pyproject.toml: add license metadata to package (#526)

Remove unused `messages` variable from `thinking-generate` example

.github/workflows/publish.yaml

@@ -14,14 +14,11 @@ jobs:
       contents: write
     steps:
       - uses: actions/checkout@v4
-      - run: pipx install poetry
       - uses: actions/setup-python@v5
+      - uses: astral-sh/setup-uv@v5
         with:
-          python-version: '3.x'
-          cache: poetry
-      - run: |
-          poetry version ${GITHUB_REF_NAME#v}
-          poetry build
+          enable-cache: true
+      - run: uv build
       - uses: pypa/gh-action-pypi-publish@release/v1
       - run: gh release upload $GITHUB_REF_NAME dist/*
         env:

.github/workflows/test.yaml

@@ -1,33 +1,36 @@
 name: test
 
 on:
+  push:
+    branches:
+      - main
   pull_request:
 
 jobs:
   test:
-    strategy:
-      matrix:
-        python-version: ['3.8', '3.9', '3.10', '3.11', '3.12']
     runs-on: ubuntu-latest
     steps:
       - uses: actions/checkout@v4
-      - run: pipx install poetry
-      - uses: actions/setup-python@v5
+      - uses: astral-sh/setup-uv@v5
         with:
-          python-version: ${{ matrix.python-version }}
-          cache: poetry
-      - run: poetry install --with=dev
-      - run: poetry run ruff check --output-format=github .
-      - run: poetry run ruff format --check .
-      - run: poetry run pytest . --junitxml=junit/test-results-${{ matrix.python-version }}.xml --cov=ollama --cov-report=xml --cov-report=html
-      - name: check poetry.lock is up-to-date
-        run: poetry check --lock
+          enable-cache: true
+      - run: uvx hatch test -acp
+        if: ${{ always() }}
+  lint:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v4
+      - uses: actions/setup-python@v5
+      - uses: astral-sh/setup-uv@v5
+        with:
+          enable-cache: true
+      - name: check formatting
+        run: uvx hatch fmt --check -f
+      - name: check linting
+        run: uvx hatch fmt --check -l --output-format=github
+      - name: check uv.lock is up-to-date
+        run: uv lock --check
       - name: check requirements.txt is up-to-date
         run: |
-          poetry export >requirements.txt
+          uv export >requirements.txt
           git diff --exit-code requirements.txt
-      - uses: actions/upload-artifact@v4
-        with:
-          name: pytest-results-${{ matrix.python-version }}
-          path: junit/test-results-${{ matrix.python-version }}.xml
-        if: ${{ always() }}

README.md

@@ -2,6 +2,12 @@
 
 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
@@ -11,25 +17,31 @@ pip install ollama
 ## Usage
 
 ```python
-import ollama
-response = ollama.chat(model='llama3.1', messages=[
+from ollama import chat
+from ollama import ChatResponse
+
+response: ChatResponse = chat(model='llama3.2', 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`, modifying function calls to return a Python generator where each part is an object in the stream.
+Response streaming can be enabled by setting `stream=True`.
 
 ```python
-import ollama
+from ollama import chat
 
-stream = ollama.chat(
-    model='llama3.1',
+stream = chat(
+    model='llama3.2',
     messages=[{'role': 'user', 'content': 'Why is the sky blue?'}],
     stream=True,
 )
@@ -38,92 +50,18 @@ for chunk in stream:
   print(chunk['message']['content'], end='', flush=True)
 ```
 
-## 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='llama3.1', messages=[{'role': 'user', 'content': 'Why is the sky blue?'}])
-```
-
-### Generate
-
-```python
-ollama.generate(model='llama3.1', prompt='Why is the sky blue?')
-```
-
-### List
-
-```python
-ollama.list()
-```
-
-### Show
-
-```python
-ollama.show('llama3.1')
-```
-
-### Create
-
-```python
-modelfile='''
-FROM llama3.1
-SYSTEM You are mario from super mario bros.
-'''
-
-ollama.create(model='example', modelfile=modelfile)
-```
-
-### Copy
-
-```python
-ollama.copy('llama3.1', 'user/llama3.1')
-```
-
-### Delete
-
-```python
-ollama.delete('llama3.1')
-```
-
-### Pull
-
-```python
-ollama.pull('llama3.1')
-```
-
-### Push
-
-```python
-ollama.push('user/llama3.1')
-```
-
-### Embeddings
-
-```python
-ollama.embeddings(model='llama3.1', prompt='The sky is blue because of rayleigh scattering')
-```
-
-### Ps
-
-```python
-ollama.ps()
-```
-
 ## Custom client
+A custom client can be created by instantiating `Client` or `AsyncClient` from `ollama`.
 
-A custom client can be created with the following fields:
-
-- `host`: The Ollama host to connect to
-- `timeout`: The timeout for requests
+All extra keyword arguments are passed into the [`httpx.Client`](https://www.python-httpx.org/api/#client).
 
 ```python
 from ollama import Client
-client = Client(host='http://localhost:11434')
-response = client.chat(model='llama3.1', messages=[
+client = Client(
+  host='http://localhost:11434',
+  headers={'x-some-header': 'some-value'}
+)
+response = client.chat(model='llama3.2', messages=[
   {
     'role': 'user',
     'content': 'Why is the sky blue?',
@@ -133,13 +71,15 @@ response = client.chat(model='llama3.1', 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='llama3.1', messages=[message])
+  response = await AsyncClient().chat(model='llama3.2', messages=[message])
 
 asyncio.run(chat())
 ```
@@ -152,12 +92,89 @@ from ollama import AsyncClient
 
 async def chat():
   message = {'role': 'user', 'content': 'Why is the sky blue?'}
-  async for part in await AsyncClient().chat(model='llama3.1', messages=[message], stream=True):
+  async for part in await AsyncClient().chat(model='llama3.2', 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
+ollama.create(model='example', from_='llama3.2', system="You are Mario from Super Mario Bros.")
+```
+
+### 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.

SECURITY.md

@@ -0,0 +1,25 @@
+# Security
+
+The Ollama maintainer team takes security seriously and will actively work to resolve security issues.
+
+## Reporting a vulnerability
+
+If you discover a security vulnerability, please do not open a public issue. Instead, please report it by emailing hello@ollama.com. We ask that you give us sufficient time to investigate and address the vulnerability before disclosing it publicly.
