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","maintainers":[{"name":"mcgrapeng","email":"mcgrapengzhang@gmail.com"}],"readme":"
\n\n\n \n \"Innies\n\n\n

\n 知满科技 AI 编码助手
\n 基于 OpenAI Codex 深度定制 · 模型替换为知满自研 qwen35_35b\n

\n\n

\n \"license\"\n \"node\"\n \"platform\"\n \"model\"\n \"context\"\n

\n\n\n 速览 ·\n 安装 ·\n Provider 配置 ·\n 快速上手 ·\n 差异 ·\n 🛣️ 路线 ·\n 🧪 验证 ·\n ⚠️ 风险 ·\n 文档\n\n\n
\n\n---\n\n## 速览\n\n> [!NOTE]\n> 把官方 Codex CLI 的\"大脑\"换成知满自研模型 `qwen35_35b`，骨架（Agent 编排、TUI、MCP、沙箱、SDK）原样保留。\n\n| 维度 | 内容 |\n| :--- | :--- |\n| **为什么换** | 数据不出境 · 无需 ChatGPT 账号 · 可私有化部署到客户机房 · 与原版 Codex 配置完全隔离 |\n| **核心取舍** | `qwen35_35b` 综合推理弱于 GPT-5 · 不支持并行工具调用 · 长链路重构需更多人工拆解 |\n| **谁该用** | 合规优先、内网部署、可接受\"能力换主权\"的团队 |\n| **谁不该用** | 追求最强模型能力、复杂长链路推理、不要求数据驻留的场景——请继续用官方 Codex / Claude Code |\n\n---\n\n## 安装\n\n```bash\nnpm install -g @zhiman_innies/innies-codex@latest\ninnies --version\n```\n\n> 要求：Node.js ≥ 16 · macOS 12+ / Windows 10/11（**Linux 不支持**，启动时编译期强制退出）\n>\n> 源码构建参见 [`docs/install.md`](docs/install.md)。\n\n---\n\n## First-Run Setup (重要 · N20)\n\n> [!WARNING]\n> **首次跑 `innies` 之前,必须先配置 base_url 和 api key,否则会立即报:**\n>\n> ```\n> ERROR: Missing environment variable: ZHIMAN_BASE_URL (or [model_providers.zhiman_35b].base_url)\n> ```\n>\n> 这是 N20 fresh-install 阻断 — 因为模板里 base_url 是注释占位符,而 Rust provider resolver 会在 env_key 缺失时**静默回退**到 `api.openai.com/v1`(见 [`docs/n20-fresh-install-base-url-fail.md`](docs/n20-fresh-install-base-url-fail.md))。\n\n**三种配置方式任选其一(优先级从高到低):**\n\n### 1. 环境变量 (推荐用于 CI / 无交互场景)\n\n```bash\n# 私有部署 (zhiman_35b / zhiman_27b 共享 ZHIMAN_API_KEY,见模板注释)\nexport ZHIMAN_API_KEY=\"sk-...\"\nexport ZHIMAN_BASE_URL=\"http://your-private-deployment/v1\" # 可选,覆盖 config.toml\n\n# 阿里云 dashscope 公网\nexport DASHSCOPE_API_KEY=\"sk-...\"\nexport DASHSCOPE_BASE_URL=\"https://dashscope.aliyuncs.com/compatible-mode/v1\" # 可选\n```\n\n`export` 到 `~/.zshrc` 或 `~/.bashrc` 后 `source` 一下即持久化。\n\n### 2. 编辑 `~/.inniescoder/config.toml`\n\n```bash\n# 第一次跑会自动创建 config.toml\ninnies 2>&1 | head -5 # 看到 [innies-onboarding] 横幅后 Ctrl+C 中断\n# 然后编辑 ~/.inniescoder/config.toml,取消下面这种行的 # 号:\n# # base_url = \"http://your-private-deployment/v1\" # FILL IN: ...\n# # env_key = \"ZHIMAN_API_KEY\" # FILL IN: ...\n# 取消注释 + 填值后保存。env_key 是\"环境变量名\"(不是 key 本身),然后确保那个\n# env var 已经在你的 shell 里 export 过(或写在 rc 文件里)。