include tool calls

2026-06-16 21:24:52 +00:00 · 2024-07-16 11:39:42 -07:00
39 changed files with 1067 additions and 3011 deletions
@@ -2,15 +2,12 @@ name: test

 on:
  pull_request:
-    paths-ignore:
-      - 'examples/**'
-      - '**/README.md'

 jobs:
  test:
    strategy:
      matrix:
-        python-version: ['3.8', '3.9', '3.10', '3.11', '3.12', '3.13']
+        python-version: ['3.8', '3.9', '3.10', '3.11', '3.12']
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
@@ -2,12 +2,6 @@

 The Ollama Python library provides the easiest way to integrate Python 3.8+ projects with [Ollama](https://github.com/ollama/ollama).

-## 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`
-  - See [Ollama.com](https://ollama.com/search) for more information on the models available.
-
 ## Install

 ```sh
@@ -17,31 +11,25 @@ pip install ollama
 ## Usage

 ```python
-from ollama import chat
-from ollama import ChatResponse
-
-response: ChatResponse = chat(model='llama3.2', messages=[
+import ollama
+response = ollama.chat(model='llama3', messages=[
  {
    'role': 'user',
    'content': 'Why is the sky blue?',
  },
 ])
 print(response['message']['content'])
-# or access fields directly from the response object
-print(response.message.content)
 ```

-See [_types.py](ollama/_types.py) for more information on the response types.
-
 ## Streaming responses

-Response streaming can be enabled by setting `stream=True`.
+Response streaming can be enabled by setting `stream=True`, modifying function calls to return a Python generator where each part is an object in the stream.

 ```python
-from ollama import chat
+import ollama

-stream = chat(
-    model='llama3.2',
+stream = ollama.chat(
+    model='llama3',
    messages=[{'role': 'user', 'content': 'Why is the sky blue?'}],
    stream=True,
 )
@@ -50,18 +38,92 @@ for chunk in stream:
  print(chunk['message']['content'], end='', flush=True)
 ```

-## Custom client
-A custom client can be created by instantiating `Client` or `AsyncClient` from `ollama`.
+## API

-All extra keyword arguments are passed into the [`httpx.Client`](https://www.python-httpx.org/api/#client).
+The Ollama Python library's API is designed around the [Ollama REST API](https://github.com/ollama/ollama/blob/main/docs/api.md)
+
+### Chat
+
+```python
+ollama.chat(model='llama3', messages=[{'role': 'user', 'content': 'Why is the sky blue?'}])
+```
+
+### Generate
+
+```python
+ollama.generate(model='llama3', prompt='Why is the sky blue?')
+```
+
+### List
+
+```python
+ollama.list()
+```
+
+### Show
+
+```python
+ollama.show('llama3')
+```
+
+### Create
+
+```python
+modelfile='''
+FROM llama3
+SYSTEM You are mario from super mario bros.
+'''
+
+ollama.create(model='example', modelfile=modelfile)
+```
+
+### Copy
+
+```python
+ollama.copy('llama3', 'user/llama3')
+```
+
+### Delete
+
+```python
+ollama.delete('llama3')
+```
+
+### Pull
+
+```python
+ollama.pull('llama3')
+```
+
+### Push
+
+```python
+ollama.push('user/llama3')
+```
+
+### Embeddings
+
+```python
+ollama.embeddings(model='llama3', prompt='The sky is blue because of rayleigh scattering')
+```
+
+### Ps
+
+```python
+ollama.ps()
+```
+
+## Custom client
+
+A custom client can be created with the following fields:
+
+- `host`: The Ollama host to connect to
+- `timeout`: The timeout for requests

 ```python
 from ollama import Client
-client = Client(
-  host='http://localhost:11434',
-  headers={'x-some-header': 'some-value'}
-)
-response = client.chat(model='llama3.2', messages=[
+client = Client(host='http://localhost:11434')
+response = client.chat(model='llama3', messages=[
  {
    'role': 'user',
    'content': 'Why is the sky blue?',
@@ -71,15 +133,13 @@ response = client.chat(model='llama3.2', messages=[

 ## Async client

-The `AsyncClient` class is used to make asynchronous requests. It can be configured with the same fields as the `Client` class.
-
 ```python
 import asyncio
 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='llama3', messages=[message])

 asyncio.run(chat())
 ```
@@ -92,94 +152,12 @@ 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='llama3', messages=[message], stream=True):
    print(part['message']['content'], end='', flush=True)

 asyncio.run(chat())
 ```

-## API
-
-The Ollama Python library's API is designed around the [Ollama REST API](https://github.com/ollama/ollama/blob/main/docs/api.md)
-
-### Chat
-
-```python
-ollama.chat(model='llama3.2', messages=[{'role': 'user', 'content': 'Why is the sky blue?'}])
-```
-
-### Generate
-
-```python
-ollama.generate(model='llama3.2', prompt='Why is the sky blue?')
-```
-
-### List
-
-```python
-ollama.list()
-```
-
-### Show
-
-```python
-ollama.show('llama3.2')
-```
-
-### Create
-
-```python
-modelfile='''
-FROM llama3.2
-SYSTEM You are mario from super mario bros.
-'''
-
-ollama.create(model='example', modelfile=modelfile)
-```
-
-### Copy
-
-```python
-ollama.copy('llama3.2', 'user/llama3.2')
-```
-
-### Delete
-
-```python
-ollama.delete('llama3.2')
-```
-
-### Pull
-
-```python
-ollama.pull('llama3.2')
-```
-
-### Push
-
-```python
-ollama.push('user/llama3.2')
-```
-
-### Embed
-
-```python
-ollama.embed(model='llama3.2', 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'])
-```
-
-### Ps
-
-```python
-ollama.ps()
-```
-
-
 ## Errors

 Errors are raised if requests return an error status or if an error is detected while streaming.
@@ -1,63 +0,0 @@
-# Running Examples
-
-Run the examples in this directory with:
-```sh
-# Run example
-python3 examples/<example>.py
-```
-
-### 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)
-
-
-### 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 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
-```python
-python create.py <model> <modelfile>
-```
- [create.py](create.py) 
-
-See [ollama/docs/modelfile.md](https://github.com/ollama/ollama/blob/main/docs/modelfile.md) for more information on the Modelfile format.
-
-
-### Ollama Embed - Generate embeddings with a model
- [embed.py](embed.py)
-
@@ -0,0 +1,3 @@
+# async-chat-stream
+
+This example demonstrates how to create a conversation history using an asynchronous Ollama client and the chat endpoint. The streaming response is outputted to `stdout` as well as a TTS if enabled with `--speak` and available. Supported TTS are `say` on macOS and `espeak` on Linux.
@@ -0,0 +1,59 @@
+import shutil
+import asyncio
+import argparse
+
+import ollama
+
+
+async def speak(speaker, content):
+  if speaker:
+    p = await asyncio.create_subprocess_exec(speaker, content)
+    await p.communicate()
+
+
+async def main():
+  parser = argparse.ArgumentParser()
+  parser.add_argument('--speak', default=False, action='store_true')
+  args = parser.parse_args()
+
+  speaker = None
+  if not args.speak:
+    ...
+  elif say := shutil.which('say'):
+    speaker = say
+  elif (espeak := shutil.which('espeak')) or (espeak := shutil.which('espeak-ng')):
+    speaker = espeak
+
+  client = ollama.AsyncClient()
+
+  messages = []
+
+  while True:
+    if content_in := input('>>> '):
+      messages.append({'role': 'user', 'content': content_in})
+
+      content_out = ''
+      message = {'role': 'assistant', 'content': ''}
+      async for response in await client.chat(model='mistral', messages=messages, stream=True):
+        if response['done']:
+          messages.append(message)
+
+        content = response['message']['content']
+        print(content, end='', flush=True)
+
+        content_out += content
+        if content in ['.', '!', '?', '\n']:
+          await speak(speaker, content_out)
+          content_out = ''
+
+        message['content'] += content
+
+      if content_out:
+        await speak(speaker, content_out)
+      print()
+
+
+try:
+  asyncio.run(main())
+except (KeyboardInterrupt, EOFError):
+  ...
@@ -1,19 +0,0 @@
-import asyncio
-from ollama import AsyncClient
-
-
-async def main():
-  messages = [
-    {
-      'role': 'user',
-      'content': 'Why is the sky blue?',
-    },
-  ]
-
-  client = AsyncClient()
-  response = await client.chat('llama3.2', messages=messages)
-  print(response['message']['content'])
-
-
-if __name__ == '__main__':
-  asyncio.run(main())
@@ -1,15 +0,0 @@
-import asyncio
-import ollama
-
-
-async def main():
-  client = ollama.AsyncClient()
-  response = await client.generate('llama3.2', 'Why is the sky blue?')
-  print(response['response'])
-
-
-if __name__ == '__main__':
-  try:
-    asyncio.run(main())
-  except KeyboardInterrupt:
-    print('\nGoodbye!')
