LLM Requests

This reference covers request fields and the built-in provider mappings. For the integration flow and a construction example, read LLM-Related Protocols. For the reply, continue to Responses and Streams.

Request envelope

An algorithm receives Request. Its llm_request contains the conversation; the remaining envelope data belongs to the application.

Field and type	Meaning
Request.llm_request: LlmRequest	The conversation and settings used by the algorithm and model client.
Request.metadata: Option<Metadata>	Optional session, correlation, and routing metadata.
Request.raw_request: Option<Value>	An optional original body retained by the host. Translation codecs do not read this field.

Codec replay uses LlmRequest.preservation, separately from the envelope's raw body. See preservation and edits before changing a decoded request.

Conversation fields

These mappings describe the built-in codecs. Supported features also depend on the destination model. Select a Rust field or type for its full crate definition.

Protocol field and type	Meaning	Anthropic Messages	OpenAI Responses	Chat Completions
LlmRequest.model: Option<String>	Addressed model; the host can replace it with the selected target.	model	model	model
LlmRequest.instructions: Vec<InstructionBlock>	System and developer instructions.	Top-level system; no distinct developer authority	instructions and system/developer messages in input	System/developer messages in messages
LlmRequest.messages: Vec<Message>	Ordered turns, each with a role and content blocks.	messages[]	Messages and tool items in input	messages[]
LlmRequest.tools: Vec<Tool>	Available functions, MCP toolsets, or retained provider definitions.	tools[]	tools[]	tools[]; function definitions are nested in function
LlmRequest.tool_choice: Option<ToolChoice>	Let the model choose, require a call, forbid calls, or select a named tool.	auto, any, none, or tool	auto, required, none, or function	auto, required, none, or function
LlmRequest.stream: bool	Request incremental output.	stream	stream	stream
LlmRequest.extensions: ProviderExtensions	Provider fields without a first-class neutral field.	Source fields retained by the codec	Source fields retained by the codec	Source fields retained by the codec
LlmRequest.preservation: PreservationMetadata	Original JSON used for same-format replay.	Original parsed body	Original parsed body	Original parsed body

Messages and tool content

Message.role is a Role; Message.content is an ordered Vec<ContentBlock>. The content variants cover text, reasoning, media, tools, MCP activity, refusals, and unknown provider blocks. An unknown block retains its source format and raw JSON. Its retention does not make it usable in a different API.

Protocol field and type	Meaning	Anthropic Messages	OpenAI Responses	Chat Completions
ToolDefinition.parameters: Value	JSON Schema for function arguments.	input_schema	Function parameters	tools[].function.parameters
ToolCall.id: String	Identifier that pairs a call with its result.	tool_use.id	function_call.call_id	tool_calls[].id
ToolCall.name: String	Function name.	tool_use.name	function_call.name	tool_calls[].function.name
ToolCall.arguments: Value	Parsed argument value.	JSON-valued input	arguments, commonly a JSON-encoded string	function.arguments, commonly a JSON-encoded string
ToolResult.tool_call_id: String	Identifier of the call being answered.	tool_result.tool_use_id	function_call_output.call_id	Tool message tool_call_id
ToolResult.content: Vec<ContentBlock>	Ordered tool output.	tool_result.content	function_call_output.output	Tool message content
ToolResult.is_error: Option<bool>	Whether tool execution failed, if reported.	tool_result.is_error	No dedicated error flag	No standard error flag

Tool definitions describe available work. A ToolCall records a model's request to execute that work; it does not execute the tool. Keep call IDs and content order intact when writing an adapter.

Tool::Provider retains an unsupported tool definition for its source format. Built-in provider tools and reasoning signatures may have no valid counterpart in another API. Consult the translation limits instead of assuming a successful parse implies cross-provider support.

Generation settings

The request groups these fields in SamplingParams, OutputParams, and ReasoningParams. Optional values remain unspecified when absent; individual providers apply their own defaults and accepted ranges.

Protocol field and type	Meaning	Anthropic Messages	OpenAI Responses	Chat Completions
SamplingParams.temperature: Option<f64>	Sampling temperature.	temperature	temperature	temperature
SamplingParams.top_p: Option<f64>	Nucleus-sampling probability mass.	top_p	top_p	top_p
SamplingParams.top_k: Option<i64>	Maximum candidate-token count.	top_k	No standard field	No standard field
OutputParams.max_output_tokens: Option<u64>	Output token budget.	max_tokens	max_output_tokens	max_completion_tokens, or legacy max_tokens
OutputParams.response_format: Option<Value>	Requested structured-output shape.	output_config.format	text.format	response_format
OutputParams.is_schema_enforced: Option<bool>	Override whether the provider must enforce the schema; absence retains native behavior.	Schema-backed output configuration	Schema strictness in text.format	Schema strictness in response_format
ReasoningParams.effort: Option<String>	Requested reasoning effort.	output_config.effort	reasoning.effort	reasoning_effort
ReasoningParams.raw: Option<Value>	Provider-specific reasoning configuration.	thinking controls	reasoning object	No standard equivalent for the whole object

Preserved same-format bodies take precedence over edits to these settings, including schema enforcement. See encoding an edited request.

Provider contracts

For complete provider schemas, see Anthropic Messages, OpenAI Responses, and Chat Completions. For response fields and event ownership, continue to Responses and Streams.