\n```\n\n### 3. Interactive 引导 (默认首次跑触发)\n\n```bash\ninnies # 不要 pipe,保持 stdin 是 TTY\n```\n\n首次跑会打印:\n\n```\n=============================================================================\n[innies-onboarding] 首次运行检测 (N20 fresh-install 阻断防护)\nconfig.toml: /Users/you/.inniescoder/config.toml\n\n检测到以下 provider 块的 base_url 仍是占位符(注释状态):\n - [model_providers.zhiman_35b] base_url = \"http://your-private-deployment/v1\"\n - [model_providers.zhiman_27b] base_url = \"http://your-private-deployment/v1\"\n - [model_providers.dashscope] base_url = \"https://dashscope.aliyuncs.com/compatible-mode/v1\"\n\n请选择配置方式:\n 1. 现在交互式填入 base_url 和 api key (推荐) — 写回 config.toml\n 2. 跳过,我会自己编辑 /Users/you/.inniescoder/config.toml\n 3. 退出 innies\n> \n```\n\n- **选项 1**: 逐步输入每个 provider 的 `base_url` 和 env_key 名,自动写回 `config.toml`,然后继续启动 innies。\n- **选项 2**: 跳过(接受 N20 会 fail)。之后自己编辑 `~/.inniescoder/config.toml` 填值。\n- **选项 3**: 退出 innies(`process.exit(0)`),让你先手动配。\n\n**跳过引导**: 设 `export INNIES_SKIP_ONBOARDING=1` 后跑 `innies`,永远不弹引导横幅。CI / smoke 测试用。\n\n**详见 `~/.inniescoder/config.toml` 顶部的 `⚠️ FIRST-RUN SETUP REQUIRED` 横幅注释(模板在 [`codex-cli/bin/innies-config.js`](codex-cli/bin/innies-config.js) 的 `defaultInniesConfig` 里,首次 `innies` 启动时会写入)。**\n\n---\n\n## Provider 配置\n\n> [!IMPORTANT]\n> **首次安装的硬约束（2026-06-10 起）**：`npm install -g` 写入 `~/.inniescoder/config.toml` 时，会自动创建 `zhiman` 与 `bailian` 两个 provider 块且每个必要 key 都存在，**但 `base_url` 与 `env_key` 一律留空** —— 由你或实施团队事后填值。一旦你或任何工具写入非空值，**`npm install`、`innies` 启动、模型切换都不会再覆盖它们**。\n\n首次运行 `innies` 会在 `~/.inniescoder/config.toml`（Windows: `%USERPROFILE%\\.inniescoder\\config.toml`，或环境变量 `INNIES_HOME` 指向的目录）写入默认配置：\n\n```toml\nmodel_provider = \"zhiman\" # 私有化部署 / 评估（知满网关）\nmodel = \"qwen35_35b\" # 模型 slug，可切换 qwen36_27b / qwen3.6-27b\n\n[model_providers.zhiman]\nname = \"zhiman\"\nbase_url = \"\" # ← 由用户填值；空串 = 启动器会失败并提示\nwire_api = \"responses\"\nenv_key = \"ZHIMAN_API_KEY\"\n\n[model_providers.bailian]\nname = \"bailian\"\nbase_url = \"\" # ← 由用户填值（dashscope 公网 URL）\nwire_api = \"responses\"\nenv_key = \"BAILIAN_API_KEY\"\n```\n\n### 两个 provider 块的语义\n\n| 块 | 用途 | 典型部署 | 可用模型 slug |\n| :--- | :--- | :--- | :--- |\n| `[model_providers.zhiman]` | **私有化**（评估期走知满网关、生产期走客户机房内网） | http://101.237.37.116:7380/v1（评估）· `https:///v1`（生产） | `qwen36_27b` · `qwen35_35b` |\n| `[model_providers.bailian]` | **阿里百炼公网**（dashscope） | https://dashscope.aliyuncs.com/compatible-mode/v1 | `qwen3.6-27b` |\n\n切换模型只需要改**根**字段：\n\n```bash\n# 私有化 · 35B（默认）\nexport INNIES_MODEL='model = \"qwen35_35b\"' # + model_provider = \"zhiman\"\n\n# 私有化 · 27B\nexport INNIES_MODEL='model = \"qwen36_27b\"' # + model_provider = \"zhiman\"\n\n# 公网 · 27B\nexport INNIES_MODEL='model = \"qwen3.6-27b\"' # + model_provider = \"bailian\"\n```\n\n填 `base_url`：\n\n```toml\n# 私有化生产（你客户机房内网地址）\n[model_providers.zhiman]\nbase_url = \"https:///v1\"\n\n# 公网\n[model_providers.bailian]\nbase_url = \"https://dashscope.aliyuncs.com/compatible-mode/v1\"\n```\n\nAPI Key 通过环境变量注入，**不要**写进 `config.toml`：\n\n```bash\nexport ZHIMAN_API_KEY=\"...\" # 私有化\nexport BAILIAN_API_KEY=\"...\" # 公网 dashscope\n# 写入 ~/.zshrc 或 ~/.bashrc 后持久化\n```\n\n### 不覆盖用户值（核心约束）\n\n`normalizeProviderBlock` 的语义（截至 v0.122.46）：\n\n> 对 `name` / `base_url` / `wire_api` / `env_key` / `model_slug` 这五个 key： \n> **若用户已写入非空值，保留**；仅当值为空 / 全空白时才写入占位。 \n> `stripReservedProviderBlocks` 改为 **noop**（即便你写了 `[model_providers.openai]` 等块，npm install 也不会删除）。 \n> `stripManagedRootSettings` 同样只 strip **空值**：根 `model_provider` / `model` 一旦被你填过，启动器永不触碰。\n\n可执行 [`scripts/innies-isolation-validate.sh`](scripts/innies-isolation-validate.sh) 验证 7 轮不变量：首次安装 / 用户 base_url 保留 / 缺失整块自动补齐 / 幂等 / `INNIES_HOME` 覆写 / `~/.codex` 严格隔离 / 用户自定义 key 保留。\n\n### 与原生 Codex 的隔离\n\n| 维度 | Innies Codex | 官方 Codex |\n| :--- | :--- | :--- |\n| 配置目录 | `~/.inniescoder/` | `~/.codex/` |\n| `INNIES_HOME` | ✅ 可改写 home 目录 | — |\n| 互相读取 | ❌ 完全隔离 | ❌ 完全隔离 |\n| `npm install` 时副作用 | 仅写 `~/.inniescoder/*` | — |\n\n`innies-isolation-validate.sh` 第 6 轮在快照前后对比 `~/.codex/` 文件清单，**任何文件增减即视为隔离破坏，验证失败**。\n\n完整步骤与历史迁移指南：[`docs/Inniescoder用户使用手册.md`](docs/Inniescoder用户使用手册.md) · 字段参考：[`docs/config.md`](docs/config.md)\n\n---\n\n## 快速上手\n\n```bash\ncd /path/to/your/project\n\ninnies # 交互式 TUI\ninnies exec \"运行所有测试并总结失败用例\" # 非交互执行，适合 CI\ninnies review --base main # 代码审查\ninnies app-server # JSON-RPC + WebSocket，供 IDE/系统集成\n```\n\n---\n\n## 与原生 Codex 的差异\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
维度Innies Codex官方 OpenAI Codex
默认模型qwen35_35b（知满自研 35B）gpt-5.4 / gpt-5.3-codex
数据流向知满网关（评估）/ 客户机房内网（生产）OpenAI 海外
接入门槛API KeyChatGPT 订阅或 OpenAI API
配置目录~/.inniescoder/（独立）~/.codex/
TUI 品牌Zhiman ASCII 字 + 中文文案OpenAI 原版
备选模型百炼公网 qwen3.6-27b（provider bailian）· 私有化 qwen36_27b / qwen35_35b（provider zhiman）—
