gitdataai/libs/room/src/service/ai_streaming.rs
ZhenYi ddd24bfb6d fix(streaming): add seq field for strict chunk ordering
- Add seq: u64 to RoomMessageStreamChunkEvent
- Frontend sorts by seq on insert for ordered replay
- Initial event now includes seq: 0
2026-04-28 09:42:41 +08:00

282 lines
12 KiB
Rust

use std::pin::Pin;
use std::sync::Arc;
use chrono::Utc;
use db::cache::AppCache;
use db::database::AppDatabase;
use models::rooms::room_ai;
use queue::{MessageProducer, ProjectRoomEvent, RoomMessageEnvelope};
use sea_orm::{sea_query::Expr, ColumnTrait, EntityTrait, ExprTrait, QueryFilter};
use uuid::Uuid;
use super::sequence::next_room_message_seq_internal;
use crate::connection::RoomConnectionManager;
use agent::chat::{AiRequest, ChatService};
pub async fn process_message_ai_streaming(
chat_service: Arc<ChatService>,
request: AiRequest,
room_id: Uuid,
project_id: Uuid,
model_id: Uuid,
lock_guard: crate::room_ai_queue::RoomAiLockGuard,
db: AppDatabase,
cache: AppCache,
queue: MessageProducer,
room_manager: Arc<RoomConnectionManager>,
) {
use queue::RoomMessageStreamChunkEvent;
let streaming_msg_id = Uuid::now_v7();
let seq = match next_room_message_seq_internal(room_id, &db, &cache).await {
Ok(s) => s,
Err(e) => {
tracing::error!(error = %e, "Failed to get seq for streaming AI message");
return;
}
};
let _ = room_manager
.register_stream_channel(streaming_msg_id)
.await;
let initial_event = RoomMessageStreamChunkEvent {
message_id: streaming_msg_id,
room_id,
seq: 0,
content: String::new(),
done: false,
error: None,
display_name: Some(request.model.name.clone()),
chunk_type: Some("thinking".to_string()),
};
room_manager.broadcast_stream_chunk(initial_event).await;
let room_id_inner = room_id;
let project_id_inner = project_id;
let now = Utc::now();
let sender_type = "ai".to_string();
let ai_display_name = request.model.name.clone();
tokio::spawn(async move {
let _lock_guard = lock_guard;
let ai_typing_id = Uuid::parse_str("00000000-0000-0000-0000-000000000001")
.expect("constant UUID should always parse");
let ai_display_name_for_chunk = ai_display_name.clone();
let ai_display_name_for_final = ai_display_name.clone();
let chunk_count = std::sync::Arc::new(std::sync::atomic::AtomicU64::new(0));
let room_manager_cb = room_manager.clone();
let on_chunk = move |chunk: agent::chat::AiStreamChunk| {
Box::pin({
let room_manager = room_manager_cb.clone();
let streaming_msg_id = streaming_msg_id;
let room_id = room_id_inner;
let chunk_count = chunk_count.clone();
let ai_display_name_for_chunk = ai_display_name_for_chunk.clone();
async move {
let chunk_type_str = match chunk.chunk_type {
agent::chat::AiChunkType::Thinking => "thinking",
agent::chat::AiChunkType::Answer => "answer",
agent::chat::AiChunkType::ToolCall => "tool_call",
agent::chat::AiChunkType::ToolResult => "tool_result",
};
let seq = chunk_count.fetch_add(1, std::sync::atomic::Ordering::Relaxed);
let event = RoomMessageStreamChunkEvent {
message_id: streaming_msg_id,
room_id,
seq,
content: chunk.content,
done: chunk.done,
error: None,
display_name: Some(ai_display_name_for_chunk),
chunk_type: Some(chunk_type_str.to_string()),
};
room_manager.broadcast_stream_chunk(event).await;
}
}) as Pin<Box<dyn std::future::Future<Output = ()> + Send>>
};
let stream_callback: agent::chat::StreamCallback = Box::new(on_chunk);
let typing_start = queue::TypingEvent {
room_id: room_id_inner,
user_id: ai_typing_id,
username: ai_display_name.clone(),
avatar_url: None,
action: "start".to_string(),
sender_type: Some("ai".to_string()),
};
room_manager.broadcast_typing(room_id_inner, typing_start.clone()).await;
let (typing_cancel_tx, typing_cancel_rx) = tokio::sync::oneshot::channel::<()>();
let typing_renew_handle = tokio::spawn({
let mut interval = tokio::time::interval(std::time::Duration::from_secs(30));
interval.set_missed_tick_behavior(tokio::time::MissedTickBehavior::Skip);
let mgr = room_manager.clone();
let rid = room_id_inner;
let evt = typing_start.clone();
async move {
tokio::select! {
_ = typing_cancel_rx => {}
_ = async {
loop {
interval.tick().await;
mgr.broadcast_typing(rid, evt.clone()).await;
}
} => {}
}
}
});
match chat_service.process_stream(request, stream_callback).await {
Ok(result) => {
// Store ordered chunks as JSON in thinking_content for ordered replay.
