mirror of
https://github.com/openai/codex.git
synced 2026-09-16 12:13:30 +00:00
fix: chat completions API to work with tools
This commit is contained in:
@@ -28,8 +28,7 @@ use crate::models::ResponseItem;
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use crate::openai_tools::create_tools_json_for_chat_completions_api;
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use crate::util::backoff;
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/// Implementation for the classic Chat Completions API. This is intentionally
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/// minimal: we only stream back plain assistant text.
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/// Implementation for the classic Chat Completions API.
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pub(crate) async fn stream_chat_completions(
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prompt: &Prompt,
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model: &str,
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@@ -43,17 +42,67 @@ pub(crate) async fn stream_chat_completions(
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messages.push(json!({"role": "system", "content": full_instructions}));
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for item in &prompt.input {
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if let ResponseItem::Message { role, content } = item {
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let mut text = String::new();
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for c in content {
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match c {
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ContentItem::InputText { text: t } | ContentItem::OutputText { text: t } => {
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text.push_str(t);
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match item {
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ResponseItem::Message { role, content } => {
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let mut text = String::new();
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for c in content {
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match c {
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ContentItem::InputText { text: t }
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| ContentItem::OutputText { text: t } => {
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text.push_str(t);
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}
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_ => {}
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}
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_ => {}
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}
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messages.push(json!({"role": role, "content": text}));
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}
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ResponseItem::FunctionCall {
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name,
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arguments,
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call_id,
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} => {
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messages.push(json!({
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"role": "assistant",
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"content": null,
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"tool_calls": [{
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"id": call_id,
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"type": "function",
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"function": {
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"name": name,
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"arguments": arguments,
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}
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}]
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}));
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}
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ResponseItem::LocalShellCall {
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id,
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call_id: _,
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status,
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action,
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} => {
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// Confirm with API team.
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messages.push(json!({
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"role": "assistant",
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"content": null,
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"tool_calls": [{
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"id": id.clone().unwrap_or_else(|| "".to_string()),
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"type": "local_shell_call",
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"status": status,
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"action": action,
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}]
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}));
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}
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ResponseItem::FunctionCallOutput { call_id, output } => {
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messages.push(json!({
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"role": "tool",
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"tool_call_id": call_id,
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"content": output.content,
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}));
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}
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ResponseItem::Reasoning { .. } | ResponseItem::Other => {
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// Omit these items from the conversation history.
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continue;
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}
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messages.push(json!({"role": role, "content": text}));
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}
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}
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@@ -140,6 +189,21 @@ where
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let idle_timeout = *OPENAI_STREAM_IDLE_TIMEOUT_MS;
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// State to accumulate a function call across streaming chunks.
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// OpenAI may split the `arguments` string over multiple `delta` events
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// until the chunk whose `finish_reason` is `tool_calls` is emitted. We
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// keep collecting the pieces here and forward a single
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// `ResponseItem::FunctionCall` once the call is complete.
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#[derive(Default)]
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struct FunctionCallState {
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name: Option<String>,
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arguments: String,
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call_id: Option<String>,
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active: bool,
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}
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let mut fn_call_state = FunctionCallState::default();
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loop {
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let sse = match timeout(idle_timeout, stream.next()).await {
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Ok(Some(Ok(ev))) => ev,
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@@ -179,23 +243,89 @@ where
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Ok(v) => v,
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Err(_) => continue,
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};
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trace!("chat_completions received SSE chunk: {chunk:?}");
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let content_opt = chunk
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.get("choices")
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.and_then(|c| c.get(0))
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.and_then(|c| c.get("delta"))
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.and_then(|d| d.get("content"))
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.and_then(|c| c.as_str());
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let choice_opt = chunk.get("choices").and_then(|c| c.get(0));
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if let Some(content) = content_opt {
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let item = ResponseItem::Message {
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role: "assistant".to_string(),
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content: vec![ContentItem::OutputText {
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text: content.to_string(),
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}],
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};
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if let Some(choice) = choice_opt {
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// Handle assistant content tokens.
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if let Some(content) = choice
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.get("delta")
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.and_then(|d| d.get("content"))
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.and_then(|c| c.as_str())
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{
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let item = ResponseItem::Message {
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role: "assistant".to_string(),
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content: vec![ContentItem::OutputText {
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text: content.to_string(),
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}],
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};
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let _ = tx_event.send(Ok(ResponseEvent::OutputItemDone(item))).await;
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let _ = tx_event.send(Ok(ResponseEvent::OutputItemDone(item))).await;
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}
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// Handle streaming function / tool calls.
