Skip to main content

Agent Control Models

Shared Pydantic models used by the server and SDKs. These models define the API contract for agents, controls, evaluation requests, and responses.

What this package provides

  • Strongly typed request/response schemas
  • Consistent validation and serialization across server and SDKs
  • A single source of truth for model changes

Usage

from agent_control_models import Agent, Step

agent = Agent(agent_name="support-bot", agent_description="Support agent")
step = Step(type="llm", name="chat", input="hello")

Control execution duration

Evaluation responses include an optional top-level execution_duration_ms on each ControlMatch in matches, non_matches, and errors. It measures that control's condition evaluation in wall-clock milliseconds, including the visited condition leaves, evaluator work, and time waiting for an evaluator concurrency slot. Control loading and request/response overhead are outside this measurement.

Completed evaluations include a nonnegative value, including evaluator failures. Precheck failures have no duration, and canceled evaluations produce no result. Older responses without the field remain valid. The Python SDK copies the value to ControlExecutionEvent.execution_duration_ms; the TypeScript SDK exposes it as executionDurationMs.

Tests

cd models
uv run pytest

Full guide: https://docs.agentcontrol.dev/components/models

Metadata

Release files for agent-control-models 8.14.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for agent-control-models 8.14.0
File Size Uploaded Provenance
agent_control_models-8.14.0.tar.gz 34.2 kB Without provenance Details

Built distribution (wheel)

Table of built distributions (wheels) for agent-control-models 8.14.0
File Interpreter ABI Platform
agent_control_models-8.14.0-py3-none-any.whl Python 3 none any Details

Total release size: 67.7 kB

Release files / agent_control_models-8.14.0.tar.gz

Download URL agent_control_models-8.14.0.tar.gz
Size 34.2 kB
Tags Source
SHA-256 checksum
How to use checksums
c0cf3fe08155eb15f586cfe9cd7ffb52aa6d8a8346059bdd45954cfc575d60d6
BLAKE2b-256 checksum
How to use checksums
d86c1ddca4a6522e3295d4edbb1107d0e822fd8b633b0677c1bc655c1411b07e
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/7.0.0 CPython/3.13.14

Release files / agent_control_models-8.14.0-py3-none-any.whl

Download URL agent_control_models-8.14.0-py3-none-any.whl
Size 33.4 kB
Tags Python 3
SHA-256 checksum
How to use checksums
e2937e5ea0a8afc1028c49309c04807735520500a2e3f6a13ce87cc947c68edf
BLAKE2b-256 checksum
How to use checksums
ecfd4e4e06ea95f0fc8d84003fe56e0b8c13f1f694f91fd6aa866d37fe51dce9
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/7.0.0 CPython/3.13.14

Security for agent-control-models 8.14.0

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

No provenance found

None of the files in this release were uploaded with provenance metadata.

A note on package security

PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.

Release history Release notifications | RSS feed

This release

8.14.0 This release

2 release files No provenance

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page