nvidia-nat-atif
Subpackage for ATIF schema models in NVIDIA NeMo Agent Toolkit
Decision gist · record as of 2026-08-14
Yes, if you are building or evaluating agents within the NVIDIA NeMo ecosystem and need standardized schema models for agent interactions and evaluation. The low install friction, active maintenance, permissive license, and zero known vulnerabilities make it a safe choice. If you are not working with NeMo agents or do not need structured ATIF schemas, it is not applicable.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.11 or later (supports 3.11, 3.12, 3.13)
- Low install friction with a single runtime dependency on pydantic.
- The package is actively maintained with recent commits and sits within the top 15000 PyPI packages by download volume.
License · maintenance · safety
Apache-2.0 (permissive) — Licensed under Apache-2.0 (permissive), allowing free use, modification, and distribution with minimal restrictions—suitable for both open and commercial projects.
last release 2026-06-17 (58 days) · last repo commit 2026-08-12 · 2,576 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 173,911 downloads/mo, #10,295 on PyPI
Alternatives
Verify before relying
pip install nvidia-nat-atif
from nvidia_nat_atif import <schema_model>
import pydantic
# Use pydantic-validated ATIF schema models for agent data- What specific ATIF schema models are included and their intended use cases within agent evaluation
- Whether this subpackage can be used independently or requires other NeMo Agent Toolkit components
- Performance characteristics or scalability limits for large-scale agent evaluation workflows
What it is and what it does
This is a subpackage of the NVIDIA NeMo Agent Toolkit that provides ATIF schema models for structuring and validating agent data. It leverages pydantic for data validation, enabling developers to work with standardized, type-safe representations of agent interactions and evaluation metrics.
The package targets Python 3.11–3.13 and is maintained as part of an active, well-starred GitHub repository. It is intended for teams building or evaluating AI agents within the NeMo ecosystem, where consistent schema enforcement across agent interactions and evaluation pipelines is needed.
Use it for
- Validate and structure agent interaction logs using standardized ATIF schemas within NeMo Agent Toolkit workflows
- Build evaluation pipelines that consume and process agent behavior data in a type-safe, schema-compliant format
- Integrate agent evaluation metrics and results into larger NeMo-based AI systems with consistent data models
- Develop custom agent evaluation tools that rely on pydantic-validated ATIF data structures
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you are building or evaluating agents within the NVIDIA NeMo ecosystem and need standardized schema models for agent interactions and evaluation.
The low install friction, active maintenance, permissive license, and zero known vulnerabilities make it a safe choice. If you are not working with NeMo agents or do not need structured ATIF schemas, it is not applicable.
Install
nvidia-nat-atif on PyPI
Before you install
Low install friction with a single runtime dependency on pydantic. The package is actively maintained with recent commits and sits within the top 15000 PyPI packages by download volume.
Requires Python 3.11 or later (supports 3.11, 3.12, 3.13)
License in practice
Licensed under Apache-2.0 (permissive), allowing free use, modification, and distribution with minimal restrictions—suitable for both open and commercial projects.
Quickstart
pip install nvidia-nat-atif
from nvidia_nat_atif import <schema_model>
import pydantic
# Use pydantic-validated ATIF schema models for agent dataVerify before relying
- What specific ATIF schema models are included and their intended use cases within agent evaluation
- Whether this subpackage can be used independently or requires other NeMo Agent Toolkit components
- Performance characteristics or scalability limits for large-scale agent evaluation workflows
Package facts
| License | Apache-2.0 permissive |
| Python support | Supports the current Python release <3.14,>=3.11 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 1 packagepydantic |
| Maintenance | Actively maintained 58 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 173,911 / month, #10,295 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Programming Language :: PythonProgramming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13 |
Evidence: nvidia_nat_atif-1.8.0-py3-none-any.whl
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See also nvidia-nat-eval · nvidia-nat-mcp · nvidia-nat-opentelemetry · nvidia-nat-core · nvidia-nat-langchain · nv-ingest-client · nvidia-nat · nemo-relay · data-designer-config · aiperf