稳定性补丁qwen streaming · 命令中断 · 首启报错等 10+ 项—
Agent / MCP / 沙箱 / SDK与上游完全一致
\n\n> [!TIP]\n> **设计原则**：*只换大脑，不换骨架。* 上游 Codex 每个 release 都会跟进，定制点仅落在模型层、品牌层、稳定性补丁层。\n\n---\n\n## 🛣️ 迭代路线\n\n| 阶段 | 状态 | 内容 |\n| :--- | :---: | :--- |\n| **v1 · CLI Agent** | ✅ 已发布 | 稳定的 TUI / `exec` / `review` / `app-server` 入口，知满 `qwen35_35b` 适配，14 项 Superpowers 技能 |\n| **v2 · 私有化部署套件** | 🟢 进行中 | 推理服务镜像、Helm Chart、模型权重交付、客户机房一键部署 |\n| **v3 · InniesCoding 端到端工作流** | 🟡 内测 | 由自然语言需求自动驱动的五阶段管线，详见下文 |\n| **v4 · IDE 插件 / Web 控制台** | ⚪ 规划中 | 基于现有 App Server 能力延伸 |\n\n### InniesCoding 端到端工作流（v3 预览）\n\n`InniesCoding` 是建在 Innies Codex 之上的**研发自动化管线**，由 RAG（检索增强）与 KG（知识图谱）MCP server 驱动，将一个自然语言需求拆解为五个可追溯阶段：\n\n```\n需求分析 → 代码定位与影响评估 → Spec 生成 → 代码变更 → 测试用例补全\n```\n\n| 阶段 | 输入 | 输出 |\n| :--- | :--- | :--- |\n| `requirement_analysis` | 原始需求 | PRD 草稿（含 RAG 证据 + KG 影响范围） |\n| `code_search_and_assessment` | PRD + 项目代码 | 受影响文件、调用链、风险点 |\n| `spec_generation` | 影响范围 | 技术 Spec |\n| `code_change` | Spec | 代码补丁 |\n| `test_case_lookup_and_generation` | 变更 | 单元 / 集成测试用例 |\n\n> [!NOTE]\n> 当前以 `INNIES_CODING_STAGE` 环境变量内部触发，公开版本将以 `innies coding ` 子命令形式暴露。实现入口见 [`codex-cli/bin/innies-coding-runtime.js`](codex-cli/bin/innies-coding-runtime.js)。\n\n---\n\n## 🧪 质量验证现状\n\n> [!NOTE]\n> 基于 [`docs/innies-qwen35-*`](docs/) 系列报告的真实压测产出。最近一次验收：**2026-05-24**。\n\n### 已完成\n\n| 验证项 | 结果 | 证据 |\n| :--- | :---: | :--- |\n| 全链路功能矩阵（CLI / API / Skills / Output Schema / Spawn Agent） | ✅ | [full-chain 2026-05-17](docs/innies-qwen35-full-chain-test-report-2026-05-17.md) |\n| 单用户基线 | ✅ | [single-user 2026-05-17](docs/innies-qwen35-single-user-test-report-2026-05-17.md) |\n| 30 并发 API 突发 | ✅ 30/30 | full-chain 2026-05-17 |\n| **复杂任务通过率（A 计划验收）** | **✅ 118/120 = 98.3%** | [complex-task-fix-report 2026-05-24](docs/innies-qwen35-complex-task-fix-report-2026-05-24.md) |\n| · `multi_agent_review` | ✅ 40/40 = 100%（60% → 100%） | 同上 |\n| · `system_design` | ✅ 38/40 = 95%（75% → 95%） | 同上 |\n| · `superpowers_chain` | ✅ 40/40 = 100% | 同上 |\n| 长稳 harness + 监控脚本就绪 | ✅ | [`scripts/long_soak.py`](scripts/long_soak.py) · [`scripts/long_soak_monitor.py`](scripts/long_soak_monitor.py) |\n| 长稳预演（1h 子集） | ✅ | corpus `long-soak-preflight-20260524-*` |\n| **8 小时长稳正式跑（B 计划验收）** | **✅ 302/303 = 99.67%** | [long-soak-report 2026-05-26](docs/innies-qwen35-long-soak-report-2026-05-26.md) |\n| · `superpowers_chain` | ✅ 