[agent] Deep Research - Log Analysis
$ uvicorn main:app --host 0.0.0.0 --port 8080 --reload INFO: Will watch for changes in these directories: ['/home/jeffrey/Desktop/MyDesktop/lv7/deep-research/launch-DeepResearch-Backend'] INFO: Uvicorn running on http://0.0.0.0:8080 (Press CTRL+C to quit) INFO: Started reloader process [1393238] using StatReload 2026-09-04 21:01:07 | WARNING | [SUPABASE] 2-50 Credentials not provided; using in-memory storage INFO: Started server process [1393240] INFO: Waiting for application startup. INFO: Application startup complete. 2026-09-04 21:01:22 | INFO | [REST] 1-01 解释：进入 REST API 层：接收客户端的 Deep Research 请求，先完成参数校验，再创建 SSE 流式响应。 2026-09-04 21:01:22 | INFO | [REST] 1-02 ────────────── POST /research/stream ────────────── 2026-09-04 21:01:22 | INFO | [REST] 1-03 解释：REST 接口输入：客户端传入研究问题、模型类型和 API Key（Key 只记录为已提供，不打印真实值）。
2026-09-04 21:01:22 | INFO | [REST] 1-04 ┌─ INPUT [PAIR=REST.stream_research:3c40c60] | model=ModelType.ANTHROPIC | query=请研究一下长期恋爱关系中，哪些因素最影响双方的满意度和稳定性，并给出有研究依据的结论。 | api_key=<redacted> 2026-09-04 21:01:22 | INFO | [REST] 1-05 REQUEST received | model=ModelType.ANTHROPIC | query=请研究一下长期恋爱关系中，哪些因素最影响双方的满意度和稳定性，并给出有研究依据的结论。 | api_key=<redacted> 2026-09-04 21:01:22 | INFO | [REST] 1-35 FLOW | 前因：客户端请求已经进入 /research/stream，REST 已拿到 query/model/API Key | 当前：依次校验 query、API Key 是否存在，以及 model 是否受支持 | 下一步：全部通过后创建 SSE StreamingResponse 2026-09-04 21:01:22 | INFO | [REST] 1-06 VALIDATE query 2026-09-04 21:01:22 | INFO | [REST] 1-08 VALIDATE api_key presence (value never logged) 2026-09-04 21:01:22 | INFO | [REST] 1-10 VALIDATE model | requested=ModelType.ANTHROPIC | available=['openai', 'anthropic', 'kimi'] 2026-09-04 21:01:22 | INFO | [REST] 1-12 解释：请求参数校验通过；下面创建 SSE StreamingResponse，真正的研究流程会在流式生成器中继续执行。 2026-09-04 21:01:22 | INFO | [REST] 1-13 VALIDATION OK | creating SSE StreamingResponse 2026-09-04 21:01:22 | INFO | [REST] 1-36 FLOW | 前因：query/API Key/model 三项校验全部通过 | 当前：创建 StreamingResponse；HTTP 200 只代表流已建立，不代表研究已经完成 | 下一步：客户端开始消费 generate_research_stream() 产生的 SSE 数据 2026-09-04 21:01:22 | INFO | [REST] 1-27 解释：REST 接口输出：HTTP 层返回的是一个 SSE StreamingResponse；此时只是建立流，后续研究结果会持续写入这个响应。 2026-09-04 21:01:22 | INFO | [REST] 1-28 └─ OUTPUT [PAIR=REST.stream_research:3c40c60] | StreamingResponse(media_type=text/event-stream) created; body will be produced asynchronously by generate_research_stream()
INFO: 127.0.0.1:45460 - "POST /research/stream HTTP/1.1" 200 OK 2026-09-04 21:01:22 | INFO | [REST] 1-14 [research_1788519682] 解释：进入 SSE 会话：从这一行开始，同一个 research_id 的事件会持续推送给客户端，直到研究完成或发生错误。 2026-09-04 21:01:22 | INFO | [REST] 1-15 [research_1788519682] ────────────── SSE SESSION START ────────────── 2026-09-04 21:01:22 | INFO | [REST] 1-16 [research_1788519682] 解释：SSE 会话输入：把本次请求的 query/model 交给流式研究流程。 2026-09-04 21:01:22 | INFO | [REST] 1-17 [research_1788519682] ┌─ INPUT [PAIR=SSE.session:research_1788519682] | query=请研究一下长期恋爱关系中，哪些因素最影响双方的满意度和稳定性，并给出有研究依据的结论。 | model=ModelType.ANTHROPIC 2026-09-04 21:01:22 | INFO | [REST] 1-18 [research_1788519682] SSE -> session_start | model=ModelType.ANTHROPIC 2026-09-04 21:01:22 | INFO | [REST] 1-37 [research_1788519682] FLOW | 前因：SSE 连接已经建立，并为本次请求生成 research_id | 当前：先向客户端发送 session_start，标记一条新的研究会话 | 下一步：调用 DeepResearchService.stream_research()，真正准备并启动 LangGraph 2026-09-04 21:01:22 | INFO | [SERVICE] 2-01 [research_1788519682] CALL DeepResearchService.stream_research() 2026-09-04 21:01:22 | INFO | [SERVICE] 2-03 [research_1788519682] 解释：进入 Service 层：REST 已完成 HTTP 参数校验；现在开始把请求转换成 LangGraph 需要的运行参数、config、context 和初始 state。 2026-09-04 21:01:22 | INFO | [SERVICE] 2-04 [research_1788519682] ────────────── DeepResearchService.stream_research ────────────── 2026-09-04 21:01:22 | INFO | [SERVICE] 2-92 [research_1788519682] FLOW | 前因：REST 已验证 query/model/API Key，并建立 SSE 会话 | 当前：Service 接管请求，开始做 Graph 启动前准备 | 下一步：按 6 个步骤准备 INPUT → RUNTIME → CONFIG → CONTEXT → STATE → SSE 2026-09-04 21:01:22 | INFO | [SERVICE] 2-05 [research_1788519682] 解释：PREP 1/6（INPUT）：确认这次研究任务的原始输入；这些值来自 REST 层，是后续所有准备工作的起点。 2026-09-04 21:01:22 | INFO | [SERVICE] 2-06 [research_1788519682] ┌─ INPUT [PAIR=SERVICE.stream_research:research_1788519682] | query=请研究一下长期恋爱关系中，哪些因素最影响双方的满意度和稳定性，并给出有研究依据的结论。 | model=ModelType.ANTHROPIC | api_key=<redacted> 2026-09-04 21:01:22 | INFO | [SERVICE] 2-07 [research_1788519682] PREP 1/6 INPUT: 2026-09-04 21:01:22 | INFO | [SERVICE] 2-07 [research_1788519682] │ { 2026-09-04 21:01:22 | INFO | [SERVICE] 2-07 [research_1788519682] │ "research_id": "research_1788519682", 2026-09-04 21:01:22 | INFO | [SERVICE] 2-07 [research_1788519682] │ "model": "anthropic", 2026-09-04 21:01:22 | INFO | [SERVICE] 2-07 [research_1788519682] │ "query": "请研究一下长期恋爱关系中，哪些因素最影响双方的满意度和稳定性，并给出有研究依据的结论。", 2026-09-04 21:01:22 | INFO | [SERVICE] 2-07 [research_1788519682] │ "query_chars": 43, 2026-09-04 21:01:22 | INFO | [SERVICE] 2-07 [research_1788519682] │ "api_key": "<redacted>" 2026-09-04 21:01:22 | INFO | [SERVICE] 2-07 [research_1788519682] │ } 2026-09-04 21:01:22 | INFO | [SERVICE] 2-69 [research_1788519682] ────────────── PRE-GRAPH PREPARATION ────────────── 2026-09-04 21:01:22 | INFO | [SERVICE] 2-70 [research_1788519682] 解释：Graph 启动前一共有 6 项准备：①输入；②运行规则；③RunnableConfig；④关联上下文；⑤初始 AgentState；⑥初始化 SSE。每一步都明确说明前因、当前和下一步。 2026-09-04 21:01:22 | INFO | [SERVICE] 2-93 [research_1788519682] FLOW | 前因：PREP 1/6 已确认研究输入 | 当前：PREP 2/6 设置 Graph 的运行保护和 streaming 规则 | 下一步：根据 model/API Key 构造 RunnableConfig 2026-09-04 21:01:22 | INFO | [SERVICE] 2-71 [research_1788519682] PREP 2/6 RUNTIME: 2026-09-04 21:01:22 | INFO | [SERVICE] 2-71 [research_1788519682] │ { 2026-09-04 21:01:22 | INFO | [SERVICE] 2-71 [research_1788519682] │ "timeout_seconds": 900, 2026-09-04 21:01:22 | INFO | [SERVICE] 2-71 [research_1788519682] │ "heartbeat_check_seconds": 25, 2026-09-04 21:01:22 | INFO | [SERVICE] 2-71 [research_1788519682] │ "stream_mode": "updates", 2026-09-04 21:01:22 | INFO | [SERVICE] 2-71 [research_1788519682] │ "timeout_action": "return_partial_results", 2026-09-04 21:01:22 | INFO | [SERVICE] 2-71 [research_1788519682] │ "initial_stage": "ResearchStage.INITIALIZATION" 2026-09-04 21:01:22 | INFO | [SERVICE] 2-71 [research_1788519682] │ } 2026-09-04 21:01:22 | INFO | [SERVICE] 2-72 [research_1788519682] 解释：注意：当前 timeout/heartbeat 都是在 Graph 返回一个 chunk 之后检查，不是独立后台定时器；如果单个节点运行很久，检查也会被推迟。 2026-09-04 21:01:22 | INFO | [SERVICE] 2-73 [research_1788519682] FLOW | 前因：PREP 2/6 已确定 timeout、heartbeat 和 stream_mode | 当前：PREP 3/6 解析模型/Provider，并组装 RunnableConfig | 下一步：把 research_id/model_type 放入 metadata，建立跨层日志关联 2026-09-04 21:01:22 | INFO | [SERVICE] 2-08 [research_1788519682] CREATE RunnableConfig
2026-09-04 21:01:22 | INFO | [CONFIG] 2-83 ────────────── RUNNABLE CONFIG PREPARATION ────────────── 2026-09-04 21:01:22 | INFO | [CONFIG] 2-21 解释：配置模块输入：根据客户端选择的 provider/model 和 API Key 生成 LangChain RunnableConfig。
2026-09-04 21:01:22 | INFO | [CONFIG] 2-22 ┌─ INPUT [PAIR=SERVICE.create_config:dc74778] | model=ModelType.ANTHROPIC | api_key=<redacted> 2026-09-04 21:01:22 | INFO | [CONFIG] 2-96 FLOW | 前因：Service 已拿到客户端选择的 model 和 API Key | 当前：CONFIG 1/4 解析模型别名，确定真正传给 LangChain/Provider 的模型名 | 下一步：准备 Provider endpoint 和凭证绑定 2026-09-04 21:01:22 | INFO | [CONFIG] 2-84 解释：CONFIG 1/4：解析客户端的模型别名，确定真正传给 LangChain/Provider 的模型名称。 2026-09-04 21:01:22 | INFO | [CONFIG] 2-23 Resolve model mapping | requested=ModelType.ANTHROPIC 2026-09-04 21:01:22 | INFO | [CONFIG] 2-24 Resolved model | ModelType.ANTHROPIC -> claude-sonnet-4-6 2026-09-04 21:01:22 | INFO | [CONFIG] 2-97 FLOW | 前因：模型别名已解析为 claude-sonnet-4-6 | 当前：CONFIG 2/4 准备 Provider endpoint、provider binding 和 API Key | 下一步：组装 Graph 的运行策略参数 2026-09-04 21:01:22 | INFO | [CONFIG] 2-85 解释：CONFIG 2/4：准备 Provider 调用环境与凭证；API Key 只绑定到 RunnableConfig，日志永远只显示 <redacted>。 2026-09-04 21:01:22 | INFO | [CONFIG] 2-86 Credential binding | user_api_key=<redacted> 2026-09-04 21:01:22 | INFO | [CONFIG] 2-87 Provider environment ready | endpoint=default ModelType.ANTHROPIC provider endpoint 2026-09-04 21:01:22 | INFO | [CONFIG] 2-88 Provider binding ready | model_provider=anthropic 2026-09-04 21:01:22 | INFO | [CONFIG] 2-98 FLOW | 前因：Provider 调用环境与凭证绑定已准备好 | 当前：CONFIG 3/4 组装模型、token、search、Researcher/Tool/并发等运行策略 | 下一步：把完整配置封装成 RunnableConfig 2026-09-04 21:01:22 | INFO | [CONFIG] 2-89 解释：CONFIG 3/4：准备 Graph 的运行策略参数，包括各阶段模型、token 上限、search API、Researcher 迭代/工具调用/并发预算。 2026-09-04 21:01:22 | INFO | [CONFIG] 2-90 Runtime policy ready | search_api=anthropic | allow_clarification=False | researcher_iterations=1 | react_tool_calls=3 | concurrent_units=2 2026-09-04 21:01:22 | INFO | [CONFIG] 2-26 RunnableConfig.configurable: 2026-09-04 21:01:22 | INFO | [CONFIG] 2-26 │ { 2026-09-04 21:01:22 | INFO | [CONFIG] 2-26 │ "research_model": "claude-sonnet-4-6", 2026-09-04 21:01:22 | INFO | [CONFIG] 2-26 │ "research_model_max_tokens": 4000, 2026-09-04 21:01:22 | INFO | [CONFIG] 2-26 │ "final_report_model": "claude-sonnet-4-6", 2026-09-04 21:01:22 | INFO | [CONFIG] 2-26 │ "final_report_model_max_tokens": 8000, 2026-09-04 21:01:22 | INFO | [CONFIG] 2-26 │ "compression_model": "claude-sonnet-4-6", 2026-09-04 21:01:22 | INFO | [CONFIG] 2-26 │ "compression_model_max_tokens": 4000, 2026-09-04 21:01:22 | INFO | [CONFIG] 2-26 │ "summarization_model": "claude-sonnet-4-6", 2026-09-04 21:01:22 | INFO | [CONFIG] 2-26 │ "summarization_model_max_tokens": 4000, 2026-09-04 21:01:22 | INFO | [CONFIG] 2-26 │ "allow_clarification": false, 2026-09-04 21:01:22 | INFO | [CONFIG] 2-26 │ "max_structured_output_retries": 2, 2026-09-04 21:01:22 | INFO | [CONFIG] 2-26 │ "search_api": "anthropic", 2026-09-04 21:01:22 | INFO | [CONFIG] 2-26 │ "max_researcher_iterations": 1, 2026-09-04 21:01:22 | INFO | [CONFIG] 2-26 │ "max_react_tool_calls": 3, 2026-09-04 21:01:22 | INFO | [CONFIG] 2-26 │ "max_concurrent_research_units": 2, 2026-09-04 21:01:22 | INFO | [CONFIG] 2-26 │ "user_api_key": "<redacted>", 2026-09-04 21:01:22 | INFO | [CONFIG] 2-26 │ "research_model_provider": "anthropic", 2026-09-04 21:01:22 | INFO | [CONFIG] 2-26 │ "final_report_model_provider": "anthropic", 2026-09-04 21:01:22 | INFO | [CONFIG] 2-26 │ "compression_model_provider": "anthropic", 2026-09-04 21:01:22 | INFO | [CONFIG] 2-26 │ "summarization_model_provider": "anthropic" 2026-09-04 21:01:22 | INFO | [CONFIG] 2-26 │ } 2026-09-04 21:01:22 | INFO | [CONFIG] 2-99 FLOW | 前因：CONFIG 3/4 已得到完整 configurable dict | 当前：CONFIG 4/4 封装 LangChain RunnableConfig | 下一步：返回 Service，并继续准备 metadata / initial_state 2026-09-04 21:01:22 | INFO | [CONFIG] 2-91 解释：CONFIG 4/4：把前面的模型、Provider、运行策略和凭证正式封装成 LangChain RunnableConfig。 2026-09-04 21:01:22 | INFO | [CONFIG] 2-27 解释：配置模块输出：RunnableConfig 已组装完成；后续所有 Graph/LLM/Tool 节点都会从这里读取模型、限额和 API 配置。 2026-09-04 21:01:22 | INFO | [CONFIG] 2-28 └─ OUTPUT [PAIR=SERVICE.create_config:dc74778] | RunnableConfig ready | resolved_model=claude-sonnet-4-6 | provider=anthropic | search_api=anthropic | limits={researcher_iterations:1, react_tool_calls:3, concurrent_units:2}
2026-09-04 21:01:22 | INFO | [SERVICE] 2-09 [research_1788519682] PREP 3/6 CONFIG SUMMARY: 2026-09-04 21:01:22 | INFO | [SERVICE] 2-09 [research_1788519682] │ { 2026-09-04 21:01:22 | INFO | [SERVICE] 2-09 [research_1788519682] │ "requested_model": "anthropic", 2026-09-04 21:01:22 | INFO | [SERVICE] 2-09 [research_1788519682] │ "resolved_model": "claude-sonnet-4-6", 2026-09-04 21:01:22 | INFO | [SERVICE] 2-09 [research_1788519682] │ "provider": "anthropic", 2026-09-04 21:01:22 | INFO | [SERVICE] 2-09 [research_1788519682] │ "search_api": "anthropic", 2026-09-04 21:01:22 | INFO | [SERVICE] 2-09 [research_1788519682] │ "limits": { 2026-09-04 21:01:22 | INFO | [SERVICE] 2-09 [research_1788519682] │ "max_researcher_iterations": 1, 2026-09-04 21:01:22 | INFO | [SERVICE] 2-09 [research_1788519682] │ "max_react_tool_calls": 3, 2026-09-04 21:01:22 | INFO | [SERVICE] 2-09 [research_1788519682] │ "max_concurrent_research_units": 2 2026-09-04 21:01:22 | INFO | [SERVICE] 2-09 [research_1788519682] │ } 2026-09-04 21:01:22 | INFO | [SERVICE] 2-09 [research_1788519682] │ } 2026-09-04 21:01:22 | INFO | [SERVICE] 2-74 [research_1788519682] FLOW | 前因：PREP 3/6 已生成 RunnableConfig，并已解析实际模型 | 当前：PREP 4/6 把 research_id/model_type 放入 config.metadata | 下一步：用用户 query 创建 Main Graph 的 initial_state 2026-09-04 21:01:22 | INFO | [SERVICE] 2-94 [research_1788519682] PREP 4/6 CONTEXT: 2026-09-04 21:01:22 | INFO | [SERVICE] 2-94 [research_1788519682] │ { 2026-09-04 21:01:22 | INFO | [SERVICE] 2-94 [research_1788519682] │ "metadata": { 2026-09-04 21:01:22 | INFO | [SERVICE] 2-94 [research_1788519682] │ "model_type": "anthropic", 2026-09-04 21:01:22 | INFO | [SERVICE] 2-94 [research_1788519682] │ "research_id": "research_1788519682" 2026-09-04 21:01:22 | INFO | [SERVICE] 2-94 [research_1788519682] │ }, 2026-09-04 21:01:22 | INFO | [SERVICE] 2-94 [research_1788519682] │ "purpose": "correlate service / graph / researcher / tool logs for the same run" 2026-09-04 21:01:22 | INFO | [SERVICE] 2-94 [research_1788519682] │ } 2026-09-04 21:01:22 | INFO | [SERVICE] 2-75 [research_1788519682] FLOW | 前因：PREP 4/6 已建立本次运行的关联上下文 | 当前：PREP 5/6 把 REST query 包装成 LangGraph 的 AgentInputState/HumanMessage | 下一步：在 Graph 启动前向客户端发送初始化 SSE 2026-09-04 21:01:22 | INFO | [SERVICE] 2-10 [research_1788519682] PREP 5/6 STATE: 2026-09-04 21:01:22 | INFO | [SERVICE] 2-10 [research_1788519682] │ { 2026-09-04 21:01:22 | INFO | [SERVICE] 2-10 [research_1788519682] │ "state_type": "AgentInputState", 2026-09-04 21:01:22 | INFO | [SERVICE] 2-10 [research_1788519682] │ "messages": [ 2026-09-04 21:01:22 | INFO | [SERVICE] 2-10 [research_1788519682] │ { 2026-09-04 21:01:22 | INFO | [SERVICE] 2-10 [research_1788519682] │ "type": "HumanMessage", 2026-09-04 21:01:22 | INFO | [SERVICE] 2-10 [research_1788519682] │ "content": "请研究一下长期恋爱关系中，哪些因素最影响双方的满意度和稳定性，并给出有研究依据的结论。" 2026-09-04 21:01:22 | INFO | [SERVICE] 2-10 [research_1788519682] │ } 2026-09-04 21:01:22 | INFO | [SERVICE] 2-10 [research_1788519682] │ ] 2026-09-04 21:01:22 | INFO | [SERVICE] 2-10 [research_1788519682] │ } 2026-09-04 21:01:22 | INFO | [SERVICE] 2-77 [research_1788519682] FLOW | 前因：PREP 5/6 已得到 Main Graph 的 initial_state | 当前：PREP 6/6 先发送 session/model 初始化事件，让客户端知道研究已开始 | 下一步：初始化 chunk 计数器，然后真正调用 deep_researcher.astream() 2026-09-04 21:01:22 | INFO | [SERVICE] 2-95 [research_1788519682] PREP 6/6 SSE EVENTS: 2026-09-04 21:01:22 | INFO | [SERVICE] 2-95 [research_1788519682] │ { 2026-09-04 21:01:22 | INFO | [SERVICE] 2-95 [research_1788519682] │ "events": [ 2026-09-04 21:01:22 | INFO | [SERVICE] 2-95 [research_1788519682] │ { 2026-09-04 21:01:22 | INFO | [SERVICE] 2-95 [research_1788519682] │ "type": "stage_start", 2026-09-04 21:01:22 | INFO | [SERVICE] 2-95 [research_1788519682] │ "stage": "ResearchStage.INITIALIZATION" 2026-09-04 21:01:22 | INFO | [SERVICE] 2-95 [research_1788519682] │ }, 2026-09-04 21:01:22 | INFO | [SERVICE] 2-95 [research_1788519682] │ { 2026-09-04 21:01:22 | INFO | [SERVICE] 2-95 [research_1788519682] │ "type": "api_call", 2026-09-04 21:01:22 | INFO | [SERVICE] 2-95 [research_1788519682] │ "resolved_model": "claude-sonnet-4-6", 2026-09-04 21:01:22 | INFO | [SERVICE] 2-95 [research_1788519682] │ "provider": "anthropic" 2026-09-04 21:01:22 | INFO | [SERVICE] 2-95 [research_1788519682] │ } 2026-09-04 21:01:22 | INFO | [SERVICE] 2-95 [research_1788519682] │ ], 2026-09-04 21:01:22 | INFO | [SERVICE] 2-95 [research_1788519682] │ "timing": "before Main Graph starts", 2026-09-04 21:01:22 | INFO | [SERVICE] 2-95 [research_1788519682] │ "purpose": "announce session start and resolved model" 2026-09-04 21:01:22 | INFO | [SERVICE] 2-95 [research_1788519682] │ } 2026-09-04 21:01:22 | INFO | [REST] 1-19 [research_1788519682] SSE -> type=stage_start | stage=ResearchStage.INITIALIZATION 2026-09-04 21:01:22 | INFO | [REST] 1-19 [research_1788519682] SSE -> type=api_call | stage=ResearchStage.INITIALIZATION
2026-09-04 21:01:22 | INFO | [SERVICE] 2-80 [research_1788519682] FLOW | 前因：PREP 1/6～6/6 全部完成，initial_state 和 RunnableConfig 均已就绪 | 当前：Graph 启动前准备结束；初始化 outer chunk 计数器和等待计时器 | 下一步：进入 MAIN GRAPH，调用 deep_researcher.astream(stream_mode=updates) 2026-09-04 21:01:22 | INFO | [SERVICE] 2-81 [research_1788519682] PRE-GRAPH READY: 2026-09-04 21:01:22 | INFO | [SERVICE] 2-81 [research_1788519682] │ { 2026-09-04 21:01:22 | INFO | [SERVICE] 2-81 [research_1788519682] │ "resolved_model": "claude-sonnet-4-6", 2026-09-04 21:01:22 | INFO | [SERVICE] 2-81 [research_1788519682] │ "provider": "anthropic", 2026-09-04 21:01:22 | INFO | [SERVICE] 2-81 [research_1788519682] │ "initial_state_messages": 1, 2026-09-04 21:01:22 | INFO | [SERVICE] 2-81 [research_1788519682] │ "stream_mode": "updates", 2026-09-04 21:01:22 | INFO | [SERVICE] 2-81 [research_1788519682] │ "timeout_seconds": 900, 2026-09-04 21:01:22 | INFO | [SERVICE] 2-81 [research_1788519682] │ "heartbeat_check_seconds": 25, 2026-09-04 21:01:22 | INFO | [SERVICE] 2-81 [research_1788519682] │ "next": "deep_researcher.astream" 2026-09-04 21:01:22 | INFO | [SERVICE] 2-81 [research_1788519682] │ } 2026-09-04 21:01:22 | INFO | [SERVICE] 2-82 [research_1788519682] ────────────── END PRE-GRAPH PREPARATION ──────────────
2026-09-04 21:01:22 | INFO | [MAIN GRAPH] 3-01 [research_1788519682] 解释：进入最外层 LangGraph：从 initial_state 开始，依次运行 clarification、research brief、research supervisor 和 final report。 2026-09-04 21:01:22 | INFO | [MAIN GRAPH] 3-02 [research_1788519682] ────────────── START ────────────── 2026-09-04 21:01:22 | INFO | [MAIN GRAPH] 3-03 [research_1788519682] 解释：Main Graph 输入：“一个包含用户问题的初始 Agent state”，以及“本次 RunnableConfig”。
