gitdataai/libs/room/src/service/mod.rs
ZhenYi 93ec515f29 feat(room): batch-embed all room messages into Qdrant on persist
- make_persist_fn now accepts embed_service, collects persisted text messages
- Filters non-text, non-empty, non-system/tool messages
- Groups by room→project_name, batch-embeds via embed_memories_batch
- Removes old per-message synchronous embed_memory call
- Workers thread embed_service through to persist_fn
2026-04-28 13:03:59 +08:00

468 lines
15 KiB
Rust

mod access;
mod ai_common;
mod ai_nonstreaming;
mod ai_react_nonstreaming;
mod ai_react_streaming;
mod ai_streaming;
mod history;
mod mentions;
mod notifications;
mod patterns;
mod sequence;
mod workers;
pub use access::{check_room_access, check_project_member, require_room_member, find_room_or_404};
pub use ai_common::create_and_publish_ai_message;
pub use ai_nonstreaming::process_message_ai_nonstreaming;
pub use ai_react_nonstreaming::process_message_ai_react_nonstreaming;
pub use ai_react_streaming::process_message_ai_react_streaming;
pub use ai_streaming::process_message_ai_streaming;
pub use history::{get_room_history, get_user_names, get_room_ai_config, extract_mention_context};
pub use mentions::extract_mentions;
pub use notifications::{notify_project_members, publish_room_event};
pub use sequence::next_room_message_seq_internal;
pub use workers::{start_workers, spawn_agent_task, spawn_room_workers, PushNotificationFn};
use std::sync::Arc;
use chrono::Utc;
use db::cache::AppCache;
use db::database::AppDatabase;
use models::rooms::room;
use models::rooms::room_ai;
use queue::{MessageProducer, ProjectRoomEvent};
use sea_orm::{ColumnTrait, EntityTrait, QueryFilter};
use uuid::Uuid;
use crate::connection::{RoomConnectionManager, DedupCache};
use crate::error::RoomError;
use agent::chat::{AiRequest, ChatService};
use agent::embed::EmbedService;
use agent::TaskService;
use models::agent_task::AgentType;
use crate::service::patterns::{mention_bracket_re, mention_tag_re};
const DEFAULT_MAX_CONCURRENT_WORKERS: usize = 1024;
#[derive(Clone)]
pub struct RoomService {
pub db: AppDatabase,
pub cache: AppCache,
pub config: config::AppConfig,
pub room_manager: Arc<RoomConnectionManager>,
pub queue: MessageProducer,
pub redis_url: String,
pub chat_service: Option<Arc<ChatService>>,
pub task_service: Option<Arc<TaskService>>,
pub embed_service: Option<Arc<EmbedService>>,
pub push_fn: Option<workers::PushNotificationFn>,
worker_semaphore: Arc<tokio::sync::Semaphore>,
dedup_cache: DedupCache,
}
impl RoomService {
pub fn new(
db: AppDatabase,
cache: AppCache,
config: config::AppConfig,
queue: MessageProducer,
room_manager: Arc<RoomConnectionManager>,
redis_url: String,
chat_service: Option<Arc<ChatService>>,
task_service: Option<Arc<TaskService>>,
max_concurrent_workers: Option<usize>,
push_fn: Option<workers::PushNotificationFn>,
embed_service: Option<Arc<EmbedService>>,
) -> Self {
let dedup_cache: DedupCache =
Arc::new(dashmap::DashMap::with_capacity_and_hasher(10000, Default::default()));
Self {
db,
cache,
config,
room_manager,
queue,
redis_url,
chat_service,
task_service,
embed_service,
worker_semaphore: Arc::new(tokio::sync::Semaphore::new(
max_concurrent_workers.unwrap_or(DEFAULT_MAX_CONCURRENT_WORKERS),
)),
dedup_cache,
push_fn,
}
}
pub async fn start_workers(
&self,
shutdown_rx: tokio::sync::broadcast::Receiver<()>,
) -> anyhow::Result<()> {
workers::start_workers(
self.db.clone(),
self.cache.clone(),
self.room_manager.clone(),
self.queue.clone(),
self.redis_url.clone(),
self.dedup_cache.clone(),
self.task_service.clone(),
None, // max_concurrent_workers handled by semaphore
shutdown_rx,
self.embed_service.clone(),
)
.await
}
pub async fn spawn_agent_task<F, Fut>(
&self,
project_id: Uuid,
agent_type: AgentType,
input: String,
_title: Option<String>,
execute: F,
) -> anyhow::Result<i64>
where
F: FnOnce(i64, Arc<TaskService>) -> Fut + Send + 'static,
Fut: std::future::Future<Output = Result<String, String>> + Send,
{
let task_service = match &self.task_service {
Some(ts) => ts.clone(),
None => return Err(anyhow::anyhow!("task service not configured")),
};
workers::spawn_agent_task(
project_id,
agent_type,
input,
task_service,
self.queue.clone(),
