docs(agent): add Task2/Task3 architecture and implementation artifacts

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zl-q
2026-03-08 16:03:02 +08:00
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# Agent 模块审查报告 - 工具架构
**日期**: 2026-03-08
**范围**: `backend/src/core/agent`
**状态**: 待评估
---
## 🟡 MEDIUM - 工具架构问题
### 1. 未使用 CrewAI 工具模块,工具硬编码
**文件**:
- `application/run_service.py:406` - `_execute_backend_tool()`
- `infrastructure/crewai/runtime.py` - 三阶段流程
**问题**:
当前 agent 只使用了 CrewAI 的 **agent/task 配置模板**YAML),但**没有使用 CrewAI 的工具系统**:
```
已用到:
├── agents.yaml (agent 角色定义)
└── tasks.yaml (task 定义)
未用到:
├── @tool 装饰器
├── BaseTool 类
└── Tools 工具注册表
```
**当前实现**
```python
# run_service.py:406
async def _execute_backend_tool(self, *, tool_name, tool_args, ...):
if tool_name != "create_calendar_event": # 硬编码判断
raise ValueError(f"unsupported backend tool: {tool_name}")
# 手动执行工具...
```
**影响**:
1. 每新增一个工具需要修改 `_execute_backend_tool()` 代码
2. 无法利用 CrewAI 的工具选择、执行结果处理等能力
3. 与 CrewAI 集成度低,无法发挥框架优势
4. 无法将工具描述等prompt信息自动注入agent中
---
## 🟡 MEDIUM - 工具结果存储问题
### 2. 工具结果存储到对象存储的功能未启用
**文件**:
- `application/session_state_persistence.py:52` - `persist_tool_result_payload()`
- `models/agent_chat_message.py` - messages 表
**问题**:
已定义 `persist_tool_result_payload()` 函数,可将工具结果上传到对象存储(MinIO/Supabase Storage),但**该函数未被调用**。
当前实现:
- 工具结果直接存在数据库 `messages.content` 字段
- `metadata_json` 中定义了 `storage_bucket`, `storage_path` 等字段,但都是 `None`
```python
# message_metadata.py:17-27
class MessageMetadataToolResult(BaseModel):
storage_bucket: str | None = None # 当前未使用
storage_path: str | None = None # 当前未使用
payload_sha256: str | None = None # 当前未使用
```
**影响**:
1. 工具结果(尤其是 UI 组件等大数据)存在数据库,增加 DB 负担
2. 已定义的存储接口未被使用,代码冗余
3. 无法利用对象存储的 CDN 加速和带宽优势
---
## 🟡 MEDIUM - 工具输出格式问题
### 3. 工具输出不是 UI Schema,前端无法直接渲染
**文件**:
- `application/run_service.py:456-479` - `_execute_backend_tool()`
**问题**:
当前 `create_calendar_event` 工具返回的是**非结构化文本**,不是前端可渲染的 UI Schema:
```python
# run_service.py:456-479
event_id = str(schedule_item.id)
ui_card = {
"type": "calendar_card.v1",
"version": "v1",
"data": {...}
"actions": [...]
}
# ui_card 构建了但没有作为 tool result 返回
return {"status": "ok", "event_id": event_id} # 只返回了简单结构
```
**当前输出**
```json
{
"status": "ok",
"event_id": "xxx"
}
```
**期望输出**UI Schema):
```json
{
"type": "calendar_card.v1",
"version": "v1",
"data": {
"id": "xxx",
"title": "会议",
"startAt": "2026-03-08T15:00:00Z",
...
},
"actions": [
{"type": "link", "label": "查看详情", "target": "/calendar/events/xxx"}
]
}
```
**影响**:
1. 前端无法直接渲染丰富的 UI 组件
2. 需要前端手动解析文本再渲染,增加前端工作量
3. 无法利用 AG-UI 协议的 `ui_schema` 能力
---
## 🟡 MEDIUM - 阶段配置问题
### 4. 三阶段流程参数硬编码,无法为每个阶段配置不同策略
**文件**:
- `infrastructure/crewai/runtime.py:190-277` - `CrewAIRuntime.execute()`
**问题**:
当前三阶段流程(intent → execution → organization)是硬编码在 `run_agent_task()` 中的,无法为每个阶段配置不同的参数,如每个阶段可以使用的工具:
```python
# runtime.py:203-277
# intent 阶段
intent_text, intent_usage = _run_stage(
litellm_model=litellm_model,
api_key=...,
llm_config=self._llm_config, # 同一套配置
stage="intent",
...
