build(deps): bump actions/checkout from 6 to 7

Bumps [actions/checkout](https://github.com/actions/checkout) from 6 to 7.
- [Release notes](https://github.com/actions/checkout/releases)
- [Changelog](https://github.com/actions/checkout/blob/main/CHANGELOG.md)
- [Commits](https://github.com/actions/checkout/compare/v6...v7)

---
updated-dependencies:
- dependency-name: actions/checkout
  dependency-version: '7'
  dependency-type: direct:production
  update-type: version-update:semver-major
...

Signed-off-by: dependabot[bot] <support@github.com>

.github/workflows/publish.yaml

@@ -13,7 +13,7 @@ jobs:
       id-token: write
       contents: write
     steps:
-      - uses: actions/checkout@v5
+      - uses: actions/checkout@v7
       - uses: actions/setup-python@v6
       - uses: astral-sh/setup-uv@v5
         with:

.github/workflows/test.yaml

@@ -10,7 +10,7 @@ jobs:
   test:
     runs-on: ubuntu-latest
     steps:
-      - uses: actions/checkout@v5
+      - uses: actions/checkout@v7
       - uses: astral-sh/setup-uv@v5
         with:
           enable-cache: true
@@ -19,7 +19,7 @@ jobs:
   lint:
     runs-on: ubuntu-latest
     steps:
-      - uses: actions/checkout@v5
+      - uses: actions/checkout@v7
       - uses: actions/setup-python@v6
       - uses: astral-sh/setup-uv@v5
         with:

README.md

@@ -50,6 +50,82 @@ for chunk in stream:
   print(chunk['message']['content'], end='', flush=True)
 ```
 
+## Cloud Models
+
+Run larger models by offloading to Ollama’s cloud while keeping your local workflow.
+
+- Supported models: `deepseek-v3.1:671b-cloud`, `gpt-oss:20b-cloud`, `gpt-oss:120b-cloud`, `kimi-k2:1t-cloud`, `qwen3-coder:480b-cloud`, `kimi-k2-thinking` See [Ollama Models - Cloud](https://ollama.com/search?c=cloud) for more information
+
+### Run via local Ollama
+
+1) Sign in (one-time):
+
+```
+ollama signin
+```
+
+2) Pull a cloud model:
+
+```
+ollama pull gpt-oss:120b-cloud
+```
+
+3) Make a request:
+
+```python
+from ollama import Client
+
+client = Client()
+
+messages = [
+  {
+    'role': 'user',
+    'content': 'Why is the sky blue?',
+  },
+]
+
+for part in client.chat('gpt-oss:120b-cloud', messages=messages, stream=True):
+  print(part.message.content, end='', flush=True)
+```
+
+### Cloud API (ollama.com)
+
+Access cloud models directly by pointing the client at `https://ollama.com`.
+
+1) Create an API key from [ollama.com](https://ollama.com/settings/keys) , then set:
+
+```
+export OLLAMA_API_KEY=your_api_key
+```
+
+2) (Optional) List models available via the API:
+
+```
+curl https://ollama.com/api/tags
+```
+
+3) Generate a response via the cloud API:
+
+```python
+import os
+from ollama import Client
+
+client = Client(
+    host='https://ollama.com',
+    headers={'Authorization': 'Bearer ' + os.environ.get('OLLAMA_API_KEY')}
+)
+
+messages = [
+  {
+    'role': 'user',
+    'content': 'Why is the sky blue?',
+  },
+]
+
+for part in client.chat('gpt-oss:120b', messages=messages, stream=True):
+  print(part.message.content, end='', flush=True)
+```
+
 ## Custom client
 A custom client can be created by instantiating `Client` or `AsyncClient` from `ollama`.
 
@@ -174,7 +250,6 @@ ollama.embed(model='gemma3', input=['The sky is blue because of rayleigh scatter
 ollama.ps()
 ```
 
-
 ## Errors
 
 Errors are raised if requests return an error status or if an error is detected while streaming.

