qzl
e80a82bef4
- 更新 http-error-codes, user-points-chat-data-protocol - 更新 divination-run-protocol, profile-protocol - 删除废弃的后端和前端设计计划文档
201 lines
6.5 KiB
Markdown
201 lines
6.5 KiB
Markdown
# Bug: 追问时 agent_output 被重新生成，导致 sign_level 被覆盖
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日期：2026-04-08
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状态：已确认根因（未修复）
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## 问题描述
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首次解卦完成后，用户继续追问时，agent 会重新生成 `agent_output`，重新计算卦的结论和标签。
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**具体表现**：
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- 首次解卦结论：`中下签`
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- 追问后结论：`下下签`（同一个卦，结果被重新生成）
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## 根因分析
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**问题定位**：`backend/src/core/agentscope/runtime/runner.py`
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### 根因链条
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1. **`runner.py:execute()` 方法（第 70-133 行）**
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无论 `runtime_mode` 是 `chat` 还是 `follow_up`，都会执行以下逻辑：
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```python
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# 第 105-119 行：始终推导卦象
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derived_divination = self._resolve_derived_divination(run_input=run_input)
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await self._emit_step_event(
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pipeline=pipeline,
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run_input=run_input,
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step_name="divination",
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event_type="DIVINATION_DERIVED", # <-- 追问时不应发射此事件
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...
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)
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```
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2. **`runner.py:_execute_worker_step()` 方法（第 200-245 行）**
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始终将 `derived_divination` 传递给 worker：
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```python
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# 第 294-302 行：始终将 divination_derived 放入 worker_output
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await emitter.emit_final_text_end(
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worker_output={
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**worker_payload.model_dump(mode="json", exclude_none=True),
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"divination_derived": derived_divination.model_dump(...), # <-- 追问时不应包含
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},
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...
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)
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```
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3. **`stage_emitter.py:emit_final_text_end()` 方法（第 46-73 行）**
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始终将所有字段放入 `TEXT_MESSAGE_END` 事件：
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```python
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payload = {
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"messageId": message_id,
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"role": "assistant",
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"stage": self._stage,
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"status": worker_output.get("status"),
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"sign_level": worker_output.get("sign_level"), # <-- 追问时不应有
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"conclusion": worker_output.get("conclusion", []), # <-- 追问时不应有
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"focus_points": worker_output.get("focus_points", []),
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"advice": worker_output.get("advice", []),
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"keywords": worker_output.get("keywords", []),
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"answer": worker_output.get("answer", ""),
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"error": worker_output.get("error"),
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"divination_derived": worker_output.get("divination_derived"), # <-- 追问时不应有
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...
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}
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```
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4. **`store.py:_persist_text_message()` 方法（第 125-160 行）**
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从事件中提取所有字段并完整存储：
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```python
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worker_output_fields = (
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"status",
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"sign_level", # <-- 追问时被重新生成并覆盖
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"conclusion", # <-- 追问时被重新生成并覆盖
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"focus_points",
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"advice",
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"keywords",
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"answer",
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"error",
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"divination_derived", # <-- 追问时被重新生成
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"ui_hints",
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)
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```
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### 问题本质
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`runtime_mode=follow_up` 时，系统仍在：
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1. 重新推导卦象（调用 `_resolve_derived_divination`）
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2. 发射完整的 `DIVINATION_DERIVED` 事件
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3. 生成包含所有结构化字段的 `worker_output`
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4. 将所有字段存储到数据库
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但根据工程计划（`docs/plans/2026-04-08-followup-session-history-eng-plan.md:37-40`），追问时的预期行为是：
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```
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[一次追问]
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user -> /agent/runs(runtime_mode=follow_up)
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-> assistant(content [+ optional metadata.agent_output.answer])
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```
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即：追问时只输出 `answer`（内容），不重新生成卦象结构。
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## 证据
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### 数据库证据
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Session `015fe0f9-0500-43ab-911a-4ce8e3160032`：
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| 时间 | 角色 | sign_level | divination_derived | 问题 |
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|------|------|------------|-------------------|------|
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| 05:21:19 | user | - | - | 首问问题 |
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| 05:21:28 | assistant | 中下签 | 完整 | 首答（正确） |
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| 05:22:24 | user | - | - | 追问 |
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| 05:22:33 | assistant | **下下签** | 完整 | 追问答（sign_level 被重新生成） |
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两个 assistant 消息的 `divination_derived` 完全相同，但 `sign_level` 不同，证明是重新生成的。
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## 修复方向
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### 1. `runner.py`
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在 `execute()` 方法中，根据 `runtime_mode` 决定是否推导卦象：
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```python
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async def execute(self, ...):
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runtime_mode = self._resolve_runtime_mode(run_input=run_input)
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if runtime_mode == RuntimeMode.CHAT:
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derived_divination = self._resolve_derived_divination(run_input=run_input)
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await self._emit_step_event(...) # DIVINATION_DERIVED
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else:
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derived_divination = None # follow_up 不推导
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```
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### 2. `stage_emitter.py`
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`emit_final_text_end()` 根据 `runtime_mode` 决定发送哪些字段：
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```python
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async def emit_final_text_end(self, ..., runtime_mode: str):
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payload = {"messageId": ..., "role": "assistant", "stage": self._stage}
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if runtime_mode == "chat":
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payload.update({
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"status": worker_output.get("status"),
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"sign_level": worker_output.get("sign_level"),
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"conclusion": worker_output.get("conclusion", []),
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"focus_points": worker_output.get("focus_points", []),
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"advice": worker_output.get("advice", []),
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"keywords": worker_output.get("keywords", []),
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"divination_derived": worker_output.get("divination_derived"),
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...
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})
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else: # follow_up
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payload["answer"] = worker_output.get("answer", "")
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```
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### 3. `store.py`
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`_persist_text_message()` 根据 `runtime_mode` 决定提取哪些字段：
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```python
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async def _persist_text_message(self, ...):
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runtime_mode = self._resolve_runtime_mode(event=event)
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if runtime_mode == "chat":
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worker_output_fields = ("status", "sign_level", "conclusion", ...)
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else: # follow_up
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worker_output_fields = ("answer",) # 只存储 answer
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```
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### 4. `runtime_models.py`
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`resolve_worker_output_model()` 应根据 `runtime_mode` 返回不同 schema：
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```python
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def resolve_worker_output_model(runtime_mode: RuntimeMode = RuntimeMode.CHAT) -> type[WorkerAgentOutputLite]:
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if runtime_mode == RuntimeMode.FOLLOW_UP:
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return WorkerAgentOutputLite # 只有 answer
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return AgentOutput # 完整结构（继承自 WorkerAgentOutputRich）
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```
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## 相关文件
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- `backend/src/core/agentscope/runtime/runner.py` - 主编排逻辑
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- `backend/src/core/agentscope/runtime/stage_emitter.py` - 事件发射
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- `backend/src/core/agentscope/events/store.py` - 事件持久化
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- `backend/src/schemas/agent/runtime_models.py` - 输出 schema 定义
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## 相关文档
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- 工程计划：`docs/plans/2026-04-08-followup-session-history-eng-plan.md`
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- 协议文档：`docs/protocols/divination/divination-run-protocol.md`
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