self.room_manager.clone(),
self.worker_semaphore.clone(),
execute,
)
.await
}
pub fn spawn_room_workers(&self, room_id: uuid::Uuid) {
workers::spawn_room_workers(
room_id,
self.db.clone(),
self.room_manager.clone(),
self.queue.clone(),
self.redis_url.clone(),
self.worker_semaphore.clone(),
self.embed_service.clone(),
);
}
pub async fn publish_room_event(
&self,
project_id: uuid::Uuid,
event_type: super::RoomEventType,
room_id: Option<uuid::Uuid>,
category_id: Option<uuid::Uuid>,
message_id: Option<uuid::Uuid>,
seq: Option<i64>,
) {
let event = ProjectRoomEvent {
event_type: event_type.as_str().into(),
project_id,
room_id,
category_id,
message_id,
seq,
timestamp: Utc::now(),
};
self.queue
.publish_project_room_event(project_id, event)
.await;
}
pub fn notify_project_members(
&self,
project_id: uuid::Uuid,
notification_type: super::NotificationType,
title: String,
content: Option<String>,
related_room_id: Option<uuid::Uuid>,
) {
notifications::notify_project_members(
self.db.clone(),
project_id,
notification_type,
title,
content,
related_room_id,
);
}
pub fn extract_mentions(content: &str) -> Vec<Uuid> {
mentions::extract_mentions(content)
}
pub async fn resolve_mentions(&self, content: &str) -> Vec<Uuid> {
use models::users::User;
use sea_orm::EntityTrait;
let mut resolved: Vec<Uuid> = Vec::new();
let mut seen_usernames: Vec<String> = Vec::new();
for cap in mention_bracket_re().captures_iter(content) {
if let (Some(type_m), Some(id_m)) = (cap.get(1), cap.get(2)) {
if type_m.as_str() == "user" {
let id = id_m.as_str().trim();
if let Ok(uuid) = Uuid::parse_str(id) {
if !resolved.contains(&uuid) {
resolved.push(uuid);
}
} else if let Some(label_m) = cap.get(3) {
let label = label_m.as_str().trim();
if !label.is_empty() {
let label_lower = label.to_lowercase();
if seen_usernames.contains(&label_lower) {
continue;
}
seen_usernames.push(label_lower.clone());
if let Some(user) = User::find()
.filter(models::users::user::Column::Username.eq(label_lower))
.one(&self.db)
.await
.ok()
.flatten()
{
if !resolved.contains(&user.uid) {
resolved.push(user.uid);
}
}
}
}
}
}
}
resolved
}
pub async fn check_room_access(&self, room_id: Uuid, user_id: Uuid) -> Result<(), RoomError> {
access::check_room_access(&self.db, room_id, user_id).await
}
pub async fn check_project_member(
&self,
project_id: Uuid,
user_id: Uuid,
) -> Result<(), RoomError> {
access::check_project_member(&self.db, project_id, user_id).await
}
pub async fn should_ai_respond(&self, room_id: Uuid, content: &str) -> Result<bool, RoomError> {
let ai_config = history::get_room_ai_config(&self.db, room_id).await?;
let config = match ai_config {
Some(c) => c,
None => return Ok(false),
};
if !config.use_exact {
return Ok(true);
}
let model_id_str = config.model.to_string();
for cap in mention_bracket_re().captures_iter(content) {
if let (Some(type_m), Some(id_m)) = (cap.get(1), cap.get(2)) {
if type_m.as_str() == "ai" && id_m.as_str().trim() == model_id_str {
return Ok(true);
}
}
}
for cap in mention_tag_re().captures_iter(content) {
if let (Some(type_m), Some(id_m)) = (cap.get(1), cap.get(2)) {
if type_m.as_str() == "ai" && id_m.as_str().trim() == model_id_str {
return Ok(true);
}
}
}
Ok(false)
}
pub async fn get_room_ai_config(
&self,
room_id: Uuid,
) -> Result<Option<room_ai::Model>, RoomError> {
history::get_room_ai_config(&self.db, room_id).await
}
pub async fn get_user_names(
&self,
user_ids: &[Uuid],
) -> std::collections::HashMap<Uuid, String> {
history::get_user_names(&self.db, user_ids).await
}
pub async fn require_room_member(&self, room_id: Uuid, user_id: Uuid) -> Result<(), RoomError> {
access::require_room_member(&self.db, room_id, user_id).await
}
pub async fn find_room_or_404(&self, room_id: Uuid) -> Result<room::Model, RoomError> {
access::find_room_or_404(&self.db, room_id).await
}
pub async fn process_message_ai(
&self,
room_id: Uuid,
_message_id: Uuid,
sender_id: Uuid,
content: String,
) -> Result<(), RoomError> {
let Some(chat_service) = &self.chat_service else {
return Ok(());
};
let Some(ai_config) = self.get_room_ai_config(room_id).await? else {
return Ok(());
};
let Some(lock_guard) =
crate::room_ai_queue::acquire_room_ai_lock(&self.cache, room_id).await?
