types: relax type for tools (#550)

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 +27,10 @@ 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) - Using tools with gpt-oss
+- [gpt-oss-tools-stream.py](gpt-oss-tools-stream.py) - Using tools with gpt-oss, with streaming enabled
+
 
 ### Multimodal with Images - Chat with a multimodal (image chat) model
 - [multimodal-chat.py](multimodal-chat.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-stream.py

@@ -0,0 +1,77 @@
+import random
+from typing import Iterator
+
+from ollama import chat
+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?'}]
+
+
+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] = chat(model=model, messages=messages, tools=[get_weather, get_weather_conditions], stream=True)
+
+  for chunk in response_stream:
+    if chunk.message.content:
+      if not (chunk.message.thinking or chunk.message.thinking == '') and final:
+        print('\nFinal result: ')
+        final = False
+      print(chunk.message.content, end='', flush=True)
+    if chunk.message.thinking:
+      print(chunk.message.thinking, end='', flush=True)
+
+  print()
+
+  if chunk.message.tool_calls:
+    for tool_call in chunk.message.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')
+
+        messages.append(chunk.message)
+        messages.append({'role': 'tool', 'content': result, 'tool_name': tool_call.function.name})
+      else:
+        print(f'Tool {tool_call.function.name} not found')
+
+  else:
+    # no more tool calls, we can stop the loop
+    break

examples/gpt-oss-tools.py

@@ -0,0 +1,70 @@
+import random
+
+from ollama import chat
+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?'}]
+
+
+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 = 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')
+
+  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(response.message)
+        messages.append({'role': 'tool', 'content': result, 'tool_name': tool_call.function.name})
+      else:
+        print(f'Tool {tool_call.function.name} not found')
+
+  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=[
     {

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
@@ -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

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():