examples/README.md

@@ -78,6 +78,12 @@ Configuration to use with an MCP client:
 - [multimodal-chat.py](multimodal-chat.py)
 - [multimodal-generate.py](multimodal-generate.py)
 
+### Image Generation (Experimental) - Generate images with a model
+
+> **Note:** Image generation is experimental and currently only available on macOS.
+
+- [generate-image.py](generate-image.py)
+
 ### Structured Outputs - Generate structured outputs with a model
 
 - [structured-outputs.py](structured-outputs.py)

examples/generate-image.py

@@ -0,0 +1,18 @@
+# Image generation is experimental and currently only available on macOS
+
+import base64
+
+from ollama import generate
+
+prompt = 'a sunset over mountains'
+print(f'Prompt: {prompt}')
+
+for response in generate(model='x/z-image-turbo', prompt=prompt, stream=True):
+  if response.image:
+    # Final response contains the image
+    with open('output.png', 'wb') as f:
+      f.write(base64.b64decode(response.image))
+    print('\nImage saved to output.png')
+  elif response.total:
+    # Progress update
+    print(f'Progress: {response.completed or 0}/{response.total}', end='\r')

ollama/_client.py

@@ -1,3 +1,4 @@
+import contextlib
 import ipaddress
 import json
 import os
@@ -75,7 +76,7 @@ from ollama._types import (
 T = TypeVar('T')
 
 
-class BaseClient:
+class BaseClient(contextlib.AbstractContextManager, contextlib.AbstractAsyncContextManager):
   def __init__(
     self,
     client,
@@ -116,6 +117,12 @@ class BaseClient:
       **kwargs,
     )
 
+  def __exit__(self, exc_type, exc_val, exc_tb):
+    self.close()
+
+  async def __aexit__(self, exc_type, exc_val, exc_tb):
+    await self.close()
+
 
 CONNECTION_ERROR_MESSAGE = 'Failed to connect to Ollama. Please check that Ollama is downloaded, running and accessible. https://ollama.com/download'
 
@@ -124,6 +131,9 @@ class Client(BaseClient):
   def __init__(self, host: Optional[str] = None, **kwargs) -> None:
     super().__init__(httpx.Client, host, **kwargs)
 
+  def close(self):
+    self._client.close()
+
   def _request_raw(self, *args, **kwargs):
     try:
       r = self._client.request(*args, **kwargs)
@@ -207,6 +217,9 @@ class Client(BaseClient):
     images: Optional[Sequence[Union[str, bytes, Image]]] = None,
     options: Optional[Union[Mapping[str, Any], Options]] = None,
     keep_alive: Optional[Union[float, str]] = None,
+    width: Optional[int] = None,
+    height: Optional[int] = None,
+    steps: Optional[int] = None,
   ) -> GenerateResponse: ...
 
   @overload
@@ -228,6 +241,9 @@ class Client(BaseClient):
     images: Optional[Sequence[Union[str, bytes, Image]]] = None,
     options: Optional[Union[Mapping[str, Any], Options]] = None,
     keep_alive: Optional[Union[float, str]] = None,
+    width: Optional[int] = None,
+    height: Optional[int] = None,
+    steps: Optional[int] = None,
   ) -> Iterator[GenerateResponse]: ...
 
   def generate(
@@ -248,6 +264,9 @@ class Client(BaseClient):
     images: Optional[Sequence[Union[str, bytes, Image]]] = None,
     options: Optional[Union[Mapping[str, Any], Options]] = None,
     keep_alive: Optional[Union[float, str]] = None,
+    width: Optional[int] = None,
+    height: Optional[int] = None,
+    steps: Optional[int] = None,
   ) -> Union[GenerateResponse, Iterator[GenerateResponse]]:
     """
     Create a response using the requested model.
@@ -279,6 +298,9 @@ class Client(BaseClient):
         images=list(_copy_images(images)) if images else None,
         options=options,
         keep_alive=keep_alive,
+        width=width,
+        height=height,
+        steps=steps,
       ).model_dump(exclude_none=True),
       stream=stream,
     )
@@ -702,6 +724,9 @@ class AsyncClient(BaseClient):
   def __init__(self, host: Optional[str] = None, **kwargs) -> None:
     super().__init__(httpx.AsyncClient, host, **kwargs)
 