+
+Please include the following details in your report:
+- A description of the vulnerability
+- Steps to reproduce the issue
+- Your assessment of the potential impact
+- Any possible mitigations
+
+## Security best practices
+
+While the maintainer team does their best to secure Ollama, users are encouraged to implement their own security best practices, such as:
+
+- Regularly updating to the latest version of Ollama
+- Securing access to hosted instances of Ollama
+- Monitoring systems for unusual activity
+
+## Contact
+
+For any other questions or concerns related to security, please contact us at hello@ollama.com

examples/README.md

@@ -0,0 +1,71 @@
+# Running Examples
+
+Run the examples in this directory with:
+```sh
+# Run example
+python3 examples/<example>.py
+```
+
+See [ollama/docs/api.md](https://github.com/ollama/ollama/blob/main/docs/api.md) for full API documentation
+
+### Chat - Chat with a model
+- [chat.py](chat.py)
+- [async-chat.py](async-chat.py)
+- [chat-stream.py](chat-stream.py) - Streamed outputs
+- [chat-with-history.py](chat-with-history.py) - Chat with model and maintain history of the conversation
+
+
+### Generate - Generate text with a model
+- [generate.py](generate.py)
+- [async-generate.py](async-generate.py)
+- [generate-stream.py](generate-stream.py) - Streamed outputs
+- [fill-in-middle.py](fill-in-middle.py) - Given a prefix and suffix, fill in the middle
+
+
+### Tools/Function Calling - Call a function with a model
+- [tools.py](tools.py) - Simple example of Tools/Function Calling
+- [async-tools.py](async-tools.py)
+- [multi-tool.py](multi-tool.py) - Using multiple tools, with thinking enabled
+
+
+### Multimodal with Images - Chat with a multimodal (image chat) model
+- [multimodal-chat.py](multimodal-chat.py)
+- [multimodal-generate.py](multimodal-generate.py)
+
+
+### Structured Outputs - Generate structured outputs with a model
+- [structured-outputs.py](structured-outputs.py)
+- [async-structured-outputs.py](async-structured-outputs.py)
+- [structured-outputs-image.py](structured-outputs-image.py)
+
+
+### Ollama List - List all downloaded models and their properties
+- [list.py](list.py)
+
+
+### Ollama Show - Display model properties and capabilities
+- [show.py](show.py)
+
+
+### Ollama ps - Show model status with CPU/GPU usage
+- [ps.py](ps.py)
+
+
+### Ollama Pull - Pull a model from Ollama
+Requirement: `pip install tqdm`
+- [pull.py](pull.py) 
+
+
+### Ollama Create - Create a model from a Modelfile
+- [create.py](create.py) 
+
+
+### Ollama Embed - Generate embeddings with a model
+- [embed.py](embed.py)
+
+
+### Thinking - Enable thinking mode for a model
+- [thinking.py](thinking.py)
+
+### Thinking (generate) - Enable thinking mode for a model
+- [thinking-generate.py](thinking-generate.py)

examples/async-chat-stream/README.md

@@ -1,3 +0,0 @@
-# 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.

examples/async-chat-stream/main.py

@@ -1,59 +0,0 @@
-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):
-  ...

examples/async-chat.py

@@ -0,0 +1,20 @@
+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())

examples/async-generate.py

@@ -0,0 +1,16 @@
+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!')

examples/async-structured-outputs.py

@@ -0,0 +1,34 @@
+import asyncio
+
+from pydantic import BaseModel
+
+from ollama import AsyncClient
+
+
+# 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())

examples/async-tools.py

@@ -0,0 +1,93 @@
+import asyncio
+
+import ollama
+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,
+}
+
+
+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), 'tool_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!')

examples/chat-stream.py

@@ -1,6 +1,5 @@
 from ollama import chat
 
-
 messages = [
   {
     'role': 'user',
@@ -8,8 +7,7 @@ messages = [
   },
 ]
 
-for part in chat('mistral', messages=messages, stream=True):
+for part in chat('llama3.2', messages=messages, stream=True):
   print(part['message']['content'], end='', flush=True)
 
-# end with a newline
 print()

examples/chat-with-history.py

@@ -0,0 +1,34 @@
+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')

examples/chat.py

@@ -1,6 +1,5 @@
 from ollama import chat
 
-
 messages = [
   {
     'role': 'user',
@@ -8,5 +7,5 @@ messages = [
   },
 ]
 
-response = chat('mistral', messages=messages)
+response = chat('llama3.2', messages=messages)
 print(response['message']['content'])

examples/create.py

@@ -0,0 +1,10 @@
+from ollama import Client
+
+client = Client()
+response = client.create(
+  model='my-assistant',
+  from_='llama3.2',
+  system='You are mario from Super Mario Bros.',
+  stream=False,
+)
+print(response.status)

examples/create/main.py

@@ -1,20 +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 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'])

examples/embed.py

@@ -0,0 +1,4 @@
+from ollama import embed
+
+response = embed(model='llama3.2', input='Hello, world!')
+print(response['embeddings'])

examples/generate-stream.py

@@ -1,5 +1,4 @@
 from ollama import generate
 
-
-for part in generate('mistral', 'Why is the sky blue?', stream=True):
+for part in generate('llama3.2', 'Why is the sky blue?', stream=True):
   print(part['response'], end='', flush=True)

examples/generate.py

@@ -1,5 +1,4 @@
 from ollama import generate
 
-
-response = generate('mistral', 'Why is the sky blue?')
+response = generate('llama3.2', 'Why is the sky blue?')
 print(response['response'])

examples/list.py

@@ -0,0 +1,13 @@
+from ollama import ListResponse, list
+
+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')

examples/multi-tool.py

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

examples/multimodal-chat.py

@@ -0,0 +1,24 @@
+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)

examples/multimodal-generate.py

@@ -1,17 +1,14 @@
-import sys
 import random
+import sys
+
 import httpx
 
 from ollama import generate
 
-
 latest = httpx.get('https://xkcd.com/info.0.json')
 latest.raise_for_status()
 
-if len(sys.argv) > 1:
-  num = int(sys.argv[1])
-else:
-  num = random.randint(1, latest.json().get('num'))
+num = int(sys.argv[1]) if len(sys.argv) > 1 else random.randint(1, latest.json().get('num'))
 
 comic = httpx.get(f'https://xkcd.com/{num}/info.0.json')
 comic.raise_for_status()

examples/ps.py

@@ -0,0 +1,27 @@
+from ollama import ProcessResponse, chat, ps, pull
+
+# 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('  Context length: ', model.context_length)
+  print('\n')

examples/ps/main.py

@@ -1,31 +0,0 @@
-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')

examples/pull-progress/README.md

@@ -1,9 +0,0 @@
-# pull-progress
-
-This example emulates `ollama pull` using the Python library and [`tqdm`](https://tqdm.github.io/).
-
-## Setup
-
-```shell
-pip install -r requirements.txt
-```

examples/pull-progress/requirements.txt

@@ -1 +0,0 @@
-tqdm==4.66.1

examples/pull.py

@@ -1,9 +1,9 @@
 from tqdm import tqdm
+
 from ollama import pull
 
-
 current_digest, bars = '', {}
-for progress in pull('mistral', stream=True):
+for progress in pull('llama3.2', stream=True):
   digest = progress.get('digest', '')
   if digest != current_digest and current_digest in bars:
     bars[current_digest].close()

examples/show.py

@@ -0,0 +1,12 @@
+from ollama import ShowResponse, show
+
+response: ShowResponse = show('gemma3')
+print('Model Information:')
+print(f'Modified at:   {response.modified_at}')
+print(f'Template:      {response.template}')
+print(f'Modelfile:     {response.modelfile}')
+print(f'License:       {response.license}')
+print(f'Details:       {response.details}')
+print(f'Model Info:    {response.modelinfo}')
+print(f'Parameters:    {response.parameters}')
+print(f'Capabilities:  {response.capabilities}')

examples/structured-outputs-image.py

@@ -0,0 +1,51 @@
+from pathlib import Path
+from typing import Literal
+
+from pydantic import BaseModel
+
+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)

examples/structured-outputs.py

@@ -0,0 +1,27 @@
+from pydantic import BaseModel
+
+from ollama import chat
+
+
+# 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)

examples/thinking-generate.py

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

examples/thinking.py

@@ -0,0 +1,13 @@
+from ollama import chat
+
+messages = [
+  {
+    'role': 'user',
+    'content': 'What is 10 + 23?',
+  },
+]
+
+response = chat('deepseek-r1', messages=messages, think=True)
+
+print('Thinking:\n========\n\n' + response.message.thinking)
+print('\nResponse:\n========\n\n' + response.message.content)

examples/tools.py

@@ -0,0 +1,84 @@
+from ollama import ChatResponse, chat
+
+
+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
+  """
+
+  # The cast is necessary as returned tool call arguments don't always conform exactly to schema
+  # E.g. this would prevent "what is 30 + 12" to produce '3012' instead of 42
+  return int(a) + int(b)
+
+
+def subtract_two_numbers(a: int, b: int) -> int:
+  """
+  Subtract two numbers
+  """
+
+  # The cast is necessary as returned tool call arguments don't always conform exactly to schema
+  return int(a) - int(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), 'tool_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')

examples/tools/README.md

@@ -1,3 +0,0 @@
-# tools
-
-This example demonstrates how to utilize tool calls with an asynchronous Ollama client and the chat endpoint. 

