more wip

Resolves #554

.github/workflows/publish.yaml

@@ -13,7 +13,7 @@ jobs:
       id-token: write
       contents: write
     steps:
-      - uses: actions/checkout@v4
+      - uses: actions/checkout@v5
       - uses: actions/setup-python@v5
       - 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@v4
+      - uses: actions/checkout@v5
       - uses: astral-sh/setup-uv@v5
         with:
           enable-cache: true
@@ -19,7 +19,7 @@ jobs:
   lint:
     runs-on: ubuntu-latest
     steps:
-      - uses: actions/checkout@v4
+      - uses: actions/checkout@v5
       - uses: actions/setup-python@v5
       - uses: astral-sh/setup-uv@v5
         with:

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,
 )
@@ -61,7 +61,7 @@ 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 +79,7 @@ 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 +92,7 @@ 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 +105,13 @@ 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 +123,49 @@ 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

@@ -27,6 +27,12 @@ See [ollama/docs/api.md](https://github.com/ollama/ollama/blob/main/docs/api.md)
 - [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) 
+- [gpt-oss-tools-browser.py](gpt-oss-tools-browser.py) - Using browser research tools with gpt-oss
+- [gpt-oss-tools-browser-stream.py](gpt-oss-tools-browser-stream.py) - Using browser research tools with gpt-oss, with streaming enabled
+
 
 ### Multimodal with Images - Chat with a multimodal (image chat) model
 - [multimodal-chat.py](multimodal-chat.py)
@@ -69,3 +75,6 @@ Requirement: `pip install tqdm`
 
 ### 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/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

@@ -22,7 +22,7 @@ messages = [
 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-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-browser-stream.py

@@ -0,0 +1,198 @@
+# /// script
+# requires-python = ">=3.11"
+# dependencies = [
+#     "gpt-oss",
+#     "ollama",
+#     "rich",
+# ]
+# ///
+
+import asyncio
+import json
+from typing import Iterator, Optional
+
+from gpt_oss.tools.simple_browser import ExaBackend, SimpleBrowserTool
+from openai_harmony import Author, Role, TextContent
+from openai_harmony import Message as HarmonyMessage
+from rich import print
+
+from ollama import Client
+from ollama._types import ChatResponse
+
+_backend = ExaBackend(source='web')
+_browser_tool = SimpleBrowserTool(backend=_backend)
+
+
+def heading(text):
+  print(text)
+  print('=' * (len(text) + 3))
+
+
+async def _browser_search_async(query: str, topn: int = 10, source: str | None = None) -> str:
+  # map Ollama message to Harmony format
+  harmony_message = HarmonyMessage(
+    author=Author(role=Role.USER),
+    content=[TextContent(text=json.dumps({'query': query, 'topn': topn}))],
+    recipient='browser.search',
+  )
+
+  result_text: str = ''
+  async for response in _browser_tool._process(harmony_message):
+    if response.content:
+      for content in response.content:
+        if isinstance(content, TextContent):
+          result_text += content.text
+  return result_text or f'No results for query: {query}'
+
+
+async def _browser_open_async(id: int | str = -1, cursor: int = -1, loc: int = -1, num_lines: int = -1, *, view_source: bool = False, source: str | None = None) -> str:
+  payload = {'id': id, 'cursor': cursor, 'loc': loc, 'num_lines': num_lines, 'view_source': view_source, 'source': source}
+
+  harmony_message = HarmonyMessage(
+    author=Author(role=Role.USER),