@@ -1,32 +0,0 @@
-from pydantic import BaseModel
-from ollama import AsyncClient
-import asyncio
-
-
-# Define the schema for the response
-class FriendInfo(BaseModel):
-  name: str
-  age: int
-  is_available: bool
-
-
-class FriendList(BaseModel):
-  friends: list[FriendInfo]
-
-
-async def main():
-  client = AsyncClient()
-  response = await client.chat(
-    model='llama3.1:8b',
-    messages=[{'role': 'user', 'content': 'I have two friends. The first is Ollama 22 years old busy saving the world, and the second is Alonso 23 years old and wants to hang out. Return a list of friends in JSON format'}],
-    format=FriendList.model_json_schema(),  # Use Pydantic to generate the schema
-    options={'temperature': 0},  # Make responses more deterministic
-  )
-
-  # Use Pydantic to validate the response
-  friends_response = FriendList.model_validate_json(response.message.content)
-  print(friends_response)
-
-
-if __name__ == '__main__':
-  asyncio.run(main())
@@ -1,92 +0,0 @@
-import asyncio
-from ollama import ChatResponse
-import ollama
-
-
-def add_two_numbers(a: int, b: int) -> int:
-  """
-  Add two numbers
-
-  Args:
-    a (int): The first number
-    b (int): The second number
-
-  Returns:
-    int: The sum of the two numbers
-  """
-  return a + b
-
-
-def subtract_two_numbers(a: int, b: int) -> int:
-  """
-  Subtract two numbers
-  """
-  return a - b
-
-
-# Tools can still be manually defined and passed into chat
-subtract_two_numbers_tool = {
-  'type': 'function',
-  'function': {
-    'name': 'subtract_two_numbers',
-    'description': 'Subtract two numbers',
-    'parameters': {
-      'type': 'object',
-      'required': ['a', 'b'],
-      'properties': {
-        'a': {'type': 'integer', 'description': 'The first number'},
-        'b': {'type': 'integer', 'description': 'The second number'},
-      },
-    },
-  },
-}
-
-messages = [{'role': 'user', 'content': 'What is three plus one?'}]
-print('Prompt:', messages[0]['content'])
-
-available_functions = {
-  'add_two_numbers': add_two_numbers,
-  'subtract_two_numbers': subtract_two_numbers,
-}
-
-
-async def main():
-  client = ollama.AsyncClient()
-
-  response: ChatResponse = await client.chat(
-    'llama3.1',
-    messages=messages,
-    tools=[add_two_numbers, subtract_two_numbers_tool],
-  )
-
-  if response.message.tool_calls:
-    # There may be multiple tool calls in the response
-    for tool in response.message.tool_calls:
-      # Ensure the function is available, and then call it
-      if function_to_call := available_functions.get(tool.function.name):
-        print('Calling function:', tool.function.name)
-        print('Arguments:', tool.function.arguments)
-        output = function_to_call(**tool.function.arguments)
-        print('Function output:', output)
-      else:
-        print('Function', tool.function.name, 'not found')
-
-  # Only needed to chat with the model using the tool call results
-  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})
-
-    # Get final response from model with function outputs
-    final_response = await client.chat('llama3.1', messages=messages)
-    print('Final response:', final_response.message.content)
-
-  else:
-    print('No tool calls returned from model')
-
-
-if __name__ == '__main__':
-  try:
-    asyncio.run(main())
-  except KeyboardInterrupt:
-    print('\nGoodbye!')
@@ -8,7 +8,8 @@ messages = [
  },
 ]

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

+# end with a newline
 print()
@@ -1,38 +0,0 @@
-from ollama import chat
-
-
-messages = [
-  {
-    'role': 'user',
-    'content': 'Why is the sky blue?',
-  },
-  {
-    'role': 'assistant',
-    'content': "The sky is blue because of the way the Earth's atmosphere scatters sunlight.",
-  },
-  {
-    'role': 'user',
-    'content': 'What is the weather in Tokyo?',
-  },
-  {
-    '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.',
-  },
-]
-
-while True:
-  user_input = input('Chat with history: ')
-  response = chat(
-    'llama3.2',
-    messages=messages
-    + [
-      {'role': 'user', 'content': user_input},
-    ],
-  )
-
-  # Add the response to the messages to maintain the history
-  messages += [
-    {'role': 'user', 'content': user_input},
-    {'role': 'assistant', 'content': response.message.content},
-  ]
-  print(response.message.content + '\n')
@@ -1,5 +1,6 @@
 from ollama import chat

+
 messages = [
  {
    'role': 'user',
@@ -7,5 +8,5 @@ messages = [
  },
 ]

-response = chat('llama3.2', messages=messages)
+response = chat('mistral', messages=messages)
 print(response['message']['content'])
@@ -1,30 +0,0 @@
-import sys
-
-from ollama import create
-
-
-args = sys.argv[1:]
-if len(args) == 2:
-  # create from local file
-  path = args[1]
-else:
-  print('usage: python create.py <name> <filepath>')
-  sys.exit(1)
-
-# TODO: update to real Modelfile values
-modelfile = f"""
-FROM {path}
-"""
-example_modelfile = """
-FROM llama3.2
-# sets the temperature to 1 [higher is more creative, lower is more coherent]
-PARAMETER temperature 1
-# sets the context window size to 4096, this controls how many tokens the LLM can use as context to generate the next token
-PARAMETER num_ctx 4096
-
-# sets a custom system message to specify the behavior of the chat assistant
-SYSTEM You are Mario from super mario bros, acting as an assistant.
-"""
-
-for response in create(model=args[0], modelfile=modelfile, stream=True):
-  print(response['status'])
@@ -0,0 +1,20 @@
+import sys
+
+from ollama import create
+
+
+args = sys.argv[1:]
+if len(args) == 2:
+  # create from local file
+  path = args[1]
+else:
+  print('usage: python main.py <name> <filepath>')
+  sys.exit(1)
+
+# TODO: update to real Modelfile values
+modelfile = f"""
+FROM {path}
+"""
+
+for response in create(model=args[0], modelfile=modelfile, stream=True):
+  print(response['status'])
@@ -1,4 +0,0 @@
-from ollama import embed
-
-response = embed(model='llama3.2', input='Hello, world!')
-print(response['embeddings'])
@@ -1,16 +1,16 @@
 from ollama import generate

-prompt = '''def remove_non_ascii(s: str) -> str:
+prefix = '''def remove_non_ascii(s: str) -> str:
    """ '''

 suffix = """
    return result
 """

+
 response = generate(
  model='codellama:7b-code',
-  prompt=prompt,
-  suffix=suffix,
+  prompt=f'<PRE> {prefix} <SUF>{suffix} <MID>',
  options={
    'num_predict': 128,
    'temperature': 0,
@@ -1,5 +1,5 @@
 from ollama import generate


-for part in generate('llama3.2', 'Why is the sky blue?', stream=True):
+for part in generate('mistral', 'Why is the sky blue?', stream=True):
  print(part['response'], end='', flush=True)
@@ -1,5 +1,5 @@
 from ollama import generate


-response = generate('llama3.2', 'Why is the sky blue?')
+response = generate('mistral', 'Why is the sky blue?')
 print(response['response'])
@@ -1,14 +0,0 @@
-from ollama import list
-from ollama import ListResponse
-
-response: ListResponse = list()
-
-for model in response.models:
-  print('Name:', model.model)
-  print('  Size (MB):', f'{(model.size.real / 1024 / 1024):.2f}')
-  if model.details:
-    print('  Format:', model.details.format)
-    print('  Family:', model.details.family)
-    print('  Parameter Size:', model.details.parameter_size)
-    print('  Quantization Level:', model.details.quantization_level)
-  print('\n')
@@ -1,23 +0,0 @@
-from ollama import chat
-# from pathlib import Path
-
-# Pass in the path to the image
-path = input('Please enter the path to the image: ')
-
-# You can also pass in base64 encoded image data
-# img = base64.b64encode(Path(path).read_bytes()).decode()
-# or the raw bytes
-# img = Path(path).read_bytes()
-
-response = chat(
-  model='llama3.2-vision',
-  messages=[
-    {
-      'role': 'user',
-      'content': 'What is in this image? Be concise.',
-      'images': [path],
-    }
-  ],
-)
-
-print(response.message.content)
@@ -1,27 +0,0 @@
-from ollama import ps, pull, chat
-from ollama import ProcessResponse
-
-# Ensure at least one model is loaded
-response = pull('llama3.2', stream=True)
-progress_states = set()
-for progress in response:
-  if progress.get('status') in progress_states:
-    continue
-  progress_states.add(progress.get('status'))
-  print(progress.get('status'))
-
-print('\n')
-
-print('Waiting for model to load... \n')
-chat(model='llama3.2', messages=[{'role': 'user', 'content': 'Why is the sky blue?'}])
-
-
-response: ProcessResponse = ps()
-for model in response.models:
-  print('Model: ', model.model)
-  print('  Digest: ', model.digest)
-  print('  Expires at: ', model.expires_at)
-  print('  Size: ', model.size)
-  print('  Size vram: ', model.size_vram)
-  print('  Details: ', model.details)
-  print('\n')
@@ -0,0 +1,31 @@
+from ollama import ps, pull, chat
+
+response = pull('mistral', stream=True)
+progress_states = set()
+for progress in response:
+  if progress.get('status') in progress_states:
+    continue
+  progress_states.add(progress.get('status'))
+  print(progress.get('status'))
+
+print('\n')
+
+response = chat('mistral', messages=[{'role': 'user', 'content': 'Hello!'}])
+print(response['message']['content'])
+
+print('\n')
+
+response = ps()
+
+name = response['models'][0]['name']
+size = response['models'][0]['size']
+size_vram = response['models'][0]['size_vram']
+
+if size == size_vram:
+  print(f'{name}: 100% GPU')
+elif not size_vram:
+  print(f'{name}: 100% CPU')
+else:
+  size_cpu = size - size_vram
+  cpu_percent = round(size_cpu / size * 100)
+  print(f'{name}: {cpu_percent}% CPU/{100 - cpu_percent}% GPU')
@@ -0,0 +1,9 @@
+# pull-progress
+
+This example emulates `ollama pull` using the Python library and [`tqdm`](https://tqdm.github.io/).
