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use crate::client::RainyClient;
use crate::error::Result;
use crate::models::{
ChatCompletionRequest, ChatCompletionResponse, ChatCompletionStreamResponse, ChatStreamEvent,
OpenAIChatCompletionRequest, OpenAIChatCompletionResponse, RainyEnvelope,
};
use futures::{Stream, StreamExt};
use std::pin::Pin;
impl RainyClient {
/// Create a chat completion
///
/// This endpoint sends a chat completion request to the Rainy API.
///
/// # Arguments
///
/// * `request` - The chat completion request parameters
///
/// # Returns
///
/// Returns the chat completion response from the AI model.
///
/// # Example
///
/// ```rust,no_run
/// # use rainy_sdk::{RainyClient, ChatCompletionRequest, ChatMessage, MessageRole};
/// # async fn example() -> Result<(), Box<dyn std::error::Error>> {
/// let client = RainyClient::with_api_key("user-api-key")?;
///
/// let messages = vec![
/// ChatMessage::user("Hello, how are you?"),
/// ];
///
/// let request = ChatCompletionRequest::new("gemini-pro", messages)
/// .with_max_tokens(150)
/// .with_temperature(0.7);
///
/// let response = client.create_chat_completion(request).await?;
///
/// if let Some(choice) = response.choices.first() {
/// println!("Response: {}", choice.message.content);
/// }
/// # Ok(())
/// # }
/// ```
pub async fn create_chat_completion(
&self,
request: ChatCompletionRequest,
) -> Result<ChatCompletionResponse> {
let body = serde_json::to_value(request)?;
self.make_request(reqwest::Method::POST, "/chat/completions", Some(body))
.await
}
/// Create an OpenAI-compatible chat completion with full tool-call replay support.
///
/// This variant accepts the complete OpenAI message shape, including:
/// assistant `tool_calls`, `tool` role messages, multimodal content parts, and
/// provider-specific metadata such as thought signatures.
pub async fn create_openai_chat_completion(
&self,
request: OpenAIChatCompletionRequest,
) -> Result<OpenAIChatCompletionResponse> {
let body = serde_json::to_value(request)?;
self.make_request(reqwest::Method::POST, "/chat/completions", Some(body))
.await
}
/// Create a chat completion in envelope mode.
pub async fn create_chat_completion_envelope(
&self,
request: ChatCompletionRequest,
) -> Result<RainyEnvelope<ChatCompletionResponse>> {
let (response, _) = self.chat_completion_envelope(request).await?;
Ok(response)
}
/// Create an OpenAI-compatible chat completion in envelope mode.
pub async fn create_openai_chat_completion_envelope(
&self,
request: OpenAIChatCompletionRequest,
) -> Result<RainyEnvelope<OpenAIChatCompletionResponse>> {
let (response, _) = self.openai_chat_completion_envelope(request).await?;
Ok(response)
}
/// Create a chat completion with streaming
///
/// This method provides streaming support for chat completions.
///
/// # Arguments
///
/// * `request` - The chat completion request parameters
///
/// # Returns
///
/// Returns a stream of chat completion responses.
///
/// # Example
///
/// ```rust,no_run
/// # use rainy_sdk::{RainyClient, ChatCompletionRequest, ChatMessage, MessageRole};
/// # use futures::StreamExt;
/// # async fn example() -> Result<(), Box<dyn std::error::Error>> {
/// let client = RainyClient::with_api_key("user-api-key")?;
///
/// let messages = vec![
/// ChatMessage::user("Tell me a story"),
/// ];
///
/// let request = ChatCompletionRequest::new("llama-3.1-8b-instant", messages)
/// .with_max_tokens(500)
/// .with_temperature(0.8)
/// .with_stream(true);
///
/// let mut stream = client.create_chat_completion_stream(request).await?;
///
/// while let Some(chunk) = stream.next().await {
/// match chunk {
/// Ok(response) => {
/// if let Some(choice) = response.choices.first() {
/// if let Some(content) = &choice.delta.content {
/// print!("{}", content);
/// }
/// }
/// }
/// Err(e) => eprintln!("Error: {}", e),
/// }
/// }
/// # Ok(())
/// # }
/// ```
pub async fn create_chat_completion_stream(
&self,
request: ChatCompletionRequest,
) -> Result<Pin<Box<dyn Stream<Item = Result<ChatCompletionStreamResponse>> + Send>>> {
self.chat_completion_stream(request).await
}
/// Create a streaming OpenAI-compatible chat completion.
///
/// This method uses the same `/api/v1/chat/completions` route but accepts the full
/// OpenAI-compatible message format so callers can replay tool history without a
/// separate compatibility bridge.
pub async fn create_openai_chat_completion_stream(
&self,
request: OpenAIChatCompletionRequest,
) -> Result<Pin<Box<dyn Stream<Item = Result<ChatCompletionStreamResponse>> + Send>>> {
let mut request_with_stream = request;
request_with_stream.stream = Some(true);
let url = self.api_v1_url("/chat/completions");
let response = self
.http_client()
.post(&url)
.json(&request_with_stream)
.send()
.await?;
let events = self.handle_chat_stream_response(response).await?;
let stream = events.filter_map(|event| async move {
match event {
Ok(ChatStreamEvent::Chunk(chunk)) => Some(Ok(chunk)),
Ok(ChatStreamEvent::Billing(_)) | Ok(ChatStreamEvent::Raw(_)) => None,
Err(error) => Some(Err(error)),
}
});
Ok(Box::pin(stream))
}
/// Create a streaming chat completion returning typed stream events.
pub async fn create_chat_completion_stream_events(
&self,
request: ChatCompletionRequest,
) -> Result<Pin<Box<dyn Stream<Item = Result<ChatStreamEvent>> + Send>>> {
self.chat_completion_stream_events(request).await
}
/// Create a streaming OpenAI-compatible chat completion returning typed stream events.
pub async fn create_openai_chat_completion_stream_events(
&self,
request: OpenAIChatCompletionRequest,
) -> Result<Pin<Box<dyn Stream<Item = Result<ChatStreamEvent>> + Send>>> {
let mut request_with_stream = request;
request_with_stream.stream = Some(true);
let url = self.api_v1_url("/chat/completions");
let response = self
.http_client()
.post(&url)
.json(&request_with_stream)
.send()
.await?;
self.handle_chat_stream_response(response).await
}
}