+  async def close(self):
+    await self._client.aclose()
+
   async def _request_raw(self, *args, **kwargs):
     try:
       r = await self._client.request(*args, **kwargs)
@@ -825,6 +850,9 @@ class AsyncClient(BaseClient):
     images: Optional[Sequence[Union[str, bytes, Image]]] = None,
     options: Optional[Union[Mapping[str, Any], Options]] = None,
     keep_alive: Optional[Union[float, str]] = None,
+    width: Optional[int] = None,
+    height: Optional[int] = None,
+    steps: Optional[int] = None,
   ) -> GenerateResponse: ...
 
   @overload
@@ -846,6 +874,9 @@ class AsyncClient(BaseClient):
     images: Optional[Sequence[Union[str, bytes, Image]]] = None,
     options: Optional[Union[Mapping[str, Any], Options]] = None,
     keep_alive: Optional[Union[float, str]] = None,
+    width: Optional[int] = None,
+    height: Optional[int] = None,
+    steps: Optional[int] = None,
   ) -> AsyncIterator[GenerateResponse]: ...
 
   async def generate(
@@ -866,6 +897,9 @@ class AsyncClient(BaseClient):
     images: Optional[Sequence[Union[str, bytes, Image]]] = None,
     options: Optional[Union[Mapping[str, Any], Options]] = None,
     keep_alive: Optional[Union[float, str]] = None,
+    width: Optional[int] = None,
+    height: Optional[int] = None,
+    steps: Optional[int] = None,
   ) -> Union[GenerateResponse, AsyncIterator[GenerateResponse]]:
     """
     Create a response using the requested model.
@@ -896,6 +930,9 @@ class AsyncClient(BaseClient):
         images=list(_copy_images(images)) if images else None,
         options=options,
         keep_alive=keep_alive,
+        width=width,
+        height=height,
+        steps=steps,
       ).model_dump(exclude_none=True),
       stream=stream,
     )

ollama/_types.py

@@ -216,6 +216,16 @@ class GenerateRequest(BaseGenerateRequest):
   top_logprobs: Optional[int] = None
   'Number of alternative tokens and log probabilities to include per position (0-20).'
 
+  # Experimental image generation parameters
+  width: Optional[int] = None
+  'Width of the generated image in pixels (for image generation models).'
+
+  height: Optional[int] = None
+  'Height of the generated image in pixels (for image generation models).'
+
+  steps: Optional[int] = None
+  'Number of diffusion steps (for image generation models).'
+
 
 class BaseGenerateResponse(SubscriptableBaseModel):
   model: Optional[str] = None
@@ -267,7 +277,7 @@ class GenerateResponse(BaseGenerateResponse):
   Response returned by generate requests.
   """
 
-  response: str
+  response: Optional[str] = None
   'Response content. When streaming, this contains a fragment of the response.'
 
   thinking: Optional[str] = None
@@ -279,6 +289,17 @@ class GenerateResponse(BaseGenerateResponse):
   logprobs: Optional[Sequence[Logprob]] = None
   'Log probabilities for generated tokens.'
 
+  # Image generation response fields
+  image: Optional[str] = None
+  'Base64-encoded generated image data (for image generation models).'
+
+  # Streaming progress fields (for image generation)
+  completed: Optional[int] = None
+  'Number of completed steps (for image generation streaming).'
+
+  total: Optional[int] = None
+  'Total number of steps (for image generation streaming).'
+
 
 class Message(SubscriptableBaseModel):
   """

tests/test_client.py

@@ -568,6 +568,115 @@ async def test_async_client_generate_format_pydantic(httpserver: HTTPServer):
   assert response['response'] == '{"answer": "Because of Rayleigh scattering", "confidence": 0.95}'
 