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if let Some(tool_calls) = choice
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.get("delta")
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.and_then(|d| d.get("tool_calls"))
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.and_then(|tc| tc.as_array())
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{
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if let Some(tool_call) = tool_calls.first() {
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// Mark that we have an active function call in progress.
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fn_call_state.active = true;
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// Extract call_id if present.
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if let Some(id) = tool_call.get("id").and_then(|v| v.as_str()) {
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fn_call_state.call_id.get_or_insert_with(|| id.to_string());
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}
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// Extract function details if present.
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if let Some(function) = tool_call.get("function") {
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if let Some(name) = function.get("name").and_then(|n| n.as_str()) {
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fn_call_state.name.get_or_insert_with(|| name.to_string());
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}
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if let Some(args_fragment) =
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function.get("arguments").and_then(|a| a.as_str())
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{
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fn_call_state.arguments.push_str(args_fragment);
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}
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}
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}
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}
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// Emit end-of-turn when finish_reason signals completion.
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if let Some(finish_reason) = choice.get("finish_reason").and_then(|v| v.as_str()) {
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match finish_reason {
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"tool_calls" if fn_call_state.active => {
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// Build the FunctionCall response item.
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let item = ResponseItem::FunctionCall {
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name: fn_call_state.name.clone().unwrap_or_else(|| "".to_string()),
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arguments: fn_call_state.arguments.clone(),
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call_id: fn_call_state.call_id.clone().unwrap_or_else(String::new),
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};
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// Emit it downstream.
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let _ = tx_event.send(Ok(ResponseEvent::OutputItemDone(item))).await;
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}
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"stop" => {
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// Regular turn without tool-call.
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}
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_ => {}
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}
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// Emit Completed regardless of reason so the agent can advance.
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let _ = tx_event
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.send(Ok(ResponseEvent::Completed {
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response_id: String::new(),
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}))
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.await;
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// Prepare for potential next turn (should not happen in same stream).
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// fn_call_state = FunctionCallState::default();
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return; // End processing for this SSE stream.
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}
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}
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}
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}
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@@ -242,9 +372,14 @@ where
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Poll::Ready(None) => return Poll::Ready(None),
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Poll::Ready(Some(Err(e))) => return Poll::Ready(Some(Err(e))),
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Poll::Ready(Some(Ok(ResponseEvent::OutputItemDone(item)))) => {
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// Accumulate *assistant* text but do not emit yet.
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if let crate::models::ResponseItem::Message { role, content } = &item {
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if role == "assistant" {
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// If this is an incremental assistant message chunk, accumulate but
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// do NOT emit yet. Forward any other item (e.g. FunctionCall) right
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// away so downstream consumers see it.
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let is_assistant_delta = matches!(&item, crate::models::ResponseItem::Message { role, .. } if role == "assistant");
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if is_assistant_delta {
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if let crate::models::ResponseItem::Message { content, .. } = &item {
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if let Some(text) = content.iter().find_map(|c| match c {
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crate::models::ContentItem::OutputText { text } => Some(text),
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_ => None,
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@@ -252,10 +387,13 @@ where
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this.cumulative.push_str(text);
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}
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}
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// Swallow partial assistant chunk; keep polling.
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continue;
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}
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// Swallow partial event; keep polling.
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continue;
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// Not an assistant message – forward immediately.
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return Poll::Ready(Some(Ok(ResponseEvent::OutputItemDone(item))));
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}
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Poll::Ready(Some(Ok(ResponseEvent::Completed { response_id }))) => {
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if !this.cumulative.is_empty() {
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@@ -20,6 +20,7 @@ use codex_apply_patch::MaybeApplyPatchVerified;
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use codex_apply_patch::maybe_parse_apply_patch_verified;
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use codex_apply_patch::print_summary;
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use futures::prelude::*;
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use mcp_types::CallToolResult;
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use serde::Serialize;
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use serde_json;
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use tokio::sync::Notify;
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@@ -388,7 +389,7 @@ impl Session {
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tool: &str,
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arguments: Option<serde_json::Value>,
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timeout: Option<Duration>,
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) -> anyhow::Result<mcp_types::CallToolResult> {
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) -> anyhow::Result<CallToolResult> {
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self.mcp_connection_manager
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.call_tool(server, tool, arguments, timeout)
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.await
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@@ -775,6 +776,7 @@ async fn run_task(sess: Arc<Session>, sub_id: String, input: Vec<InputItem>) {
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let mut pending_response_input: Vec<ResponseInputItem> = vec![ResponseInputItem::from(input)];
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let last_agent_message: Option<String>;
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loop {
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debug!("pending_response_input: {pending_response_input:?}");
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let mut net_new_turn_input = pending_response_input
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.drain(..)
