release: 3.0.0-beta.1

.github/workflows/ci.yml

@@ -16,7 +16,7 @@ jobs:
   lint:
     timeout-minutes: 10
     name: lint
-    runs-on: ${{ github.repository == 'stainless-sdks/gradientai-python' && 'depot-ubuntu-24.04' || 'ubuntu-latest' }}
+    runs-on: ${{ github.repository == 'stainless-sdks/gradient-python' && 'depot-ubuntu-24.04' || 'ubuntu-latest' }}
     if: github.event_name == 'push' || github.event.pull_request.head.repo.fork
     steps:
       - uses: actions/checkout@v4
@@ -36,7 +36,7 @@ jobs:
         run: ./scripts/lint
 
   build:
-    if: github.repository == 'stainless-sdks/gradientai-python' && (github.event_name == 'push' || github.event.pull_request.head.repo.fork)
+    if: github.repository == 'stainless-sdks/gradient-python' && (github.event_name == 'push' || github.event.pull_request.head.repo.fork)
     timeout-minutes: 10
     name: build
     permissions:
@@ -76,7 +76,7 @@ jobs:
   test:
     timeout-minutes: 10
     name: test
-    runs-on: ${{ github.repository == 'stainless-sdks/gradientai-python' && 'depot-ubuntu-24.04' || 'ubuntu-latest' }}
+    runs-on: ${{ github.repository == 'stainless-sdks/gradient-python' && 'depot-ubuntu-24.04' || 'ubuntu-latest' }}
     if: github.event_name == 'push' || github.event.pull_request.head.repo.fork
     steps:
       - uses: actions/checkout@v4

.github/workflows/publish-pypi.yml

@@ -1,6 +1,6 @@
 # This workflow is triggered when a GitHub release is created.
 # It can also be run manually to re-publish to PyPI in case it failed for some reason.
-# You can run this workflow by navigating to https://www.github.com/digitalocean/gradientai-python/actions/workflows/publish-pypi.yml
+# You can run this workflow by navigating to https://www.github.com/digitalocean/gradient-python/actions/workflows/publish-pypi.yml
 name: Publish PyPI
 on:
   workflow_dispatch:
@@ -28,4 +28,4 @@ jobs:
         run: |
           bash ./bin/publish-pypi
         env:
-          PYPI_TOKEN: ${{ secrets.GRADIENT_AI_PYPI_TOKEN || secrets.PYPI_TOKEN }}
+          PYPI_TOKEN: ${{ secrets.GRADIENT_PYPI_TOKEN || secrets.PYPI_TOKEN }}

.github/workflows/release-doctor.yml

@@ -9,7 +9,7 @@ jobs:
   release_doctor:
     name: release doctor
     runs-on: ubuntu-latest
-    if: github.repository == 'digitalocean/gradientai-python' && (github.event_name == 'push' || github.event_name == 'workflow_dispatch' || startsWith(github.head_ref, 'release-please') || github.head_ref == 'next')
+    if: github.repository == 'digitalocean/gradient-python' && (github.event_name == 'push' || github.event_name == 'workflow_dispatch' || startsWith(github.head_ref, 'release-please') || github.head_ref == 'next')
 
     steps:
       - uses: actions/checkout@v4
@@ -18,4 +18,4 @@ jobs:
         run: |
           bash ./bin/check-release-environment
         env:
-          PYPI_TOKEN: ${{ secrets.GRADIENT_AI_PYPI_TOKEN || secrets.PYPI_TOKEN }}
+          PYPI_TOKEN: ${{ secrets.GRADIENT_PYPI_TOKEN || secrets.PYPI_TOKEN }}

.release-please-manifest.json

@@ -1,3 +1,3 @@
 {
-  ".": "0.1.0-beta.4"
+  ".": "3.0.0-beta.1"
 }

.stats.yml

@@ -1,4 +1,4 @@
 configured_endpoints: 170
-openapi_spec_url: https://storage.googleapis.com/stainless-sdk-openapi-specs/digitalocean%2Fgradientai-015417b36365dfcb32166e67379c38de8bf5127c33dff646097a819a7b4dc588.yml
+openapi_spec_url: https://storage.googleapis.com/stainless-sdk-openapi-specs/digitalocean%2Fgradient-015417b36365dfcb32166e67379c38de8bf5127c33dff646097a819a7b4dc588.yml
 openapi_spec_hash: d7d811c13cc79f15d82fe680cf425859
-config_hash: 3ad1734779befb065101197f2f35568c
+config_hash: 77ddef130940a6ad8ea6c6f66aee8757