+
+## Setup
+
+```shell
+pip install -r requirements.txt
+```
@@ -3,7 +3,7 @@ from ollama import pull


 current_digest, bars = '', {}
-for progress in pull('llama3.2', stream=True):
+for progress in pull('mistral', stream=True):
  digest = progress.get('digest', '')
  if digest != current_digest and current_digest in bars:
    bars[current_digest].close()
@@ -0,0 +1 @@
+tqdm==4.66.1
@@ -1,49 +0,0 @@
-from pathlib import Path
-from pydantic import BaseModel
-from typing import Literal
-from ollama import chat
-
-
-# Define the schema for image objects
-class Object(BaseModel):
-  name: str
-  confidence: float
-  attributes: str
-
-
-class ImageDescription(BaseModel):
-  summary: str
-  objects: list[Object]
-  scene: str
-  colors: list[str]
-  time_of_day: Literal['Morning', 'Afternoon', 'Evening', 'Night']
-  setting: Literal['Indoor', 'Outdoor', 'Unknown']
-  text_content: str | None = None
-
-
-# Get path from user input
-path = input('Enter the path to your image: ')
-path = Path(path)
-
-# Verify the file exists
-if not path.exists():
-  raise FileNotFoundError(f'Image not found at: {path}')
-
-# Set up chat as usual
-response = chat(
-  model='llama3.2-vision',
-  format=ImageDescription.model_json_schema(),  # Pass in the schema for the response
-  messages=[
-    {
-      'role': 'user',
-      'content': 'Analyze this image and return a detailed JSON description including objects, scene, colors and any text detected. If you cannot determine certain details, leave those fields empty.',
-      'images': [path],
-    },
-  ],
-  options={'temperature': 0},  # Set temperature to 0 for more deterministic output
-)
-
-
-# Convert received content to the schema
-image_analysis = ImageDescription.model_validate_json(response.message.content)
-print(image_analysis)
@@ -1,26 +0,0 @@
-from ollama import chat
-from pydantic import BaseModel
-
-
-# Define the schema for the response
-class FriendInfo(BaseModel):
-  name: str
-  age: int
-  is_available: bool
-
-
-class FriendList(BaseModel):
-  friends: list[FriendInfo]
-
-
-# schema = {'type': 'object', 'properties': {'friends': {'type': 'array', 'items': {'type': 'object', 'properties': {'name': {'type': 'string'}, 'age': {'type': 'integer'}, 'is_available': {'type': 'boolean'}}, 'required': ['name', 'age', 'is_available']}}}, 'required': ['friends']}
-response = chat(
-  model='llama3.1:8b',
-  messages=[{'role': 'user', 'content': 'I have two friends. The first is Ollama 22 years old busy saving the world, and the second is Alonso 23 years old and wants to hang out. Return a list of friends in JSON format'}],
-  format=FriendList.model_json_schema(),  # Use Pydantic to generate the schema or format=schema
-  options={'temperature': 0},  # Make responses more deterministic
-)
-
-# Use Pydantic to validate the response
-friends_response = FriendList.model_validate_json(response.message.content)
-print(friends_response)
@@ -1,80 +0,0 @@
-from ollama import chat
-from ollama import ChatResponse
-
-
-def add_two_numbers(a: int, b: int) -> int:
-  """
-  Add two numbers
-
-  Args:
-    a (int): The first number
-    b (int): The second number
-
-  Returns:
-    int: The sum of the two numbers
-  """
-  return a + b
-
-
-def subtract_two_numbers(a: int, b: int) -> int:
-  """
-  Subtract two numbers
-  """
-  return a - b
-
-
-# Tools can still be manually defined and passed into chat
-subtract_two_numbers_tool = {
-  'type': 'function',
-  'function': {
-    'name': 'subtract_two_numbers',
-    'description': 'Subtract two numbers',
-    'parameters': {
-      'type': 'object',
-      'required': ['a', 'b'],
-      'properties': {
-        'a': {'type': 'integer', 'description': 'The first number'},
-        'b': {'type': 'integer', 'description': 'The second number'},
-      },
-    },
-  },
-}
-
-messages = [{'role': 'user', 'content': 'What is three plus one?'}]
-print('Prompt:', messages[0]['content'])
-
-available_functions = {
-  'add_two_numbers': add_two_numbers,
-  'subtract_two_numbers': subtract_two_numbers,
-}
-
-response: ChatResponse = chat(
-  'llama3.1',
-  messages=messages,
-  tools=[add_two_numbers, subtract_two_numbers_tool],
-)
-
-if response.message.tool_calls:
-  # There may be multiple tool calls in the response
-  for tool in response.message.tool_calls:
-    # Ensure the function is available, and then call it
-    if function_to_call := available_functions.get(tool.function.name):
-      print('Calling function:', tool.function.name)
-      print('Arguments:', tool.function.arguments)
-      output = function_to_call(**tool.function.arguments)
-      print('Function output:', output)
-    else:
-      print('Function', tool.function.name, 'not found')
-
-# Only needed to chat with the model using the tool call results
-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})
-
-  # Get final response from model with function outputs
-  final_response = chat('llama3.1', messages=messages)
-  print('Final response:', final_response.message.content)
-
-else:
-  print('No tool calls returned from model')
@@ -1,18 +1,10 @@
 from ollama._client import Client, AsyncClient
 from ollama._types import (
-  Options,
-  Message,
-  Image,
-  Tool,
  GenerateResponse,
  ChatResponse,
-  EmbedResponse,
-  EmbeddingsResponse,
-  StatusResponse,
  ProgressResponse,
-  ListResponse,
-  ShowResponse,
-  ProcessResponse,
+  Message,
+  Options,
  RequestError,
  ResponseError,
 )
@@ -20,28 +12,30 @@ from ollama._types import (
 __all__ = [
  'Client',
  'AsyncClient',
-  'Options',
-  'Message',
-  'Image',
-  'Tool',
  'GenerateResponse',
  'ChatResponse',
-  'EmbedResponse',
-  'EmbeddingsResponse',
-  'StatusResponse',
  'ProgressResponse',
-  'ListResponse',
-  'ShowResponse',
-  'ProcessResponse',
+  'Message',
+  'Options',
  'RequestError',
  'ResponseError',
+  'generate',
+  'chat',
+  'embeddings',
+  'pull',
+  'push',
+  'create',
+  'delete',
+  'list',
+  'copy',
+  'show',
+  'ps',
 ]

 _client = Client()

 generate = _client.generate
 chat = _client.chat
-embed = _client.embed
 embeddings = _client.embeddings
 pull = _client.pull
 push = _client.push
@@ -1,242 +1,43 @@
 import json
-from base64 import b64decode, b64encode
-from pathlib import Path
-from datetime import datetime
-from typing import Any, Mapping, Optional, Union, Sequence
+from typing import Any, TypedDict, Sequence, Literal

-from pydantic.json_schema import JsonSchemaValue
-from typing_extensions import Annotated, Literal
+import sys

-from pydantic import (
-  BaseModel,
-  ByteSize,
-  ConfigDict,
-  Field,
-  model_serializer,
-)
+if sys.version_info < (3, 11):
+  from typing_extensions import NotRequired
+else:
+  from typing import NotRequired


-class SubscriptableBaseModel(BaseModel):
-  def __getitem__(self, key: str) -> Any:
-    """
-    >>> msg = Message(role='user')
-    >>> msg['role']
-    'user'
-    >>> msg = Message(role='user')
-    >>> msg['nonexistent']
-    Traceback (most recent call last):
-    KeyError: 'nonexistent'
-    """
-    if key in self:
-      return getattr(self, key)
-
-    raise KeyError(key)
-
-  def __setitem__(self, key: str, value: Any) -> None:
-    """
-    >>> msg = Message(role='user')
-    >>> msg['role'] = 'assistant'
-    >>> msg['role']
-    'assistant'
-    >>> tool_call = Message.ToolCall(function=Message.ToolCall.Function(name='foo', arguments={}))
-    >>> msg = Message(role='user', content='hello')
-    >>> msg['tool_calls'] = [tool_call]
-    >>> msg['tool_calls'][0]['function']['name']
-    'foo'
-    """
-    setattr(self, key, value)
-
-  def __contains__(self, key: str) -> bool:
-    """
-    >>> msg = Message(role='user')
-    >>> 'nonexistent' in msg
-    False
-    >>> 'role' in msg
-    True
-    >>> 'content' in msg
-    False
-    >>> msg.content = 'hello!'
