Skip to main content

Isaacus Python API library

PyPI version

The Isaacus Python library provides convenient access to the Isaacus REST API from any Python 3.9+ 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.

MCP Server

Use the Isaacus MCP Server to enable AI assistants to interact with this API, allowing them to explore endpoints, make test requests, and use documentation to help integrate this SDK into your application.

Add to Cursor Install in VS Code

Note: You may need to set environment variables in your MCP client.

Documentation

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

Installation

# install from PyPI
pip install isaacus

Usage

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

import os
from isaacus import Isaacus

client = Isaacus(
    api_key=os.environ.get("ISAACUS_API_KEY"),  # This is the default and can be omitted
)

embedding_response = client.embeddings.create(
    model="kanon-2-embedder",
    texts=[
        "Are restraints of trade enforceable under English law?",
        "What is a non-compete clause?",
    ],
    task="retrieval/query",
)
print(embedding_response.embeddings)

While you can provide an api_key keyword argument, we recommend using python-dotenv to add ISAACUS_API_KEY="My API Key" to your .env file so that your API Key is not stored in source control.

Async usage

Simply import AsyncIsaacus instead of Isaacus and use await with each API call:

import os
import asyncio
from isaacus import AsyncIsaacus

client = AsyncIsaacus(
    api_key=os.environ.get("ISAACUS_API_KEY"),  # This is the default and can be omitted
)


async def main() -> None:
    embedding_response = await client.embeddings.create(
        model="kanon-2-embedder",
        texts=[
            "Are restraints of trade enforceable under English law?",
            "What is a non-compete clause?",
        ],
        task="retrieval/query",
    )
    print(embedding_response.embeddings)


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:

# install from PyPI
pip install isaacus[aiohttp]

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

import os
import asyncio
from isaacus import DefaultAioHttpClient
from isaacus import AsyncIsaacus


async def main() -> None:
    async with AsyncIsaacus(
        api_key=os.environ.get("ISAACUS_API_KEY"),  # This is the default and can be omitted
        http_client=DefaultAioHttpClient(),
    ) as client:
        embedding_response = await client.embeddings.create(
            model="kanon-2-embedder",
            texts=[
                "Are restraints of trade enforceable under English law?",
                "What is a non-compete clause?",
            ],
            task="retrieval/query",
        )
        print(embedding_response.embeddings)


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 earlier, set python.analysis.typeCheckingMode to basic.

Nested params

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

from isaacus import Isaacus

client = Isaacus()

universal_classification_response = client.classifications.universal.create(
    model="kanon-universal-classifier",
    query="This is a confidentiality clause.",
    texts=["I agree not to tell anyone about the document."],
    chunking_options={
        "overlap_ratio": 0.1,
        "overlap_tokens": None,
        "size": 512,
    },
)
print(universal_classification_response.classifications)

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 isaacus.APIConnectionError is raised.

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

All errors inherit from isaacus.APIError.

import isaacus
from isaacus import Isaacus

client = Isaacus()

try:
    client.embeddings.create(
        model="kanon-2-embedder",
        texts=[
            "Are restraints of trade enforceable under English law?",
            "What is a non-compete clause?",
        ],
        task="retrieval/query",
    )
except isaacus.APIConnectionError as e:
    print("The server could not be reached")
    print(e.__cause__)  # an underlying Exception, likely raised within httpx.
except isaacus.RateLimitError as e:
    print("A 429 status code was received; we should back off a bit.")
except isaacus.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 isaacus import Isaacus

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

# Or, configure per-request:
client.with_options(max_retries=5).embeddings.create(
    model="kanon-2-embedder",
    texts=[
        "Are restraints of trade enforceable under English law?",
        "What is a non-compete clause?",
    ],
    task="retrieval/query",
)

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 isaacus import Isaacus

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

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

# Override per-request:
client.with_options(timeout=5.0).embeddings.create(
    model="kanon-2-embedder",
    texts=[
        "Are restraints of trade enforceable under English law?",
        "What is a non-compete clause?",
    ],
    task="retrieval/query",
)

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 ISAACUS_LOG to info.

$ export ISAACUS_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)

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

from isaacus import Isaacus

client = Isaacus()
response = client.embeddings.with_raw_response.create(
    model="kanon-2-embedder",
    texts=["Are restraints of trade enforceable under English law?", "What is a non-compete clause?"],
    task="retrieval/query",
)
print(response.headers.get('X-My-Header'))

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

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.embeddings.with_streaming_response.create(
    model="kanon-2-embedder",
    texts=[
        "Are restraints of trade enforceable under English law?",
        "What is a non-compete clause?",
    ],
    task="retrieval/query",
) 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) 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:

import httpx
from isaacus import Isaacus, DefaultHttpxClient

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

from isaacus import Isaacus

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

# HTTP client is now closed

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 isaacus
print(isaacus.__version__)

Requirements

Python 3.9 or higher.

Contributing

See the contributing documentation.

Metadata

Release files for isaacus 0.22.1

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for isaacus 0.22.1
File Size Uploaded
isaacus-0.22.1.tar.gz 140.3 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for isaacus 0.22.1
File Interpreter ABI Platform
isaacus-0.22.1-py3-none-any.whl Python 3 none any Details

Total release size: 264.7 kB

Release files / isaacus-0.22.1.tar.gz

Download URL isaacus-0.22.1.tar.gz
Size 140.3 kB
Tags Source
SHA-256 checksum
How to use checksums
8ab61b901b37347b436fb167c112f990b000eecae9cd794c77498f43f04ec86f
BLAKE2b-256 checksum
How to use checksums
50b0ddf19e86e6cc1ef23bb79ad72cb1b8faffc6238d1d21178c490c337e9a69
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/5.1.1 CPython/3.12.9

Release files / isaacus-0.22.1-py3-none-any.whl

Download URL isaacus-0.22.1-py3-none-any.whl
Size 124.3 kB
Tags Python 3
SHA-256 checksum
How to use checksums
b3e655db7b7c94ddb5cdac3232ddacf94a647f35200130f6fbd28d2d772a1709
BLAKE2b-256 checksum
How to use checksums
c60396661f13bb42cb658f468561d1bcd21f299aef920c042ca28b531f86ae4f
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/5.1.1 CPython/3.12.9
Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page