 
+def test_client_generate_image(httpserver: HTTPServer):
+  httpserver.expect_ordered_request(
+    '/api/generate',
+    method='POST',
+    json={
+      'model': 'dummy-image',
+      'prompt': 'a sunset over mountains',
+      'stream': False,
+      'width': 1024,
+      'height': 768,
+      'steps': 20,
+    },
+  ).respond_with_json(
+    {
+      'model': 'dummy-image',
+      'image': PNG_BASE64,
+      'done': True,
+      'done_reason': 'stop',
+    }
+  )
+
+  client = Client(httpserver.url_for('/'))
+  response = client.generate('dummy-image', 'a sunset over mountains', width=1024, height=768, steps=20)
+  assert response['model'] == 'dummy-image'
+  assert response['image'] == PNG_BASE64
+  assert response['done'] is True
+
+
+def test_client_generate_image_stream(httpserver: HTTPServer):
+  def stream_handler(_: Request):
+    def generate():
+      # Progress updates
+      for i in range(1, 4):
+        yield (
+          json.dumps(
+            {
+              'model': 'dummy-image',
+              'completed': i,
+              'total': 3,
+              'done': False,
+            }
+          )
+          + '\n'
+        )
+      # Final response with image
+      yield (
+        json.dumps(
+          {
+            'model': 'dummy-image',
+            'image': PNG_BASE64,
+            'done': True,
+            'done_reason': 'stop',
+          }
+        )
+        + '\n'
+      )
+
+    return Response(generate())
+
+  httpserver.expect_ordered_request(
+    '/api/generate',
+    method='POST',
+    json={
+      'model': 'dummy-image',
+      'prompt': 'a sunset over mountains',
+      'stream': True,
+      'width': 512,
+      'height': 512,
+    },
+  ).respond_with_handler(stream_handler)
+
+  client = Client(httpserver.url_for('/'))
+  response = client.generate('dummy-image', 'a sunset over mountains', stream=True, width=512, height=512)
+
+  parts = list(response)
+  # Check progress updates
+  assert parts[0]['completed'] == 1
+  assert parts[0]['total'] == 3
+  assert parts[0]['done'] is False
+  # Check final response
+  assert parts[-1]['image'] == PNG_BASE64
+  assert parts[-1]['done'] is True
+
+
+async def test_async_client_generate_image(httpserver: HTTPServer):
+  httpserver.expect_ordered_request(
+    '/api/generate',
+    method='POST',
+    json={
+      'model': 'dummy-image',
+      'prompt': 'a robot painting',
+      'stream': False,
+      'width': 1024,
+      'height': 1024,
+    },
+  ).respond_with_json(
+    {
+      'model': 'dummy-image',
+      'image': PNG_BASE64,
+      'done': True,
+    }
+  )
+
+  client = AsyncClient(httpserver.url_for('/'))
+  response = await client.generate('dummy-image', 'a robot painting', width=1024, height=1024)
+  assert response['model'] == 'dummy-image'
+  assert response['image'] == PNG_BASE64
+
+
 def test_client_pull(httpserver: HTTPServer):
   httpserver.expect_ordered_request(
     '/api/pull',
@@ -1347,3 +1456,33 @@ def test_client_explicit_bearer_header_overrides_env(monkeypatch: pytest.MonkeyP
   client = Client(headers={'Authorization': 'Bearer explicit-token'})
   assert client._client.headers['authorization'] == 'Bearer explicit-token'
   client.web_search('override check')
+
+
+def test_client_close():
+  client = Client()
+  client.close()
+  assert client._client.is_closed
+
+
+@pytest.mark.anyio
+async def test_async_client_close():
+  client = AsyncClient()
+  await client.close()
+  assert client._client.is_closed
+
+
+def test_client_context_manager():
+  with Client() as client:
+    assert isinstance(client, Client)
+    assert not client._client.is_closed
+
+  assert client._client.is_closed
+
+
+@pytest.mark.anyio
+async def test_async_client_context_manager():
+  async with AsyncClient() as client:
+    assert isinstance(client, AsyncClient)
+    assert not client._client.is_closed
+
+  assert client._client.is_closed