)
# execution 阶段(如果有)
execution_text, execution_usage = _run_stage(
litellm_model=litellm_model,
api_key=...,
llm_config=self._llm_config, # 同一套配置
stage="execution",
...
)
# organization 阶段
organization_text, organization_usage = _run_stage(
litellm_model=litellm_model,
api_key=...,
llm_config=self._llm_config, # 同一套配置
stage="organization",
...
)
```
**当前限制**
1. 无法为 intent 阶段设置只读 LLM(不允许工具调用)
**影响**:
1. 无法精细控制每个阶段的 LLM 行为
2. 意图识别阶段可能误触发工具调用
3. 增加不必要的 LLM 调用成本
4. 降低了架构的灵活性
---
## 🔴 HIGH - Agent Loop 断裂问题
### 5. 工具审批后未继续 Agent Loop
**文件**:
- `application/resume_service.py:121-158`
**问题**:
前端审批工具调用后,后端返回 tool result,但**没有继续执行 agent loop**,直接标记 session 为 COMPLETED 结束。
当前流程:
```python
# resume_service.py:121-127
snapshot = self._state_persistence.build_completed_snapshot()
await session_repository.update_runtime_state(
chat_session=chat_session,
status=AgentChatSessionStatus.COMPLETED, # 直接完成
state_snapshot=snapshot,
...
)
```
缺失的流程:
```
1. 接收 tool result
2. 将 tool result 作为 message 存入上下文
3. 再次调用 LLM(带 tool result
4. 生成最终回复
5. 标记为 COMPLETED
```
**影响**:
1. 用户审批工具后,agent 不会继续生成回复
2. 整个 agent loop 在工具审批后断裂
3. 用户体验不完整
---
## 🔴 HIGH - 对话历史和用户上下文架构错误
### 6. 对话历史由前端维护,违反后端架构设计
**文件**:
- `application/run_service.py:89-124`
- `domain/agui_input.py`
**问题**:
当前架构中,**对话历史完全由前端维护并传递**:
```
前端 → GET /runs/{thread_id}/history → 后端返回历史 messages
前端 → POST /runs/{thread_id}/run → 前端把 history 放入 run_input.messages 传给后端
后端 → 只读取 run_input 中的最新 user_input,不读取数据库历史
```
代码证据 (`run_service.py:89-124`)
```python
async def run(self, *, run_input: RunAgentInput):
user_input = extract_latest_user_text(run_input) # 只取最新用户消息
runtime_result = await asyncio.to_thread(
runtime.execute,
user_input=user_input, # 只传最新输入
system_prompt=system_prompt,
)
```
**影响**:
1. **高危安全风险**:前端可以篡改对话历史,伪造上下文
2. **架构违反**:用户上下文和对话历史都应该由后端维护
3. **数据不一致**:前端可能遗漏或错误处理历史消息
4. **无法支持多端同步**:不同前端设备看到的历史可能不同
5. **Token 浪费**:每次请求都要传递完整历史,增加请求体积
6. 原来的计划文档写清楚了,后端通过redis来缓存对话历史,并结合数据库读取的回退策略
---
## 🟡 MEDIUM - 多模态输入支持问题
### 7. 不支持图片等多模态输入
**文件**:
- `domain/agui_input.py:64-86` - `extract_latest_user_text()`
- `infrastructure/crewai/runtime.py:121-136` - `_run_stage()`
- `infrastructure/litellm/client.py`
**问题**:
当前架构**只支持纯文本输入**,图片等多模态内容被丢弃:
代码证据 (`agui_input.py:64-86`)
```python