-    >>> 'content' in msg
-    True
-    >>> msg = Message(role='user', content='hello!')
-    >>> 'content' in msg
-    True
-    >>> 'tool_calls' in msg
-    False
-    >>> msg['tool_calls'] = []
-    >>> 'tool_calls' in msg
-    True
-    >>> msg['tool_calls'] = [Message.ToolCall(function=Message.ToolCall.Function(name='foo', arguments={}))]
-    >>> 'tool_calls' in msg
-    True
-    >>> msg['tool_calls'] = None
-    >>> 'tool_calls' in msg
-    True
-    >>> tool = Tool()
-    >>> 'type' in tool
-    True
-    """
-    if key in self.model_fields_set:
-      return True
-
-    if key in self.model_fields:
-      return self.model_fields[key].default is not None
-
-    return False
-
-  def get(self, key: str, default: Any = None) -> Any:
-    """
-    >>> msg = Message(role='user')
-    >>> msg.get('role')
-    'user'
-    >>> msg = Message(role='user')
-    >>> msg.get('nonexistent')
-    >>> msg = Message(role='user')
-    >>> msg.get('nonexistent', 'default')
-    'default'
-    >>> msg = Message(role='user', tool_calls=[ Message.ToolCall(function=Message.ToolCall.Function(name='foo', arguments={}))])
-    >>> msg.get('tool_calls')[0]['function']['name']
-    'foo'
-    """
-    return self[key] if key in self else default
-
-
-class Options(SubscriptableBaseModel):
-  # load time options
-  numa: Optional[bool] = None
-  num_ctx: Optional[int] = None
-  num_batch: Optional[int] = None
-  num_gpu: Optional[int] = None
-  main_gpu: Optional[int] = None
-  low_vram: Optional[bool] = None
-  f16_kv: Optional[bool] = None
-  logits_all: Optional[bool] = None
-  vocab_only: Optional[bool] = None
-  use_mmap: Optional[bool] = None
-  use_mlock: Optional[bool] = None
-  embedding_only: Optional[bool] = None
-  num_thread: Optional[int] = None
-
-  # runtime options
-  num_keep: Optional[int] = None
-  seed: Optional[int] = None
-  num_predict: Optional[int] = None
-  top_k: Optional[int] = None
-  top_p: Optional[float] = None
-  tfs_z: Optional[float] = None
-  typical_p: Optional[float] = None
-  repeat_last_n: Optional[int] = None
-  temperature: Optional[float] = None
-  repeat_penalty: Optional[float] = None
-  presence_penalty: Optional[float] = None
-  frequency_penalty: Optional[float] = None
-  mirostat: Optional[int] = None
-  mirostat_tau: Optional[float] = None
-  mirostat_eta: Optional[float] = None
-  penalize_newline: Optional[bool] = None
-  stop: Optional[Sequence[str]] = None
-
-
-class BaseRequest(SubscriptableBaseModel):
-  model: Annotated[str, Field(min_length=1)]
-  'Model to use for the request.'
-
-
-class BaseStreamableRequest(BaseRequest):
-  stream: Optional[bool] = None
-  'Stream response.'
-
-
-class BaseGenerateRequest(BaseStreamableRequest):
-  options: Optional[Union[Mapping[str, Any], Options]] = None
-  'Options to use for the request.'
-
-  format: Optional[Union[Literal['', 'json'], JsonSchemaValue]] = None
-  'Format of the response.'
-
-  keep_alive: Optional[Union[float, str]] = None
-  'Keep model alive for the specified duration.'
-
-
-class Image(BaseModel):
-  value: Union[str, bytes, Path]
-
-  @model_serializer
-  def serialize_model(self):
-    if isinstance(self.value, (Path, bytes)):
-      return b64encode(self.value.read_bytes() if isinstance(self.value, Path) else self.value).decode()
-
-    if isinstance(self.value, str):
-      try:
-        if Path(self.value).exists():
-          return b64encode(Path(self.value).read_bytes()).decode()
-      except Exception:
-        # Long base64 string can't be wrapped in Path, so try to treat as base64 string
-        pass
-
-      # String might be a file path, but might not exist
-      if self.value.split('.')[-1] in ('png', 'jpg', 'jpeg', 'webp'):
-        raise ValueError(f'File {self.value} does not exist')
-
-      try:
-        # Try to decode to check if it's already base64
-        b64decode(self.value)
-        return self.value
-      except Exception:
-        raise ValueError('Invalid image data, expected base64 string or path to image file') from Exception
-
-
-class GenerateRequest(BaseGenerateRequest):
-  prompt: Optional[str] = None
-  'Prompt to generate response from.'
-
-  suffix: Optional[str] = None
-  'Suffix to append to the response.'
-
-  system: Optional[str] = None
-  'System prompt to prepend to the prompt.'
-
-  template: Optional[str] = None
-  'Template to use for the response.'
-
-  context: Optional[Sequence[int]] = None
-  'Tokenized history to use for the response.'
-
-  raw: Optional[bool] = None
-
-  images: Optional[Sequence[Image]] = None
-  'Image data for multimodal models.'
-
-
-class BaseGenerateResponse(SubscriptableBaseModel):
-  model: Optional[str] = None
+class BaseGenerateResponse(TypedDict):
+  model: str
  'Model used to generate response.'

-  created_at: Optional[str] = None
+  created_at: str
  'Time when the request was created.'

-  done: Optional[bool] = None
+  done: bool
  'True if response is complete, otherwise False. Useful for streaming to detect the final response.'

-  done_reason: Optional[str] = None
+  done_reason: str
  'Reason for completion. Only present when done is True.'

-  total_duration: Optional[int] = None
+  total_duration: int
  'Total duration in nanoseconds.'

-  load_duration: Optional[int] = None
+  load_duration: int
  'Load duration in nanoseconds.'

-  prompt_eval_count: Optional[int] = None
+  prompt_eval_count: int
  'Number of tokens evaluated in the prompt.'

-  prompt_eval_duration: Optional[int] = None
+  prompt_eval_duration: int
  'Duration of evaluating the prompt in nanoseconds.'

-  eval_count: Optional[int] = None
+  eval_count: int
  'Number of tokens evaluated in inference.'

-  eval_duration: Optional[int] = None
+  eval_duration: int
  'Duration of evaluating inference in nanoseconds.'


@@ -248,22 +49,24 @@ class GenerateResponse(BaseGenerateResponse):
  response: str
  'Response content. When streaming, this contains a fragment of the response.'

-  context: Optional[Sequence[int]] = None
+  context: Sequence[int]
  'Tokenized history up to the point of the response.'

+  tool_calls: Sequence[Any]
+  'List of tool calls made by the model.'

-class Message(SubscriptableBaseModel):
+class Message(TypedDict):
  """
  Chat message.
  """

-  role: Literal['user', 'assistant', 'system', 'tool']
-  "Assumed role of the message. Response messages has role 'assistant' or 'tool'."
+  role: Literal['user', 'assistant', 'system']
+  "Assumed role of the message. Response messages always has role 'assistant'."

-  content: Optional[str] = None
+  content: str
  'Content of the message. Response messages contains message fragments when streaming.'

-  images: Optional[Sequence[Image]] = None
+  images: NotRequired[Sequence[Any]]
  """
  Optional list of image data for multimodal models.

@@ -275,62 +78,6 @@ class Message(SubscriptableBaseModel):
  Valid image formats depend on the model. See the model card for more information.
  """

-  class ToolCall(SubscriptableBaseModel):
-    """
-    Model tool calls.
-    """
-
-    class Function(SubscriptableBaseModel):
-      """
-      Tool call function.
-      """
-
-      name: str
-      'Name of the function.'
-
-      arguments: Mapping[str, Any]
-      'Arguments of the function.'
-
-    function: Function
-    'Function to be called.'
-
-  tool_calls: Optional[Sequence[ToolCall]] = None
-  """
-  Tools calls to be made by the model.
-  """
-
-
-class Tool(SubscriptableBaseModel):
-  type: Optional[Literal['function']] = 'function'
-
-  class Function(SubscriptableBaseModel):
-    name: Optional[str] = None
-    description: Optional[str] = None
-
-    class Parameters(SubscriptableBaseModel):
-      type: Optional[Literal['object']] = 'object'
-      required: Optional[Sequence[str]] = None
-
-      class Property(SubscriptableBaseModel):
-        model_config = ConfigDict(arbitrary_types_allowed=True)
-
-        type: Optional[str] = None
-        description: Optional[str] = None
-
-      properties: Optional[Mapping[str, Property]] = None
-
-    parameters: Optional[Parameters] = None
-
-  function: Optional[Function] = None
-
-
-class ChatRequest(BaseGenerateRequest):
-  messages: Optional[Sequence[Union[Mapping[str, Any], Message]]] = None
-  'Messages to chat with.'
-
-  tools: Optional[Sequence[Tool]] = None
-  'Tools to use for the chat.'
-

 class ChatResponse(BaseGenerateResponse):
  """
@@ -341,157 +88,47 @@ class ChatResponse(BaseGenerateResponse):
  'Response message.'


-class EmbedRequest(BaseRequest):
-  input: Union[str, Sequence[str]]
-  'Input text to embed.'
