types/examples: add tool_name to message and examples (#537)

examples/README.md

@@ -25,6 +25,7 @@ See [ollama/docs/api.md](https://github.com/ollama/ollama/blob/main/docs/api.md)
 ### 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
 
 
 ### Multimodal with Images - Chat with a multimodal (image chat) model

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/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/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)

ollama/_types.py

@@ -284,6 +284,9 @@ 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.

pyproject.toml

@@ -60,6 +60,7 @@ select = [
     'FLY', # flynt
     'RUF', # ruff-specific rules
 ]
+ignore = ['FBT001'] # Boolean-typed positional argument in function definition
 
 [tool.pytest.ini_options]
 addopts = ['--doctest-modules']