Messages

Anthropic Messages API for all providers

The messages and amessages functions use the Anthropic Messages API format. All providers support this through automatic conversion, so you can use the same Anthropic-style message format regardless of backend.

any_llm.messages()

def messages(
    model: str,
    messages: list[dict[str, Any]],
    max_tokens: int,
    *,
    provider: str | LLMProvider | None = None,
    system: str | list[dict[str, Any]] | None = None,
    temperature: float | None = None,
    top_p: float | None = None,
    top_k: int | None = None,
    stream: bool | None = None,
    stop_sequences: list[str] | None = None,
    tools: list[dict[str, Any]] | None = None,
    tool_choice: dict[str, Any] | None = None,
    metadata: dict[str, Any] | None = None,
    thinking: dict[str, Any] | None = None,
    cache_control: dict[str, Any] | None = None,
    output_format: type | None = None,
    api_key: str | None = None,
    api_base: str | None = None,
    client_args: dict[str, Any] | None = None,
    **kwargs: Any,
) -> MessageResponse | ParsedMessage[Any] | Iterator[RawMessageStartEvent | RawMessageDeltaEvent | RawMessageStopEvent | RawContentBlockStartEvent | RawContentBlockDeltaEvent | RawContentBlockStopEvent]

any_llm.amessages()

Async variant with the same parameters. Returns MessageResponse | AsyncIterator[MessageStreamEvent].

async def amessages(
    model: str,
    messages: list[dict[str, Any]],
    max_tokens: int,
    *,
    provider: str | LLMProvider | None = None,
    system: str | list[dict[str, Any]] | None = None,
    temperature: float | None = None,
    top_p: float | None = None,
    top_k: int | None = None,
    stream: bool | None = None,
    stop_sequences: list[str] | None = None,
    tools: list[dict[str, Any]] | None = None,
    tool_choice: dict[str, Any] | None = None,
    metadata: dict[str, Any] | None = None,
    thinking: dict[str, Any] | None = None,
    cache_control: dict[str, Any] | None = None,
    output_format: type | None = None,
    api_key: str | None = None,
    api_base: str | None = None,
    client_args: dict[str, Any] | None = None,
    **kwargs: Any,
) -> MessageResponse | ParsedMessage[Any] | AsyncIterator[RawMessageStartEvent | RawMessageDeltaEvent | RawMessageStopEvent | RawContentBlockStartEvent | RawContentBlockDeltaEvent | RawContentBlockStopEvent]

Parameters

Parameter	Type	Default	Description
model	str	required	Model identifier. Recommended: Use with separate provider parameter. Alternative: Combined format 'provider:model'.
messages	list[dict[str, Any]]	required	List of messages in Anthropic format.
max_tokens	int	required	Maximum number of tokens to generate.
provider	str | LLMProvider | None	None	Provider name to use for the request.
system	str | list[dict[str, Any]] | None	None	System prompt (string or list of content blocks with optional cache_control).
temperature	float | None	None	Controls randomness (0.0 to 1.0).
top_p	float | None	None	Controls diversity via nucleus sampling.
top_k	int | None	None	Only sample from the top K options.
stream	bool | None	None	Whether to stream the response.
stop_sequences	list[str] | None	None	Custom stop sequences.
tools	list[dict[str, Any]] | None	None	List of tools in Anthropic format.
tool_choice	dict[str, Any] | None	None	Controls which tool the model uses.
metadata	dict[str, Any] | None	None	Request metadata.
thinking	dict[str, Any] | None	None	Thinking/reasoning configuration.
cache_control	dict[str, Any] | None	None	Cache control configuration for prompt caching.
output_format	type | None	None	Structured-output type, mirroring Anthropic's messages.parse(output_format=...). A Pydantic BaseModel or dataclass makes the call return Anthropic's ParsedMessage, with the typed object on its parsed_output property. Not supported with streaming.
api_key	str | None	None	API key for the provider.
api_base	str | None	None	Base URL for the provider API.
client_args	dict[str, Any] | None	None	Additional provider-specific arguments for client instantiation.
**kwargs	Any	required	Additional provider-specific arguments.

Return Value

• Non-streaming: Returns a MessageResponse object.

• Streaming (stream=True): Returns an Iterator[MessageStreamEvent] (sync) or AsyncIterator[MessageStreamEvent] (async).

Usage

Basic message

from any_llm.api import messages

response = messages(
    model="claude-sonnet-4-20250514",
    provider="anthropic",
    messages=[{"role": "user", "content": "Hello!"}],
    max_tokens=1024,
)
print(response.content[0].text)

With system prompt

response = messages(
    model="claude-sonnet-4-20250514",
    provider="anthropic",
    messages=[{"role": "user", "content": "Translate to French: Hello"}],
    max_tokens=1024,
    system="You are a professional translator.",
)

Async

import asyncio
from any_llm.api import amessages

async def main():
    response = await amessages(
        model="claude-sonnet-4-20250514",
        provider="anthropic",
        messages=[{"role": "user", "content": "Hello!"}],
        max_tokens=1024,
    )
    print(response.content[0].text)

asyncio.run(main())