Make Presidio a required dependency

README.md

@@ -14,14 +14,9 @@ For full details, advanced usage, and API reference, see here: [OpenAI Guardrail
    - Use the [Guardrails web UI](https://guardrails.openai.com/) to create a JSON configuration file describing which guardrails to apply and how to configure them.
    - The wizard outputs a file like `guardrail_specs.json`.
 
-2. **Install dependencies**
-   - **Install from this repo:**
+2. **Install**
      ```bash
-     pip install -e '.[presidio]'
-     ```
-   - **Eventually this will be:**
-     ```bash
-     pip install openai-guardrails
+     pip install guardrails
      ```
 
 3. **Wrap your OpenAI client with Guardrails**

docs/quickstart.md

@@ -8,11 +8,6 @@ Get started with Guardrails in minutes. Guardrails provides drop-in replacements
 pip install guardrails
 ```
 
-For PII detection (optional):
-```bash
-pip install guardrails[presidio]
-```
-
 ## Set API Key
 
 ```bash

examples/basic/hello_world.py

@@ -10,13 +10,18 @@
 
 console = Console()
 
-# Pipeline configuration with input guardrails
+# Pipeline configuration with pre_flight and input guardrails
 PIPELINE_CONFIG = {
     "version": 1,
-    "input": {
+    "pre_flight": {
         "version": 1,
         "guardrails": [
             {"name": "Contains PII", "config": {"entities": ["US_SSN", "PHONE_NUMBER", "EMAIL_ADDRESS"]}},
+        ],
+    },
+    "input": {
+        "version": 1,
+        "guardrails": [
             {
                 "name": "Custom Prompt Check",
                 "config": {

pyproject.toml

@@ -6,7 +6,13 @@ readme = "README.md"
 requires-python = ">=3.11"
 license = "MIT"
 authors = [{ name = "OpenAI", email = "[email protected]" }]
-dependencies = ["openai>=1.75.0", "pydantic>=2.11.3", "openai-agents>=0.3.3"]
+dependencies = [
+    "openai>=1.75.0",
+    "pydantic>=2.11.3",
+    "openai-agents>=0.3.3",
+    "pip>=25.0.1",
+    "presidio-analyzer>=2.2.358",
+]
 classifiers = [
   "Typing :: Typed",
   "Intended Audience :: Developers",
@@ -25,10 +31,6 @@ examples = [
     "pillow>=11.2.1",
     "rich>=14.0.0",
 ]
-presidio = [
-    "pip>=25.0.1",  # Required to load spaCy dependency for presidio-analyzer
-    "presidio-analyzer>=2.2.358",
-]
 benchmark = [
     "numpy>=1.24.0",
     "scikit-learn>=1.3.0",

