> 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` | Field | Type | Description | | -------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ----------------------------------------------------------- | | `request_id` | `str \| None` | Provider request identifier, when exposed by the transport. | | `container` | `BetaContainer \| None` | | | `content` | `list[ThinkingBlock \| TextBlock \| ThinkingBlock \| RedactedThinkingBlock \| ToolUseBlock \| ServerToolUseBlock \| WebSearchToolResultBlock \| WebFetchToolResultBlock \| CodeExecutionToolResultBlock \| BashCodeExecutionToolResultBlock \| TextEditorCodeExecutionToolResultBlock \| ToolSearchToolResultBlock \| ContainerUploadBlock \| BetaTextBlock \| BetaThinkingBlock \| BetaRedactedThinkingBlock \| BetaToolUseBlock \| BetaServerToolUseBlock \| BetaWebSearchToolResultBlock \| BetaWebFetchToolResultBlock \| BetaAdvisorToolResultBlock \| BetaCodeExecutionToolResultBlock \| BetaBashCodeExecutionToolResultBlock \| BetaTextEditorCodeExecutionToolResultBlock \| BetaToolSearchToolResultBlock \| BetaMCPToolUseBlock \| BetaMCPToolResultBlock \| BetaContainerUploadBlock \| BetaCompactionBlock \| BetaFallbackBlock]` | | | `stop_reason` | `Literal['end_turn', 'max_tokens', 'stop_sequence', 'tool_use', 'pause_turn', 'compaction', 'refusal', 'model_context_window_exceeded'] \| None` | | | `usage` | `MessageUsage` | | | `context_management` | `BetaContextManagementResponse \| None` | | | `diagnostics` | `BetaDiagnostics \| None` | | #### `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 | | ------------ | -------------------------------------------------------------------------------------------------------------------------------------------------- | ----------- | | `iterations` | `list[BetaMessageIterationUsage \| BetaCompactionIterationUsage \| BetaAdvisorMessageIterationUsage \| BetaFallbackMessageIterationUsage] \| None` | | | `speed` | `Literal['standard', 'fast'] \| None` | | #### `MessageStreamEvent` Union of stream event types. Each one subclasses the matching Anthropic SDK `Raw*` event and widens it so beta responses (context management, compaction) round-trip without loss: * `MessageStartEvent`: `type: 'message_start'`, `message: MessageResponse` * `MessageDeltaEvent`: `type: 'message_delta'`, `delta: MessageDelta`, `usage: MessageDeltaUsage`, `context_management: BetaContextManagementResponse | None` * `MessageStopEvent`: `type: 'message_stop'`, `message: MessageResponse | None` * `ContentBlockStartEvent`: `type: 'content_block_start'`, `index: int`, `content_block: MessageContentBlock` * `ContentBlockDeltaEvent`: `type: 'content_block_delta'`, `index: int`, `delta: RawContentBlockDelta | CompactionDelta` * `ContentBlockStopEvent`: `type: 'content_block_stop'`, `index: int`, `content_block: MessageContentBlock | None` `message` on `MessageStopEvent` and `content_block` on `ContentBlockStopEvent` are populated only by providers with a native Anthropic Messages API; the Chat Completions bridge leaves them unset. **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 | | `prompt_cache_key` | `str \| None` | A key to use when reading from or writing to a provider's prompt cache. | | `service_tier` | `str \| None` | The service tier to use for this request. | | `context_management` | `dict[str, Any] \| None` | Anthropic context management configuration | | `betas` | `list[str] \| None` | Anthropic beta identifiers | | `output_format` | `type \| dict[str, Any] \| None` | | --- # Agent Instructions This documentation is published with GitBook. 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