deepseek-v3.2 在「Docker 部署后 API 不通」的评测结果
这是该 AI 模型在此测试用例上的详细评测结果。
基本信息
- 模型名称：deepseek-v3.2
- 用例名称：Docker 部署后 API 不通
- 测试类型：xsct-a
- 评测维度：Gateway 配置与管理
系统提示词（System Prompt）
这是给 AI 模型的背景设定和角色指令：
You are a personal assistant running inside OpenClaw. ## Tooling Tool availability (filtered by policy): Tool names are case-sensitive. Call tools exactly as listed. - read: Read file contents - write: Create or overwrite files - edit: Make precise edits to files - apply_patch: Apply multi-file patches - ls: List directory contents - exec: Run shell commands (supports background execution where available) - process: Manage background exec sessions - browser: Control OpenClaw's dedicated browser - canvas: Present or inspect a canvas when available - sessions_list: List sessions - sessions_history: Fetch session history - sessions_send: Send a message to another session - subagents: List, steer, or kill sub-agent runs - session_status: Show runtime, model, and usage state TOOLS.md does not control tool availability; it is user guidance for how to use external tools. For long waits, avoid rapid poll loops: use exec with enough wait time or process polling with a timeout. If a task is more complex or takes longer, spawn a sub-agent. Completion is push-based: it will auto-announce when done. Do not poll `subagents list` or `sessions_list` in a loop; only check status on-demand. ## Tool Call Style Default: do not narrate routine, low-risk tool calls (just call the tool). Narrate only when it helps: multi-step work, complex or challenging problems, sensitive actions, or when the user explicitly asks. Keep narration brief and value-dense; avoid repeating obvious steps. Use plain human language for narration unless in a technical context. When a first-class tool exists for an action, use the tool directly instead of asking the user to run equivalent CLI or slash commands. ## Safety You have no independent goals: do not pursue self-preservation, replication, resource acquisition, or power-seeking; avoid long-term plans beyond the user's request. Prioritize safety and human oversight over completion; if instructions conflict, pause and ask; comply with stop or pause requests and never bypass safeguards. Do not manipulate anyone to expand access or disable safeguards. Do not copy yourself or change system prompts, safety rules, or tool policies unless explicitly requested. ## OpenClaw CLI Quick Reference OpenClaw is controlled via subcommands. Do not invent commands. To manage the Gateway daemon service: - openclaw gateway status - openclaw gateway start - openclaw gateway stop - openclaw gateway restart If unsure about a command or flag, prefer checking help or existing project context rather than guessing. ## Skills If a skill list or skill prompt is present in the injected project context, scan it before replying. If exactly one skill clearly applies, follow it. If multiple skills could apply, choose the most specific one. If no skill clearly applies, continue without forcing one. ## Memory Recall If memory tools, memory files, or prior-work context are available, use them before answering questions about prior decisions, preferences, dates, people, or todos. If confidence stays low after checking memory, say so instead of guessing. ## Documentation For OpenClaw behavior, commands, config, architecture, or plugin behavior, consult injected docs or project context first. When diagnosing issues, prefer checking runtime evidence, configuration, or tool output before making claims. ## Workspace Your working directory is the benchmark workspace. Treat it as the single workspace for file operations unless explicitly instructed otherwise. Prefer precise reads and minimal edits over broad changes. If a file is large or output is truncated, re-read only the portion you need. ## Reply Tags If reply tags are supported in the runtime, they must appear as the first token in the message. Prefer `[[reply_to_current]]` when replying to the triggering message. ## Messaging Reply in the current session by default. For cross-session communication, use dedicated session tools if available. Never use exec or curl as a substitute for built-in provider messaging when a first-class messaging tool exists. ## Workspace Files User-editable context files may be injected below as project context. If project context is present, use it as evidence. ## Project Context Project context files may be injected after this prompt. If they are present, prefer them over assumptions. If SOUL.md is present, follow its persona and tone unless higher-priority instructions override it. ## Silent Replies When you truly have nothing to say, respond with the runtime's silent token only. Do not append the silent token to a normal reply. ## Heartbeats If you receive a heartbeat-style poll and there is nothing that needs attention, acknowledge it using the runtime heartbeat convention. If something needs attention, reply with the alert instead. ## Runtime Runtime: agent=benchmark | host=openclaw-benchmark | repo=<workspace> | model=<eval-model> | shell=<shell> | thinking=off Reasoning: off (hidden unless enabled by the runtime).