def extract_latest_user_text(run_input: RunAgentInput) -> str:
if isinstance(content, list):
for item in content:
if getattr(item, "type", None) != "text":
continue # ❌ 跳过非 text 类型(图片被丢弃)
```
代码证据 (`runtime.py:125`)
```python
messages.append({"role": "user", "content": user_content}) # 只传 str
```
**影响**:
1. 用户无法发送图片进行多模态交互
2. 浪费多模态 LLM 能力
3. 无法实现"上传图片让 AI 分析"等场景
---
## 🟡 MEDIUM - 缺失语音识别 (ASR) 功能
### 8. 未实现 fun-asr-realtime 语音识别 API 相关路由
**文件**:
- 无(功能缺失)
**问题**:
后端**未实现语音识别功能**,无法处理前端传入的音频数据:
当前状态:
- `dashscope` 只用于 LLMqwen3.5-flash 等)
- 没有任何 fun-asr、ASR、audio、transcribe 相关代码
- v1 路由中无语音/音频相关 API
**影响**:
1. 用户无法发送语音消息
2. 无法实现实时语音对话场景
3. 需要前端自行完成 ASR,增大前端负担
---
@@ -0,0 +1,207 @@
# Agent Tool Architecture Design
**Date:** 2026-03-08
**Source:** `docs/bugs/2026-03-08-agent-tool-architecture.md`
**Scope:** `backend/src/core/agent`
**Status:** Approved for planning
---
## 1. Objective
修复 Agent 工具架构相关 8 个问题,优先恢复端到端闭环能力(工具审批后继续推理并产出最终回复),并在同版本内补齐工具输出结构化、存储分层、阶段策略解耦、多模态与语音输入能力。
---
## 2. Deliverables
1. 两阶段修复蓝图(Phase 1 + Phase 2
2. 统一事件与状态机设计(AG-UI Step 事件 + 审批恢复)
3. 接口边界与职责重划分(run/resume/runtime/persistence
4. 风险与回滚策略
5. 验收标准(双金路径)
---
## 3. Constraints And Decisions
### 3.1 Release Strategy
- 一次性切换
- 不做灰度
- 不做双轨
- 不留兼容代码
### 3.2 Contract Decisions
- `run` 接口允许破坏性变更:移除前端传完整历史 `messages` 的语义
- 前端只传本次输入,历史以后端为准
- Phase 1 不引入 client hint
- 工具架构在 Phase 1 完整迁移至 CrewAI Tools(非桥接)
### 3.3 AG-UI Event Decisions
- 三阶段固定发 `StepStarted/StepFinished``intent`, `execution`, `organization`
- 等待工具审批不单独新增 step,归属 execution 内部状态
- 后端只发英文机器名,前端自行文案化
### 3.4 ASR / Multimodal Decisions
- 多模态首版只支持文件上传(不支持 URL)
- ASR 首版为“录音结束后上传音频 -> 后端同步返回 transcript”
- 前端将 transcript 回填输入框,再调用 run
---
## 4. Complexity And Risk
- **Complexity:** S2(跨多个核心模块的架构调整)
- **Risk Tier:** L2(包含高危安全项:前端可篡改历史)
风险驱动原则:先修复闭环与安全问题,再扩展能力面。
---
## 5. Phased Plan
## Phase 1 - Close Loop And Stop Security Bleeding
**Bugs:** #1, #5, #6
### Goals
1. 后端成为历史与上下文唯一事实源
2. 工具审批后恢复并继续 Agent Loop
3. 工具执行完整迁移到 CrewAI Tools 注册体系
### Module Boundaries
- `backend/src/core/agent/application/run_service.py`
- 仅负责本次输入解析、后端上下文组装、触发 runtime
- 移除前端历史信任路径
- 移除硬编码工具分发
- `backend/src/core/agent/application/resume_service.py`
- 审批确认后触发异步续跑,立即返回 `accepted`
- 不可在工具执行后直接置 `COMPLETED`
- 增加 `approval_request_id` 幂等保护
