fix: #33 内置多模态工具现在在工具市场 /api/v1/tools 中可见

list_tools 端点合并内置工具（image_ocr/image_vision/speech_to_text/text_to_speech 等），
按 scope=public/all 时自动包含，无需额外种子到 DB。

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

backend/app/api/agent_chat.py

@@ -183,6 +183,50 @@ async def orchestrate_agents(
     )
 
 
+class GraphOrchestrateRequest(BaseModel):
+    """图编排请求 — 以 nodes + edges 描述 DAG"""
+    message: str
+    nodes: List[Dict[str, Any]] = Field(..., description="编排节点列表")
+    edges: List[Dict[str, Any]] = Field(default_factory=list, description="编排连线列表")
+    model: Optional[str] = None
+
+
+@router.post("/orchestrate/graph", response_model=OrchestrateResponse)
+async def orchestrate_graph(
+    req: GraphOrchestrateRequest,
+    current_user: User = Depends(get_current_user),
+    db: Session = Depends(get_db),
+):
+    """图编排模式：按 DAG 拓扑顺序执行 Agent 和条件节点。"""
+    on_llm_call = _make_llm_logger(db, agent_id=None, user_id=current_user.id)
+    orchestrator = AgentOrchestrator(
+        default_llm_config=AgentLLMConfig(
+            model=req.model or "deepseek-v4-flash",
+            temperature=0.3,
+        ),
+    )
+    result = await orchestrator._graph(
+        req.message, req.nodes, req.edges, on_llm_call=on_llm_call,
+    )
+    return OrchestrateResponse(
+        mode=result.mode,
+        final_answer=result.final_answer,
+        steps=[
+            OrchestrateStepItem(
+                agent_id=s.agent_id,
+                agent_name=s.agent_name,
+                input=s.input,
+                output=s.output,
+                iterations_used=s.iterations_used,
+                tool_calls_made=s.tool_calls_made,
+                error=s.error,
+            )
+            for s in result.steps
+        ],
+        agent_results=result.agent_results,
+    )
+
+
 @router.post("/bare", response_model=ChatResponse)
 async def chat_bare(
     req: ChatRequest,