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feat: 添加最终结果处理和调度压缩功能，重构会话管理逻辑以优化代码结构

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This commit is contained in:
ooodc 2026-04-28 10:58:01 +08:00
parent 33f5a4cbd2
commit b2c8d76820
5 changed files with 75 additions and 58 deletions
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35
src/gateway/execution.rs
View File

@ -1,11 +1,13 @@
use std::collections::HashMap;
use std::sync::Arc;
use crate::agent::{AgentError, AgentProcessResult};
use crate::bus::message::ToolMessageState;
use crate::bus::{ChatMessage, OutboundMessage};
use crate::config::LLMProviderConfig;
use tokio::sync::Mutex;
use super::session::Session;
use super::session::{Session, schedule_background_history_compaction};
const SCHEDULED_TASK_EXECUTION_SYSTEM_PROMPT: &str = "系统说明：当前输入来自一次已经触发的定时任务执行。你现在需要执行任务内容本身，而不是创建、修改、恢复、暂停或查询新的定时任务。除非当前任务内容明确要求管理调度器，否则不要调用任何定时任务管理工具；像“每小时”、“每天”、“cron”、“定时”等词，只应视为任务背景，不应再解释为新的建任务请求。";
@ -112,6 +114,37 @@ impl AgentExecutionService {
should_schedule_compaction: true,
})
}
pub(crate) async fn finalize_result_and_schedule_compaction(
&self,
session: Arc<Mutex<Session>>,
request: FinalizeAgentResultRequest<'_>,
) -> Result<Vec<OutboundMessage>, AgentError> {
let channel_name = request.channel_name.to_string();
let chat_id = request.chat_id.to_string();
let execution_kind = request.execution_kind.to_string();
let finalized_result = {
let mut session_guard = session.lock().await;
self.finalize_result(&mut session_guard, request)?
};
if finalized_result.should_schedule_compaction {
if let Err(error) =
schedule_background_history_compaction(session.clone(), chat_id.clone()).await
{
tracing::warn!(
channel = %channel_name,
chat_id = %chat_id,
execution_kind = %execution_kind,
error = %error,
"Failed to schedule background history compaction"
);
}
}
Ok(finalized_result.outbound_messages)
}
}
pub(crate) fn should_display_message_to_user(