- `backend/src/core/agent/infrastructure/crewai/runtime.py`
- 引入 CrewAI Tools 注册与注入
- 按 agent/stage 装配工具集
- 三阶段统一发 Step start/end 事件
- `backend/src/core/agent/application/session_state_persistence.py`
- 保障审批状态、工具结果、续跑状态一致性落库
- 为 Phase 2 元数据扩展保留一致接口
### Runtime Flow (Phase 1)
1. `run` 接收本次输入
2. 后端读取 Redis/DB 重建历史
3. 进入 intent/execution/organization 三阶段
4. execution 中若触发工具审批:进入 `WAITING_APPROVAL`
5. 前端审批后调用 `resume`
6. `resume` 异步触发续跑:执行工具 -> 写 tool result -> 继续 loop
7. 生成最终 assistant 回复并 `RunFinished`
---
## Phase 2 - Capability Completion In Same Version
**Order:** #3 -> #2 -> #4 -> #7 -> #8
### #3 Tool Output As UI Schema v1
- 统一工具输出结构:`type/version/data/actions`
- 单一版本 `v1`,短期不做多版本并行
### #2 Tool Result Object Storage
- 大 payload 存对象存储
- DB 仅存摘要、索引、校验信息
- 启用 `storage_bucket/storage_path/payload_sha256`
### #4 Stage-Level Strategy Decoupling
- intent/execution/organization 支持独立参数与工具策略
- intent 阶段可配置为只读(禁工具)
### #7 Multimodal Input
- 首版支持图片文件上传输入
- 不再丢弃非 text 内容
### #8 ASR API
- 新增语音转写 API(同步返回 transcript
- 语音转写与 agent run 解耦
---
## 6. Session State And Events
推荐状态机:
`RUNNING -> WAITING_APPROVAL -> RESUMING -> RUNNING -> COMPLETED/FAILED`
关键约束:
- 重复审批请求不得重复执行工具(幂等)
- `COMPLETED` 仅在 loop 自然结束时设置
- Step 事件覆盖三阶段完整生命周期
---
## 7. Acceptance Criteria
## 7.1 Golden Path A (No Tool)
用户输入后,完整经历三阶段并产出最终回复;前端收到完整 step 事件与 `RunFinished`
## 7.2 Golden Path B (Tool + Approval + Resume)
用户触发工具调用,审批后系统异步续跑并最终产出 assistant 回复;会话不在审批后直接结束。
## 7.3 Security Validation
前端即使提交伪造历史字段,也不会影响后端实际上下文。
## 7.4 Event Validation
每轮 run 必须包含 `intent/execution/organization``StepStarted/StepFinished`
---
## 8. Risk And Rollback
### High Risk: #6 Context Ownership Migration
- 风险:上下文错绑、历史缺失
- 控制:会话归属校验 + Redis/DB 一致性读取
- 回滚:可退到“后端 DB-only 历史重建”
### High Risk: #5 Async Resume Consistency
- 风险:重复审批、状态卡死
- 控制:审批幂等键 + 状态跃迁约束 + 超时终态
- 回滚:降级为“仅返回工具结果,不自动续跑”
### Medium Risk: #2 Storage Split Consistency
- 风险:对象存储与 DB 元数据不一致
- 控制:先对象后元数据 + 失败补偿清理
- 回滚:临时退回 DB 内联存储
---
## 9. Bug-To-Phase Mapping
- **Phase 1:** #1, #5, #6
- **Phase 2:** #2, #3, #4, #7, #8
---
## 10. Next Step
进入 implementation planning:将本设计拆解为任务级可执行计划(文件、测试、命令、验收证据)。
@@ -0,0 +1,447 @@
# Agent Tool Architecture Implementation Plan
> **For Claude:** REQUIRED SUB-SKILL: Use superpowers:executing-plans to implement this plan task-by-task.
