> For clean Markdown of any page, append .md to the page URL.
> For a complete documentation index, see https://docs.nvidia.com/nemo-helix/v0.5.0/documentation/reference/python-sdk/llms.txt.
> For AI client integration (Claude Code, Cursor, etc.), connect to the MCP server at https://docs.nvidia.com/nemo-helix/_mcp/server.

# NeMo Helix Python SDK Reference

The [NeMo Helix Python SDK](https://pypi.org/project/nemo-platform/) is a library for building and deploying AI models, abstracting the underlying infrastructure and providing a high-level interface for NeMo Helix APIs.

## Installation

Install the PyPI `nemo-platform` wrapper package using `pip`. The wrapper defines the `all` extra and includes the SDK. If you are working from a source checkout, run `make bootstrap` from the repository root instead; the generated SDK package under `sdk/python/nemo-platform/pyproject.toml` does not define the wrapper extras.

```bash
pip install "nemo-platform[all]"
```

> **Note**
>
> This project will download and install additional third-party open source software projects. Review the license terms of these open source projects before use.

If you previously installed the `nemo-microservices` package, uninstall it first to avoid conflicts:

```bash
pip uninstall nemo-microservices
```

## Usage

This section describes how to use NeMo Helix Python SDK.

### Import the Main Client Class

Import the main client class from the `nemo_platform` package and create a client instance as follows:

```python
from nemo_platform import NeMoPlatform

client = NeMoPlatform(
    base_url="http://nemo.test",
)

# Sample API call
page = client.workspaces.list()
print(page.data)
```

After creating the client instance, you can use the client to interact with NeMo Helix APIs.

## Async Usage

If you want to use the asynchronous client, simply import `AsyncNeMoPlatform` instead of `NeMoPlatform` and use `await` with each API call:

```python
import asyncio
from nemo_platform import AsyncNeMoPlatform

client = AsyncNeMoPlatform(
    base_url="http://nemo.test",
)

# Sample API call
async def main() -> None:
    page = await client.workspaces.list()
    print(page.data)

asyncio.run(main())
```

Functionality between the synchronous and asynchronous clients is otherwise identical.

### With aiohttp

By default, the async client uses `httpx` for HTTP requests. However, for improved concurrency performance you may also use `aiohttp` as the HTTP backend.

You can enable this by installing `aiohttp`:

```sh
pip install 'nemo-platform[aiohttp]'
```

Then you can enable it by instantiating the client with `http_client=DefaultAioHttpClient()`:

```python
import asyncio
from nemo_platform import DefaultAioHttpClient
from nemo_platform import AsyncNeMoPlatform

async def main() -> None:
    async with AsyncNeMoPlatform(
        base_url="http://nemo.test",
        http_client=DefaultAioHttpClient(),
    ) as client:
        page = await client.workspaces.list()
        print(page.data)

asyncio.run(main())
```

## Using Types

Nested request parameters are [TypedDicts](https://docs.python.org/3/library/typing.html#typing.TypedDict). Responses are [Pydantic models](https://docs.pydantic.dev) which also provide helper methods for things like:

* Serializing back into JSON, `model.to_json()`
* Converting to a dictionary, `model.to_dict()`

Typed requests and responses provide autocomplete and documentation within your editor. If you would like to see type errors in VS Code to help catch bugs, set `python.analysis.typeCheckingMode` to `basic`.

## Pagination

List methods in NeMo Helix API are paginated.

This library provides auto-paginating iterators with each list response, so you do not have to request successive pages manually:

```python
from nemo_platform import NeMoPlatform

client = NeMoPlatform(
    base_url="http://nemo.test",
)

all_jobs = []
# Automatically fetches more pages as needed.
for job in client.jobs.list(workspace="my-workspace"):
    # Do something with job here
    all_jobs.append(job)
print(all_jobs)
```

Or, asynchronously:

```python
import asyncio
from nemo_platform import AsyncNeMoPlatform

client = AsyncNeMoPlatform(
    base_url="http://nemo.test",
)

async def main() -> None:
    all_jobs = []
    # Iterate through items across all pages, issuing requests as needed.
    async for job in client.jobs.list(workspace="my-workspace"):
        all_jobs.append(job)
    print(all_jobs)

asyncio.run(main())
```