else {
return Ok(());
};
let room = self.find_room_or_404(room_id).await?;
let project = models::projects::project::Entity::find_by_id(room.project)
.one(&self.db)
.await?
.ok_or_else(|| RoomError::NotFound("Project not found".to_string()))?;
let mentioned_model_id = {
let mut found = None;
for cap in mention_bracket_re().captures_iter(&content) {
if let (Some(type_m), Some(id_m)) = (cap.get(1), cap.get(2)) {
if type_m.as_str() == "ai" {
if let Ok(uuid) = Uuid::parse_str(id_m.as_str().trim()) {
found = Some(uuid);
break;
}
}
}
}
found
};
let model_id = mentioned_model_id.unwrap_or(ai_config.model);
let model = models::agents::model::Entity::find_by_id(model_id)
.one(&self.db)
.await?
.ok_or_else(|| RoomError::NotFound("AI model not found".to_string()))?;
let sender = models::users::User::find_by_id(sender_id)
.one(&self.db)
.await?
.ok_or_else(|| RoomError::NotFound("Sender not found".to_string()))?;
let history = history::get_room_history(&self.db, room_id, 50).await?;
let user_ids: Vec<Uuid> = history
.iter()
.filter_map(|m| m.sender_id)
.chain(std::iter::once(sender_id))
.collect();
let user_names = self.get_user_names(&user_ids).await;
let mentions = history::extract_mention_context(&self.db, room.project, &content).await;
let request = AiRequest {
db: self.db.clone(),
cache: self.cache.clone(),
config: self.config.clone(),
model,
project: project.clone(),
sender,
room: room.clone(),
input: content,
mention: mentions,
history,
user_names,
temperature: ai_config.temperature.unwrap_or(0.7),
max_tokens: ai_config.max_tokens.unwrap_or(4096) as i32,
top_p: 1.0,
frequency_penalty: 0.0,
presence_penalty: 0.0,
think: ai_config.think,
tools: Some(chat_service.tools()),
max_tool_depth: 1000,
};
let use_streaming = ai_config.stream;
let is_react = ai_config.agent_type.as_deref() == Some("react");
if is_react {
if use_streaming {
ai_react_streaming::process_message_ai_react_streaming(
chat_service.clone(),
request,
room_id,
room.project,
model_id,
lock_guard,
self.db.clone(),
self.cache.clone(),
self.queue.clone(),
self.room_manager.clone(),
)
.await;
} else {
ai_react_nonstreaming::process_message_ai_react_nonstreaming(
chat_service.clone(),
request,
room_id,
room.project,
model_id,
lock_guard,
self.db.clone(),
self.cache.clone(),
self.queue.clone(),
self.room_manager.clone(),
)
.await;
}
} else if use_streaming {
ai_streaming::process_message_ai_streaming(
chat_service.clone(),
request,
room_id,
room.project,
model_id,
lock_guard,
self.db.clone(),
self.cache.clone(),
self.queue.clone(),
self.room_manager.clone(),
)
.await;
} else {
ai_nonstreaming::process_message_ai_nonstreaming(
chat_service.clone(),
request,
room_id,
room.project,
model_id,
lock_guard,
self.db.clone(),
self.cache.clone(),
self.queue.clone(),
self.room_manager.clone(),
)
.await;
}
Ok(())
}
}