build(deps): bump actions/checkout from 5 to 6 (#602)

Bumps [actions/checkout](https://github.com/actions/checkout) from 5 to 6.
- [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/v5...v6)

---
updated-dependencies:
- dependency-name: actions/checkout
  dependency-version: '6'
  dependency-type: direct:production
  update-type: version-update:semver-major
...

Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>

.github/workflows/publish.yaml

@@ -13,8 +13,8 @@ jobs:
       id-token: write
       contents: write
     steps:
-      - uses: actions/checkout@v4
+      - uses: actions/checkout@v6
-      - uses: actions/setup-python@v5
+      - uses: actions/setup-python@v6
       - uses: astral-sh/setup-uv@v5
         with:
           enable-cache: true

.github/workflows/test.yaml

@@ -10,7 +10,7 @@ jobs:
   test:
     runs-on: ubuntu-latest
     steps:
-      - uses: actions/checkout@v4
+      - uses: actions/checkout@v6
       - uses: astral-sh/setup-uv@v5
         with:
           enable-cache: true
@@ -19,8 +19,8 @@ jobs:
   lint:
     runs-on: ubuntu-latest
     steps:
-      - uses: actions/checkout@v4
+      - uses: actions/checkout@v6
-      - uses: actions/setup-python@v5
+      - uses: actions/setup-python@v6
       - uses: astral-sh/setup-uv@v5
         with:
           enable-cache: true

README.md

@@ -5,7 +5,7 @@ The Ollama Python library provides the easiest way to integrate Python 3.8+ proj
 ## Prerequisites
 
 - [Ollama](https://ollama.com/download) should be installed and running
-- Pull a model to use with the library: `ollama pull <model>` e.g. `ollama pull llama3.2`
+- Pull a model to use with the library: `ollama pull <model>` e.g. `ollama pull gemma3`
   - See [Ollama.com](https://ollama.com/search) for more information on the models available.
 
 ## Install
@@ -20,7 +20,7 @@ pip install ollama
 from ollama import chat
 from ollama import ChatResponse
 
-response: ChatResponse = chat(model='llama3.2', messages=[
+response: ChatResponse = chat(model='gemma3', messages=[
   {
     'role': 'user',
     'content': 'Why is the sky blue?',
@@ -41,7 +41,7 @@ Response streaming can be enabled by setting `stream=True`.
 from ollama import chat
 
 stream = chat(
-    model='llama3.2',
+    model='gemma3',
     messages=[{'role': 'user', 'content': 'Why is the sky blue?'}],
     stream=True,
 )
@@ -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`.
 
@@ -61,7 +137,7 @@ client = Client(
   host='http://localhost:11434',
   headers={'x-some-header': 'some-value'}
 )
-response = client.chat(model='llama3.2', messages=[
+response = client.chat(model='gemma3', messages=[
   {
     'role': 'user',
     'content': 'Why is the sky blue?',
@@ -79,7 +155,7 @@ from ollama import AsyncClient
 
 async def chat():
   message = {'role': 'user', 'content': 'Why is the sky blue?'}
-  response = await AsyncClient().chat(model='llama3.2', messages=[message])
+  response = await AsyncClient().chat(model='gemma3', messages=[message])
 
 asyncio.run(chat())
 ```
@@ -92,7 +168,7 @@ from ollama import AsyncClient
 
 async def chat():
   message = {'role': 'user', 'content': 'Why is the sky blue?'}
-  async for part in await AsyncClient().chat(model='llama3.2', messages=[message], stream=True):
+  async for part in await AsyncClient().chat(model='gemma3', messages=[message], stream=True):
     print(part['message']['content'], end='', flush=True)
 
 asyncio.run(chat())
@@ -105,13 +181,13 @@ The Ollama Python library's API is designed around the [Ollama REST API](https:/
 ### Chat
 
 ```python
-ollama.chat(model='llama3.2', messages=[{'role': 'user', 'content': 'Why is the sky blue?'}])
+ollama.chat(model='gemma3', messages=[{'role': 'user', 'content': 'Why is the sky blue?'}])
 ```
 
 ### Generate
 
 ```python
-ollama.generate(model='llama3.2', prompt='Why is the sky blue?')
+ollama.generate(model='gemma3', prompt='Why is the sky blue?')
 ```
 
 ### List
@@ -123,49 +199,49 @@ ollama.list()
 ### Show
 
 ```python
-ollama.show('llama3.2')
+ollama.show('gemma3')
 ```
 
 ### Create
 
 ```python
-ollama.create(model='example', from_='llama3.2', system="You are Mario from Super Mario Bros.")
+ollama.create(model='example', from_='gemma3', system="You are Mario from Super Mario Bros.")
 ```
 
 ### Copy
 
 ```python
-ollama.copy('llama3.2', 'user/llama3.2')
+ollama.copy('gemma3', 'user/gemma3')
 ```
 
 ### Delete
 
 ```python
-ollama.delete('llama3.2')
+ollama.delete('gemma3')
 ```
 
 ### Pull
 
 ```python
-ollama.pull('llama3.2')
+ollama.pull('gemma3')
 ```
 
 ### Push
 
 ```python
-ollama.push('user/llama3.2')
+ollama.push('user/gemma3')
 ```
 
 ### Embed
 
 ```python
-ollama.embed(model='llama3.2', input='The sky is blue because of rayleigh scattering')
+ollama.embed(model='gemma3', input='The sky is blue because of rayleigh scattering')
 ```
 
 ### Embed (batch)
 