+    content=[TextContent(text=json.dumps(payload))],
+    recipient='browser.open',
+  )
+
+  result_text: str = ''
+  async for response in _browser_tool._process(harmony_message):
+    if response.content:
+      for content in response.content:
+        if isinstance(content, TextContent):
+          result_text += content.text
+  return result_text or f'Could not open: {id}'
+
+
+async def _browser_find_async(pattern: str, cursor: int = -1) -> str:
+  payload = {'pattern': pattern, 'cursor': cursor}
+
+  harmony_message = HarmonyMessage(
+    author=Author(role=Role.USER),
+    content=[TextContent(text=json.dumps(payload))],
+    recipient='browser.find',
+  )
+
+  result_text: str = ''
+  async for response in _browser_tool._process(harmony_message):
+    if response.content:
+      for content in response.content:
+        if isinstance(content, TextContent):
+          result_text += content.text
+  return result_text or f'Pattern not found: {pattern}'
+
+
+def browser_search(query: str, topn: int = 10, source: Optional[str] = None) -> str:
+  return asyncio.run(_browser_search_async(query=query, topn=topn, source=source))
+
+
+def browser_open(id: int | str = -1, cursor: int = -1, loc: int = -1, num_lines: int = -1, *, view_source: bool = False, source: Optional[str] = None) -> str:
+  return asyncio.run(_browser_open_async(id=id, cursor=cursor, loc=loc, num_lines=num_lines, view_source=view_source, source=source))
+
+
+def browser_find(pattern: str, cursor: int = -1) -> str:
+  return asyncio.run(_browser_find_async(pattern=pattern, cursor=cursor))
+
+
+# Schema definitions for each browser tool
+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,
+}
+
+
+model = 'gpt-oss:20b'
+print('Model: ', model, '\n')
+
+prompt = 'What is Ollama?'
+print('You: ', prompt, '\n')
+messages = [{'role': 'user', 'content': prompt}]
+
+client = Client()
+
+# 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=[browser_search_schema, browser_open_schema, browser_find_schema],
+    options={'num_ctx': 8192},  # 8192 is the recommended lower limit for the context window
+    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:
+        heading('\n\nFinal result: ')
+        final = False
+      print(chunk.message.content, end='', flush=True)
+
+    if chunk.message.thinking:
+      thinking += chunk.message.thinking
+      print(chunk.message.thinking, end='', flush=True)
+
+  if thinking != '':
+    messages.append({'role': 'assistant', 'content': thinking, 'tool_calls': tool_calls})
+
+  print()
+
+  if tool_calls:
+    for tool_call in tool_calls:
+      tool_name = tool_call.function.name
+      args = tool_call.function.arguments or {}
+      function_to_call = available_tools.get(tool_name)
+
+      if function_to_call:
+        heading(f'\nCalling tool: {tool_name}')
+        if args:
+          print(f'Arguments: {args}')
+
+        try:
+          result = function_to_call(**args)
+          print(f'Tool result: {result[:200]}')
+          if len(result) > 200:
+            heading('... [truncated]')
+          print()
+
+          result_message = {'role': 'tool', 'content': result, 'tool_name': tool_name}
+          messages.append(result_message)
+
+        except Exception as e:
+          err = f'Error from {tool_name}: {e}'
+          print(err)
+          messages.append({'role': 'tool', 'content': err, 'tool_name': tool_name})
+      else:
+        print(f'Tool {tool_name} not found')
+  else:
+    # no more tool calls, we can stop the loop
+    break