2026-09-04 21:01:22 | INFO | [MAIN GRAPH] 3-04 [research_1788519682] ┌─ INPUT [PAIR=MAIN_GRAPH.run:research_1788519682] | initial_state.messages=HumanMessage=1 | query=请研究一下长期恋爱关系中，哪些因素最影响双方的满意度和稳定性，并给出有研究依据的结论。 | stream_mode=updates 2026-09-04 21:01:22 | INFO | [MAIN GRAPH] 3-76 [research_1788519682] 解释：关键：下一行 3-05 才真正调用 Graph。async for 负责消费 Graph 的 update 流：外层节点执行完成 -> LangGraph 返回 chunk -> Service 处理/转成 SSE -> 再等待下一个 chunk。后面的 GRAPH PATH 会把相邻节点连成 A -> B，而不是只打印孤立节点。注意：这里追踪的是 Main Graph 层；Supervisor/Researcher 子图内部循环看各自第 4/5 层日志。 2026-09-04 21:01:22 | INFO | [MAIN GRAPH] 3-77 [research_1788519682] FLOW | 前因：Service 的 6 项 PREP 已完成，initial_state + RunnableConfig 已就绪 | 当前：调用 deep_researcher.astream()，把执行权交给 LangGraph | 下一步：等待 Graph 完成第一个外层节点并返回 update chunk 2026-09-04 21:01:22 | INFO | [MAIN GRAPH] 3-05 [research_1788519682] CALL deep_researcher.astream(stream_mode=updates) 2026-09-04 21:01:22 | INFO | [MAIN GRAPH] 3-15 [research_1788519682] 解释：Main Graph 节点 clarify_with_user：判断是否需要向用户追问；当前配置若关闭 clarification，则直接路由到 research brief。 2026-09-04 21:01:22 | INFO | [MAIN GRAPH] 3-16 [research_1788519682] ────────────── NODE clarify_with_user ──────────────
2026-09-04 21:01:22 | INFO | [clarify_with_user] 3-17 [research_1788519682] 解释：节点输入：当前 AgentState 中的用户消息与运行配置。 2026-09-04 21:01:22 | INFO | [clarify_with_user] 3-18 [research_1788519682] ┌─ INPUT [PAIR=NODE.clarify_with_user:research_1788519682] | state_keys=['messages', 'supervisor_messages', 'raw_notes', 'notes'] | messages=HumanMessage=1 2026-09-04 21:01:22 | INFO | [clarify_with_user] 3-19 [research_1788519682] ENTER | state_keys=['messages', 'supervisor_messages', 'raw_notes', 'notes'] | messages=HumanMessage=1 2026-09-04 21:01:22 | INFO | [clarify_with_user] 3-20 [research_1788519682] CONFIG | allow_clarification=False 2026-09-04 21:01:22 | INFO | [clarify_with_user] 3-21 [research_1788519682] SKIP LLM | clarification disabled 2026-09-04 21:01:22 | INFO | [clarify_with_user] 3-22 [research_1788519682] ROUTE -> write_research_brief 2026-09-04 21:01:22 | INFO | [clarify_with_user] 3-23 [research_1788519682] 解释：节点输出：不调用 LLM，不修改 state，直接告诉 LangGraph 下一跳是 write_research_brief。 2026-09-04 21:01:22 | INFO | [clarify_with_user] 3-24 [research_1788519682] └─ OUTPUT [PAIR=NODE.clarify_with_user:research_1788519682] | Command(goto=write_research_brief) | state_update=none
class AgentInputState(MessagesState):
"""InputState is only 'messages'."""
class AgentState(MessagesState):
"""Main agent state containing messages and research data."""
supervisor_messages: Annotated[list[MessageLikeRepresentation], override_reducer]
research_brief: Optional[str]
raw_notes: Annotated[list[str], override_reducer] = []
notes: Annotated[list[str], override_reducer] = []
final_report: str
2026-09-04 21:01:22 | INFO | [MAIN GRAPH] 3-78 [research_1788519682] 解释：收到 chunk 时，对应的外层 Graph 节点已经执行完并提交了 update；这里看到的是节点执行后的结果，不是 Service 在这里触发该节点。 2026-09-04 21:01:22 | INFO | [MAIN GRAPH] 3-06 [research_1788519682] CHUNK 1 returned | nodes=['clarify_with_user'] | wait=0.00s
return Command(goto="write_research_brief")
所以上面的notes中，因为这次没有update操作，虽然是 chunk.keys，但里面记录的是 刚刚经过的 node name。
2026-09-04 21:01:22 | INFO | [MAIN GRAPH] 3-82 [research_1788519682] FLOW | 前因：Graph 已完成 chunk 1 对应的外层节点并返回 state update | 当前：Service 读取这个 chunk，并把 node update 翻译成客户端 SSE event | 下一步：yield SSE；处理完当前 chunk 后，再等待 Graph 的下一个 update 2026-09-04 21:01:22 | INFO | [REST] 1-19 [research_1788519682] SSE -> type=api_call | stage=ResearchStage.INITIALIZATION
2026-09-04 21:01:22 | INFO | [MAIN GRAPH] 3-79 [research_1788519682] CHUNK ADAPTER | chunk=1 | entries=1 | action=translate node updates to client SSE 2026-09-04 21:01:22 | INFO | [MAIN GRAPH] 3-83 [research_1788519682] GRAPH PATH | START -> clarify_with_user | path_so_far=START -> clarify_with_user 2026-09-04 21:01:22 | INFO | [MAIN GRAPH] 3-80 [research_1788519682] 解释：内层 for 只是在遍历这个 chunk 里的 node update，并调用 Service adapter 转成 SSE；不会重新执行 LangGraph node。 2026-09-04 21:01:22 | INFO | [MAIN GRAPH] 3-07 [research_1788519682] PROCESS outer-node update | node=clarify_with_user | chunk=1 | data_type=NoneType
2026-09-04 21:01:22 | INFO | [NODE VIEW] 2-32 [research_1788519682] 解释：Service 节点适配器输入：接收 Main Graph 的 node update，并把它转换成前端可理解的 StreamingEvent。 2026-09-04 21:01:22 | INFO | [NODE VIEW] 2-33 [research_1788519682] ┌─ INPUT [PAIR=SERVICE.process_node:484c5b5] | node=clarify_with_user | chunk=1 | data_type=NoneType | keys=none 2026-09-04 21:01:22 | INFO | [NODE VIEW] 2-39 [research_1788519682] node=clarify_with_user | data_type=NoneType | keys=none 2026-09-04 21:01:22 | INFO | [NODE VIEW] 2-41 [research_1788519682] raw=None 2026-09-04 21:01:22 | INFO | [NODE VIEW] 2-34 [research_1788519682] 解释：Service 节点适配器输出：Graph node update 已转成一个 stage_update SSE 事件；Graph state 本身没有在这里被修改。 2026-09-04 21:01:22 | INFO | [NODE VIEW] 2-35 [research_1788519682] └─ OUTPUT [PAIR=SERVICE.process_node:484c5b5] | StreamingEvent(type=stage_update, stage=ResearchStage.CLARIFICATION) | content_chars=121
2026-09-04 21:01:22 | INFO | [SERVICE] 2-12 [research_1788519682] YIELD event | node=clarify_with_user | type=stage_update | stage=ResearchStage.CLARIFICATION | processing=0.000s 2026-09-04 21:01:22 | INFO | [REST] 1-19 [research_1788519682] SSE -> type=stage_update | stage=ResearchStage.CLARIFICATION 2026-09-04 21:01:22 | INFO | [MAIN GRAPH] 3-81 [research_1788519682] FLOW | 前因：chunk 1 中的 node update 已完成 SSE 转换/发送 | 当前：当前 chunk 的 Service adapter 工作结束 | 下一步：async for 回到 astream，等待 Graph 继续执行并返回下一个 chunk
2026-09-04 21:01:22 | INFO | [MAIN GRAPH] 3-37 [research_1788519682] 解释：Main Graph 节点 write_research_brief：把原始用户问题改写成结构化 Research Brief，并初始化 Supervisor 的上下文。 2026-09-04 21:01:22 | INFO | [MAIN GRAPH] 3-38 [research_1788519682] ────────────── NODE write_research_brief ────────────── 2026-09-04 21:01:22 | INFO | [write_research_brief] 3-39 [research_1788519682] 解释：节点输入：Main Graph 当前 messages；这是生成 Research Brief 的原材料。 2026-09-04 21:01:22 | INFO | [write_research_brief] 3-40 [research_1788519682] ┌─ INPUT [PAIR=NODE.write_research_brief:research_1788519682] | messages=HumanMessage=1 | message_buffer=Human: 请研究一下长期恋爱关系中，哪些因素最影响双方的满意度和稳定性，并给出有研究依据的结论。 2026-09-04 21:01:22 | INFO | [write_research_brief] 3-41 [research_1788519682] ENTER | messages=HumanMessage=1
2026-09-04 21:01:22 | INFO | [LLM] 3-42 [research_1788519682] 解释：LLM 输入：用户对话 + 日期 + Research Brief 生成指令。 2026-09-04 21:01:22 | INFO | [LLM] 3-43 [research_1788519682] ┌─ INPUT [PAIR=LLM.research_brief:research_1788519682] | model=claude-sonnet-4-6 | prompt_chars=1994 | prompt=You will be given a set of messages that have been exchanged so far between yourself and the user. Your job is to translate these messages into a more detailed and concrete research question that will be used to guide the research. The messages that have been … 2026-09-04 21:01:22 | INFO | [LLM] 3-44 [research_1788519682] CALL research-brief model | model=claude-sonnet-4-6 | prompt_chars=1994 2026-09-04 21:01:38 | INFO | [LLM] 3-45 [research_1788519682] RETURN research brief | duration=16.56s | brief_chars=746 | brief=我想深入了解长期恋爱关系（如长期伴侣关系、婚姻或同居关系，关系持续时间通常在数年以上）中，哪些核心因素最显著地影响双方的关系满意度（relationship satisfaction）和关系稳定性（relationship stability）。具体请研究以下维度： 1. **心理与个性因素**：如依恋风格（attachment style）、人格特质（如大五人格）、自尊心、情绪调节能力等对满意度和稳定性的影响。 2. **沟通与冲突处理**：如沟通质量、冲突解决方式（建设性 vs 破坏性）、积极倾听等因素的作用。 3. **亲密感与承诺感**：包括情感亲密度（emotional intima… 2026-09-04 21:01:38 | INFO | [LLM] 3-46 [research_1788519682] 解释：LLM 输出：结构化 ResearchQuestion，其中 research_brief 将成为 Supervisor 的核心任务说明。 2026-09-04 21:01:38 | INFO | [LLM] 3-47 [research_1788519682] └─ OUTPUT [PAIR=LLM.research_brief:research_1788519682] | ResearchQuestion.research_brief chars=746 | value=我想深入了解长期恋爱关系（如长期伴侣关系、婚姻或同居关系，关系持续时间通常在数年以上）中，哪些核心因素最显著地影响双方的关系满意度（relationship satisfaction）和关系稳定性（relationship stability）。具体请研究以下维度： 1. **心理与个性因素**：如依恋风格（attachment style）、人格特质（如大五人格）、自尊心、情绪调节能力等对满意度和稳定性的影响。 2. **沟通与冲突处理**：如沟通质量、冲突解决方式（建设性 vs 破坏性）、积极倾听等因素的作用。 3. **亲密感与承诺感**：包括情感亲密度（emotional intimacy）、性亲密度（sexual inti…
2026-09-04 21:01:38 | INFO | [write_research_brief] 3-48 [research_1788519682] INIT supervisor_messages | SystemMessage + HumanMessage(research_brief) 2026-09-04 21:01:38 | INFO | [write_research_brief] 3-49 [research_1788519682] ROUTE -> research_supervisor 2026-09-04 21:01:38 | INFO | [write_research_brief] 3-50 [research_1788519682] 解释：节点输出：把 research_brief 写入 state，同时重置 supervisor_messages，然后进入整个 Supervisor 子图。 2026-09-04 21:01:38 | INFO | [write_research_brief] 3-51 [research_1788519682] └─ OUTPUT [PAIR=NODE.write_research_brief:research_1788519682] | Command(goto=research_supervisor) | research_brief_chars=746 | supervisor_messages=SystemMessage+HumanMessage
2026-09-04 21:01:38 | INFO | [MAIN GRAPH] 3-78 [research_1788519682] 解释：收到 chunk 时，对应的外层 Graph 节点已经执行完并提交了 update；这里看到的是节点执行后的结果，不是 Service 在这里触发该节点。 2026-09-04 21:01:38 | INFO | [MAIN GRAPH] 3-06 [research_1788519682] CHUNK 2 returned | nodes=['write_research_brief'] | wait=16.56s 2026-09-04 21:01:38 | INFO | [MAIN GRAPH] 3-82 [research_1788519682] FLOW | 前因：Graph 已完成 chunk 2 对应的外层节点并返回 state update | 当前：Service 读取这个 chunk，并把 node update 翻译成客户端 SSE event | 下一步：yield SSE；处理完当前 chunk 后，再等待 Graph 的下一个 update 2026-09-04 21:01:38 | INFO | [REST] 1-19 [research_1788519682] SSE -> type=api_call | stage=ResearchStage.CLARIFICATION 2026-09-04 21:01:38 | INFO | [MAIN GRAPH] 3-79 [research_1788519682] CHUNK ADAPTER | chunk=2 | entries=1 | action=translate node updates to client SSE 2026-09-04 21:01:38 | INFO | [MAIN GRAPH] 3-83 [research_1788519682] GRAPH PATH | clarify_with_user -> write_research_brief | path_so_far=START -> clarify_with_user -> write_research_brief 2026-09-04 21:01:38 | INFO | [MAIN GRAPH] 3-80 [research_1788519682] 解释：内层 for 只是在遍历这个 chunk 里的 node update，并调用 Service adapter 转成 SSE；不会重新执行 LangGraph node。 2026-09-04 21:01:38 | INFO | [MAIN GRAPH] 3-07 [research_1788519682] PROCESS outer-node update | node=write_research_brief | chunk=2 | data_type=dict
2026-09-04 21:01:38 | INFO | [NODE VIEW] 2-32 [research_1788519682] 解释：Service 节点适配器输入：接收 Main Graph 的 node update，并把它转换成前端可理解的 StreamingEvent。 2026-09-04 21:01:38 | INFO | [NODE VIEW] 2-33 [research_1788519682] ┌─ INPUT [PAIR=SERVICE.process_node:3b3bd51] | node=write_research_brief | chunk=2 | data_type=dict | keys=research_brief, supervisor_messages 2026-09-04 21:01:38 | INFO | [NODE VIEW] 2-39 [research_1788519682] node=write_research_brief | data_type=dict | keys=research_brief, supervisor_messages 2026-09-04 21:01:38 | INFO | [NODE VIEW] 2-40 [research_1788519682] field=supervisor_messages | type=dict | size=2 | preview={"type": "override", "value": ["content='You are a research supervisor. Your job is to conduct research by calling the \"ConductResearch\" tool. For context, today\\'s date is Fri Sep 4, 2026.\\n\\n<Task>\\nYour focus is to call the \"Condu… 2026-09-04 21:01:38 | INFO | [NODE VIEW] 2-40 [research_1788519682] field=research_brief | type=str | size=746 | preview=我想深入了解长期恋爱关系（如长期伴侣关系、婚姻或同居关系，关系持续时间通常在数年以上）中，哪些核心因素最显著地影响双方的关系满意度（relationship satisfaction）和关系稳定性（relationship stability）。具体请研究以下维度： 1. **心理与个性因素**：如依恋风格（attachment style）、人格特质（如大五人格）、自尊心、情绪调节能力等对满意度和稳定性的影响。 2. **沟通与冲突处理**：如沟通质量、冲突解决方式（建设性… 2026-09-04 21:01:38 | INFO | [NODE VIEW] 2-34 [research_1788519682] 解释：Service 节点适配器输出：Graph node update 已转成一个 stage_update SSE 事件；Graph state 本身没有在这里被修改。 2026-09-04 21:01:38 | INFO | [NODE VIEW] 2-35 [research_1788519682] └─ OUTPUT [PAIR=SERVICE.process_node:3b3bd51] | StreamingEvent(type=stage_update, stage=ResearchStage.RESEARCH_BRIEF) | content_chars=836 2026-09-04 21:01:38 | INFO | [SERVICE] 2-12 [research_1788519682] YIELD event | node=write_research_brief | type=stage_update | stage=ResearchStage.RESEARCH_BRIEF | processing=0.001s 2026-09-04 21:01:38 | INFO | [REST] 1-19 [research_1788519682] SSE -> type=stage_update | stage=ResearchStage.RESEARCH_BRIEF 2026-09-04 21:01:38 | INFO | [MAIN GRAPH] 3-81 [research_1788519682] FLOW | 前因：chunk 2 中的 node update 已完成 SSE 转换/发送 | 当前：当前 chunk 的 Service adapter 工作结束 | 下一步：async for 回到 astream，等待 Graph 继续执行并返回下一个 chunk
2026-09-04 21:01:38 | INFO | [SUPERVISOR] 4-01 [research_1788519682] 解释：Supervisor 子图的思考节点：读取累计 supervisor_messages，决定调用 think_tool、ConductResearch 或 ResearchComplete。 2026-09-04 21:01:38 | INFO | [SUPERVISOR] 4-02 [research_1788519682] ────────────── NODE supervisor ────────────── 2026-09-04 21:01:38 | INFO | [supervisor] 4-03 [research_1788519682] 解释：节点输入：Supervisor 到目前为止的全部对话/ToolMessage，以及当前研究迭代次数。 2026-09-04 21:01:38 | INFO | [supervisor] 4-04 [research_1788519682] ┌─ INPUT [PAIR=NODE.supervisor:bb5e6d0] | iteration=0 | messages=SystemMessage=1, HumanMessage=1 | message_count=2 2026-09-04 21:01:38 | INFO | [supervisor] 4-05 [research_1788519682] ENTER | iteration=0 | messages=SystemMessage=1, HumanMessage=1 2026-09-04 21:01:38 | INFO | [supervisor] 4-06 [research_1788519682] TOOLS bound=['ConductResearch', 'ResearchComplete', 'think_tool']
2026-09-04 21:01:38 | INFO | [LLM] 4-07 [research_1788519682] 解释：LLM 输入：Supervisor 消息历史 + 可调用工具定义；模型的主要输出是下一步 tool_calls。 2026-09-04 21:01:38 | INFO | [LLM] 4-08 [research_1788519682] ┌─ INPUT [PAIR=LLM.supervisor:bb5e6d0] | model=claude-sonnet-4-6 | messages=2 | tools=['ConductResearch', 'ResearchComplete', 'think_tool'] 2026-09-04 21:01:38 | INFO | [LLM] 4-09 [research_1788519682] CALL supervisor | model=claude-sonnet-4-6 | messages=2 2026-09-04 21:01:46 | INFO | [LLM] 4-10 [research_1788519682] RETURN supervisor | duration=8.06s | type=AIMessage, model=claude-sonnet-4-6, stop=tool_use, usage={"input_tokens": 2035, "output_tokens": 298, "total_tokens": 2333, "input_token_details": {"cache_read": 0, "cache_creation": 0, "ephemeral_5m_input_tokens": 0, "ephemeral_1h_input_tokens": 0}}, content=[{"id": "toolu_01Wvsa1Mzwrz5FBFQ5xVeZ8j", "caller": {"type": "direct"}, "input": {"reflection": "The user wants a comprehensive, academically rigorous research report on factors af…, tool_calls=['think_tool'] 2026-09-04 21:01:46 | INFO | [LLM] 4-11 [research_1788519682] 解释：LLM 输出：AIMessage，重点看 tool_calls；Supervisor 节点不会自己执行工具，只把它们交给 supervisor_tools。 2026-09-04 21:01:46 | INFO | [LLM] 4-12 [research_1788519682] └─ OUTPUT [PAIR=LLM.supervisor:bb5e6d0] | type=AIMessage, model=claude-sonnet-4-6, stop=tool_use, usage={"input_tokens": 2035, "output_tokens": 298, "total_tokens": 2333, "input_token_details": {"cache_read": 0, "cache_creation": 0, "ephemeral_5m_input_tokens": 0, "ephemeral_1h_input_tokens": 0}}, content=[{"id": "toolu_01Wvsa1Mzwrz5FBFQ5xVeZ8j", "caller": {"type": "direct"}, "input": {"reflection": "The user wants a comprehensive, academically rigorous research report on factors af…, tool_calls=['think_tool']
《值得仔细研究研究》AIMessage= Supervisor LLM 这一轮思考后的输出消息。它随后会被supervisor_tools节点读取。
AIMessage( type="AIMessage", model="claude-sonnet-4-6", stop="tool_use", usage={ "input_tokens": 2200, # 示例 "output_tokens": 298, # 你之前日志里这一轮大约是这个量级 "total_tokens": 2498, "input_token_details": { "cache_read": 0, "cache_creation": 0, "ephemeral_5m_input_tokens": 0, "ephemeral_1h_input_tokens": 0 } }, content=[ # Claude 喜欢的格式 { "id": "toolu_THINK_001", "caller": { "type": "direct" }, "input": { "reflection": "The user wants a rigorous research report. " "I should divide the problem into separate research areas, " "including psychological/personality factors and " "relationship/communication factors." }, "name": "think_tool", "type": "tool_use" } ], tool_calls=[ # Langchain喜欢的格式 { "name": "think_tool", "args": { "reflection": "The user wants a rigorous research report. " "I should divide the problem into separate research areas, " "including psychological/personality factors and " "relationship/communication factors." }, "id": "toolu_THINK_001", "type": "tool_call" } ] )
2026-09-04 21:01:46 | INFO | [supervisor] 4-13 [research_1788519682] TOOL CALL 1 | name=think_tool | id=toolu_01Wvsa1Mzwrz5FBFQ5xVeZ8j | args: 2026-09-04 21:01:46 | INFO | [supervisor] 4-13 [research_1788519682] │ { 2026-09-04 21:01:46 | INFO | [supervisor] 4-13 [research_1788519682] │ "reflection": "The user wants a comprehensive, academically rigorous research report on factors affecting relationship satisfaction and stability in long-term romantic relationships. The request covers 6 distinct dimensions:\n\n1. Psychological & personality factors\n2. Communication & conflict resolution\n3. Intimacy & commitment\n4. Social & external factors\n5. Relationship maintenance behaviors\n6. Temporal dynamics\n\nThis is a complex, multi-dimensional research question. Given the 6 clear, independent dimensions, I should parallelize research across them. However, my hard limit is 2 parallel agents per iteration. Let me plan:\n\nRound 1: I'll cover dimensions 1 & 2 in parallel (psychological factors + communication)\nRound 2: I'll cover dimensions 3 & 4 in parallel (intimacy/commitment + social factors)\nRound 3: I'll cover dimensions 5 & 6 in parallel (maintenance behaviors + temporal dynamics)\n\nThis gives 3 rounds of research with 2 parallel agents each = 6 total ConductResearch calls. This seems appropriate for the depth requested.\n\nLet me start with Round 1." 2026-09-04 21:01:46 | INFO | [supervisor] 4-13 [research_1788519682] │ } 2026-09-04 21:01:46 | INFO | [supervisor] 4-14 [research_1788519682] ROUTE -> supervisor_tools | next_iteration=1 2026-09-04 21:01:46 | INFO | [supervisor] 4-15 [research_1788519682] 解释：节点输出：把本次 AIMessage 追加进 supervisor_messages、迭代计数 +1，并进入 supervisor_tools 执行/分发工具。 2026-09-04 21:01:46 | INFO | [supervisor] 4-16 [research_1788519682] └─ OUTPUT [PAIR=NODE.supervisor:bb5e6d0] | Command(goto=supervisor_tools) | supervisor_messages+=AIMessage | research_iterations=1 | tool_calls=['think_tool']
2026-09-04 21:01:46 | INFO | [SUPERVISOR] 4-17 [research_1788519682] ────────────── NODE supervisor_tools ────────────── 2026-09-04 21:01:46 | INFO | [SUPERVISOR] 4-18 [research_1788519682] 解释：Supervisor 工具节点：检查退出条件，然后执行 think_tool 或把 ConductResearch 分派给一个/多个 Researcher 子图。 2026-09-04 21:01:46 | INFO | [supervisor_tools] 4-19 [research_1788519682] 解释：节点输入：上一轮 Supervisor AIMessage 中的 tool_calls，以及当前迭代上限。