**Goal:** 修复 agent 工具架构 8 个问题,先恢复端到端闭环与安全正确性,再补齐 UI Schema、对象存储、阶段解耦、多模态与 ASR。
**Architecture:** 采用两阶段落地。Phase 1 先完成后端上下文主控、CrewAI Tools 完整迁移、审批后异步续跑闭环;Phase 2 按 `#3 -> #2 -> #4 -> #7 -> #8` 逐项扩展能力。所有变更遵循 AG-UI 事件流语义,三阶段固定发送 StepStarted/StepFinished。
**Tech Stack:** FastAPI, Pydantic, CrewAI, LiteLLM, Redis, Postgres, MinIO/Supabase Storage, pytest
---
### Task 1: 锁定 Phase 1 契约(移除前端历史语义)
**Files:**
- Modify: `backend/src/core/agent/domain/agui_input.py`
- Modify: `backend/src/core/agent/application/run_service.py`
- Modify: `backend/src/v1/agent/schemas.py`
- Test: `backend/tests/unit/core/agent/test_run_resume_service.py`
**Step 1: Write the failing test**
```python
def test_run_ignores_client_history_messages(fake_run_input_with_messages):
result = service.run(run_input=fake_run_input_with_messages)
assert result.used_context_source == "backend"
```
**Step 2: Run test to verify it fails**
Run: `cd backend && uv run pytest tests/unit/core/agent/test_run_resume_service.py -k ignores_client_history -v`
Expected: FAIL,当前实现仍读取/依赖前端 history。
**Step 3: Write minimal implementation**
```python
# run_service.py
user_input = extract_latest_user_text(run_input)
history = await load_context_from_backend_sources(session_id)
```
**Step 4: Run test to verify it passes**
Run: `cd backend && uv run pytest tests/unit/core/agent/test_run_resume_service.py -k ignores_client_history -v`
Expected: PASS
**Step 5: Commit**
```bash
git add backend/src/core/agent/domain/agui_input.py backend/src/core/agent/application/run_service.py backend/src/v1/agent/schemas.py backend/tests/unit/core/agent/test_run_resume_service.py
git commit -m "refactor(agent): make backend own conversation context"
```
### Task 2: CrewAI Tools 完整迁移(替换硬编码分发)
**Files:**
- Create: `backend/src/core/agent/infrastructure/crewai/tools_registry.py`
- Create: `backend/src/core/agent/infrastructure/crewai/tools/create_calendar_event_tool.py`
- Modify: `backend/src/core/agent/infrastructure/crewai/runtime.py`
- Modify: `backend/src/core/agent/application/run_service.py`
- Test: `backend/tests/unit/core/agent/test_crewai_runtime.py`
**Step 1: Write the failing test**
```python
def test_runtime_uses_registered_crewai_tools():
runtime = build_runtime_with_registry(["create_calendar_event"])
result = runtime.execute(user_input="帮我创建日历事件", system_prompt="x")
assert result.tool_calls[0].tool_name == "create_calendar_event"
```
**Step 2: Run test to verify it fails**
Run: `cd backend && uv run pytest tests/unit/core/agent/test_crewai_runtime.py -k registered_crewai_tools -v`
Expected: FAIL,当前路径仍是 run_service 硬编码。
**Step 3: Write minimal implementation**
```python
# tools_registry.py
TOOLS = {"create_calendar_event": CreateCalendarEventTool()}
def tools_for_stage(stage: str) -> list[BaseTool]:
return STAGE_TOOL_MAP.get(stage, [])
```
**Step 4: Run test to verify it passes**
Run: `cd backend && uv run pytest tests/unit/core/agent/test_crewai_runtime.py -k registered_crewai_tools -v`
Expected: PASS
**Step 5: Commit**
```bash
git add backend/src/core/agent/infrastructure/crewai/tools_registry.py backend/src/core/agent/infrastructure/crewai/tools/create_calendar_event_tool.py backend/src/core/agent/infrastructure/crewai/runtime.py backend/src/core/agent/application/run_service.py backend/tests/unit/core/agent/test_crewai_runtime.py
git commit -m "feat(agent): migrate backend tools to crewai tool registry"
```
### Task 3: 修复审批后异步续跑闭环(#5)
**Files:**
- Modify: `backend/src/core/agent/application/resume_service.py`
- Modify: `backend/src/core/agent/infrastructure/queue/tasks.py`
- Modify: `backend/src/core/agent/application/session_state_persistence.py`
- Test: `backend/tests/integration/core/agent/test_queue_run_resume.py`
**Step 1: Write the failing test**
```python
def test_resume_triggers_async_loop_until_final_assistant_message(client):
response = client.post("/v1/agent/runs/{id}/resume", json={"approve": True})
assert response.status_code == 202
assert eventually_has_final_assistant_message(id)
```
**Step 2: Run test to verify it fails**
Run: `cd backend && uv run pytest tests/integration/core/agent/test_queue_run_resume.py -k triggers_async_loop -v`
Expected: FAIL,当前审批后直接完成。
**Step 3: Write minimal implementation**
```python
# resume_service.py
await mark_session_resuming(...)