 ```python
-ollama.embed(model='llama3.2', input=['The sky is blue because of rayleigh scattering', 'Grass is green because of chlorophyll'])
+ollama.embed(model='gemma3', input=['The sky is blue because of rayleigh scattering', 'Grass is green because of chlorophyll'])
 ```
 
 ### Ps

examples/README.md

@@ -1,67 +1,123 @@
 # Running Examples
 
 Run the examples in this directory with:
+
 ```sh
 # Run example
 python3 examples/<example>.py
+
+# or with uv
+uv run examples/<example>.py
 ```
 
 See [ollama/docs/api.md](https://github.com/ollama/ollama/blob/main/docs/api.md) for full API documentation
 
 ### Chat - Chat with a model
+
 - [chat.py](chat.py)
 - [async-chat.py](async-chat.py)
 - [chat-stream.py](chat-stream.py) - Streamed outputs
 - [chat-with-history.py](chat-with-history.py) - Chat with model and maintain history of the conversation
 
-
 ### Generate - Generate text with a model
+
 - [generate.py](generate.py)
 - [async-generate.py](async-generate.py)
 - [generate-stream.py](generate-stream.py) - Streamed outputs
 - [fill-in-middle.py](fill-in-middle.py) - Given a prefix and suffix, fill in the middle
 
-
 ### Tools/Function Calling - Call a function with a model
+
 - [tools.py](tools.py) - Simple example of Tools/Function Calling
 - [async-tools.py](async-tools.py)
+- [multi-tool.py](multi-tool.py) - Using multiple tools, with thinking enabled
 
+#### gpt-oss
+
+- [gpt-oss-tools.py](gpt-oss-tools.py)
+- [gpt-oss-tools-stream.py](gpt-oss-tools-stream.py)
+
+### Web search
+
+An API key from Ollama's cloud service is required. You can create one [here](https://ollama.com/settings/keys).
+
+```shell
+export OLLAMA_API_KEY="your_api_key_here"
+```
+
+- [web-search.py](web-search.py)
+- [web-search-gpt-oss.py](web-search-gpt-oss.py) - Using browser research tools with gpt-oss
+
+#### MCP server
+
+The MCP server can be used with an MCP client like Cursor, Cline, Codex, Open WebUI, Goose, and more.
+
+```sh
+uv run examples/web-search-mcp.py
+```
+
+Configuration to use with an MCP client:
+
+```json
+{
+  "mcpServers": {
+    "web_search": {
+      "type": "stdio",
+      "command": "uv",
+      "args": ["run", "path/to/ollama-python/examples/web-search-mcp.py"],
+      "env": { "OLLAMA_API_KEY": "your_api_key_here" }
+    }
+  }
+}
+```
+
+- [web-search-mcp.py](web-search-mcp.py)
 
 ### Multimodal with Images - Chat with a multimodal (image chat) model
+
 - [multimodal-chat.py](multimodal-chat.py)
 - [multimodal-generate.py](multimodal-generate.py)
 
-
 ### Structured Outputs - Generate structured outputs with a model
+
 - [structured-outputs.py](structured-outputs.py)
 - [async-structured-outputs.py](async-structured-outputs.py)
 - [structured-outputs-image.py](structured-outputs-image.py)
 
-
 ### Ollama List - List all downloaded models and their properties
+
 - [list.py](list.py)
 
-
 ### Ollama Show - Display model properties and capabilities
+
 - [show.py](show.py)
 
-
 ### Ollama ps - Show model status with CPU/GPU usage
+
 - [ps.py](ps.py)
 
-
 ### Ollama Pull - Pull a model from Ollama
+
 Requirement: `pip install tqdm`
+
 - [pull.py](pull.py)
 
-
 ### Ollama Create - Create a model from a Modelfile
+
 - [create.py](create.py)
 
-
 ### Ollama Embed - Generate embeddings with a model
+
 - [embed.py](embed.py)
 
-
 ### Thinking - Enable thinking mode for a model
+
 - [thinking.py](thinking.py)
+
+### Thinking (generate) - Enable thinking mode for a model
+
+- [thinking-generate.py](thinking-generate.py)
+
+### Thinking (levels) - Choose the thinking level
+
+- [thinking-levels.py](thinking-levels.py)

examples/async-chat.py

@@ -12,7 +12,7 @@ async def main():
   ]
 
   client = AsyncClient()
-  response = await client.chat('llama3.2', messages=messages)
+  response = await client.chat('gemma3', messages=messages)
   print(response['message']['content'])
 
 

examples/async-generate.py

@@ -5,7 +5,7 @@ import ollama
 
 async def main():
   client = ollama.AsyncClient()
-  response = await client.generate('llama3.2', 'Why is the sky blue?')
+  response = await client.generate('gemma3', 'Why is the sky blue?')
   print(response['response'])
 
 

examples/async-tools.py

@@ -76,7 +76,7 @@ async def main():
   if response.message.tool_calls:
     # Add the function response to messages for the model to use
     messages.append(response.message)
-    messages.append({'role': 'tool', 'content': str(output), 'name': tool.function.name})
+    messages.append({'role': 'tool', 'content': str(output), 'tool_name': tool.function.name})
 
     # Get final response from model with function outputs
     final_response = await client.chat('llama3.1', messages=messages)

examples/chat-logprobs.py

@@ -0,0 +1,31 @@
+from typing import Iterable
+
+import ollama
+
+
+def print_logprobs(logprobs: Iterable[dict], label: str) -> None:
+  print(f'\n{label}:')
+  for entry in logprobs:
+    token = entry.get('token', '')
+    logprob = entry.get('logprob')
+    print(f'  token={token!r:<12} logprob={logprob:.3f}')
+    for alt in entry.get('top_logprobs', []):
+      if alt['token'] != token:
+        print(f'    alt -> {alt["token"]!r:<12} ({alt["logprob"]:.3f})')
+
+
+messages = [
+  {
+    'role': 'user',
+    'content': 'hi! be concise.',
+  },
+]
+
+response = ollama.chat(
+  model='gemma3',
+  messages=messages,
+  logprobs=True,
+  top_logprobs=3,
+)
+print('Chat response:', response['message']['content'])
+print_logprobs(response.get('logprobs', []), 'chat logprobs')

examples/chat-stream.py

@@ -7,7 +7,5 @@ messages = [
   },
 ]
 
-for part in chat('llama3.2', messages=messages, stream=True):
+for part in chat('gemma3', messages=messages, stream=True):
   print(part['message']['content'], end='', flush=True)
-
-print()

examples/chat-with-history.py

@@ -15,14 +15,15 @@ messages = [
   },
   {
     'role': 'assistant',
-    'content': 'The weather in Tokyo is typically warm and humid during the summer months, with temperatures often exceeding 30°C (86°F). The city experiences a rainy season from June to September, with heavy rainfall and occasional typhoons. Winter is mild, with temperatures rarely dropping below freezing. The city is known for its high-tech and vibrant culture, with many popular tourist attractions such as the Tokyo Tower, Senso-ji Temple, and the bustling Shibuya district.',
+    'content': """The weather in Tokyo is typically warm and humid during the summer months, with temperatures often exceeding 30°C (86°F). The city experiences a rainy season from June to September, with heavy rainfall and occasional typhoons. Winter is mild, with temperatures
+    rarely dropping below freezing. The city is known for its high-tech and vibrant culture, with many popular tourist attractions such as the Tokyo Tower, Senso-ji Temple, and the bustling Shibuya district.""",
   },
 ]
 
 while True:
   user_input = input('Chat with history: ')
   response = chat(
-    'llama3.2',
+    'gemma3',
     messages=[*messages, {'role': 'user', 'content': user_input}],
   )
 

examples/chat.py

@@ -7,5 +7,5 @@ messages = [
   },
 ]
 
-response = chat('llama3.2', messages=messages)
+response = chat('gemma3', messages=messages)
 print(response['message']['content'])

examples/create.py

@@ -3,7 +3,7 @@ from ollama import Client
 client = Client()
 response = client.create(
   model='my-assistant',
-  from_='llama3.2',
+  from_='gemma3',
   system='You are mario from Super Mario Bros.',
   stream=False,
 )

examples/generate-logprobs.py

@@ -0,0 +1,24 @@
+from typing import Iterable
+
+import ollama
+
+
+def print_logprobs(logprobs: Iterable[dict], label: str) -> None:
+  print(f'\n{label}:')
+  for entry in logprobs:
+    token = entry.get('token', '')
+    logprob = entry.get('logprob')
+    print(f'  token={token!r:<12} logprob={logprob:.3f}')
+    for alt in entry.get('top_logprobs', []):
+      if alt['token'] != token:
+        print(f'    alt -> {alt["token"]!r:<12} ({alt["logprob"]:.3f})')
+
+
+response = ollama.generate(
+  model='gemma3',
+  prompt='hi! be concise.',
+  logprobs=True,
+  top_logprobs=3,
+)
+print('Generate response:', response['response'])
+print_logprobs(response.get('logprobs', []), 'generate logprobs')

examples/generate-stream.py

@@ -1,4 +1,4 @@
 from ollama import generate
 
-for part in generate('llama3.2', 'Why is the sky blue?', stream=True):
+for part in generate('gemma3', 'Why is the sky blue?', stream=True):
   print(part['response'], end='', flush=True)

examples/generate.py

@@ -1,4 +1,4 @@
 from ollama import generate
 
-response = generate('llama3.2', 'Why is the sky blue?')
+response = generate('gemma3', 'Why is the sky blue?')
 print(response['response'])

examples/gpt-oss-tools-stream.py

@@ -0,0 +1,105 @@
+# /// script
+# requires-python = ">=3.11"
+# dependencies = [
+#     "gpt-oss",
+#     "ollama",
+#     "rich",
+# ]
+# ///
+import random
+from typing import Iterator
+
+from rich import print
+
+from ollama import Client
+from ollama._types import ChatResponse
+
+
+def get_weather(city: str) -> str:
+  """
+  Get the current temperature for a city
+
+  Args:
+      city (str): The name of the city
+
+  Returns:
+      str: The current temperature
+  """
+  temperatures = list(range(-10, 35))
+
+  temp = random.choice(temperatures)
+
+  return f'The temperature in {city} is {temp}°C'
+
+
+def get_weather_conditions(city: str) -> str:
+  """
+  Get the weather conditions for a city
+
+  Args:
+      city (str): The name of the city
+
+  Returns:
+      str: The current weather conditions
+  """
+  conditions = ['sunny', 'cloudy', 'rainy', 'snowy', 'foggy']
+  return random.choice(conditions)
+
+
+available_tools = {'get_weather': get_weather, 'get_weather_conditions': get_weather_conditions}
+
+messages = [{'role': 'user', 'content': 'What is the weather like in London? What are the conditions in Toronto?'}]
+
+client = Client(
+  # Ollama Turbo
+  # host="https://ollama.com", headers={'Authorization': (os.getenv('OLLAMA_API_KEY'))}
+)
+
+model = 'gpt-oss:20b'
+# gpt-oss can call tools while "thinking"
+# a loop is needed to call the tools and get the results