requirements.txt

@@ -5,45 +5,232 @@ annotated-types==0.7.0
 anyio==4.9.0
     # via
     #   httpx
+    #   mcp
     #   openai
+    #   sse-starlette
+    #   starlette
+attrs==25.3.0
+    # via
+    #   jsonschema
+    #   referencing
+blis==1.3.0
+    # via thinc
+catalogue==2.0.10
+    # via
+    #   spacy
+    #   srsly
+    #   thinc
 certifi==2025.4.26
     # via
     #   httpcore
     #   httpx
+    #   requests
+charset-normalizer==3.4.3
+    # via requests
+click==8.3.0
+    # via
+    #   typer
+    #   uvicorn
+cloudpathlib==0.22.0
+    # via weasel
+colorama==0.4.6
+    # via griffe
+confection==0.1.5
+    # via
+    #   thinc
+    #   weasel
+cymem==2.0.11
+    # via
+    #   preshed
+    #   spacy
+    #   thinc
 distro==1.9.0
     # via openai
+filelock==3.19.1
+    # via tldextract
+griffe==1.14.0
+    # via openai-agents
 h11==0.16.0
-    # via httpcore
+    # via
+    #   httpcore
+    #   uvicorn
 httpcore==1.0.9
     # via httpx
 httpx==0.28.1
-    # via openai
+    # via
+    #   mcp
+    #   openai
+httpx-sse==0.4.1
+    # via mcp
 idna==3.10
     # via
     #   anyio
     #   httpx
+    #   requests
+    #   tldextract
+jinja2==3.1.6
+    # via spacy
 jiter==0.9.0
     # via openai
-openai==1.77.0
+jsonschema==4.25.1
+    # via mcp
+jsonschema-specifications==2025.9.1
+    # via jsonschema
+langcodes==3.5.0
+    # via spacy
+language-data==1.3.0
+    # via langcodes
+marisa-trie==1.3.1
+    # via language-data
+markdown-it-py==4.0.0
+    # via rich
+markupsafe==3.0.3
+    # via jinja2
+mcp==1.16.0
+    # via openai-agents
+mdurl==0.1.2
+    # via markdown-it-py
+murmurhash==1.0.13
+    # via
+    #   preshed
+    #   spacy
+    #   thinc
+numpy==2.3.3
+    # via
+    #   blis
+    #   spacy
+    #   thinc
+openai==1.109.1
+    # via
+    #   guardrails (pyproject.toml)
+    #   openai-agents
+openai-agents==0.3.3
+    # via guardrails (pyproject.toml)
+packaging==25.0
+    # via
+    #   spacy
+    #   thinc
+    #   weasel
+phonenumbers==9.0.15
+    # via presidio-analyzer
+pip==25.2
+    # via guardrails (pyproject.toml)
+preshed==3.0.10
+    # via
+    #   spacy
+    #   thinc
+presidio-analyzer==2.2.360
     # via guardrails (pyproject.toml)
 pydantic==2.11.4
     # via
     #   guardrails (pyproject.toml)
+    #   confection
+    #   mcp
     #   openai
+    #   openai-agents
+    #   pydantic-settings
+    #   spacy
+    #   thinc
+    #   weasel
 pydantic-core==2.33.2
     # via pydantic
+pydantic-settings==2.11.0
+    # via mcp
+pygments==2.19.2
+    # via rich
+python-dotenv==1.1.1
+    # via pydantic-settings
+python-multipart==0.0.20
+    # via mcp
+pyyaml==6.0.3
+    # via presidio-analyzer
+referencing==0.36.2
+    # via
+    #   jsonschema
+    #   jsonschema-specifications
+regex==2025.9.18
+    # via presidio-analyzer
+requests==2.32.5
+    # via
+    #   openai-agents
+    #   requests-file
+    #   spacy
+    #   tldextract
+    #   weasel
+requests-file==2.1.0
+    # via tldextract
+rich==14.1.0
+    # via typer
+rpds-py==0.27.1
+    # via
+    #   jsonschema
+    #   referencing
+setuptools==80.9.0
+    # via
+    #   spacy
+    #   thinc
+shellingham==1.5.4
+    # via typer
+smart-open==7.3.1
+    # via weasel
 sniffio==1.3.1
     # via
     #   anyio
     #   openai
+spacy==3.8.7
+    # via presidio-analyzer
+spacy-legacy==3.0.12
+    # via spacy
+spacy-loggers==1.0.5
+    # via spacy
+srsly==2.5.1
+    # via
+    #   confection
+    #   spacy
+    #   thinc
+    #   weasel
+sse-starlette==3.0.2
+    # via mcp
+starlette==0.48.0
+    # via mcp
+thinc==8.3.6
+    # via spacy
+tldextract==5.3.0
+    # via presidio-analyzer
 tqdm==4.67.1
-    # via openai
+    # via
+    #   openai
+    #   spacy
+typer==0.19.2
+    # via
+    #   spacy
+    #   weasel
+types-requests==2.32.4.20250913
+    # via openai-agents
 typing-extensions==4.13.2
     # via
-    #   anyio
     #   openai
+    #   openai-agents
     #   pydantic
     #   pydantic-core
+    #   typer
     #   typing-inspection
 typing-inspection==0.4.0
-    # via pydantic
+    # via
+    #   pydantic
+    #   pydantic-settings
+urllib3==2.5.0
+    # via
+    #   requests
+    #   types-requests
+uvicorn==0.37.0
+    # via mcp
+wasabi==1.1.3
+    # via
+    #   spacy
+    #   thinc
+    #   weasel
+weasel==0.4.1
+    # via spacy
+wrapt==1.17.3
+    # via smart-open

src/guardrails/checks/text/pii.py

@@ -77,8 +77,10 @@
 from collections.abc import Sequence
 from dataclasses import dataclass
 from enum import Enum
-from typing import TYPE_CHECKING, Any, Final
+from typing import Any, Final
 
+from presidio_analyzer import AnalyzerEngine, RecognizerResult
+from presidio_analyzer.nlp_engine import NlpEngineProvider
 from pydantic import BaseModel, ConfigDict, Field
 
 from guardrails.registry import default_spec_registry
@@ -89,27 +91,14 @@
 
 logger = logging.getLogger(__name__)
 
-if TYPE_CHECKING:
-    from presidio_analyzer import AnalyzerEngine, AnalyzerResult
-
 
 @functools.lru_cache(maxsize=1)
 def _get_analyzer_engine() -> AnalyzerEngine:
     """Return a cached, configured Presidio AnalyzerEngine instance.
 
     Returns:
         AnalyzerEngine: Initialized Presidio analyzer engine.
-
-    Raises:
-        ImportError: If required Presidio packages are not installed.
     """
-    try:
-        from presidio_analyzer import AnalyzerEngine
-        from presidio_analyzer.nlp_engine import NlpEngineProvider
-    except ImportError as e:
-        logger.error("Failed to import Presidio analyzer: %s", e)
-        raise ImportError("Presidio analyzer package is required") from e
-
     # Define a smaller NLP configuration
     sm_nlp_config: Final[dict[str, Any]] = {
         "nlp_engine_name": "spacy",
@@ -226,11 +215,11 @@ class PiiDetectionResult:
 
     Attributes:
         mapping (dict[str, list[str]]): Mapping from entity type to list of detected strings.
-        analyzer_results (Sequence[AnalyzerResult]): Raw analyzer results for position information.
+        analyzer_results (Sequence[RecognizerResult]): Raw analyzer results for position information.
     """
 
     mapping: dict[str, list[str]]
-    analyzer_results: Sequence[AnalyzerResult]
+    analyzer_results: Sequence[RecognizerResult]
 
     def to_dict(self) -> dict[str, list[str]]:
         """Convert the result to a dictionary.