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//! `OpenAI` Responses API model implementation.
//!
//! The Responses API is `OpenAI`'s newer API surface that supports reasoning models,
//! multi-turn conversations via `previous_response_id`, and server-executed tools
//! (shell, `code_interpreter`, `web_search`, `apply_patch`, MCP, etc.).
use crate::core::types::{GenerateOptions, GenerateResult, Prompt, StreamPart, Usage};
use crate::openai::responses_types::*;
use anyhow::anyhow;
use async_trait::async_trait;
use eventsource_stream::Eventsource;
use futures::stream::BoxStream;
use futures_util::StreamExt;
use reqwest::Client;
/// `OpenAI` Responses API model.
pub struct OpenAIResponsesModel {
pub api_key: String,
pub base_url: String,
pub client: Client,
}
impl OpenAIResponsesModel {
#[must_use]
pub fn new(api_key: String) -> Self {
Self {
api_key,
base_url: "https://api.openai.com/v1".to_string(),
client: Client::new(),
}
}
/// Build a `ResponsesRequest` from core Prompt and `GenerateOptions`.
fn build_request(&self, prompt: Prompt, options: GenerateOptions) -> ResponsesRequest {
let input = prompt
.messages
.into_iter()
.map(|msg| {
match msg.role {
crate::core::types::Role::System => ResponsesInputItem::Message {
role: ResponsesRole::System,
content: ResponsesMessageContent::Text(
msg.content
.into_iter()
.filter_map(|c| match c {
crate::core::types::Content::Text { text } => Some(text),
_ => None,
})
.collect::<String>(),
),
},
crate::core::types::Role::User => ResponsesInputItem::Message {
role: ResponsesRole::User,
content: ResponsesMessageContent::Parts(
msg.content
.into_iter()
.map(|c| match c {
crate::core::types::Content::Text { text } => {
ResponsesContentPart::InputText { text }
}
crate::core::types::Content::Image { source } => {
let url = match source {
crate::core::types::ImageSource::Url { url } => url,
crate::core::types::ImageSource::Base64 {
data,
media_type,
} => {
format!("data:{media_type};base64,{data}")
}
};
ResponsesContentPart::InputImage { image_url: url }
}
_ => ResponsesContentPart::InputText {
text: String::new(),
},
})
.collect(),
),
},
crate::core::types::Role::Assistant => ResponsesInputItem::Message {
role: ResponsesRole::Assistant,
content: ResponsesMessageContent::Parts(
msg.content
.into_iter()
.filter_map(|c| match c {
crate::core::types::Content::Text { text } => {
Some(ResponsesContentPart::OutputText { text })
}
_ => None,
})
.collect(),
),
},
crate::core::types::Role::Tool => {
// Tool results: extract text + id from ToolResult content
let mut call_id = String::new();
let mut output_text = String::new();
for c in msg.content {
match c {
crate::core::types::Content::ToolResult { id, result } => {
call_id = id;
output_text = result.to_string();
}
crate::core::types::Content::Text { text } => {
output_text = text;
}
_ => {}
}
}
ResponsesInputItem::FunctionCallOutput {
call_id,
output: serde_json::Value::String(output_text),
}
}
}
})
.collect();
let tools = options.tools.map(|tool_defs| {
tool_defs
.into_iter()
.map(|t| ResponsesTool::Function {
name: t.name,
description: Some(t.description),
parameters: t.parameters,
strict: None,
})
.collect()
});
ResponsesRequest {
model: options.model_id,
input,
temperature: options.temperature,
top_p: options.top_p,
max_output_tokens: options.max_tokens,
tools,
tool_choice: None,
text: None,
reasoning: None,
previous_response_id: None,
store: None,
include: None,
stream: None,
instructions: None,
metadata: None,
truncation: None,
service_tier: None,
user: None,
}
}
/// Extract text from response output items.
