> For the complete documentation index, see [llms.txt](https://docs.valohai.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.valohai.com/readme/philosophy/yaml-over-sdk.md).

# YAML Over SDK

Valohai is built on a simple principle: **your ML code should not be entangled with your MLOps platform**.

Many tools ask you to decorate functions, subclass Tracker objects, or wrap training loops in platform-specific APIs. We don't.

## Why We Avoid SDK Integration

Valohai treats `valohai.yaml` as the single source of truth for your ML workflows. This architectural choice brings immediate benefits:

* **No vendor lock-in** — Your ML code stays agnostic, portable, and unmodified
* **Zero hidden orchestration** — What you see in YAML is what runs
* **No tight coupling** — Platform configuration lives separately from business logic

## Benefits of YAML-First Architecture

### Portability Without Pain

Delete Valohai tomorrow and your code still runs. No refactoring, no API removal, no broken imports.

### Git-Native Configuration

Your entire pipeline configuration lives in version control:

* Track changes with standard Git workflows
* Review pipelines in pull requests
* Roll back configurations instantly

### Team-Friendly Reviews

Platform engineers can audit pipelines without understanding your ML framework. Data scientists can focus on algorithms without learning orchestration APIs.

## The Philosophy in Practice

When you run an execution, Valohai:

1. Reads your `valohai.yaml` configuration
2. Provisions the compute environment
3. Injects parameters command line arguments or through JSON/YAML files
4. Runs your code exactly as written

Your training script doesn't need to know it's running on Valohai. That's the point.


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation by asking a question.

Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters:

```
GET https://docs.valohai.com/readme/philosophy/yaml-over-sdk.md?ask=<question>&goal=<user_goal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case.

The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.