+final = True
+while True:
+  response_stream: Iterator[ChatResponse] = client.chat(model=model, messages=messages, tools=[get_weather, get_weather_conditions], stream=True)
+  tool_calls = []
+  thinking = ''
+  content = ''
+
+  for chunk in response_stream:
+    if chunk.message.tool_calls:
+      tool_calls.extend(chunk.message.tool_calls)
+
+    if chunk.message.content:
+      if not (chunk.message.thinking or chunk.message.thinking == '') and final:
+        print('\n\n' + '=' * 10)
+        print('Final result: ')
+        final = False
+      print(chunk.message.content, end='', flush=True)
+
+    if chunk.message.thinking:
+      # accumulate thinking
+      thinking += chunk.message.thinking
+      print(chunk.message.thinking, end='', flush=True)
+
+  if thinking != '' or content != '' or len(tool_calls) > 0:
+    messages.append({'role': 'assistant', 'thinking': thinking, 'content': content, 'tool_calls': tool_calls})
+
+  print()
+
+  if tool_calls:
+    for tool_call in tool_calls:
+      function_to_call = available_tools.get(tool_call.function.name)
+      if function_to_call:
+        print('\nCalling tool:', tool_call.function.name, 'with arguments: ', tool_call.function.arguments)
+        result = function_to_call(**tool_call.function.arguments)
+        print('Tool result: ', result + '\n')
+
+        result_message = {'role': 'tool', 'content': result, 'tool_name': tool_call.function.name}
+        messages.append(result_message)
+      else:
+        print(f'Tool {tool_call.function.name} not found')
+        messages.append({'role': 'tool', 'content': f'Tool {tool_call.function.name} not found', 'tool_name': tool_call.function.name})
+
+  else:
+    # no more tool calls, we can stop the loop
+    break

examples/gpt-oss-tools.py

@@ -0,0 +1,84 @@
+# /// script
+# requires-python = ">=3.11"
+# dependencies = [
+#     "gpt-oss",
+#     "ollama",
+#     "rich",
+# ]
+# ///
+import random
+
+from rich import print
+
+from ollama import Client
+from ollama._types import ChatResponse
+
+
+def get_weather(city: str) -> str:
+  """
+  Get the current temperature for a city
+
+  Args:
+      city (str): The name of the city
+
+  Returns:
+      str: The current temperature
+  """
+  temperatures = list(range(-10, 35))
+
+  temp = random.choice(temperatures)
+
+  return f'The temperature in {city} is {temp}°C'
+
+
+def get_weather_conditions(city: str) -> str:
+  """
+  Get the weather conditions for a city
+
+  Args:
+      city (str): The name of the city
+
+  Returns:
+      str: The current weather conditions
+  """
+  conditions = ['sunny', 'cloudy', 'rainy', 'snowy', 'foggy']
+  return random.choice(conditions)
+
+
+available_tools = {'get_weather': get_weather, 'get_weather_conditions': get_weather_conditions}
+
+messages = [{'role': 'user', 'content': 'What is the weather like in London? What are the conditions in Toronto?'}]
+
+
+client = Client(
+  # Ollama Turbo
+  # host="https://ollama.com", headers={'Authorization': (os.getenv('OLLAMA_API_KEY'))}
+)
+model = 'gpt-oss:20b'
+# gpt-oss can call tools while "thinking"
+# a loop is needed to call the tools and get the results
+while True:
+  response: ChatResponse = client.chat(model=model, messages=messages, tools=[get_weather, get_weather_conditions])
+
+  if response.message.content:
+    print('Content: ')
+    print(response.message.content + '\n')
+  if response.message.thinking:
+    print('Thinking: ')
+    print(response.message.thinking + '\n')
+
+  messages.append(response.message)
+
+  if response.message.tool_calls:
+    for tool_call in response.message.tool_calls:
+      function_to_call = available_tools.get(tool_call.function.name)
+      if function_to_call:
+        result = function_to_call(**tool_call.function.arguments)
+        print('Result from tool call name: ', tool_call.function.name, 'with arguments: ', tool_call.function.arguments, 'result: ', result + '\n')
+        messages.append({'role': 'tool', 'content': result, 'tool_name': tool_call.function.name})
+      else:
+        print(f'Tool {tool_call.function.name} not found')
+        messages.append({'role': 'tool', 'content': f'Tool {tool_call.function.name} not found', 'tool_name': tool_call.function.name})
+  else:
+    # no more tool calls, we can stop the loop
+    break

examples/multi-tool.py

@@ -0,0 +1,88 @@
+import random
+from typing import Iterator
+
+from ollama import ChatResponse, Client
+
+
+def get_temperature(city: str) -> int:
+  """
+  Get the temperature for a city in Celsius
+
+  Args:
+    city (str): The name of the city
+
+  Returns:
+    int: The current temperature in Celsius
+  """
+  # This is a mock implementation - would need to use a real weather API
+  import random
+
+  if city not in ['London', 'Paris', 'New York', 'Tokyo', 'Sydney']:
+    return 'Unknown city'
+
+  return str(random.randint(0, 35)) + ' degrees Celsius'
+
+
+def get_conditions(city: str) -> str:
+  """
+  Get the weather conditions for a city
+  """
+  if city not in ['London', 'Paris', 'New York', 'Tokyo', 'Sydney']:
+    return 'Unknown city'
+  # This is a mock implementation - would need to use a real weather API
+  conditions = ['sunny', 'cloudy', 'rainy', 'snowy']
+  return random.choice(conditions)
+
+
+available_functions = {
+  'get_temperature': get_temperature,
+  'get_conditions': get_conditions,
+}
+
+
+cities = ['London', 'Paris', 'New York', 'Tokyo', 'Sydney']
+city = random.choice(cities)
+city2 = random.choice(cities)
+messages = [{'role': 'user', 'content': f'What is the temperature in {city}? and what are the weather conditions in {city2}?'}]
+print('----- Prompt:', messages[0]['content'], '\n')
+
+model = 'qwen3'
+client = Client()
+response: Iterator[ChatResponse] = client.chat(model, stream=True, messages=messages, tools=[get_temperature, get_conditions], think=True)
+
+for chunk in response:
+  if chunk.message.thinking:
+    print(chunk.message.thinking, end='', flush=True)
+  if chunk.message.content:
+    print(chunk.message.content, end='', flush=True)
+  if chunk.message.tool_calls:
+    for tool in chunk.message.tool_calls:
+      if function_to_call := available_functions.get(tool.function.name):
+        print('\nCalling function:', tool.function.name, 'with arguments:', tool.function.arguments)
+        output = function_to_call(**tool.function.arguments)
+        print('> Function output:', output, '\n')
+
+        # Add the assistant message and tool call result to the messages
+        messages.append(chunk.message)
+        messages.append({'role': 'tool', 'content': str(output), 'tool_name': tool.function.name})
+      else:
+        print('Function', tool.function.name, 'not found')
+
+print('----- Sending result back to model \n')
+if any(msg.get('role') == 'tool' for msg in messages):
+  res = client.chat(model, stream=True, tools=[get_temperature, get_conditions], messages=messages, think=True)
+  done_thinking = False
+  for chunk in res:
+    if chunk.message.thinking:
+      print(chunk.message.thinking, end='', flush=True)
+    if chunk.message.content:
+      if not done_thinking:
+        print('\n----- Final result:')
+        done_thinking = True
+      print(chunk.message.content, end='', flush=True)
+    if chunk.message.tool_calls:
+      # Model should be explaining the tool calls and the results in this output
+      print('Model returned tool calls:')
+      print(chunk.message.tool_calls)
+else:
+  print('No tool calls returned')

examples/multimodal-chat.py

@@ -11,7 +11,7 @@ path = input('Please enter the path to the image: ')
 # img = Path(path).read_bytes()
 
 response = chat(
-  model='llama3.2-vision',
+  model='gemma3',
   messages=[
     {
       'role': 'user',

examples/ps.py

@@ -1,7 +1,7 @@
 from ollama import ProcessResponse, chat, ps, pull
 
 # Ensure at least one model is loaded
-response = pull('llama3.2', stream=True)
+response = pull('gemma3', stream=True)
 progress_states = set()
 for progress in response:
   if progress.get('status') in progress_states:
@@ -12,7 +12,7 @@ for progress in response:
 print('\n')
 
 print('Waiting for model to load... \n')
-chat(model='llama3.2', messages=[{'role': 'user', 'content': 'Why is the sky blue?'}])
+chat(model='gemma3', messages=[{'role': 'user', 'content': 'Why is the sky blue?'}])
 
 
 response: ProcessResponse = ps()
@@ -23,4 +23,5 @@ for model in response.models:
   print('  Size: ', model.size)
   print('  Size vram: ', model.size_vram)
   print('  Details: ', model.details)
+  print('  Context length: ', model.context_length)
   print('\n')

examples/pull.py

@@ -3,7 +3,7 @@ from tqdm import tqdm
 from ollama import pull
 
 current_digest, bars = '', {}
-for progress in pull('llama3.2', stream=True):
+for progress in pull('gemma3', stream=True):
   digest = progress.get('digest', '')
   if digest != current_digest and current_digest in bars:
     bars[current_digest].close()

examples/structured-outputs-image.py

@@ -33,7 +33,7 @@ if not path.exists():
 
 # Set up chat as usual
 response = chat(
-  model='llama3.2-vision',
+  model='gemma3',
   format=ImageDescription.model_json_schema(),  # Pass in the schema for the response
   messages=[
     {

examples/thinking-generate.py

@@ -0,0 +1,6 @@
+from ollama import generate
+
+response = generate('deepseek-r1', 'why is the sky blue', think=True)
+
+print('Thinking:\n========\n\n' + response.thinking)
+print('\nResponse:\n========\n\n' + response.response)

examples/thinking-levels.py

@@ -0,0 +1,26 @@
+from ollama import chat
+
+
+def heading(text):
+  print(text)
+  print('=' * len(text))
+
+
+messages = [
+  {'role': 'user', 'content': 'What is 10 + 23?'},
+]
+
+# gpt-oss supports 'low', 'medium', 'high'
+levels = ['low', 'medium', 'high']
+for i, level in enumerate(levels):
+  response = chat('gpt-oss:20b', messages=messages, think=level)
+
+  heading(f'Thinking ({level})')
+  print(response.message.thinking)
+  print('\n')
+  heading('Response')
+  print(response.message.content)
+  print('\n')
+  if i < len(levels) - 1:
+    print('-' * 20)
+    print('\n')

