Struct OpenAI 

pub struct OpenAI {
    pub enable_web_search: bool,
    pub web_search_context_size: Option<String>,
    pub web_search_user_location_type: Option<String>,
    pub web_search_user_location_approximate_country: Option<String>,
    pub web_search_user_location_approximate_city: Option<String>,
    pub web_search_user_location_approximate_region: Option<String>,
    /* private fields */
}

Client for OpenAI API

Fields

enable_web_search: bool

web_search_context_size: Option<String>

web_search_user_location_type: Option<String>

web_search_user_location_approximate_country: Option<String>

web_search_user_location_approximate_city: Option<String>

web_search_user_location_approximate_region: Option<String>

Implementations

impl OpenAI

pub fn new( api_key: impl Into<String>, base_url: Option<String>, model: Option<String>, max_tokens: Option<u32>, temperature: Option<f32>, timeout_seconds: Option<u64>, system: Option<String>, top_p: Option<f32>, top_k: Option<u32>, embedding_encoding_format: Option<String>, embedding_dimensions: Option<u32>, tools: Option<Vec<Tool>>, tool_choice: Option<ToolChoice>, reasoning_effort: Option<String>, json_schema: Option<StructuredOutputFormat>, voice: Option<String>, enable_web_search: Option<bool>, web_search_context_size: Option<String>, web_search_user_location_type: Option<String>, web_search_user_location_approximate_country: Option<String>, web_search_user_location_approximate_city: Option<String>, web_search_user_location_approximate_region: Option<String>, ) -> Result<Self, LLMError>

Creates a new OpenAI client with the specified configuration.

Arguments

• api_key - OpenAI API key
• model - Model to use (defaults to “gpt-3.5-turbo”)
• max_tokens - Maximum tokens to generate
• temperature - Sampling temperature
• timeout_seconds - Request timeout in seconds
• system - System prompt
• stream - Whether to stream responses
• top_p - Top-p sampling parameter
• top_k - Top-k sampling parameter
• embedding_encoding_format - Format for embedding outputs
• embedding_dimensions - Dimensions for embedding vectors
• tools - Function tools that the model can use
• tool_choice - Determines how the model uses tools
• reasoning_effort - Reasoning effort level
• json_schema - JSON schema for structured output

impl OpenAI

pub fn api_key(&self) -> &str

pub fn model(&self) -> &str

pub fn base_url(&self) -> &Url

pub fn timeout_seconds(&self) -> Option<u64>

pub fn client(&self) -> &Client

pub fn tools(&self) -> Option<&[Tool]>

pub async fn chat_with_hosted_tools( &self, input: String, hosted_tools: Vec<OpenAITool>, ) -> Result<Box<dyn ChatResponse>, LLMError>

Chat with OpenAI-hosted tools using the /responses endpoint

Arguments

• input - The input message
• hosted_tools - List of OpenAI hosted tools to use

Returns

The provider’s response text or an error

Trait Implementations

impl ChatProvider for OpenAI

fn chat_with_tools<'life0, 'life1, 'life2, 'async_trait>( &'life0 self, messages: &'life1 [ChatMessage], tools: Option<&'life2 [Tool]>, ) -> Pin<Box<dyn Future<Output = Result<Box<dyn ChatResponse>, LLMError>> + Send + 'async_trait>>

where Self: 'async_trait, 'life0: 'async_trait, 'life1: 'async_trait, 'life2: 'async_trait,

Chat with tool calls enabled

fn chat_stream<'life0, 'life1, 'async_trait>( &'life0 self, messages: &'life1 [ChatMessage], ) -> Pin<Box<dyn Future<Output = Result<Pin<Box<dyn Stream<Item = Result<String, LLMError>> + Send>>, LLMError>> + Send + 'async_trait>>

where Self: 'async_trait, 'life0: 'async_trait, 'life1: 'async_trait,

Stream chat responses as a stream of strings

fn chat_stream_struct<'life0, 'life1, 'async_trait>( &'life0 self, messages: &'life1 [ChatMessage], ) -> Pin<Box<dyn Future<Output = Result<Pin<Box<dyn Stream<Item = Result<StreamResponse, LLMError>> + Send>>, LLMError>> + Send + 'async_trait>>

