Tuning Engines

Tuning Engines exposes an OpenAI-compatible endpoint for teams that want Agno agents to run through a governed AI control plane. Agno owns the agent behavior, tools, memory, and orchestration, while Tuning Engines centralizes model access, policy checks, audit logs, traces, and usage/cost reporting.

Authentication

Create a Tuning Engines inference key and enable the model alias you want the agent to use.

export TUNING_ENGINES_API_KEY=sk-te-your-inference-key
export TUNING_ENGINES_MODEL=your-model-alias
# Optional, only when using a custom host:
export TUNING_ENGINES_BASE_URL=https://api.tuningengines.com/v1

setx TUNING_ENGINES_API_KEY sk-te-your-inference-key
setx TUNING_ENGINES_MODEL your-model-alias
:: Optional, only when using a custom host:
setx TUNING_ENGINES_BASE_URL https://api.tuningengines.com/v1

Example

Install the openai package:

uv pip install -U agno openai

Use Agno’s TuningEngines model provider:

from os import getenv

from agno.agent import Agent
from agno.models.tuning_engines import TuningEngines

agent = Agent(
    model=TuningEngines(
        id=getenv("TUNING_ENGINES_MODEL", "your-model-alias"),
    ),
    markdown=True,
)

agent.print_response("Share a short checklist for running production AI agents.", stream=True)

Params

Parameter	Type	Description	Default
`id`	`str`	Model alias enabled in Tuning Engines	`"gpt-4o"`
`api_key`	`Optional[str]`	Tuning Engines inference key, read from `TUNING_ENGINES_API_KEY`	`None`
`base_url`	`str`	Tuning Engines OpenAI-compatible API endpoint	`TUNING_ENGINES_BASE_URL` or `"https://api.tuningengines.com/v1"`

TuningEngines extends OpenAILike, so it supports the same OpenAI-compatible model parameters documented in OpenAI Like.

View a runnable example here.

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Tuning Engines

Authentication

Example

Params

​Authentication

​Example

​Params

Authentication

Example

Params