examples/tools.py

@@ -74,7 +74,7 @@ if response.message.tool_calls:
 if response.message.tool_calls:
   # Add the function response to messages for the model to use
   messages.append(response.message)
-  messages.append({'role': 'tool', 'content': str(output), 'name': tool.function.name})
+  messages.append({'role': 'tool', 'content': str(output), 'tool_name': tool.function.name})
 
   # Get final response from model with function outputs
   final_response = chat('llama3.1', messages=messages)

examples/web-search-gpt-oss.py

@@ -0,0 +1,99 @@
+# /// script
+# requires-python = ">=3.11"
+# dependencies = [
+#     "ollama",
+# ]
+# ///
+from typing import Any, Dict, List
+
+from web_search_gpt_oss_helper import Browser
+
+from ollama import Client
+
+
+def main() -> None:
+  client = Client()
+  browser = Browser(initial_state=None, client=client)
+
+  def browser_search(query: str, topn: int = 10) -> str:
+    return browser.search(query=query, topn=topn)['pageText']
+
+  def browser_open(id: int | str | None = None, cursor: int = -1, loc: int = -1, num_lines: int = -1) -> str:
+    return browser.open(id=id, cursor=cursor, loc=loc, num_lines=num_lines)['pageText']
+
+  def browser_find(pattern: str, cursor: int = -1, **_: Any) -> str:
+    return browser.find(pattern=pattern, cursor=cursor)['pageText']
+
+  browser_search_schema = {
+    'type': 'function',
+    'function': {
+      'name': 'browser.search',
+    },
+  }
+
+  browser_open_schema = {
+    'type': 'function',
+    'function': {
+      'name': 'browser.open',
+    },
+  }
+
+  browser_find_schema = {
+    'type': 'function',
+    'function': {
+      'name': 'browser.find',
+    },
+  }
+
+  available_tools = {
+    'browser.search': browser_search,
+    'browser.open': browser_open,
+    'browser.find': browser_find,
+  }
+
+  query = "what is ollama's new engine"
+  print('Prompt:', query, '\n')
+
+  messages: List[Dict[str, Any]] = [{'role': 'user', 'content': query}]
+
+  while True:
+    resp = client.chat(
+      model='gpt-oss:120b-cloud',
+      messages=messages,
+      tools=[browser_search_schema, browser_open_schema, browser_find_schema],
+      think=True,
+    )
+
+    if resp.message.thinking:
+      print('Thinking:\n========\n')
+      print(resp.message.thinking + '\n')
+
+    if resp.message.content:
+      print('Response:\n========\n')
+      print(resp.message.content + '\n')
+
+    messages.append(resp.message)
+
+    if not resp.message.tool_calls:
+      break
+
+    for tc in resp.message.tool_calls:
+      tool_name = tc.function.name
+      args = tc.function.arguments or {}
+      print(f'Tool name: {tool_name}, args: {args}')
+      fn = available_tools.get(tool_name)
+      if not fn:
+        messages.append({'role': 'tool', 'content': f'Tool {tool_name} not found', 'tool_name': tool_name})
+        continue
+
+      try:
+        result_text = fn(**args)
+        print('Result: ', result_text[:200] + '...')
+      except Exception as e:
+        result_text = f'Error from {tool_name}: {e}'
+
+      messages.append({'role': 'tool', 'content': result_text, 'tool_name': tool_name})
+
+
+if __name__ == '__main__':
+  main()

examples/web-search-mcp.py

@@ -0,0 +1,116 @@
+# /// script
+# requires-python = ">=3.11"
+# dependencies = [
+#   "mcp",
+#   "rich",
+#   "ollama",
+# ]
+# ///
+"""
+MCP stdio server exposing Ollama web_search and web_fetch as tools.
+
+Environment:
+- OLLAMA_API_KEY (required): if set, will be used as Authorization header.
+"""
+
+from __future__ import annotations
+
+import asyncio
+from typing import Any, Dict
+
+from ollama import Client
+
+try:
+  # Preferred high-level API (if available)
+  from mcp.server.fastmcp import FastMCP  # type: ignore
+
+  _FASTMCP_AVAILABLE = True
+except Exception:
+  _FASTMCP_AVAILABLE = False
+
+if not _FASTMCP_AVAILABLE:
+  # Fallback to the low-level stdio server API
+  from mcp.server import Server  # type: ignore
+  from mcp.server.stdio import stdio_server  # type: ignore
+
+
+client = Client()
+
+
+def _web_search_impl(query: str, max_results: int = 3) -> Dict[str, Any]:
+  res = client.web_search(query=query, max_results=max_results)
+  return res.model_dump()
+
+
+def _web_fetch_impl(url: str) -> Dict[str, Any]:
+  res = client.web_fetch(url=url)
+  return res.model_dump()
+
+
+if _FASTMCP_AVAILABLE:
+  app = FastMCP('ollama-search-fetch')
+
+  @app.tool()
+  def web_search(query: str, max_results: int = 3) -> Dict[str, Any]:
+    """
+    Perform a web search using Ollama's hosted search API.
+
+    Args:
+      query: The search query to run.
+      max_results: Maximum results to return (default: 3).
+
+    Returns:
+      JSON-serializable dict matching ollama.WebSearchResponse.model_dump()
+    """
+
+    return _web_search_impl(query=query, max_results=max_results)
+
+  @app.tool()
+  def web_fetch(url: str) -> Dict[str, Any]:
+    """
+    Fetch the content of a web page for the provided URL.
+
+    Args:
+      url: The absolute URL to fetch.
+
+    Returns:
+      JSON-serializable dict matching ollama.WebFetchResponse.model_dump()
+    """
+
+    return _web_fetch_impl(url=url)
+
+  if __name__ == '__main__':
+    app.run()
+
+else:
+  server = Server('ollama-search-fetch')  # type: ignore[name-defined]
+
+  @server.tool()  # type: ignore[attr-defined]
+  async def web_search(query: str, max_results: int = 3) -> Dict[str, Any]:
+    """
+    Perform a web search using Ollama's hosted search API.
+
+    Args:
+      query: The search query to run.
+      max_results: Maximum results to return (default: 3).
+    """
+
+    return await asyncio.to_thread(_web_search_impl, query, max_results)
+
+  @server.tool()  # type: ignore[attr-defined]
+  async def web_fetch(url: str) -> Dict[str, Any]:
+    """
+    Fetch the content of a web page for the provided URL.
+
+    Args:
+      url: The absolute URL to fetch.
+    """
+
+    return await asyncio.to_thread(_web_fetch_impl, url)
+
+  async def _main() -> None:
+    async with stdio_server() as (read, write):  # type: ignore[name-defined]
+      await server.run(read, write)  # type: ignore[attr-defined]
+
+  if __name__ == '__main__':
+    asyncio.run(_main())

examples/web-search.py

@@ -0,0 +1,85 @@
+# /// script
+# requires-python = ">=3.11"
+# dependencies = [
+#     "rich",
+#     "ollama",
+# ]
+# ///
+from typing import Union
+
+from rich import print
+
+from ollama import WebFetchResponse, WebSearchResponse, chat, web_fetch, web_search
+
+
+def format_tool_results(
+  results: Union[WebSearchResponse, WebFetchResponse],
+  user_search: str,
+):
+  output = []
+  if isinstance(results, WebSearchResponse):
+    output.append(f'Search results for "{user_search}":')
+    for result in results.results:
+      output.append(f'{result.title}' if result.title else f'{result.content}')
+      output.append(f'   URL: {result.url}')
+      output.append(f'   Content: {result.content}')
+      output.append('')
+    return '\n'.join(output).rstrip()
+
+  elif isinstance(results, WebFetchResponse):
+    output.append(f'Fetch results for "{user_search}":')
+    output.extend(
+      [
+        f'Title: {results.title}',
+        f'URL: {user_search}' if user_search else '',
+        f'Content: {results.content}',
+      ]
+    )
+    if results.links:
+      output.append(f'Links: {", ".join(results.links)}')
+    output.append('')
+    return '\n'.join(output).rstrip()
+
+
+# client = Client(headers={'Authorization': f"Bearer {os.getenv('OLLAMA_API_KEY')}"} if api_key else None)
+available_tools = {'web_search': web_search, 'web_fetch': web_fetch}
+
+query = "what is ollama's new engine"
+print('Query: ', query)
+
+messages = [{'role': 'user', 'content': query}]
+while True:
+  response = chat(model='qwen3', messages=messages, tools=[web_search, web_fetch], think=True)
+  if response.message.thinking:
+    print('Thinking: ')
+    print(response.message.thinking + '\n\n')
+  if response.message.content:
+    print('Content: ')
+    print(response.message.content + '\n')
+
+  messages.append(response.message)
+
+  if response.message.tool_calls:
+    for tool_call in response.message.tool_calls:
+      function_to_call = available_tools.get(tool_call.function.name)
+      if function_to_call:
+        args = tool_call.function.arguments
+        result: Union[WebSearchResponse, WebFetchResponse] = function_to_call(**args)
+        print('Result from tool call name:', tool_call.function.name, 'with arguments:')
+        print(args)
+        print()
+
+        user_search = args.get('query', '') or args.get('url', '')
+        formatted_tool_results = format_tool_results(result, user_search=user_search)
+
+        print(formatted_tool_results[:300])
+        print()
+
+        # caps the result at ~2000 tokens
+        messages.append({'role': 'tool', 'content': formatted_tool_results[: 2000 * 4], 'tool_name': tool_call.function.name})
+      else:
+        print(f'Tool {tool_call.function.name} not found')
+        messages.append({'role': 'tool', 'content': f'Tool {tool_call.function.name} not found', 'tool_name': tool_call.function.name})
+  else:
+    # no more tool calls, we can stop the loop
+    break

examples/web_search_gpt_oss_helper.py

@@ -0,0 +1,514 @@
+from __future__ import annotations
+
+import re
+from dataclasses import dataclass, field
+from datetime import datetime
+from typing import Any, Dict, List, Optional, Protocol, Tuple
+from urllib.parse import urlparse
+
+from ollama import Client
+
+
+@dataclass
+class Page:
+  url: str
+  title: str
+  text: str
+  lines: List[str]
+  links: Dict[int, str]
+  fetched_at: datetime
+
+
+@dataclass
+class BrowserStateData:
+  page_stack: List[str] = field(default_factory=list)
+  view_tokens: int = 1024
+  url_to_page: Dict[str, Page] = field(default_factory=dict)
+
+
+@dataclass
+class WebSearchResult:
+  title: str
+  url: str
+  content: Dict[str, str]
+
+
+class SearchClient(Protocol):
+  def search(self, queries: List[str], max_results: Optional[int] = None): ...
+
+
+class CrawlClient(Protocol):
