diff --git a/submissions/mcp-hackathon/yai-agent-core/RIGHTS.md b/submissions/mcp-hackathon/yai-agent-core/RIGHTS.md new file mode 100644 index 0000000..637af5e --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/RIGHTS.md @@ -0,0 +1,56 @@ +# RIGHTS · 权利与授权声明 + +## 1. 提交人 + +- 提交团队：**YAI**（单人团队） +- 提交人 / 版权人：**Gi-Tuu**（https://github.com/Gi-Tuu） +- 项目仓库：https://github.com/Gi-Tuu/yai-agent-core +- 提交人声明：本项目全部代码、文档、示例均由本人原创编写，对代码、服务、依赖与数据拥有提交所需的全部权利；不存在未披露的第三方代码抄袭、虚假部署或身份操纵。 + +## 2. 项目许可证 + +本项目以 **MIT License** 开源，许可证全文见 `source/LICENSE`： + +> Copyright (c) 2026 Gi-Tuu + +任何人（含 X-Agent 评审与后续 MCP 标准化流程）可在 MIT 条款下使用、复制、修改、合并、发布、再许可与分发。 + +## 3. 第三方依赖许可证 + +内核本体（`src/yai_core/` 的核心部分）**零第三方运行时依赖**，仅使用 Python 标准库。 +下列依赖全部为可选 extras（按需安装、模块内懒加载），均为 MIT / BSD / Apache 类宽松许可证，完整版本锁定见 `source/uv.lock`，各依赖的许可证原文随其分发包提供： + +| 依赖（extras） | 用途 | 许可证 | +|---|---|---| +| openai（llm） | OpenAI 兼容模型客户端（线上接 DeepSeek） | Apache-2.0 | +| fastapi（server） | HTTP API 框架 | MIT | +| uvicorn[standard]（server） | ASGI 服务器 | BSD-3-Clause | +| pydantic（server） | 请求模型与数据校验 | MIT | +| starlette（fastapi 传递依赖） | ASGI 工具集 | BSD-3-Clause | +| mcp（mcp） | 官方 Model Context Protocol Python SDK v2 | MIT | +| anyio / httpx / httpcore（传递依赖） | 异步与 HTTP 运行时 | MIT / BSD-3-Clause | +| pydantic-core / typing-extensions / sniffio / h11 / idna 等 | 运行时支撑库 | MIT / BSD / PSF 类宽松许可 | + +开发期工具（pytest、ruff、python-docx 等）仅用于测试与文档构建，**不进入运行时镜像与服务**。 +如评审需要逐包许可证清单，可在隔离环境执行 `uv tree` / 查看 `uv.lock` 完整复现。 + +## 4. 数据与外部服务 + +- 线上服务不采集、不存储、不转发任何用户个人数据；内置示例数据（3 条演示笔记、演示天气文案）均为虚构。 +- 运行时唯一的外部出站请求是发往模型 API（线上为 DeepSeek，https://api.deepseek.com）的任务推理请求，遵循该服务方的公开服务条款；提交人对发送内容负责，不包含任何第三方隐私数据。 +- 不使用任何未授权的付费资源、私有数据集或抓取数据。 + +## 5. 提交与存档授权 + +提交人授权 X-Agent 官方及评审流程： + +1. 在隔离评审环境中拉取、构建、运行本提交的 `source/` 与在线服务，进行硬门槛校验、源码评审、安全与数据审查； +2. 在通过评审后，将与评审基线 commit 一致的完整源码复制到官方存档 ref、生成不可变的验收 release； +3. 对入选项目按公开规则进行 MCP 标准化适配（适配器与提交包由 X-Agent 侧拥有，底层能力的真实性、运行与维护责任由提交人承担）。 + +提交人理解：通过评审不构成 OKX 收录、上架、流量或收益的承诺；撤回未合并 PR 即视为退赛；已验收/获奖的源码将保留在官方存档中。 + +## 6. 商标与署名 + +- "YAI Agent Core" 与 "AMBRACE（拥爱）"为提交人自有项目名称； +- DeepSeek、OKX、X-Agent、Render、GitHub 等名称归各自权利人所有，本项目仅作技术兼容性描述，不暗示任何背书或关联关系。 