27/27 = 100% | 同上 |\n| · `multi_agent_review` | ✅ 27/27 = 100% | 同上 |\n| · `system_design` | ✅ 26/27 = 96.3%（1 次超时，无熔断） | 同上 |\n| · KV cache 命中率 | ✅ 83.6%（37.4M input / 31.3M cached） | 同上 |\n| 失败语料库（供后续 SFT/DPO） | ✅ 4 个样本 | [`docs/qwen35-finetune-corpus/`](docs/qwen35-finetune-corpus/) |\n\n### 进行中 / 未完成\n\n| 验证项 | 状态 | 说明 |\n| :--- | :---: | :--- |\n| 100+ 并发 API 突发 | ❌ 已知失败 | 43/102，45s 超时；待服务端容量整改后复跑 |\n| 长稳复跑（次日不同时段） | ⚪ 未启动 | B 计划首跑已验收，复跑视客户落地节奏安排 |\n| 24h / 7×24 持续运行 | ⚪ 未启动 | 8h 已达标，24h 验证服务长尾稳定性 |\n| Windows 平台行为 | ⚪ 未验证 | 当前全部测试仅在 macOS 跑过；Linux 已编译期强制禁用 |\n| 客户机房私有化部署后的长稳 | ⚪ 未验证 | 实施时与客户联合验证 |\n| 多机器分布式 agent / 故障注入 / 多租户 | ⚪ 未启动 | B 计划延伸事项 |\n\n### 已落地的工程工件（A 计划，2026-05-24）\n\n- 失败归因脚本 [`scripts/classify_complex_failures.py`](scripts/classify_complex_failures.py)\n- output_schema 压测 [`scripts/schema_pressure.py`](scripts/schema_pressure.py)\n- 长稳 harness [`scripts/long_soak.py`](scripts/long_soak.py)（419 行）\n- 长稳监控 [`scripts/long_soak_monitor.py`](scripts/long_soak_monitor.py)（含 RSS / FD / 目录大小 / 崩溃信号）\n- 三路径修复（B1 Prompt 末尾固化 marker · B2 强制 output_schema · B3 Harness 层 re-prompt 兜底）合并进主压测 runner\n\n---\n\n## ⚠️ 已知限制与风险\n\n> [!WARNING]\n> 以下内容**基于代码与配置事实**列出，落地前请完整阅读。\n\n### 1. 模型能力差距是真实存在的\n\n`qwen35_35b` 在以下维度**可被代码直接证实**地弱于 GPT-5 系列：\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
能力qwen35_35bgpt-5.4 / Claude 4.7
并行工具调用❌ supports_parallel_tool_calls: false✅
推理强度档位❌ supported_reasoning_levels: []（无 high/medium/low）✅
输出截断阈值10 000 tokens（较激进）同
综合代码任务主观体验：复杂多文件重构、长链路调试明显落后
\n\n**实际影响**：\n\n- 一次 turn 里需要\"读 5 个文件 + grep 3 次\"时，`qwen35_35b` 会**串行**逐个发起，整体延迟约为 GPT-5 的 2-3 倍\n- 跨 10+ 文件的架构级重构需要更多人工拆解和多轮迭代，**不要期望一次到位**\n- 不能通过 `model_reasoning_effort` 让模型\"想久一点\"——这个开关对 `qwen35_35b` 无效\n\n> [!TIP]\n> **已工程化缓解**：复杂任务里\"指令跟随不稳定\"（如 final marker 缺失）这类故障，已通过 A 计划落地的三路径修复（Prompt 末尾固化 marker + 强制 output_schema + Harness re-prompt 兜底）将 `multi_agent_review` 从 60% 提升到 100%、`system_design` 从 75% 提升到 95%。详见 [质量验证现状](#-质量验证现状)。模型本身的并行/推理档位差距仍然存在。\n\n### 2. 上游跟随有滞后与冲突风险\n\n- 仓库跟随官方 Codex 每个 release（最近一次 `rust-v0.122.32`）\n- 上游做 breaking change 时，定制点（品牌、模型目录、隔离逻辑）需要手动 cherry-pick，**预期延迟 1~2 周**\n- 上游 OpenAI 一旦移除 Responses API 或调整工具调用 schema，`qwen35_35b` 适配需追加工作量\n\n### 3. 治理边界仅覆盖到本机\n\n- macOS 沙箱基于 Seatbelt（`sandbox-exec`），Windows 沙箱能力受限（仅文件系统 ACL）；**Linux 不在支持范围内**，启动时即报错退出\n- 没有组织级 IAM、角色、审计后台——多人协作的合规治理需对接外部系统\n- API Key 是单 token、无作用域、无过期——一旦泄露需手动轮换全员\n\n### 4. 