+  def crawl(self, urls: List[str]): ...
+
+
+# ---- Constants ---------------------------------------------------------------
+
+DEFAULT_VIEW_TOKENS = 1024
+CAPPED_TOOL_CONTENT_LEN = 8000
+
+# ---- Helpers ----------------------------------------------------------------
+
+
+def cap_tool_content(text: str) -> str:
+  if not text:
+    return text
+  if len(text) <= CAPPED_TOOL_CONTENT_LEN:
+    return text
+  if CAPPED_TOOL_CONTENT_LEN <= 1:
+    return text[:CAPPED_TOOL_CONTENT_LEN]
+  return text[: CAPPED_TOOL_CONTENT_LEN - 1] + '…'
+
+
+def _safe_domain(u: str) -> str:
+  try:
+    parsed = urlparse(u)
+    host = parsed.netloc or u
+    return host.replace('www.', '') if host else u
+  except Exception:
+    return u
+
+
+# ---- BrowserState ------------------------------------------------------------
+
+
+class BrowserState:
+  def __init__(self, initial_state: Optional[BrowserStateData] = None):
+    self._data = initial_state or BrowserStateData(view_tokens=DEFAULT_VIEW_TOKENS)
+
+  def get_data(self) -> BrowserStateData:
+    return self._data
+
+  def set_data(self, data: BrowserStateData) -> None:
+    self._data = data
+
+
+# ---- Browser ----------------------------------------------------------------
+
+
+class Browser:
+  def __init__(
+    self,
+    initial_state: Optional[BrowserStateData] = None,
+    client: Optional[Client] = None,
+  ):
+    self.state = BrowserState(initial_state)
+    self._client: Optional[Client] = client
+
+  def set_client(self, client: Client) -> None:
+    self._client = client
+
+  def get_state(self) -> BrowserStateData:
+    return self.state.get_data()
+
+  # ---- internal utils ----
+
+  def _save_page(self, page: Page) -> None:
+    data = self.state.get_data()
+    data.url_to_page[page.url] = page
+    data.page_stack.append(page.url)
+    self.state.set_data(data)
+
+  def _page_from_stack(self, url: str) -> Page:
+    data = self.state.get_data()
+    page = data.url_to_page.get(url)
+    if not page:
+      raise ValueError(f'Page not found for url {url}')
+    return page
+
+  def _join_lines_with_numbers(self, lines: List[str]) -> str:
+    result = []
+    for i, line in enumerate(lines):
+      result.append(f'L{i}: {line}')
+    return '\n'.join(result)
+
+  def _wrap_lines(self, text: str, width: int = 80) -> List[str]:
+    if width <= 0:
+      width = 80
+    src_lines = text.split('\n')
+    wrapped: List[str] = []
+    for line in src_lines:
+      if line == '':
+        wrapped.append('')
+      elif len(line) <= width:
+        wrapped.append(line)
+      else:
+        words = re.split(r'\s+', line)
+        if not words:
+          wrapped.append(line)
+          continue
+        curr = ''
+        for w in words:
+          test = (curr + ' ' + w) if curr else w
+          if len(test) > width and curr:
+            wrapped.append(curr)
+            curr = w
+          else:
+            curr = test
+        if curr:
+          wrapped.append(curr)
+    return wrapped
+
+  def _process_markdown_links(self, text: str) -> Tuple[str, Dict[int, str]]:
+    links: Dict[int, str] = {}
+    link_id = 0
+
+    multiline_pattern = re.compile(r'\[([^\]]+)\]\s*\n\s*\(([^)]+)\)')
+    text = multiline_pattern.sub(lambda m: f'[{m.group(1)}]({m.group(2)})', text)
+    text = re.sub(r'\s+', ' ', text)
+
+    link_pattern = re.compile(r'\[([^\]]+)\]\(([^)]+)\)')
+
+    def _repl(m: re.Match) -> str:
+      nonlocal link_id
+      link_text = m.group(1).strip()
+      link_url = m.group(2).strip()
+      domain = _safe_domain(link_url)
+      formatted = f'【{link_id}†{link_text}†{domain}】'
+      links[link_id] = link_url
+      link_id += 1
+      return formatted
+
+    processed = link_pattern.sub(_repl, text)
+    return processed, links
+
+  def _get_end_loc(self, loc: int, num_lines: int, total_lines: int, lines: List[str]) -> int:
+    if num_lines <= 0:
+      txt = self._join_lines_with_numbers(lines[loc:])
+      data = self.state.get_data()
+      chars_per_token = 4
+      max_chars = min(data.view_tokens * chars_per_token, len(txt))
+      num_lines = txt[:max_chars].count('\n') + 1
+    return min(loc + num_lines, total_lines)
+
+  def _display_page(self, page: Page, cursor: int, loc: int, num_lines: int) -> str:
+    total_lines = len(page.lines) or 0
+    if total_lines == 0:
+      page.lines = ['']
+      total_lines = 1
+
+    if loc != loc or loc < 0:
+      loc = 0
+    elif loc >= total_lines:
+      loc = max(0, total_lines - 1)
+
+    end_loc = self._get_end_loc(loc, num_lines, total_lines, page.lines)
+
+    header = f'[{cursor}] {page.title}'
+    header += f'({page.url})\n' if page.url else '\n'
+    header += f'**viewing lines [{loc} - {end_loc - 1}] of {total_lines - 1}**\n\n'
+
+    body_lines = []
+    for i in range(loc, end_loc):
+      body_lines.append(f'L{i}: {page.lines[i]}')
+
+    return header + '\n'.join(body_lines)
+
+  # ---- page builders ----
+
+  def _build_search_results_page_collection(self, query: str, results: Dict[str, Any]) -> Page:
+    page = Page(
+      url=f'search_results_{query}',
+      title=query,
+      text='',
+      lines=[],
+      links={},
+      fetched_at=datetime.utcnow(),
+    )
+
+    tb = []
+    tb.append('')
+    tb.append('# Search Results')
+    tb.append('')
+
+    link_idx = 0
+    for query_results in results.get('results', {}).values():
+      for result in query_results:
+        domain = _safe_domain(result.get('url', ''))
+        link_fmt = f'* 【{link_idx}†{result.get("title", "")}†{domain}】'
+        tb.append(link_fmt)
+
+        raw_snip = result.get('content') or ''
+        capped = (raw_snip[:400] + '…') if len(raw_snip) > 400 else raw_snip
+        cleaned = re.sub(r'\d{40,}', lambda m: m.group(0)[:40] + '…', capped)
+        cleaned = re.sub(r'\s{3,}', ' ', cleaned)
+        tb.append(cleaned)
+        page.links[link_idx] = result.get('url', '')
+        link_idx += 1
+
+    page.text = '\n'.join(tb)
+    page.lines = self._wrap_lines(page.text, 80)
+    return page
+
+  def _build_search_result_page(self, result: WebSearchResult, link_idx: int) -> Page:
+    page = Page(
+      url=result.url,
+      title=result.title,
+      text='',
+      lines=[],
+      links={},
+      fetched_at=datetime.utcnow(),
+    )
+
+    link_fmt = f'【{link_idx}†{result.title}】\n'
+    preview = link_fmt + f'URL: {result.url}\n'
+    full_text = result.content.get('fullText', '') if result.content else ''
+    preview += full_text[:300] + '\n\n'
+
+    if not full_text:
+      page.links[link_idx] = result.url
+
+    if full_text:
+      raw = f'URL: {result.url}\n{full_text}'
+      processed, links = self._process_markdown_links(raw)
+      page.text = processed
+      page.links = links
+    else:
+      page.text = preview
+
+    page.lines = self._wrap_lines(page.text, 80)
+    return page
+
+  def _build_page_from_fetch(self, requested_url: str, fetch_response: Dict[str, Any]) -> Page:
+    page = Page(
+      url=requested_url,
+      title=requested_url,
+      text='',
+      lines=[],
+      links={},
+      fetched_at=datetime.utcnow(),
+    )
+
+    for url, url_results in fetch_response.get('results', {}).items():
+      if url_results:
+        r0 = url_results[0]
+        if r0.get('content'):
+          page.text = r0['content']
+        if r0.get('title'):
+          page.title = r0['title']
+        page.url = url
+        break
+
+    if not page.text:
+      page.text = 'No content could be extracted from this page.'
+    else:
+      page.text = f'URL: {page.url}\n{page.text}'
+
+    processed, links = self._process_markdown_links(page.text)
+    page.text = processed
+    page.links = links
+    page.lines = self._wrap_lines(page.text, 80)
+    return page
+
+  def _build_find_results_page(self, pattern: str, page: Page) -> Page:
+    find_page = Page(
+      url=f'find_results_{pattern}',
+      title=f'Find results for text: `{pattern}` in `{page.title}`',
+      text='',
+      lines=[],
+      links={},
+      fetched_at=datetime.utcnow(),
+    )
+
+    max_results = 50
+    num_show_lines = 4
+    pattern_lower = pattern.lower()
+
+    result_chunks: List[str] = []
+    line_idx = 0
+    while line_idx < len(page.lines):
+      line = page.lines[line_idx]
+      if pattern_lower not in line.lower():
+        line_idx += 1
+        continue
+
+      end_line = min(line_idx + num_show_lines, len(page.lines))
+      snippet = '\n'.join(page.lines[line_idx:end_line])
+      link_fmt = f'【{len(result_chunks)}†match at L{line_idx}】'
+      result_chunks.append(f'{link_fmt}\n{snippet}')
+
+      if len(result_chunks) >= max_results:
+        break
+      line_idx += num_show_lines
+
+    if not result_chunks:
+      find_page.text = f'No `find` results for pattern: `{pattern}`'
+    else:
+      find_page.text = '\n\n'.join(result_chunks)
+
+    find_page.lines = self._wrap_lines(find_page.text, 80)
+    return find_page
+
+  # ---- public API: search / open / find ------------------------------------
+
+  def search(self, *, query: str, topn: int = 5) -> Dict[str, Any]:
+    if not self._client:
+      raise RuntimeError('Client not provided')
+
+    resp = self._client.web_search(query, max_results=topn)
+
+    normalized: Dict[str, Any] = {'results': {}}
+    rows: List[Dict[str, str]] = []
+    for item in resp.results:
+      content = item.content or ''
+      rows.append(
+        {
+          'title': item.title,
+          'url': item.url,
+          'content': content,
+        }
+      )
+    normalized['results'][query] = rows
+
+    search_page = self._build_search_results_page_collection(query, normalized)
+    self._save_page(search_page)
+    cursor = len(self.get_state().page_stack) - 1
+
+    for query_results in normalized.get('results', {}).values():
+      for i, r in enumerate(query_results):
+        ws = WebSearchResult(
+          title=r.get('title', ''),
+          url=r.get('url', ''),
+          content={'fullText': r.get('content', '') or ''},
+        )
+        result_page = self._build_search_result_page(ws, i + 1)
