# The async version ## Setup ``` python from cachy import enable_cachy ``` ``` python enable_cachy() ``` ``` python from IPython.display import display,Image ``` ## Async SDK ``` python model = models[1] cli = AsyncAnthropic() ``` ``` python prompt = "I'm Jeremy" m = mk_msg(prompt) r = await cli.messages.create(messages=[m], model=model, max_tokens=100) r ``` Hi Jeremy! Nice to meet you. How can I help you today?
- id: `msg_01Q3123HGtAxWnUraLL65H24` - container: `None` - content: `[{'citations': None, 'text': 'Hi Jeremy! Nice to meet you. How can I help you today?', 'type': 'text'}]` - model: `claude-sonnet-4-6` - role: `assistant` - stop_reason: `end_turn` - stop_sequence: `None` - type: `message` - usage: `{'cache_creation': {'ephemeral_1h_input_tokens': 0, 'ephemeral_5m_input_tokens': 0}, 'cache_creation_input_tokens': 0, 'cache_read_input_tokens': 0, 'inference_geo': 'global', 'input_tokens': 10, 'output_tokens': 18, 'server_tool_use': None, 'service_tier': 'standard'}`
``` python msgs = mk_msgs([prompt, r, "I forgot my name. Can you remind me please?"]) msgs ``` [{'role': 'user', 'content': "I'm Jeremy"}, {'role': 'assistant', 'content': [TextBlock(citations=None, text='Hi Jeremy! Nice to meet you. How can I help you today?', type='text')]}, {'role': 'user', 'content': 'I forgot my name. Can you remind me please?'}] ``` python await cli.messages.create(messages=msgs, model=model, max_tokens=200) ``` Your name is Jeremy! You told me that at the start of our conversation. 😊
- id: `msg_01QTvdUwQAyKRQT3H73STdU3` - container: `None` - content: `[{'citations': None, 'text': 'Your name is Jeremy! You told me that at the start of our conversation. 😊', 'type': 'text'}]` - model: `claude-sonnet-4-6` - role: `assistant` - stop_reason: `end_turn` - stop_sequence: `None` - type: `message` - usage: `{'cache_creation': {'ephemeral_1h_input_tokens': 0, 'ephemeral_5m_input_tokens': 0}, 'cache_creation_input_tokens': 0, 'cache_read_input_tokens': 0, 'inference_geo': 'global', 'input_tokens': 42, 'output_tokens': 22, 'server_tool_use': None, 'service_tier': 'standard'}`
------------------------------------------------------------------------ source ### AsyncClient ``` python def AsyncClient( model, cli:NoneType=None, log:bool=False, cache:bool=False ): ``` *Async Anthropic messages client.*
Exported source ``` python class AsyncClient(Client): def __init__(self, model, cli=None, log=False, cache=False): "Async Anthropic messages client." super().__init__(model,cli,log,cache) if not cli: self.c = AsyncAnthropic(default_headers={'anthropic-beta': 'prompt-caching-2024-07-31'}) ```
``` python c = AsyncClient(model) ``` ``` python c._r(r) c.use ``` In: 10; Out: 18; Cache create: 0; Cache read: 0; Total Tokens: 28; Search: 0; Fetch: 0 ------------------------------------------------------------------------ source ### AsyncClient.\_\_call\_\_ ``` python async def __call__( msgs:list, # List of messages in the dialog sp:str='', # The system prompt temp:int=0, # Temperature maxtok:int=4096, # Maximum tokens maxthinktok:int=0, # Maximum thinking tokens prefill:str='', # Optional prefill to pass to Claude as start of its response stream:bool=False, # Stream response? stop:NoneType=None, # Stop sequence tools:Optional=None, # List of tools to make available to Claude tool_choice:Optional=None, # Optionally force use of some tool cb:NoneType=None, # Callback to pass result to when complete cli:NoneType=None, log:bool=False, cache:bool=False ): ``` *Make an async call to Claude.*
Exported source ``` python @asave_iter async def _astream(o, cm, prefill, cb): async with cm as s: yield prefill async for x in s.text_stream: yield x o.value = await s.get_final_message() await cb(o.value) ```