examples/gpt-oss-tools-browser.py

@@ -0,0 +1,175 @@
+# /// script
+# requires-python = ">=3.11"
+# dependencies = [
+#     "gpt-oss",
+#     "ollama",
+#     "rich",
+# ]
+# ///
+
+import asyncio
+import json
+from typing import Optional
+
+from gpt_oss.tools.simple_browser import ExaBackend, SimpleBrowserTool
+from openai_harmony import Author, Role, TextContent
+from openai_harmony import Message as HarmonyMessage
+
+from ollama import Client
+
+_backend = ExaBackend(source='web')
+_browser_tool = SimpleBrowserTool(backend=_backend)
+
+
+def heading(text):
+  print(text)
+  print('=' * (len(text) + 3))
+
+
+async def _browser_search_async(query: str, topn: int = 10, source: str | None = None) -> str:
+  # map Ollama message to Harmony format
+  harmony_message = HarmonyMessage(
+    author=Author(role=Role.USER),
+    content=[TextContent(text=json.dumps({'query': query, 'topn': topn}))],
+    recipient='browser.search',
+  )
+
+  result_text: str = ''
+  async for response in _browser_tool._process(harmony_message):
+    if response.content:
+      for content in response.content:
+        if isinstance(content, TextContent):
+          result_text += content.text
+  return result_text or f'No results for query: {query}'
+
+
+async def _browser_open_async(id: int | str = -1, cursor: int = -1, loc: int = -1, num_lines: int = -1, *, view_source: bool = False, source: str | None = None) -> str:
+  payload = {'id': id, 'cursor': cursor, 'loc': loc, 'num_lines': num_lines, 'view_source': view_source, 'source': source}
+
+  harmony_message = HarmonyMessage(
+    author=Author(role=Role.USER),
+    content=[TextContent(text=json.dumps(payload))],
+    recipient='browser.open',
+  )
+
+  result_text: str = ''
+  async for response in _browser_tool._process(harmony_message):
+    if response.content:
+      for content in response.content:
+        if isinstance(content, TextContent):
+          result_text += content.text
+  return result_text or f'Could not open: {id}'
+
+
+async def _browser_find_async(pattern: str, cursor: int = -1) -> str:
+  payload = {'pattern': pattern, 'cursor': cursor}
+
+  harmony_message = HarmonyMessage(
+    author=Author(role=Role.USER),
+    content=[TextContent(text=json.dumps(payload))],
+    recipient='browser.find',
+  )
+
+  result_text: str = ''
+  async for response in _browser_tool._process(harmony_message):
+    if response.content:
+      for content in response.content:
+        if isinstance(content, TextContent):
+          result_text += content.text
+  return result_text or f'Pattern not found: {pattern}'
+
+
+def browser_search(query: str, topn: int = 10, source: Optional[str] = None) -> str:
+  return asyncio.run(_browser_search_async(query=query, topn=topn, source=source))
+
+
+def browser_open(id: int | str = -1, cursor: int = -1, loc: int = -1, num_lines: int = -1, *, view_source: bool = False, source: Optional[str] = None) -> str:
+  return asyncio.run(_browser_open_async(id=id, cursor=cursor, loc=loc, num_lines=num_lines, view_source=view_source, source=source))
+
+
+def browser_find(pattern: str, cursor: int = -1) -> str:
+  return asyncio.run(_browser_find_async(pattern=pattern, cursor=cursor))
+
+
+# Schema definitions for each browser tool
+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,
+}
+
+
+model = 'gpt-oss:20b'
+print('Model: ', model, '\n')
+
+prompt = 'What is Ollama?'
+print('You: ', prompt, '\n')
+messages = [{'role': 'user', 'content': prompt}]
+
+client = Client()
+while True:
+  response = client.chat(
+    model=model,
+    messages=messages,
+    tools=[browser_search_schema, browser_open_schema, browser_find_schema],
+    options={'num_ctx': 8192},  # 8192 is the recommended lower limit for the context window
+  )
+
+  if hasattr(response.message, 'thinking') and response.message.thinking:
+    heading('Thinking')
+    print(response.message.thinking.strip() + '\n')
+
+  if hasattr(response.message, 'content') and response.message.content:
+    heading('Assistant')
+    print(response.message.content.strip() + '\n')
+
+  # add message to chat history
+  messages.append(response.message)
+
+  if response.message.tool_calls:
+    for tool_call in response.message.tool_calls:
+      tool_name = tool_call.function.name
+      args = tool_call.function.arguments or {}
+      function_to_call = available_tools.get(tool_name)
+      if not function_to_call:
+        print(f'Unknown tool: {tool_name}')
+        continue
+
+      try:
+        result = function_to_call(**args)
+        heading(f'Tool: {tool_name}')
+        if args:
+          print(f'Arguments: {args}')
+        print(result[:200])
+        if len(result) > 200:
+          print('... [truncated]')
+        print()
+        messages.append({'role': 'tool', 'content': result, 'tool_name': tool_name})
+      except Exception as e:
+        err = f'Error from {tool_name}: {e}'
+        print(err)
+        messages.append({'role': 'tool', 'content': err, 'tool_name': tool_name})
+  else:
+    # break on no more tool calls
+    break

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/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()

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-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')

ollama/__init__.py

@@ -1,4 +1,8 @@
 from ollama._client import AsyncClient, Client
+
+from ollama._browser import (
+  Browser
+)
 from ollama._types import (
   ChatResponse,
   EmbeddingsResponse,
@@ -15,6 +19,8 @@ from ollama._types import (
   ShowResponse,
   StatusResponse,
   Tool,
+  WebSearchResponse,
+  WebCrawlResponse,
 )
 
 __all__ = [
@@ -35,6 +41,9 @@ __all__ = [
   'ShowResponse',
   'StatusResponse',
   'Tool',
+  'WebSearchResponse',
+  'WebCrawlResponse',
+  'Browser',
 ]
 
 _client = Client()
@@ -51,3 +60,5 @@ list = _client.list
 copy = _client.copy
 show = _client.show
 ps = _client.ps
+websearch = _client.websearch
+webcrawl = _client.webcrawl

ollama/_client.py

@@ -66,6 +66,10 @@ from ollama._types import (
   ShowResponse,
   StatusResponse,
   Tool,
+  WebCrawlRequest,
+  WebCrawlResponse,
+  WebSearchRequest,
+  WebSearchResponse,
 )
 