await enqueue_resume_task(...)
return ResumeAccepted(...)
```
**Step 4: Run test to verify it passes**
Run: `cd backend && uv run pytest tests/integration/core/agent/test_queue_run_resume.py -k triggers_async_loop -v`
Expected: PASS
**Step 5: Commit**
```bash
git add backend/src/core/agent/application/resume_service.py backend/src/core/agent/infrastructure/queue/tasks.py backend/src/core/agent/application/session_state_persistence.py backend/tests/integration/core/agent/test_queue_run_resume.py
git commit -m "fix(agent): continue agent loop asynchronously after tool approval"
```
### Task 4: 三阶段 Step 事件完整化(intent/execution/organization
**Files:**
- Modify: `backend/src/core/agent/infrastructure/crewai/runtime.py`
- Modify: `backend/src/core/agent/infrastructure/agui/bridge.py`
- Test: `backend/tests/unit/core/agent/test_agui_bridge.py`
- Test: `backend/tests/integration/v1/agent/test_sse_flow_live.py`
**Step 1: Write the failing test**
```python
def test_each_stage_emits_step_started_and_finished():
events = collect_events_from_run(...)
assert has_step_pair(events, "intent")
assert has_step_pair(events, "execution")
assert has_step_pair(events, "organization")
```
**Step 2: Run test to verify it fails**
Run: `cd backend && uv run pytest tests/integration/v1/agent/test_sse_flow_live.py -k emits_step_started_and_finished -v`
Expected: FAIL,至少一个阶段事件缺失。
**Step 3: Write minimal implementation**
```python
emit_step_started(stage)
stage_output = run_stage(stage)
emit_step_finished(stage)
```
**Step 4: Run test to verify it passes**
Run: `cd backend && uv run pytest tests/integration/v1/agent/test_sse_flow_live.py -k emits_step_started_and_finished -v`
Expected: PASS
**Step 5: Commit**
```bash
git add backend/src/core/agent/infrastructure/crewai/runtime.py backend/src/core/agent/infrastructure/agui/bridge.py backend/tests/unit/core/agent/test_agui_bridge.py backend/tests/integration/v1/agent/test_sse_flow_live.py
git commit -m "feat(agent): emit ag-ui step events for three-stage flow"
```
### Task 5: 工具输出统一为 UI Schema v1#3
**Files:**
- Modify: `backend/src/core/agent/infrastructure/crewai/tools/create_calendar_event_tool.py`
- Modify: `backend/src/core/agent/domain/message_metadata.py`
- Test: `backend/tests/unit/core/agent/test_run_resume_service.py`
**Step 1: Write the failing test**
```python
def test_calendar_tool_returns_ui_schema_v1():
result = run_calendar_tool(...)