CONTRIBUTING.md

@@ -36,7 +36,7 @@ $ pip install -r requirements-dev.lock
 
 Most of the SDK is generated code. Modifications to code will be persisted between generations, but may
 result in merge conflicts between manual patches and changes from the generator. The generator will never
-modify the contents of the `src/do_gradientai/lib/` and `examples/` directories.
+modify the contents of the `src/gradient/lib/` and `examples/` directories.
 
 ## Adding and running examples
 
@@ -62,7 +62,7 @@ If you’d like to use the repository from source, you can either install from g
 To install via git:
 
 ```sh
-$ pip install git+ssh://[email protected]/digitalocean/gradientai-python.git
+$ pip install git+ssh://[email protected]/digitalocean/gradient-python.git
 ```
 
 Alternatively, you can build from source and install the wheel file:
@@ -120,7 +120,7 @@ the changes aren't made through the automated pipeline, you may want to make rel
 
 ### Publish with a GitHub workflow
 
-You can release to package managers by using [the `Publish PyPI` GitHub action](https://www.github.com/digitalocean/gradientai-python/actions/workflows/publish-pypi.yml). This requires a setup organization or repository secret to be set up.
+You can release to package managers by using [the `Publish PyPI` GitHub action](https://www.github.com/digitalocean/gradient-python/actions/workflows/publish-pypi.yml). This requires a setup organization or repository secret to be set up.
 
 ### Publish manually
 

LICENSE

@@ -186,7 +186,7 @@
       same "printed page" as the copyright notice for easier
       identification within third-party archives.
 
-   Copyright 2025 Gradient AI
+   Copyright 2025 Gradient
 
    Licensed under the Apache License, Version 2.0 (the "License");
    you may not use this file except in compliance with the License.

README.md

@@ -6,7 +6,7 @@
 > Use with care in production environments and keep an eye on releases for updates or breaking changes.
 
 <!-- prettier-ignore -->
-[![PyPI version](https://img.shields.io/pypi/v/do_gradientai.svg?label=pypi%20(stable))](https://pypi.org/project/do_gradientai/)
+[![PyPI version](https://img.shields.io/pypi/v/gradient.svg?label=pypi%20(stable))](https://pypi.org/project/gradient/)
 [![Docs](https://img.shields.io/badge/Docs-8A2BE2)](https://gradientai.digitalocean.com/getting-started/overview/)
 
 The Gradient Python library provides convenient access to the Gradient REST API from any Python 3.8+
@@ -25,7 +25,7 @@ The full API of this library can be found in [api.md](api.md).
 
 ```sh
 # install from PyPI
-pip install --pre do_gradientai
+pip install --pre gradient
 ```
 
 ## Usage
@@ -39,18 +39,18 @@ The full API of this library can be found in [api.md](api.md).
 
 ```python
 import os
-from do_gradientai import GradientAI
+from gradient import Gradient
 
-api_client = GradientAI(
-    api_key=os.environ.get("GRADIENTAI_API_KEY"),  # This is the default and can be omitted
+client = Gradient(
+    api_key=os.environ.get("GRADIENT_API_KEY"),  # This is the default and can be omitted
 )
-inference_client = GradientAI(
+inference_client = Gradient(
     inference_key=os.environ.get(
-        "GRADIENTAI_INFERENCE_KEY"
+        "GRADIENT_INFERENCE_KEY"
     ),  # This is the default and can be omitted
 )
-agent_client = GradientAI(
-    agent_key=os.environ.get("GRADIENTAI_AGENT_KEY"),  # This is the default and can be omitted
+agent_client = Gradient(
+    agent_key=os.environ.get("GRADIENT_AGENT_KEY"),  # This is the default and can be omitted
     agent_endpoint="https://my-agent.agents.do-ai.run",
 )
 
@@ -92,20 +92,20 @@ print(agent_response.choices[0].message.content)
 
 While you can provide an `api_key`, `inference_key` keyword argument,
 we recommend using [python-dotenv](https://pypi.org/project/python-dotenv/)
-to add `GRADIENTAI_API_KEY="My API Key"`, `GRADIENTAI_INFERENCE_KEY="My INFERENCE Key"` to your `.env` file
+to add `GRADIENT_API_KEY="My API Key"`, `GRADIENT_INFERENCE_KEY="My INFERENCE Key"` to your `.env` file
 so that your keys are not stored in source control.
 
 ## Async usage
 
-Simply import `AsyncGradientAI` instead of `GradientAI` and use `await` with each API call:
+Simply import `AsyncGradient` instead of `Gradient` and use `await` with each API call:
 