-
-  truncate: Optional[bool] = None
-  'Truncate the input to the maximum token length.'
-
-  options: Optional[Union[Mapping[str, Any], Options]] = None
-  'Options to use for the request.'
-
-  keep_alive: Optional[Union[float, str]] = None
+class ProgressResponse(TypedDict):
+  status: str
+  completed: int
+  total: int
+  digest: str


-class EmbedResponse(BaseGenerateResponse):
-  """
-  Response returned by embed requests.
-  """
+class Options(TypedDict, total=False):
+  # load time options
+  numa: bool
+  num_ctx: int
+  num_batch: int
+  num_gpu: int
+  main_gpu: int
+  low_vram: bool
+  f16_kv: bool
+  logits_all: bool
+  vocab_only: bool
+  use_mmap: bool
+  use_mlock: bool
+  embedding_only: bool
+  num_thread: int

-  embeddings: Sequence[Sequence[float]]
-  'Embeddings of the inputs.'
-
-
-class EmbeddingsRequest(BaseRequest):
-  prompt: Optional[str] = None
-  'Prompt to generate embeddings from.'
-
-  options: Optional[Union[Mapping[str, Any], Options]] = None
-  'Options to use for the request.'
-
-  keep_alive: Optional[Union[float, str]] = None
-
-
-class EmbeddingsResponse(SubscriptableBaseModel):
-  """
-  Response returned by embeddings requests.
-  """
-
-  embedding: Sequence[float]
-  'Embedding of the prompt.'
-
-
-class PullRequest(BaseStreamableRequest):
-  """
-  Request to pull the model.
-  """
-
-  insecure: Optional[bool] = None
-  'Allow insecure (HTTP) connections.'
-
-
-class PushRequest(BaseStreamableRequest):
-  """
-  Request to pull the model.
-  """
-
-  insecure: Optional[bool] = None
-  'Allow insecure (HTTP) connections.'
-
-
-class CreateRequest(BaseStreamableRequest):
-  """
-  Request to create a new model.
-  """
-
-  modelfile: Optional[str] = None
-
-  quantize: Optional[str] = None
-
-
-class ModelDetails(SubscriptableBaseModel):
-  parent_model: Optional[str] = None
-  format: Optional[str] = None
-  family: Optional[str] = None
-  families: Optional[Sequence[str]] = None
-  parameter_size: Optional[str] = None
-  quantization_level: Optional[str] = None
-
-
-class ListResponse(SubscriptableBaseModel):
-  class Model(SubscriptableBaseModel):
-    model: Optional[str] = None
-    modified_at: Optional[datetime] = None
-    digest: Optional[str] = None
-    size: Optional[ByteSize] = None
-    details: Optional[ModelDetails] = None
-
-  models: Sequence[Model]
-  'List of models.'
-
-
-class DeleteRequest(BaseRequest):
-  """
-  Request to delete a model.
-  """
-
-
-class CopyRequest(BaseModel):
-  """
-  Request to copy a model.
-  """
-
-  source: str
-  'Source model to copy.'
-
-  destination: str
-  'Destination model to copy to.'
-
-
-class StatusResponse(SubscriptableBaseModel):
-  status: Optional[str] = None
-
-
-class ProgressResponse(StatusResponse):
-  completed: Optional[int] = None
-  total: Optional[int] = None
-  digest: Optional[str] = None
-
-
-class ShowRequest(BaseRequest):
-  """
-  Request to show model information.
-  """
-
-
-class ShowResponse(SubscriptableBaseModel):
-  modified_at: Optional[datetime] = None
-
-  template: Optional[str] = None
-
-  modelfile: Optional[str] = None
-
-  license: Optional[str] = None
-
-  details: Optional[ModelDetails] = None
-
-  modelinfo: Optional[Mapping[str, Any]] = Field(alias='model_info')
-
-  parameters: Optional[str] = None
-
-
-class ProcessResponse(SubscriptableBaseModel):
-  class Model(SubscriptableBaseModel):
-    model: Optional[str] = None
-    name: Optional[str] = None
-    digest: Optional[str] = None
-    expires_at: Optional[datetime] = None
-    size: Optional[ByteSize] = None
-    size_vram: Optional[ByteSize] = None
-    details: Optional[ModelDetails] = None
-
-  models: Sequence[Model]
+  # runtime options
+  num_keep: int
+  seed: int
+  num_predict: int
+  top_k: int
+  top_p: float
+  tfs_z: float
+  typical_p: float
+  repeat_last_n: int
+  temperature: float
+  repeat_penalty: float
+  presence_penalty: float
+  frequency_penalty: float
+  mirostat: int
+  mirostat_tau: float
+  mirostat_eta: float
+  penalize_newline: bool
+  stop: Sequence[str]


 class RequestError(Exception):
@@ -1,87 +0,0 @@
-from __future__ import annotations
-from collections import defaultdict
-import inspect
-from typing import Callable, Union
-import re
-
-import pydantic
-from ollama._types import Tool
-
-
-def _parse_docstring(doc_string: Union[str, None]) -> dict[str, str]:
-  parsed_docstring = defaultdict(str)
-  if not doc_string:
-    return parsed_docstring
-
-  key = hash(doc_string)
-  for line in doc_string.splitlines():
-    lowered_line = line.lower().strip()
-    if lowered_line.startswith('args:'):
-      key = 'args'
-    elif lowered_line.startswith('returns:') or lowered_line.startswith('yields:') or lowered_line.startswith('raises:'):
-      key = '_'
-
-    else:
-      # maybe change to a list and join later
-      parsed_docstring[key] += f'{line.strip()}\n'
-
-  last_key = None
-  for line in parsed_docstring['args'].splitlines():
-    line = line.strip()
-    if ':' in line:
-      # Split the line on either:
-      # 1. A parenthetical expression like (integer) - captured in group 1
-      # 2. A colon :
-      # Followed by optional whitespace. Only split on first occurrence.
-      parts = re.split(r'(?:\(([^)]*)\)|:)\s*', line, maxsplit=1)
-
-      arg_name = parts[0].strip()
-      last_key = arg_name
-
-      # Get the description - will be in parts[1] if parenthetical or parts[-1] if after colon
-      arg_description = parts[-1].strip()
-      if len(parts) > 2 and parts[1]:  # Has parenthetical content
-        arg_description = parts[-1].split(':', 1)[-1].strip()
-
-      parsed_docstring[last_key] = arg_description
-
-    elif last_key and line:
-      parsed_docstring[last_key] += ' ' + line
-
-  return parsed_docstring
-
-
-def convert_function_to_tool(func: Callable) -> Tool:
-  doc_string_hash = hash(inspect.getdoc(func))
-  parsed_docstring = _parse_docstring(inspect.getdoc(func))
-  schema = type(
-    func.__name__,
-    (pydantic.BaseModel,),
-    {
-      '__annotations__': {k: v.annotation if v.annotation != inspect._empty else str for k, v in inspect.signature(func).parameters.items()},
-      '__signature__': inspect.signature(func),
-      '__doc__': parsed_docstring[doc_string_hash],
-    },
-  ).model_json_schema()
-
-  for k, v in schema.get('properties', {}).items():
-    # If type is missing, the default is string
-    types = {t.get('type', 'string') for t in v.get('anyOf')} if 'anyOf' in v else {v.get('type', 'string')}
-    if 'null' in types:
-      schema['required'].remove(k)
-      types.discard('null')
-
-    schema['properties'][k] = {
-      'description': parsed_docstring[k],
-      'type': ', '.join(types),
-    }
-
-  tool = Tool(
-    function=Tool.Function(
-      name=func.__name__,
-      description=schema.get('description', ''),
-      parameters=Tool.Function.Parameters(**schema),
-    )
-  )
-
-  return Tool.model_validate(tool)
@@ -1,28 +1,14 @@
-# This file is automatically @generated by Poetry 1.8.5 and should not be changed by hand.
-
-[[package]]
-name = "annotated-types"
-version = "0.7.0"
-description = "Reusable constraint types to use with typing.Annotated"
-optional = false
-python-versions = ">=3.8"
-files = [
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-    {file = "annotated_types-0.7.0.tar.gz", hash = "sha256:aff07c09a53a08bc8cfccb9c85b05f1aa9a2a6f23728d790723543408344ce89"},
-]
-
-[package.dependencies]
-typing-extensions = {version = ">=4.0.0", markers = "python_version < \"3.9\""}
+# This file is automatically @generated by Poetry 1.8.2 and should not be changed by hand.

