+Used to automatically select an NLP model when `models` is not specified.
+See [spaCy documentation](https://spacy.io/models) for the full list of available spaCy models.
+
 #### __init__
 
 ```python
 __init__(
     *,
     language: str = "en",
     entities: list[str] | None = None,
-    score_threshold: float = 0.35
+    score_threshold: float = 0.35,
+    models: list[dict[str, str]] | None = None
 ) -> None
 ```
 
 Initializes the PresidioDocumentCleaner.
 
 **Parameters:**
 
-- **language** (<code>str</code>) – Language code for PII detection. Defaults to `"en"`.
+- **language** (<code>str</code>) – ISO 639-1 language code for PII detection. Defaults to `"en"`.
+  For languages in the built-in mapping (e.g. `"de"`, `"fr"`, `"es"`), the appropriate
+  spaCy model is loaded automatically at warm-up time — no need to set `models`.
+  For unsupported languages, use the `models` parameter to configure a custom model.
   See [Presidio supported languages](https://microsoft.github.io/presidio/analyzer/languages/).
 - **entities** (<code>list\[str\] | None</code>) – List of PII entity types to detect and anonymize (e.g. `["PERSON", "EMAIL_ADDRESS"]`).
   If `None`, all supported entity types are used.
   See [Presidio supported entities](https://microsoft.github.io/presidio/supported_entities/).
 - **score_threshold** (<code>float</code>) – Minimum confidence score (0-1) for a detected entity to be anonymized. Defaults to `0.35`.
   See [Presidio analyzer documentation](https://microsoft.github.io/presidio/analyzer/).
+- **models** (<code>list\[dict\[str, str\]\] | None</code>) – Advanced override: list of spaCy model configurations.
+  Each entry must contain `"lang_code"` and `"model_name"` keys,
+  e.g. `[{"lang_code": "fr", "model_name": "fr_core_news_md"}]`.
+  Use this only when you need a specific model variant or a language not covered by the
+  built-in mapping. If `None`, the model is selected automatically from `SPACY_DEFAULT_MODELS`
+  based on `language`.
 
 #### warm_up
 
@@ -188,28 +230,49 @@ print(result["texts"][0])
 # Hi, I am <PERSON>, call me at <PHONE_NUMBER>
 ```
 
+#### SPACY_DEFAULT_MODELS
+
+```python
+SPACY_DEFAULT_MODELS: dict[str, str] = _SPACY_DEFAULT_MODELS
+```
+
+Mapping from ISO 639-1 language code to the largest available spaCy model for that language.
+
+Used to automatically select an NLP model when `models` is not specified.
+See [spaCy documentation](https://spacy.io/models) for the full list of available spaCy models.
+
 #### __init__
 
 ```python
 __init__(
     *,
     language: str = "en",
     entities: list[str] | None = None,
-    score_threshold: float = 0.35
+    score_threshold: float = 0.35,
+    models: list[dict[str, str]] | None = None
 ) -> None
 ```
 
 Initializes the PresidioTextCleaner.
 
 **Parameters:**
 
-- **language** (<code>str</code>) – Language code for PII detection. Defaults to `"en"`.
+- **language** (<code>str</code>) – ISO 639-1 language code for PII detection. Defaults to `"en"`.
+  For languages in the built-in mapping (e.g. `"de"`, `"fr"`, `"es"`), the appropriate
+  spaCy model is loaded automatically at warm-up time — no need to set `models`.
+  For unsupported languages, use the `models` parameter to configure a custom model.
   See [Presidio supported languages](https://microsoft.github.io/presidio/analyzer/languages/).
 - **entities** (<code>list\[str\] | None</code>) – List of PII entity types to detect and anonymize (e.g. `["PERSON", "PHONE_NUMBER"]`).
   If `None`, all supported entity types are used.
   See [Presidio supported entities](https://microsoft.github.io/presidio/supported_entities/).
 - **score_threshold** (<code>float</code>) – Minimum confidence score (0-1) for a detected entity to be anonymized. Defaults to `0.35`.
   See [Presidio analyzer documentation](https://microsoft.github.io/presidio/analyzer/).
+- **models** (<code>list\[dict\[str, str\]\] | None</code>) – Advanced override: list of spaCy model configurations.
+  Each entry must contain `"lang_code"` and `"model_name"` keys,
+  e.g. `[{"lang_code": "fr", "model_name": "fr_core_news_md"}]`.
+  Use this only when you need a specific model variant or a language not covered by the
+  built-in mapping. If `None`, the model is selected automatically from `SPACY_DEFAULT_MODELS`
+  based on `language`.
 
 #### warm_up
 

docs-website/reference_versioned_docs/version-2.18/integrations-api/presidio.md

@@ -36,28 +36,49 @@ print(result["documents"][0].meta["entities"])
 #  {"entity_type": "EMAIL_ADDRESS", "start": 17, "end": 34, "score": 1.0}]
 ```
 
