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feat: inject user comments into agent conversation in real-time (try_recv between LLM calls)

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This commit is contained in:
Fam Zheng 2026-04-06 22:01:28 +01:00
parent 409bc89284
commit f70328be0b
1 changed files with 17 additions and 0 deletions
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17
src/agent.rs
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@ -683,6 +683,15 @@ pub async fn run_step_loop(
let step_order = step.order;
for iteration in 0..50 {
// Drain any pending user comments and inject as feedback
while let Ok(event) = event_rx.try_recv() {
if let AgentEvent::Comment { content, .. } = event {
tracing::info!("[workflow {}] Step {} received user feedback: {}", workflow_id, step_order, &content[..content.len().min(100)]);
step_chat_history.push(ChatMessage::user(&format!("【用户反馈】{}", content)));
send_execution(update_tx, workflow_id, step_order, "user_feedback", &content, "已注入到对话上下文", "done").await;
}
}
// Build messages: system + user context + chat history
let mut messages = vec![
ChatMessage::system(&system_prompt),
@ -1087,6 +1096,14 @@ pub async fn run_agent_loop(
break;
}
// Drain pending user comments
while let Ok(event) = event_rx.try_recv() {
if let AgentEvent::Comment { content, .. } = event {
tracing::info!("[workflow {}] Planning received user feedback: {}", workflow_id, &content[..content.len().min(100)]);
state.current_step_chat_history.push(ChatMessage::user(&format!("【用户反馈】{}", content)));
}
}
let system_prompt = build_planning_prompt(project_id, instructions);
let messages = state.build_messages(&system_prompt, requirement);
let msg_count = messages.len() as i32;