fn extract_text(output: &[ResponsesOutputItem]) -> String {
let mut texts = Vec::new();
for item in output {
match item {
ResponsesOutputItem::Message { content: parts, .. } => {
for part in parts {
texts.push(part.text.clone());
}
}
ResponsesOutputItem::Reasoning { summary, .. } => {
for s in summary {
texts.push(s.text.clone());
}
}
_ => {}
}
}
texts.join("")
}
/// Determine finish reason from output items.
fn finish_reason(output: &[ResponsesOutputItem]) -> String {
for item in output {
if matches!(
item,
ResponsesOutputItem::FunctionCall { .. }
| ResponsesOutputItem::CustomToolCall { .. }
) {
return "tool_calls".to_string();
}
}
"stop".to_string()
}
}
#[async_trait]
impl crate::core::LanguageModel for OpenAIResponsesModel {
async fn generate(
&self,
prompt: Prompt,
options: GenerateOptions,
) -> crate::core::Result<GenerateResult> {
let request = self.build_request(prompt, options);
let resp = self
.client
.post(format!("{}/responses", self.base_url))
.header("Authorization", &format!("Bearer {}", self.api_key))
.json(&request)
.send()
.await?;
if !resp.status().is_success() {
let error_text = resp.text().await?;
return Err(anyhow!("OpenAI Responses API error: {error_text}").into());
}
let response: ResponsesResponse = resp.json().await?;
if let Some(err) = response.error {
return Err(anyhow!("OpenAI Responses API error: {}", err.message).into());
}
let text = Self::extract_text(&response.output);
let finish_reason = Self::finish_reason(&response.output);
let usage = response.usage.map_or(
Usage {
prompt_tokens: 0,
completion_tokens: 0,
},
|u| Usage {
prompt_tokens: u.input_tokens,
completion_tokens: u.output_tokens,
},
);
Ok(GenerateResult {
text,
usage,
finish_reason,
tool_calls: Vec::new(),
})
}
async fn generate_stream(
&self,
prompt: Prompt,
options: GenerateOptions,
) -> crate::core::Result<BoxStream<'static, StreamPart>> {
let mut request = self.build_request(prompt, options);
request.stream = Some(true);
let resp = self
.client
.post(format!("{}/responses", self.base_url))
.header("Authorization", &format!("Bearer {}", self.api_key))
.json(&request)
.send()
.await?;
if !resp.status().is_success() {
let error_text = resp.text().await?;
return Err(anyhow!("OpenAI Responses API stream error: {error_text}").into());
}
let stream = resp.bytes_stream().eventsource();
let mapped = stream.filter_map(|event| async move {
match event {
Ok(ev) => {
if ev.data == "[DONE]" {
return Some(StreamPart::Finish {
finish_reason: "stop".to_string(),
});
}
match serde_json::from_str::<ResponsesStreamEvent>(&ev.data) {
Ok(ResponsesStreamEvent::OutputTextDelta { delta, .. }) => {
Some(StreamPart::TextDelta { delta })
}
Ok(ResponsesStreamEvent::ReasoningSummaryTextDelta { delta, .. }) => {
Some(StreamPart::TextDelta { delta })
}
Ok(ResponsesStreamEvent::FunctionCallArgumentsDelta {
delta,
item_id,
call_id,
..
}) => Some(StreamPart::ToolCallDelta {
index: 0,
id: Some(call_id),
name: Some(item_id),
arguments_delta: Some(delta),
}),
Ok(ResponsesStreamEvent::ResponseCompleted { response }) => {
if let Some(usage) = response.usage {
Some(StreamPart::Usage {
usage: Usage {
prompt_tokens: usage.input_tokens,
completion_tokens: usage.output_tokens,
},
})
} else {
Some(StreamPart::Finish {
finish_reason: "stop".to_string(),
})
}
}
Ok(ResponsesStreamEvent::ResponseFailed { response }) => {
let msg = response
.error
.map_or_else(|| "Unknown error".to_string(), |e| e.message);
Some(StreamPart::Error { message: msg })
}
Ok(_) => None,
Err(_) => None,
}
}
Err(e) => Some(StreamPart::Error {
message: format!("SSE error: {e}"),
}),
}
});
Ok(Box::pin(mapped))
}
}