 [[package]]
 name = "anyio"
-version = "4.5.2"
+version = "4.3.0"
 description = "High level compatibility layer for multiple asynchronous event loop implementations"
 optional = false
 python-versions = ">=3.8"
 files = [
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+    {file = "anyio-4.3.0-py3-none-any.whl", hash = "sha256:048e05d0f6caeed70d731f3db756d35dcc1f35747c8c403364a8332c630441b8"},
+    {file = "anyio-4.3.0.tar.gz", hash = "sha256:f75253795a87df48568485fd18cdd2a3fa5c4f7c5be8e5e36637733fce06fed6"},
 ]

 [package.dependencies]
@@ -32,19 +18,19 @@ sniffio = ">=1.1"
 typing-extensions = {version = ">=4.1", markers = "python_version < \"3.11\""}

 [package.extras]
-doc = ["Sphinx (>=7.4,<8.0)", "packaging", "sphinx-autodoc-typehints (>=1.2.0)", "sphinx-rtd-theme"]
-test = ["anyio[trio]", "coverage[toml] (>=7)", "exceptiongroup (>=1.2.0)", "hypothesis (>=4.0)", "psutil (>=5.9)", "pytest (>=7.0)", "pytest-mock (>=3.6.1)", "trustme", "truststore (>=0.9.1)", "uvloop (>=0.21.0b1)"]
-trio = ["trio (>=0.26.1)"]
+doc = ["Sphinx (>=7)", "packaging", "sphinx-autodoc-typehints (>=1.2.0)", "sphinx-rtd-theme"]
+test = ["anyio[trio]", "coverage[toml] (>=7)", "exceptiongroup (>=1.2.0)", "hypothesis (>=4.0)", "psutil (>=5.9)", "pytest (>=7.0)", "pytest-mock (>=3.6.1)", "trustme", "uvloop (>=0.17)"]
+trio = ["trio (>=0.23)"]

 [[package]]
 name = "certifi"
-version = "2024.8.30"
+version = "2024.2.2"
 description = "Python package for providing Mozilla's CA Bundle."
 optional = false
 python-versions = ">=3.6"
 files = [
-    {file = "certifi-2024.8.30-py3-none-any.whl", hash = "sha256:922820b53db7a7257ffbda3f597266d435245903d80737e34f8a45ff3e3230d8"},
-    {file = "certifi-2024.8.30.tar.gz", hash = "sha256:bec941d2aa8195e248a60b31ff9f0558284cf01a52591ceda73ea9afffd69fd9"},
+    {file = "certifi-2024.2.2-py3-none-any.whl", hash = "sha256:dc383c07b76109f368f6106eee2b593b04a011ea4d55f652c6ca24a754d1cdd1"},
+    {file = "certifi-2024.2.2.tar.gz", hash = "sha256:0569859f95fc761b18b45ef421b1290a0f65f147e92a1e5eb3e635f9a5e4e66f"},
 ]

 [[package]]
@@ -60,83 +46,63 @@ files = [

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+version = "7.4.4"
 description = "Code coverage measurement for Python"
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 http2 = ["h2 (>=3,<5)"]
 socks = ["socksio (==1.*)"]
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 python-versions = ">=3.8"
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 socks = ["socksio (==1.*)"]
-zstd = ["zstandard (>=0.18.0)"]

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 version = "2.0.0"
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+version = "24.0"
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 version = "1.5.0"
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 testing = ["pytest", "pytest-benchmark"]

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 ]

 [[package]]
@@ -572,35 +495,35 @@ files = [

 [[package]]
 name = "tomli"
-version = "2.0.2"
+version = "2.0.1"
 description = "A lil' TOML parser"
 optional = false
-python-versions = ">=3.8"
+python-versions = ">=3.7"
 files = [
-    {file = "tomli-2.0.2-py3-none-any.whl", hash = "sha256:2ebe24485c53d303f690b0ec092806a085f07af5a5aa1464f3931eec36caaa38"},
-    {file = "tomli-2.0.2.tar.gz", hash = "sha256:d46d457a85337051c36524bc5349dd91b1877838e2979ac5ced3e710ed8a60ed"},
+    {file = "tomli-2.0.1-py3-none-any.whl", hash = "sha256:939de3e7a6161af0c887ef91b7d41a53e7c5a1ca976325f429cb46ea9bc30ecc"},
+    {file = "tomli-2.0.1.tar.gz", hash = "sha256:de526c12914f0c550d15924c62d72abc48d6fe7364aa87328337a31007fe8a4f"},
 ]

 [[package]]
 name = "typing-extensions"
-version = "4.12.2"
+version = "4.10.0"
 description = "Backported and Experimental Type Hints for Python 3.8+"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "typing_extensions-4.12.2-py3-none-any.whl", hash = "sha256:04e5ca0351e0f3f85c6853954072df659d0d13fac324d0072316b67d7794700d"},
-    {file = "typing_extensions-4.12.2.tar.gz", hash = "sha256:1a7ead55c7e559dd4dee8856e3a88b41225abfe1ce8df57b7c13915fe121ffb8"},
+    {file = "typing_extensions-4.10.0-py3-none-any.whl", hash = "sha256:69b1a937c3a517342112fb4c6df7e72fc39a38e7891a5730ed4985b5214b5475"},
+    {file = "typing_extensions-4.10.0.tar.gz", hash = "sha256:b0abd7c89e8fb96f98db18d86106ff1d90ab692004eb746cf6eda2682f91b3cb"},
 ]

 [[package]]
 name = "werkzeug"
-version = "3.0.6"
+version = "3.0.1"
 description = "The comprehensive WSGI web application library."
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "werkzeug-3.0.6-py3-none-any.whl", hash = "sha256:1bc0c2310d2fbb07b1dd1105eba2f7af72f322e1e455f2f93c993bee8c8a5f17"},
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+    {file = "werkzeug-3.0.1-py3-none-any.whl", hash = "sha256:90a285dc0e42ad56b34e696398b8122ee4c681833fb35b8334a095d82c56da10"},
+    {file = "werkzeug-3.0.1.tar.gz", hash = "sha256:507e811ecea72b18a404947aded4b3390e1db8f826b494d76550ef45bb3b1dcc"},
 ]

 [package.dependencies]
@@ -612,4 +535,4 @@ watchdog = ["watchdog (>=2.3)"]
 [metadata]
 lock-version = "2.0"
 python-versions = "^3.8"
-content-hash = "8e93767305535b0a02f0d724edf1249fd928ff1021644eb9dc26dbfa191f6971"
+content-hash = "aa94e026d55b1357763a45d56cdcd20d0b53ec318350c2176b19313e315ab96d"
@@ -5,20 +5,20 @@ description = "The official Python client for Ollama."
 authors = ["Ollama <hello@ollama.com>"]
 license = "MIT"
 readme = "README.md"
-homepage = "https://ollama.com"
-repository = "https://github.com/ollama/ollama-python"
+homepage = "https://ollama.ai"
+repository = "https://github.com/jmorganca/ollama-python"

 [tool.poetry.dependencies]
 python = "^3.8"
 httpx = "^0.27.0"
-pydantic = "^2.9.0"

 [tool.poetry.group.dev.dependencies]
 pytest = ">=7.4.3,<9.0.0"
-pytest-asyncio = ">=0.23.2,<0.25.0"
+pytest-asyncio = "^0.23.2"
 pytest-cov = ">=4.1,<6.0"
 pytest-httpserver = "^1.0.8"
-ruff = ">=0.1.8,<0.8.0"
+pillow = "^10.2.0"
+ruff = ">=0.1.8,<0.5.0"

 [build-system]
 requires = ["poetry-core"]
@@ -1,123 +1,27 @@
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-    --hash=sha256:1f02e8b43a8fbbc3f3e0d4f0f4bfc8131bcb4eebe8849b8e5c773f3a1c582a53 \
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-anyio==4.5.2 ; python_version >= "3.8" and python_version < "4.0" \
-    --hash=sha256:23009af4ed04ce05991845451e11ef02fc7c5ed29179ac9a420e5ad0ac7ddc5b \
-    --hash=sha256:c011ee36bc1e8ba40e5a81cb9df91925c218fe9b778554e0b56a21e1b5d4716f
-certifi==2024.8.30 ; python_version >= "3.8" and python_version < "4.0" \
-    --hash=sha256:922820b53db7a7257ffbda3f597266d435245903d80737e34f8a45ff3e3230d8 \
-    --hash=sha256:bec941d2aa8195e248a60b31ff9f0558284cf01a52591ceda73ea9afffd69fd9
-exceptiongroup==1.2.2 ; python_version >= "3.8" and python_version < "3.11" \
-    --hash=sha256:3111b9d131c238bec2f8f516e123e14ba243563fb135d3fe885990585aa7795b \
-    --hash=sha256:47c2edf7c6738fafb49fd34290706d1a1a2f4d1c6df275526b62cbb4aa5393cc
+anyio==4.3.0 ; python_version >= "3.8" and python_version < "4.0" \
+    --hash=sha256:048e05d0f6caeed70d731f3db756d35dcc1f35747c8c403364a8332c630441b8 \
+    --hash=sha256:f75253795a87df48568485fd18cdd2a3fa5c4f7c5be8e5e36637733fce06fed6
+certifi==2024.2.2 ; python_version >= "3.8" and python_version < "4.0" \
+    --hash=sha256:0569859f95fc761b18b45ef421b1290a0f65f147e92a1e5eb3e635f9a5e4e66f \
+    --hash=sha256:dc383c07b76109f368f6106eee2b593b04a011ea4d55f652c6ca24a754d1cdd1
+exceptiongroup==1.2.0 ; python_version >= "3.8" and python_version < "3.11" \
