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/*
* OpenAI API
*
* The OpenAI REST API. Please see pub https://platform.openai.com/docs/api-reference for more details.
*
* OpenAPI spec pub version: 2.3.0
*
* Generated pub by: https://github.com/swagger-api/swagger-codegen.git
*/
/// pub AssistantObject : Represents an `assistant` that can call the model and use tools.
#[allow(unused_imports)]
use serde_json::Value;
/// # on openapi.yaml
///
/// ```yaml
/// AssistantObject:
/// type: object
/// title: Assistant
/// description: Represents an `assistant` that can call the model and use tools.
/// properties:
/// id:
/// description: The identifier, which can be referenced in API endpoints.
/// type: string
/// object:
/// description: The object type, which is always `assistant`.
/// type: string
/// enum:
/// - assistant
/// x-stainless-const: true
/// created_at:
/// description: The Unix timestamp (in seconds) for when the assistant was created.
/// type: integer
/// name:
/// description: |
/// The name of the assistant. The maximum length is 256 characters.
/// type: string
/// maxLength: 256
/// nullable: true
/// description:
/// description: >
/// The description of the assistant. The maximum length is 512
/// characters.
/// type: string
/// maxLength: 512
/// nullable: true
/// model:
/// description: >
/// ID of the model to use. You can use the [List
/// models](/docs/api-reference/models/list) API to see all of your
/// available models, or see our [Model overview](/docs/models) for
/// descriptions of them.
/// type: string
/// instructions:
/// description: >
/// The system instructions that the assistant uses. The maximum length
/// is 256,000 characters.
/// type: string
/// maxLength: 256000
/// nullable: true
/// tools:
/// description: >
/// A list of tool enabled on the assistant. There can be a maximum of
/// 128 tools per assistant. Tools can be of types `code_interpreter`,
/// `file_search`, or `function`.
/// default: []
/// type: array
/// maxItems: 128
/// items:
/// oneOf:
/// - $ref: "#/components/schemas/AssistantToolsCode"
/// - $ref: "#/components/schemas/AssistantToolsFileSearch"
/// - $ref: "#/components/schemas/AssistantToolsFunction"
/// tool_resources:
/// type: object
/// description: >
/// A set of resources that are used by the assistant's tools. The
/// resources are specific to the type of tool. For example, the
/// `code_interpreter` tool requires a list of file IDs, while the
/// `file_search` tool requires a list of vector store IDs.
/// properties:
/// code_interpreter:
/// type: object
/// properties:
/// file_ids:
/// type: array
/// description: >
/// A list of [file](/docs/api-reference/files) IDs made
/// available to the `code_interpreter`` tool. There can be a
/// maximum of 20 files associated with the tool.
/// default: []
/// maxItems: 20
/// items:
/// type: string
/// file_search:
/// type: object
/// properties:
/// vector_store_ids:
/// type: array
/// description: >
/// The ID of the [vector
/// store](/docs/api-reference/vector-stores/object) attached to
/// this assistant. There can be a maximum of 1 vector store
/// attached to the assistant.
/// maxItems: 1
/// items:
/// type: string
/// nullable: true
/// metadata:
/// $ref: "#/components/schemas/Metadata"
/// temperature:
/// description: >
/// What sampling temperature to use, between 0 and 2. Higher values
/// like 0.8 will make the output more random, while lower values like
/// 0.2 will make it more focused and deterministic.
/// type: number
/// minimum: 0
/// maximum: 2
/// default: 1
/// example: 1
/// nullable: true
/// top_p:
/// type: number
/// minimum: 0
/// maximum: 1
/// default: 1
/// example: 1
/// nullable: true
/// description: >
/// An alternative to sampling with temperature, called nucleus
/// sampling, where the model considers the results of the tokens with
/// top_p probability mass. So 0.1 means only the tokens comprising the
/// top 10% probability mass are considered.
///
///
/// We generally recommend altering this or temperature but not both.
/// response_format:
/// $ref: "#/components/schemas/AssistantsApiResponseFormatOption"
/// nullable: true
/// required:
/// - id
/// - object
/// - created_at
/// - name
/// - description
/// - model
/// - instructions
/// - tools
/// - metadata
/// x-oaiMeta:
/// name: The assistant object
/// beta: true
/// example: >
/// {
/// "id": "asst_abc123",
/// "object": "assistant",
/// "created_at": 1698984975,
/// "name": "Math Tutor",
/// "description": null,
/// "model": "gpt-4o",
/// "instructions": "You are a personal math tutor. When asked a question, write and run Python code to answer the question.",
/// "tools": [
/// {
/// "type": "code_interpreter"
/// }
/// ],
/// "metadata": {},
/// "top_p": 1.0,
/// "temperature": 1.0,
/// "response_format": "auto"
/// }
/// ```
#[derive(Debug, Serialize, Deserialize)]
pub struct AssistantObject {
/// The Unix timestamp (in seconds) for when the assistant was created.
#[serde(rename = "created_at")]
pub created_at: i32,
/// The description of the assistant. The maximum length is 512 characters.
#[serde(rename = "description")]
pub description: String,
/// The identifier, which can be referenced in API endpoints.
#[serde(rename = "id")]
pub id: String,
/// The system instructions that the assistant uses. The maximum length is 256,000 characters.
#[serde(rename = "instructions")]
pub instructions: String,
#[serde(rename = "metadata")]
pub metadata: crate::models::Metadata,
/// ID of the model to use. You can use the [List models](/docs/api-reference/models/list) API to see all of your available models, or see our [Model overview](/docs/models) for descriptions of them.
#[serde(rename = "model")]
pub model: String,
/// The name of the assistant. The maximum length is 256 characters.
#[serde(rename = "name")]
pub name: String,
/// The object type, which is always `assistant`.
#[serde(rename = "object")]
#[serde(default = "default_object")]
pub object: String,
#[serde(rename = "response_format")]
pub response_format: Option<crate::models::AssistantsApiResponseFormatOption>,
/// What sampling temperature to use, between 0 and 2. Higher values like 0.8 will make the output more random, while lower values like 0.2 will make it more focused and deterministic.
#[serde(rename = "temperature")]
pub temperature: Option<f32>,
#[serde(rename = "tool_resources")]
pub tool_resources: Option<crate::models::AssistantObjectToolResources>,
/// A list of tool enabled on the assistant. There can be a maximum of 128 tools per assistant. Tools can be of types `code_interpreter`, `file_search`, or `function`.
#[serde(rename = "tools")]
pub tools: Vec<AssistantObjectTool>,
/// An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the tokens with top_p probability mass. So 0.1 means only the tokens comprising the top 10% probability mass are considered. We generally recommend altering this or temperature but not both.
#[serde(rename = "top_p")]
pub top_p: Option<f32>,
}
fn default_object() -> String {
"assistant".into()
}
#[derive(Debug, Serialize, Deserialize)]
#[serde(untagged)]
pub enum AssistantObjectTool {
Code(crate::AssistantToolsCode),
FileSearch(crate::AssistantToolsFileSearch),
Function(crate::AssistantToolsFunction),
}