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,
    prompt_cache_key: str | None = None,
    service_tier: str | None = None,
    context_management: dict[str, Any] | None = None,
    betas: list[str] | None = None,
    container: str | dict[str, Any] | None = None,
    output_format: type | dict[str, Any] | None = None,
    timeout: float | None = None,
    api_key: str | None = None,
    api_base: str | None = None,
    client_args: dict[str, Any] | None = None,
    **kwargs: Any,
) -> MessageResponse | ParsedMessage[Any] | ParsedBetaMessage[Any] | Iterator[MessageStartEvent | MessageDeltaEvent | MessageStopEvent | ContentBlockStartEvent | ContentBlockDeltaEvent | ContentBlockStopEvent]

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,
    prompt_cache_key: str | None = None,
    service_tier: str | None = None,
    context_management: dict[str, Any] | None = None,
    betas: list[str] | None = None,
    container: str | dict[str, Any] | None = None,
    output_format: type | dict[str, Any] | None = None,
    timeout: float | None = None,
    api_key: str | None = None,
    api_base: str | None = None,
    client_args: dict[str, Any] | None = None,
    **kwargs: Any,
) -> MessageResponse | ParsedMessage[Any] | ParsedBetaMessage[Any] | AsyncIterator[MessageStartEvent | MessageDeltaEvent | MessageStopEvent | ContentBlockStartEvent | ContentBlockDeltaEvent | ContentBlockStopEvent]

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. Anthropic deprecates this for current Claude models.
top_p	float | None	None	Controls nucleus sampling. Anthropic deprecates this for current Claude models.
top_k	int | None	None	Restricts sampling to the top K options. Anthropic deprecates this for current Claude models.
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.
prompt_cache_key	str | None	None	A key to use when reading from or writing to a provider's prompt cache.
service_tier	str | None	None	The service tier to use for this request.
context_management	dict[str, Any] | None	None	Anthropic context management configuration. The compact_20260112 strategy requires a supported model. Its input_tokens trigger value must be at least 50,000 when provided; see Anthropic's compaction documentation.
betas	list[str] | None	None	Anthropic beta identifiers.
container	str | dict[str, Any] | None	None	Container identifier, or an object with optional id and skills. A string reuses an existing container. An object selects Skills for a fresh container or reuses one while attaching Skills. See Anthropic's Skills container parameter.
output_format	type | dict[str, Any] | None	None	Structured output, mirroring Anthropic's messages.parse/output_config. Either a Pydantic BaseModel/dataclass type (typed parsed_output) or a raw Anthropic output_config dict for non-Pydantic JSON schemas (parsed_output holds the parsed JSON). Non-streaming calls return Anthropic's ParsedMessage for types or mappings with a non-empty schema dict. Mappings without one return MessageResponse. Providers with native support can stream schema-constrained Messages events. Native Anthropic typed beta requests return ParsedBetaMessage when context_management is set or beta identifiers are supplied.
timeout	float | None	None	Per-request timeout in seconds, passed through to the provider's client/SDK. An explicit None is treated the same as omitting it (the provider's default applies), so it cannot request an unbounded timeout. Providers that have no per-request timeout raise UnsupportedParameterError; set a timeout on their client via client_args instead.
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())