Alternatively, you can use the `.has_next_page()`, `.next_page_info()`, or `.get_next_page()` methods for more granular control working with pages:

```python
first_page = await client.jobs.list(workspace="my-workspace")
if first_page.has_next_page():
    print(f"will fetch next page using these details: {first_page.next_page_info()}")
    next_page = await first_page.get_next_page()
    print(f"number of items we just fetched: {len(next_page.data)}")

# Remove `await` for non-async usage.
```

Or just work directly with the returned data:

```python
first_page = await client.jobs.list(workspace="my-workspace")
for job in first_page.data:
    print(job.id)

# Remove `await` for non-async usage.
```

## Nested Parameters

Nested parameters are dictionaries, typed using `TypedDict`, for example:

```python
from nemo_platform import NeMoPlatform

client = NeMoPlatform(
    base_url="http://nemo.test",
)

audit_config = client.audit.configs.create(
    workspace="my-workspace",
    name="name",
    plugins={
        "buffs": {},
        "buffs_include_original_prompt": False,
        "detector_spec": "auto",
        "detectors": {},
        "extended_detectors": False,
        "generators": {},
        "harnesses": {},
        "probe_spec": "all",
        "probes": {"encoding": {"payloads": "bar"}},
    },
    reporting={},
    run={},
    system={},
)
print(audit_config.plugins)
```

## Handling Errors

The library raises errors when it cannot connect to the API or when the API returns a non-success status code.

When the library cannot connect to the API (for example, due to network connection problems or a timeout), it raises a subclass of `nemo_platform.APIConnectionError`.

When the API returns a non-success status code (that is, 4xx or 5xx
response), it raises a subclass of `nemo_platform.APIStatusError`, containing `status_code` and `response` properties.

All errors inherit from `nemo_platform.APIError`.

```python
import nemo_platform
from nemo_platform import NeMoPlatform

client = NeMoPlatform()

try:
    client.workspaces.list()
except nemo_platform.APIConnectionError as e:
    print("The server could not be reached")
    print(e.__cause__)  # an underlying Exception, likely raised within httpx.
except nemo_platform.RateLimitError as e:
    print("A 429 status code was received; we should back off a bit.")
except nemo_platform.APIStatusError as e:
    print("Another non-200-range status code was received")
    print(e.status_code)
    print(e.response)
```

Error codes are as follows:

| Status Code | Error Type                 |
| ----------- | -------------------------- |
| 400         | `BadRequestError`          |
| 401         | `AuthenticationError`      |
| 403         | `PermissionDeniedError`    |
| 404         | `NotFoundError`            |
| 422         | `UnprocessableEntityError` |
| 429         | `RateLimitError`           |
| >=500       | `InternalServerError`      |
| N/A         | `APIConnectionError`       |

## Retries

Certain errors are automatically retried 2 times by default, with a short exponential backoff.
Connection errors (for example, due to a network connectivity problem), 408 Request Timeout, 409 Conflict,
429 Rate Limit, and >=500 Internal errors are all retried by default.

You can use the `max_retries` option to configure or disable retry settings:

```python
from nemo_platform import NeMoPlatform

# Configure the default for all requests:
client = NeMoPlatform(
    base_url="http://nemo.test",
    # default is 2
    max_retries=0,
)

# Or, configure per-request:
client.with_options(max_retries=5).workspaces.list()
```

## Timeouts

By default, requests time out after 1 minute. You can configure this with a `timeout` option,
which accepts a float or an [`httpx.Timeout`](https://www.python-httpx.org/advanced/timeouts/#fine-tuning-the-configuration) object:

```python
from nemo_platform import NeMoPlatform

# Configure the default for all requests:
client = NeMoPlatform(
    base_url="http://nemo.test",
    # 20 seconds (default is 1 minute)
    timeout=20.0,
)

# More granular control:
client = NeMoPlatform(
    timeout=httpx.Timeout(60.0, read=5.0, write=10.0, connect=2.0),
)

# Override per-request:
client.with_options(timeout=5.0).workspaces.list()
```

On timeout, an `APITimeoutError` is thrown.

Note that requests that time out are [retried twice by default](#retries).

## Advanced Usage

### Logging

We use the standard library [`logging`](https://docs.python.org/3/library/logging.html) module.