+        data = self.get_state()
+        data.url_to_page[result_page.url] = result_page
+        self.state.set_data(data)
+
+    page_text = self._display_page(search_page, cursor, loc=0, num_lines=-1)
+    return {'state': self.get_state(), 'pageText': cap_tool_content(page_text)}
+
+  def open(
+    self,
+    *,
+    id: Optional[str | int] = None,
+    cursor: int = -1,
+    loc: int = 0,
+    num_lines: int = -1,
+  ) -> Dict[str, Any]:
+    if not self._client:
+      raise RuntimeError('Client not provided')
+
+    state = self.get_state()
+
+    if isinstance(id, str):
+      url = id
+      if url in state.url_to_page:
+        self._save_page(state.url_to_page[url])
+        cursor = len(self.get_state().page_stack) - 1
+        page_text = self._display_page(state.url_to_page[url], cursor, loc, num_lines)
+        return {'state': self.get_state(), 'pageText': cap_tool_content(page_text)}
+
+      fetch_response = self._client.web_fetch(url)
+      normalized: Dict[str, Any] = {
+        'results': {
+          url: [
+            {
+              'title': fetch_response.title or url,
+              'url': url,
+              'content': fetch_response.content or '',
+            }
+          ]
+        }
+      }
+      new_page = self._build_page_from_fetch(url, normalized)
+      self._save_page(new_page)
+      cursor = len(self.get_state().page_stack) - 1
+      page_text = self._display_page(new_page, cursor, loc, num_lines)
+      return {'state': self.get_state(), 'pageText': cap_tool_content(page_text)}
+
+    # Resolve current page from stack only if needed (int id or no id)
+    page: Optional[Page] = None
+    if cursor >= 0:
+      if state.page_stack:
+        if cursor >= len(state.page_stack):
+          cursor = max(0, len(state.page_stack) - 1)
+        page = self._page_from_stack(state.page_stack[cursor])
+      else:
+        page = None
+    else:
+      if state.page_stack:
+        page = self._page_from_stack(state.page_stack[-1])
+
+    if isinstance(id, int):
+      if not page:
+        raise RuntimeError('No current page to resolve link from')
+
+      link_url = page.links.get(id)
+      if not link_url:
+        err = Page(
+          url=f'invalid_link_{id}',
+          title=f'No link with id {id} on `{page.title}`',
+          text='',
+          lines=[],
+          links={},
+          fetched_at=datetime.utcnow(),
+        )
+        available = sorted(page.links.keys())
+        available_list = ', '.join(map(str, available)) if available else '(none)'
+        err.text = '\n'.join(
+          [
+            f'Requested link id: {id}',
+            f'Current page: {page.title}',
+            f'Available link ids on this page: {available_list}',
+            '',
+            'Tips:',
+            '- To scroll this page, call browser_open with { loc, num_lines } (no id).',
+            '- To open a result from a search results page, pass the correct { cursor, id }.',
+          ]
+        )
+        err.lines = self._wrap_lines(err.text, 80)
+        self._save_page(err)
+        cursor = len(self.get_state().page_stack) - 1
+        page_text = self._display_page(err, cursor, 0, -1)
+        return {'state': self.get_state(), 'pageText': cap_tool_content(page_text)}
+
+      new_page = state.url_to_page.get(link_url)
+      if not new_page:
+        fetch_response = self._client.web_fetch(link_url)
+        normalized: Dict[str, Any] = {
+          'results': {
+            link_url: [
+              {
+                'title': fetch_response.title or link_url,
+                'url': link_url,
+                'content': fetch_response.content or '',
+              }
+            ]
+          }
+        }
+        new_page = self._build_page_from_fetch(link_url, normalized)
+
+      self._save_page(new_page)
+      cursor = len(self.get_state().page_stack) - 1
+      page_text = self._display_page(new_page, cursor, loc, num_lines)
+      return {'state': self.get_state(), 'pageText': cap_tool_content(page_text)}
+
+    if not page:
+      raise RuntimeError('No current page to display')
+
+    cur = self.get_state()
+    cur.page_stack.append(page.url)
+    self.state.set_data(cur)
+    cursor = len(cur.page_stack) - 1
+    page_text = self._display_page(page, cursor, loc, num_lines)
+    return {'state': self.get_state(), 'pageText': cap_tool_content(page_text)}
+
+  def find(self, *, pattern: str, cursor: int = -1) -> Dict[str, Any]:
+    state = self.get_state()
+    if cursor == -1:
+      if not state.page_stack:
+        raise RuntimeError('No pages to search in')
+      page = self._page_from_stack(state.page_stack[-1])
+      cursor = len(state.page_stack) - 1
+    else:
+      if cursor < 0 or cursor >= len(state.page_stack):
+        cursor = max(0, min(cursor, len(state.page_stack) - 1))
+      page = self._page_from_stack(state.page_stack[cursor])
+
+    find_page = self._build_find_results_page(pattern, page)
+    self._save_page(find_page)
+    new_cursor = len(self.get_state().page_stack) - 1
+
+    page_text = self._display_page(find_page, new_cursor, 0, -1)
+    return {'state': self.get_state(), 'pageText': cap_tool_content(page_text)}

ollama/__init__.py

@@ -15,6 +15,8 @@ from ollama._types import (
   ShowResponse,
   StatusResponse,
   Tool,
+  WebFetchResponse,
+  WebSearchResponse,
 )
 
 __all__ = [
@@ -35,6 +37,8 @@ __all__ = [
   'ShowResponse',
   'StatusResponse',
   'Tool',
+  'WebFetchResponse',
+  'WebSearchResponse',
 ]
 
 _client = Client()
@@ -51,3 +55,5 @@ list = _client.list
 copy = _client.copy
 show = _client.show
 ps = _client.ps
+web_search = _client.web_search
+web_fetch = _client.web_fetch

ollama/_client.py

@@ -1,3 +1,4 @@
+import contextlib
 import ipaddress
 import json
 import os
@@ -66,12 +67,16 @@ from ollama._types import (
   ShowResponse,
   StatusResponse,
   Tool,
+  WebFetchRequest,
+  WebFetchResponse,
+  WebSearchRequest,
+  WebSearchResponse,
 )
 
 T = TypeVar('T')
 
 
-class BaseClient:
+class BaseClient(contextlib.AbstractContextManager, contextlib.AbstractAsyncContextManager):
   def __init__(
     self,
     client,
@@ -90,11 +95,6 @@ class BaseClient:
     `kwargs` are passed to the httpx client.
     """
 
-    self._client = client(
-      base_url=_parse_host(host or os.getenv('OLLAMA_HOST')),
-      follow_redirects=follow_redirects,
-      timeout=timeout,
-      # Lowercase all headers to ensure override
     headers = {
       k.lower(): v
       for k, v in {
@@ -103,10 +103,26 @@ class BaseClient:
         'Accept': 'application/json',
         'User-Agent': f'ollama-python/{__version__} ({platform.machine()} {platform.system().lower()}) Python/{platform.python_version()}',
       }.items()
-      },
+      if v is not None
+    }
+    api_key = os.getenv('OLLAMA_API_KEY', None)
+    if not headers.get('authorization') and api_key:
+      headers['authorization'] = f'Bearer {api_key}'
+
+    self._client = client(
+      base_url=_parse_host(host or os.getenv('OLLAMA_HOST')),
+      follow_redirects=follow_redirects,
+      timeout=timeout,
+      headers=headers,
       **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'
 
@@ -115,6 +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)
@@ -190,6 +209,9 @@ class Client(BaseClient):
     template: str = '',
     context: Optional[Sequence[int]] = None,
     stream: Literal[False] = False,
+    think: Optional[bool] = None,
+    logprobs: Optional[bool] = None,
+    top_logprobs: Optional[int] = None,
     raw: bool = False,
     format: Optional[Union[Literal['', 'json'], JsonSchemaValue]] = None,
     images: Optional[Sequence[Union[str, bytes, Image]]] = None,
@@ -208,6 +230,9 @@ class Client(BaseClient):
     template: str = '',
     context: Optional[Sequence[int]] = None,
     stream: Literal[True] = True,
+    think: Optional[bool] = None,
+    logprobs: Optional[bool] = None,
+    top_logprobs: Optional[int] = None,
     raw: bool = False,
     format: Optional[Union[Literal['', 'json'], JsonSchemaValue]] = None,
     images: Optional[Sequence[Union[str, bytes, Image]]] = None,
@@ -225,6 +250,9 @@ class Client(BaseClient):
     template: Optional[str] = None,
     context: Optional[Sequence[int]] = None,
     stream: bool = False,
+    think: Optional[bool] = None,
+    logprobs: Optional[bool] = None,
+    top_logprobs: Optional[int] = None,
     raw: Optional[bool] = None,
     format: Optional[Union[Literal['', 'json'], JsonSchemaValue]] = None,
     images: Optional[Sequence[Union[str, bytes, Image]]] = None,
@@ -253,6 +281,9 @@ class Client(BaseClient):
         template=template,
         context=context,
         stream=stream,
+        think=think,
+        logprobs=logprobs,
+        top_logprobs=top_logprobs,
         raw=raw,
         format=format,
         images=list(_copy_images(images)) if images else None,
@@ -270,7 +301,9 @@ class Client(BaseClient):
     *,
     tools: Optional[Sequence[Union[Mapping[str, Any], Tool, Callable]]] = None,
     stream: Literal[False] = False,
-    think: Optional[bool] = None,
+    think: Optional[Union[bool, Literal['low', 'medium', 'high']]] = None,
+    logprobs: Optional[bool] = None,
+    top_logprobs: Optional[int] = None,
     format: Optional[Union[Literal['', 'json'], JsonSchemaValue]] = None,
     options: Optional[Union[Mapping[str, Any], Options]] = None,
     keep_alive: Optional[Union[float, str]] = None,
@@ -284,7 +317,9 @@ class Client(BaseClient):
     *,
     tools: Optional[Sequence[Union[Mapping[str, Any], Tool, Callable]]] = None,
     stream: Literal[True] = True,
-    think: Optional[bool] = None,
+    think: Optional[Union[bool, Literal['low', 'medium', 'high']]] = None,
+    logprobs: Optional[bool] = None,
+    top_logprobs: Optional[int] = None,
     format: Optional[Union[Literal['', 'json'], JsonSchemaValue]] = None,
     options: Optional[Union[Mapping[str, Any], Options]] = None,
     keep_alive: Optional[Union[float, str]] = None,
@@ -297,7 +332,9 @@ class Client(BaseClient):
     *,
     tools: Optional[Sequence[Union[Mapping[str, Any], Tool, Callable]]] = None,
