guardrails-ai-types
Offical Guardrails AI Types
Decision gist · record as of 2026-08-14
Yes, if you are using the guardrails-ai SDK to validate LLM outputs or create guarded chat completions. The package provides essential type definitions with minimal overhead (one pydantic dependency), active maintenance, and permissive licensing. Install it as part of your guardrails-ai setup for type safety and IDE support.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.10 or later (supports_current); designed as a types package for use with the guardrails-ai SDK client.
- Low friction install with a single runtime dependency on pydantic.
- Actively maintained with recent commits and releases within the past month.
License · maintenance · safety
permissive license (permissive) — MIT License permits free use, modification, and distribution with minimal restrictions—suitable for both open-source and commercial projects.
last release 2026-07-10 (35 days) · last repo commit 2026-07-10 · 2 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 122,775 downloads/mo, #11,934 on PyPI
Alternatives
Verify before relying
pip install guardrails-ai-types
from guardrails_ai.sdk import Guard, ValidationOutcome
# Use imported types in your guardrails client code
guard: Guard = await client.guards.retrieve(name="my-guard")
validation_outcome: ValidationOutcome = await client.guards.validate(name="my-guard", llm_output="Hello, world.")- Whether this package is intended for direct installation or primarily as a transitive dependency of guardrails-ai-sdk.
- What specific validation rules or guardrail types are included beyond the core Guard and ValidationOutcome classes shown in the excerpt.
What it is and what it does
guardrails-ai-types is a types package providing Pydantic-based data structures for the Guardrails AI REST client. It defines the core types—Guard, ValidationOutcome, and related structures—needed to interact with the guardrails-api service for validating LLM outputs and creating guarded chat completions. The package serves as the type layer for the guardrails-ai SDK, enabling type-safe Python code when working with remote guardrails services.
The package is actively maintained and has low installation friction, depending only on pydantic. It supports current Python versions (3.10+) and is distributed under the MIT License, making it freely usable in both open-source and commercial contexts.
Use it for
- Type-checking guardrails client code when validating LLM outputs against remote guard definitions.
- Building type-safe applications that create and manage guarded chat completions with streaming support.
- Defining validation outcomes and summaries when integrating LLM safety checks into production systems.
- Enabling IDE autocomplete and static analysis for guardrails-ai SDK method calls and responses.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you are using the guardrails-ai SDK to validate LLM outputs or create guarded chat completions.
The package provides essential type definitions with minimal overhead (one pydantic dependency), active maintenance, and permissive licensing. Install it as part of your guardrails-ai setup for type safety and IDE support.
Install
guardrails-ai-types on PyPI
Before you install
Low friction install with a single runtime dependency on pydantic. Actively maintained with recent commits and releases within the past month.
Requires Python 3.10 or later (supports_current); designed as a types package for use with the guardrails-ai SDK client.
License in practice
MIT License permits free use, modification, and distribution with minimal restrictions—suitable for both open-source and commercial projects.
Quickstart
pip install guardrails-ai-types
from guardrails_ai.sdk import Guard, ValidationOutcome
# Use imported types in your guardrails client code
guard: Guard = await client.guards.retrieve(name="my-guard")
validation_outcome: ValidationOutcome = await client.guards.validate(name="my-guard", llm_output="Hello, world.")Verify before relying
- Whether this package is intended for direct installation or primarily as a transitive dependency of guardrails-ai-sdk.
- What specific validation rules or guardrail types are included beyond the core Guard and ValidationOutcome classes shown in the excerpt.
Package facts
| License | permissive license permissive |
| Python support | Supports the current Python release <4,>=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 1 packagepydantic |
| Maintenance | Actively maintained 35 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 122,775 / month, #11,934 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
Evidence: guardrails_ai_types-0.5.0-py3-none-any.whl
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See also guardrails-ai · guardrails-hub-types · nemoguardrails · openresponses-types · datarobot-moderations · openai-guardrails · flake8-typing-imports · pydantic-ai-shields · k8 · llm-guard