2026-09-04 21:01:46 | INFO | [supervisor_tools] 4-20 [research_1788519682] ┌─ INPUT [PAIR=NODE.supervisor_tools:f04375c] | iteration=1/1 | tool_calls=['think_tool'] 2026-09-04 21:01:46 | INFO | [supervisor_tools] 4-21 [research_1788519682] ENTER | iteration=1/1 | tool_calls=['think_tool'] 2026-09-04 21:01:46 | INFO | [supervisor_tools] 4-22 [research_1788519682] EXIT CHECK | exceeded=False | no_tool_calls=False | ResearchComplete=False
2026-09-04 21:01:46 | INFO | [think_tool] 6-01 [research_1788519682] 解释：工具输入：Supervisor 把自己的策略反思文字传给 think_tool；这个工具不访问外部系统。 2026-09-04 21:01:46 | INFO | [think_tool] 6-02 [research_1788519682] ┌─ INPUT [PAIR=TOOL.think_tool:toolu_01Wvsa1Mzwrz5FBFQ5xVeZ8j] | reflection=The user wants a comprehensive, academically rigorous research report on factors affecting relationship satisfaction and stability in long-term romantic relationships. The request covers 6 distinct dimensions: 1. Psychological & personality factors 2. Communication & conflict resolution 3. Intimacy & commitment 4. Soci… 2026-09-04 21:01:46 | INFO | [think_tool] 6-03 [research_1788519682] EXECUTE supervisor reflection | call_id=toolu_01Wvsa1Mzwrz5FBFQ5xVeZ8j | reflection=The user wants a comprehensive, academically rigorous research report on factors affecting relationship satisfaction and stability in long-term romantic relationships. The request covers 6 distinct dimensions: 1. Psychological & personality factors 2. Communic… 2026-09-04 21:01:46 | INFO | [think_tool] 6-04 [research_1788519682] 解释：工具输出：生成与原 tool_call_id 对应的 ToolMessage，下一轮 Supervisor 会把它作为上下文再次看到。 2026-09-04 21:01:46 | INFO | [think_tool] 6-05 [research_1788519682] └─ OUTPUT [PAIR=TOOL.think_tool:toolu_01Wvsa1Mzwrz5FBFQ5xVeZ8j] | ToolMessage(name=think_tool, tool_call_id=toolu_01Wvsa1Mzwrz5FBFQ5xVeZ8j) | content=Reflection recorded: The user wants a comprehensive, academically rigorous research report on factors affecting relationship satisfaction and stability in long-term romantic relationships. The request covers 6 distinct dimensions: 1. Psychol…
2026-09-04 21:01:46 | INFO | [supervisor_tools] 4-33 [research_1788519682] ROUTE -> supervisor | returning_tool_messages=1 | raw_notes_added=False 2026-09-04 21:01:46 | INFO | [supervisor_tools] 4-34 [research_1788519682] 解释：节点输出：工具执行结果已转成 ToolMessage 写回 state，控制权回到 supervisor 进行下一轮判断。 2026-09-04 21:01:46 | INFO | [supervisor_tools] 4-35 [research_1788519682] └─ OUTPUT [PAIR=NODE.supervisor_tools:f04375c] | Command(goto=supervisor) | supervisor_messages+=ToolMessage x1 | raw_notes_added=False
2026-09-04 21:01:46 | INFO | [SUPERVISOR] 4-01 [research_1788519682] 解释：Supervisor 子图的思考节点：读取累计 supervisor_messages，决定调用 think_tool、ConductResearch 或 ResearchComplete。 2026-09-04 21:01:46 | INFO | [SUPERVISOR] 4-02 [research_1788519682] ────────────── NODE supervisor ────────────── 2026-09-04 21:01:46 | INFO | [supervisor] 4-03 [research_1788519682] 解释：节点输入：Supervisor 到目前为止的全部对话/ToolMessage，以及当前研究迭代次数。 2026-09-04 21:01:46 | INFO | [supervisor] 4-04 [research_1788519682] ┌─ INPUT [PAIR=NODE.supervisor:a18d497] | iteration=1 | messages=SystemMessage=1, HumanMessage=1, AIMessage=1, ToolMessage=1 | message_count=4
supervisor_messages = [ # ① SystemMessage = 1 SystemMessage( content="Supervisor 的工作规则..." ), # ② HumanMessage = 1 HumanMessage( content="整理后的 research_brief..." ), # ③ AIMessage = 1 AIMessage( tool_calls=[ { "name": "think_tool", "args": { "reflection": "Supervisor 刚才的规划..." }, "id": "toolu_..." } ] ), # ④ ToolMessage = 1 ToolMessage( content="Reflection recorded: Supervisor 刚才的规划...", name="think_tool", tool_call_id="toolu_..." ) ]
2026-09-04 21:01:46 | INFO | [supervisor] 4-05 [research_1788519682] ENTER | iteration=1 | messages=SystemMessage=1, HumanMessage=1, AIMessage=1, ToolMessage=1 2026-09-04 21:01:46 | INFO | [supervisor] 4-06 [research_1788519682] TOOLS bound=['ConductResearch', 'ResearchComplete', 'think_tool']
2026-09-04 21:01:46 | INFO | [LLM] 4-07 [research_1788519682] 解释：LLM 输入：Supervisor 消息历史 + 可调用工具定义；模型的主要输出是下一步 tool_calls。 2026-09-04 21:01:46 | INFO | [LLM] 4-08 [research_1788519682] ┌─ INPUT [PAIR=LLM.supervisor:a18d497] | model=claude-sonnet-4-6 | messages=4 | tools=['ConductResearch', 'ResearchComplete', 'think_tool'] 2026-09-04 21:01:46 | INFO | [LLM] 4-09 [research_1788519682] CALL supervisor | model=claude-sonnet-4-6 | messages=4 2026-09-04 21:01:56 | INFO | [LLM] 4-10 [research_1788519682] RETURN supervisor | duration=9.31s | type=AIMessage, model=claude-sonnet-4-6, stop=tool_use, usage={"input_tokens": 2594, "output_tokens": 478, "total_tokens": 3072, "input_token_details": {"cache_read": 0, "cache_creation": 0, "ephemeral_5m_input_tokens": 0, "ephemeral_1h_input_tokens": 0}}, content=[{"id": "toolu_01A1rC1FGi8aFJaRP25BVxW2", "caller": {"type": "direct"}, "input": {"research_topic": "Academic research on psychological and personality factors affecting long-term …, tool_calls=['ConductResearch', 'ConductResearch'] 2026-09-04 21:01:56 | INFO | [LLM] 4-11 [research_1788519682] 解释：LLM 输出：AIMessage，重点看 tool_calls；Supervisor 节点不会自己执行工具，只把它们交给 supervisor_tools。 2026-09-04 21:01:56 | INFO | [LLM] 4-12 [research_1788519682] └─ OUTPUT [PAIR=LLM.supervisor:a18d497] | type=AIMessage, model=claude-sonnet-4-6, stop=tool_use, usage={"input_tokens": 2594, "output_tokens": 478, "total_tokens": 3072, "input_token_details": {"cache_read": 0, "cache_creation": 0, "ephemeral_5m_input_tokens": 0, "ephemeral_1h_input_tokens": 0}}, content=[{"id": "toolu_01A1rC1FGi8aFJaRP25BVxW2", "caller": {"type": "direct"}, "input": {"research_topic": "Academic research on psychological and personality factors affecting long-term …, tool_calls=['ConductResearch', 'ConductResearch']
AIMessage( type="AIMessage", model="claude-sonnet-4-6", stop="tool_use", usage={ "input_tokens": 2594, "output_tokens": 478, "total_tokens": 3072, "input_token_details": { "cache_read": 0, "cache_creation": 0, "ephemeral_5m_input_tokens": 0, "ephemeral_1h_input_tokens": 0 } }, content=[ { "id": "toolu_01A1rC1FGi8aFJaRP25BVxW2", "caller": { "type": "direct" }, "input": { "research_topic": "Academic research on psychological and personality " "factors affecting long-term relationship stability, " "including attachment style, emotional regulation, " "personality traits, and individual differences." }, "name": "ConductResearch", "type": "tool_use" }, { "id": "toolu_RESEARCH_002", "caller": { "type": "direct" }, "input": { "research_topic": "Academic research on interpersonal and relationship " "factors affecting long-term relationship stability, " "including communication patterns, conflict resolution, " "trust, commitment, and relationship satisfaction." }, "name": "ConductResearch", "type": "tool_use" } ], tool_calls=[ { "name": "ConductResearch", "args": { "research_topic": "Academic research on psychological and personality " "factors affecting long-term relationship stability, " "including attachment style, emotional regulation, " "personality traits, and individual differences." }, "id": "toolu_01A1rC1FGi8aFJaRP25BVxW2", "type": "tool_call" }, { "name": "ConductResearch", "args": { "research_topic": "Academic research on interpersonal and relationship " "factors affecting long-term relationship stability, " "including communication patterns, conflict resolution, " "trust, commitment, and relationship satisfaction." }, "id": "toolu_RESEARCH_002", "type": "tool_call" } ] )
2026-09-04 21:01:56 | INFO | [supervisor] 4-13 [research_1788519682] TOOL CALL 1 | name=ConductResearch | id=toolu_01A1rC1FGi8aFJaRP25BVxW2 | args: 2026-09-04 21:01:56 | INFO | [supervisor] 4-13 [research_1788519682] │ { 2026-09-04 21:01:56 | INFO | [supervisor] 4-13 [research_1788519682] │ "research_topic": "Academic research on psychological and personality factors affecting long-term romantic relationship satisfaction and stability. Specifically: (1) Attachment styles (secure, anxious, avoidant) and their effects on relationship satisfaction and stability over multiple years; (2) Big Five personality traits (especially neuroticism, agreeableness, conscientiousness) and relationship outcomes; (3) Self-esteem and its relationship to partner satisfaction; (4) Emotion regulation abilities and how they predict relationship quality and dissolution. Focus on peer-reviewed studies published in journals such as Journal of Personality and Social Psychology, Journal of Marriage and Family, Personal Relationships, Psychological Bulletin, and similar high-quality outlets. Distinguish between correlational and causal findings. Provide direct DOI links or journal URLs where possible. Please gather specific study findings, effect sizes, and key author names." 2026-09-04 21:01:56 | INFO | [supervisor] 4-13 [research_1788519682] │ } 2026-09-04 21:01:56 | INFO | [supervisor] 4-13 [research_1788519682] TOOL CALL 2 | name=ConductResearch | id=toolu_01RKnPjh1cCECw7Rd37WX7gi | args: 2026-09-04 21:01:56 | INFO | [supervisor] 4-13 [research_1788519682] │ { 2026-09-04 21:01:56 | INFO | [supervisor] 4-13 [research_1788519682] │ "research_topic": "Academic research on communication quality and conflict resolution strategies in long-term romantic relationships (marriages, cohabiting partnerships lasting several years or more) and their effects on relationship satisfaction and stability. Specifically: (1) Communication quality (positive vs. negative communication patterns) and relationship satisfaction; (2) Constructive vs. destructive conflict resolution styles, including the \"demand-withdraw\" pattern; (3) Active listening and its role in relationship quality; (4) John Gottman's research on the \"Four Horsemen\" (criticism, contempt, defensiveness, stonewalling) and relationship dissolution; (5) Behavioral observation studies and longitudinal findings. Focus on peer-reviewed empirical studies published in top journals (Journal of Personality and Social Psychology, Journal of Marriage and Family, Journal of Consulting and Clinical Psychology, Personal Relationships). Include specific study findings, effect sizes, author names, and direct DOI or journal links. Distinguish between correlational and causal findings." 2026-09-04 21:01:56 | INFO | [supervisor] 4-13 [research_1788519682] │ } 2026-09-04 21:01:56 | INFO | [supervisor] 4-14 [research_1788519682] ROUTE -> supervisor_tools | next_iteration=2 2026-09-04 21:01:56 | INFO | [supervisor] 4-15 [research_1788519682] 解释：节点输出：把本次 AIMessage 追加进 supervisor_messages、迭代计数 +1，并进入 supervisor_tools 执行/分发工具。 2026-09-04 21:01:56 | INFO | [supervisor] 4-16 [research_1788519682] └─ OUTPUT [PAIR=NODE.supervisor:a18d497] | Command(goto=supervisor_tools) | supervisor_messages+=AIMessage | research_iterations=2 | tool_calls=['ConductResearch', 'ConductResearch']
2026-09-04 21:01:56 | INFO | [SUPERVISOR] 4-17 [research_1788519682] ────────────── NODE supervisor_tools ────────────── 2026-09-04 21:01:56 | INFO | [SUPERVISOR] 4-18 [research_1788519682] 解释：Supervisor 工具节点：检查退出条件，然后执行 think_tool 或把 ConductResearch 分派给一个/多个 Researcher 子图。 2026-09-04 21:01:56 | INFO | [supervisor_tools] 4-19 [research_1788519682] 解释：节点输入：上一轮 Supervisor AIMessage 中的 tool_calls，以及当前迭代上限。 2026-09-04 21:01:56 | INFO | [supervisor_tools] 4-20 [research_1788519682] ┌─ INPUT [PAIR=NODE.supervisor_tools:d9db1e1] | iteration=2/1 | tool_calls=['ConductResearch', 'ConductResearch'] 2026-09-04 21:01:56 | INFO | [supervisor_tools] 4-21 [research_1788519682] ENTER | iteration=2/1 | tool_calls=['ConductResearch', 'ConductResearch'] 2026-09-04 21:01:56 | INFO | [supervisor_tools] 4-22 [research_1788519682] EXIT CHECK | exceeded=True | no_tool_calls=False | ResearchComplete=False 2026-09-04 21:01:56 | INFO | [supervisor_tools] 4-23 [research_1788519682] ROUTE -> END | reason=max_iterations | notes=1 2026-09-04 21:01:56 | INFO | [supervisor_tools] 4-24 [research_1788519682] 解释：节点输出：命中 Supervisor 退出条件，不再执行本轮工具；整理已有 ToolMessage 为 notes 后结束 Supervisor 子图。 2026-09-04 21:01:56 | INFO | [supervisor_tools] 4-25 [research_1788519682] └─ OUTPUT [PAIR=NODE.supervisor_tools:d9db1e1] | Command(goto=END) | reason=max_iterations | notes=1 | research_brief_chars=746
2026-09-04 21:01:56 | INFO | [MAIN GRAPH] 3-78 [research_1788519682] 解释：收到 chunk 时，对应的外层 Graph 节点已经执行完并提交了 update；这里看到的是节点执行后的结果，不是 Service 在这里触发该节点。 2026-09-04 21:01:56 | INFO | [MAIN GRAPH] 3-06 [research_1788519682] CHUNK 3 returned | nodes=['research_supervisor'] | wait=17.38s 2026-09-04 21:01:56 | INFO | [MAIN GRAPH] 3-82 [research_1788519682] FLOW | 前因：Graph 已完成 chunk 3 对应的外层节点并返回 state update | 当前：Service 读取这个 chunk，并把 node update 翻译成客户端 SSE event | 下一步：yield SSE；处理完当前 chunk 后，再等待 Graph 的下一个 update 2026-09-04 21:01:56 | INFO | [REST] 1-19 [research_1788519682] SSE -> type=api_call | stage=ResearchStage.RESEARCH_BRIEF 2026-09-04 21:01:56 | INFO | [REST] 1-19 [research_1788519682] SSE -> type=heartbeat | stage=ResearchStage.RESEARCH_BRIEF # ----> 这里是个错误设计，没有考虑到 supervisor_tool里内部的运行
2026-09-04 21:01:56 | INFO | [MAIN GRAPH] 3-79 [research_1788519682] CHUNK ADAPTER | chunk=3 | entries=1 | action=translate node updates to client SSE 2026-09-04 21:01:56 | INFO | [MAIN GRAPH] 3-83 [research_1788519682] GRAPH PATH | write_research_brief -> research_supervisor | path_so_far=START -> clarify_with_user -> write_research_brief -> research_supervisor 2026-09-04 21:01:56 | INFO | [MAIN GRAPH] 3-80 [research_1788519682] 解释：内层 for 只是在遍历这个 chunk 里的 node update，并调用 Service adapter 转成 SSE；不会重新执行 LangGraph node。 2026-09-04 21:01:56 | INFO | [MAIN GRAPH] 3-07 [research_1788519682] PROCESS outer-node update | node=research_supervisor | chunk=3 | data_type=dict
2026-09-04 21:01:56 | INFO | [NODE VIEW] 2-32 [research_1788519682] 解释：Service 节点适配器输入：接收 Main Graph 的 node update，并把它转换成前端可理解的 StreamingEvent。 2026-09-04 21:01:56 | INFO | [NODE VIEW] 2-33 [research_1788519682] ┌─ INPUT [PAIR=SERVICE.process_node:17442ac] | node=research_supervisor | chunk=3 | data_type=dict | keys=notes, raw_notes, research_brief, supervisor_messages 2026-09-04 21:01:56 | INFO | [NODE VIEW] 2-39 [research_1788519682] node=research_supervisor | data_type=dict | keys=notes, raw_notes, research_brief, supervisor_messages 2026-09-04 21:01:56 | INFO | [NODE VIEW] 2-40 [research_1788519682] field=supervisor_messages | type=list | size=5 | preview=["content='You are a research supervisor. Your job is to conduct research by calling the \"ConductResearch\" tool. For context, today\\'s date is Fri Sep 4, 2026.\\n\\n<Task>\\nYour focus is to call the \"ConductResearch\" tool to conduct r… 2026-09-04 21:01:56 | INFO | [NODE VIEW] 2-40 [research_1788519682] field=research_brief | type=str | size=746 | preview=我想深入了解长期恋爱关系（如长期伴侣关系、婚姻或同居关系，关系持续时间通常在数年以上）中，哪些核心因素最显著地影响双方的关系满意度（relationship satisfaction）和关系稳定性（relationship stability）。具体请研究以下维度： 1. **心理与个性因素**：如依恋风格（attachment style）、人格特质（如大五人格）、自尊心、情绪调节能力等对满意度和稳定性的影响。 2. **沟通与冲突处理**：如沟通质量、冲突解决方式（建设性… 2026-09-04 21:01:56 | INFO | [NODE VIEW] 2-40 [research_1788519682] field=notes | type=list | size=1 | preview=["Reflection recorded: The user wants a comprehensive, academically rigorous research report on factors affecting relationship satisfaction and stability in long-term romantic relationships. The request covers 6 distinct dimensions:\n\n1. P… 2026-09-04 21:01:56 | INFO | [NODE VIEW] 2-40 [research_1788519682] field=raw_notes | type=list | size=0 | preview=[] 2026-09-04 21:01:56 | INFO | [NODE VIEW] 2-34 [research_1788519682] 解释：Service 节点适配器输出：Graph node update 已转成一个 stage_update SSE 事件；Graph state 本身没有在这里被修改。 2026-09-04 21:01:56 | INFO | [NODE VIEW] 2-35 [research_1788519682] └─ OUTPUT [PAIR=SERVICE.process_node:17442ac] | StreamingEvent(type=stage_update, stage=ResearchStage.RESEARCH_EXECUTION) | content_chars=67
2026-09-04 21:01:56 | INFO | [SERVICE] 2-12 [research_1788519682] YIELD event | node=research_supervisor | type=stage_update | stage=ResearchStage.RESEARCH_EXECUTION | processing=0.001s 2026-09-04 21:01:56 | INFO | [REST] 1-19 [research_1788519682] SSE -> type=stage_update | stage=ResearchStage.RESEARCH_EXECUTION 2026-09-04 21:01:56 | INFO | [SERVICE] 2-13 [research_1788519682] BUILD supplementary supervisor SSE events | chunk=3 2026-09-04 21:01:56 | INFO | [SERVICE] 2-14 [research_1788519682] YIELD supervisor event | type=research_step | stage=ResearchStage.RESEARCH_PLANNING 2026-09-04 21:01:56 | INFO | [REST] 1-19 [research_1788519682] SSE -> type=research_step | stage=ResearchStage.RESEARCH_PLANNING 2026-09-04 21:01:56 | INFO | [SERVICE] 2-14 [research_1788519682] YIELD supervisor event | type=research_step | stage=ResearchStage.RESEARCH_PLANNING 2026-09-04 21:01:56 | INFO | [REST] 1-19 [research_1788519682] SSE -> type=research_step | stage=ResearchStage.RESEARCH_PLANNING 2026-09-04 21:01:56 | INFO | [SERVICE] 2-14 [research_1788519682] YIELD supervisor event | type=research_step | stage=ResearchStage.RESEARCH_ANALYSIS 2026-09-04 21:01:56 | INFO | [REST] 1-19 [research_1788519682] SSE -> type=research_step | stage=ResearchStage.RESEARCH_ANALYSIS 2026-09-04 21:01:56 | INFO | [SERVICE] 2-14 [research_1788519682] YIELD supervisor event | type=research_step | stage=ResearchStage.RESEARCH_SYNTHESIS 2026-09-04 21:01:56 | INFO | [REST] 1-19 [research_1788519682] SSE -> type=research_step | stage=ResearchStage.RESEARCH_SYNTHESIS