// Uses {"__chunks__": [...]} marker so legacy plain-text still works.
let thinking_content = if result.chunks.is_empty() {
None
} else {
let chunks_json = serde_json::json!({
"__chunks__": result.chunks.iter().map(|c| {
let type_str = match c.chunk_type {
agent::client::StreamChunkType::Thinking => "thinking",
agent::client::StreamChunkType::Answer => "answer",
agent::client::StreamChunkType::ToolCall => "tool_call",
};
serde_json::json!({
"type": type_str,
"content": c.content,
})
}).collect::<Vec<_>>(),
});
Some(chunks_json.to_string())
};
let envelope = RoomMessageEnvelope {
id: streaming_msg_id,
dedup_key: Some(format!("{}:{}", room_id_inner, streaming_msg_id)),
room_id: room_id_inner,
sender_type: sender_type.clone(),
sender_id: None,
model_id: Some(model_id),
thread_id: None,
content: result.content.clone(),
content_type: "text".to_string(),
thinking_content: thinking_content.clone(),
send_at: now,
seq,
in_reply_to: None,
display_name: Some(ai_display_name_for_final.clone()),
};
if let Err(e) = queue.publish(room_id_inner, envelope).await {
tracing::error!(error = %e, "Failed to publish streaming AI message");
} else {
let now = Utc::now();
if let Err(e) = room_ai::Entity::update_many()
.col_expr(
room_ai::Column::CallCount,
Expr::col(room_ai::Column::CallCount).add(1),
)
.col_expr(
room_ai::Column::LastCallAt,
Expr::value(Some(now)),
)
.filter(room_ai::Column::Room.eq(room_id_inner))
.filter(room_ai::Column::Model.eq(model_id))
.exec(&db)
.await
{
tracing::warn!(error = %e, "Failed to update room_ai call stats");
}
// Record billing (non-fatal)
if let Err(e) = super::billing::record_ai_usage(
&db,
project_id_inner,
model_id,
result.input_tokens,
result.output_tokens,
)
.await
{
tracing::warn!(error = %e, "AI billing recording failed");
}
let msg_event = queue::RoomMessageEvent {
id: streaming_msg_id,
room_id: room_id_inner,
sender_type: sender_type.clone(),
sender_id: None,
thread_id: None,
content: result.content.clone(),
content_type: "text".to_string(),
thinking_content: thinking_content.clone(),
send_at: now,
seq,
display_name: Some(ai_display_name_for_final.clone()),
in_reply_to: None,
reactions: None,
message_id: None,
};
room_manager.broadcast(room_id_inner, msg_event).await;
room_manager.metrics.messages_sent.increment(1);
let _ = typing_cancel_tx.send(());
typing_renew_handle.abort();
let typing_stop = queue::TypingEvent {
room_id: room_id_inner,
user_id: ai_typing_id,
username: ai_display_name_for_final.clone(),
avatar_url: None,
action: "stop".to_string(),
sender_type: Some("ai".to_string()),
};
room_manager.broadcast_typing(room_id_inner, typing_stop).await;
let event = ProjectRoomEvent {
event_type: crate::RoomEventType::NewMessage.as_str().into(),
project_id: project_id_inner,
room_id: Some(room_id_inner),
category_id: None,
message_id: Some(streaming_msg_id),
seq: Some(seq),
timestamp: now,
};
queue
.publish_project_room_event(project_id_inner, event)
.await;
}
}
Err(e) => {
tracing::error!(error = %e, "AI streaming failed");
let _ = typing_cancel_tx.send(());
typing_renew_handle.abort();
let typing_stop = queue::TypingEvent {
room_id: room_id_inner,
user_id: ai_typing_id,
username: ai_display_name.clone(),
avatar_url: None,
action: "stop".to_string(),
sender_type: Some("ai".to_string()),
};
room_manager.broadcast_typing(room_id_inner, typing_stop).await;
let event = RoomMessageStreamChunkEvent {
message_id: streaming_msg_id,
room_id: room_id_inner,
seq: 0,
content: String::new(),
done: true,
error: Some(e.to_string()),
display_name: Some(ai_display_name.clone()),
chunk_type: None,
};
room_manager.broadcast_stream_chunk(event).await;
}
}
room_manager.close_stream_channel(streaming_msg_id).await;
});
}