Struct CreateMessagesRequest 

pub struct CreateMessagesRequest {

    pub max_tokens: i64,
    pub messages: Vec<MessagesMessage>,
    pub metadata: Option<MessagesMetadata>,
    pub model: String,
    pub output_config: Option<MessagesOutputConfig>,
    pub stop_sequences: Vec<String>,
    pub stream: bool,
    pub system: Option<CreateMessagesRequestSystem>,
    pub temperature: Option<f32>,
    pub thinking: Option<CreateMessagesRequestThinking>,
    pub tool_choice: Option<MessagesToolChoice>,
    pub tools: Vec<MessagesTool>,
    pub top_k: Option<i64>,
    pub top_p: Option<f32>,
}

Request body for creating a message via the Anthropic-compatible Messages API.

JSON schema

{
 "description": "Request body for creating a message via the Anthropic-compatible\nMessages API.\n",
 "type": "object",
 "required": [
   "max_tokens",
   "messages",
   "model"
 ],
 "properties": {
   "max_tokens": {
     "description": "The maximum number of tokens to generate before stopping.\n",
     "type": "integer"
   },
   "messages": {
     "description": "The messages to generate a response for. Each message has a\n`role` (user or assistant) and `content`.\n",
     "type": "array",
     "items": {
       "$ref": "#/definitions/MessagesMessage"
     }
   },
   "metadata": {
     "$ref": "#/definitions/MessagesMetadata"
   },
   "model": {
     "description": "The model to use for generating the message.",
     "type": "string"
   },
   "output_config": {
     "$ref": "#/definitions/MessagesOutputConfig"
   },
   "stop_sequences": {
     "description": "Custom text sequences that will cause the model to stop\ngenerating.\n",
     "type": "array",
     "items": {
       "type": "string"
     }
   },
   "stream": {
     "description": "Whether to stream the response using server-sent events.\n",
     "default": false,
     "type": "boolean"
   },
   "system": {
     "description": "The system prompt. Can be a string or an array of system content\nblocks (for prompt caching).\n",
     "oneOf": [
       {
         "description": "System prompt as a string.",
         "type": "string"
       },
       {
         "type": "array",
         "items": {
           "$ref": "#/definitions/MessagesTextBlock"
         }
       }
     ]
   },
   "temperature": {
     "description": "Amount of randomness injected into the response. Ranges from\n0.0 to 1.0. Use closer to 0 for analytical / multiple choice,\ncloser to 1 for creative and generative tasks.\n",
     "type": "number",
     "format": "float"
   },
   "thinking": {
     "description": "Configuration for extended thinking.\n",
     "type": "object",
     "required": [
       "budget_tokens",
       "type"
     ],
     "properties": {
       "budget_tokens": {
         "description": "The maximum number of tokens the model is allowed to use\nfor thinking.\n",
         "type": "integer"
       },
       "type": {
         "description": "Always `enabled`.",
         "type": "string",
         "enum": [
           "enabled"
         ]
       }
     }
   },
   "tool_choice": {
     "$ref": "#/definitions/MessagesToolChoice"
   },
   "tools": {
     "description": "Definitions of tools the model may call. Each tool can include\n`cache_control` for prompt caching.\n",
     "type": "array",
     "items": {
       "$ref": "#/definitions/MessagesTool"
     }
   },
   "top_k": {
     "description": "Only sample from the top K options for each subsequent token.\n",
     "type": "integer"
   },
   "top_p": {
     "description": "Use nucleus sampling. Only consider the tokens with top_p\nprobability mass.\n",
     "type": "number",
     "format": "float"
   }
 }
}

Fields

max_tokens: i64

The maximum number of tokens to generate before stopping.

messages: Vec<MessagesMessage>

The messages to generate a response for. Each message has a role (user or assistant) and content.

metadata: Option<MessagesMetadata>

model: String

The model to use for generating the message.

output_config: Option<MessagesOutputConfig>

stop_sequences: Vec<String>

Custom text sequences that will cause the model to stop generating.

stream: bool

Whether to stream the response using server-sent events.

system: Option<CreateMessagesRequestSystem>

The system prompt. Can be a string or an array of system content blocks (for prompt caching).

temperature: Option<f32>

Amount of randomness injected into the response. Ranges from 0.0 to 1.0. Use closer to 0 for analytical / multiple choice, closer to 1 for creative and generative tasks.

thinking: Option<CreateMessagesRequestThinking>

tool_choice: Option<MessagesToolChoice>

tools: Vec<MessagesTool>

Definitions of tools the model may call. Each tool can include cache_control for prompt caching.

top_k: Option<i64>

Only sample from the top K options for each subsequent token.

top_p: Option<f32>

Use nucleus sampling. Only consider the tokens with top_p probability mass.

Trait Implementations

impl Clone for CreateMessagesRequest

fn clone(&self) -> CreateMessagesRequest

Returns a duplicate of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for CreateMessagesRequest

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl<'de> Deserialize<'de> for CreateMessagesRequest

fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error>

where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl Serialize for CreateMessagesRequest

fn serialize<__S>(&self, __serializer: __S) -> Result<__S::Ok, __S::Error>

where __S: Serializer,

Serialize this value into the given Serde serializer.