2026-09-04 21:01:56 | INFO | [MAIN GRAPH] 3-81 [research_1788519682] FLOW | 前因：chunk 3 中的 node update 已完成 SSE 转换/发送 | 当前：当前 chunk 的 Service adapter 工作结束 | 下一步：async for 回到 astream，等待 Graph 继续执行并返回下一个 chunk 2026-09-04 21:01:56 | INFO | [MAIN GRAPH] 3-52 [research_1788519682] 解释：Main Graph 最终报告节点：读取 research_brief + Supervisor 汇总的 notes，一次性生成最终面向用户的报告。 2026-09-04 21:01:56 | INFO | [MAIN GRAPH] 3-53 [research_1788519682] ────────────── NODE final_report_generation ────────────── 2026-09-04 21:01:56 | INFO | [final_report_generation] 3-54 [research_1788519682] 解释：节点输入：Supervisor 阶段留下的 notes（研究证据摘要）以及原始 research_brief。 2026-09-04 21:01:56 | INFO | [final_report_generation] 3-55 [research_1788519682] ┌─ INPUT [PAIR=NODE.final_report_generation:research_1788519682] | notes=1 | findings_chars=1078 | research_brief_chars=746 | findings_preview=Reflection recorded: The user wants a comprehensive, academically rigorous research report on factors affecting relationship satisfaction and stability in long-term romantic relationships. The request covers 6 distinct dimensions: 1. Psychological & personality factors 2. Communi… 2026-09-04 21:01:56 | INFO | [final_report_generation] 3-56 [research_1788519682] ENTER | notes=1 | findings_chars=1078 | brief_chars=746 2026-09-04 21:01:56 | INFO | [LLM] 3-57 [research_1788519682] 解释：LLM 输入：Research Brief + 原始用户消息 + 已收集 findings，要求生成最终完整报告。 2026-09-04 21:01:56 | INFO | [LLM] 3-58 [research_1788519682] ┌─ INPUT [PAIR=LLM.final_report:497790e] | model=claude-sonnet-4-6 | retry=0/3 | prompt_chars=6252 | findings_chars=1078 2026-09-04 21:01:56 | INFO | [LLM] 3-59 [research_1788519682] CALL final report | model=claude-sonnet-4-6 | retry=0/3 | prompt_chars=6252 | findings_chars=1078 2026-09-04 21:04:36 | INFO | [LLM] 3-60 [research_1788519682] RETURN final report | duration=160.04s | report_chars=8814 | preview=# 长期恋爱关系中影响满意度与稳定性的核心因素：综合学术研究报告 --- ## 概述 长期恋爱关系（包括婚姻、同居及持续数年的伴侣关系）是人类心理健康与社会福祉的核心组成部分。大量研究表明，高质量的亲密关系不仅与个体的心理健康、身体健康和寿命密切相关，更是人们生活满意度的重要预测因素。然而，维系一段长期、稳定且令双方满意的关系，并非易事——据统计，西方国家约40%至50%的婚姻以离婚告终，而更多关系在正式破裂前已陷入长期的不满与疏离。 理解哪些因素真正决定长期关系的质量，不仅具有重要的学术价值，更有深远的现实意义。本报告系统整合了发表于《人格与社会心理学杂志》（*Journal of Pers… 2026-09-04 21:04:36 | INFO | [LLM] 3-61 [research_1788519682] 解释：LLM 输出：最终报告正文 AIMessage。 2026-09-04 21:04:36 | INFO | [LLM] 3-62 [research_1788519682] └─ OUTPUT [PAIR=LLM.final_report:497790e] | report_chars=8814 | preview=# 长期恋爱关系中影响满意度与稳定性的核心因素：综合学术研究报告 --- ## 概述 长期恋爱关系（包括婚姻、同居及持续数年的伴侣关系）是人类心理健康与社会福祉的核心组成部分。大量研究表明，高质量的亲密关系不仅与个体的心理健康、身体健康和寿命密切相关，更是人们生活满意度的重要预测因素。然而，维系一段长期、稳定且令双方满意的关系，并非易事——据统计，西方国家约40%至50%的婚姻以离婚告终，而更多关系在正式破裂前已陷入长期的不满与疏离。 理解哪些因素真正决定长期关系的质量，不仅具有重要的学术价值，更有深远的现实意义。本报告系统整合了发表于《人格与社会心理学杂志》（*Journal of Personality and Social P… 2026-09-04 21:04:36 | INFO | [final_report_generation] 3-63 [research_1788519682] EXIT success | ROUTE -> END 2026-09-04 21:04:36 | INFO | [final_report_generation] 3-64 [research_1788519682] 解释：节点输出：把 final_report 写入 Main Graph state、清空 notes，并结束最外层 Graph。 2026-09-04 21:04:36 | INFO | [final_report_generation] 3-65 [research_1788519682] └─ OUTPUT [PAIR=NODE.final_report_generation:research_1788519682] | final_report_chars=8814 | messages+=AIMessage | notes=override([]) | ROUTE=END 2026-09-04 21:04:36 | INFO | [MAIN GRAPH] 3-78 [research_1788519682] 解释：收到 chunk 时，对应的外层 Graph 节点已经执行完并提交了 update；这里看到的是节点执行后的结果，不是 Service 在这里触发该节点。 2026-09-04 21:04:36 | INFO | [MAIN GRAPH] 3-06 [research_1788519682] CHUNK 4 returned | nodes=['final_report_generation'] | wait=160.05s 2026-09-04 21:04:36 | INFO | [MAIN GRAPH] 3-82 [research_1788519682] FLOW | 前因：Graph 已完成 chunk 4 对应的外层节点并返回 state update | 当前：Service 读取这个 chunk，并把 node update 翻译成客户端 SSE event | 下一步：yield SSE；处理完当前 chunk 后，再等待 Graph 的下一个 update 2026-09-04 21:04:36 | INFO | [REST] 1-19 [research_1788519682] SSE -> type=api_call | stage=ResearchStage.RESEARCH_EXECUTION 2026-09-04 21:04:36 | INFO | [REST] 1-19 [research_1788519682] SSE -> type=heartbeat | stage=ResearchStage.RESEARCH_EXECUTION 2026-09-04 21:04:36 | INFO | [MAIN GRAPH] 3-79 [research_1788519682] CHUNK ADAPTER | chunk=4 | entries=1 | action=translate node updates to client SSE 2026-09-04 21:04:36 | INFO | [MAIN GRAPH] 3-83 [research_1788519682] GRAPH PATH | research_supervisor -> final_report_generation | path_so_far=START -> clarify_with_user -> write_research_brief -> research_supervisor -> final_report_generation 2026-09-04 21:04:36 | INFO | [MAIN GRAPH] 3-80 [research_1788519682] 解释：内层 for 只是在遍历这个 chunk 里的 node update，并调用 Service adapter 转成 SSE；不会重新执行 LangGraph node。 2026-09-04 21:04:36 | INFO | [MAIN GRAPH] 3-07 [research_1788519682] PROCESS outer-node update | node=final_report_generation | chunk=4 | data_type=dict 2026-09-04 21:04:36 | INFO | [NODE VIEW] 2-32 [research_1788519682] 解释：Service 节点适配器输入：接收 Main Graph 的 node update，并把它转换成前端可理解的 StreamingEvent。 2026-09-04 21:04:36 | INFO | [NODE VIEW] 2-33 [research_1788519682] ┌─ INPUT [PAIR=SERVICE.process_node:5094fa5] | node=final_report_generation | chunk=4 | data_type=dict | keys=final_report, messages, notes 2026-09-04 21:04:36 | INFO | [NODE VIEW] 2-39 [research_1788519682] node=final_report_generation | data_type=dict | keys=final_report, messages, notes 2026-09-04 21:04:36 | INFO | [NODE VIEW] 2-40 [research_1788519682] field=messages | type=list | size=1 | preview=["content='# 长期恋爱关系中影响满意度与稳定性的核心因素：综合学术研究报告\\n\\n---\\n\\n## 概述\\n\\n长期恋爱关系（包括婚姻、同居及持续数年的伴侣关系）是人类心理健康与社会福祉的核心组成部分。大量研究表明，高质量的亲密关系不仅与个体的心理健康、身体健康和寿命密切相关，更是人们生活满意度的重要预测因素。然而，维系一段长期、稳定且令双方满意的关系，并非易事——据统计，西方国家约40%至50%的婚姻以离婚告终，而更多关系在正式破裂前已陷入长期的不… 2026-09-04 21:04:36 | INFO | [NODE VIEW] 2-40 [research_1788519682] field=final_report | type=str | size=8814 | preview=# 长期恋爱关系中影响满意度与稳定性的核心因素：综合学术研究报告 --- ## 概述 长期恋爱关系（包括婚姻、同居及持续数年的伴侣关系）是人类心理健康与社会福祉的核心组成部分。大量研究表明，高质量的亲密关系不仅与个体的心理健康、身体健康和寿命密切相关，更是人们生活满意度的重要预测因素。然而，维系一段长期、稳定且令双方满意的关系，并非易事——据统计，西方国家约40%至50%的婚姻以离婚告终，而更多关系在正式破裂前已陷入长期的不满与疏离。 理解哪些因素真正决定长期关系的质量，不仅… 2026-09-04 21:04:36 | INFO | [NODE VIEW] 2-40 [research_1788519682] field=notes | type=dict | size=2 | preview={"type": "override", "value": []} 2026-09-04 21:04:36 | INFO | [NODE VIEW] 2-34 [research_1788519682] 解释：Service 节点适配器输出：Graph node update 已转成一个 stage_update SSE 事件；Graph state 本身没有在这里被修改。 2026-09-04 21:04:36 | INFO | [NODE VIEW] 2-35 [research_1788519682] └─ OUTPUT [PAIR=SERVICE.process_node:5094fa5] | StreamingEvent(type=stage_update, stage=ResearchStage.FINAL_REPORT) | content_chars=8901 2026-09-04 21:04:36 | INFO | [SERVICE] 2-12 [research_1788519682] YIELD event | node=final_report_generation | type=stage_update | stage=ResearchStage.FINAL_REPORT | processing=0.002s 2026-09-04 21:04:36 | INFO | [REST] 1-19 [research_1788519682] SSE -> type=stage_update | stage=ResearchStage.FINAL_REPORT 2026-09-04 21:04:36 | INFO | [MAIN GRAPH] 3-81 [research_1788519682] FLOW | 前因：chunk 4 中的 node update 已完成 SSE 转换/发送 | 当前：当前 chunk 的 Service adapter 工作结束 | 下一步：async for 回到 astream，等待 Graph 继续执行并返回下一个 chunk 2026-09-04 21:04:36 | INFO | [MAIN GRAPH] 3-84 [research_1788519682] GRAPH PATH SUMMARY | START -> clarify_with_user -> write_research_brief -> research_supervisor -> final_report_generation | updates=4 2026-09-04 21:04:36 | INFO | [MAIN GRAPH] 3-08 [research_1788519682] STREAM COMPLETE | outer_chunks=4 | elapsed=194.00s 2026-09-04 21:04:36 | INFO | [MAIN GRAPH] 3-09 [research_1788519682] 解释：Main Graph 输出：最外层图执行结束；下面回到 Service/REST 层继续发送完成事件。 2026-09-04 21:04:36 | INFO | [MAIN GRAPH] 3-10 [research_1788519682] └─ OUTPUT [PAIR=MAIN_GRAPH.run:research_1788519682] | outer_chunks=4 | elapsed=194.00s | final_stage=ResearchStage.FINAL_REPORT 2026-09-04 21:04:36 | INFO | [MAIN GRAPH] 3-11 [research_1788519682] ────────────── END ────────────── 2026-09-04 21:04:36 | INFO | [SERVICE] 2-16 [research_1788519682] 解释：Service 输出：Graph 已执行完成，Service 最后产出 stage_complete 事件交回 REST/SSE 层。 2026-09-04 21:04:36 | INFO | [SERVICE] 2-17 [research_1788519682] └─ OUTPUT [PAIR=SERVICE.stream_research:research_1788519682] | stage_complete | total_outer_nodes=4 | elapsed=194.00s 2026-09-04 21:04:36 | INFO | [REST] 1-19 [research_1788519682] SSE -> type=stage_complete | stage=ResearchStage.COMPLETED 2026-09-04 21:04:36 | INFO | [REST] 1-20 [research_1788519682] SSE -> research_complete | duration=194.00s 2026-09-04 21:04:36 | INFO | [METRICS] 2-100 [research_1788519682] FLOW | 前因：研究流已经结束并发送 research_complete | 当前：记录本次运行的 research_id/model/duration/query 指标 | 下一步：结束 SSE session 2026-09-04 21:04:36 | INFO | [METRICS] 2-02 [research_1788519682] STORE research metrics 2026-09-04 21:04:36 | INFO | [METRICS] 2-59 Stored research metrics | research_id=research_1788519682 | model=ModelType.ANTHROPIC 2026-09-04 21:04:36 | INFO | [REST] 1-21 [research_1788519682] 解释：SSE 会话输出：研究流程已经结束，completion 事件已发送，并完成本次运行指标记录。 2026-09-04 21:04:36 | INFO | [REST] 1-22 [research_1788519682] └─ OUTPUT [PAIR=SSE.session:research_1788519682] | research_complete | duration=194.00s | metrics_stored=True 2026-09-04 21:04:36 | INFO | [REST] 1-23 [research_1788519682] ────────────── SSE SESSION END ──────────────
以上的日志，在 supervisor再次调用tools并要生成researcher的时候，日志打印不够全面。所以，暂时终端，生成新的版本代码，继续分析。
更新版本后的日志，海量！
$ uvicorn main:app --host 0.0.0.0 --port 8080 --reload INFO: Will watch for changes in these directories: ['/home/jeffrey/Desktop/MyDesktop/lv7/deep-research/launch-DeepResearch-Backend-logging-v7-claude46'] INFO: Uvicorn running on http://0.0.0.0:8080 (Press CTRL+C to quit) INFO: Started reloader process [37850] using StatReload 2026-09-08 14:30:48 | WARNING | [SUPABASE] 2-50 Credentials not provided; using in-memory storage INFO: Started server process [37852] INFO: Waiting for application startup. INFO: Application startup complete. 2026-09-08 14:31:04 | INFO | [REST] 1-01 解释：进入 REST API 层：接收客户端的 Deep Research 请求，先完成参数校验，再创建 SSE 流式响应。 2026-09-08 14:31:04 | INFO | [REST] 1-02 ────────────── POST /research/stream ────────────── 2026-09-08 14:31:04 | INFO | [REST] 1-03 解释：REST 接口输入：客户端传入研究问题、模型类型和 API Key（Key 只记录为已提供，不打印真实值）。 2026-09-08 14:31:04 | INFO | [REST] 1-04 ┌─ INPUT [PAIR=REST.stream_research:f295b0c] | model=ModelType.ANTHROPIC | query=请研究一下长期恋爱关系中，哪些因素最影响双方的满意度和稳定性，并给出有研究依据的结论。 | api_key=<redacted> 2026-09-08 14:31:04 | INFO | [REST] 1-05 REQUEST received | model=ModelType.ANTHROPIC | query=请研究一下长期恋爱关系中，哪些因素最影响双方的满意度和稳定性，并给出有研究依据的结论。 | api_key=<redacted> 2026-09-08 14:31:04 | INFO | [REST] 1-35 FLOW | 前因：客户端请求已经进入 /research/stream，REST 已拿到 query/model/API Key | 当前：依次校验 query、API Key 是否存在，以及 model 是否受支持 | 下一步：全部通过后创建 SSE StreamingResponse 2026-09-08 14:31:04 | INFO | [REST] 1-06 VALIDATE query 2026-09-08 14:31:04 | INFO | [REST] 1-08 VALIDATE api_key presence (value never logged) 2026-09-08 14:31:04 | INFO | [REST] 1-10 VALIDATE model | requested=ModelType.ANTHROPIC | available=['openai', 'anthropic', 'kimi'] 2026-09-08 14:31:04 | INFO | [REST] 1-12 解释：请求参数校验通过；下面创建 SSE StreamingResponse，真正的研究流程会在流式生成器中继续执行。 2026-09-08 14:31:04 | INFO | [REST] 1-13 VALIDATION OK | creating SSE StreamingResponse 2026-09-08 14:31:04 | INFO | [REST] 1-36 FLOW | 前因：query/API Key/model 三项校验全部通过 | 当前：创建 StreamingResponse；HTTP 200 只代表流已建立，不代表研究已经完成 | 下一步：客户端开始消费 generate_research_stream() 产生的 SSE 数据 2026-09-08 14:31:04 | INFO | [REST] 1-27 解释：REST 接口输出：HTTP 层返回的是一个 SSE StreamingResponse；此时只是建立流，后续研究结果会持续写入这个响应。 2026-09-08 14:31:04 | INFO | [REST] 1-28 └─ OUTPUT [PAIR=REST.stream_research:f295b0c] | StreamingResponse(media_type=text/event-stream) created; body will be produced asynchronously by generate_research_stream() INFO: 127.0.0.1:48194 - "POST /research/stream HTTP/1.1" 200 OK 2026-09-08 14:31:04 | INFO | [REST] 1-14 [research_1788841864] 解释：进入 SSE 会话：从这一行开始，同一个 research_id 的事件会持续推送给客户端，直到研究完成或发生错误。 2026-09-08 14:31:04 | INFO | [REST] 1-15 [research_1788841864] ────────────── SSE SESSION START ────────────── 2026-09-08 14:31:04 | INFO | [REST] 1-16 [research_1788841864] 解释：SSE 会话输入：把本次请求的 query/model 交给流式研究流程。 2026-09-08 14:31:04 | INFO | [REST] 1-17 [research_1788841864] ┌─ INPUT [PAIR=SSE.session:research_1788841864] | query=请研究一下长期恋爱关系中，哪些因素最影响双方的满意度和稳定性，并给出有研究依据的结论。 | model=ModelType.ANTHROPIC 2026-09-08 14:31:04 | INFO | [REST] 1-18 [research_1788841864] SSE -> session_start | model=ModelType.ANTHROPIC 2026-09-08 14:31:04 | INFO | [REST] 1-37 [research_1788841864] FLOW | 前因：SSE 连接已经建立，并为本次请求生成 research_id | 当前：先向客户端发送 session_start，标记一条新的研究会话 | 下一步：调用 DeepResearchService.stream_research()，真正准备并启动 LangGraph 2026-09-08 14:31:04 | INFO | [SERVICE] 2-01 [research_1788841864] CALL DeepResearchService.stream_research() 2026-09-08 14:31:04 | INFO | [SERVICE] 2-03 [research_1788841864] 解释：进入 Service 层：REST 已完成 HTTP 参数校验；现在开始把请求转换成 LangGraph 需要的运行参数、config、context 和初始 state。 2026-09-08 14:31:04 | INFO | [SERVICE] 2-04 [research_1788841864] ────────────── DeepResearchService.stream_research ────────────── 2026-09-08 14:31:04 | INFO | [SERVICE] 2-92 [research_1788841864] FLOW | 前因：REST 已验证 query/model/API Key，并建立 SSE 会话 | 当前：Service 接管请求，开始做 Graph 启动前准备 | 下一步：按 6 个步骤准备 INPUT → RUNTIME → CONFIG → CONTEXT → STATE → SSE 2026-09-08 14:31:04 | INFO | [SERVICE] 2-05 [research_1788841864] 解释：PREP 1/6（INPUT）：确认这次研究任务的原始输入；这些值来自 REST 层，是后续所有准备工作的起点。 2026-09-08 14:31:04 | INFO | [SERVICE] 2-06 [research_1788841864] ┌─ INPUT [PAIR=SERVICE.stream_research:research_1788841864] | query=请研究一下长期恋爱关系中，哪些因素最影响双方的满意度和稳定性，并给出有研究依据的结论。 | model=ModelType.ANTHROPIC | api_key=<redacted> 2026-09-08 14:31:04 | INFO | [SERVICE] 2-07 [research_1788841864] PREP 1/6 INPUT: 2026-09-08 14:31:04 | INFO | [SERVICE] 2-07 [research_1788841864] │ { 2026-09-08 14:31:04 | INFO | [SERVICE] 2-07 [research_1788841864] │ "research_id": "research_1788841864", 2026-09-08 14:31:04 | INFO | [SERVICE] 2-07 [research_1788841864] │ "model": "anthropic", 2026-09-08 14:31:04 | INFO | [SERVICE] 2-07 [research_1788841864] │ "query": "请研究一下长期恋爱关系中，哪些因素最影响双方的满意度和稳定性，并给出有研究依据的结论。", 2026-09-08 14:31:04 | INFO | [SERVICE] 2-07 [research_1788841864] │ "query_chars": 43, 2026-09-08 14:31:04 | INFO | [SERVICE] 2-07 [research_1788841864] │ "api_key": "<redacted>" 2026-09-08 14:31:04 | INFO | [SERVICE] 2-07 [research_1788841864] │ } 2026-09-08 14:31:04 | INFO | [SERVICE] 2-69 [research_1788841864] ────────────── PRE-GRAPH PREPARATION ────────────── 2026-09-08 14:31:04 | INFO | [SERVICE] 2-70 [research_1788841864] 解释：Graph 启动前一共有 6 项准备：①输入；②运行规则；③RunnableConfig；④关联上下文；⑤初始 AgentState；⑥初始化 SSE。每一步都明确说明前因、当前和下一步。 2026-09-08 14:31:04 | INFO | [SERVICE] 2-93 [research_1788841864] FLOW | 前因：PREP 1/6 已确认研究输入 | 当前：PREP 2/6 设置 Graph 的运行保护和 streaming 规则 | 下一步：根据 model/API Key 构造 RunnableConfig 2026-09-08 14:31:04 | INFO | [SERVICE] 2-71 [research_1788841864] PREP 2/6 RUNTIME: 2026-09-08 14:31:04 | INFO | [SERVICE] 2-71 [research_1788841864] │ { 2026-09-08 14:31:04 | INFO | [SERVICE] 2-71 [research_1788841864] │ "timeout_seconds": 900, 2026-09-08 14:31:04 | INFO | [SERVICE] 2-71 [research_1788841864] │ "heartbeat_check_seconds": 25, 2026-09-08 14:31:04 | INFO | [SERVICE] 2-71 [research_1788841864] │ "stream_mode": [ 2026-09-08 14:31:04 | INFO | [SERVICE] 2-71 [research_1788841864] │ "updates", 2026-09-08 14:31:04 | INFO | [SERVICE] 2-71 [research_1788841864] │ "custom" 2026-09-08 14:31:04 | INFO | [SERVICE] 2-71 [research_1788841864] │ ], 2026-09-08 14:31:04 | INFO | [SERVICE] 2-71 [research_1788841864] │ "timeout_action": "return_partial_results", 2026-09-08 14:31:04 | INFO | [SERVICE] 2-71 [research_1788841864] │ "initial_stage": "ResearchStage.INITIALIZATION" 2026-09-08 14:31:04 | INFO | [SERVICE] 2-71 [research_1788841864] │ } 2026-09-08 14:31:04 | INFO | [SERVICE] 2-72 [research_1788841864] 解释：V7：heartbeat/timeout 由独立的 Service timer 驱动，不依赖 Graph 是否返回 update；单个 LLM/子图长时间运行时仍会持续发 heartbeat。 2026-09-08 14:31:04 | INFO | [SERVICE] 2-73 [research_1788841864] FLOW | 前因：PREP 2/6 已确定 timeout、heartbeat 和 stream_mode | 当前：PREP 3/6 解析模型/Provider，并组装 RunnableConfig | 下一步：把 research_id/model_type 放入 metadata，建立跨层日志关联 2026-09-08 14:31:04 | INFO | [SERVICE] 2-08 [research_1788841864] CREATE RunnableConfig 2026-09-08 14:31:04 | INFO | [CONFIG] 2-83 ────────────── RUNNABLE CONFIG PREPARATION ────────────── 2026-09-08 14:31:04 | INFO | [CONFIG] 2-21 解释：配置模块输入：根据客户端选择的 provider/model 和 API Key 生成 LangChain RunnableConfig。 2026-09-08 14:31:04 | INFO | [CONFIG] 2-22 ┌─ INPUT [PAIR=SERVICE.create_config:dc74778] | model=ModelType.ANTHROPIC | api_key=<redacted> 2026-09-08 14:31:04 | INFO | [CONFIG] 2-96 FLOW | 前因：Service 已拿到客户端选择的 model 和 API Key | 当前：CONFIG 1/4 解析模型别名，确定真正传给 LangChain/Provider 的模型名 | 下一步：准备 Provider endpoint 和凭证绑定 2026-09-08 14:31:04 | INFO | [CONFIG] 2-84 解释：CONFIG 1/4：解析客户端的模型别名，确定真正传给 LangChain/Provider 的模型名称。 2026-09-08 14:31:04 | INFO | [CONFIG] 2-23 Resolve model mapping | requested=ModelType.ANTHROPIC 2026-09-08 14:31:04 | INFO | [CONFIG] 2-24 Resolved model | ModelType.ANTHROPIC -> claude-sonnet-4-6 2026-09-08 14:31:04 | INFO | [CONFIG] 2-97 FLOW | 前因：模型别名已解析为 claude-sonnet-4-6 | 当前：CONFIG 2/4 准备 Provider endpoint、provider binding 和 API Key | 下一步：组装 Graph 的运行策略参数 2026-09-08 14:31:04 | INFO | [CONFIG] 2-85 解释：CONFIG 2/4：准备 Provider 调用环境与凭证；API Key 只绑定到 RunnableConfig，日志永远只显示 <redacted>。 2026-09-08 14:31:04 | INFO | [CONFIG] 2-86 Credential binding | user_api_key=<redacted> 2026-09-08 14:31:04 | INFO | [CONFIG] 2-87 Provider environment ready | endpoint=default ModelType.ANTHROPIC provider endpoint 2026-09-08 14:31:04 | INFO | [CONFIG] 2-88 Provider binding ready | model_provider=anthropic 2026-09-08 14:31:04 | INFO | [CONFIG] 2-98 FLOW | 前因：Provider 调用环境与凭证绑定已准备好 | 当前：CONFIG 3/4 组装模型、token、search、Researcher/Tool/并发等运行策略 | 下一步：把完整配置封装成 RunnableConfig 2026-09-08 14:31:04 | INFO | [CONFIG] 2-89 解释：CONFIG 3/4：准备 Graph 的运行策略参数，包括各阶段模型、token 上限、search API、Researcher 迭代/工具调用/并发预算。 