 T = TypeVar('T')
@@ -102,6 +106,8 @@ class BaseClient:
           'Content-Type': 'application/json',
           'Accept': 'application/json',
           'User-Agent': f'ollama-python/{__version__} ({platform.machine()} {platform.system().lower()}) Python/{platform.python_version()}',
+          # TODO: this is to make the client feel good
+          'Authorization': f'Bearer {(headers or {}).get("Authorization") or os.getenv("OLLAMA_API_KEY")}' if (headers or {}).get("Authorization") or os.getenv("OLLAMA_API_KEY") else None,
         }.items()
       },
       **kwargs,
@@ -274,7 +280,7 @@ 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,
     format: Optional[Union[Literal['', 'json'], JsonSchemaValue]] = None,
     options: Optional[Union[Mapping[str, Any], Options]] = None,
     keep_alive: Optional[Union[float, str]] = None,
@@ -288,7 +294,7 @@ 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,
     format: Optional[Union[Literal['', 'json'], JsonSchemaValue]] = None,
     options: Optional[Union[Mapping[str, Any], Options]] = None,
     keep_alive: Optional[Union[float, str]] = None,
@@ -301,7 +307,7 @@ 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,
     format: Optional[Union[Literal['', 'json'], JsonSchemaValue]] = None,
     options: Optional[Union[Mapping[str, Any], Options]] = None,
     keep_alive: Optional[Union[float, str]] = None,
@@ -622,6 +628,45 @@ class Client(BaseClient):
       '/api/ps',
     )
 
+  def websearch(self, query: str, max_results: int = 3) -> WebSearchResponse:
+    """
+    Perform a web search using ollama.com. 
+
+    Args:
+      query: The query to search for max_results: The maximum number of results to return.
+
+    Returns:
+      WebSearchResponse with the search results
+    """
+    return self._request(
+      WebSearchResponse,
+      'POST',
+      'https://ollama.com/api/web_search',
+      json=WebSearchRequest(
+        queries=[query],
+        max_results=max_results,
+      ).model_dump(exclude_none=True),
+    )
+
+  def webcrawl(self, urls: Sequence[str]) -> WebCrawlResponse:
+    """
+    Gets the content of web pages for the provided URLs.
+
+    Args:
+      urls: The URLs to crawl
+
+    Returns:
+      WebCrawlResponse with the crawl results
+    """
+    return self._request(
+      WebCrawlResponse,
+      'POST',
+      'https://ollama.com/api/web_crawl',
+      json=WebCrawlRequest(
+        urls=urls,
+      ).model_dump(exclude_none=True),
+    )
+
 
 class AsyncClient(BaseClient):
   def __init__(self, host: Optional[str] = None, **kwargs) -> None:
@@ -702,7 +747,7 @@ 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,
     raw: bool = False,
     format: Optional[Union[Literal['', 'json'], JsonSchemaValue]] = None,
     images: Optional[Sequence[Union[str, bytes, Image]]] = None,
@@ -721,7 +766,7 @@ 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,
     raw: bool = False,
     format: Optional[Union[Literal['', 'json'], JsonSchemaValue]] = None,
     images: Optional[Sequence[Union[str, bytes, Image]]] = None,
@@ -739,7 +784,7 @@ 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,
     raw: Optional[bool] = None,
     format: Optional[Union[Literal['', 'json'], JsonSchemaValue]] = None,
     images: Optional[Sequence[Union[str, bytes, Image]]] = None,
@@ -785,7 +830,7 @@ 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,
     format: Optional[Union[Literal['', 'json'], JsonSchemaValue]] = None,
     options: Optional[Union[Mapping[str, Any], Options]] = None,
     keep_alive: Optional[Union[float, str]] = None,
@@ -799,7 +844,7 @@ 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,
     format: Optional[Union[Literal['', 'json'], JsonSchemaValue]] = None,
     options: Optional[Union[Mapping[str, Any], Options]] = None,
     keep_alive: Optional[Union[float, str]] = None,
@@ -812,7 +857,7 @@ 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,
     format: Optional[Union[Literal['', 'json'], JsonSchemaValue]] = None,
     options: Optional[Union[Mapping[str, Any], Options]] = None,
     keep_alive: Optional[Union[float, str]] = None,

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
@@ -207,7 +207,7 @@ 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).'
 