examples/tools/main.py

@@ -1,87 +0,0 @@
-import json
-import ollama
-import asyncio
-
-
-# Simulates an API call to get flight times
-# In a real application, this would fetch data from a live database or API
-def get_flight_times(departure: str, arrival: str) -> str:
-  flights = {
-    'NYC-LAX': {'departure': '08:00 AM', 'arrival': '11:30 AM', 'duration': '5h 30m'},
-    'LAX-NYC': {'departure': '02:00 PM', 'arrival': '10:30 PM', 'duration': '5h 30m'},
-    'LHR-JFK': {'departure': '10:00 AM', 'arrival': '01:00 PM', 'duration': '8h 00m'},
-    'JFK-LHR': {'departure': '09:00 PM', 'arrival': '09:00 AM', 'duration': '7h 00m'},
-    'CDG-DXB': {'departure': '11:00 AM', 'arrival': '08:00 PM', 'duration': '6h 00m'},
-    'DXB-CDG': {'departure': '03:00 AM', 'arrival': '07:30 AM', 'duration': '7h 30m'},
-  }
-
-  key = f'{departure}-{arrival}'.upper()
-  return json.dumps(flights.get(key, {'error': 'Flight not found'}))
-
-
-async def run(model: str):
-  client = ollama.AsyncClient()
-  # Initialize conversation with a user query
-  messages = [{'role': 'user', 'content': 'What is the flight time from New York (NYC) to Los Angeles (LAX)?'}]
-
-  # First API call: Send the query and function description to the model
-  response = await client.chat(
-    model=model,
-    messages=messages,
-    tools=[
-      {
-        'type': 'function',
-        'function': {
-          'name': 'get_flight_times',
-          'description': 'Get the flight times between two cities',
-          'parameters': {
-            'type': 'object',
-            'properties': {
-              'departure': {
-                'type': 'string',
-                'description': 'The departure city (airport code)',
-              },
-              'arrival': {
-                'type': 'string',
-                'description': 'The arrival city (airport code)',
-              },
-            },
-            'required': ['departure', 'arrival'],
-          },
-        },
-      },
-    ],
-  )
-
-  # Add the model's response to the conversation history
-  messages.append(response['message'])
-
-  # Check if the model decided to use the provided function
-  if not response['message'].get('tool_calls'):
-    print("The model didn't use the function. Its response was:")
-    print(response['message']['content'])
-    return
-
-  # Process function calls made by the model
-  if response['message'].get('tool_calls'):
-    available_functions = {
-      'get_flight_times': get_flight_times,
-    }
-    for tool in response['message']['tool_calls']:
-      function_to_call = available_functions[tool['function']['name']]
-      function_response = function_to_call(tool['function']['arguments']['departure'], tool['function']['arguments']['arrival'])
-      # Add function response to the conversation
-      messages.append(
-        {
-          'role': 'tool',
-          'content': function_response,
-        }
-      )
-
-  # Second API call: Get final response from the model
-  final_response = await client.chat(model=model, messages=messages)
-  print(final_response['message']['content'])
-
-
-# Run the async function
-asyncio.run(run('mistral'))

ollama/__init__.py

@@ -1,36 +1,40 @@
-from ollama._client import Client, AsyncClient
+from ollama._client import AsyncClient, Client
 from ollama._types import (
-  GenerateResponse,
   ChatResponse,
-  ProgressResponse,
+  EmbeddingsResponse,
+  EmbedResponse,
+  GenerateResponse,
+  Image,
+  ListResponse,
   Message,
   Options,
+  ProcessResponse,
+  ProgressResponse,
   RequestError,
   ResponseError,
+  ShowResponse,
+  StatusResponse,
+  Tool,
 )
 
 __all__ = [
-  'Client',
   'AsyncClient',
-  'GenerateResponse',
   'ChatResponse',
-  'ProgressResponse',
+  'Client',
+  'EmbedResponse',
+  'EmbeddingsResponse',
+  'GenerateResponse',
+  'Image',
+  'ListResponse',
   'Message',
   'Options',
+  'ProcessResponse',
+  'ProgressResponse',
   'RequestError',
   'ResponseError',
-  'generate',
-  'chat',
-  'embed',
-  'embeddings',
-  'pull',
-  'push',
-  'create',
-  'delete',
-  'list',
-  'copy',
-  'show',
-  'ps',
+  'ShowResponse',
+  'StatusResponse',
+  'Tool',
 ]
 
 _client = Client()

ollama/_types.py

@@ -1,43 +1,245 @@
+import contextlib
 import json
-from typing import Any, TypedDict, Sequence, Literal, Mapping
+from base64 import b64decode, b64encode
+from datetime import datetime
+from pathlib import Path
+from typing import Any, Dict, List, Mapping, Optional, Sequence, Union
 
-import sys
-
-if sys.version_info < (3, 11):
-  from typing_extensions import NotRequired
-else:
-  from typing import NotRequired
+from pydantic import (
+  BaseModel,
+  ByteSize,
+  ConfigDict,
+  Field,
+  model_serializer,
+)
+from pydantic.json_schema import JsonSchemaValue
+from typing_extensions import Annotated, Literal
 
 
-class BaseGenerateResponse(TypedDict):
-  model: str
+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 value := self.model_fields.get(key):
+      return value.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 getattr(self, key) if hasattr(self, key) 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.'
+
+  think: Optional[bool] = None
+  'Enable thinking mode (for thinking models).'
+
+
+class BaseGenerateResponse(SubscriptableBaseModel):
+  model: Optional[str] = None
   'Model used to generate response.'
 
-  created_at: str
+  created_at: Optional[str] = None
   'Time when the request was created.'
 
-  done: bool
+  done: Optional[bool] = None
   'True if response is complete, otherwise False. Useful for streaming to detect the final response.'
 
-  done_reason: str
+  done_reason: Optional[str] = None
   'Reason for completion. Only present when done is True.'
 
-  total_duration: int
+  total_duration: Optional[int] = None
   'Total duration in nanoseconds.'
 
-  load_duration: int
+  load_duration: Optional[int] = None
   'Load duration in nanoseconds.'
 
-  prompt_eval_count: int
+  prompt_eval_count: Optional[int] = None
   'Number of tokens evaluated in the prompt.'
 
-  prompt_eval_duration: int
+  prompt_eval_duration: Optional[int] = None
   'Duration of evaluating the prompt in nanoseconds.'
 
-  eval_count: int
+  eval_count: Optional[int] = None
   'Number of tokens evaluated in inference.'
 
-  eval_duration: int
+  eval_duration: Optional[int] = None
   'Duration of evaluating inference in nanoseconds.'
 
 
@@ -49,43 +251,28 @@ class GenerateResponse(BaseGenerateResponse):
   response: str
   'Response content. When streaming, this contains a fragment of the response.'
 
-  context: Sequence[int]
+  thinking: Optional[str] = None
+  'Thinking content. Only present when thinking is enabled.'
+
+  context: Optional[Sequence[int]] = None
   'Tokenized history up to the point of the response.'
 
 
-class ToolCallFunction(TypedDict):
-  """
-  Tool call function.
-  """
-
-  name: str
-  'Name of the function.'
-
-  arguments: NotRequired[Mapping[str, Any]]
-  'Arguments of the function.'
-
-
-class ToolCall(TypedDict):
-  """
-  Model tool calls.