     stream: bool = False,
-    think: Optional[bool] = None,
+    think: Optional[Union[bool, Literal['low', 'medium', 'high']]] = None,
+    logprobs: Optional[bool] = None,
+    top_logprobs: Optional[int] = None,
     format: Optional[Union[Literal['', 'json'], JsonSchemaValue]] = None,
     options: Optional[Union[Mapping[str, Any], Options]] = None,
     keep_alive: Optional[Union[float, str]] = None,
@@ -345,6 +382,8 @@ class Client(BaseClient):
         tools=list(_copy_tools(tools)),
         stream=stream,
         think=think,
+        logprobs=logprobs,
+        top_logprobs=top_logprobs,
         format=format,
         options=options,
         keep_alive=keep_alive,
@@ -359,6 +398,7 @@ class Client(BaseClient):
     truncate: Optional[bool] = None,
     options: Optional[Union[Mapping[str, Any], Options]] = None,
     keep_alive: Optional[Union[float, str]] = None,
+    dimensions: Optional[int] = None,
   ) -> EmbedResponse:
     return self._request(
       EmbedResponse,
@@ -370,6 +410,7 @@ class Client(BaseClient):
         truncate=truncate,
         options=options,
         keep_alive=keep_alive,
+        dimensions=dimensions,
       ).model_dump(exclude_none=True),
     )
 
@@ -618,11 +659,62 @@ class Client(BaseClient):
       '/api/ps',
     )
 
+  def web_search(self, query: str, max_results: int = 3) -> WebSearchResponse:
+    """
+    Performs a web search
+
+    Args:
+      query: The query to search for
+      max_results: The maximum number of results to return (default: 3)
+
+    Returns:
+      WebSearchResponse with the search results
+    Raises:
+      ValueError: If OLLAMA_API_KEY environment variable is not set
+    """
+    if not self._client.headers.get('authorization', '').startswith('Bearer '):
+      raise ValueError('Authorization header with Bearer token is required for web search')
+
+    return self._request(
+      WebSearchResponse,
+      'POST',
+      'https://ollama.com/api/web_search',
+      json=WebSearchRequest(
+        query=query,
+        max_results=max_results,
+      ).model_dump(exclude_none=True),
+    )
+
+  def web_fetch(self, url: str) -> WebFetchResponse:
+    """
+    Fetches the content of a web page for the provided URL.
+
+    Args:
+      url: The URL to fetch
+
+    Returns:
+      WebFetchResponse with the fetched result
+    """
+    if not self._client.headers.get('authorization', '').startswith('Bearer '):
+      raise ValueError('Authorization header with Bearer token is required for web fetch')
+
+    return self._request(
+      WebFetchResponse,
+      'POST',
+      'https://ollama.com/api/web_fetch',
+      json=WebFetchRequest(
+        url=url,
+      ).model_dump(exclude_none=True),
+    )
+
 
 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)
@@ -687,6 +779,46 @@ class AsyncClient(BaseClient):
 
     return cls(**(await self._request_raw(*args, **kwargs)).json())
 
+  async def web_search(self, query: str, max_results: int = 3) -> WebSearchResponse:
+    """
+    Performs a web search
+
+    Args:
+      query: The query to search for
+      max_results: The maximum number of results to return (default: 3)
+
+    Returns:
+      WebSearchResponse with the search results
+    """
+    return await self._request(
+      WebSearchResponse,
+      'POST',
+      'https://ollama.com/api/web_search',
+      json=WebSearchRequest(
+        query=query,
+        max_results=max_results,
+      ).model_dump(exclude_none=True),
+    )
+
+  async def web_fetch(self, url: str) -> WebFetchResponse:
+    """
+    Fetches the content of a web page for the provided URL.
+
+    Args:
+      url: The URL to fetch
+
+    Returns:
+      WebFetchResponse with the fetched result
+    """
+    return await self._request(
+      WebFetchResponse,
+      'POST',
+      'https://ollama.com/api/web_fetch',
+      json=WebFetchRequest(
+        url=url,
+      ).model_dump(exclude_none=True),
+    )
+
   @overload
   async def generate(
     self,
@@ -698,7 +830,9 @@ class AsyncClient(BaseClient):
     template: str = '',
     context: Optional[Sequence[int]] = None,
     stream: Literal[False] = False,
-    think: Optional[bool] = None,
+    think: Optional[Union[bool, Literal['low', 'medium', 'high']]] = None,
+    logprobs: Optional[bool] = None,
+    top_logprobs: Optional[int] = None,
     raw: bool = False,
     format: Optional[Union[Literal['', 'json'], JsonSchemaValue]] = None,
     images: Optional[Sequence[Union[str, bytes, Image]]] = None,
@@ -717,7 +851,9 @@ class AsyncClient(BaseClient):
     template: str = '',
     context: Optional[Sequence[int]] = None,
     stream: Literal[True] = True,
-    think: Optional[bool] = None,
+    think: Optional[Union[bool, Literal['low', 'medium', 'high']]] = None,
+    logprobs: Optional[bool] = None,
+    top_logprobs: Optional[int] = None,
     raw: bool = False,
     format: Optional[Union[Literal['', 'json'], JsonSchemaValue]] = None,
     images: Optional[Sequence[Union[str, bytes, Image]]] = None,
@@ -735,7 +871,9 @@ class AsyncClient(BaseClient):
     template: Optional[str] = None,
     context: Optional[Sequence[int]] = None,
     stream: bool = False,
-    think: Optional[bool] = None,
+    think: Optional[Union[bool, Literal['low', 'medium', 'high']]] = None,
+    logprobs: Optional[bool] = None,
+    top_logprobs: Optional[int] = None,
     raw: Optional[bool] = None,
     format: Optional[Union[Literal['', 'json'], JsonSchemaValue]] = None,
     images: Optional[Sequence[Union[str, bytes, Image]]] = None,
@@ -764,6 +902,8 @@ class AsyncClient(BaseClient):
         context=context,
         stream=stream,
         think=think,
+        logprobs=logprobs,
+        top_logprobs=top_logprobs,
         raw=raw,
         format=format,
         images=list(_copy_images(images)) if images else None,
@@ -781,7 +921,9 @@ class AsyncClient(BaseClient):
     *,
     tools: Optional[Sequence[Union[Mapping[str, Any], Tool, Callable]]] = None,
     stream: Literal[False] = False,
-    think: Optional[bool] = None,
+    think: Optional[Union[bool, Literal['low', 'medium', 'high']]] = None,
+    logprobs: Optional[bool] = None,
+    top_logprobs: Optional[int] = None,
     format: Optional[Union[Literal['', 'json'], JsonSchemaValue]] = None,
     options: Optional[Union[Mapping[str, Any], Options]] = None,
     keep_alive: Optional[Union[float, str]] = None,
@@ -795,7 +937,9 @@ class AsyncClient(BaseClient):
     *,
     tools: Optional[Sequence[Union[Mapping[str, Any], Tool, Callable]]] = None,
     stream: Literal[True] = True,
-    think: Optional[bool] = None,
+    think: Optional[Union[bool, Literal['low', 'medium', 'high']]] = None,
+    logprobs: Optional[bool] = None,
+    top_logprobs: Optional[int] = None,
     format: Optional[Union[Literal['', 'json'], JsonSchemaValue]] = None,
     options: Optional[Union[Mapping[str, Any], Options]] = None,
     keep_alive: Optional[Union[float, str]] = None,
@@ -808,7 +952,9 @@ class AsyncClient(BaseClient):
     *,
     tools: Optional[Sequence[Union[Mapping[str, Any], Tool, Callable]]] = None,
     stream: bool = False,
-    think: Optional[bool] = None,
+    think: Optional[Union[bool, Literal['low', 'medium', 'high']]] = None,
+    logprobs: Optional[bool] = None,
+    top_logprobs: Optional[int] = None,
     format: Optional[Union[Literal['', 'json'], JsonSchemaValue]] = None,
     options: Optional[Union[Mapping[str, Any], Options]] = None,
     keep_alive: Optional[Union[float, str]] = None,
@@ -857,6 +1003,8 @@ class AsyncClient(BaseClient):
         tools=list(_copy_tools(tools)),
         stream=stream,
         think=think,
+        logprobs=logprobs,
+        top_logprobs=top_logprobs,
         format=format,
         options=options,
         keep_alive=keep_alive,
@@ -871,6 +1019,7 @@ class AsyncClient(BaseClient):
     truncate: Optional[bool] = None,
     options: Optional[Union[Mapping[str, Any], Options]] = None,
     keep_alive: Optional[Union[float, str]] = None,
+    dimensions: Optional[int] = None,
   ) -> EmbedResponse:
     return await self._request(
       EmbedResponse,
@@ -882,6 +1031,7 @@ class AsyncClient(BaseClient):
         truncate=truncate,
         options=options,
         keep_alive=keep_alive,
+        dimensions=dimensions,
       ).model_dump(exclude_none=True),
     )
 

ollama/_types.py

@@ -79,7 +79,7 @@ class SubscriptableBaseModel(BaseModel):
     if key in self.model_fields_set:
       return True
 
-    if value := self.model_fields.get(key):
+    if value := self.__class__.model_fields.get(key):
       return value.default is not None
 
     return False
@@ -207,9 +207,15 @@ class GenerateRequest(BaseGenerateRequest):
   images: Optional[Sequence[Image]] = None
   'Image data for multimodal models.'
 
-  think: Optional[bool] = None
+  think: Optional[Union[bool, Literal['low', 'medium', 'high']]] = None
   'Enable thinking mode (for thinking models).'
 
+  logprobs: Optional[bool] = None
+  'Return log probabilities for generated tokens.'
+
+  top_logprobs: Optional[int] = None
+  'Number of alternative tokens and log probabilities to include per position (0-20).'
+
 
 class BaseGenerateResponse(SubscriptableBaseModel):
   model: Optional[str] = None
@@ -243,6 +249,19 @@ class BaseGenerateResponse(SubscriptableBaseModel):
   'Duration of evaluating inference in nanoseconds.'
 
 
+class TokenLogprob(SubscriptableBaseModel):
+  token: str
+  'Token text.'
+
+  logprob: float
+  'Log probability for the token.'
+
+
+class Logprob(TokenLogprob):
+  top_logprobs: Optional[Sequence[TokenLogprob]] = None
+  'Most likely tokens and their log probabilities.'
+
+
 class GenerateResponse(BaseGenerateResponse):
   """
   Response returned by generate requests.
@@ -257,6 +276,9 @@ class GenerateResponse(BaseGenerateResponse):
   context: Optional[Sequence[int]] = None
   'Tokenized history up to the point of the response.'
 
+  logprobs: Optional[Sequence[Logprob]] = None
+  'Log probabilities for generated tokens.'
+
 
 class Message(SubscriptableBaseModel):