+    --hash=sha256:4bfd3996ac73b41e9b9628b04e079f193850720ea5945fc96a08633c66912f14 \
+    --hash=sha256:91f5c769735f051a4290d52edd0858999b57e5876e9f85937691bd4c9fa3ed68
 h11==0.14.0 ; python_version >= "3.8" and python_version < "4.0" \
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    --hash=sha256:e3fe4ac4b851c468cc8363d500db52c2ead036020723024a109d37346efaa761
-httpcore==1.0.6 ; python_version >= "3.8" and python_version < "4.0" \
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-    --hash=sha256:73f6dbd6eb8c21bbf7ef8efad555481853f5f6acdeaff1edb0694289269ee17f
-httpx==0.27.2 ; python_version >= "3.8" and python_version < "4.0" \
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-    --hash=sha256:f7c2be1d2f3c3c3160d441802406b206c2b76f5947b11115e6df10c6c65e66c2
-idna==3.10 ; python_version >= "3.8" and python_version < "4.0" \
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-    --hash=sha256:946d195a0d259cbba61165e88e65941f16e9b36ea6ddb97f00452bae8b1287d3
-pydantic-core==2.23.4 ; python_version >= "3.8" and python_version < "4.0" \
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-    --hash=sha256:9d18368b137c6295db49ce7218b1a9ba15c5bc254c96d7c9f9e924a9bc7825ad \
-    --hash=sha256:a4fa4fc04dff799089689f4fd502ce7d59de529fc2f40a2c8836886c03e0175a \
-    --hash=sha256:a5c7ba8ffb6d6f8f2ab08743be203654bb1aaa8c9dcb09f82ddd34eadb695605 \
-    --hash=sha256:aea443fffa9fbe3af1a9ba721a87f926fe548d32cab71d188a6ede77d0ff244e \
-    --hash=sha256:b10bd51f823d891193d4717448fab065733958bdb6a6b351967bd349d48d5c9b \
-    --hash=sha256:ba1a0996f6c2773bd83e63f18914c1de3c9dd26d55f4ac302a7efe93fb8e7433 \
-    --hash=sha256:bb2802e667b7051a1bebbfe93684841cc9351004e2badbd6411bf357ab8d5ac8 \
-    --hash=sha256:cfdd16ab5e59fc31b5e906d1a3f666571abc367598e3e02c83403acabc092e07 \
-    --hash=sha256:d06b0c8da4f16d1d1e352134427cb194a0a6e19ad5db9161bf32b2113409e728 \
-    --hash=sha256:d0776dea117cf5272382634bd2a5c1b6eb16767c223c6a5317cd3e2a757c61a0 \
-    --hash=sha256:d18ca8148bebe1b0a382a27a8ee60350091a6ddaf475fa05ef50dc35b5df6327 \
-    --hash=sha256:d4488a93b071c04dc20f5cecc3631fc78b9789dd72483ba15d423b5b3689b555 \
-    --hash=sha256:d5f7a395a8cf1621939692dba2a6b6a830efa6b3cee787d82c7de1ad2930de64 \
-    --hash=sha256:d7a80d21d613eec45e3d41eb22f8f94ddc758a6c4720842dc74c0581f54993d6 \
-    --hash=sha256:d97683ddee4723ae8c95d1eddac7c192e8c552da0c73a925a89fa8649bf13eea \
-    --hash=sha256:dcedcd19a557e182628afa1d553c3895a9f825b936415d0dbd3cd0bbcfd29b4b \
-    --hash=sha256:de6d1d1b9e5101508cb37ab0d972357cac5235f5c6533d1071964c47139257df \
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-    --hash=sha256:df933278128ea1cd77772673c73954e53a1c95a4fdf41eef97c2b779271bd0bd \
-    --hash=sha256:e08277a400de01bc72436a0ccd02bdf596631411f592ad985dcee21445bd0068 \
-    --hash=sha256:e38e63e6f3d1cec5a27e0afe90a085af8b6806ee208b33030e65b6516353f1a3 \
-    --hash=sha256:e55541f756f9b3ee346b840103f32779c695a19826a4c442b7954550a0972040 \
-    --hash=sha256:ec4e55f79b1c4ffb2eecd8a0cfba9955a2588497d96851f4c8f99aa4a1d39b12 \
-    --hash=sha256:ed1a53de42fbe34853ba90513cea21673481cd81ed1be739f7f2efb931b24916 \
-    --hash=sha256:ed541d70698978a20eb63d8c5d72f2cc6d7079d9d90f6b50bad07826f1320f5f \
-    --hash=sha256:f09e2ff1f17c2b51f2bc76d1cc33da96298f0a036a137f5440ab3ec5360b624f \
-    --hash=sha256:f220b0eea5965dec25480b6333c788fb72ce5f9129e8759ef876a1d805d00801 \
-    --hash=sha256:f3e0da4ebaef65158d4dfd7d3678aad692f7666877df0002b8a522cdf088f231 \
-    --hash=sha256:f455ee30a9d61d3e1a15abd5068827773d6e4dc513e795f380cdd59932c782d5 \
-    --hash=sha256:f5ef8f42bec47f21d07668a043f077d507e5bf4e668d5c6dfe6aaba89de1a5b8 \
-    --hash=sha256:f69a8e0b033b747bb3e36a44e7732f0c99f7edd5cea723d45bc0d6e95377ffee \
-    --hash=sha256:ff02b6d461a6de369f07ec15e465a88895f3223eb75073ffea56b84d9331f607
-pydantic==2.9.2 ; python_version >= "3.8" and python_version < "4.0" \
-    --hash=sha256:d155cef71265d1e9807ed1c32b4c8deec042a44a50a4188b25ac67ecd81a9c0f \
-    --hash=sha256:f048cec7b26778210e28a0459867920654d48e5e62db0958433636cde4254f12
+httpcore==1.0.4 ; python_version >= "3.8" and python_version < "4.0" \
+    --hash=sha256:ac418c1db41bade2ad53ae2f3834a3a0f5ae76b56cf5aa497d2d033384fc7d73 \
+    --hash=sha256:cb2839ccfcba0d2d3c1131d3c3e26dfc327326fbe7a5dc0dbfe9f6c9151bb022
+httpx==0.27.0 ; python_version >= "3.8" and python_version < "4.0" \
+    --hash=sha256:71d5465162c13681bff01ad59b2cc68dd838ea1f10e51574bac27103f00c91a5 \
+    --hash=sha256:a0cb88a46f32dc874e04ee956e4c2764aba2aa228f650b06788ba6bda2962ab5
+idna==3.6 ; python_version >= "3.8" and python_version < "4.0" \
+    --hash=sha256:9ecdbbd083b06798ae1e86adcbfe8ab1479cf864e4ee30fe4e46a003d12491ca \
+    --hash=sha256:c05567e9c24a6b9faaa835c4821bad0590fbb9d5779e7caa6e1cc4978e7eb24f
 sniffio==1.3.1 ; python_version >= "3.8" and python_version < "4.0" \
    --hash=sha256:2f6da418d1f1e0fddd844478f41680e794e6051915791a034ff65e5f100525a2 \
    --hash=sha256:f4324edc670a0f49750a81b895f35c3adb843cca46f0530f79fc1babb23789dc
-typing-extensions==4.12.2 ; python_version >= "3.8" and python_version < "4.0" \
-    --hash=sha256:04e5ca0351e0f3f85c6853954072df659d0d13fac324d0072316b67d7794700d \
-    --hash=sha256:1a7ead55c7e559dd4dee8856e3a88b41225abfe1ce8df57b7c13915fe121ffb8
+typing-extensions==4.10.0 ; python_version >= "3.8" and python_version < "3.11" \
+    --hash=sha256:69b1a937c3a517342112fb4c6df7e72fc39a38e7891a5730ed4985b5214b5475 \
+    --hash=sha256:b0abd7c89e8fb96f98db18d86106ff1d90ab692004eb746cf6eda2682f91b3cb
@@ -1,54 +0,0 @@
-from base64 import b64encode
-from pathlib import Path
-
-import pytest
-from ollama._types import Image
-import tempfile
-
-
-def test_image_serialization_bytes():
-  image_bytes = b'test image bytes'
-  encoded_string = b64encode(image_bytes).decode()
-  img = Image(value=image_bytes)
-  assert img.model_dump() == encoded_string
-
-
-def test_image_serialization_base64_string():
-  b64_str = 'dGVzdCBiYXNlNjQgc3RyaW5n'
-  img = Image(value=b64_str)
-  assert img.model_dump() == b64_str  # Should return as-is if valid base64
-
-
-def test_image_serialization_long_base64_string():
-  b64_str = 'dGVzdCBiYXNlNjQgc3RyaW5n' * 1000
-  img = Image(value=b64_str)
-  assert img.model_dump() == b64_str  # Should return as-is if valid base64
-
-
-def test_image_serialization_plain_string():
-  img = Image(value='not a path or base64')
-  assert img.model_dump() == 'not a path or base64'  # Should return as-is
-
-
-def test_image_serialization_path():
-  with tempfile.NamedTemporaryFile() as temp_file:
-    temp_file.write(b'test file content')
-    temp_file.flush()
-    img = Image(value=Path(temp_file.name))
-    assert img.model_dump() == b64encode(b'test file content').decode()
-
-
-def test_image_serialization_string_path():
-  with tempfile.NamedTemporaryFile() as temp_file:
-    temp_file.write(b'test file content')
-    temp_file.flush()
-    img = Image(value=temp_file.name)
-    assert img.model_dump() == b64encode(b'test file content').decode()
-
-  with pytest.raises(ValueError):
-    img = Image(value='some_path/that/does/not/exist.png')
-    img.model_dump()
-
-  with pytest.raises(ValueError):
-    img = Image(value='not an image')
-    img.model_dump()
@@ -1,270 +0,0 @@
-import json
-import sys
-from typing import Dict, List, Mapping, Sequence, Set, Tuple, Union
-
-
-from ollama._utils import convert_function_to_tool
-
-
-def test_function_to_tool_conversion():
-  def add_numbers(x: int, y: Union[int, None] = None) -> int:
-    """Add two numbers together.