-  """
-
-  function: ToolCallFunction
-  'Function to be called.'
-
-
-class Message(TypedDict):
+class Message(SubscriptableBaseModel):
   """
   Chat message.
   """
 
-  role: Literal['user', 'assistant', 'system', 'tool']
-  "Assumed role of the message. Response messages always has role 'assistant' or 'tool'."
+  role: str
+  "Assumed role of the message. Response messages has role 'assistant' or 'tool'."
 
-  content: NotRequired[str]
+  content: Optional[str] = None
   'Content of the message. Response messages contains message fragments when streaming.'
 
-  images: NotRequired[Sequence[Any]]
+  thinking: Optional[str] = None
+  'Thinking content. Only present when thinking is enabled.'
+
+  images: Optional[Sequence[Image]] = None
   """
   Optional list of image data for multimodal models.
 
@@ -97,33 +284,81 @@ class Message(TypedDict):
   Valid image formats depend on the model. See the model card for more information.
   """
 
-  tool_calls: NotRequired[Sequence[ToolCall]]
+  tool_name: Optional[str] = None
+  'Name of the executed tool.'
+
+  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 Property(TypedDict):
-  type: str
-  description: str
-  enum: NotRequired[Sequence[str]]  # `enum` is optional and can be a list of strings
+class Tool(SubscriptableBaseModel):
+  type: Optional[Literal['function']] = 'function'
+
+  class Function(SubscriptableBaseModel):
+    name: Optional[str] = None
+    description: Optional[str] = None
+
+    class Parameters(SubscriptableBaseModel):
+      model_config = ConfigDict(populate_by_name=True)
+      type: Optional[Literal['object']] = 'object'
+      defs: Optional[Any] = Field(None, alias='$defs')
+      items: Optional[Any] = None
+      required: Optional[Sequence[str]] = None
+
+      class Property(SubscriptableBaseModel):
+        model_config = ConfigDict(arbitrary_types_allowed=True)
+
+        type: Optional[Union[str, Sequence[str]]] = None
+        items: Optional[Any] = None
+        description: Optional[str] = None
+        enum: Optional[Sequence[Any]] = None
+
+      properties: Optional[Mapping[str, Property]] = None
+
+    parameters: Optional[Parameters] = None
+
+  function: Optional[Function] = None
 
 
-class Parameters(TypedDict):
-  type: str
-  required: Sequence[str]
-  properties: Mapping[str, Property]
+class ChatRequest(BaseGenerateRequest):
+  @model_serializer(mode='wrap')
+  def serialize_model(self, nxt):
+    output = nxt(self)
+    if output.get('tools'):
+      for tool in output['tools']:
+        if 'function' in tool and 'parameters' in tool['function'] and 'defs' in tool['function']['parameters']:
+          tool['function']['parameters']['$defs'] = tool['function']['parameters'].pop('defs')
+    return output
 
+  messages: Optional[Sequence[Union[Mapping[str, Any], Message]]] = None
+  'Messages to chat with.'
 
-class ToolFunction(TypedDict):
-  name: str
-  description: str
-  parameters: Parameters
+  tools: Optional[Sequence[Tool]] = None
+  'Tools to use for the chat.'
 
-
-class Tool(TypedDict):
-  type: str
-  function: ToolFunction
+  think: Optional[bool] = None
+  'Enable thinking mode (for thinking models).'
 
 
 class ChatResponse(BaseGenerateResponse):
@@ -135,47 +370,172 @@ class ChatResponse(BaseGenerateResponse):
   'Response message.'
 
 
-class ProgressResponse(TypedDict):
-  status: str
-  completed: int
-  total: int
-  digest: str
+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 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
+class EmbedResponse(BaseGenerateResponse):
+  """
+  Response returned by embed requests.
+  """
 
-  # 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]
+  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):
+  @model_serializer(mode='wrap')
+  def serialize_model(self, nxt):
+    output = nxt(self)
+    if 'from_' in output:
+      output['from'] = output.pop('from_')
+    return output
+
+  """
+  Request to create a new model.
+  """
+  quantize: Optional[str] = None
+  from_: Optional[str] = None
+  files: Optional[Dict[str, str]] = None
+  adapters: Optional[Dict[str, str]] = None
+  template: Optional[str] = None
+  license: Optional[Union[str, List[str]]] = None
+  system: Optional[str] = None
+  parameters: Optional[Union[Mapping[str, Any], Options]] = None
+  messages: Optional[Sequence[Union[Mapping[str, Any], Message]]] = 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
+
+  capabilities: Optional[List[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
+    context_length: Optional[int] = None
+
+  models: Sequence[Model]
 
 
 class RequestError(Exception):
@@ -195,12 +555,10 @@ class ResponseError(Exception):
   """
 
   def __init__(self, error: str, status_code: int = -1):
-    try:
-      # try to parse content as JSON and extract 'error'
-      # fallback to raw content if JSON parsing fails
+    # try to parse content as JSON and extract 'error'
+    # fallback to raw content if JSON parsing fails
+    with contextlib.suppress(json.JSONDecodeError):
       error = json.loads(error).get('error', error)
-    except json.JSONDecodeError:
-      ...
 
     super().__init__(error)
     self.error = error
@@ -208,3 +566,6 @@ class ResponseError(Exception):
 
     self.status_code = status_code
     'HTTP status code of the response.'
+
+  def __str__(self) -> str:
+    return f'{self.error} (status code: {self.status_code})'

ollama/_utils.py

@@ -0,0 +1,89 @@
+from __future__ import annotations
+
+import inspect
+import re
+from collections import defaultdict
+from typing import Callable, Union
+
+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 = str(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:', 'yields:', '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 = str(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)

poetry.lock

@@ -1,550 +0,0 @@
-# This file is automatically @generated by Poetry 1.8.3 and should not be changed by hand.
-
-[[package]]
-name = "anyio"
-version = "4.3.0"
-description = "High level compatibility layer for multiple asynchronous event loop implementations"
-optional = false
-python-versions = ">=3.8"
-files = [
-    {file = "anyio-4.3.0-py3-none-any.whl", hash = "sha256:048e05d0f6caeed70d731f3db756d35dcc1f35747c8c403364a8332c630441b8"},
-    {file = "anyio-4.3.0.tar.gz", hash = "sha256:f75253795a87df48568485fd18cdd2a3fa5c4f7c5be8e5e36637733fce06fed6"},
-]
-
-[package.dependencies]
-exceptiongroup = {version = ">=1.0.2", markers = "python_version < \"3.11\""}
-idna = ">=2.8"
-sniffio = ">=1.1"
-typing-extensions = {version = ">=4.1", markers = "python_version < \"3.11\""}
-
-[package.extras]
-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 = "2024.2.2"
-description = "Python package for providing Mozilla's CA Bundle."
-optional = false
-python-versions = ">=3.6"
-files = [
-    {file = "certifi-2024.2.2-py3-none-any.whl", hash = "sha256:dc383c07b76109f368f6106eee2b593b04a011ea4d55f652c6ca24a754d1cdd1"},
-    {file = "certifi-2024.2.2.tar.gz", hash = "sha256:0569859f95fc761b18b45ef421b1290a0f65f147e92a1e5eb3e635f9a5e4e66f"},
-]
-
-[[package]]
-name = "colorama"
-version = "0.4.6"
-description = "Cross-platform colored terminal text."