2026-09-08 14:31:04 | INFO | [CONFIG] 2-90 Runtime policy ready | search_api=anthropic | allow_clarification=False | researcher_iterations=6 | react_tool_calls=3 | concurrent_units=2 2026-09-08 14:31:04 | INFO | [CONFIG] 2-26 RunnableConfig.configurable: 2026-09-08 14:31:04 | INFO | [CONFIG] 2-26 │ { 2026-09-08 14:31:04 | INFO | [CONFIG] 2-26 │ "research_model": "claude-sonnet-4-6", 2026-09-08 14:31:04 | INFO | [CONFIG] 2-26 │ "research_model_max_tokens": 4000, 2026-09-08 14:31:04 | INFO | [CONFIG] 2-26 │ "final_report_model": "claude-sonnet-4-6", 2026-09-08 14:31:04 | INFO | [CONFIG] 2-26 │ "final_report_model_max_tokens": 8000, 2026-09-08 14:31:04 | INFO | [CONFIG] 2-26 │ "compression_model": "claude-sonnet-4-6", 2026-09-08 14:31:04 | INFO | [CONFIG] 2-26 │ "compression_model_max_tokens": 4000, 2026-09-08 14:31:04 | INFO | [CONFIG] 2-26 │ "summarization_model": "claude-sonnet-4-6", 2026-09-08 14:31:04 | INFO | [CONFIG] 2-26 │ "summarization_model_max_tokens": 4000, 2026-09-08 14:31:04 | INFO | [CONFIG] 2-26 │ "allow_clarification": false, 2026-09-08 14:31:04 | INFO | [CONFIG] 2-26 │ "max_structured_output_retries": 2, 2026-09-08 14:31:04 | INFO | [CONFIG] 2-26 │ "search_api": "anthropic", 2026-09-08 14:31:04 | INFO | [CONFIG] 2-26 │ "max_researcher_iterations": 6, 2026-09-08 14:31:04 | INFO | [CONFIG] 2-26 │ "max_react_tool_calls": 3, 2026-09-08 14:31:04 | INFO | [CONFIG] 2-26 │ "max_concurrent_research_units": 2, 2026-09-08 14:31:04 | INFO | [CONFIG] 2-26 │ "user_api_key": "<redacted>", 2026-09-08 14:31:04 | INFO | [CONFIG] 2-26 │ "research_model_provider": "anthropic", 2026-09-08 14:31:04 | INFO | [CONFIG] 2-26 │ "final_report_model_provider": "anthropic", 2026-09-08 14:31:04 | INFO | [CONFIG] 2-26 │ "compression_model_provider": "anthropic", 2026-09-08 14:31:04 | INFO | [CONFIG] 2-26 │ "summarization_model_provider": "anthropic" 2026-09-08 14:31:04 | INFO | [CONFIG] 2-26 │ } 2026-09-08 14:31:04 | INFO | [CONFIG] 2-99 FLOW | 前因：CONFIG 3/4 已得到完整 configurable dict | 当前：CONFIG 4/4 封装 LangChain RunnableConfig | 下一步：返回 Service，并继续准备 metadata / initial_state 2026-09-08 14:31:04 | INFO | [CONFIG] 2-91 解释：CONFIG 4/4：把前面的模型、Provider、运行策略和凭证正式封装成 LangChain RunnableConfig。 2026-09-08 14:31:04 | INFO | [CONFIG] 2-27 解释：配置模块输出：RunnableConfig 已组装完成；后续所有 Graph/LLM/Tool 节点都会从这里读取模型、限额和 API 配置。 2026-09-08 14:31:04 | INFO | [CONFIG] 2-28 └─ OUTPUT [PAIR=SERVICE.create_config:dc74778] | RunnableConfig ready | resolved_model=claude-sonnet-4-6 | provider=anthropic | search_api=anthropic | limits={researcher_iterations:6, react_tool_calls:3, concurrent_units:2} 2026-09-08 14:31:04 | INFO | [SERVICE] 2-09 [research_1788841864] PREP 3/6 CONFIG SUMMARY: 2026-09-08 14:31:04 | INFO | [SERVICE] 2-09 [research_1788841864] │ { 2026-09-08 14:31:04 | INFO | [SERVICE] 2-09 [research_1788841864] │ "requested_model": "anthropic", 2026-09-08 14:31:04 | INFO | [SERVICE] 2-09 [research_1788841864] │ "resolved_model": "claude-sonnet-4-6", 2026-09-08 14:31:04 | INFO | [SERVICE] 2-09 [research_1788841864] │ "provider": "anthropic", 2026-09-08 14:31:04 | INFO | [SERVICE] 2-09 [research_1788841864] │ "search_api": "anthropic", 2026-09-08 14:31:04 | INFO | [SERVICE] 2-09 [research_1788841864] │ "limits": { 2026-09-08 14:31:04 | INFO | [SERVICE] 2-09 [research_1788841864] │ "max_researcher_iterations": 6, 2026-09-08 14:31:04 | INFO | [SERVICE] 2-09 [research_1788841864] │ "max_react_tool_calls": 3, 2026-09-08 14:31:04 | INFO | [SERVICE] 2-09 [research_1788841864] │ "max_concurrent_research_units": 2 2026-09-08 14:31:04 | INFO | [SERVICE] 2-09 [research_1788841864] │ } 2026-09-08 14:31:04 | INFO | [SERVICE] 2-09 [research_1788841864] │ } 2026-09-08 14:31:04 | INFO | [SERVICE] 2-74 [research_1788841864] FLOW | 前因：PREP 3/6 已生成 RunnableConfig，并已解析实际模型 | 当前：PREP 4/6 把 research_id/model_type 放入 config.metadata | 下一步：用用户 query 创建 Main Graph 的 initial_state 2026-09-08 14:31:04 | INFO | [SERVICE] 2-94 [research_1788841864] PREP 4/6 CONTEXT: 2026-09-08 14:31:04 | INFO | [SERVICE] 2-94 [research_1788841864] │ { 2026-09-08 14:31:04 | INFO | [SERVICE] 2-94 [research_1788841864] │ "metadata": { 2026-09-08 14:31:04 | INFO | [SERVICE] 2-94 [research_1788841864] │ "model_type": "anthropic", 2026-09-08 14:31:04 | INFO | [SERVICE] 2-94 [research_1788841864] │ "research_id": "research_1788841864" 2026-09-08 14:31:04 | INFO | [SERVICE] 2-94 [research_1788841864] │ }, 2026-09-08 14:31:04 | INFO | [SERVICE] 2-94 [research_1788841864] │ "purpose": "correlate service / graph / researcher / tool logs for the same run" 2026-09-08 14:31:04 | INFO | [SERVICE] 2-94 [research_1788841864] │ } 2026-09-08 14:31:04 | INFO | [SERVICE] 2-75 [research_1788841864] FLOW | 前因：PREP 4/6 已建立本次运行的关联上下文 | 当前：PREP 5/6 把 REST query 包装成 LangGraph 的 AgentInputState/HumanMessage | 下一步：在 Graph 启动前向客户端发送初始化 SSE 2026-09-08 14:31:04 | INFO | [SERVICE] 2-10 [research_1788841864] PREP 5/6 STATE: 2026-09-08 14:31:04 | INFO | [SERVICE] 2-10 [research_1788841864] │ { 2026-09-08 14:31:04 | INFO | [SERVICE] 2-10 [research_1788841864] │ "state_type": "AgentInputState", 2026-09-08 14:31:04 | INFO | [SERVICE] 2-10 [research_1788841864] │ "messages": [ 2026-09-08 14:31:04 | INFO | [SERVICE] 2-10 [research_1788841864] │ { 2026-09-08 14:31:04 | INFO | [SERVICE] 2-10 [research_1788841864] │ "type": "HumanMessage", 2026-09-08 14:31:04 | INFO | [SERVICE] 2-10 [research_1788841864] │ "content": "请研究一下长期恋爱关系中，哪些因素最影响双方的满意度和稳定性，并给出有研究依据的结论。" 2026-09-08 14:31:04 | INFO | [SERVICE] 2-10 [research_1788841864] │ } 2026-09-08 14:31:04 | INFO | [SERVICE] 2-10 [research_1788841864] │ ] 2026-09-08 14:31:04 | INFO | [SERVICE] 2-10 [research_1788841864] │ } 2026-09-08 14:31:04 | INFO | [SERVICE] 2-77 [research_1788841864] FLOW | 前因：PREP 5/6 已得到 Main Graph 的 initial_state | 当前：PREP 6/6 先发送 session/model 初始化事件，让客户端知道研究已开始 | 下一步：初始化 outer update 计数器，然后真正调用 deep_researcher.astream() 2026-09-08 14:31:04 | INFO | [SERVICE] 2-95 [research_1788841864] PREP 6/6 SSE EVENTS: 2026-09-08 14:31:04 | INFO | [SERVICE] 2-95 [research_1788841864] │ { 2026-09-08 14:31:04 | INFO | [SERVICE] 2-95 [research_1788841864] │ "events": [ 2026-09-08 14:31:04 | INFO | [SERVICE] 2-95 [research_1788841864] │ { 2026-09-08 14:31:04 | INFO | [SERVICE] 2-95 [research_1788841864] │ "type": "stage_start", 2026-09-08 14:31:04 | INFO | [SERVICE] 2-95 [research_1788841864] │ "stage": "ResearchStage.INITIALIZATION" 2026-09-08 14:31:04 | INFO | [SERVICE] 2-95 [research_1788841864] │ }, 2026-09-08 14:31:04 | INFO | [SERVICE] 2-95 [research_1788841864] │ { 2026-09-08 14:31:04 | INFO | [SERVICE] 2-95 [research_1788841864] │ "type": "api_call", 2026-09-08 14:31:04 | INFO | [SERVICE] 2-95 [research_1788841864] │ "resolved_model": "claude-sonnet-4-6", 2026-09-08 14:31:04 | INFO | [SERVICE] 2-95 [research_1788841864] │ "provider": "anthropic" 2026-09-08 14:31:04 | INFO | [SERVICE] 2-95 [research_1788841864] │ } 2026-09-08 14:31:04 | INFO | [SERVICE] 2-95 [research_1788841864] │ ], 2026-09-08 14:31:04 | INFO | [SERVICE] 2-95 [research_1788841864] │ "timing": "before Main Graph starts", 2026-09-08 14:31:04 | INFO | [SERVICE] 2-95 [research_1788841864] │ "purpose": "announce session start and resolved model" 2026-09-08 14:31:04 | INFO | [SERVICE] 2-95 [research_1788841864] │ } 2026-09-08 14:31:04 | INFO | [REST] 1-19 [research_1788841864] SSE -> type=stage_start | stage=ResearchStage.INITIALIZATION | event=None | source=None | content=🚀 Starting deep research for: 请研究一下长期恋爱关系中，哪些因素最影响双方的满意度和稳定性，并给出有研究依据的结论。 2026-09-08 14:31:04 | INFO | [REST] 1-19 [research_1788841864] SSE -> type=api_call | stage=ResearchStage.INITIALIZATION | event=None | source=None | content=Using resolved model: claude-sonnet-4-6 (provider: anthropic) 2026-09-08 14:31:04 | INFO | [SERVICE] 2-80 [research_1788841864] FLOW | 前因：PREP 1/6～6/6 全部完成，initial_state 和 RunnableConfig 均已就绪 | 当前：Graph 启动前准备结束；初始化 outer update 计数器和等待计时器 | 下一步：进入 MAIN GRAPH，调用 deep_researcher.astream(stream_mode=[updates, custom], subgraphs=True) 2026-09-08 14:31:04 | INFO | [SERVICE] 2-81 [research_1788841864] PRE-GRAPH READY: 2026-09-08 14:31:04 | INFO | [SERVICE] 2-81 [research_1788841864] │ { 2026-09-08 14:31:04 | INFO | [SERVICE] 2-81 [research_1788841864] │ "resolved_model": "claude-sonnet-4-6", 2026-09-08 14:31:04 | INFO | [SERVICE] 2-81 [research_1788841864] │ "provider": "anthropic", 2026-09-08 14:31:04 | INFO | [SERVICE] 2-81 [research_1788841864] │ "initial_state_messages": 1, 2026-09-08 14:31:04 | INFO | [SERVICE] 2-81 [research_1788841864] │ "stream_mode": [ 2026-09-08 14:31:04 | INFO | [SERVICE] 2-81 [research_1788841864] │ "updates", 2026-09-08 14:31:04 | INFO | [SERVICE] 2-81 [research_1788841864] │ "custom" 2026-09-08 14:31:04 | INFO | [SERVICE] 2-81 [research_1788841864] │ ], 2026-09-08 14:31:04 | INFO | [SERVICE] 2-81 [research_1788841864] │ "timeout_seconds": 900, 2026-09-08 14:31:04 | INFO | [SERVICE] 2-81 [research_1788841864] │ "heartbeat_check_seconds": 25, 2026-09-08 14:31:04 | INFO | [SERVICE] 2-81 [research_1788841864] │ "next": "deep_researcher.astream" 2026-09-08 14:31:04 | INFO | [SERVICE] 2-81 [research_1788841864] │ } 2026-09-08 14:31:04 | INFO | [SERVICE] 2-82 [research_1788841864] ────────────── END PRE-GRAPH PREPARATION ────────────── 2026-09-08 14:31:04 | INFO | [MAIN GRAPH] 3-01 [research_1788841864] 解释：进入最外层 LangGraph：从 initial_state 开始，依次运行 clarification、research brief、research supervisor 和 final report。 2026-09-08 14:31:04 | INFO | [MAIN GRAPH] 3-02 [research_1788841864] ────────────── START ────────────── 2026-09-08 14:31:04 | INFO | [MAIN GRAPH] 3-03 [research_1788841864] 解释：Main Graph 输入：一个包含用户问题的初始 Agent state，以及本次 RunnableConfig。 2026-09-08 14:31:04 | INFO | [MAIN GRAPH] 3-04 [research_1788841864] ┌─ INPUT [PAIR=MAIN_GRAPH.run:research_1788841864] | initial_state.messages=HumanMessage=1 | query=请研究一下长期恋爱关系中，哪些因素最影响双方的满意度和稳定性，并给出有研究依据的结论。 | stream_mode=[updates, custom] | subgraphs=True 2026-09-08 14:31:04 | INFO | [MAIN GRAPH] 3-76 [research_1788841864] 解释：V7 关键：3-05 真正调用 Graph。Service 同时消费 updates + custom，并开启 subgraphs=True。custom 是节点执行中的实时进度；updates 是节点完成后的 State update。Supervisor/Researcher 子图内部事件也会直接透传，所以 SSE 不再等整个 research_supervisor 结束后才更新 stage。 2026-09-08 14:31:04 | INFO | [MAIN GRAPH] 3-77 [research_1788841864] FLOW | 前因：Service 的 6 项 PREP 已完成，initial_state + RunnableConfig 已就绪 | 当前：调用 deep_researcher.astream()，把执行权交给 LangGraph | 下一步：等待 Graph 的实时 custom progress 或完成后的 update，哪一个先到就先处理 2026-09-08 14:31:04 | INFO | [MAIN GRAPH] 3-05 [research_1788841864] CALL deep_researcher.astream(stream_mode=[updates, custom], subgraphs=True) 2026-09-08 14:31:04 | INFO | [MAIN GRAPH] 3-15 [research_1788841864] 解释：Main Graph 节点 clarify_with_user：判断是否需要向用户追问；当前配置若关闭 clarification，则直接路由到 research brief。 2026-09-08 14:31:04 | INFO | [MAIN GRAPH] 3-16 [research_1788841864] ────────────── NODE clarify_with_user ────────────── 2026-09-08 14:31:04 | INFO | [clarify_with_user] 3-17 [research_1788841864] 解释：节点输入：当前 AgentState 中的用户消息与运行配置。 2026-09-08 14:31:04 | INFO | [clarify_with_user] 3-18 [research_1788841864] ┌─ INPUT [PAIR=NODE.clarify_with_user:research_1788841864] | state_keys=['messages', 'supervisor_messages', 'raw_notes', 'notes'] | messages=HumanMessage=1 2026-09-08 14:31:04 | INFO | [clarify_with_user] 3-19 [research_1788841864] ENTER | state_keys=['messages', 'supervisor_messages', 'raw_notes', 'notes'] | messages=HumanMessage=1 2026-09-08 14:31:04 | INFO | [clarify_with_user] 3-20 [research_1788841864] CONFIG | allow_clarification=False 2026-09-08 14:31:04 | INFO | [clarify_with_user] 3-21 [research_1788841864] SKIP LLM | clarification disabled 2026-09-08 14:31:04 | INFO | [clarify_with_user] 3-22 [research_1788841864] ROUTE -> write_research_brief 2026-09-08 14:31:04 | INFO | [clarify_with_user] 3-23 [research_1788841864] 解释：节点输出：不调用 LLM，不修改 state，直接告诉 LangGraph 下一跳是 write_research_brief。 2026-09-08 14:31:04 | INFO | [clarify_with_user] 3-24 [research_1788841864] └─ OUTPUT [PAIR=NODE.clarify_with_user:research_1788841864] | Command(goto=write_research_brief) | state_update=none 2026-09-08 14:31:04 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] clarification_started | stage=clarification | source=clarify_with_user: 2026-09-08 14:31:04 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ { 2026-09-08 14:31:04 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ "message": "Checking whether the research request needs clarification.", 2026-09-08 14:31:04 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ "namespace": [], 2026-09-08 14:31:04 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ "metadata": { 2026-09-08 14:31:04 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ "event": "clarification_started", 2026-09-08 14:31:04 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ "source": "clarify_with_user", 2026-09-08 14:31:04 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ "namespace": [], 2026-09-08 14:31:04 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ "stage_transition": "initialization->clarification" 2026-09-08 14:31:04 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ } 2026-09-08 14:31:04 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ } 2026-09-08 14:31:04 | INFO | [REST] 1-19 [research_1788841864] SSE -> type=research_step | stage=ResearchStage.CLARIFICATION | event=clarification_started | source=clarify_with_user | content=Checking whether the research request needs clarification. 2026-09-08 14:31:04 | INFO | [MAIN GRAPH] 3-06 [research_1788841864] OUTER UPDATE #1 returned | completed_nodes=['clarify_with_user'] | wait=0.01s | live_stage=clarification 2026-09-08 14:31:04 | INFO | [REST] 1-19 [research_1788841864] SSE -> type=api_call | stage=ResearchStage.CLARIFICATION | event=None | source=None | content=📊 Outer graph update #1: clarify_with_user completed (⏱️ 0.0s, total: 0.0s) 2026-09-08 14:31:04 | INFO | [MAIN GRAPH] 3-83 [research_1788841864] GRAPH PATH | START -> clarify_with_user | path_so_far=START -> clarify_with_user 2026-09-08 14:31:04 | INFO | [MAIN GRAPH] 3-07 [research_1788841864] PROCESS completed outer-node update | node=clarify_with_user | outer_update=1 | data_type=NoneType 2026-09-08 14:31:04 | INFO | [NODE VIEW] 2-32 [research_1788841864] 解释：Service 节点适配器输入：接收 Main Graph 的 node update，并把它转换成前端可理解的 StreamingEvent。 2026-09-08 14:31:04 | INFO | [NODE VIEW] 2-33 [research_1788841864] ┌─ INPUT [PAIR=SERVICE.process_node:06fe5bf] | node=clarify_with_user | chunk=1 | data_type=NoneType | keys=none 2026-09-08 14:31:04 | INFO | [NODE VIEW] 2-39 [research_1788841864] node=clarify_with_user | data_type=NoneType | keys=none 2026-09-08 14:31:04 | INFO | [NODE VIEW] 2-41 [research_1788841864] raw=None 2026-09-08 14:31:04 | INFO | [NODE VIEW] 2-34 [research_1788841864] 解释：Service 节点适配器输出：这是 node_completed 完成通知，不负责推进 live stage；实时 stage 由 custom progress 在节点执行时更新。 2026-09-08 14:31:04 | INFO | [NODE VIEW] 2-35 [research_1788841864] └─ OUTPUT [PAIR=SERVICE.process_node:06fe5bf] | StreamingEvent(type=node_completed, stage=ResearchStage.CLARIFICATION) | content_chars=121 2026-09-08 14:31:04 | INFO | [SERVICE] 2-12 [research_1788841864] YIELD completed-node event | node=clarify_with_user | type=node_completed | stage=ResearchStage.CLARIFICATION 2026-09-08 14:31:04 | INFO | [REST] 1-19 [research_1788841864] SSE -> type=node_completed | stage=ResearchStage.CLARIFICATION | event=None | source=None | content=🔍 Step 1: Analyzing research scope and clarifying requirements ✅ No clarification needed - proceeding with original query 2026-09-08 14:31:04 | INFO | [MAIN GRAPH] 3-37 [research_1788841864] 解释：Main Graph 节点 write_research_brief：把原始用户问题改写成结构化 Research Brief，并初始化 Supervisor 的上下文。 2026-09-08 14:31:04 | INFO | [MAIN GRAPH] 3-38 [research_1788841864] ────────────── NODE write_research_brief ────────────── 2026-09-08 14:31:04 | INFO | [write_research_brief] 3-39 [research_1788841864] 解释：节点输入：Main Graph 当前 messages；这是生成 Research Brief 的原材料。 2026-09-08 14:31:04 | INFO | [write_research_brief] 3-40 [research_1788841864] ┌─ INPUT [PAIR=NODE.write_research_brief:research_1788841864] | messages=HumanMessage=1 | message_buffer=Human: 请研究一下长期恋爱关系中，哪些因素最影响双方的满意度和稳定性，并给出有研究依据的结论。 2026-09-08 14:31:04 | INFO | [write_research_brief] 3-41 [research_1788841864] ENTER | messages=HumanMessage=1 2026-09-08 14:31:04 | INFO | [LLM] 3-42 [research_1788841864] 解释：LLM 输入：用户对话 + 日期 + Research Brief 生成指令。 2026-09-08 14:31:04 | INFO | [LLM] 3-43 [research_1788841864] ┌─ INPUT [PAIR=LLM.research_brief:research_1788841864] | model=claude-sonnet-4-6 | prompt_chars=1994 | prompt=You will be given a set of messages that have been exchanged so far between yourself and the user. Your job is to translate these messages into a more detailed and concrete research question that will be used to guide the research. The messages that have been … 2026-09-08 14:31:04 | INFO | [LLM] 3-44 [research_1788841864] CALL research-brief model | model=claude-sonnet-4-6 | prompt_chars=1994 2026-09-08 14:31:05 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] research_brief_started | stage=research_brief | source=write_research_brief: 2026-09-08 14:31:05 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ { 2026-09-08 14:31:05 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ "message": "Creating a structured research brief from the user request.", 2026-09-08 14:31:05 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ "namespace": [], 2026-09-08 14:31:05 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ "metadata": { 2026-09-08 14:31:05 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ "event": "research_brief_started", 2026-09-08 14:31:05 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ "source": "write_research_brief", 2026-09-08 14:31:05 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ "namespace": [], 2026-09-08 14:31:05 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ "stage_transition": "clarification->research_brief" 2026-09-08 14:31:05 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ } 2026-09-08 14:31:05 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ } 2026-09-08 14:31:05 | INFO | [REST] 1-19 [research_1788841864] SSE -> type=research_step | stage=ResearchStage.RESEARCH_BRIEF | event=research_brief_started | source=write_research_brief | content=Creating a structured research brief from the user request. 