+#### SPACY_DEFAULT_MODELS
+
+```python
+SPACY_DEFAULT_MODELS: dict[str, str] = _SPACY_DEFAULT_MODELS
+```
+
+Mapping from ISO 639-1 language code to the largest available spaCy model for that language.
+
+Used to automatically select an NLP model when `models` is not specified.
+See [spaCy documentation](https://spacy.io/models) for the full list of available spaCy models.
+
 #### __init__
 
 ```python
 __init__(
     *,
     language: str = "en",
     entities: list[str] | None = None,
-    score_threshold: float = 0.35
+    score_threshold: float = 0.35,
+    models: list[dict[str, str]] | None = None
 ) -> None
 ```
 
 Initializes the PresidioEntityExtractor.
 
 **Parameters:**
 
-- **language** (<code>str</code>) – Language code for PII detection. Defaults to `"en"`.
+- **language** (<code>str</code>) – ISO 639-1 language code for PII detection. Defaults to `"en"`.
+  For languages in the built-in mapping (e.g. `"de"`, `"fr"`, `"es"`), the appropriate
+  spaCy model is loaded automatically at warm-up time — no need to set `models`.
+  For unsupported languages, use the `models` parameter to configure a custom model.
   See [Presidio supported languages](https://microsoft.github.io/presidio/analyzer/languages/).
 - **entities** (<code>list\[str\] | None</code>) – List of PII entity types to detect (e.g. `["PERSON", "EMAIL_ADDRESS"]`).
   If `None`, all supported entity types are detected.
   See [Presidio supported entities](https://microsoft.github.io/presidio/supported_entities/).
 - **score_threshold** (<code>float</code>) – Minimum confidence score (0-1) for a detected entity to be included. Defaults to `0.35`.
   See [Presidio analyzer documentation](https://microsoft.github.io/presidio/analyzer/).
+- **models** (<code>list\[dict\[str, str\]\] | None</code>) – Advanced override: list of spaCy model configurations.
+  Each entry must contain `"lang_code"` and `"model_name"` keys,
+  e.g. `[{"lang_code": "fr", "model_name": "fr_core_news_md"}]`.
+  Use this only when you need a specific model variant or a language not covered by the
+  built-in mapping. If `None`, the model is selected automatically from `SPACY_DEFAULT_MODELS`
+  based on `language`.
 
 #### warm_up
 
@@ -114,28 +135,49 @@ print(result["documents"][0].content)
 # My name is <PERSON> and my email is <EMAIL_ADDRESS>
 ```
 
+#### SPACY_DEFAULT_MODELS
+
+```python
+SPACY_DEFAULT_MODELS: dict[str, str] = _SPACY_DEFAULT_MODELS
+```
+
+Mapping from ISO 639-1 language code to the largest available spaCy model for that language.
+
+Used to automatically select an NLP model when `models` is not specified.
+See [spaCy documentation](https://spacy.io/models) for the full list of available spaCy models.
+
 #### __init__
 