-optional = false
-python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,!=3.6.*,>=2.7"
-files = [
-    {file = "colorama-0.4.6-py2.py3-none-any.whl", hash = "sha256:4f1d9991f5acc0ca119f9d443620b77f9d6b33703e51011c16baf57afb285fc6"},
-    {file = "colorama-0.4.6.tar.gz", hash = "sha256:08695f5cb7ed6e0531a20572697297273c47b8cae5a63ffc6d6ed5c201be6e44"},
-]
-
-[[package]]
-name = "coverage"
-version = "7.4.4"
-description = "Code coverage measurement for Python"
-optional = false
-python-versions = ">=3.8"
-files = [
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-]
-
-[package.extras]
-docs = ["furo", "olefile", "sphinx (>=7.3)", "sphinx-copybutton", "sphinx-inline-tabs", "sphinxext-opengraph"]
-fpx = ["olefile"]
-mic = ["olefile"]
-tests = ["check-manifest", "coverage", "defusedxml", "markdown2", "olefile", "packaging", "pyroma", "pytest", "pytest-cov", "pytest-timeout"]
-typing = ["typing-extensions"]
-xmp = ["defusedxml"]
-
-[[package]]
-name = "pluggy"
-version = "1.5.0"
-description = "plugin and hook calling mechanisms for python"
-optional = false
-python-versions = ">=3.8"
-files = [
-    {file = "pluggy-1.5.0-py3-none-any.whl", hash = "sha256:44e1ad92c8ca002de6377e165f3e0f1be63266ab4d554740532335b9d75ea669"},
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-]
-
-[package.extras]
-dev = ["pre-commit", "tox"]
-testing = ["pytest", "pytest-benchmark"]
-
-[[package]]
-name = "pytest"
-version = "8.3.2"
-description = "pytest: simple powerful testing with Python"
-optional = false
-python-versions = ">=3.8"
-files = [
-    {file = "pytest-8.3.2-py3-none-any.whl", hash = "sha256:4ba08f9ae7dcf84ded419494d229b48d0903ea6407b030eaec46df5e6a73bba5"},
-    {file = "pytest-8.3.2.tar.gz", hash = "sha256:c132345d12ce551242c87269de812483f5bcc87cdbb4722e48487ba194f9fdce"},
-]
-
-[package.dependencies]
-colorama = {version = "*", markers = "sys_platform == \"win32\""}
-exceptiongroup = {version = ">=1.0.0rc8", markers = "python_version < \"3.11\""}
-iniconfig = "*"
-packaging = "*"
-pluggy = ">=1.5,<2"
-tomli = {version = ">=1", markers = "python_version < \"3.11\""}
-
-[package.extras]
-dev = ["argcomplete", "attrs (>=19.2)", "hypothesis (>=3.56)", "mock", "pygments (>=2.7.2)", "requests", "setuptools", "xmlschema"]
-
-[[package]]
-name = "pytest-asyncio"
-version = "0.24.0"
-description = "Pytest support for asyncio"
-optional = false
-python-versions = ">=3.8"
-files = [
-    {file = "pytest_asyncio-0.24.0-py3-none-any.whl", hash = "sha256:a811296ed596b69bf0b6f3dc40f83bcaf341b155a269052d82efa2b25ac7037b"},
-    {file = "pytest_asyncio-0.24.0.tar.gz", hash = "sha256:d081d828e576d85f875399194281e92bf8a68d60d72d1a2faf2feddb6c46b276"},
-]
-
-[package.dependencies]
-pytest = ">=8.2,<9"
-
-[package.extras]
-docs = ["sphinx (>=5.3)", "sphinx-rtd-theme (>=1.0)"]
-testing = ["coverage (>=6.2)", "hypothesis (>=5.7.1)"]
-
-[[package]]
-name = "pytest-cov"
-version = "5.0.0"
-description = "Pytest plugin for measuring coverage."
-optional = false
-python-versions = ">=3.8"
-files = [
-    {file = "pytest-cov-5.0.0.tar.gz", hash = "sha256:5837b58e9f6ebd335b0f8060eecce69b662415b16dc503883a02f45dfeb14857"},
-    {file = "pytest_cov-5.0.0-py3-none-any.whl", hash = "sha256:4f0764a1219df53214206bf1feea4633c3b558a2925c8b59f144f682861ce652"},
-]
-
-[package.dependencies]
-coverage = {version = ">=5.2.1", extras = ["toml"]}
-pytest = ">=4.6"
-
-[package.extras]
-testing = ["fields", "hunter", "process-tests", "pytest-xdist", "virtualenv"]
-
-[[package]]
-name = "pytest-httpserver"
-version = "1.1.0"
-description = "pytest-httpserver is a httpserver for pytest"
-optional = false
-python-versions = ">=3.8"
-files = [
-    {file = "pytest_httpserver-1.1.0-py3-none-any.whl", hash = "sha256:7ef88be8ed3354b6784daa3daa75a422370327c634053cefb124903fa8d73a41"},
-    {file = "pytest_httpserver-1.1.0.tar.gz", hash = "sha256:6b1cb0199e2ed551b1b94d43f096863bbf6ae5bcd7c75c2c06845e5ce2dc8701"},
-]
-
-[package.dependencies]
-Werkzeug = ">=2.0.0"
-
-[[package]]
-name = "ruff"
-version = "0.6.3"
-description = "An extremely fast Python linter and code formatter, written in Rust."
-optional = false
-python-versions = ">=3.7"
-files = [
-    {file = "ruff-0.6.3-py3-none-linux_armv6l.whl", hash = "sha256:97f58fda4e309382ad30ede7f30e2791d70dd29ea17f41970119f55bdb7a45c3"},
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-]
-
-[[package]]
-name = "sniffio"
-version = "1.3.1"
-description = "Sniff out which async library your code is running under"
-optional = false
-python-versions = ">=3.7"
-files = [
-    {file = "sniffio-1.3.1-py3-none-any.whl", hash = "sha256:2f6da418d1f1e0fddd844478f41680e794e6051915791a034ff65e5f100525a2"},
-    {file = "sniffio-1.3.1.tar.gz", hash = "sha256:f4324edc670a0f49750a81b895f35c3adb843cca46f0530f79fc1babb23789dc"},
-]
-
-[[package]]
-name = "tomli"
-version = "2.0.1"
-description = "A lil' TOML parser"
-optional = false
-python-versions = ">=3.7"
-files = [
-    {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 = "4.10.0"
-description = "Backported and Experimental Type Hints for Python 3.8+"
-optional = false
-python-versions = ">=3.8"
-files = [
-    {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 = "3.0.1"
-description = "The comprehensive WSGI web application library."
-optional = false
-python-versions = ">=3.8"
-files = [
-    {file = "werkzeug-3.0.1-py3-none-any.whl", hash = "sha256:90a285dc0e42ad56b34e696398b8122ee4c681833fb35b8334a095d82c56da10"},
-    {file = "werkzeug-3.0.1.tar.gz", hash = "sha256:507e811ecea72b18a404947aded4b3390e1db8f826b494d76550ef45bb3b1dcc"},
-]
-
-[package.dependencies]
-MarkupSafe = ">=2.1.1"
-
-[package.extras]
-watchdog = ["watchdog (>=2.3)"]
-
-[metadata]
-lock-version = "2.0"
-python-versions = "^3.8"
-content-hash = "e36516c932ab9dd7497acc0c3d55ab2c963004595efe97c2bc80854687c32c1e"

pyproject.toml

@@ -1,40 +1,67 @@
-[tool.poetry]
-name = "ollama"
-version = "0.0.0"
-description = "The official Python client for Ollama."
-authors = ["Ollama <hello@ollama.com>"]
+[project]
+name = 'ollama'
+description = 'The official Python client for Ollama.'