 
@@ -313,7 +313,7 @@ class Message(SubscriptableBaseModel):
 
 
 class Tool(SubscriptableBaseModel):
-  type: Optional[Literal['function']] = 'function'
+  type: Optional[str] = 'function'
 
   class Function(SubscriptableBaseModel):
     name: Optional[str] = None
@@ -357,7 +357,7 @@ 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).'
 
 
@@ -538,6 +538,103 @@ class ProcessResponse(SubscriptableBaseModel):
   models: Sequence[Model]
 
 
+class WebSearchRequest(SubscriptableBaseModel):
+  queries: Sequence[str]
+  max_results: Optional[int] = None
+
+class SearchResult(SubscriptableBaseModel):
+  title: str
+  url: str
+  content: str
+  metadata: Optional['SearchResultMetadata'] = None
+
+
+class CrawlResult(SubscriptableBaseModel):
+  title: str
+  url: str
+  content: str
+  links: Optional[Sequence[str]] = None
+  metadata: Optional['CrawlResultMetadata'] = None
+
+
+class SearchResultContent(SubscriptableBaseModel):
+  snippet: str
+  full_text: str
+
+
+class SearchResultMetadata(SubscriptableBaseModel):
+  published_date: Optional[str] = None
+  author: Optional[str] = None
+
+
+class WebSearchResponse(SubscriptableBaseModel):
+  results: Mapping[str, Sequence[SearchResult]]
+  success: bool
+  errors: Optional[Sequence[str]] = None
+
+  def __str__(self) -> str:
+    if not self.success:
+      error_msg = ', '.join(self.errors) if self.errors else 'Unknown error'
+      return f'Web search failed: {error_msg}'
+    
+    output = []
+    for query, search_results in self.results.items():
+      output.append(f'Search results for "{query}":')
+      for i, result in enumerate(search_results, 1):
+        output.append(f'{i}. {result.title}')
+        output.append(f'   URL: {result.url}')
+        output.append(f'   Content: {result.content}')
+        if result.metadata and result.metadata.published_date:
+          output.append(f'   Published: {result.metadata.published_date}')
+        if result.metadata and result.metadata.author:
+          output.append(f'   Author: {result.metadata.author}')
+        output.append('')
+    
+    return '\n'.join(output).rstrip()
+
+class WebCrawlRequest(SubscriptableBaseModel):
+  urls: Sequence[str]
+
+
+class CrawlResultContent(SubscriptableBaseModel):
+  # provides the first 200 characters of the full text
+  snippet: str
+  full_text: str
+
+
+class CrawlResultMetadata(SubscriptableBaseModel):
+  published_date: Optional[str] = None
+  author: Optional[str] = None
+
+
+class WebCrawlResponse(SubscriptableBaseModel):
+  results: Mapping[str, Sequence[CrawlResult]]
+  success: bool
+  errors: Optional[Sequence[str]] = None
+
+  def __str__(self) -> str:
+    if not self.success:
+      error_msg = ', '.join(self.errors) if self.errors else 'Unknown error'
+      return f'Web crawl failed: {error_msg}'
+    
+    output = []
+    for url, crawl_results in self.results.items():
+      output.append(f'Crawl results for "{url}":')
+      for i, result in enumerate(crawl_results, 1):
+        output.append(f'{i}. {result.title}')
+        output.append(f'   URL: {result.url}')
+        output.append(f'   Content: {result.content}')
+        if result.links:
+          output.append(f'   Links: {", ".join(result.links)}')
+        if result.metadata and result.metadata.published_date:
+          output.append(f'   Published: {result.metadata.published_date}')
+        if result.metadata and result.metadata.author:
+          output.append(f'   Author: {result.metadata.author}')
+        output.append('')
+    
+    return '\n'.join(output).rstrip()
+
+
 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)

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
 
@@ -1136,10 +1136,11 @@ def test_copy_tools():
 
 
 def test_tool_validation():
-  # Raises ValidationError when used as it is a generator
-  with pytest.raises(ValidationError):
-    invalid_tool = {'type': 'invalid_type', 'function': {'name': 'test'}}
-    list(_copy_tools([invalid_tool]))
+  arbitrary_tool = {'type': 'custom_type', 'function': {'name': 'test'}}
+  tools = list(_copy_tools([arbitrary_tool]))
+  assert len(tools) == 1
+  assert tools[0].type == 'custom_type'
+  assert tools[0].function.name == 'test'
 
 
 def test_client_connection_error():