Skip to main content

The official Python library for the agents API

Project description

Agents Python API library

PyPI version

The Agents Python library provides convenient access to the Agents REST API from any Python 3.7+ application. The library includes type definitions for all request params and response fields, and offers both synchronous and asynchronous clients powered by httpx.

It is generated with Stainless.

Documentation

The REST API documentation can be found on docs.agents.com. The full API of this library can be found in api.md.

Installation

# install from PyPI
pip install --pre scale-gp-agents

Usage

The full API of this library can be found in api.md.

from sgp_agents import Agents

client = Agents(
    api_key="My API Key",
)

config = client.configs.create(
    config={
        "plan": [
            {"workflow_name": "workflow_name"},
            {"workflow_name": "workflow_name"},
            {"workflow_name": "workflow_name"},
        ]
    },
)

Async usage

Simply import AsyncAgents instead of Agents and use await with each API call:

import asyncio
from sgp_agents import AsyncAgents

client = AsyncAgents(
    api_key="My API Key",
)


async def main() -> None:
    config = await client.configs.create(
        config={
            "plan": [
                {"workflow_name": "workflow_name"},
                {"workflow_name": "workflow_name"},
                {"workflow_name": "workflow_name"},
            ]
        },
    )


asyncio.run(main())

Functionality between the synchronous and asynchronous clients is otherwise identical.

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 earlier, set python.analysis.typeCheckingMode to basic.

Handling errors

When the library is unable to connect to the API (for example, due to network connection problems or a timeout), a subclass of sgp_agents.APIConnectionError is raised.

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

All errors inherit from sgp_agents.APIError.

import sgp_agents
from sgp_agents import Agents

client = Agents()

try:
    client.configs.create(
        config={
            "plan": [
                {"workflow_name": "workflow_name"},
                {"workflow_name": "workflow_name"},
                {"workflow_name": "workflow_name"},
            ]
        },
    )
except sgp_agents.APIConnectionError as e:
    print("The server could not be reached")
    print(e.__cause__)  # an underlying Exception, likely raised within httpx.
except sgp_agents.RateLimitError as e:
    print("A 429 status code was received; we should back off a bit.")
except sgp_agents.APIStatusError as e:
    print("Another non-200-range status code was received")
    print(e.status_code)
    print(e.response)

Error codes are as followed:

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 sgp_agents import Agents

# Configure the default for all requests:
client = Agents(
    # default is 2
    max_retries=0,
)

# Or, configure per-request:
client.with_options(max_retries=5).configs.create(
    config={
        "plan": [
            {"workflow_name": "workflow_name"},
            {"workflow_name": "workflow_name"},
            {"workflow_name": "workflow_name"},
        ]
    },
)

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 sgp_agents import Agents

# Configure the default for all requests:
client = Agents(
    # 20 seconds (default is 1 minute)
    timeout=20.0,
)

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

# Override per-request:
client.with_options(timeout=5.0).configs.create(
    config={
        "plan": [
            {"workflow_name": "workflow_name"},
            {"workflow_name": "workflow_name"},
            {"workflow_name": "workflow_name"},
        ]
    },
)

On timeout, an APITimeoutError is thrown.

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

Advanced

Logging

We use the standard library logging module.

You can enable logging by setting the environment variable AGENTS_LOG to debug.

$ export AGENTS_LOG=debug

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)

The "raw" Response object can be accessed by prefixing .with_raw_response. to any HTTP method call, e.g.,

from sgp_agents import Agents

client = Agents()
response = client.configs.with_raw_response.create(
    config={
        "plan": [{
            "workflow_name": "workflow_name"
        }, {
            "workflow_name": "workflow_name"
        }, {
            "workflow_name": "workflow_name"
        }]
    },
)
print(response.headers.get('X-My-Header'))

config = response.parse()  # get the object that `configs.create()` would have returned
print(config)

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.configs.with_streaming_response.create(
    config={
        "plan": [
            {"workflow_name": "workflow_name"},
            {"workflow_name": "workflow_name"},
            {"workflow_name": "workflow_name"},
        ]
    },
) 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, the library can still be used.

Undocumented endpoints

To make requests to undocumented endpoints, you can make requests using client.get, client.post, and other http verbs. Options on the client will be respected (such as retries) will be respected 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
from sgp_agents import Agents, DefaultHttpxClient

client = Agents(
    # Or use the `AGENTS_BASE_URL` env var
    base_url="http://my.test.server.example.com:8083",
    http_client=DefaultHttpxClient(
        proxies="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 with a context manager that closes when exiting.

Versioning

This package generally follows SemVer conventions, though certain backwards-incompatible changes may be released as minor versions:

  1. Changes that only affect static types, without breaking runtime behavior.
  2. Changes to library internals which are technically public but not intended or documented for external use. (Please open a GitHub issue to let us know if you are relying on such internals).
  3. Changes that we do not expect to impact the vast majority of users in practice.

We take backwards-compatibility seriously and work hard to ensure you can rely on a smooth upgrade experience.

We are keen for your feedback; please open an issue with questions, bugs, or suggestions.

Determining the installed version

If you've upgraded to the latest version but aren't seeing any new features you were expecting then your python environment is likely still using an older version.

You can determine the version that is being used at runtime with:

import sgp_agents
print(sgp_agents.__version__)

Requirements

Python 3.7 or higher.

Contributing

See the contributing documentation.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

scale_gp_agents-0.1.0a3.tar.gz (98.9 kB view details)

Uploaded Source

Built Distribution

scale_gp_agents-0.1.0a3-py3-none-any.whl (101.9 kB view details)

Uploaded Python 3

File details

Details for the file scale_gp_agents-0.1.0a3.tar.gz.

File metadata

  • Download URL: scale_gp_agents-0.1.0a3.tar.gz
  • Upload date:
  • Size: 98.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.12.3

File hashes

Hashes for scale_gp_agents-0.1.0a3.tar.gz
Algorithm Hash digest
SHA256 0bbdcacad68c79db11cb97717900ddf64aec822bddd8b313fcd1372f805c0ac4
MD5 1d780db57e7a348713c69af872d469fd
BLAKE2b-256 5544b98562f95b367fd0503d0d7108664138a0d253fee4b48b9012cd4473ff58

See more details on using hashes here.

File details

Details for the file scale_gp_agents-0.1.0a3-py3-none-any.whl.

File metadata

File hashes

Hashes for scale_gp_agents-0.1.0a3-py3-none-any.whl
Algorithm Hash digest
SHA256 6022be2398b57566648d695a6560dfa69f1e6395b107d7671d2a6fce3efe1a4b
MD5 2df086a2dc468a3874b953b0cb33b372
BLAKE2b-256 c778c92d47aba4c51b61d0c9f1542d1211724f81e2a088530978a3d1161d42f8

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page