+authors = [
+    { email = 'hello@ollama.com' },
+]
+readme = 'README.md'
+requires-python = '>=3.8'
+dependencies = [
+    'httpx>=0.27',
+    'pydantic>=2.9',
+]
+dynamic = [ 'version' ]
 license = "MIT"
-readme = "README.md"
-homepage = "https://ollama.ai"
-repository = "https://github.com/jmorganca/ollama-python"
 
-[tool.poetry.dependencies]
-python = "^3.8"
-httpx = "^0.27.0"
-
-[tool.poetry.group.dev.dependencies]
-pytest = ">=7.4.3,<9.0.0"
-pytest-asyncio = ">=0.23.2,<0.25.0"
-pytest-cov = ">=4.1,<6.0"
-pytest-httpserver = "^1.0.8"
-pillow = "^10.2.0"
-ruff = ">=0.1.8,<0.7.0"
+[project.urls]
+homepage = 'https://ollama.com'
+repository = 'https://github.com/ollama/ollama-python'
+issues = 'https://github.com/ollama/ollama-python/issues'
 
 [build-system]
-requires = ["poetry-core"]
-build-backend = "poetry.core.masonry.api"
+requires = [ 'hatchling', 'hatch-vcs' ]
+build-backend = 'hatchling.build'
+
+[tool.hatch.version]
+source = 'vcs'
+
+[tool.hatch.envs.hatch-test]
+default-args = ['ollama', 'tests']
+extra-dependencies = [
+    'pytest-anyio',
+    'pytest-httpserver',
+]
+
+[tool.hatch.envs.hatch-static-analysis]
+dependencies = [ 'ruff>=0.9.1' ]
+config-path = 'none'
 
 [tool.ruff]
 line-length = 999
 indent-width = 2
 
 [tool.ruff.format]
-quote-style = "single"
-indent-style = "space"
+quote-style = 'single'
+indent-style = 'space'
+docstring-code-format = false
 
 [tool.ruff.lint]
-select = ["E", "F", "B"]
-ignore = ["E501"]
+select = [
+    'F', # pyflakes
+    'E', # pycodestyle errors
+    'W', # pycodestyle warnings
+    'I', # sort imports
+    'N', # pep8-naming
+    'ASYNC', # flake8-async
+    'FBT', # flake8-boolean-trap
+    'B', # flake8-bugbear
+    'C4', # flake8-comprehensions
+    'PIE', # flake8-pie
+    'SIM', # flake8-simplify
+    'FLY', # flynt
+    'RUF', # ruff-specific rules
+]
+ignore = ['FBT001'] # Boolean-typed positional argument in function definition
 
 [tool.pytest.ini_options]
-addopts = '--doctest-modules --ignore examples'
+addopts = ['--doctest-modules']

requirements.txt

@@ -1,27 +1,161 @@
-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" \
+# This file was autogenerated by uv via the following command:
+#    uv export
+-e .
+annotated-types==0.7.0 \
+    --hash=sha256:1f02e8b43a8fbbc3f3e0d4f0f4bfc8131bcb4eebe8849b8e5c773f3a1c582a53 \
+    --hash=sha256:aff07c09a53a08bc8cfccb9c85b05f1aa9a2a6f23728d790723543408344ce89
+    # via pydantic
+anyio==4.5.2 ; python_full_version < '3.9' \
+    --hash=sha256:23009af4ed04ce05991845451e11ef02fc7c5ed29179ac9a420e5ad0ac7ddc5b \
+    --hash=sha256:c011ee36bc1e8ba40e5a81cb9df91925c218fe9b778554e0b56a21e1b5d4716f
+    # via httpx
+anyio==4.8.0 ; python_full_version >= '3.9' \
+    --hash=sha256:1d9fe889df5212298c0c0723fa20479d1b94883a2df44bd3897aa91083316f7a \
+    --hash=sha256:b5011f270ab5eb0abf13385f851315585cc37ef330dd88e27ec3d34d651fd47a
+    # via httpx
+certifi==2025.1.31 \
+    --hash=sha256:3d5da6925056f6f18f119200434a4780a94263f10d1c21d032a6f6b2baa20651 \
+    --hash=sha256:ca78db4565a652026a4db2bcdf68f2fb589ea80d0be70e03929ed730746b84fe
+    # via
+    #   httpcore
+    #   httpx
+exceptiongroup==1.2.2 ; python_full_version < '3.11' \
+    --hash=sha256:3111b9d131c238bec2f8f516e123e14ba243563fb135d3fe885990585aa7795b \
+    --hash=sha256:47c2edf7c6738fafb49fd34290706d1a1a2f4d1c6df275526b62cbb4aa5393cc
+    # via anyio
+h11==0.14.0 \
     --hash=sha256:8f19fbbe99e72420ff35c00b27a34cb9937e902a8b810e2c88300c6f0a3b699d \
     --hash=sha256:e3fe4ac4b851c468cc8363d500db52c2ead036020723024a109d37346efaa761
-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" \
+    # via httpcore
+httpcore==1.0.7 \
+    --hash=sha256:8551cb62a169ec7162ac7be8d4817d561f60e08eaa485234898414bb5a8a0b4c \
+    --hash=sha256:a3fff8f43dc260d5bd363d9f9cf1830fa3a458b332856f34282de498ed420edd
+    # via httpx
+httpx==0.28.1 \
+    --hash=sha256:75e98c5f16b0f35b567856f597f06ff2270a374470a5c2392242528e3e3e42fc \
+    --hash=sha256:d909fcccc110f8c7faf814ca82a9a4d816bc5a6dbfea25d6591d6985b8ba59ad
+    # via ollama
+idna==3.10 \
+    --hash=sha256:12f65c9b470abda6dc35cf8e63cc574b1c52b11df2c86030af0ac09b01b13ea9 \
+    --hash=sha256:946d195a0d259cbba61165e88e65941f16e9b36ea6ddb97f00452bae8b1287d3
+    # via
+    #   anyio
+    #   httpx
+pydantic==2.10.6 \
+    --hash=sha256:427d664bf0b8a2b34ff5dd0f5a18df00591adcee7198fbd71981054cef37b584 \
+    --hash=sha256:ca5daa827cce33de7a42be142548b0096bf05a7e7b365aebfa5f8eeec7128236
+    # via ollama
+pydantic-core==2.27.2 \
+    --hash=sha256:00bad2484fa6bda1e216e7345a798bd37c68fb2d97558edd584942aa41b7d278 \
+    --hash=sha256:0296abcb83a797db256b773f45773da397da75a08f5fcaef41f2044adec05f50 \
+    --hash=sha256:03d0f86ea3184a12f41a2d23f7ccb79cdb5a18e06993f8a45baa8dfec746f0e9 \
+    --hash=sha256:044a50963a614ecfae59bb1eaf7ea7efc4bc62f49ed594e18fa1e5d953c40e9f \
+    --hash=sha256:05e3a55d124407fffba0dd6b0c0cd056d10e983ceb4e5dbd10dda135c31071d6 \
+    --hash=sha256:08e125dbdc505fa69ca7d9c499639ab6407cfa909214d500897d02afb816e7cc \
+    --hash=sha256:097830ed52fd9e427942ff3b9bc17fab52913b2f50f2880dc4a5611446606a54 \
+    --hash=sha256:0d1e85068e818c73e048fe28cfc769040bb1f475524f4745a5dc621f75ac7630 \
+    --hash=sha256:0d75070718e369e452075a6017fbf187f788e17ed67a3abd47fa934d001863d9 \
+    --hash=sha256:14d4a5c49d2f009d62a2a7140d3064f686d17a5d1a268bc641954ba181880236 \
+    --hash=sha256:172fce187655fece0c90d90a678424b013f8fbb0ca8b036ac266749c09438cb7 \
+    --hash=sha256:18a101c168e4e092ab40dbc2503bdc0f62010e95d292b27827871dc85450d7ee \
+    --hash=sha256:1a4207639fb02ec2dbb76227d7c751a20b1a6b4bc52850568e52260cae64ca3b \
+    --hash=sha256:1c1fd185014191700554795c99b347d64f2bb637966c4cfc16998a0ca700d048 \
+    --hash=sha256:1e2cb691ed9834cd6a8be61228471d0a503731abfb42f82458ff27be7b2186fc \