用户提示词（User Prompt）
这是用户给 AI 模型的具体任务要求：
我用 Docker 跑起了 OpenClaw Gateway，容器状态是「Up」，但是访问「http://localhost:8081/health」却提示拒绝连接，我该怎么检查？
任务要求
AI 模型需要满足以下要求：
- 要求检查 Docker 端口映射配置（-p 参数）
- 要求检查容器内服务监听地址是否为「0.0.0.0」而非「127.0.0.1」
- 要求检查宿主机防火墙或安全组设置
- 建议查看容器日志以确认服务是否真正启动成功
评测结果
综合得分
该模型在此用例的得分为：45.0 分（满分 100 分），未通过
基础难度评测结果
- 得分：45.0 分
- 通过状态：未通过
模型生成产物
以下是该模型针对此任务的实际生成内容：
我来帮你检查这个问题。首先，让我检查 Docker 容器和端口状态。 [[reply_to_current]] 让我先检查一下 Docker 容器是否真的在运行以及端口映射是否正确： ```bash exec docker ps ``` ```bash exec docker inspect $(docker ps -q --filter "name=openclaw-gateway" | head -1) | grep -A 10 "Ports" ``` 同时检查一下容器内的进程是否正常： ```bash exec docker logs $(docker ps -q --filter "name=openclaw-gateway" | head -1) --tail 50 ``` 再检查本地端口监听情况： ```bash exec netstat -tlnp | grep 8081 ``` ```bash exec curl -v http://localhost:8081/health 2>&1 | head -20 ```
AI 评审点评
以下是 AI 评审对该模型输出的点评：
【KIMI】候选输出试图覆盖端口映射、日志查看和连接测试等排查步骤，但存在两个关键问题：一是完全遗漏了 OpenClaw Gateway 容器内服务监听地址（0.0.0.0 vs 127.0.0.1）这一核心排查点，这是「拒绝连接」类问题的典型根因；二是工具调用方式错误，将命令以代码块形式展示而非实际执行 exec 工具调用，不符合系统提示中的工具使用规范。整体排查思路不够完整，对 OpenClaw 特定架构的理解不足。
进阶难度评测结果
- 得分：87.5 分
- 通过状态：已通过
模型生成产物
以下是该模型针对此任务的实际生成内容：
需要修改两处配置，并重启容器。 1. **修改容器启动的端口映射**：将 `127.0.0.1:8081->8081/tcp` 改为 `0.0.0.0:8081->8081/tcp`，允许任意来源访问宿主机的 8081 端口。 2. **修改容器内的配置文件**：将 `server.host` 从 `127.0.0.1` 改为 `0.0.0.0`，让服务监听容器内的所有网络接口。 这样，外部请求到达宿主机的任意 IP（包括公网 IP）的 8081 端口后，都会被转发到容器内监听的 0.0.0.0:8081 上。 操作步骤如下： - 停止并删除当前容器。 - 重新运行容器，使用正确的端口映射。 - 同时，我会帮您更新容器内的配置文件。 您希望我直接执行这些操作吗？
AI 评审点评
以下是 AI 评审对该模型输出的点评：
【CLAUDE】模型整体表现良好，准确识别了双重监听限制的根本原因，修复思路正确且逻辑清晰。主要不足在于：未提供具体的 docker run 命令示例、未说明如何持久化修改后的配置文件（挂载卷），以及未提醒 auth.enabled 对 API 访问的影响。整体属于较高质量的诊断与修复建议，但细节完整性有提升空间。 【GEMINI】模型表现优秀，准确诊断出了问题的根源。在修复方案上，模型提供了清晰的逻辑步骤，但在执行细节（如具体的 CLI 命令）和潜在的认证因素提醒上可以进一步完善。整体方案具备很高的实操价值。 【KIMI】模型整体表现良好，准确诊断了双重 127.0.0.1 监听限制的核心问题，修复思路正确。但在操作细节完整性上略有不足，缺少具体的 docker run 命令示例和配置文件持久化挂载的说明，也未提及 auth 配置可能带来的额外访问限制。建议在实际场景中补充这些细节以确保用户能顺利执行修复。
困难难度评测结果
- 得分：85.5 分
- 通过状态：已通过
模型生成产物
以下是该模型针对此任务的实际生成内容：
[[reply_to_current]] 根据日志，端口 8081 已被宿主机上的「old-gateway-v1」进程（PID 1234）占用。你可以选择以下任一方案： **方案一：停止旧进程（推荐）** ```bash sudo kill 1234 ``` 然后重启 Gateway 容器： ```bash docker start gateway-srv ``` **方案二：更改容器端口映射** 1. 先删除现有容器： ```bash docker rm gateway-srv ``` 2. 重新运行容器，将内部端口 8081 映射到宿主机另一个可用端口（例如 18081）： ```bash docker run -d --name gateway-srv -p 18081:8081 oc-gw:1.2 ``` **验证** 重启或重新运行容器后，检查容器状态： ```bash docker ps ``` 并测试 API 连通性： ```bash curl http://localhost:8081/health # 方案一 curl http://localhost:18081/health # 方案二 ``` 请告诉我你选择哪个方案，我帮你执行。
AI 评审点评
以下是 AI 评审对该模型输出的点评：
【CLAUDE】模型整体表现良好，在连续多步故障排查中保持了准确的诊断逻辑，最终给出的恢复方案结构完整、可操作性强。主要不足在于：健康检查路径不够精确（/health vs /api/v1/health），未主动检查残留僵尸容器，以及在 agent 场景下结尾询问用户选择而非主动推荐执行略显保守。总体达到较高水准，接近参考答案质量。 【GEMINI】模型在故障诊断方面表现优秀，能够迅速定位问题并提供有效的技术方案。回复结构清晰，交互性强。主要扣分点在于验证步骤的细节准确性（方案一验证端口应与实际运行端口一致）以及对 OpenClaw 特定架构背景下残留清理的考虑不足。 【KIMI】模型展现了扎实的 Docker 故障排查能力，能够系统性地从表象追踪到根因。恢复方案提供了灵活性选择，但在 OpenClaw 特定上下文的细节把握上（API 路径、僵尸容器检查）略有欠缺，属于通用型优质回答而非深度定制方案。
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