You can enable logging by setting the environment variable `NMP_LOG` to `info`.

```shell
$ export NMP_LOG=info
```

Or to `debug` for more verbose logging.

#### How to Tell Whether `None` Means `null` or Missing

In an API response, a field may be explicitly `null`, or missing entirely; in either case, its value is `None` in this library. You can differentiate the two cases with `.model_fields_set`:

```py
if response.my_field is None:
  if 'my_field' not in response.model_fields_set:
    print('Got json like {}, without a "my_field" key present at all.')
  else:
    print('Got json like {"my_field": null}.')
```

### Accessing Raw Response Data (e.g. Headers)

You can access the "raw" response object by prefixing `.with_raw_response.` to any HTTP method call, for example:

```py
from nemo_platform import NeMoPlatform

client = NeMoPlatform(base_url="http://nemo.test")
response = client.workspaces.with_raw_response.list()
print(response.headers.get('X-My-Header'))

workspace = response.parse()  # get the object that `workspaces.list()` would have returned
print(workspace.id)
```

These methods return an `APIResponse` object.

The async client returns an `AsyncAPIResponse` with the same structure, the only difference being `await`able methods for reading the response content.

#### `.with_streaming_response`

The above interface eagerly reads the full response body when you make the request, which may not always be what you want.

To stream the response body, use `.with_streaming_response` instead, which requires a context manager and only reads the response body once you call `.read()`, `.text()`, `.json()`, `.iter_bytes()`, `.iter_text()`, `.iter_lines()` or `.parse()`. In the async client, these are async methods.

```python
with client.workspaces.with_streaming_response.list() as response:
    print(response.headers.get("X-My-Header"))

    for line in response.iter_lines():
        print(line)
```

The context manager is required so that the response will reliably be closed.

### Making Custom/Undocumented Requests

This library is typed for convenient access to the documented API.

If you need to access undocumented endpoints, params, or response properties, you can still use the library.

#### Undocumented Endpoints

To make requests to undocumented endpoints, you can make requests using `client.get`, `client.post`, and other
http verbs. The client will respect options (such as retries) when making this request.

```py
import httpx

response = client.post(
    "/foo",
    cast_to=httpx.Response,
    body={"my_param": True},
)

print(response.headers.get("x-foo"))
```

#### Undocumented Request Params

If you want to explicitly send an extra param, you can do so with the `extra_query`, `extra_body`, and `extra_headers` request
options.

#### Undocumented Response Properties

To access undocumented response properties, you can access the extra fields like `response.unknown_prop`. You
can also get all the extra fields on the Pydantic model as a dict with
[`response.model_extra`](https://docs.pydantic.dev/latest/api/base_model/#pydantic.BaseModel.model_extra).

### Configuring the HTTP Client

You can directly override the [httpx client](https://www.python-httpx.org/api/#client) to customize it for your use case, including:

* Support for [proxies](https://www.python-httpx.org/advanced/proxies/)
* Custom [transports](https://www.python-httpx.org/advanced/transports/)
* Additional [advanced](https://www.python-httpx.org/advanced/clients/) functionality

```python
import httpx
from nemo_platform import NeMoPlatform, DefaultHttpxClient

client = NeMoPlatform(
    base_url="http://nemo.test",
    http_client=DefaultHttpxClient(
        proxy="http://my.test.proxy.example.com",
        transport=httpx.HTTPTransport(local_address="0.0.0.0"),
    ),
)
```

You can also customize the client on a per-request basis by using `with_options()`:

```python
client.with_options(http_client=DefaultHttpxClient(...))
```

### Managing HTTP Resources

By default the library closes underlying HTTP connections whenever the client is [garbage collected](https://docs.python.org/3/reference/datamodel.html#object.__del__). You can manually close the client using the `.close()` method if desired, or use a context manager that closes when exiting.

```py
from nemo_platform import NeMoPlatform

with NeMoPlatform() as client:
  # make requests here
  ...

# HTTP client is now closed
```

## Next Steps

* Read more about connecting with the [client APIs](/documentation/reference/python-sdk/client-ap-is).
* Browse the [REST API Reference](/documentation/reference/api-reference).

## Docs

- [Client APIs](https://docs.nvidia.com/nemo-helix/v0.5.0/documentation/reference/python-sdk/client-ap-is.md):