Exported source ``` python @patch @delegates(Client) async def __call__(self:AsyncClient, msgs:list, # List of messages in the dialog sp='', # The system prompt temp=0, # Temperature maxtok=4096, # Maximum tokens maxthinktok=0, # Maximum thinking tokens prefill='', # Optional prefill to pass to Claude as start of its response stream:bool=False, # Stream response? stop=None, # Stop sequence tools:Optional[list]=None, # List of tools to make available to Claude tool_choice:Optional[dict]=None, # Optionally force use of some tool cb=None, # Callback to pass result to when complete **kwargs): "Make an async call to Claude." msgs,kwargs = self._precall(msgs, prefill, sp, temp, maxtok, maxthinktok, stream, stop, tools, tool_choice, kwargs) m = self.c.messages f = m.stream if stream else m.create res = f(model=self.model, messages=msgs, **kwargs) async def _cb(v): self._log(v, prefill=prefill, msgs=msgs, **kwargs) if cb: await cb(v) if stream: return _astream(res, prefill, _cb) res = await res try: return res finally: await _cb(res) ```
``` python c = AsyncClient(model, log=True) c.use ``` In: 0; Out: 0; Cache create: 0; Cache read: 0; Total Tokens: 0; Search: 0; Fetch: 0 ``` python c.model = models[1] await c('Hi') ``` Hi there! How are you doing? Is there something I can help you with today? 😊
- id: `msg_01NSbD7ZmQJKeY16gJ6apjAH` - container: `None` - content: `[{'citations': None, 'text': 'Hi there! How are you doing? Is there something I can help you with today? 😊', 'type': 'text'}]` - model: `claude-sonnet-4-6` - role: `assistant` - stop_reason: `end_turn` - stop_sequence: `None` - type: `message` - usage: `{'cache_creation': {'ephemeral_1h_input_tokens': 0, 'ephemeral_5m_input_tokens': 0}, 'cache_creation_input_tokens': 0, 'cache_read_input_tokens': 0, 'inference_geo': 'global', 'input_tokens': 8, 'output_tokens': 24, 'server_tool_use': None, 'service_tier': 'standard'}`
``` python c.use ``` In: 8; Out: 24; Cache create: 0; Cache read: 0; Total Tokens: 32; Search: 0; Fetch: 0 ``` python def sums( a:int, # First thing to sum b:int=1 # Second thing to sum ) -> int: # The sum of the inputs "Adds a + b." print(f"Finding the sum of {a} and {b}") return a + b ``` ``` python a,b = 604542,6458932 pr = f"What is {a}+{b}?" sp = "You are a summing expert." ``` ``` python tools=[sums] choice = mk_tool_choice('sums') choice ``` {'type': 'tool', 'name': 'sums'} ``` python msgs = mk_msgs(pr) r = await c(msgs, sp=sp, tools=tools, tool_choice=choice) r ``` \[ToolUseBlock(id=‘toolu_016CNnqECCx2AcanFfQAR6Dz’, caller=DirectCaller(type=‘direct’), input={‘a’: 604542, ‘b’: 6458932}, name=‘sums’, type=‘tool_use’)\]
- id: `msg_013mLdHfZhRGsihW3NxusZWB` - container: `None` - content: `[{'id': 'toolu_016CNnqECCx2AcanFfQAR6Dz', 'caller': {'type': 'direct'}, 'input': {'a': 604542, 'b': 6458932}, 'name': 'sums', 'type': 'tool_use'}]` - model: `claude-sonnet-4-6` - role: `assistant` - stop_reason: `tool_use` - stop_sequence: `None` - type: `message` - usage: `{'cache_creation': {'ephemeral_1h_input_tokens': 0, 'ephemeral_5m_input_tokens': 0}, 'cache_creation_input_tokens': 0, 'cache_read_input_tokens': 0, 'inference_geo': 'global', 'input_tokens': 719, 'output_tokens': 57, 'server_tool_use': None, 'service_tier': 'standard'}`
