feat(api): add gpu droplets

Author: stainless-app[bot]

.stats.yml

@@ -1,4 +1,4 @@
 configured_endpoints: 168
 openapi_spec_url: https://storage.googleapis.com/stainless-sdk-openapi-specs/digitalocean%2Fgradientai-f8e8c290636c1e218efcf7bfe92ba7570c11690754d21287d838919fbc943a80.yml
 openapi_spec_hash: 1eddf488ecbe415efb45445697716f5d
-config_hash: 683ea6ba4d63037c1c72484e5936e73c
+config_hash: 0a72b6161859b504ed3b5a2a142ba5a5

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/gradientai/lib/` and `examples/` directories.
+modify the contents of the `src/do_gradientai/lib/` and `examples/` directories.
 
 ## Adding and running examples
 

README.md

@@ -26,7 +26,7 @@ The full API of this library can be found in [api.md](api.md).
 
 ```python
 import os
-from gradientai import GradientAI
+from do_gradientai import GradientAI
 
 api_client = GradientAI(
     api_key=os.environ.get("GRADIENTAI_API_KEY"),  # This is the default and can be omitted
@@ -38,6 +38,7 @@ inference_client = GradientAI(
 )
 agent_client = GradientAI(
     agent_key=os.environ.get("GRADIENTAI_AGENT_KEY"),  # This is the default and can be omitted
+    agent_endpoint="https://my-cool-agent.agents.do-ai.run",
 )
 
 print(api_client.agents.list())
@@ -67,7 +68,7 @@ Simply import `AsyncGradientAI` instead of `GradientAI` and use `await` with eac
 ```python
 import os
 import asyncio
-from gradientai import AsyncGradientAI
+from do_gradientai import AsyncGradientAI
 
 client = AsyncGradientAI(
     api_key=os.environ.get("GRADIENTAI_API_KEY"),  # This is the default and can be omitted
@@ -107,8 +108,8 @@ Then you can enable it by instantiating the client with `http_client=DefaultAioH
 
 ```python
 import asyncio
-from gradientai import DefaultAioHttpClient
-from gradientai import AsyncGradientAI
+from do_gradientai import DefaultAioHttpClient
+from do_gradientai import AsyncGradientAI
 
 
 async def main() -> None:
@@ -136,7 +137,7 @@ asyncio.run(main())
 We provide support for streaming responses using Server Side Events (SSE).
 
 ```python
-from gradientai import GradientAI
+from do_gradientai import GradientAI
 
 client = GradientAI()
 
@@ -157,7 +158,7 @@ for completion in stream:
 The async client uses the exact same interface.
 
 ```python
-from gradientai import AsyncGradientAI
+from do_gradientai import AsyncGradientAI
 
 client = AsyncGradientAI()
 
@@ -189,7 +190,7 @@ Typed requests and responses provide autocomplete and documentation within your
 Nested parameters are dictionaries, typed using `TypedDict`, for example:
 
 ```python
-from gradientai import GradientAI
+from do_gradientai import GradientAI
 
 client = GradientAI()
 
@@ -208,16 +209,16 @@ 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 `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 `do_gradientai.APIConnectionError` is raised.
 
 When the API returns a non-success status code (that is, 4xx or 5xx
-response), a subclass of `gradientai.APIStatusError` is raised, containing `status_code` and `response` properties.
+response), a subclass of `do_gradientai.APIStatusError` is raised, containing `status_code` and `response` properties.
 
-All errors inherit from `gradientai.APIError`.
+All errors inherit from `do_gradientai.APIError`.
 
 ```python
-import gradientai
-from gradientai import GradientAI
+import do_gradientai
+from do_gradientai import GradientAI
 
 client = GradientAI()
 
@@ -231,12 +232,12 @@ try:
         ],
         model="llama3.3-70b-instruct",
     )
-except gradientai.APIConnectionError as e:
+except do_gradientai.APIConnectionError as e:
     print("The server could not be reached")
     print(e.__cause__)  # an underlying Exception, likely raised within httpx.
-except gradientai.RateLimitError as e:
+except do_gradientai.RateLimitError as e:
     print("A 429 status code was received; we should back off a bit.")
-except gradientai.APIStatusError as e:
+except do_gradientai.APIStatusError as e:
     print("Another non-200-range status code was received")
     print(e.status_code)
     print(e.response)
@@ -264,7 +265,7 @@ 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 gradientai import GradientAI
+from do_gradientai import GradientAI
 
 # Configure the default for all requests:
 client = GradientAI(
@@ -290,7 +291,7 @@ 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 gradientai import GradientAI
+from do_gradientai import GradientAI
 
 # Configure the default for all requests:
 client = GradientAI(
@@ -350,7 +351,7 @@ 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 gradientai import GradientAI
+from do_gradientai import GradientAI
 
 client = GradientAI()
 response = client.chat.completions.with_raw_response.create(
@@ -366,9 +367,9 @@ 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/gradientai/_response.py) object.
+These methods return an [`APIResponse`](https://github.com/digitalocean/gradientai-python/tree/main/src/do_gradientai/_response.py) object.
 
-The async client returns an [`AsyncAPIResponse`](https://github.com/digitalocean/gradientai-python/tree/main/src/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/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.
 
 #### `.with_streaming_response`
 
@@ -438,7 +439,7 @@ You can directly override the [httpx client](https://www.python-httpx.org/api/#c
 
 ```python
 import httpx
-from gradientai import GradientAI, DefaultHttpxClient
+from do_gradientai import GradientAI, DefaultHttpxClient
 
 client = GradientAI(
     # Or use the `GRADIENT_AI_BASE_URL` env var
@@ -461,7 +462,7 @@ 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 gradientai import GradientAI
+from do_gradientai import GradientAI
 
 with GradientAI() as client:
   # make requests here
@@ -489,8 +490,8 @@ 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 gradientai
-print(gradientai.__version__)
+import do_gradientai
+print(do_gradientai.__version__)
 ```
 
 ## Requirements