 ```python
 import os
 import asyncio
-from do_gradientai import AsyncGradientAI
+from gradient import AsyncGradient
 
-client = AsyncGradientAI(
-    api_key=os.environ.get("GRADIENTAI_API_KEY"),  # This is the default and can be omitted
+client = AsyncGradient(
+    api_key=os.environ.get("GRADIENT_API_KEY"),  # This is the default and can be omitted
 )
 
 
@@ -135,19 +135,19 @@ You can enable this by installing `aiohttp`:
 
 ```sh
 # install from PyPI
-pip install --pre do_gradientai[aiohttp]
+pip install --pre gradient[aiohttp]
 ```
 
 Then you can enable it by instantiating the client with `http_client=DefaultAioHttpClient()`:
 
 ```python
 import asyncio
-from do_gradientai import DefaultAioHttpClient
-from do_gradientai import AsyncGradientAI
+from gradient import DefaultAioHttpClient
+from gradient import AsyncGradient
 
 
 async def main() -> None:
-    async with AsyncGradientAI(
+    async with AsyncGradient(
         api_key="My API Key",
         http_client=DefaultAioHttpClient(),
     ) as client:
@@ -171,9 +171,9 @@ asyncio.run(main())
 We provide support for streaming responses using Server Side Events (SSE).
 
 ```python
-from do_gradientai import GradientAI
+from gradient import Gradient
 
-client = GradientAI()
+client = Gradient()
 
 stream = client.chat.completions.create(
     messages=[
@@ -192,9 +192,9 @@ for completion in stream:
 The async client uses the exact same interface.
 
 ```python
-from do_gradientai import AsyncGradientAI
+from gradient import AsyncGradient
 
-client = AsyncGradientAI()
+client = AsyncGradient()
 
 stream = await client.chat.completions.create(
     messages=[
@@ -224,9 +224,9 @@ Typed requests and responses provide autocomplete and documentation within your
 Nested parameters are dictionaries, typed using `TypedDict`, for example:
 
 ```python
-from do_gradientai import GradientAI
+from gradient import Gradient
 
-client = GradientAI()
+client = Gradient()
 
 completion = client.chat.completions.create(
     messages=[
@@ -243,18 +243,18 @@ print(completion.stream_options)
 
 ## 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 `do_gradientai.APIConnectionError` is raised.
+When the library is unable to connect to the API (for example, due to network connection problems or a timeout), a subclass of `gradient.APIConnectionError` is raised.
 
 When the API returns a non-success status code (that is, 4xx or 5xx
-response), a subclass of `do_gradientai.APIStatusError` is raised, containing `status_code` and `response` properties.
+response), a subclass of `gradient.APIStatusError` is raised, containing `status_code` and `response` properties.
 
-All errors inherit from `do_gradientai.APIError`.
+All errors inherit from `gradient.APIError`.
 
 ```python
-import do_gradientai
-from do_gradientai import GradientAI
+import gradient
+from gradient import Gradient
 
-client = GradientAI()
+client = Gradient()
 
 try:
     client.chat.completions.create(
@@ -266,12 +266,12 @@ try:
         ],
         model="llama3.3-70b-instruct",
     )
-except do_gradientai.APIConnectionError as e:
+except gradient.APIConnectionError as e:
     print("The server could not be reached")
     print(e.__cause__)  # an underlying Exception, likely raised within httpx.
-except do_gradientai.RateLimitError as e:
+except gradient.RateLimitError as e:
     print("A 429 status code was received; we should back off a bit.")
-except do_gradientai.APIStatusError as e:
+except gradient.APIStatusError as e:
     print("Another non-200-range status code was received")
     print(e.status_code)
     print(e.response)
@@ -299,10 +299,10 @@ Connection errors (for example, due to a network connectivity problem), 408 Requ
 You can use the `max_retries` option to configure or disable retry settings:
 