------------------------------------------------------------------------ source ### mk_funcres_async ``` python async def mk_funcres_async( fc, ns ): ``` *Given tool use block `fc`, get tool result, and create a tool_result response.* ------------------------------------------------------------------------ source ### mk_toolres_async ``` python async def mk_toolres_async( r:Mapping, # Tool use request response from Claude ns:Optional=None, # Namespace to search for tools ): ``` *Create a `tool_result` message from response `r`.* ``` python tr = await mk_toolres_async(r, ns=globals()) tr ``` Finding the sum of 604542 and 6458932 [{'role': 'assistant', 'content': [{'id': 'toolu_016CNnqECCx2AcanFfQAR6Dz', 'caller': {'type': 'direct'}, 'input': {'a': 604542, 'b': 6458932}, 'name': 'sums', 'type': 'tool_use'}]}, {'role': 'user', 'content': [{'type': 'tool_result', 'tool_use_id': 'toolu_016CNnqECCx2AcanFfQAR6Dz', 'content': '7063474'}]}] ``` python msgs += tr r = contents(await c(msgs, sp=sp, tools=sums)) r ``` 'The result of **604,542 + 6,458,932 = 7,063,474**!' ## Structured Output ------------------------------------------------------------------------ source ### AsyncClient.structured ``` python async def structured( msgs:list, # List of messages in the dialog tools:Optional=None, # List of tools to make available to Claude ns:Optional=None, # Namespace to search for tools sp:str='', # The system prompt temp:int=0, # Temperature maxtok:int=4096, # Maximum tokens maxthinktok:int=0, # Maximum thinking tokens prefill:str='', # Optional prefill to pass to Claude as start of its response stream:bool=False, # Stream response? stop:NoneType=None, # Stop sequence tool_choice:Optional=None, # Optionally force use of some tool cb:NoneType=None, # Callback to pass result to when complete cache_control:Optional[CacheControlEphemeralParam] | Omit=, container:Optional[str] | Omit=, inference_geo:Optional[str] | Omit=, metadata:MetadataParam | Omit=, output_config:OutputConfigParam | Omit=, service_tier:Literal['auto', 'standard_only'] | Omit=, stop_sequences:SequenceNotStr[str] | Omit=, system:Union[str, Iterable[TextBlockParam]] | Omit=, temperature:float | Omit=, thinking:ThinkingConfigParam | Omit=, top_k:int | Omit=, top_p:float | Omit=, user_profile_id:str | Omit=, extra_headers:Headers | None=None, # Use the following arguments if you need to pass additional parameters to the API that aren't available via kwargs. # The extra values given here take precedence over values defined on the client or passed to this method. extra_query:Query | None=None, extra_body:Body | None=None, timeout:float | httpx.Timeout | None | NotGiven=NOT_GIVEN ): ``` *Return the value of all tool calls (generally used for structured outputs)* ``` python await c.structured(pr, sums) ``` Finding the sum of 604542 and 6458932 [7063474] ``` python c ``` \[ToolUseBlock(id=‘toolu_01ENhz5EnfqZFT8PeizJ3gKr’, caller=DirectCaller(type=‘direct’), input={‘a’: 604542, ‘b’: 6458932}, name=‘sums’, type=‘tool_use’)\]
Metric Count Cost (USD)
Input tokens 2,153 0.006459
Output tokens 166 0.002490
Cache tokens 0 0.000000
Server tool use 0 0.000000
Total 2,319 $0.008949
## AsyncChat ------------------------------------------------------------------------ source ### AsyncChat ``` python def AsyncChat( model:Optional=None, # Model to use (leave empty if passing `cli`) cli:Optional=None, # Client to use (leave empty if passing `model`) sp:str='', # Optional system prompt tools:Optional=None, # List of tools to make available to Claude temp:int=0, # Temperature cont_pr:Optional=None, # User prompt to continue an assistant response cache:bool=False, # Use Claude cache? hist:list=None, # Initialize history ns:Optional=None, # Namespace to search for tools ): ``` *Anthropic async chat client.*
Exported source ``` python @delegates() class AsyncChat(Chat): def __init__(self, model:Optional[str]=None, # Model to use (leave empty if passing `cli`) cli:Optional[Client]=None, # Client to use (leave empty if passing `model`) **kwargs): "Anthropic async chat client." super().__init__(model, cli, **kwargs) if not cli: self.c = AsyncClient(model) ```