where Self: 'async_trait, 'life0: 'async_trait, 'life1: 'async_trait,

Stream chat responses as ChatMessage structured objects, including usage information

fn chat_with_web_search<'life0, 'async_trait>( &'life0 self, input: String, ) -> Pin<Box<dyn Future<Output = Result<Box<dyn ChatResponse>, LLMError>> + Send + 'async_trait>>

where Self: 'async_trait, 'life0: 'async_trait,

Sends a chat with web search request to the provider

fn chat<'life0, 'life1, 'async_trait>( &'life0 self, messages: &'life1 [ChatMessage], ) -> Pin<Box<dyn Future<Output = Result<Box<dyn ChatResponse>, LLMError>> + Send + 'async_trait>>

where Self: 'async_trait, 'life0: 'async_trait, 'life1: 'async_trait,

Sends a chat request to the provider with a sequence of messages.

fn memory_contents<'life0, 'async_trait>( &'life0 self, ) -> Pin<Box<dyn Future<Output = Option<Vec<ChatMessage>>> + Send + 'async_trait>>

where Self: 'async_trait, 'life0: 'async_trait,

Get current memory contents if provider supports memory

fn summarize_history<'life0, 'life1, 'async_trait>( &'life0 self, msgs: &'life1 [ChatMessage], ) -> Pin<Box<dyn Future<Output = Result<String, LLMError>> + Send + 'async_trait>>

where Self: 'async_trait, 'life0: 'async_trait, 'life1: 'async_trait,

Summarizes a conversation history into a concise 2-3 sentence summary

impl CompletionProvider for OpenAI

fn complete<'life0, 'life1, 'async_trait>( &'life0 self, _req: &'life1 CompletionRequest, ) -> Pin<Box<dyn Future<Output = Result<CompletionResponse, LLMError>> + Send + 'async_trait>>

where Self: 'async_trait, 'life0: 'async_trait, 'life1: 'async_trait,

Sends a completion request to generate text.

impl EmbeddingProvider for OpenAI

fn embed<'life0, 'async_trait>( &'life0 self, input: Vec<String>, ) -> Pin<Box<dyn Future<Output = Result<Vec<Vec<f32>>, LLMError>> + Send + 'async_trait>>

where Self: 'async_trait, 'life0: 'async_trait,

impl LLMProvider for OpenAI

fn tools(&self) -> Option<&[Tool]>

impl ModelsProvider for OpenAI

fn list_models<'life0, 'life1, 'async_trait>( &'life0 self, _request: Option<&'life1 ModelListRequest>, ) -> Pin<Box<dyn Future<Output = Result<Box<dyn ModelListResponse>, LLMError>> + Send + 'async_trait>>

where Self: 'async_trait, 'life0: 'async_trait, 'life1: 'async_trait,

Asynchronously retrieves the list of available models ID’s from the provider.

impl SpeechToTextProvider for OpenAI

fn transcribe<'life0, 'async_trait>( &'life0 self, _audio: Vec<u8>, ) -> Pin<Box<dyn Future<Output = Result<String, LLMError>> + Send + 'async_trait>>

where Self: 'async_trait, 'life0: 'async_trait,

Transcribe the given audio bytes into text

fn transcribe_file<'life0, 'life1, 'async_trait>( &'life0 self, file_path: &'life1 str, ) -> Pin<Box<dyn Future<Output = Result<String, LLMError>> + Send + 'async_trait>>

where Self: 'async_trait, 'life0: 'async_trait, 'life1: 'async_trait,

impl TextToSpeechProvider for OpenAI

fn speech<'life0, 'life1, 'async_trait>( &'life0 self, _text: &'life1 str, ) -> Pin<Box<dyn Future<Output = Result<Vec<u8>, LLMError>> + Send + 'async_trait>>

where Self: 'async_trait, 'life0: 'async_trait, 'life1: 'async_trait,

Convert the given text into speech audio