 ```python
-from do_gradientai import GradientAI
+from gradient import Gradient
 
 # Configure the default for all requests:
-client = GradientAI(
+client = Gradient(
     # default is 2
     max_retries=0,
 )
@@ -325,16 +325,16 @@ By default requests time out after 1 minute. You can configure this with a `time
 which accepts a float or an [`httpx.Timeout`](https://www.python-httpx.org/advanced/timeouts/#fine-tuning-the-configuration) object:
 
 ```python
-from do_gradientai import GradientAI
+from gradient import Gradient
 
 # Configure the default for all requests:
-client = GradientAI(
+client = Gradient(
     # 20 seconds (default is 1 minute)
     timeout=20.0,
 )
 
 # More granular control:
-client = GradientAI(
+client = Gradient(
     timeout=httpx.Timeout(60.0, read=5.0, write=10.0, connect=2.0),
 )
 
@@ -360,10 +360,10 @@ Note that requests that time out are [retried twice by default](#retries).
 
 We use the standard library [`logging`](https://docs.python.org/3/library/logging.html) module.
 
-You can enable logging by setting the environment variable `GRADIENT_AI_LOG` to `info`.
+You can enable logging by setting the environment variable `GRADIENT_LOG` to `info`.
 
 ```shell
-$ export GRADIENT_AI_LOG=info
+$ export GRADIENT_LOG=info
 ```
 
 Or to `debug` for more verbose logging.
@@ -385,9 +385,9 @@ if response.my_field is None:
 The "raw" Response object can be accessed by prefixing `.with_raw_response.` to any HTTP method call, e.g.,
 
 ```py
-from do_gradientai import GradientAI
+from gradient import Gradient
 
-client = GradientAI()
+client = Gradient()
 response = client.chat.completions.with_raw_response.create(
     messages=[{
         "role": "user",
@@ -401,9 +401,9 @@ completion = response.parse()  # get the object that `chat.completions.create()`
 print(completion.choices)
 ```
 
-These methods return an [`APIResponse`](https://github.com/digitalocean/gradientai-python/tree/main/src/do_gradientai/_response.py) object.
+These methods return an [`APIResponse`](https://github.com/digitalocean/gradient-python/tree/main/src/gradient/_response.py) object.
 
-The async client returns an [`AsyncAPIResponse`](https://github.com/digitalocean/gradientai-python/tree/main/src/do_gradientai/_response.py) with the same structure, the only difference being `await`able methods for reading the response content.
+The async client returns an [`AsyncAPIResponse`](https://github.com/digitalocean/gradient-python/tree/main/src/gradient/_response.py) with the same structure, the only difference being `await`able methods for reading the response content.
 
 #### `.with_streaming_response`
 
@@ -473,10 +473,10 @@ You can directly override the [httpx client](https://www.python-httpx.org/api/#c
 
 ```python
 import httpx
-from do_gradientai import GradientAI, DefaultHttpxClient
+from gradient import Gradient, DefaultHttpxClient
 
-client = GradientAI(
-    # Or use the `GRADIENT_AI_BASE_URL` env var
+client = Gradient(
+    # Or use the `GRADIENT_BASE_URL` env var
     base_url="http://my.test.server.example.com:8083",
     http_client=DefaultHttpxClient(
         proxy="http://my.test.proxy.example.com",
@@ -496,9 +496,9 @@ client.with_options(http_client=DefaultHttpxClient(...))
 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 with a context manager that closes when exiting.
 
 ```py
-from do_gradientai import GradientAI
+from gradient import Gradient
 
-with GradientAI() as client:
+with Gradient() as client:
   # make requests here
   ...
 
@@ -515,7 +515,7 @@ This package generally follows [SemVer](https://semver.org/spec/v2.0.0.html) con
 
 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](https://www.github.com/digitalocean/gradientai-python/issues) with questions, bugs, or suggestions.
+We are keen for your feedback; please open an [issue](https://www.github.com/digitalocean/gradient-python/issues) with questions, bugs, or suggestions.
 
 ### Determining the installed version
 
@@ -524,8 +524,8 @@ If you've upgraded to the latest version but aren't seeing any new features you
 You can determine the version that is being used at runtime with:
 
 ```py
-import do_gradientai
-print(do_gradientai.__version__)
+import gradient
+print(gradient.__version__)
 ```
 
 ## Requirements