92
src/gateway/session.rs
View File

@ -1430,11 +1430,10 @@ impl SessionManager {
let result = agent.process(history).await?;
let finalized_result = {
let mut session_guard = session.lock().await;
let metadata = HashMap::new();
AgentExecutionService::new(self.show_tool_results).finalize_result(
&mut session_guard,
let metadata = HashMap::new();
let outbound_messages = AgentExecutionService::new(self.show_tool_results)
.finalize_result_and_schedule_compaction(
session.clone(),
FinalizeAgentResultRequest {
channel_name,
chat_id,
@ -1444,26 +1443,18 @@ impl SessionManager {
suppress_live_tool_calls: live_emitter.is_some(),
execution_kind: "message",
},
)?
};
if finalized_result.should_schedule_compaction {
if let Err(error) =
schedule_background_history_compaction(session.clone(), chat_id.to_string()).await
{
tracing::warn!(channel = %channel_name, chat_id = %chat_id, error = %error, "Failed to schedule background history compaction");
}
}
)
.await?;
#[cfg(debug_assertions)]
tracing::debug!(
channel = %channel_name,
chat_id = %chat_id,
outbound_count = finalized_result.outbound_messages.len(),
outbound_count = outbound_messages.len(),
"Agent response sequence received"
);
Ok(finalized_result.outbound_messages)
Ok(outbound_messages)
}
pub async fn run_scheduled_agent_task(
@ -1528,10 +1519,9 @@ impl SessionManager {
let result = agent.process(history).await?;
let finalized_result = {
let mut session_guard = session.lock().await;
AgentExecutionService::new(self.show_tool_results).finalize_result(
&mut session_guard,
AgentExecutionService::new(self.show_tool_results)
.finalize_result_and_schedule_compaction(
session.clone(),
FinalizeAgentResultRequest {
channel_name,
chat_id,
@ -1541,18 +1531,8 @@ impl SessionManager {
suppress_live_tool_calls: false,
execution_kind: "scheduled_task",
},
)?
};
if finalized_result.should_schedule_compaction {
if let Err(error) =
schedule_background_history_compaction(session.clone(), chat_id.to_string()).await
{
tracing::warn!(channel = %channel_name, chat_id = %chat_id, error = %error, "Failed to schedule background history compaction for scheduled task");
}
}
Ok(finalized_result.outbound_messages)
)
.await
}
/// 清除指定 session 的所有历史
@ -1725,16 +1705,21 @@ mod tests {
}
async fn start_mock_openai_server() -> String {
async fn handle(Json(body): Json<Value>) -> Json<Value> {
start_mock_openai_server_with_content(None).await
}
async fn start_mock_openai_server_with_content(
mock_response_content: Option<String>,
) -> String {
async fn handle(
axum::extract::State(mock_response_content): axum::extract::State<Option<String>>,
Json(body): Json<Value>,
) -> Json<Value> {
let model = body
.get("model")
.and_then(|value| value.as_str())
.unwrap_or("unknown-model");
let content = body
.get("mock_response_content")
.and_then(|value| value.as_str())
.map(ToString::to_string)
.unwrap_or_else(|| format!("reply from {}", model));
let content = mock_response_content.unwrap_or_else(|| format!("reply from {}", model));
Json(json!({
"id": "mock-response",
@ -1755,7 +1740,9 @@ mod tests {
}))
}
let app = Router::new().route("/chat/completions", post(handle));
let app = Router::new()
.route("/chat/completions", post(handle))
.with_state(mock_response_content);
let listener = TcpListener::bind("127.0.0.1:0").await.unwrap();
let address = listener.local_addr().unwrap();
tokio::spawn(async move {
@ -1778,11 +1765,15 @@ mod tests {
format!("http://{}", address)
}
async fn start_mock_openai_flaky_server() -> String {
async fn start_mock_openai_flaky_server(mock_response_content: String) -> String {
let attempts = StdArc::new(AtomicUsize::new(0));
let state = (attempts, mock_response_content);
async fn handle(
axum::extract::State(attempts): axum::extract::State<StdArc<AtomicUsize>>,
axum::extract::State((attempts, mock_response_content)): axum::extract::State<(
StdArc<AtomicUsize>,
String,
)>,
Json(body): Json<Value>,
) -> (StatusCode, Json<Value>) {
let attempt = attempts.fetch_add(1, Ordering::SeqCst);
@ -1797,11 +1788,6 @@ mod tests {
.get("model")
.and_then(|value| value.as_str())
.unwrap_or("unknown-model");
let content = body
.get("mock_response_content")
.and_then(|value| value.as_str())
.unwrap_or("{\"user_facts\":[],\"preferences\":[],\"behavior_patterns\":[],\"merges\":[],\"conflicts\":[],\"low_value_ids\":[],\"managed_markdown\":\"\"}");
(
StatusCode::OK,
Json(json!({
@ -1810,7 +1796,7 @@ mod tests {
"choices": [
{
"message": {
"content": content,
"content": mock_response_content,
"tool_calls": []
}
}
@ -1826,7 +1812,7 @@ mod tests {
let app = Router::new()
.route("/chat/completions", post(handle))
.with_state(attempts);
.with_state(state);
let listener = TcpListener::bind("127.0.0.1:0").await.unwrap();
let address = listener.local_addr().unwrap();
tokio::spawn(async move {
@ -2012,7 +1998,6 @@ mod tests {
#[tokio::test]
async fn test_summarize_memory_maintenance_for_scope_uses_model_output() {
let base_url = start_mock_openai_server().await;
let mock_response_content = serde_json::to_string(&json!({
"user_facts": ["用户在做AI产品"],
"preferences": ["偏好简洁表达"],
@ -2023,6 +2008,8 @@ mod tests {
"managed_markdown": "### 用户事实\n- 用户在做AI产品\n\n### 用户偏好\n- 偏好简洁表达\n\n### 行为模式\n- 习惯先问方案再要代码"
}))
.unwrap();
let base_url =
start_mock_openai_server_with_content(Some(mock_response_content.clone())).await;
let provider_config = LLMProviderConfig {
provider_type: "openai".to_string(),
@ -2112,7 +2099,6 @@ mod tests {
#[tokio::test]
async fn test_summarize_memory_maintenance_retries_recoverable_provider_errors() {
let base_url = start_mock_openai_flaky_server().await;
let mock_response_content = serde_json::to_string(&json!({
"user_facts": ["用户在做AI产品"],
"preferences": [],
@ -2123,6 +2109,7 @@ mod tests {
"managed_markdown": "### 用户事实\n- 用户在做AI产品"
}))
.unwrap();
let base_url = start_mock_openai_flaky_server(mock_response_content.clone()).await;
let provider_config = LLMProviderConfig {
provider_type: "openai".to_string(),
@ -2182,8 +2169,9 @@ mod tests {
#[tokio::test]
async fn test_summarize_memory_maintenance_for_scope_extracts_wrapped_json_object() {
let base_url = start_mock_openai_server().await;
let mock_response_content = "结果如下：\n```json\n{\n \"user_facts\": [\"用户在做AI产品\"],\n \"preferences\": [],\n \"behavior_patterns\": [],\n \"merges\": [],\n \"conflicts\": [],\n \"low_value_ids\": [],\n \"managed_markdown\": \"### 用户事实\\n- 用户在做AI产品\"\n}\n```\n";
let base_url =
start_mock_openai_server_with_content(Some(mock_response_content.to_string())).await;
let provider_config = LLMProviderConfig {
provider_type: "openai".to_string(),

2
src/gateway/ws.rs
View File

@ -515,7 +515,7 @@ mod tests {
assert_eq!(tool_call_id, "call-1");
assert_eq!(tool_name, "calculator");
assert_eq!(arguments["expression"], "1 + 1");
assert_eq!(content, "### calculator\n- expression: 1 + 1");
assert_eq!(content, "calculator\nargs: {\"expression\":\"1 + 1\"}");
}
other => panic!("unexpected outbound variant: {:?}", other),
}

2
tests/test_integration.rs
View File

@ -25,9 +25,7 @@ fn load_config() -> Option<LLMProviderConfig> {
max_tokens: Some(100),
model_extra: HashMap::new(),
max_tool_iterations: 20,
token_limit: 128_000,
tool_result_max_chars: 20_000,
context_summary_max_chars: 20_000,
context_tool_result_trim_chars: 20_000,
})
}

2
tests/test_tool_calling.rs
View File

@ -25,9 +25,7 @@ fn load_openai_config() -> Option<LLMProviderConfig> {
max_tokens: Some(100),
model_extra: HashMap::new(),
max_tool_iterations: 20,
token_limit: 128_000,
tool_result_max_chars: 20_000,
context_summary_max_chars: 20_000,
context_tool_result_trim_chars: 20_000,
})
}