NeMo Microservices Python SDK#

The NeMo Microservices Python SDK is a library for building and deploying AI models, abstracting the underlying infrastructure and providing a high-level interface for the NeMo microservices APIs.

Installation#

Install the NeMo Microservices Python SDK using pip:

pip install nemo-microservices

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.

Usage#

This section describes how to use the NeMo microservices Python SDK.

Import the Main Client Class#

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

from nemo_microservices import NeMoMicroservices

client = NeMoMicroservices(
    base_url="http://nemo.test",
    inference_base_url="http://nim.test"
)

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

For the base_url, point to the default host for NeMo microservices. This sets up the client to interact with the NeMo microservices APIs except the NIM Proxy microservice APIs.
For the inference_base_url, point to the host for the NIM Proxy microservice. You can also directly point to the host for a NIM microservice if the cluster admin in your organization has deployed it, or point to a NIM microservice on build.nvidia.com.

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

Async Usage#

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

import asyncio
from nemo_microservices import AsyncNeMoMicroservices

client = AsyncNeMoMicroservices(
    base_url="http://nemo.test",
    inference_base_url="http://nim.test"
)

# Sample API call
async def main() -> None:
    page = await client.namespaces.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:

pip install 'nemo-microservices[aiohttp]'

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

import asyncio
from nemo_microservices import DefaultAioHttpClient
from nemo_microservices import AsyncNeMoMicroservices


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


asyncio.run(main())

Using Types#

Nested request parameters are TypedDicts. Responses are Pydantic models 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 the NeMo microservices API are paginated.

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

from nemo_microservices import NeMoMicroservices

client = NeMoMicroservices(
    base_url="http://nemo.test",
    inference_base_url="http://nim.test"
)

all_projects = []
# Automatically fetches more pages as needed.
for project in client.projects.list():
    # Do something with project here
    all_projects.append(project)
print(all_projects)

Or, asynchronously:

import asyncio
from nemo_microservices import AsyncNeMoMicroservices

client = AsyncNeMoMicroservices(
    base_url="http://nemo.test",
    inference_base_url="http://nim.test"
)

async def main() -> None:
    all_projects = []
    # Iterate through items across all pages, issuing requests as needed.
    async for project in client.projects.list():
        all_projects.append(project)
    print(all_projects)


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:

first_page = await client.projects.list()
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:

first_page = await client.projects.list()
for project in first_page.data:
    print(project.created_at)

# Remove `await` for non-async usage.

Nested Parameters#

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

from nemo_microservices import NeMoMicroservices

client = NeMoMicroservices(
    base_url="http://nemo.test",
    inference_base_url="http://nim.test"
)

customization_config = client.customization.configs.create(
    max_seq_length=0,
    training_options=[
        {
            "finetuning_type": "p_tuning",
            "micro_batch_size": 0,
            "num_gpus": 0,
            "training_type": "sft",
        }
    ],
    ownership={},
)
print(customization_config.ownership)

Handling Errors#

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

API Connection Errors#

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

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

All errors inherit from nemo_microservices.APIError.

import nemo_microservices
from nemo_microservices import NeMoMicroservices

client = NeMoMicroservices()

try:
    client.namespaces.list()
except nemo_microservices.APIConnectionError as e:
    print("The server could not be reached")
    print(e.__cause__)  # an underlying Exception, likely raised within httpx.
except nemo_microservices.RateLimitError as e:
    print("A 429 status code was received; we should back off a bit.")
except nemo_microservices.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:

from nemo_microservices import NeMoMicroservices

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

# Or, configure per-request:
client.with_options(max_retries=5).namespaces.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 object:

from nemo_microservices import NeMoMicroservices

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

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

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

On timeout, an APITimeoutError is thrown.

Note that requests that time out are retried twice by default.

Advanced Usage#

Logging#

We use the standard library logging module.

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

$ export NEMO_MICROSERVICES_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:

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:

from nemo_microservices import NeMoMicroservices

client = NeMoMicroservices(base_url="http://nemo.test", inference_base_url="http://nim.test")
response = client.namespaces.with_raw_response.list()
print(response.headers.get('X-My-Header'))

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

These methods return an APIResponse object.

The async client returns an AsyncAPIResponse with the same structure, the only difference being awaitable 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.

with client.namespaces.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.

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.

Configuring the HTTP Client#

You can directly override the httpx client to customize it for your use case, including:

Support for proxies
Custom transports
Additional advanced functionality

import httpx
from nemo_microservices import NeMoMicroservices, DefaultHttpxClient

client = NeMoMicroservices(
    base_url="http://nemo.test",
    inference_base_url="http://nim.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():

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

Managing HTTP Resources#

By default the library closes underlying HTTP connections whenever the client is garbage collected. You can manually close the client using the .close() method if desired, or use a context manager that closes when exiting.

from nemo_microservices import NeMoMicroservices

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

# HTTP client is now closed