> ## Documentation Index
> Fetch the complete documentation index at: https://sdk.observability.getonex.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Getting Started

This guide walks you through installing the OneX Observability SDK, enabling
instrumentation for a model, and validating that signals reach your collector.

## Prerequisites

* Python 3.8+
* `pip` for installing packages
* Access to the OneX ingestion endpoint (or a Test environment)

## Installation

```bash theme={"dark"}
pip install onex-sdk[pytorch]
```

Extras are available if you use TensorFlow or JAX:

```bash theme={"dark"}
pip install onex-sdk[tensorflow]
pip install onex-sdk[jax]
pip install onex-sdk[all]  # every framework
```

> **Note**: Always review the package metadata on [PyPI](https://pypi.org/project/onex-sdk)
> to confirm the latest published version and release notes.

## Minimal instrumentation

```python theme={"dark"}
from onex import OneXMonitor

monitor = OneXMonitor(
    api_key="your-api-key",  # Fetch from https://dashboard.observability.getonex.ai
    endpoint="onex-ingestion-endpoint",  # See "Environment tagging" below
    config={
        "hidden_state_sample_tokens": 8,
        "capture_full_hidden_state": False,
    },
    # Optional: sample_rate=0.1 for 10% of requests; max_requests_per_minute=120 to cap throughput
)

model = monitor.watch(model)
```

Call your model as usual; the SDK will auto-detect the framework, attach instrumentation,
and stream signals asynchronously.

## Environment tagging

The OneX Observability platform supports multiple environments (e.g. sandbox,
development, production). Logs and signals are tagged and stored per
environment, and which environment receives your data depends on the
`endpoint` you pass to `OneXMonitor`.

Each environment has its own ingestion endpoint in the [OneX Observability
Dashboard](https://dashboard.observability.getonex.ai). Use the endpoint
for the environment where you want your logs to appear for example, use the
development endpoint when running locally, and the production endpoint in
production. Signals posted to a given endpoint are associated with that
environment in the platform.

## Verifying signals

From the platform perspective (OneX Observability Dashboard at
[https://dashboard.observability.getonex.ai](https://dashboard.observability.getonex.ai)):

1. Run a forward pass through your instrumented model so the SDK sends signals.
2. Confirm the API host for your environment receives traffic. The host is
   determined by the `endpoint` you passed to `OneXMonitor` each environment
   (sandbox, development, production) has its own ingestion URL in the
   [dashboard](https://dashboard.observability.getonex.ai).
3. In the dashboard (or your environment’s ingestion base URL), check the
   batch route (e.g. `/api/signals/batch`) to verify that signals are posted
   successfully and appear in your project logs.

To see SDK activity in your terminal (framework detection, signal export, etc.),
enable logging when creating the monitor:

```python theme={"dark"}
monitor = OneXMonitor(
    api_key="your-api-key",
    endpoint="onex-ingestion-endpoint",
    enable_logging=True,  # or config={"enable_logging": True}
    config={...},
)
```