许可与权属\n\n- 仓库代码遵循 **Apache-2.0**（见 [`LICENSE`](LICENSE)）\n- `qwen35_35b` 模型权重**不在本仓库**，使用知满推理服务即受其商务条款约束；客户机房私有化部署的权重交付由知满实施团队处理\n- TUI 品牌字、`Zhiman` 商标属知满科技\n\n### 5. 工具默认曝光（设计取舍）\n\n3 个 qwen 模型在 catalog 里 `experimental_supported_tools = []`，意味着：\n\n- ✅ **默认开**：`shell` / `exec_command` / `apply_patch`（后者需 `features.apply_patch_freeform = true`，模板已开）\n- ❌ **默认禁**：`list_dir`、`read_file` 等独立工具；模型遇到目录/文件读取需求时会自动 fallback 到 `shell ls` / `shell cat`，功能等价但 token 略多\n\n如确需 `list_dir` 作为独立工具暴露给模型（例如对延迟敏感的批量目录扫描场景），编辑 `~/.inniescoder/catalog.json`：\n\n```jsonc\n{\n \"slug\": \"qwen36_27b\",\n // ... 其他字段\n \"experimental_supported_tools\": [\"list_dir\"] // 加入想曝光的工具名\n}\n```\n\n> 这是**有意保留**的默认取舍 — 既能维持 prompt 简洁、避免 qwen 模型在工具选择上 over-think，又给需要的用户留出 catalog-level 配置开关。\n\n---\n\n## 文档\n\n| 文档 | 内容 |\n| :--- | :--- |\n| [`docs/Inniescoder用户使用手册.md`](docs/Inniescoder用户使用手册.md) | 面向最终用户的安装 / 配置 / 升级 / 卸载 / FAQ |\n| [`docs/Inniescoder能力支持说明.md`](docs/Inniescoder能力支持说明.md) | 代码辅助能力逐项对照表 |\n| [`docs/install.md`](docs/install.md) | 从源码构建 |\n| [`docs/config.md`](docs/config.md) | `config.toml` 字段参考 |\n| [`docs/sandbox.md`](docs/sandbox.md) | 沙箱与审批策略 |\n| [`docs/skills.md`](docs/skills.md) | Skill 注入机制 |\n| [`docs/innies-qwen35-complex-task-fix-plan.md`](docs/innies-qwen35-complex-task-fix-plan.md) | **A 计划**：复杂任务成功率整改方案 |\n| [`docs/innies-qwen35-complex-task-fix-report-2026-05-24.md`](docs/innies-qwen35-complex-task-fix-report-2026-05-24.md) | **A 计划验收报告**（98.3% 通过率） |\n| [`docs/innies-qwen35-long-soak-plan.md`](docs/innies-qwen35-long-soak-plan.md) | **B 计划**：8 小时长稳运行方案 |\n| [`docs/innies-qwen35-long-soak-report-2026-05-26.md`](docs/innies-qwen35-long-soak-report-2026-05-26.md) | **B 计划验收报告**（302/303 = 99.67% 通过率） |\n| [`docs/innies-qwen35-high-concurrency-plan.md`](docs/innies-qwen35-high-concurrency-plan.md) | 高并发整改计划（多 key 池 / 多端点 / 熔断） |\n| [`docs/innies-qwen35-stability-test-report-2026-05-19.md`](docs/innies-qwen35-stability-test-report-2026-05-19.md) | 修复前稳定性基线报告 |\n| [`docs/innies-qwen35-*.md`](docs/) | 其他 qwen35 全链路 / 单用户 / 早期报告 |\n| [`AGENTS.md`](AGENTS.md) | 贡献者必读（Rust 规范、测试约定） |\n| [`SECURITY.md`](SECURITY.md) | 安全披露流程 |\n\n---\n\n
\n\n· ✦ ·\n\n问题反馈 · 定制需求 → 知满科技\n
\nZhiman · intent in motion\n\n
\n","readmeFilename":"README.md"}