+    --hash=sha256:1ebaf1d0481914d004a573394f4be3a7616334be70261007e47c2a6fe7e50130 \
+    --hash=sha256:220f892729375e2d736b97d0e51466252ad84c51857d4d15f5e9692f9ef12be4 \
+    --hash=sha256:251136cdad0cb722e93732cb45ca5299fb56e1344a833640bf93b2803f8d1bfd \
+    --hash=sha256:26f0d68d4b235a2bae0c3fc585c585b4ecc51382db0e3ba402a22cbc440915e4 \
+    --hash=sha256:26f32e0adf166a84d0cb63be85c562ca8a6fa8de28e5f0d92250c6b7e9e2aff7 \
+    --hash=sha256:280d219beebb0752699480fe8f1dc61ab6615c2046d76b7ab7ee38858de0a4e7 \
+    --hash=sha256:28ccb213807e037460326424ceb8b5245acb88f32f3d2777427476e1b32c48c4 \
+    --hash=sha256:2bf14caea37e91198329b828eae1618c068dfb8ef17bb33287a7ad4b61ac314e \
+    --hash=sha256:2d367ca20b2f14095a8f4fa1210f5a7b78b8a20009ecced6b12818f455b1e9fa \
+    --hash=sha256:30c5f68ded0c36466acede341551106821043e9afaad516adfb6e8fa80a4e6a6 \
+    --hash=sha256:337b443af21d488716f8d0b6164de833e788aa6bd7e3a39c005febc1284f4962 \
+    --hash=sha256:3911ac9284cd8a1792d3cb26a2da18f3ca26c6908cc434a18f730dc0db7bfa3b \
+    --hash=sha256:3d591580c34f4d731592f0e9fe40f9cc1b430d297eecc70b962e93c5c668f15f \
+    --hash=sha256:3de3ce3c9ddc8bbd88f6e0e304dea0e66d843ec9de1b0042b0911c1663ffd474 \
+    --hash=sha256:3de9961f2a346257caf0aa508a4da705467f53778e9ef6fe744c038119737ef5 \
+    --hash=sha256:40d02e7d45c9f8af700f3452f329ead92da4c5f4317ca9b896de7ce7199ea459 \
+    --hash=sha256:42c5f762659e47fdb7b16956c71598292f60a03aa92f8b6351504359dbdba6cf \
+    --hash=sha256:47956ae78b6422cbd46f772f1746799cbb862de838fd8d1fbd34a82e05b0983a \
+    --hash=sha256:491a2b73db93fab69731eaee494f320faa4e093dbed776be1a829c2eb222c34c \
+    --hash=sha256:4c9775e339e42e79ec99c441d9730fccf07414af63eac2f0e48e08fd38a64d76 \
+    --hash=sha256:4e0b4220ba5b40d727c7f879eac379b822eee5d8fff418e9d3381ee45b3b0362 \
+    --hash=sha256:50a68f3e3819077be2c98110c1f9dcb3817e93f267ba80a2c05bb4f8799e2ff4 \
+    --hash=sha256:519f29f5213271eeeeb3093f662ba2fd512b91c5f188f3bb7b27bc5973816934 \
+    --hash=sha256:521eb9b7f036c9b6187f0b47318ab0d7ca14bd87f776240b90b21c1f4f149320 \
+    --hash=sha256:57762139821c31847cfb2df63c12f725788bd9f04bc2fb392790959b8f70f118 \
+    --hash=sha256:5e4f4bb20d75e9325cc9696c6802657b58bc1dbbe3022f32cc2b2b632c3fbb96 \
+    --hash=sha256:5e68c4446fe0810e959cdff46ab0a41ce2f2c86d227d96dc3847af0ba7def306 \
+    --hash=sha256:669e193c1c576a58f132e3158f9dfa9662969edb1a250c54d8fa52590045f046 \
+    --hash=sha256:688d3fd9fcb71f41c4c015c023d12a79d1c4c0732ec9eb35d96e3388a120dcf3 \
+    --hash=sha256:6fb4aadc0b9a0c063206846d603b92030eb6f03069151a625667f982887153e2 \
+    --hash=sha256:7041c36f5680c6e0f08d922aed302e98b3745d97fe1589db0a3eebf6624523af \
+    --hash=sha256:71b24c7d61131bb83df10cc7e687433609963a944ccf45190cfc21e0887b08c9 \
+    --hash=sha256:77d1bca19b0f7021b3a982e6f903dcd5b2b06076def36a652e3907f596e29f67 \
+    --hash=sha256:7969e133a6f183be60e9f6f56bfae753585680f3b7307a8e555a948d443cc05a \
+    --hash=sha256:7a66efda2387de898c8f38c0cf7f14fca0b51a8ef0b24bfea5849f1b3c95af27 \
+    --hash=sha256:7d0c8399fcc1848491f00e0314bd59fb34a9c008761bcb422a057670c3f65e35 \
+    --hash=sha256:7d14bd329640e63852364c306f4d23eb744e0f8193148d4044dd3dacdaacbd8b \
+    --hash=sha256:7e17b560be3c98a8e3aa66ce828bdebb9e9ac6ad5466fba92eb74c4c95cb1151 \
+    --hash=sha256:8083d4e875ebe0b864ffef72a4304827015cff328a1be6e22cc850753bfb122b \
+    --hash=sha256:82f91663004eb8ed30ff478d77c4d1179b3563df6cdb15c0817cd1cdaf34d154 \
+    --hash=sha256:82f986faf4e644ffc189a7f1aafc86e46ef70372bb153e7001e8afccc6e54133 \
+    --hash=sha256:83097677b8e3bd7eaa6775720ec8e0405f1575015a463285a92bfdfe254529ef \
+    --hash=sha256:85210c4d99a0114f5a9481b44560d7d1e35e32cc5634c656bc48e590b669b145 \
+    --hash=sha256:8c19d1ea0673cd13cc2f872f6c9ab42acc4e4f492a7ca9d3795ce2b112dd7e15 \
+    --hash=sha256:8d9b3388db186ba0c099a6d20f0604a44eabdeef1777ddd94786cdae158729e4 \
+    --hash=sha256:8e10c99ef58cfdf2a66fc15d66b16c4a04f62bca39db589ae8cba08bc55331bc \
+    --hash=sha256:953101387ecf2f5652883208769a79e48db18c6df442568a0b5ccd8c2723abee \
+    --hash=sha256:9c3ed807c7b91de05e63930188f19e921d1fe90de6b4f5cd43ee7fcc3525cb8c \
+    --hash=sha256:9e0c8cfefa0ef83b4da9588448b6d8d2a2bf1a53c3f1ae5fca39eb3061e2f0b0 \
+    --hash=sha256:9fdbe7629b996647b99c01b37f11170a57ae675375b14b8c13b8518b8320ced5 \
+    --hash=sha256:a0fcd29cd6b4e74fe8ddd2c90330fd8edf2e30cb52acda47f06dd615ae72da57 \
+    --hash=sha256:ac4dbfd1691affb8f48c2c13241a2e3b60ff23247cbcf981759c768b6633cf8b \
+    --hash=sha256:b0cb791f5b45307caae8810c2023a184c74605ec3bcbb67d13846c28ff731ff8 \
+    --hash=sha256:ba5dd002f88b78a4215ed2f8ddbdf85e8513382820ba15ad5ad8955ce0ca19a1 \
+    --hash=sha256:bca101c00bff0adb45a833f8451b9105d9df18accb8743b08107d7ada14bd7da \
+    --hash=sha256:bd8086fa684c4775c27f03f062cbb9eaa6e17f064307e86b21b9e0abc9c0f02e \
+    --hash=sha256:bec317a27290e2537f922639cafd54990551725fc844249e64c523301d0822fc \
+    --hash=sha256:c10eb4f1659290b523af58fa7cffb452a61ad6ae5613404519aee4bfbf1df993 \
+    --hash=sha256:c33939a82924da9ed65dab5a65d427205a73181d8098e79b6b426bdf8ad4e656 \
+    --hash=sha256:c61709a844acc6bf0b7dce7daae75195a10aac96a596ea1b776996414791ede4 \
+    --hash=sha256:c70c26d2c99f78b125a3459f8afe1aed4d9687c24fd677c6a4436bc042e50d6c \
+    --hash=sha256:c817e2b40aba42bac6f457498dacabc568c3b7a986fc9ba7c8d9d260b71485fb \
+    --hash=sha256:cabb9bcb7e0d97f74df8646f34fc76fbf793b7f6dc2438517d7a9e50eee4f14d \
+    --hash=sha256:cc3f1a99a4f4f9dd1de4fe0312c114e740b5ddead65bb4102884b384c15d8bc9 \
+    --hash=sha256:cca63613e90d001b9f2f9a9ceb276c308bfa2a43fafb75c8031c4f66039e8c6e \
+    --hash=sha256:ce8918cbebc8da707ba805b7fd0b382816858728ae7fe19a942080c24e5b7cd1 \
+    --hash=sha256:d2088237af596f0a524d3afc39ab3b036e8adb054ee57cbb1dcf8e09da5b29cc \
+    --hash=sha256:d262606bf386a5ba0b0af3b97f37c83d7011439e3dc1a9298f21efb292e42f1a \