-    args:
-        x (integer): The first number
-        y (integer, optional): The second number
-
-    Returns:
-        integer: The sum of x and y
-    """
-    return x + y
-
-  tool = convert_function_to_tool(add_numbers).model_dump()
-
-  assert tool['type'] == 'function'
-  assert tool['function']['name'] == 'add_numbers'
-  assert tool['function']['description'] == 'Add two numbers together.'
-  assert tool['function']['parameters']['type'] == 'object'
-  assert tool['function']['parameters']['properties']['x']['type'] == 'integer'
-  assert tool['function']['parameters']['properties']['x']['description'] == 'The first number'
-  assert tool['function']['parameters']['required'] == ['x']
-
-
-def test_function_with_no_args():
-  def simple_func():
-    """
-    A simple function with no arguments.
-    Args:
-        None
-    Returns:
-        None
-    """
-    pass
-
-  tool = convert_function_to_tool(simple_func).model_dump()
-  assert tool['function']['name'] == 'simple_func'
-  assert tool['function']['description'] == 'A simple function with no arguments.'
-  assert tool['function']['parameters']['properties'] == {}
-
-
-def test_function_with_all_types():
-  if sys.version_info >= (3, 10):
-
-    def all_types(
-      x: int,
-      y: str,
-      z: list[int],
-      w: dict[str, int],
-      v: int | str | None,
-    ) -> int | dict[str, int] | str | list[int] | None:
-      """
-      A function with all types.
-      Args:
-          x (integer): The first number
-          y (string): The second number
-          z (array): The third number
-          w (object): The fourth number
-          v (integer | string | None): The fifth number
-      """
-      pass
-  else:
-
-    def all_types(
-      x: int,
-      y: str,
-      z: Sequence,
-      w: Mapping[str, int],
-      d: Dict[str, int],
-      s: Set[int],
-      t: Tuple[int, str],
-      l: List[int],  # noqa: E741
-      o: Union[int, None],
-    ) -> Union[Mapping[str, int], str, None]:
-      """
-      A function with all types.
-      Args:
-          x (integer): The first number
-          y (string): The second number
-          z (array): The third number
-          w (object): The fourth number
-          d (object): The fifth number
-          s (array): The sixth number
-          t (array): The seventh number
-          l (array): The eighth number
-          o (integer | None): The ninth number
-      """
-      pass
-
-  tool_json = convert_function_to_tool(all_types).model_dump_json()
-  tool = json.loads(tool_json)
-  assert tool['function']['parameters']['properties']['x']['type'] == 'integer'
-  assert tool['function']['parameters']['properties']['y']['type'] == 'string'
-
-  if sys.version_info >= (3, 10):
-    assert tool['function']['parameters']['properties']['z']['type'] == 'array'
-    assert tool['function']['parameters']['properties']['w']['type'] == 'object'
-    assert set(x.strip().strip("'") for x in tool['function']['parameters']['properties']['v']['type'].removeprefix('[').removesuffix(']').split(',')) == {'string', 'integer'}
-    assert tool['function']['parameters']['properties']['v']['type'] != 'null'
-    assert tool['function']['parameters']['required'] == ['x', 'y', 'z', 'w']
-  else:
-    assert tool['function']['parameters']['properties']['z']['type'] == 'array'
-    assert tool['function']['parameters']['properties']['w']['type'] == 'object'
-    assert tool['function']['parameters']['properties']['d']['type'] == 'object'
-    assert tool['function']['parameters']['properties']['s']['type'] == 'array'
-    assert tool['function']['parameters']['properties']['t']['type'] == 'array'
-    assert tool['function']['parameters']['properties']['l']['type'] == 'array'
-    assert tool['function']['parameters']['properties']['o']['type'] == 'integer'
-    assert tool['function']['parameters']['properties']['o']['type'] != 'null'
-    assert tool['function']['parameters']['required'] == ['x', 'y', 'z', 'w', 'd', 's', 't', 'l']
-
-
-def test_function_docstring_parsing():
-  from typing import List, Dict, Any
-
-  def func_with_complex_docs(x: int, y: List[str]) -> Dict[str, Any]:
-    """
-    Test function with complex docstring.
-
-    Args:
-        x (integer): A number
-            with multiple lines
-        y (array of string): A list
-            with multiple lines
-
-    Returns:
-        object: A dictionary
-            with multiple lines
-    """
-    pass
-
-  tool = convert_function_to_tool(func_with_complex_docs).model_dump()
-  assert tool['function']['description'] == 'Test function with complex docstring.'
-  assert tool['function']['parameters']['properties']['x']['description'] == 'A number with multiple lines'
-  assert tool['function']['parameters']['properties']['y']['description'] == 'A list with multiple lines'
-
-
-def test_skewed_docstring_parsing():
-  def add_two_numbers(x: int, y: int) -> int:
-    """
-    Add two numbers together.
-    Args:
-        x (integer): : The first number
-
-
-
-
-        y (integer ): The second number
-    Returns:
-        integer: The sum of x and y
-    """
-    pass
-
-  tool = convert_function_to_tool(add_two_numbers).model_dump()
-  assert tool['function']['parameters']['properties']['x']['description'] == ': The first number'
-  assert tool['function']['parameters']['properties']['y']['description'] == 'The second number'
-
-
-def test_function_with_no_docstring():
-  def no_docstring():
-    pass
-
-  def no_docstring_with_args(x: int, y: int):
-    pass
-
-  tool = convert_function_to_tool(no_docstring).model_dump()
-  assert tool['function']['description'] == ''
-
-  tool = convert_function_to_tool(no_docstring_with_args).model_dump()
-  assert tool['function']['description'] == ''
-  assert tool['function']['parameters']['properties']['x']['description'] == ''
-  assert tool['function']['parameters']['properties']['y']['description'] == ''
-
-
-def test_function_with_only_description():
-  def only_description():
-    """
-    A function with only a description.
-    """
-    pass
-
-  tool = convert_function_to_tool(only_description).model_dump()
-  assert tool['function']['description'] == 'A function with only a description.'
-  assert tool['function']['parameters'] == {'type': 'object', 'properties': {}, 'required': None}
-
-  def only_description_with_args(x: int, y: int):
-    """
-    A function with only a description.
-    """
-    pass
-
-  tool = convert_function_to_tool(only_description_with_args).model_dump()
-  assert tool['function']['description'] == 'A function with only a description.'
-  assert tool['function']['parameters'] == {
-    'type': 'object',
-    'properties': {
-      'x': {'type': 'integer', 'description': ''},
-      'y': {'type': 'integer', 'description': ''},
-    },
-    'required': ['x', 'y'],
-  }
-
-
-def test_function_with_yields():
-  def function_with_yields(x: int, y: int):
-    """
-    A function with yields section.
-
-    Args:
-      x: the first number
-      y: the second number
-
-    Yields:
-      The sum of x and y
-    """
-    pass
-
-  tool = convert_function_to_tool(function_with_yields).model_dump()
-  assert tool['function']['description'] == 'A function with yields section.'
-  assert tool['function']['parameters']['properties']['x']['description'] == 'the first number'
-  assert tool['function']['parameters']['properties']['y']['description'] == 'the second number'
-
-
-def test_function_with_no_types():
-  def no_types(a, b):
-    """
-    A function with no types.
-    """
-    pass
-
-  tool = convert_function_to_tool(no_types).model_dump()
-  assert tool['function']['parameters']['properties']['a']['type'] == 'string'
-  assert tool['function']['parameters']['properties']['b']['type'] == 'string'
-
-
-def test_function_with_parentheses():
-  def func_with_parentheses(a: int, b: int) -> int:
-    """
-    A function with parentheses.
-    Args:
-        a: First (:thing) number to add
-        b: Second number to add
-    Returns:
-        int: The sum of a and b
-    """
-    pass
-
-  def func_with_parentheses_and_args(a: int, b: int):
-    """
-    A function with parentheses and args.
-    Args:
-        a(integer) : First (:thing) number to add
-        b(integer) :Second number to add
-    """
-    pass
-
-  tool = convert_function_to_tool(func_with_parentheses).model_dump()
-  assert tool['function']['parameters']['properties']['a']['description'] == 'First (:thing) number to add'
-  assert tool['function']['parameters']['properties']['b']['description'] == 'Second number to add'
-
-  tool = convert_function_to_tool(func_with_parentheses_and_args).model_dump()
-  assert tool['function']['parameters']['properties']['a']['description'] == 'First (:thing) number to add'
-  assert tool['function']['parameters']['properties']['b']['description'] == 'Second number to add'