163 lines
3.8 KiB
Markdown
163 lines
3.8 KiB
Markdown
# Phase 3：Agent 集成
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日期：2026-04-04
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状态：待实施
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依赖：Phase 1 + Phase 2 完成
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---
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## 1. 本阶段目的
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将代码指挥官接入 LangGraph：
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- Graph 节点
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- 边路由
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- 任务模型
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---
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## 2. 详细任务
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### 2.1 Graph 节点
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**文件**: `backend/app/agents/graph.py`
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```python
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# 新增 code_commander_node
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async def code_commander_node(state: AgentState) -> AgentState:
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"""代码指挥官节点"""
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# 1. 获取用户需求和选择的 AI 提供商
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user_message = state.messages[-1].content
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ai_provider = state.get("ai_provider", "claude")
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# 2. 安全分级
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classifier = SecurityClassifier()
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risk_level = classifier.classify(user_message)
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# 3. 根据风险等级选择执行器
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adapter = get_adapter(ai_provider)
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if risk_level == RiskLevel.LOW:
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executor = DirectExecutor(adapter)
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result = await executor.execute(user_message)
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else:
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sandbox = await SandboxEnvironment.create()
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executor = SandboxExecutor(adapter)
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result = await executor.execute(user_message, sandbox.session_id)
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state["workspace_path"] = str(sandbox.workspace_path)
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state["execution_session_id"] = sandbox.session_id
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# 4. 更新状态
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state.messages.append(AIMessage(content=str(result)))
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state["next_step"] = None # 任务完成
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return state
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# 节点注册到 NODES
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NODES: dict[str, NodeCallable] = {
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# ... 现有节点 ...
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"code_commander": code_commander_node,
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}
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```
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### 2.2 边路由
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**文件**: `backend/app/agents/graph.py`
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```python
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def _should_route_to_code_commander(state: AgentState) -> str:
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"""判断是否路由到代码指挥官"""
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if state.current_agent == "code_commander":
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return "code_commander"
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# ... 其他条件
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return END
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# 边注册
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def _build_graph() -> CompiledGraph:
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# ... 现有边 ...
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# 新增代码指挥官相关边
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graph.add_conditional_edges(
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"master",
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_should_route_to_code_commander,
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{
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"code_commander": "code_commander",
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END: END,
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}
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)
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graph.add_edge("code_commander", END)
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return graph.compile()
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```
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### 2.3 任务模型
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**文件**: `backend/app/agents/schemas/task.py`
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```python
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from pydantic import BaseModel, Field
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from typing import Literal
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class CodeProviderType(str, Enum):
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CLAUDE = "claude"
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GEMINI = "gemini"
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CODEX = "codex"
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OPENCODE = "opencode"
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class RiskLevelType(str, Enum):
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LOW = "low"
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HIGH = "high"
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class CodeTask(BaseModel):
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"""代码任务"""
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id: str = Field(default_factory=lambda: f"code_{uuid.uuid4().hex[:8]}")
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provider: CodeProviderType
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prompt: str
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risk_level: RiskLevelType
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sandbox_mode: bool
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workspace_path: str | None = None
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session_id: str | None = None
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status: Literal["pending", "running", "completed", "failed"] = "pending"
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created_at: datetime = Field(default_factory=datetime.now)
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class CodeExecutionResult(BaseModel):
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"""代码执行结果"""
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task_id: str
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success: bool
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exit_code: int
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stdout: str
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stderr: str
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files_created: list[str] = Field(default_factory=list)
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workspace_path: str | None = None
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completed_at: datetime = Field(default_factory=datetime.now)
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```
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---
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## 3. 核心文件清单
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| 文件 | 操作 | 说明 |
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|------|------|------|
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| `graph.py` | 修改 | 新增 `code_commander_node` 和边路由 |
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| `schemas/task.py` | 修改 | 新增 `CodeTask`, `CodeExecutionResult` 等模型 |
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---
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## 4. 验收标准
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- [ ] `code_commander_node` 正确处理任务
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- [ ] `SecurityClassifier` 被正确调用
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- [ ] 高低风险任务路由到正确的执行器
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- [ ] `CodeTask` 和 `CodeExecutionResult` 模型正确
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---
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## 5. 依赖关系
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```
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Phase 1 + Phase 2
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↓
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本阶段 → Phase 4（流式交互）
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→ Phase 5（前端集成）
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```
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