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.map(ResponseItem::from)
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@@ -828,31 +830,102 @@ async fn run_task(sess: Arc<Session>, sub_id: String, input: Vec<InputItem>) {
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})
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})
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.collect();
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debug!("Turn input: {turn_input:?}");
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match run_turn(&sess, sub_id.clone(), turn_input).await {
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Ok(turn_output) => {
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let (items, responses): (Vec<_>, Vec<_>) = turn_output
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.into_iter()
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.map(|p| (p.item, p.response))
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.unzip();
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let responses = responses
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.into_iter()
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.flatten()
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.collect::<Vec<ResponseInputItem>>();
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let mut items_to_record_to_conversation_history = Vec::<ResponseItem>::new();
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let mut responses = Vec::<ResponseInputItem>::new();
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for processed_response_item in turn_output {
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let ProcessedResponseItem { item, response } = processed_response_item;
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match (&item, &response) {
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(ResponseItem::Message { role, content, .. }, None)
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if role == "assistant" =>
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{
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// If the model returned a message, we need to record it.
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items_to_record_to_conversation_history.push(ResponseItem::Message {
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content: content.clone(),
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role: "assistant".to_string(),
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});
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}
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(
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ResponseItem::LocalShellCall { .. },
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Some(ResponseInputItem::FunctionCallOutput { call_id, output }),
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) => {
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items_to_record_to_conversation_history.push(item);
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items_to_record_to_conversation_history.push(
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ResponseItem::FunctionCallOutput {
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call_id: call_id.clone(),
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output: output.clone(),
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},
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);
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}
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(
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ResponseItem::FunctionCall { .. },
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Some(ResponseInputItem::FunctionCallOutput { call_id, output }),
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) => {
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items_to_record_to_conversation_history.push(item);
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items_to_record_to_conversation_history.push(
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ResponseItem::FunctionCallOutput {
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call_id: call_id.clone(),
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output: output.clone(),
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},
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);
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}
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(
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ResponseItem::FunctionCall { .. },
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Some(ResponseInputItem::McpToolCallOutput { call_id, result }),
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) => {
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items_to_record_to_conversation_history.push(item);
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// let (content, success): (String, Option<bool>) = match result {
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// Ok(CallToolResult { content, is_error }) => {
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// (content, is_error.or_else(false))
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// }
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// Err(e) => (e.clone(), Some(true)),
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// };
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// items_to_record_to_conversation_history.push(
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// ResponseItem::FunctionCallOutput {
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// call_id: call_id.clone(),
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// output: FunctionCallOutputPayload { content, success },
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// },
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// );
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warn!(
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"Skipping MCP tool call output: {call_id:?} with response: {result:?}"
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);
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}
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_ => {
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warn!("Unexpected response item: {item:?} with response: {response:?}");
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}
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};
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if let Some(response) = response {
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responses.push(response);
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}
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}
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// Only attempt to take the lock if there is something to record.
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if !items.is_empty() {
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if !items_to_record_to_conversation_history.is_empty() {
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// First persist model-generated output to the rollout file – this only borrows.
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sess.record_rollout_items(&items).await;
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sess.record_rollout_items(&items_to_record_to_conversation_history)
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.await;
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debug!(
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"has transcript? {}",
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sess.state.lock().unwrap().zdr_transcript.is_some()
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);
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// For ZDR we also need to keep a transcript clone.
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if let Some(transcript) = sess.state.lock().unwrap().zdr_transcript.as_mut() {
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transcript.record_items(&items);
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debug!(
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"Recording items to transcript: {items_to_record_to_conversation_history:?}"
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);
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transcript.record_items(&items_to_record_to_conversation_history);
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}
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}
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if responses.is_empty() {
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debug!("Turn completed");
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last_agent_message = get_last_assistant_message_from_turn(&items);
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last_agent_message = get_last_assistant_message_from_turn(
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&items_to_record_to_conversation_history,
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);
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sess.maybe_notify(UserNotification::AgentTurnComplete {
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turn_id: sub_id.clone(),
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input_messages: turn_input_messages,
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@@ -959,6 +1032,7 @@ async fn run_turn(
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/// events map to a `ResponseItem`. A `ResponseItem` may need to be
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/// "handled" such that it produces a `ResponseInputItem` that needs to be
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/// sent back to the model on the next turn.
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#[derive(Debug)]
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struct ProcessedResponseItem {
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item: ResponseItem,
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response: Option<ResponseInputItem>,
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