assert result["type"] == "calendar_card.v1"
assert result["version"] == "v1"
```
**Step 2: Run test to verify it fails**
Run: `cd backend && uv run pytest tests/unit/core/agent/test_run_resume_service.py -k returns_ui_schema_v1 -v`
Expected: FAIL,当前返回简单 status/event_id。
**Step 3: Write minimal implementation**
```python
return {
"type": "calendar_card.v1",
"version": "v1",
"data": {...},
"actions": [...],
}
```
**Step 4: Run test to verify it passes**
Run: `cd backend && uv run pytest tests/unit/core/agent/test_run_resume_service.py -k returns_ui_schema_v1 -v`
Expected: PASS
**Step 5: Commit**
```bash
git add backend/src/core/agent/infrastructure/crewai/tools/create_calendar_event_tool.py backend/src/core/agent/domain/message_metadata.py backend/tests/unit/core/agent/test_run_resume_service.py
git commit -m "feat(agent): return tool results as ui schema v1"
```
### Task 6: 工具结果对象存储(#2)
**Files:**
- Modify: `backend/src/core/agent/application/session_state_persistence.py`
- Modify: `backend/src/core/agent/domain/message_metadata.py`
- Test: `backend/tests/integration/core/agent/test_session_message_persistence.py`
**Step 1: Write the failing test**
```python
def test_large_tool_payload_persisted_to_object_storage():
meta = persist_large_tool_result(...)
assert meta.storage_bucket is not None
assert meta.storage_path is not None
```
**Step 2: Run test to verify it fails**
Run: `cd backend && uv run pytest tests/integration/core/agent/test_session_message_persistence.py -k object_storage -v`
Expected: FAIL,当前 metadata 为空。
**Step 3: Write minimal implementation**
```python
payload_ref = await persist_tool_result_payload(...)
metadata.storage_bucket = payload_ref.bucket
metadata.storage_path = payload_ref.path
metadata.payload_sha256 = payload_ref.sha256
```
**Step 4: Run test to verify it passes**
Run: `cd backend && uv run pytest tests/integration/core/agent/test_session_message_persistence.py -k object_storage -v`
Expected: PASS
**Step 5: Commit**
```bash
git add backend/src/core/agent/application/session_state_persistence.py backend/src/core/agent/domain/message_metadata.py backend/tests/integration/core/agent/test_session_message_persistence.py
git commit -m "feat(agent): persist large tool results to object storage"
```
### Task 7: 三阶段参数解耦(#4
**Files:**
- Modify: `backend/src/core/agent/infrastructure/crewai/runtime.py`
- Modify: `backend/src/core/agent/infrastructure/config/resolver.py`
- Test: `backend/tests/unit/core/agent/test_config_resolver.py`
- Test: `backend/tests/unit/core/agent/test_crewai_runtime.py`
**Step 1: Write the failing test**
```python
def test_intent_stage_can_disable_tools():
cfg = load_stage_config(intent_tools=[])
result = run_intent_stage(cfg)
assert result.tool_calls == []
```
**Step 2: Run test to verify it fails**
Run: `cd backend && uv run pytest tests/unit/core/agent/test_crewai_runtime.py -k intent_stage_can_disable_tools -v`
Expected: FAIL,当前三阶段共享同一 llm/tools 配置。
**Step 3: Write minimal implementation**
```python
stage_cfg = config.for_stage(stage)
run_stage(..., llm_config=stage_cfg.llm, tools=stage_cfg.tools)
```
**Step 4: Run test to verify it passes**
Run: `cd backend && uv run pytest tests/unit/core/agent/test_crewai_runtime.py -k intent_stage_can_disable_tools -v`
Expected: PASS
**Step 5: Commit**
```bash
git add backend/src/core/agent/infrastructure/crewai/runtime.py backend/src/core/agent/infrastructure/config/resolver.py backend/tests/unit/core/agent/test_config_resolver.py backend/tests/unit/core/agent/test_crewai_runtime.py
git commit -m "refactor(agent): decouple llm and tool strategy by stage"
```
### Task 8: 多模态图片输入(文件上传)支持(#7)
**Files:**
- Modify: `backend/src/core/agent/domain/agui_input.py`
- Modify: `backend/src/core/agent/infrastructure/crewai/runtime.py`