   """
@@ -284,6 +306,9 @@ class Message(SubscriptableBaseModel):
   Valid image formats depend on the model. See the model card for more information.
   """
 
+  tool_name: Optional[str] = None
+  'Name of the executed tool.'
+
   class ToolCall(SubscriptableBaseModel):
     """
     Model tool calls.
@@ -310,7 +335,7 @@ class Message(SubscriptableBaseModel):
 
 
 class Tool(SubscriptableBaseModel):
-  type: Optional[Literal['function']] = 'function'
+  type: Optional[str] = 'function'
 
   class Function(SubscriptableBaseModel):
     name: Optional[str] = None
@@ -354,9 +379,15 @@ class ChatRequest(BaseGenerateRequest):
   tools: Optional[Sequence[Tool]] = None
   'Tools to use for the chat.'
 
-  think: Optional[bool] = None
+  think: Optional[Union[bool, Literal['low', 'medium', 'high']]] = None
   'Enable thinking mode (for thinking models).'
 
+  logprobs: Optional[bool] = None
+  'Return log probabilities for generated tokens.'
+
+  top_logprobs: Optional[int] = None
+  'Number of alternative tokens and log probabilities to include per position (0-20).'
+
 
 class ChatResponse(BaseGenerateResponse):
   """
@@ -366,6 +397,9 @@ class ChatResponse(BaseGenerateResponse):
   message: Message
   'Response message.'
 
+  logprobs: Optional[Sequence[Logprob]] = None
+  'Log probabilities for generated tokens if requested.'
+
 
 class EmbedRequest(BaseRequest):
   input: Union[str, Sequence[str]]
@@ -379,6 +413,9 @@ class EmbedRequest(BaseRequest):
 
   keep_alive: Optional[Union[float, str]] = None
 
+  dimensions: Optional[int] = None
+  'Dimensions truncates the output embedding to the specified dimension.'
+
 
 class EmbedResponse(BaseGenerateResponse):
   """
@@ -530,10 +567,36 @@ class ProcessResponse(SubscriptableBaseModel):
     size: Optional[ByteSize] = None
     size_vram: Optional[ByteSize] = None
     details: Optional[ModelDetails] = None
+    context_length: Optional[int] = None
 
   models: Sequence[Model]
 
 
+class WebSearchRequest(SubscriptableBaseModel):
+  query: str
+  max_results: Optional[int] = None
+
+
+class WebSearchResult(SubscriptableBaseModel):
+  content: Optional[str] = None
+  title: Optional[str] = None
+  url: Optional[str] = None
+
+
+class WebFetchRequest(SubscriptableBaseModel):
+  url: str
+
+
+class WebSearchResponse(SubscriptableBaseModel):
+  results: Sequence[WebSearchResult]
+
+
+class WebFetchResponse(SubscriptableBaseModel):
+  title: Optional[str] = None
+  content: Optional[str] = None
+  links: Optional[Sequence[str]] = None
+
+
 class RequestError(Exception):
   """
   Common class for request errors.

ollama/_utils.py

@@ -79,11 +79,12 @@ def convert_function_to_tool(func: Callable) -> Tool:
     }
 
   tool = Tool(
+    type='function',
     function=Tool.Function(
       name=func.__name__,
       description=schema.get('description', ''),
       parameters=Tool.Function.Parameters(**schema),
-    )
+    ),
   )
 
   return Tool.model_validate(tool)

pyproject.toml

@@ -11,6 +11,7 @@ dependencies = [
     'pydantic>=2.9',
 ]
 dynamic = [ 'version' ]
+license = "MIT"
 
 [project.urls]
 homepage = 'https://ollama.com'
@@ -36,7 +37,7 @@ dependencies = [ 'ruff>=0.9.1' ]
 config-path = 'none'
 
 [tool.ruff]
-line-length = 999
+line-length = 320 
 indent-width = 2
 
 [tool.ruff.format]
@@ -60,6 +61,7 @@ select = [
     'FLY', # flynt
     'RUF', # ruff-specific rules
 ]
+ignore = ['FBT001'] # Boolean-typed positional argument in function definition
 
 [tool.pytest.ini_options]
 addopts = ['--doctest-modules']

tests/test_client.py

@@ -8,7 +8,7 @@ from typing import Any
 
 import pytest
 from httpx import Response as httpxResponse
-from pydantic import BaseModel, ValidationError
+from pydantic import BaseModel
 from pytest_httpserver import HTTPServer, URIPattern
 from werkzeug.wrappers import Request, Response
 
@@ -61,6 +61,44 @@ def test_client_chat(httpserver: HTTPServer):
   assert response['message']['content'] == "I don't know."
 
 
+def test_client_chat_with_logprobs(httpserver: HTTPServer):
+  httpserver.expect_ordered_request(
+    '/api/chat',
+    method='POST',
+    json={
+      'model': 'dummy',
+      'messages': [{'role': 'user', 'content': 'Hi'}],
+      'tools': [],
+      'stream': False,
+      'logprobs': True,
+      'top_logprobs': 3,
+    },
+  ).respond_with_json(
+    {
+      'model': 'dummy',
+      'message': {
+        'role': 'assistant',
+        'content': 'Hello',
+      },
+      'logprobs': [
+        {
+          'token': 'Hello',
+          'logprob': -0.1,
+          'top_logprobs': [
+            {'token': 'Hello', 'logprob': -0.1},
+            {'token': 'Hi', 'logprob': -1.0},
+          ],
+        }
+      ],
+    }
+  )
+
+  client = Client(httpserver.url_for('/'))
+  response = client.chat('dummy', messages=[{'role': 'user', 'content': 'Hi'}], logprobs=True, top_logprobs=3)
+  assert response['logprobs'][0]['token'] == 'Hello'
+  assert response['logprobs'][0]['top_logprobs'][1]['token'] == 'Hi'
+
+
 def test_client_chat_stream(httpserver: HTTPServer):
   def stream_handler(_: Request):
     def generate():
@@ -294,6 +332,40 @@ def test_client_generate(httpserver: HTTPServer):
   assert response['response'] == 'Because it is.'
 
 
+def test_client_generate_with_logprobs(httpserver: HTTPServer):
+  httpserver.expect_ordered_request(
+    '/api/generate',
+    method='POST',
+    json={
+      'model': 'dummy',
+      'prompt': 'Why',
+      'stream': False,
+      'logprobs': True,
+      'top_logprobs': 2,
+    },
+  ).respond_with_json(
+    {
+      'model': 'dummy',
+      'response': 'Hello',
+      'logprobs': [
+        {
+          'token': 'Hello',
+          'logprob': -0.2,
+          'top_logprobs': [
+            {'token': 'Hello', 'logprob': -0.2},
+            {'token': 'Hi', 'logprob': -1.5},
+          ],
+        }
+      ],
+    }
+  )
+
+  client = Client(httpserver.url_for('/'))
+  response = client.generate('dummy', 'Why', logprobs=True, top_logprobs=2)
+  assert response['logprobs'][0]['token'] == 'Hello'
+  assert response['logprobs'][0]['top_logprobs'][1]['token'] == 'Hi'
+
+
 def test_client_generate_with_image_type(httpserver: HTTPServer):
   httpserver.expect_ordered_request(
     '/api/generate',
@@ -1136,10 +1208,11 @@ def test_copy_tools():
 
 
 def test_tool_validation():
-  # Raises ValidationError when used as it is a generator
+  arbitrary_tool = {'type': 'custom_type', 'function': {'name': 'test'}}
-  with pytest.raises(ValidationError):
+  tools = list(_copy_tools([arbitrary_tool]))
-    invalid_tool = {'type': 'invalid_type', 'function': {'name': 'test'}}
+  assert len(tools) == 1
-    list(_copy_tools([invalid_tool]))
+  assert tools[0].type == 'custom_type'
+  assert tools[0].function.name == 'test'
 
 
 def test_client_connection_error():
@@ -1194,3 +1267,113 @@ async def test_arbitrary_roles_accepted_in_message_request_async(monkeypatch: py
   client = AsyncClient()
 
   await client.chat(model='llama3.1', messages=[{'role': 'somerandomrole', 'content': "I'm ok with you adding any role message now!"}, {'role': 'user', 'content': 'Hello world!'}])
+
+
+def test_client_web_search_requires_bearer_auth_header(monkeypatch: pytest.MonkeyPatch):
+  monkeypatch.delenv('OLLAMA_API_KEY', raising=False)
+
+  client = Client()
+
+  with pytest.raises(ValueError, match='Authorization header with Bearer token is required for web search'):
+    client.web_search('test query')
+
+
+def test_client_web_fetch_requires_bearer_auth_header(monkeypatch: pytest.MonkeyPatch):
+  monkeypatch.delenv('OLLAMA_API_KEY', raising=False)
+
+  client = Client()
+
+  with pytest.raises(ValueError, match='Authorization header with Bearer token is required for web fetch'):
+    client.web_fetch('https://example.com')
+
+
+def _mock_request_web_search(self, cls, method, url, json=None, **kwargs):
+  assert method == 'POST'
+  assert url == 'https://ollama.com/api/web_search'
+  assert json is not None and 'query' in json and 'max_results' in json
+  return httpxResponse(status_code=200, content='{"results": {}, "success": true}')
+
+
+def _mock_request_web_fetch(self, cls, method, url, json=None, **kwargs):
+  assert method == 'POST'
+  assert url == 'https://ollama.com/api/web_fetch'
+  assert json is not None and 'url' in json
+  return httpxResponse(status_code=200, content='{"results": {}, "success": true}')
+
+
+def test_client_web_search_with_env_api_key(monkeypatch: pytest.MonkeyPatch):
+  monkeypatch.setenv('OLLAMA_API_KEY', 'test-key')
+  monkeypatch.setattr(Client, '_request', _mock_request_web_search)
+
+  client = Client()
+  client.web_search('what is ollama?', max_results=2)
+
+
+def test_client_web_fetch_with_env_api_key(monkeypatch: pytest.MonkeyPatch):
+  monkeypatch.setenv('OLLAMA_API_KEY', 'test-key')
+  monkeypatch.setattr(Client, '_request', _mock_request_web_fetch)
+
+  client = Client()
+  client.web_fetch('https://example.com')
+
+
+def test_client_web_search_with_explicit_bearer_header(monkeypatch: pytest.MonkeyPatch):
+  monkeypatch.delenv('OLLAMA_API_KEY', raising=False)
+  monkeypatch.setattr(Client, '_request', _mock_request_web_search)
+
+  client = Client(headers={'Authorization': 'Bearer custom-token'})
+  client.web_search('what is ollama?', max_results=1)
+
+
+def test_client_web_fetch_with_explicit_bearer_header(monkeypatch: pytest.MonkeyPatch):
+  monkeypatch.delenv('OLLAMA_API_KEY', raising=False)
+  monkeypatch.setattr(Client, '_request', _mock_request_web_fetch)
+
+  client = Client(headers={'Authorization': 'Bearer custom-token'})
+  client.web_fetch('https://example.com')
+
+
+def test_client_bearer_header_from_env(monkeypatch: pytest.MonkeyPatch):
+  monkeypatch.setenv('OLLAMA_API_KEY', 'env-token')
+
+  client = Client()
+  assert client._client.headers['authorization'] == 'Bearer env-token'
+
+
+def test_client_explicit_bearer_header_overrides_env(monkeypatch: pytest.MonkeyPatch):
+  monkeypatch.setenv('OLLAMA_API_KEY', 'env-token')
+  monkeypatch.setattr(Client, '_request', _mock_request_web_search)
+
+  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