``` python sp = "Always use tools if available, and calculations are requested." chat = AsyncChat(model, sp=sp) chat.c.use, chat.h ``` (In: 0; Out: 0; Cache create: 0; Cache read: 0; Total Tokens: 0; Search: 0; Fetch: 0, []) ------------------------------------------------------------------------ source ### AsyncChat.\_\_call\_\_ ``` python async def __call__( pr:NoneType=None, # Prompt / message temp:NoneType=None, # Temperature maxtok:int=4096, # Maximum tokens maxthinktok:int=0, # Maximum thinking tokens stream:bool=False, # Stream response? prefill:str='', # Optional prefill to pass to Claude as start of its response tool_choice:Union=None, # Optionally force use of some tool **kw ): ``` *Call self as a function.*
Exported source ``` python @patch async def _append_pr(self:AsyncChat, pr=None): prev_role = nested_idx(self.h, -1, 'role') if self.h else 'assistant' # First message should be 'user' if no history if pr and prev_role == 'user': await self() self._post_pr(pr, prev_role) ```
Exported source ``` python @patch async def __call__(self:AsyncChat, pr=None, # Prompt / message temp=None, # Temperature maxtok=4096, # Maximum tokens maxthinktok=0, # Maximum thinking tokens stream=False, # Stream response? prefill='', # Optional prefill to pass to Claude as start of its response tool_choice:Optional[Union[str,bool,dict]]=None, # Optionally force use of some tool **kw): if temp is None: temp=self.temp await self._append_pr(pr) async def _cb(v): self.last = await mk_toolres_async(v, ns=limit_ns(self.ns, self.tools, tool_choice)) self.h += self.last return await self.c(self.h, stream=stream, prefill=prefill, sp=self.sp, temp=temp, maxtok=maxtok, maxthinktok=maxthinktok, tools=self.tools, tool_choice=tool_choice, cb=_cb, **kw) ```
``` python await chat("I'm Jeremy") await chat("What's my name?") ``` Your name is Jeremy! You told me at the start of our conversation. 😊
- id: `msg_01VyEoh1pWoHVEKzCh5SeRWP` - container: `None` - content: `[{'citations': None, 'text': 'Your name is Jeremy! You told me at the start of our conversation. 😊', 'type': 'text'}]` - model: `claude-sonnet-4-6` - role: `assistant` - stop_reason: `end_turn` - stop_sequence: `None` - type: `message` - usage: `{'cache_creation': {'ephemeral_1h_input_tokens': 0, 'ephemeral_5m_input_tokens': 0}, 'cache_creation_input_tokens': 0, 'cache_read_input_tokens': 0, 'inference_geo': 'global', 'input_tokens': 48, 'output_tokens': 21, 'server_tool_use': None, 'service_tier': 'standard'}`
``` python chat = AsyncChat(model, sp=sp) r = await chat("I'm Jeremy", stream=True) async for o in r: print(o, end='') r.value ``` Hi Jeremy! Nice to meet you. How can I help you today? Hi Jeremy! Nice to meet you. How can I help you today?
- id: `msg_01JbxS96JDjpS6GtjdyjbHKa` - container: `None` - content: `[{'citations': None, 'text': 'Hi Jeremy! Nice to meet you. How can I help you today?', 'type': 'text', 'parsed_output': None}]` - model: `claude-sonnet-4-6` - role: `assistant` - stop_reason: `end_turn` - stop_sequence: `None` - type: `message` - usage: `{'cache_creation': {'ephemeral_1h_input_tokens': 0, 'ephemeral_5m_input_tokens': 0}, 'cache_creation_input_tokens': 0, 'cache_read_input_tokens': 0, 'inference_geo': 'global', 'input_tokens': 22, 'output_tokens': 18, 'server_tool_use': None, 'service_tier': 'standard'}`
``` python pr = f"What is {a}+{b}?" chat = AsyncChat(model, sp=sp, tools=[sums]) r = await chat(pr) r ``` Finding the sum of 604542 and 6458932 I’ll calculate the sum of 604542 and 6458932 right away!