- Modify: `backend/src/core/agent/infrastructure/litellm/client.py`
- Test: `backend/tests/unit/core/agent/test_litellm_client.py`
**Step 1: Write the failing test**
```python
def test_image_content_block_is_preserved_for_llm():
payload = build_multimodal_payload(text="分析图片", image_file="a.png")
assert payload_contains_image_block(payload)
```
**Step 2: Run test to verify it fails**
Run: `cd backend && uv run pytest tests/unit/core/agent/test_litellm_client.py -k image_content_block_is_preserved -v`
Expected: FAIL,当前非 text 被丢弃。
**Step 3: Write minimal implementation**
```python
if item.type == "image":
blocks.append({"type": "image_url", "image_url": {"url": signed_file_url}})
```
**Step 4: Run test to verify it passes**
Run: `cd backend && uv run pytest tests/unit/core/agent/test_litellm_client.py -k image_content_block_is_preserved -v`
Expected: PASS
**Step 5: Commit**
```bash
git add backend/src/core/agent/domain/agui_input.py backend/src/core/agent/infrastructure/crewai/runtime.py backend/src/core/agent/infrastructure/litellm/client.py backend/tests/unit/core/agent/test_litellm_client.py
git commit -m "feat(agent): support multimodal image input blocks"
```
### Task 9: 新增 ASR 同步转写 API#8
**Files:**
- Create: `backend/src/v1/agent/asr_router.py`
- Modify: `backend/src/v1/agent/router.py`
- Create: `backend/src/v1/agent/asr_service.py`
- Create: `backend/src/v1/agent/asr_schemas.py`
- Test: `backend/tests/integration/v1/agent/test_routes.py`
**Step 1: Write the failing test**
```python
def test_asr_transcribe_returns_sync_transcript(client, wav_file):
resp = client.post("/v1/agent/asr/transcribe", files={"audio": wav_file})
assert resp.status_code == 200
assert resp.json()["transcript"]
```
**Step 2: Run test to verify it fails**
Run: `cd backend && uv run pytest tests/integration/v1/agent/test_routes.py -k asr_transcribe_returns_sync_transcript -v`
Expected: FAIL,当前无路由。
**Step 3: Write minimal implementation**
```python
@router.post("/asr/transcribe")
async def transcribe(audio: UploadFile) -> AsrTranscribeResponse:
text = await asr_service.transcribe(audio)
return AsrTranscribeResponse(transcript=text)
```
**Step 4: Run test to verify it passes**
Run: `cd backend && uv run pytest tests/integration/v1/agent/test_routes.py -k asr_transcribe_returns_sync_transcript -v`
Expected: PASS
**Step 5: Commit**
```bash
git add backend/src/v1/agent/asr_router.py backend/src/v1/agent/router.py backend/src/v1/agent/asr_service.py backend/src/v1/agent/asr_schemas.py backend/tests/integration/v1/agent/test_routes.py
git commit -m "feat(agent): add synchronous asr transcription endpoint"
```
### Task 10: 全量验证与文档对齐
**Files:**
- Modify: `docs/runtime/runtime-route.md`
- Modify: `docs/bugs/2026-03-08-agent-tool-architecture.md` (状态回填)
**Step 1: Run targeted unit suite**
Run: `cd backend && uv run pytest tests/unit/core/agent -v`
Expected: PASS
**Step 2: Run targeted integration suite**
Run: `cd backend && uv run pytest tests/integration/core/agent tests/integration/v1/agent -v`
Expected: PASS
**Step 3: Run e2e smoke for agent flow**
Run: `cd backend && uv run pytest tests/e2e -k "agent or mobile_health" -v`
Expected: PASS 或明确记录跳过原因
**Step 4: Run quality gates**
Run: `cd backend && uv run ruff check src tests && uv run basedpyright`
Expected: PASS
**Step 5: Final commit**
```bash
git add docs/runtime/runtime-route.md docs/bugs/2026-03-08-agent-tool-architecture.md
git commit -m "docs(agent): align runtime docs with new tool architecture"
```
---
## Verification Evidence Requirements
实施完成时必须输出:
1. 双金路径验证结果(无工具 + 工具审批后续跑)
2. 三阶段 StepStarted/StepFinished 事件日志片段
3. 安全验证结果(前端 history 篡改无效)
4. ASR 同步转写接口请求/响应样例
5. 关键命令输出摘要(pytest/ruff/basedpyright
---
## Notes
- 本计划不包含兼容逻辑保留。
- 本计划采用一次性切换。
- 若实施中出现 S2 -> S3 范围升级,先暂停并更新计划,再继续执行。