2026-09-08 14:31:18 | INFO | [LLM] 3-45 [research_1788841864] RETURN research brief | duration=14.77s | brief_chars=692 | brief=我希望深入研究长期恋爱关系（如持续一年以上的伴侣关系或婚姻关系）中，哪些核心因素最显著地影响双方的关系满意度（relationship satisfaction）与关系稳定性（relationship stability）。具体请涵盖以下维度： 1. **心理与个性因素**：如依恋风格（attachment style）、人格特质（Big Five personality traits）、自尊水平等对关系质量的影响。 2. **沟通与冲突解决**：有效沟通模式、冲突处理方式（如建设性 vs. 破坏性冲突策略）对满意度和稳定性的作用。 3. **亲密感与承诺**：情感亲密（emotional i… 2026-09-08 14:31:18 | INFO | [LLM] 3-46 [research_1788841864] 解释：LLM 输出：结构化 ResearchQuestion，其中 research_brief 将成为 Supervisor 的核心任务说明。 2026-09-08 14:31:18 | INFO | [LLM] 3-47 [research_1788841864] └─ OUTPUT [PAIR=LLM.research_brief:research_1788841864] | ResearchQuestion.research_brief chars=692 | value=我希望深入研究长期恋爱关系（如持续一年以上的伴侣关系或婚姻关系）中，哪些核心因素最显著地影响双方的关系满意度（relationship satisfaction）与关系稳定性（relationship stability）。具体请涵盖以下维度： 1. **心理与个性因素**：如依恋风格（attachment style）、人格特质（Big Five personality traits）、自尊水平等对关系质量的影响。 2. **沟通与冲突解决**：有效沟通模式、冲突处理方式（如建设性 vs. 破坏性冲突策略）对满意度和稳定性的作用。 3. **亲密感与承诺**：情感亲密（emotional intimacy）、性满意度、承诺水平（c… 2026-09-08 14:31:18 | INFO | [write_research_brief] 3-48 [research_1788841864] INIT supervisor_messages | SystemMessage + HumanMessage(research_brief) 2026-09-08 14:31:18 | INFO | [write_research_brief] 3-49 [research_1788841864] ROUTE -> research_supervisor 2026-09-08 14:31:18 | INFO | [write_research_brief] 3-50 [research_1788841864] 解释：节点输出：把 research_brief 写入 state，同时重置 supervisor_messages，然后进入整个 Supervisor 子图。 2026-09-08 14:31:18 | INFO | [write_research_brief] 3-51 [research_1788841864] └─ OUTPUT [PAIR=NODE.write_research_brief:research_1788841864] | Command(goto=research_supervisor) | research_brief_chars=692 | supervisor_messages=SystemMessage+HumanMessage 2026-09-08 14:31:18 | INFO | [MAIN GRAPH] 3-06 [research_1788841864] OUTER UPDATE #2 returned | completed_nodes=['write_research_brief'] | wait=14.78s | live_stage=research_brief 2026-09-08 14:31:18 | INFO | [REST] 1-19 [research_1788841864] SSE -> type=api_call | stage=ResearchStage.RESEARCH_BRIEF | event=None | source=None | content=📊 Outer graph update #2: write_research_brief completed (⏱️ 14.8s, total: 14.8s) 2026-09-08 14:31:18 | INFO | [MAIN GRAPH] 3-83 [research_1788841864] GRAPH PATH | clarify_with_user -> write_research_brief | path_so_far=START -> clarify_with_user -> write_research_brief 2026-09-08 14:31:18 | INFO | [MAIN GRAPH] 3-07 [research_1788841864] PROCESS completed outer-node update | node=write_research_brief | outer_update=2 | data_type=dict 2026-09-08 14:31:18 | INFO | [NODE VIEW] 2-32 [research_1788841864] 解释：Service 节点适配器输入：接收 Main Graph 的 node update，并把它转换成前端可理解的 StreamingEvent。 2026-09-08 14:31:18 | INFO | [NODE VIEW] 2-33 [research_1788841864] ┌─ INPUT [PAIR=SERVICE.process_node:8c6007b] | node=write_research_brief | chunk=2 | data_type=dict | keys=research_brief, supervisor_messages 2026-09-08 14:31:18 | INFO | [NODE VIEW] 2-39 [research_1788841864] node=write_research_brief | data_type=dict | keys=research_brief, supervisor_messages 2026-09-08 14:31:18 | INFO | [NODE VIEW] 2-40 [research_1788841864] field=supervisor_messages | type=dict | size=2 | preview={"type": "override", "value": ["content='You are a research supervisor. Your job is to conduct research by calling the \"ConductResearch\" tool. For context, today\\'s date is Tue Sep 8, 2026.\\n\\n<Task>\\nYour focus is to call the \"Condu… 2026-09-08 14:31:18 | INFO | [NODE VIEW] 2-40 [research_1788841864] field=research_brief | type=str | size=692 | preview=我希望深入研究长期恋爱关系（如持续一年以上的伴侣关系或婚姻关系）中，哪些核心因素最显著地影响双方的关系满意度（relationship satisfaction）与关系稳定性（relationship stability）。具体请涵盖以下维度： 1. **心理与个性因素**：如依恋风格（attachment style）、人格特质（Big Five personality traits）、自尊水平等对关系质量的影响。 2. **沟通与冲突解决**：有效沟通模式、冲突处理方式（… 2026-09-08 14:31:18 | INFO | [NODE VIEW] 2-34 [research_1788841864] 解释：Service 节点适配器输出：这是 node_completed 完成通知，不负责推进 live stage；实时 stage 由 custom progress 在节点执行时更新。 2026-09-08 14:31:18 | INFO | [NODE VIEW] 2-35 [research_1788841864] └─ OUTPUT [PAIR=SERVICE.process_node:8c6007b] | StreamingEvent(type=node_completed, stage=ResearchStage.RESEARCH_BRIEF) | content_chars=782 2026-09-08 14:31:18 | INFO | [SERVICE] 2-12 [research_1788841864] YIELD completed-node event | node=write_research_brief | type=node_completed | stage=ResearchStage.RESEARCH_BRIEF 2026-09-08 14:31:18 | INFO | [REST] 1-19 [research_1788841864] SSE -> type=node_completed | stage=ResearchStage.RESEARCH_BRIEF | event=None | source=None | content=📝 Step 2: Creating comprehensive research brief and strategy 📋 Generated Research Brief: 我希望深入研究长期恋爱关系（如持续一年以上的伴侣关系或婚姻关系）中，哪些核心因素最显著地影响双方的关系满意度（relationship satisfaction）与关系稳定性（relationship stability）。具体请涵盖以下维度： 1. **心理与… 2026-09-08 14:31:18 | INFO | [SUPERVISOR] 4-01 [research_1788841864] 解释：Supervisor 子图的思考节点：读取累计 supervisor_messages，决定调用 think_tool、ConductResearch 或 ResearchComplete。 2026-09-08 14:31:18 | INFO | [SUPERVISOR] 4-02 [research_1788841864] ────────────── NODE supervisor ────────────── 2026-09-08 14:31:18 | INFO | [supervisor] 4-03 [research_1788841864] 解释：节点输入：Supervisor 到目前为止的全部对话/ToolMessage，以及当前研究迭代次数。 2026-09-08 14:31:18 | INFO | [supervisor] 4-04 [research_1788841864] ┌─ INPUT [PAIR=NODE.supervisor:c035ab3] | iteration=0 | messages=SystemMessage=1, HumanMessage=1 | message_count=2 2026-09-08 14:31:18 | INFO | [supervisor] 4-05 [research_1788841864] ENTER | iteration=0 | messages=SystemMessage=1, HumanMessage=1 2026-09-08 14:31:18 | INFO | [supervisor] 4-06 [research_1788841864] TOOLS bound=['ConductResearch', 'ResearchComplete', 'think_tool'] 2026-09-08 14:31:18 | INFO | [LLM] 4-07 [research_1788841864] 解释：LLM 输入：Supervisor 消息历史 + 可调用工具定义；模型的主要输出是下一步 tool_calls。 2026-09-08 14:31:18 | INFO | [LLM] 4-08 [research_1788841864] ┌─ INPUT [PAIR=LLM.supervisor:c035ab3] | model=claude-sonnet-4-6 | messages=2 | tools=['ConductResearch', 'ResearchComplete', 'think_tool'] 2026-09-08 14:31:18 | INFO | [LLM] 4-09 [research_1788841864] CALL supervisor | model=claude-sonnet-4-6 | messages=2 2026-09-08 14:31:18 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] supervisor_started | stage=research_planning | source=supervisor: 2026-09-08 14:31:18 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ { 2026-09-08 14:31:18 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ "message": "Supervisor is reviewing current evidence and deciding the next action.", 2026-09-08 14:31:18 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ "namespace": [ 2026-09-08 14:31:18 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ "research_supervisor:b32a1631-0c17-9ddc-c990-04c1273955c4" 2026-09-08 14:31:18 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ ], 2026-09-08 14:31:18 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ "metadata": { 2026-09-08 14:31:18 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ "iteration": 0, 2026-09-08 14:31:18 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ "message_count": 2, 2026-09-08 14:31:18 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ "event": "supervisor_started", 2026-09-08 14:31:18 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ "source": "supervisor", 2026-09-08 14:31:18 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ "namespace": [ 2026-09-08 14:31:18 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ "research_supervisor:b32a1631-0c17-9ddc-c990-04c1273955c4" 2026-09-08 14:31:18 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ ], 2026-09-08 14:31:18 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ "stage_transition": "research_brief->research_planning" 2026-09-08 14:31:18 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ } 2026-09-08 14:31:18 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ } 2026-09-08 14:31:18 | INFO | [REST] 1-19 [research_1788841864] SSE -> type=research_step | stage=ResearchStage.RESEARCH_PLANNING | event=supervisor_started | source=supervisor | content=Supervisor is reviewing current evidence and deciding the next action. 2026-09-08 14:31:35 | INFO | [LLM] 4-10 [research_1788841864] RETURN supervisor | duration=16.92s | type=AIMessage, model=claude-sonnet-4-6, stop=tool_use, usage={"input_tokens": 1970, "output_tokens": 573, "total_tokens": 2543, "input_token_details": {"cache_read": 0, "cache_creation": 0, "ephemeral_5m_input_tokens": 0, "ephemeral_1h_input_tokens": 0}}, content=[{"id": "toolu_018rtw5D5Z3EaGgaqBoLYkBf", "caller": {"type": "direct"}, "input": {"reflection": "The user wants an in-depth research report on factors affecting relationship satisf…, tool_calls=['think_tool'] 2026-09-08 14:31:35 | INFO | [LLM] 4-10 [research_1788841864] AIMessage DETAIL: 2026-09-08 14:31:35 | INFO | [LLM] 4-10 [research_1788841864] │ { 2026-09-08 14:31:35 | INFO | [LLM] 4-10 [research_1788841864] │ "type": "AIMessage", 2026-09-08 14:31:35 | INFO | [LLM] 4-10 [research_1788841864] │ "model": "claude-sonnet-4-6", 2026-09-08 14:31:35 | INFO | [LLM] 4-10 [research_1788841864] │ "stop": "tool_use", 2026-09-08 14:31:35 | INFO | [LLM] 4-10 [research_1788841864] │ "usage": { 2026-09-08 14:31:35 | INFO | [LLM] 4-10 [research_1788841864] │ "input_tokens": 1970, 2026-09-08 14:31:35 | INFO | [LLM] 4-10 [research_1788841864] │ "output_tokens": 573, 2026-09-08 14:31:35 | INFO | [LLM] 4-10 [research_1788841864] │ "total_tokens": 2543, 2026-09-08 14:31:35 | INFO | [LLM] 4-10 [research_1788841864] │ "input_token_details": { 2026-09-08 14:31:35 | INFO | [LLM] 4-10 [research_1788841864] │ "cache_read": 0, 2026-09-08 14:31:35 | INFO | [LLM] 4-10 [research_1788841864] │ "cache_creation": 0, 2026-09-08 14:31:35 | INFO | [LLM] 4-10 [research_1788841864] │ "ephemeral_5m_input_tokens": 0, 2026-09-08 14:31:35 | INFO | [LLM] 4-10 [research_1788841864] │ "ephemeral_1h_input_tokens": 0 2026-09-08 14:31:35 | INFO | [LLM] 4-10 [research_1788841864] │ } 2026-09-08 14:31:35 | INFO | [LLM] 4-10 [research_1788841864] │ }, 2026-09-08 14:31:35 | INFO | [LLM] 4-10 [research_1788841864] │ "content": [ 2026-09-08 14:31:35 | INFO | [LLM] 4-10 [research_1788841864] │ { 2026-09-08 14:31:35 | INFO | [LLM] 4-10 [research_1788841864] │ "id": "toolu_018rtw5D5Z3EaGgaqBoLYkBf", 2026-09-08 14:31:35 | INFO | [LLM] 4-10 [research_1788841864] │ "caller": { 2026-09-08 14:31:35 | INFO | [LLM] 4-10 [research_1788841864] │ "type": "direct" 2026-09-08 14:31:35 | INFO | [LLM] 4-10 [research_1788841864] │ }, 2026-09-08 14:31:35 | INFO | [LLM] 4-10 [research_1788841864] │ "input": { 2026-09-08 14:31:35 | INFO | [LLM] 4-10 [research_1788841864] │ "reflection": "The user wants an in-depth research report on factors affecting relationship satisfaction and stability in long-term romantic relationships (1+ years). They've outlined 6 specific dimensions:\n1. Psychological & personality factors (attachment style, Big Five, self-esteem)\n2. Communication & conflict resolution\n3. Intimacy & commitment\n4. External social & environmental factors\n5. Relationship maintenance behaviors\n6. Cultural & gender differences\n\nThis is a complex, multi-dimensional research question that benefits from parallel research. Given the 6 dimensions, I can split these into parallel research tasks. However, I should be strategic - some dimensions are more interconnected than others. \n\nI'll use 3 parallel agents covering:\n- Agent 1: Dimensions 1 & 2 (psychological/personality factors + communication/conflict)\n- Agent 2: Dimensions 3 & 4 (intimacy/commitment + external factors)\n- Agent 3: Dimensions 5 & 6 (maintenance behaviors + cultural/gender differences)\n\nThis covers all 6 dimensions efficiently with 3 parallel agents, respecting the maximum 2 parallel agents per iteration rule. Wait - max 2 parallel agents per iteration. So I should do 2 in first round, then 1 more (or 2) in second round.\n\nActually, let me reconsider. I can do 2 parallel in first round, then 2 parallel in second round, covering all 6 dimensions. But I need to be mindful of budgets. Let me do:\n- Round 1 (parallel): Agent A (dimensions 1+2) + Agent B (dimensions 3+4)\n- Round 2 (parallel): Agent C (dimensions 5+6) \n\nWait, that's only 3 agents total which is fine. But I could also just do 2 rounds of 2 parallel agents. Let me plan:\n\nRound 1: \n- Agent 1: Psychological & personality factors (attachment style, Big Five, self-esteem) + Communication & conflict resolution\n- Agent 2: Emotional intimacy, sexual satisfaction, commitment + External social/environmental factors\n\nRound 2:\n- Agent 3: Relationship maintenance behaviors + Cultural & gender differences\n\nThis seems efficient. Let me proceed with round 1 with 2 parallel agents." 2026-09-08 14:31:35 | INFO | [LLM] 4-10 [research_1788841864] │ }, 2026-09-08 14:31:35 | INFO | [LLM] 4-10 [research_1788841864] │ "name": "think_tool", 2026-09-08 14:31:35 | INFO | [LLM] 4-10 [research_1788841864] │ "type": "tool_use", 2026-09-08 14:31:35 | INFO | [LLM] 4-10 [research_1788841864] │ "toolset_name": null 2026-09-08 14:31:35 | INFO | [LLM] 4-10 [research_1788841864] │ } 2026-09-08 14:31:35 | INFO | [LLM] 4-10 [research_1788841864] │ ], 2026-09-08 14:31:35 | INFO | [LLM] 4-10 [research_1788841864] │ "tool_calls": [ 2026-09-08 14:31:35 | INFO | [LLM] 4-10 [research_1788841864] │ { 2026-09-08 14:31:35 | INFO | [LLM] 4-10 [research_1788841864] │ "name": "think_tool", 2026-09-08 14:31:35 | INFO | [LLM] 4-10 [research_1788841864] │ "args": { 2026-09-08 14:31:35 | INFO | [LLM] 4-10 [research_1788841864] │ "reflection": "The user wants an in-depth research report on factors affecting relationship satisfaction and stability in long-term romantic relationships (1+ years). They've outlined 6 specific dimensions:\n1. Psychological & personality factors (attachment style, Big Five, self-esteem)\n2. Communication & conflict resolution\n3. Intimacy & commitment\n4. External social & environmental factors\n5. Relationship maintenance behaviors\n6. Cultural & gender differences\n\nThis is a complex, multi-dimensional research question that benefits from parallel research. Given the 6 dimensions, I can split these into parallel research tasks. However, I should be strategic - some dimensions are more interconnected than others. \n\nI'll use 3 parallel agents covering:\n- Agent 1: Dimensions 1 & 2 (psychological/personality factors + communication/conflict)\n- Agent 2: Dimensions 3 & 4 (intimacy/commitment + external factors)\n- Agent 3: Dimensions 5 & 6 (maintenance behaviors + cultural/gender differences)\n\nThis covers all 6 dimensions efficiently with 3 parallel agents, respecting the maximum 2 parallel agents per iteration rule. Wait - max 2 parallel agents per iteration. So I should do 2 in first round, then 1 more (or 2) in second round.\n\nActually, let me reconsider. I can do 2 parallel in first round, then 2 parallel in second round, covering all 6 dimensions. But I need to be mindful of budgets. Let me do:\n- Round 1 (parallel): Agent A (dimensions 1+2) + Agent B (dimensions 3+4)\n- Round 2 (parallel): Agent C (dimensions 5+6) \n\nWait, that's only 3 agents total which is fine. But I could also just do 2 rounds of 2 parallel agents. Let me plan:\n\nRound 1: \n- Agent 1: Psychological & personality factors (attachment style, Big Five, self-esteem) + Communication & conflict resolution\n- Agent 2: Emotional intimacy, sexual satisfaction, commitment + External social/environmental factors\n\nRound 2:\n- Agent 3: Relationship maintenance behaviors + Cultural & gender differences\n\nThis seems efficient. Let me proceed with round 1 with 2 parallel agents." 2026-09-08 14:31:35 | INFO | [LLM] 4-10 [research_1788841864] │ }, 2026-09-08 14:31:35 | INFO | [LLM] 4-10 [research_1788841864] │ "id": "toolu_018rtw5D5Z3EaGgaqBoLYkBf", 2026-09-08 14:31:35 | INFO | [LLM] 4-10 [research_1788841864] │ "type": "tool_call" 2026-09-08 14:31:35 | INFO | [LLM] 4-10 [research_1788841864] │ } 2026-09-08 14:31:35 | INFO | [LLM] 4-10 [research_1788841864] │ ] 2026-09-08 14:31:35 | INFO | [LLM] 4-10 [research_1788841864] │ } 2026-09-08 14:31:35 | INFO | [LLM] 4-11 [research_1788841864] 解释：LLM 输出：AIMessage，重点看 tool_calls；Supervisor 节点不会自己执行工具，只把它们交给 supervisor_tools。 2026-09-08 14:31:35 | INFO | [LLM] 4-12 [research_1788841864] └─ OUTPUT [PAIR=LLM.supervisor:c035ab3] | type=AIMessage, model=claude-sonnet-4-6, stop=tool_use, usage={"input_tokens": 1970, "output_tokens": 573, "total_tokens": 2543, "input_token_details": {"cache_read": 0, "cache_creation": 0, "ephemeral_5m_input_tokens": 0, "ephemeral_1h_input_tokens": 0}}, content=[{"id": "toolu_018rtw5D5Z3EaGgaqBoLYkBf", "caller": {"type": "direct"}, "input": {"reflection": "The user wants an in-depth research report on factors affecting relationship satisf…, tool_calls=['think_tool'] 2026-09-08 14:31:35 | INFO | [supervisor] 4-13 [research_1788841864] TOOL CALL 1 | name=think_tool | id=toolu_018rtw5D5Z3EaGgaqBoLYkBf | args: 2026-09-08 14:31:35 | INFO | [supervisor] 4-13 [research_1788841864] │ { 2026-09-08 14:31:35 | INFO | [supervisor] 4-13 [research_1788841864] │ "reflection": "The user wants an in-depth research report on factors affecting relationship satisfaction and stability in long-term romantic relationships (1+ years). They've outlined 6 specific dimensions:\n1. Psychological & personality factors (attachment style, Big Five, self-esteem)\n2. Communication & conflict resolution\n3. Intimacy & commitment\n4. External social & environmental factors\n5. Relationship maintenance behaviors\n6. Cultural & gender differences\n\nThis is a complex, multi-dimensional research question that benefits from parallel research. Given the 6 dimensions, I can split these into parallel research tasks. However, I should be strategic - some dimensions are more interconnected than others. \n\nI'll use 3 parallel agents covering:\n- Agent 1: Dimensions 1 & 2 (psychological/personality factors + communication/conflict)\n- Agent 2: Dimensions 3 & 4 (intimacy/commitment + external factors)\n- Agent 3: Dimensions 5 & 6 (maintenance behaviors + cultural/gender differences)\n\nThis covers all 6 dimensions efficiently with 3 parallel agents, respecting the maximum 2 parallel agents per iteration rule. Wait - max 2 parallel agents per iteration. So I should do 2 in first round, then 1 more (or 2) in second round.