feat(backend): 完善 Workflow 与 DeepResearch 的运行链路与持久化能力

功能说明：\n- 重构并增强工作流网关执行链路，支持更完整的 proposal 与 run 调度参数透传\n- 增加 DeepResearch/workflow 运行事件持久化能力并补齐建表 SQL 与查询/保存接口适配\n- 优化 lead agent 与 deep research runner 的中间态处理，增强线程收集与执行链并发控制\n- 调整工作流执行器与任务路由，提升兼容性并完善错误与回放行为\n- 补充回归测试：deep_research 持久化、workflow 并发、定义加载、引擎执行、run 流程等覆盖

offline-backend-20260512/backend/README.md

@@ -55,6 +55,11 @@ The single LangGraph agent (`lead_agent`) is the runtime entry point, created vi
 - **Subagent delegation** for parallel task execution
 - **System prompt** with skills injection, memory context, and working directory guidance
 
+### Workflow Studio runtime
+
+- Candidate workflow graphs remain editable after they are loaded into the Coze-compatible canvas; the compatibility response explicitly marks the current owner as editable so node dragging is not mistaken for a read-only preview.
+- Workflow-agent SSE forwards provider `reasoning_content` as an inline `<think>…</think>` trace for the UI while keeping the executable node output limited to the visible answer text. Every native LangGraph `[AIMessage|ToolMessage, metadata]` frame is additionally persisted and sent as `node.message.data.messages` without projection or length cropping, so the Studio can replay DeerFlow's tool-result, search-result and `ask_clarification` cards exactly after reconnecting.
+
 ### Middleware Chain
 
 Middlewares execute in strict order, each handling a specific concern:
@@ -219,6 +224,21 @@ both streams `no-transform` and `X-Accel-Buffering: no`; `apps/coze-studio` also
 its Rsbuild development server `compress: false`. Agent/skill nodes use the bounded
 `workflows.agent_recursion_limit` (default `250`), rather than a chat-sized 60-step
 limit, because a model-to-tool research turn consumes about two LangGraph super-steps.
+The composer may also send a configured `modelName`: the server validates it against
+the safe model catalog, uses it for the workflow controller, and writes it into the
+generated candidate agent nodes. For a direct single-agent task it overrides only that
+projected node; confirmation still executes the immutable selected proposal snapshot.
+The controller additionally creates a per-selected-agent task contract (`mission`,
+`deliverable`, `scope`, `handoff`). The graph builder accepts contracts only for
+catalog-visible, selected agent ids and injects each one into that worker's prompt, so
+parallel branches receive complementary research assignments and sequential branches
+have an explicit review/handoff boundary rather than all workers attempting the whole
+user task. Missing controller fields receive a deterministic role-aware contract.
+When an agent emits DeerFlow's native `ask_clarification` ToolMessage, the workflow
+enters `awaiting_input` rather than completing or failing. The pause event references
+the originating `nodeRunId` and `toolCallId`; the browser renders that original card
+inside the agent message and `POST /runs/{run_id}/resume` supplies the user's reply as
+the next turn of the same agent thread.
 
 The current planner is deliberately constrained: it can rank supported strategies and
 focus resources, but the server builds the graph from the already configured agent