- id: `msg_01AjLTTKCzEr2PgYoqcQrpPy` - container: `None` - content: `[{'citations': None, 'text': "I'll calculate the sum of 604542 and 6458932 right away!", 'type': 'text'}, {'id': 'toolu_01KhnEGLFGsYP9ePCfn6gf8b', 'caller': {'type': 'direct'}, 'input': {'a': 604542, 'b': 6458932}, 'name': 'sums', 'type': 'tool_use'}]` - model: `claude-sonnet-4-6` - role: `assistant` - stop_reason: `tool_use` - stop_sequence: `None` - type: `message` - usage: `{'cache_creation': {'ephemeral_1h_input_tokens': 0, 'ephemeral_5m_input_tokens': 0}, 'cache_creation_input_tokens': 0, 'cache_read_input_tokens': 0, 'inference_geo': 'global', 'input_tokens': 631, 'output_tokens': 92, 'server_tool_use': None, 'service_tier': 'standard'}`
``` python await chat() ``` The sum of **604,542 + 6,458,932 = 7,063,474**!
- id: `msg_01MzE8hrFtWfJ8fT3PsZ8s9b` - container: `None` - content: `[{'citations': None, 'text': 'The sum of **604,542 + 6,458,932 = 7,063,474**!', 'type': 'text'}]` - model: `claude-sonnet-4-6` - role: `assistant` - stop_reason: `end_turn` - stop_sequence: `None` - type: `message` - usage: `{'cache_creation': {'ephemeral_1h_input_tokens': 0, 'ephemeral_5m_input_tokens': 0}, 'cache_creation_input_tokens': 0, 'cache_read_input_tokens': 0, 'inference_geo': 'global', 'input_tokens': 738, 'output_tokens': 28, 'server_tool_use': None, 'service_tier': 'standard'}`
AsyncChat handles missing tools gracefully. When a tool is called but not found in the namespace, it returns an error message rather than crashing. In this test, we intentionally empty the namespace (`chat.ns={}`) to simulate what would happen if Claude hallucinated a tool or if a tool was missing. The [`limit_ns`](https://claudette.answer.ai/core.html#limit_ns) function (used in the `_cb` callback) would normally filter out hallucinated tools, but here we’re testing the fallback behavior when tools aren’t available. ``` python pr = f"What is {a}+{b}?" chat = AsyncChat(model, sp=sp, tools=[sums]) chat.ns={} r = await chat(pr) r ``` I’ll calculate the sum of 604542 and 6458932 right away!
- id: `msg_01AjLTTKCzEr2PgYoqcQrpPy` - container: `None` - content: `[{'citations': None, 'text': "I'll calculate the sum of 604542 and 6458932 right away!", 'type': 'text'}, {'id': 'toolu_01KhnEGLFGsYP9ePCfn6gf8b', 'caller': {'type': 'direct'}, 'input': {'a': 604542, 'b': 6458932}, 'name': 'sums', 'type': 'tool_use'}]` - model: `claude-sonnet-4-6` - role: `assistant` - stop_reason: `tool_use` - stop_sequence: `None` - type: `message` - usage: `{'cache_creation': {'ephemeral_1h_input_tokens': 0, 'ephemeral_5m_input_tokens': 0}, 'cache_creation_input_tokens': 0, 'cache_read_input_tokens': 0, 'inference_geo': 'global', 'input_tokens': 631, 'output_tokens': 92, 'server_tool_use': None, 'service_tier': 'standard'}`
``` python chat.h ``` [{'role': 'user', 'content': 'What is 604542+6458932?'}, {'role': 'assistant', 'content': [{'text': "I'll calculate the sum of 604542 and 6458932 right away!", 'type': 'text'}, {'id': 'toolu_01KhnEGLFGsYP9ePCfn6gf8b', 'caller': {'type': 'direct'}, 'input': {'a': 604542, 'b': 6458932}, 'name': 'sums', 'type': 'tool_use'}]}, {'role': 'user', 'content': [{'type': 'tool_result', 'tool_use_id': 'toolu_01KhnEGLFGsYP9ePCfn6gf8b', 'content': 'Error - tool not defined in the tool_schemas: sums'}]}] ``` python fn = Path('samples/puppy.jpg') img = fn.read_bytes() Image(img) ``` ![](02_async_files/figure-commonmark/cell-42-output-1.jpeg) ``` python q = "In brief, what color flowers are in this image?" msg = mk_msg([img, q]) await c([msg]) ``` The flowers in the image are **purple/lavender** (blue-purple). They appear to be **asters**.