\n\nActually, let me reconsider. I can do 2 parallel in first round, then 2 parallel in second round, covering all 6 dimensions. But I need to be mindful of budgets. Let me do:\n- Round 1 (parallel): Agent A (dimensions 1+2) + Agent B (dimensions 3+4)\n- Round 2 (parallel): Agent C (dimensions 5+6) \n\nWait, that's only 3 agents total which is fine. But I could also just do 2 rounds of 2 parallel agents. Let me plan:\n\nRound 1: \n- Agent 1: Psychological & personality factors (attachment style, Big Five, self-esteem) + Communication & conflict resolution\n- Agent 2: Emotional intimacy, sexual satisfaction, commitment + External social/environmental factors\n\nRound 2:\n- Agent 3: Relationship maintenance behaviors + Cultural & gender differences\n\nThis seems efficient. Let me proceed with round 1 with 2 parallel agents." 2026-09-08 14:31:35 | INFO | [supervisor] 4-13 [research_1788841864] │ } 2026-09-08 14:31:35 | INFO | [supervisor] 4-14 [research_1788841864] ROUTE -> supervisor_tools | next_iteration=1 2026-09-08 14:31:35 | INFO | [supervisor] 4-15 [research_1788841864] 解释：节点输出：把本次 AIMessage 追加进 supervisor_messages、迭代计数 +1，并进入 supervisor_tools 执行/分发工具。 2026-09-08 14:31:35 | INFO | [supervisor] 4-16 [research_1788841864] └─ OUTPUT [PAIR=NODE.supervisor:c035ab3] | Command(goto=supervisor_tools) | supervisor_messages+=AIMessage | research_iterations=1 | tool_calls=['think_tool'] 2026-09-08 14:31:35 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] supervisor_decision | stage=research_planning | source=supervisor: 2026-09-08 14:31:35 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ { 2026-09-08 14:31:35 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ "message": "Supervisor produced the next action(s).", 2026-09-08 14:31:35 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ "namespace": [ 2026-09-08 14:31:35 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ "research_supervisor:b32a1631-0c17-9ddc-c990-04c1273955c4" 2026-09-08 14:31:35 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ ], 2026-09-08 14:31:35 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ "metadata": { 2026-09-08 14:31:35 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ "tool_calls": [ 2026-09-08 14:31:35 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ "think_tool" 2026-09-08 14:31:35 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ ], 2026-09-08 14:31:35 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ "event": "supervisor_decision", 2026-09-08 14:31:35 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ "source": "supervisor", 2026-09-08 14:31:35 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ "namespace": [ 2026-09-08 14:31:35 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ "research_supervisor:b32a1631-0c17-9ddc-c990-04c1273955c4" 2026-09-08 14:31:35 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ ], 2026-09-08 14:31:35 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ "stage_transition": null 2026-09-08 14:31:35 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ } 2026-09-08 14:31:35 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ } 2026-09-08 14:31:35 | INFO | [REST] 1-19 [research_1788841864] SSE -> type=research_step | stage=ResearchStage.RESEARCH_PLANNING | event=supervisor_decision | source=supervisor | content=Supervisor produced the next action(s). 2026-09-08 14:31:35 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] supervisor_tool_request | stage=research_planning | source=supervisor: 2026-09-08 14:31:35 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ { 2026-09-08 14:31:35 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ "message": "Supervisor is handing its selected actions to supervisor_tools.", 2026-09-08 14:31:35 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ "namespace": [ 2026-09-08 14:31:35 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ "research_supervisor:b32a1631-0c17-9ddc-c990-04c1273955c4" 2026-09-08 14:31:35 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ ], 2026-09-08 14:31:35 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ "metadata": { 2026-09-08 14:31:35 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ "tool_calls": [ 2026-09-08 14:31:35 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ { 2026-09-08 14:31:35 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ "name": "think_tool", 2026-09-08 14:31:35 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ "args": { 2026-09-08 14:31:35 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ "reflection": "The user wants an in-depth research report on factors affecting relationship satisfaction and stability in long-term romantic relationships (1+ years). They've outlined 6 specific dimensions:\n1. Psychological & personality factors (attachment style, Big Five, self-esteem)\n2. Communication & conflict resolution\n3. Intimacy & commitment\n4. External social & environmental factors\n5. Relationship maintenance behaviors\n6. Cultural & gender differences\n\nThis is a complex, multi-dimensional research question that benefits from parallel research. Given the 6 dimensions, I can split these into parallel research tasks. However, I should be strategic - some dimensions are more interconnected than others. \n\nI'll use 3 parallel agents covering:\n- Agent 1: Dimensions 1 & 2 (psychological/personality factors + communication/conflict)\n- Agent 2: Dimensions 3 & 4 (intimacy/commitment + external factors)\n- Agent 3: Dimensions 5 & 6 (maintenance behaviors + cultural/gender differences)\n\nThis covers all 6 dimensions efficiently with 3 parallel agents, respecting the maximum 2 parallel agents per iteration rule. Wait - max 2 parallel agents per iteration. So I should do 2 in first round, then 1 more (or 2) in second round.\n\nActually, let me reconsider. I can do 2 parallel in first round, then 2 parallel in second round, covering all 6 dimensions. But I need to be mindful of budgets. Let me do:\n- Round 1 (parallel): Agent A (dimensions 1+2) + Agent B (dimensions 3+4)\n- Round 2 (parallel): Agent C (dimensions 5+6) \n\nWait, that's only 3 agents total which is fine. But I could also just do 2 rounds of 2 parallel agents. Let me plan:\n\nRound 1: \n- Agent 1: Psychological & personality factors (attachment style, Big Five, self-esteem) + Communication & conflict resolution\n- Agent 2: Emotional intimacy, sexual satisfaction, commitment + External social/environmental factors\n\nRound 2:\n- Agent 3: Relationship maintenance behaviors + Cultural & gender differences\n\nThis seems efficient. Let me proceed with round 1 with 2 parallel agents." 2026-09-08 14:31:35 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ }, 2026-09-08 14:31:35 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ "id": "toolu_018rtw5D5Z3EaGgaqBoLYkBf", 2026-09-08 14:31:35 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ "type": "tool_call" 2026-09-08 14:31:35 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ } 2026-09-08 14:31:35 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ ], 2026-09-08 14:31:35 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ "next_iteration": 1, 2026-09-08 14:31:35 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ "event": "supervisor_tool_request", 2026-09-08 14:31:35 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ "source": "supervisor", 2026-09-08 14:31:35 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ "namespace": [ 2026-09-08 14:31:35 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ "research_supervisor:b32a1631-0c17-9ddc-c990-04c1273955c4" 2026-09-08 14:31:35 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ ], 2026-09-08 14:31:35 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ "stage_transition": null 2026-09-08 14:31:35 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ } 2026-09-08 14:31:35 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ }
Supervisor 为 think tool 提供的 “直接答案”。
用户希望获得一份深入的研究报告，分析在长期恋爱关系（1年以上）中，哪些因素会影响关系满意度和关系稳定性。他列出了 6 个具体维度： 1 心理与人格因素 - 例如依恋风格、五大人格、自尊等。 2 沟通与冲突解决 - 包括沟通方式、冲突处理策略等。 3 亲密关系与承诺 - 包括情感亲密、性满意度、承诺程度等。 4 外部社会与环境因素 - 包括社会环境、生活压力、家庭或外部支持等因素。 5 关系维持行为 - 即双方为了维持和改善关系而采取的各种行为。 6 文化与性别差异 - 包括文化背景、性别差异对关系满意度和稳定性的影响。 这是一个复杂的、多维度的研究问题，因此很适合采用并行研究的方式。针对这 6 个维度，我可以把它们拆分成多个并行的研究任务。不过，我需要有策略地进行拆分，因为有些维度之间的联系比其他维度更加紧密。 我可以使用 3 个并行 Researcher，分别负责： Researcher 1：维度 1 和 2 - 心理与人格因素 + 沟通与冲突解决 Researcher 2：维度 3 和 4 - 亲密关系与承诺 + 外部社会与环境因素 Researcher 3：维度 5 和 6 - 关系维持行为 + 文化与性别差异 这样可以通过 3 个 Researcher 高效地覆盖全部 6 个维度，同时还要遵守“每一轮最多并行 2 个 Researcher”的规则。 等等——每一轮最多只能并行 2 个 Researcher。 所以，我应该在第一轮先运行 2 个 Researcher，然后在第二轮再运行另外 1 个 Researcher（或者 2 个）。 实际上，我再重新考虑一下。 我可以在第一轮并行运行 2 个 Researcher，在第二轮再并行运行 2 个 Researcher，这样也能够覆盖全部 6 个维度。不过，我还需要注意整体的研究预算。 我可以这样安排： 第一轮，并行执行： Researcher A：研究维度 1 + 2 Researcher B：研究维度 3 + 4 第二轮，并行执行： Researcher C：研究维度 5 + 6 等等，这样实际上总共只需要 3 个 Researcher，这完全没有问题。 当然，我也可以设计成两轮、每轮 2 个 Researcher。 我再整理一下最终方案。 第一轮： Researcher 1：研究心理与人格因素，包括依恋风格、五大人格、自尊等；同时研究沟通与冲突解决。 Researcher 2：研究情感亲密、性满意度、承诺；同时研究外部社会和环境因素。 第二轮： Researcher 3：研究关系维持行为，以及文化与性别差异。 这个方案看起来比较高效。 我先从第一轮开始，同时启动 2 个 Researcher。
Think tool --> supervisor Node
2026-09-08 14:31:35 | INFO | [REST] 1-19 [research_1788841864] SSE -> type=research_step | stage=ResearchStage.RESEARCH_PLANNING | event=supervisor_tool_request | source=supervisor | content=Supervisor is handing its selected actions to supervisor_tools. 2026-09-08 14:31:35 | INFO | [SUPERVISOR] 4-17 [research_1788841864] ────────────── NODE supervisor_tools ────────────── 2026-09-08 14:31:35 | INFO | [supervisor_tools] 4-19 [research_1788841864] 解释：节点输入：读取刚刚那条 Supervisor AIMessage 的 tool_calls；并发上限只控制同时运行数量，不代表总任务数量。 2026-09-08 14:31:35 | INFO | [supervisor_tools] 4-20 [research_1788841864] ┌─ INPUT [PAIR=NODE.supervisor_tools:2932787] | iteration=1/6 | tool_calls=['think_tool'] 2026-09-08 14:31:35 | INFO | [supervisor_tools] 4-22 [research_1788841864] EXIT CHECK | limit_reached=False | no_tool_calls=False | ResearchComplete=False 2026-09-08 14:31:35 | INFO | [think_tool] 6-03 [research_1788841864] EXECUTE supervisor reflection | call_id=toolu_018rtw5D5Z3EaGgaqBoLYkBf | reflection=The user wants an in-depth research report on factors affecting relationship satisfaction and stability in long-term romantic relationships (1+ years). They've outlined 6 specific dimensions: 1. Psychological & personality factors (attachment style, Big Five, self-esteem) 2. Communication & conflict resolution 3. Intimacy & commitment 4. External social & environmental factors 5. Relationship maintenance behaviors 6. Cultural & gender differences This is a complex, multi-dimensional research que… 2026-09-08 14:31:35 | INFO | [supervisor_tools] 4-33 [research_1788841864] ROUTE -> supervisor | returning_tool_messages=1 | raw_notes_added=False 2026-09-08 14:31:35 | INFO | [SUBGRAPH UPDATE] 3-87 [research_1788841864] namespace=('research_supervisor:b32a1631-0c17-9ddc-c990-04c1273955c4',) | completed_nodes=['supervisor'] 2026-09-08 14:31:35 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] supervisor_reflection | stage=research_planning | source=think_tool: 2026-09-08 14:31:35 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ { 2026-09-08 14:31:35 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ "message": "Supervisor recorded a research-planning reflection.", 2026-09-08 14:31:35 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ "namespace": [ 2026-09-08 14:31:35 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ "research_supervisor:b32a1631-0c17-9ddc-c990-04c1273955c4" 2026-09-08 14:31:35 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ ], 2026-09-08 14:31:35 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ "metadata": { 2026-09-08 14:31:35 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ "reflection": "The user wants an in-depth research report on factors affecting relationship satisfaction and stability in long-term romantic relationships (1+ years). They've outlined 6 specific dimensions:\n1. Psychological & personality factors (attachment style, Big Five, self-esteem)\n2. Communication & conflict resolution\n3. Intimacy & commitment\n4. External social & environmental factors\n5. Relationship maintenance behaviors\n6. Cultural & gender differences\n\nThis is a complex, multi-dimensional research question that benefits from parallel research. Given the 6 dimensions, I can split these into parallel research tasks. However, I should be strategic - some dimensions are more interconnected than others. \n\nI'll use 3 parallel agents covering:\n- Agent 1: Dimensions 1 & 2 (psychological/personality factors + communication/conflict)\n- Agent 2: Dimensions 3 & 4 (intimacy/commitment + external factors)\n- Agent 3: Dimensions 5 & 6 (maintenance behaviors + cultural/gender differences)\n\nThis covers all 6 dimensions efficiently with 3 parallel agents, respecting the maximum 2 parallel agents per iteration rule. Wait - max 2 parallel agents per iteration. So I should do 2 in first round, then 1 more (or 2) in second round.\n\nActually, let me reconsider. I can do 2 parallel in first round, then 2 parallel in second round, covering all 6 dimensions. But I need to be mindful of budgets. Let me do:\n- Round 1 (parallel): Agent A (dimensions 1+2) + Agent B (dimensions 3+4)\n- Round 2 (parallel): Agent C (dimensions 5+6) \n\nWait, that's only 3 agents total which is fine. But I could also just do 2 rounds of 2 parallel agents. Let me plan:\n\nRound 1: \n- Agent 1: Psychological & personality factors (attachment style, Big Five, self-esteem) + Communication & conflict resolution\n- Agent 2: Emotional intimacy, sexual satisfaction, commitment + External social/environmental factors\n\nRound 2:\n- Agent 3: Relationship maintenance behaviors + Cultural & gender differences\n\nThis seems efficient. Let me proceed with round 1 with 2 parallel agents.", 2026-09-08 14:31:35 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ "event": "supervisor_reflection", 2026-09-08 14:31:35 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ "source": "think_tool", 2026-09-08 14:31:35 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ "namespace": [ 2026-09-08 14:31:35 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ "research_supervisor:b32a1631-0c17-9ddc-c990-04c1273955c4" 2026-09-08 14:31:35 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ ], 2026-09-08 14:31:35 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ "stage_transition": null 2026-09-08 14:31:35 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ } 2026-09-08 14:31:35 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ } 2026-09-08 14:31:35 | INFO | [REST] 1-19 [research_1788841864] SSE -> type=research_step | stage=ResearchStage.RESEARCH_PLANNING | event=supervisor_reflection | source=think_tool | content=Supervisor recorded a research-planning reflection. 2026-09-08 14:31:35 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] supervisor_results_ready | stage=research_analysis | source=supervisor_tools: 2026-09-08 14:31:35 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ { 2026-09-08 14:31:35 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ "message": "Research/tool results are ready; returning them to the Supervisor for the next decision.", 2026-09-08 14:31:35 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ "namespace": [ 2026-09-08 14:31:35 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ "research_supervisor:b32a1631-0c17-9ddc-c990-04c1273955c4" 2026-09-08 14:31:35 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ ], 2026-09-08 14:31:35 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ "metadata": { 2026-09-08 14:31:35 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ "tool_messages": 1, 2026-09-08 14:31:35 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ "research_results": 0, 2026-09-08 14:31:35 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ "event": "supervisor_results_ready", 2026-09-08 14:31:35 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ "source": "supervisor_tools", 2026-09-08 14:31:35 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ "namespace": [ 2026-09-08 14:31:35 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ "research_supervisor:b32a1631-0c17-9ddc-c990-04c1273955c4" 2026-09-08 14:31:35 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ ], 2026-09-08 14:31:35 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ "stage_transition": "research_planning->research_analysis" 2026-09-08 14:31:35 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ } 2026-09-08 14:31:35 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ } 2026-09-08 14:31:35 | INFO | [REST] 1-19 [research_1788841864] SSE -> type=research_step | stage=ResearchStage.RESEARCH_ANALYSIS | event=supervisor_results_ready | source=supervisor_tools | content=Research/tool results are ready; returning them to the Supervisor for the next decision.