+    --hash=sha256:d2d63f1215638d28221f664596b1ccb3944f6e25dd18cd3b86b0a4c408d5ebb9 \
+    --hash=sha256:d3e8d504bdd3f10835468f29008d72fc8359d95c9c415ce6e767203db6127506 \
+    --hash=sha256:d4041c0b966a84b4ae7a09832eb691a35aec90910cd2dbe7a208de59be77965b \
+    --hash=sha256:d716e2e30c6f140d7560ef1538953a5cd1a87264c737643d481f2779fc247fe1 \
+    --hash=sha256:d81d2068e1c1228a565af076598f9e7451712700b673de8f502f0334f281387d \
+    --hash=sha256:d9640b0059ff4f14d1f37321b94061c6db164fbe49b334b31643e0528d100d99 \
+    --hash=sha256:de3cd1899e2c279b140adde9357c4495ed9d47131b4a4eaff9052f23398076b3 \
+    --hash=sha256:e0fd26b16394ead34a424eecf8a31a1f5137094cabe84a1bcb10fa6ba39d3d31 \
+    --hash=sha256:e2bb4d3e5873c37bb3dd58714d4cd0b0e6238cebc4177ac8fe878f8b3aa8e74c \
+    --hash=sha256:eb026e5a4c1fee05726072337ff51d1efb6f59090b7da90d30ea58625b1ffb39 \
+    --hash=sha256:eda3f5c2a021bbc5d976107bb302e0131351c2ba54343f8a496dc8783d3d3a6a \
+    --hash=sha256:ef592d4bad47296fb11f96cd7dc898b92e795032b4894dfb4076cfccd43a9308 \
+    --hash=sha256:f141ee28a0ad2123b6611b6ceff018039df17f32ada8b534e6aa039545a3efb2 \
+    --hash=sha256:f66d89ba397d92f840f8654756196d93804278457b5fbede59598a1f9f90b228 \
+    --hash=sha256:f6f8e111843bbb0dee4cb6594cdc73e79b3329b526037ec242a3e49012495b3b \
+    --hash=sha256:fa8e459d4954f608fa26116118bb67f56b93b209c39b008277ace29937453dc9 \
+    --hash=sha256:fd1aea04935a508f62e0d0ef1f5ae968774a32afc306fb8545e06f5ff5cdf3ad
+    # via pydantic
+sniffio==1.3.1 \
     --hash=sha256:2f6da418d1f1e0fddd844478f41680e794e6051915791a034ff65e5f100525a2 \
     --hash=sha256:f4324edc670a0f49750a81b895f35c3adb843cca46f0530f79fc1babb23789dc
-typing-extensions==4.10.0 ; python_version >= "3.8" and python_version < "3.11" \
-    --hash=sha256:69b1a937c3a517342112fb4c6df7e72fc39a38e7891a5730ed4985b5214b5475 \
-    --hash=sha256:b0abd7c89e8fb96f98db18d86106ff1d90ab692004eb746cf6eda2682f91b3cb
+    # via anyio
+typing-extensions==4.12.2 \
+    --hash=sha256:04e5ca0351e0f3f85c6853954072df659d0d13fac324d0072316b67d7794700d \
+    --hash=sha256:1a7ead55c7e559dd4dee8856e3a88b41225abfe1ce8df57b7c13915fe121ffb8
+    # via
+    #   annotated-types
+    #   anyio
+    #   pydantic
+    #   pydantic-core

tests/test_type_serialization.py

@@ -0,0 +1,94 @@
+import tempfile
+from base64 import b64encode
+from pathlib import Path
+
+import pytest
+
+from ollama._types import CreateRequest, Image
+
+
+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()
+
+
+def test_create_request_serialization():
+  request = CreateRequest(model='test-model', from_='base-model', quantize='q4_0', files={'file1': 'content1'}, adapters={'adapter1': 'content1'}, template='test template', license='MIT', system='test system', parameters={'param1': 'value1'})
+
+  serialized = request.model_dump()
+  assert serialized['from'] == 'base-model'
+  assert 'from_' not in serialized
+  assert serialized['quantize'] == 'q4_0'
+  assert serialized['files'] == {'file1': 'content1'}
+  assert serialized['adapters'] == {'adapter1': 'content1'}
+  assert serialized['template'] == 'test template'
+  assert serialized['license'] == 'MIT'
+  assert serialized['system'] == 'test system'
+  assert serialized['parameters'] == {'param1': 'value1'}
+
+
+def test_create_request_serialization_exclude_none_true():
+  request = CreateRequest(model='test-model', from_=None, quantize=None)
+  serialized = request.model_dump(exclude_none=True)
+  assert serialized == {'model': 'test-model'}
+  assert 'from' not in serialized
+  assert 'from_' not in serialized
+  assert 'quantize' not in serialized
+
+
+def test_create_request_serialization_exclude_none_false():
+  request = CreateRequest(model='test-model', from_=None, quantize=None)
+  serialized = request.model_dump(exclude_none=False)
+  assert 'from' in serialized
+  assert 'quantize' in serialized
+  assert 'adapters' in serialized
+  assert 'from_' not in serialized
+
+
+def test_create_request_serialization_license_list():
+  request = CreateRequest(model='test-model', license=['MIT', 'Apache-2.0'])
+  serialized = request.model_dump()
+  assert serialized['license'] == ['MIT', 'Apache-2.0']

tests/test_utils.py

@@ -0,0 +1,258 @@
+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
+    """
+
+  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
+      """
+  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
+      """
+
+  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 {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 Any, Dict, List
+
+  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
+    """
+
+  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
+    """
+
+  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(): ...
+
+  def no_docstring_with_args(x: int, y: int): ...
+
+  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.
+    """
+
+  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', 'defs': None, 'items': None, 'required': None, 'properties': {}}
+
+  def only_description_with_args(x: int, y: int):
+    """
+    A function with only a description.
+    """
+
+  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',
+    'defs': None,
+    'items': None,
+    'properties': {
+      'x': {'type': 'integer', 'description': '', 'enum': None, 'items': None},
+      'y': {'type': 'integer', 'description': '', 'enum': None, 'items': None},
+    },
+    '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
+    """
+
+  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.
+    """
+
+  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
+    """
+
+  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
+    """
+
+  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'

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