- id: `msg_01DUds87tAj47fozgFfbEPrQ` - container: `None` - content: `[{'citations': None, 'text': 'The flowers in the image are **purple/lavender** (blue-purple). They appear to be **asters**.', 'type': 'text'}]` - model: `claude-sonnet-4-6` - role: `assistant` - stop_reason: `end_turn` - stop_sequence: `None` - type: `message` - usage: `{'cache_creation': {'ephemeral_1h_input_tokens': 0, 'ephemeral_5m_input_tokens': 0}, 'cache_creation_input_tokens': 0, 'cache_read_input_tokens': 0, 'inference_geo': 'global', 'input_tokens': 110, 'output_tokens': 28, 'server_tool_use': None, 'service_tier': 'standard'}`
Add `cache=True` to automatically add to Claude’s KV cache. ``` python chat = AsyncChat(model, sp=sp, cache=True) await chat("Lorem ipsum dolor sit amet" * 150) ``` It looks like you’ve sent a large block of repeated **“Lorem ipsum dolor sit amet”** placeholder text. Could you clarify what you need? For example: - ❓ Do you have a **question**? - 📝 Do you need help with **writing or editing**? - 🛠️ Was this sent **by mistake**? I’m happy to help once I know what you’re looking for! 😊
- id: `msg_01VhxH3pUWt1Z6ERyWFEpLvY` - container: `None` - content: `[{'citations': None, 'text': 'It looks like you\'ve sent a large block of repeated **"Lorem ipsum dolor sit amet"** placeholder text.\n\nCould you clarify what you need? For example:\n\n- ❓ Do you have a **question**?\n- 📝 Do you need help with **writing or editing**?\n- 🛠️ Was this sent **by mistake**?\n\nI\'m happy to help once I know what you\'re looking for! 😊', 'type': 'text'}]` - model: `claude-sonnet-4-6` - role: `assistant` - stop_reason: `end_turn` - stop_sequence: `None` - type: `message` - usage: `{'cache_creation': {'ephemeral_1h_input_tokens': 0, 'ephemeral_5m_input_tokens': 0}, 'cache_creation_input_tokens': 0, 'cache_read_input_tokens': 0, 'inference_geo': 'global', 'input_tokens': 1067, 'output_tokens': 103, 'server_tool_use': None, 'service_tier': 'standard'}`
``` python chat.use ``` In: 1067; Out: 103; Cache create: 0; Cache read: 0; Total Tokens: 1170; Search: 0; Fetch: 0 In this followup call, nearly all the tokens are cached, so the only the new additional tokens are charged at the full rate. ``` python await chat("Whoops, sorry about that!") ``` No worries at all! 😄 It happens! So, what can I help you with today?
- id: `msg_013Z7HrwVhkDCPEhnj3yNHor` - container: `None` - content: `[{'citations': None, 'text': 'No worries at all! 😄 It happens! \n\nSo, what can I help you with today?', 'type': 'text'}]` - model: `claude-sonnet-4-6` - role: `assistant` - stop_reason: `end_turn` - stop_sequence: `None` - type: `message` - usage: `{'cache_creation': {'ephemeral_1h_input_tokens': 0, 'ephemeral_5m_input_tokens': 0}, 'cache_creation_input_tokens': 0, 'cache_read_input_tokens': 0, 'inference_geo': 'global', 'input_tokens': 1181, 'output_tokens': 28, 'server_tool_use': None, 'service_tier': 'standard'}`
``` python chat.use ``` In: 2248; Out: 131; Cache create: 0; Cache read: 0; Total Tokens: 2379; Search: 0; Fetch: 0 ## Extended Thinking Let’s call the model without extended thinking enabled. ``` python chat = AsyncChat(model) await chat("Write a sentence about Python!") ``` Here’s a sentence about Python: **Python is a versatile, beginner-friendly programming language known for its clean, readable syntax and wide range of applications, from web development and data science to artificial intelligence and automation.** Would you like to know more about Python? 🐍
- id: `msg_0133ueaeXR2KvELPiPDnpFAC` - container: `None` - content: `[{'citations': None, 'text': "Here's a sentence about Python:\n\n**Python is a versatile, beginner-friendly programming language known for its clean, readable syntax and wide range of applications, from web development and data science to artificial intelligence and automation.**\n\nWould you like to know more about Python? 🐍", 'type': 'text'}]` - model: `claude-sonnet-4-6` - role: `assistant` - stop_reason: `end_turn` - stop_sequence: `None` - type: `message` - usage: `{'cache_creation': {'ephemeral_1h_input_tokens': 0, 'ephemeral_5m_input_tokens': 0}, 'cache_creation_input_tokens': 0, 'cache_read_input_tokens': 0, 'inference_geo': 'global', 'input_tokens': 13, 'output_tokens': 63, 'server_tool_use': None, 'service_tier': 'standard'}`
Now, let’s call the model with extended thinking enabled. ``` python r = await chat("Write a sentence about Python!", maxthinktok=1024) r ``` Here’s a sentence about Python: **Python is one of the most popular programming languages in the world, loved by developers for its simplicity, powerful libraries, and ability to handle complex tasks with just a few lines of code.** Fun fact: Python was named after the British comedy group **Monty Python**, not the snake! 🐍😄 Would you like to learn more about Python?