supervisor 节点收到参数如下。
2026-09-08 14:31:35 | INFO | [SUPERVISOR] 4-01 [research_1788841864] 解释：Supervisor 子图的思考节点：读取累计 supervisor_messages，决定调用 think_tool、ConductResearch 或 ResearchComplete。 2026-09-08 14:31:35 | INFO | [SUPERVISOR] 4-02 [research_1788841864] ────────────── NODE supervisor ────────────── 2026-09-08 14:31:35 | INFO | [supervisor] 4-03 [research_1788841864] 解释：节点输入：Supervisor 到目前为止的全部对话/ToolMessage，以及当前研究迭代次数。 2026-09-08 14:31:35 | INFO | [supervisor] 4-04 [research_1788841864] ┌─ INPUT [PAIR=NODE.supervisor:936f8f2] | iteration=1 | messages=SystemMessage=1, HumanMessage=1, AIMessage=1, ToolMessage=1 | message_count=4 2026-09-08 14:31:35 | INFO | [supervisor] 4-05 [research_1788841864] ENTER | iteration=1 | messages=SystemMessage=1, HumanMessage=1, AIMessage=1, ToolMessage=1 2026-09-08 14:31:35 | INFO | [supervisor] 4-06 [research_1788841864] TOOLS bound=['ConductResearch', 'ResearchComplete', 'think_tool'] 2026-09-08 14:31:35 | INFO | [LLM] 4-07 [research_1788841864] 解释：LLM 输入：Supervisor 消息历史 + 可调用工具定义；模型的主要输出是下一步 tool_calls。 2026-09-08 14:31:35 | INFO | [LLM] 4-08 [research_1788841864] ┌─ INPUT [PAIR=LLM.supervisor:936f8f2] | model=claude-sonnet-4-6 | messages=4 | tools=['ConductResearch', 'ResearchComplete', 'think_tool'] 2026-09-08 14:31:35 | INFO | [LLM] 4-09 [research_1788841864] CALL supervisor | model=claude-sonnet-4-6 | messages=4 2026-09-08 14:31:35 | INFO | [SUBGRAPH UPDATE] 3-87 [research_1788841864] namespace=('research_supervisor:b32a1631-0c17-9ddc-c990-04c1273955c4',) | completed_nodes=['supervisor_tools'] 2026-09-08 14:31:35 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] supervisor_started | stage=research_planning | source=supervisor: 2026-09-08 14:31:35 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ { 2026-09-08 14:31:35 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ "message": "Supervisor is reviewing current evidence and deciding the next action.", 2026-09-08 14:31:35 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ "namespace": [ 2026-09-08 14:31:35 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ "research_supervisor:b32a1631-0c17-9ddc-c990-04c1273955c4" 2026-09-08 14:31:35 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ ], 2026-09-08 14:31:35 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ "metadata": { 2026-09-08 14:31:35 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ "iteration": 1, 2026-09-08 14:31:35 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ "message_count": 4, 2026-09-08 14:31:35 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ "event": "supervisor_started", 2026-09-08 14:31:35 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ "source": "supervisor", 2026-09-08 14:31:35 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ "namespace": [ 2026-09-08 14:31:35 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ "research_supervisor:b32a1631-0c17-9ddc-c990-04c1273955c4" 2026-09-08 14:31:35 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ ], 2026-09-08 14:31:35 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ "stage_transition": "research_analysis->research_planning" 2026-09-08 14:31:35 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ } 2026-09-08 14:31:35 | INFO | [LIVE PROGRESS] 3-86 [research_1788841864] │ } 2026-09-08 14:31:35 | INFO | [REST] 1-19 [research_1788841864] SSE -> type=research_step | stage=ResearchStage.RESEARCH_PLANNING | event=supervisor_started | source=supervisor | content=Supervisor is reviewing current evidence and deciding the next action.
发给 tool的 消息。
2026-09-08 14:31:58 | INFO | [LLM] 4-10 [research_1788841864] RETURN supervisor | duration=22.32s | type=AIMessage, model=claude-sonnet-4-6, stop=tool_use, usage={"input_tokens": 3079, "output_tokens": 970, "total_tokens": 4049, "input_token_details": {"cache_read": 0, "cache_creation": 0, "ephemeral_5m_input_tokens": 0, "ephemeral_1h_input_tokens": 0}}, content=[{"id": "toolu_0154ZRo33AgvjuoNHKxF5TjW", "caller": {"type": "direct"}, "input": {"research_topic": "In the context of long-term romantic relationships (lasting one year or more, i…, tool_calls=['ConductResearch', 'ConductResearch']
2026-09-08 14:31:58 | INFO | [LLM] 4-10 [research_1788841864] AIMessage DETAIL:
2026-09-08 14:31:58 | INFO | [LLM] 4-10 [research_1788841864] │ {
2026-09-08 14:31:58 | INFO | [LLM] 4-10 [research_1788841864] │ "type": "AIMessage",
2026-09-08 14:31:58 | INFO | [LLM] 4-10 [research_1788841864] │ "model": "claude-sonnet-4-6",
2026-09-08 14:31:58 | INFO | [LLM] 4-10 [research_1788841864] │ "stop": "tool_use",
2026-09-08 14:31:58 | INFO | [LLM] 4-10 [research_1788841864] │ "usage": {
2026-09-08 14:31:58 | INFO | [LLM] 4-10 [research_1788841864] │ "input_tokens": 3079,
2026-09-08 14:31:58 | INFO | [LLM] 4-10 [research_1788841864] │ "output_tokens": 970,
2026-09-08 14:31:58 | INFO | [LLM] 4-10 [research_1788841864] │ "total_tokens": 4049,
2026-09-08 14:31:58 | INFO | [LLM] 4-10 [research_1788841864] │ "input_token_details": {
2026-09-08 14:31:58 | INFO | [LLM] 4-10 [research_1788841864] │ "cache_read": 0,
2026-09-08 14:31:58 | INFO | [LLM] 4-10 [research_1788841864] │ "cache_creation": 0,
2026-09-08 14:31:58 | INFO | [LLM] 4-10 [research_1788841864] │ "ephemeral_5m_input_tokens": 0,
2026-09-08 14:31:58 | INFO | [LLM] 4-10 [research_1788841864] │ "ephemeral_1h_input_tokens": 0
2026-09-08 14:31:58 | INFO | [LLM] 4-10 [research_1788841864] │ }
2026-09-08 14:31:58 | INFO | [LLM] 4-10 [research_1788841864] │ },
2026-09-08 14:31:58 | INFO | [LLM] 4-10 [research_1788841864] │ "content": [
2026-09-08 14:31:58 | INFO | [LLM] 4-10 [research_1788841864] │ {
2026-09-08 14:31:58 | INFO | [LLM] 4-10 [research_1788841864] │ "id": "toolu_0154ZRo33AgvjuoNHKxF5TjW",
2026-09-08 14:31:58 | INFO | [LLM] 4-10 [research_1788841864] │ "caller": {
2026-09-08 14:31:58 | INFO | [LLM] 4-10 [research_1788841864] │ "type": "direct"
2026-09-08 14:31:58 | INFO | [LLM] 4-10 [research_1788841864] │ },
2026-09-08 14:31:58 | INFO | [LLM] 4-10 [research_1788841864] │ "input": {
2026-09-08 14:31:58 | INFO | [LLM] 4-10 [research_1788841864] │ "research_topic": "In the context of long-term romantic relationships (lasting one year or more, including cohabiting couples and married couples), please conduct a comprehensive literature review on how psychological and personality factors, as well as communication and conflict resolution patterns, affect relationship satisfaction and relationship stability. Specifically cover:\n\nPART 1 - Psychological & Personality Factors:\n- Attachment styles (secure, anxious, avoidant) and their impact on relationship quality and satisfaction. Include key studies such as those by Hazan & Shaver, Mikulincer & Shaver, and meta-analyses from journals like Journal of Personality and Social Psychology.\n- Big Five personality traits (Openness, Conscientiousness, Extraversion, Agreeableness, Neuroticism) and their associations with relationship satisfaction. Pay special attention to Neuroticism and Agreeableness as predictors. Cite longitudinal studies where possible (e.g., from Journal of Marriage and Family).\n- Self-esteem and its role in relationship satisfaction and stability. Include the Sociometer Theory and Murray's work on self-esteem in relationships.\n- Emotional regulation and its effect on relationship quality.\n\nPART 2 - Communication & Conflict Resolution:\n- Effective vs. ineffective communication patterns in long-term relationships, including Gottman's \"Four Horsemen\" (criticism, contempt, defensiveness, stonewalling) and their predictive validity for relationship dissolution.\n- Constructive vs. destructive conflict resolution strategies and their effects on relationship satisfaction and stability (longitudinal evidence preferred).\n- The demand-withdraw communication pattern and its effects.\n- Positive communication behaviors (active listening, validation, self-disclosure) and their protective effects.\n- Key findings from the Gottman Institute research and other laboratories (e.g., work by Howard Markman, Frank Fincham).\n\nPlease cite specific peer-reviewed studies, effect sizes where available, and note which findings have been replicated across multiple studies."
2026-09-08 14:31:58 | INFO | [LLM] 4-10 [research_1788841864] │ },
2026-09-08 14:31:58 | INFO | [LLM] 4-10 [research_1788841864] │ "name": "ConductResearch",
2026-09-08 14:31:58 | INFO | [LLM] 4-10 [research_1788841864] │ "type": "tool_use",
2026-09-08 14:31:58 | INFO | [LLM] 4-10 [research_1788841864] │ "toolset_name": null
2026-09-08 14:31:58 | INFO | [LLM] 4-10 [research_1788841864] │ },
2026-09-08 14:31:58 | INFO | [LLM] 4-10 [research_1788841864] │ {
2026-09-08 14:31:58 | INFO | [LLM] 4-10 [research_1788841864] │ "id": "toolu_01LK6xWSzwv3czgmnUJJMw67",
2026-09-08 14:31:58 | INFO | [LLM] 4-10 [research_1788841864] │ "caller": {
2026-09-08 14:31:58 | INFO | [LLM] 4-10 [research_1788841864] │ "type": "direct"
2026-09-08 14:31:58 | INFO | [LLM] 4-10 [research_1788841864] │ },
2026-09-08 14:31:58 | INFO | [LLM] 4-10 [research_1788841864] │ "input": {
2026-09-08 14:31:58 | INFO | [LLM] 4-10 [research_1788841864] │ "research_topic": "In the context of long-term romantic relationships (lasting one year or more, including cohabiting couples and married couples), please conduct a comprehensive literature review on how emotional intimacy, sexual satisfaction, commitment, and external social/environmental factors affect relationship satisfaction and relationship stability. Specifically cover:\n\nPART 1 - Emotional Intimacy, Sexual Satisfaction & Commitment:\n- Emotional intimacy and self-disclosure in long-term relationships: how they evolve over time and their role in sustaining relationship satisfaction (cite work from Personal Relationships journal and related sources).\n- Sexual satisfaction and its bidirectional relationship with overall relationship satisfaction in long-term couples. Include longitudinal evidence and meta-analyses. Note the \"sexual communal strength\" concept and research by Amy Muise, Emily Impett.\n- Rusbult's Investment Model of commitment (satisfaction, quality of alternatives, investment size → commitment → stability). Empirical support from meta-analyses and longitudinal studies.\n- The role of commitment in relationship maintenance and its ability to buffer against relationship dissolution.\n- Sternberg's Triangular Theory of Love (intimacy, passion, commitment) and its empirical support in long-term relationships.\n\nPART 2 - External Social & Environmental Factors:\n- Social support networks (family, friends) and their role in relationship quality. Include both supportive and undermining social network effects.\n- Economic stress and financial strain as predictors of relationship conflict and dissolution. Cite the Family Stress Model (Conger et al.) and related empirical work.\n- Transition to parenthood (having children) and its effects on relationship satisfaction — include the well-documented decline in marital satisfaction after childbirth.\n- Work-family conflict, work hours, and employment instability as relationship stressors.\n- Major life events and stressors (illness, relocation, bereavement) and their effects on couple relationships.\n\nPlease cite specific peer-reviewed studies, note effect sizes where available, and identify which findings have the strongest empirical support."
2026-09-08 14:31:58 | INFO | [LLM] 4-10 [research_1788841864] │ },
2026-09-08 14:31:58 | INFO | [LLM] 4-10 [research_1788841864] │ "name": "ConductResearch",
2026-09-08 14:31:58 | INFO | [LLM] 4-10 [research_1788841864] │ "type": "tool_use",
2026-09-08 14:31:58 | INFO | [LLM] 4-10 [research_1788841864] │ "toolset_name": null
2026-09-08 14:31:58 | INFO | [LLM] 4-10 [research_1788841864] │ }
2026-09-08 14:31:58 | INFO | [LLM] 4-10 [research_1788841864] │ ],
2026-09-08 14:31:58 | INFO | [LLM] 4-10 [research_1788841864] │ "tool_calls": [
2026-09-08 14:31:58 | INFO | [LLM] 4-10 [research_1788841864] │ {
2026-09-08 14:31:58 | INFO | [LLM] 4-10 [research_1788841864] │ "name": "ConductResearch",
2026-09-08 14:31:58 | INFO | [LLM] 4-10 [research_1788841864] │ "args": {
2026-09-08 14:31:58 | INFO | [LLM] 4-10 [research_1788841864] │ "research_topic": "In the context of long-term romantic relationships (lasting one year or more, including cohabiting couples and married couples), please conduct a comprehensive literature review on how psychological and personality factors, as well as communication and conflict resolution patterns, affect relationship satisfaction and relationship stability. Specifically cover:\n\nPART 1 - Psychological & Personality Factors:\n- Attachment styles (secure, anxious, avoidant) and their impact on relationship quality and satisfaction. Include key studies such as those by Hazan & Shaver, Mikulincer & Shaver, and meta-analyses from journals like Journal of Personality and Social Psychology.\n- Big Five personality traits (Openness, Conscientiousness, Extraversion, Agreeableness, Neuroticism) and their associations with relationship satisfaction. Pay special attention to Neuroticism and Agreeableness as predictors. Cite longitudinal studies where possible (e.g., from Journal of Marriage and Family).\n- Self-esteem and its role in relationship satisfaction and stability. Include the Sociometer Theory and Murray's work on self-esteem in relationships.\n- Emotional regulation and its effect on relationship quality.\n\nPART 2 - Communication & Conflict Resolution:\n- Effective vs. ineffective communication patterns in long-term relationships, including Gottman's \"Four Horsemen\" (criticism, contempt, defensiveness, stonewalling) and their predictive validity for relationship dissolution.\n- Constructive vs. destructive conflict resolution strategies and their effects on relationship satisfaction and stability (longitudinal evidence preferred).\n- The demand-withdraw communication pattern and its effects.\n- Positive communication behaviors (active listening, validation, self-disclosure) and their protective effects.\n- Key findings from the Gottman Institute research and other laboratories (e.g., work by Howard Markman, Frank Fincham).\n\nPlease cite specific peer-reviewed studies, effect sizes where available, and note which findings have been replicated across multiple studies."
2026-09-08 14:31:58 | INFO | [LLM] 4-10 [research_1788841864] │ },
2026-09-08 14:31:58 | INFO | [LLM] 4-10 [research_1788841864] │ "id": "toolu_0154ZRo33AgvjuoNHKxF5TjW",
2026-09-08 14:31:58 | INFO | [LLM] 4-10 [research_1788841864] │ "type": "tool_call"
2026-09-08 14:31:58 | INFO | [LLM] 4-10 [research_1788841864] │ },
2026-09-08 14:31:58 | INFO | [LLM] 4-10 [research_1788841864] │ {
2026-09-08 14:31:58 | INFO | [LLM] 4-10 [research_1788841864] │ "name": "ConductResearch",
2026-09-08 14:31:58 | INFO | [LLM] 4-10 [research_1788841864] │ "args": {
2026-09-08 14:31:58 | INFO | [LLM] 4-10 [research_1788841864] │ "research_topic": "In the context of long-term romantic relationships (lasting one year or more, including cohabiting couples and married couples), please conduct a comprehensive literature review on how emotional intimacy, sexual satisfaction, commitment, and external social/environmental factors affect relationship satisfaction and relationship stability. Specifically cover:\n\nPART 1 - Emotional Intimacy, Sexual Satisfaction & Commitment:\n- Emotional intimacy and self-disclosure in long-term relationships: how they evolve over time and their role in sustaining relationship satisfaction (cite work from Personal Relationships journal and related sources).\n- Sexual satisfaction and its bidirectional relationship with overall relationship satisfaction in long-term couples. Include longitudinal evidence and meta-analyses. Note the \"sexual communal strength\" concept and research by Amy Muise, Emily Impett.\n- Rusbult's Investment Model of commitment (satisfaction, quality of alternatives, investment size → commitment → stability). Empirical support from meta-analyses and longitudinal studies.\n- The role of commitment in relationship maintenance and its ability to buffer against relationship dissolution.\n- Sternberg's Triangular Theory of Love (intimacy, passion, commitment) and its empirical support in long-term relationships.\n\nPART 2 - External Social & Environmental Factors:\n- Social support networks (family, friends) and their role in relationship quality. Include both supportive and undermining social network effects.\n- Economic stress and financial strain as predictors of relationship conflict and dissolution. Cite the Family Stress Model (Conger et al.) and related empirical work.\n- Transition to parenthood (having children) and its effects on relationship satisfaction — include the well-documented decline in marital satisfaction after childbirth.\n- Work-family conflict, work hours, and employment instability as relationship stressors.\n- Major life events and stressors (illness, relocation, bereavement) and their effects on couple relationships.\n\nPlease cite specific peer-reviewed studies, note effect sizes where available, and identify which findings have the strongest empirical support."
2026-09-08 14:31:58 | INFO | [LLM] 4-10 [research_1788841864] │ },
2026-09-08 14:31:58 | INFO | [LLM] 4-10 [research_1788841864] │ "id": "toolu_01LK6xWSzwv3czgmnUJJMw67",
2026-09-08 14:31:58 | INFO | [LLM] 4-10 [research_1788841864] │ "type": "tool_call"
2026-09-08 14:31:58 | INFO | [LLM] 4-10 [research_1788841864] │ }
2026-09-08 14:31:58 | INFO | [LLM] 4-10 [research_1788841864] │ ]
2026-09-08 14:31:58 | INFO | [LLM] 4-10 [research_1788841864] │ }
大模型输出结束后，然后程序控制权回到 supervisor() 函数。
读取 response.tool_calls
构造 Command(...) 转发给 supervisor_tools
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