> For the complete documentation index, see [llms.txt](https://docs.mozilla.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.mozilla.ai/api-reference/completion-1/messages.md). # Messages The Messages API types are Pydantic models used by `any_llm.api.messages()` and `any_llm.api.amessages()`. ### Primary Types #### `MessageResponse` Full response from the Messages API. **Import:** `from any_llm.types.messages import MessageResponse` #### `MessageContentBlock` Content block in a Messages API response. **Import:** `from any_llm.types.messages import MessageContentBlock` #### `MessageUsage` Token usage information for Messages API. **Import:** `from any_llm.types.messages import MessageUsage` | Field | Type | Description | | ----------------------------- | -------------------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | `cache_creation` | `CacheCreation \| None` | Breakdown of cached tokens by TTL | | `cache_creation_input_tokens` | `int \| None` | The number of input tokens used to create the cache entry. | | `cache_read_input_tokens` | `int \| None` | The number of input tokens read from the cache. | | `inference_geo` | `str \| None` | The geographic region where inference was performed for this request. | | `input_tokens` | `int` | The number of input tokens which were used. | | `output_tokens` | `int` | The number of output tokens which were used. | | `output_tokens_details` | `OutputTokensDetails \| None` | Breakdown of output tokens by category. `output_tokens` remains the inclusive, authoritative total used for billing. This object provides a read-only decomposition for observability — for example, how many of the billed output tokens were spent on internal reasoning that may have been summarized before being returned to you. | | `server_tool_use` | `ServerToolUsage \| None` | The number of server tool requests. | | `service_tier` | `Literal['standard', 'priority', 'batch'] \| None` | If the request used the priority, standard, or batch tier. | #### `MessageStreamEvent` Union of Anthropic SDK stream event types, re-exported from the `anthropic` package: * `MessageStartEvent` — `type: 'message_start'`, `message: Message` * `MessageDeltaEvent` — `type: 'message_delta'`, `delta: Delta`, `usage: MessageDeltaUsage` * `MessageStopEvent` — `type: 'message_stop'` * `ContentBlockStartEvent` — `type: 'content_block_start'`, `index: int`, `content_block: ContentBlock` * `ContentBlockDeltaEvent` — `type: 'content_block_delta'`, `index: int`, `delta: RawContentBlockDelta` * `ContentBlockStopEvent` — `type: 'content_block_stop'`, `index: int` **Import:** `from any_llm.types.messages import MessageStreamEvent` ### Internal Types #### `MessagesParams` Normalized parameters for the Anthropic Messages API, used internally to pass structured parameters from the public API to provider implementations. **Import:** `from any_llm.types.messages import MessagesParams` | Field | Type | Description | | ---------------- | ------------------------------------- | ----------------------------------------------------------------------------- | | `model` | `str` | Model identifier | | `messages` | `list[dict[str, Any]]` | List of messages for the conversation | | `max_tokens` | `int` | Maximum number of tokens to generate (required by Anthropic API) | | `system` | `str \| list[dict[str, Any]] \| None` | System prompt (string or list of content blocks with optional cache\_control) | | `temperature` | `float \| None` | Controls randomness in the response (0.0 to 1.0) | | `top_p` | `float \| None` | Controls diversity via nucleus sampling | | `top_k` | `int \| None` | Only sample from the top K options for each subsequent token | | `stream` | `bool \| None` | Whether to stream the response | | `stop_sequences` | `list[str] \| None` | Custom text sequences that will cause the model to stop generating | | `tools` | `list[dict[str, Any]] \| None` | List of tools in Anthropic format ({name, description, input\_schema}) | | `tool_choice` | `dict[str, Any] \| None` | Controls which tool the model uses | | `metadata` | `dict[str, Any] \| None` | Request metadata | | `thinking` | `dict[str, Any] \| None` | Thinking/reasoning configuration | | `cache_control` | `dict[str, Any] \| None` | Cache control configuration for prompt caching | | `output_format` | `type \| dict[str, Any] \| None` | | --- # Agent Instructions This documentation is published with GitBook. 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