Thinking The user wants another sentence about Python. Let me write a different one this time.
- id: `msg_01Vuqd8xUwuB2tTnmcexcfFp` - container: `None` - content: `[{'signature': 'Ev0BCkYICxgCKkAmUcWkc6z1j9s2pIRVL/EIaNbJYCaXR1stNeEAhQoCylzrssuUy2ZTq4vGWUl7WbH2AbV30H8aRazSNGwgnQp+Egzq7GmzjPUY/hkdH1oaDKbN8/A53z7nu/TenyIwIAhQomWRMzdCY7ueYlSChv7bcBIpnPT6Pf1gboh/KOlgAQIV0DRGX3r28/rVxj0KKmXdM/z1lMTxHXSMLE5PQkpDsNEavF0XqqGZlFXgd1Sg4mZSiaV3/9h9FTb2VWNtbpsvtztVbdvt4BbTnrO6YtNv5ehK0/7kaArbOwi61aQtZson8/+gmZgnox2vDieBHhpCc6t3ThgB', 'thinking': 'The user wants another sentence about Python. Let me write a different one this time.', 'type': 'thinking'}, {'citations': None, 'text': "Here's a sentence about Python:\n\n**Python is one of the most popular programming languages in the world, loved by developers for its simplicity, powerful libraries, and ability to handle complex tasks with just a few lines of code.**\n\nFun fact: Python was named after the British comedy group **Monty Python**, not the snake! 🐍😄\n\nWould you like to learn more about Python?", 'type': 'text'}]` - model: `claude-sonnet-4-6` - role: `assistant` - stop_reason: `end_turn` - stop_sequence: `None` - type: `message` - usage: `{'cache_creation': {'ephemeral_1h_input_tokens': 0, 'ephemeral_5m_input_tokens': 0}, 'cache_creation_input_tokens': 0, 'cache_read_input_tokens': 0, 'inference_geo': 'global', 'input_tokens': 114, 'output_tokens': 113, 'server_tool_use': None, 'service_tier': 'standard'}`
``` python r.content ``` [ThinkingBlock(signature='Ev0BCkYICxgCKkAmUcWkc6z1j9s2pIRVL/EIaNbJYCaXR1stNeEAhQoCylzrssuUy2ZTq4vGWUl7WbH2AbV30H8aRazSNGwgnQp+Egzq7GmzjPUY/hkdH1oaDKbN8/A53z7nu/TenyIwIAhQomWRMzdCY7ueYlSChv7bcBIpnPT6Pf1gboh/KOlgAQIV0DRGX3r28/rVxj0KKmXdM/z1lMTxHXSMLE5PQkpDsNEavF0XqqGZlFXgd1Sg4mZSiaV3/9h9FTb2VWNtbpsvtztVbdvt4BbTnrO6YtNv5ehK0/7kaArbOwi61aQtZson8/+gmZgnox2vDieBHhpCc6t3ThgB', thinking='The user wants another sentence about Python. Let me write a different one this time.', type='thinking'), TextBlock(citations=None, text="Here's a sentence about Python:\n\n**Python is one of the most popular programming languages in the world, loved by developers for its simplicity, powerful libraries, and ability to handle complex tasks with just a few lines of code.**\n\nFun fact: Python was named after the British comedy group **Monty Python**, not the snake! 🐍😄\n\nWould you like to learn more about Python?", type='text')]