 ```python
 __init__(
     *,
     language: str = "en",
     entities: list[str] | None = None,
-    score_threshold: float = 0.35
+    score_threshold: float = 0.35,
+    models: list[dict[str, str]] | None = None
 ) -> None
 ```
 
 Initializes the PresidioDocumentCleaner.
 
 **Parameters:**
 
-- **language** (<code>str</code>) – Language code for PII detection. Defaults to `"en"`.
+- **language** (<code>str</code>) – ISO 639-1 language code for PII detection. Defaults to `"en"`.
+  For languages in the built-in mapping (e.g. `"de"`, `"fr"`, `"es"`), the appropriate
+  spaCy model is loaded automatically at warm-up time — no need to set `models`.
+  For unsupported languages, use the `models` parameter to configure a custom model.
   See [Presidio supported languages](https://microsoft.github.io/presidio/analyzer/languages/).
 - **entities** (<code>list\[str\] | None</code>) – List of PII entity types to detect and anonymize (e.g. `["PERSON", "EMAIL_ADDRESS"]`).
   If `None`, all supported entity types are used.
   See [Presidio supported entities](https://microsoft.github.io/presidio/supported_entities/).
 - **score_threshold** (<code>float</code>) – Minimum confidence score (0-1) for a detected entity to be anonymized. Defaults to `0.35`.
   See [Presidio analyzer documentation](https://microsoft.github.io/presidio/analyzer/).
+- **models** (<code>list\[dict\[str, str\]\] | None</code>) – Advanced override: list of spaCy model configurations.
+  Each entry must contain `"lang_code"` and `"model_name"` keys,
+  e.g. `[{"lang_code": "fr", "model_name": "fr_core_news_md"}]`.
+  Use this only when you need a specific model variant or a language not covered by the
+  built-in mapping. If `None`, the model is selected automatically from `SPACY_DEFAULT_MODELS`
+  based on `language`.
 
 #### warm_up
 
@@ -188,28 +230,49 @@ print(result["texts"][0])
 # Hi, I am <PERSON>, call me at <PHONE_NUMBER>
 ```
 
+#### SPACY_DEFAULT_MODELS
+
+```python
+SPACY_DEFAULT_MODELS: dict[str, str] = _SPACY_DEFAULT_MODELS
+```
+
+Mapping from ISO 639-1 language code to the largest available spaCy model for that language.
+
+Used to automatically select an NLP model when `models` is not specified.
+See [spaCy documentation](https://spacy.io/models) for the full list of available spaCy models.
+
 #### __init__
 
 ```python
 __init__(
     *,
     language: str = "en",
     entities: list[str] | None = None,
-    score_threshold: float = 0.35
+    score_threshold: float = 0.35,
+    models: list[dict[str, str]] | None = None
 ) -> None
 ```
 
 Initializes the PresidioTextCleaner.
 
 **Parameters:**
 
-- **language** (<code>str</code>) – Language code for PII detection. Defaults to `"en"`.
+- **language** (<code>str</code>) – ISO 639-1 language code for PII detection. Defaults to `"en"`.
+  For languages in the built-in mapping (e.g. `"de"`, `"fr"`, `"es"`), the appropriate
+  spaCy model is loaded automatically at warm-up time — no need to set `models`.
+  For unsupported languages, use the `models` parameter to configure a custom model.
   See [Presidio supported languages](https://microsoft.github.io/presidio/analyzer/languages/).
 - **entities** (<code>list\[str\] | None</code>) – List of PII entity types to detect and anonymize (e.g. `["PERSON", "PHONE_NUMBER"]`).
   If `None`, all supported entity types are used.
   See [Presidio supported entities](https://microsoft.github.io/presidio/supported_entities/).
 - **score_threshold** (<code>float</code>) – Minimum confidence score (0-1) for a detected entity to be anonymized. Defaults to `0.35`.
   See [Presidio analyzer documentation](https://microsoft.github.io/presidio/analyzer/).
+- **models** (<code>list\[dict\[str, str\]\] | None</code>) – Advanced override: list of spaCy model configurations.
+  Each entry must contain `"lang_code"` and `"model_name"` keys,
+  e.g. `[{"lang_code": "fr", "model_name": "fr_core_news_md"}]`.
+  Use this only when you need a specific model variant or a language not covered by the
+  built-in mapping. If `None`, the model is selected automatically from `SPACY_DEFAULT_MODELS`
+  based on `language`.
 
 #### warm_up