diff --git a/submissions/mcp-hackathon/yai-agent-core/SUBMISSION.md b/submissions/mcp-hackathon/yai-agent-core/SUBMISSION.md new file mode 100644 index 0000000..df69135 --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/SUBMISSION.md @@ -0,0 +1,111 @@ +# YAI Agent Core · X-Agent MCP Hackathon 提交说明 + +- **项目名**：YAI Agent Core（yai-agent-core） +- **提交团队**：YAI（单人开发者 Gi-Tuu，https://github.com/Gi-Tuu） +- **一句话定位**：进程内嵌入式、自适应的 Agent 内核——已有软件只需声明自己的普通业务函数（或挂载 MCP Server），Core 自动发现能力、自适应选择执行策略并完成任务，**宿主不写一行 Agent Loop / Planner / 工具选择代码**。 +- **在线 API**：https://yai-agent-core.onrender.com +- **源码仓库**：https://github.com/Gi-Tuu/yai-agent-core（MIT） +- **评审基线 commit**：以 `submission.json` 的 `reviewCommit`（40 位 SHA）为准，与 `/health`、`/.well-known/xagent-verification.json` 三处一致。 + +--- + +## 1. 解决什么真实问题 + +市面上的 Agent 形态分两类：平台型（Dify/Coze，要把东西搬进别人的云）和框架型（LangGraph/OpenAI Agents SDK，开发者仍要自己定义 Agent、工具、编排）。 +大量已有软件（笔记应用、数据后台、陪伴 App）想要 Agent 能力，但不想重写、不想上云、也不想在业务代码里堆 Agent 胶水代码。 + +YAI Agent Core 类比"Agent 世界的 SQLite"：以库的形式运行在宿主进程内，范式是 **host-declares-capability / core-adapts**： + +1. 宿主只提供普通 Python 函数（type hints + docstring），Core 内省生成工具规格； +2. 外部 MCP Server 的工具经 MCP Client 同构接入（v0.2 已落地）； + Core 同时内置 OpenAPI 发现（可选）：任意 OpenAPI 3 REST API 提供描述即可被自动注册为工具， + 与 MCP 工具在同一 Tool Bus 上同构调度（read_only 只读模式可用于公网演示）； +3. Adaptive Router 把任务路由到 `direct / react / plan / clarify` 四种策略： + v0.2 起先由模型做一次轻量分类（输出 `{strategy, reason, tier}` JSON）， + 超时/异常/非法输出自动回退确定性规则，**两条路径都返回带来源的决策记录**； +4. Agent Loop 完成 ReAct 工具循环 / 计划拆解执行（规划轮使用路由建议的模型档位）； +5. 每一次策略选择（含 `source=llm|rules` 与理由）、工具调用、权限确认都作为事件流出， + **过程可审计，不是黑盒**。 + +它不是又一个需要开发者拼装的 Agent 框架，而是可以"装进软件里"的内核；项目最终将回流嵌入开源 AI Companion 项目 AMBRACE。 + +## 2. 在线能力（评审可直接调用） + +| 端点 | 方法 | 说明 | +|---|---|---| +| `/health` | GET | 健康检查，返回 `status` 与本次部署的 40 位 commit | +| `/.well-known/xagent-verification.json` | GET | 部署证明：`schemaVersion=1` + `slug` + `commit` | +| `/v1/tools` | GET | 当前宿主注册的全部工具（含 `source: native/mcp/openapi` 来源标注；线上实例同时挂载本地笔记工具与公共 DeepWiki MCP Server 的 3 个远程工具） | +| `/v1/agent/run` | POST | 入参 `{"task": "..."}`，返回策略、最终结果与**全过程事件流**；任务涉及外部仓库问答时会真实发起 MCP 工具调用 | + +可复现的 curl 命令与期望输出见 `verification/README.md`。 + +> 免费实例 15 分钟无流量会休眠，首次请求冷启动约 30–90 秒，请耐心等待或先请求一次 `/health` 唤醒。 + +## 3. 工程与架构 + +``` +src/yai_core/ +├── types.py # ToolSpec / AgentEvent / Strategy 等核心数据结构（零依赖） +├── spi/ # Model / Channel / Memory / Policy 四个可替换契约 +├── discovery/ # 宿主函数内省 → ToolSpec（能力自发现） +├── tools/ # ToolRegistry（统一花名册）+ ToolExecutor（权限→执行→事件） +├── kernel/ # AdaptiveRouter（策略路由）+ Context + AgentLoop（主循环） +├── llm/ # OpenAI 兼容模型后端（DeepSeek 等，可选依赖、懒加载） +├── memory/ policy/ channels/ # 默认实现：内存记忆 + SQLite 持久化（opt-in）/ 白名单权限 / CLI·收集通道 +├── integrations/ +│ ├── mcp/ # MCP Client 桥接（可选 [mcp] 依赖、懒加载） +│ └── openapi/ # OpenAPI 3 发现 → 工具（可选 [openapi] 依赖、懒加载） +└── batteries/fastapi_server/ # 在线 API Battery（可选 [server] 依赖，含限流中间件；历史保留由宿主按 env 注入） +``` + +关键工程原则： + +- **内核本体零第三方硬依赖**：`pyproject.toml` 的 `dependencies` 为空；openai / fastapi / mcp / httpx 全部归入可选 extras（llm / server / mcp / openapi）并在模块内懒加载，有 AST 测试防止顶层误引入。 +- **工具同构**：本地函数与外部 MCP 工具在 ToolRegistry 中都是 ToolSpec，Router/Loop/Executor 对工具位置零感知。 +- **错误回灌而非崩溃**：工具（含 MCP 工具）异常被捕获为失败结果回灌模型，事件流照常完整。 +- **可复现**：`uv.lock` 锁定全部依赖；Dockerfile 多阶段构建、`docker compose` 一键起；Render Blueprint（`render.yaml`）即点即部署。 + +## 4. 测试与可观测 + +- 离线测试 **125 项**全部通过（截至 v0.3，以 `pytest -q` 实跑为准；不需要网络与 API Key）：用 ScriptedModel 假模型、内存态 MCP Server 假外部服务、`httpx.MockTransport` 假 REST 端点，覆盖路由、ReAct/Plan 循环、权限、MCP/OpenAPI 桥接、记忆保留策略、限流与 API 端点。 +- GitHub Actions CI 矩阵：Ubuntu × Python 3.11/3.12/3.13 + Windows × 3.13。 +- 每次运行返回完整事件序列（strategy_selected / plan_created / tool_call / tool_result / done…），可直接作为评审的"能力证据"。 +- 长期运行的记忆治理：历史支持条数上限与 TTL（opt-in，按对话轮对齐裁剪，不拆散工具调用对），SQLite 存储在写入与启动时自动清理过期历史，裁剪规则为纯函数并有对等测试。 + +## 5. MCP 产品化准备（对应 15 分评分项） + +- 工具边界清晰：每个工具有 name / description / JSON Schema 入参，MCP 工具 schema 经白名单清洗后与本地工具同构； +- 已实现 MCP Client（官方 Python SDK v2），支持 Streamable HTTP、stdio 子进程、内存直连三种传输； +- **线上 API 自身即 MCP 消费方**：部署期通过 `MCP_SERVER_URL` 环境变量挂载公共免鉴权 MCP Server（DeepWiki），评审可直接 POST 任务让线上服务真实调用远程 MCP 工具，挂载失败不影响本地工具与验证端点（优雅降级）； +- 错误语义明确：MCP `is_error` 统一翻译为失败结果并产生 `tool_result(ok=false)` 事件； +- 权限、副作用边界在 Tool Bus 一层统一收口；超时（规划中）同样收口于此；已实现评审期限流（每 IP 每分钟 30 次、429 + Retry-After，GET 验证端点不受限）； +- 入选后可直接配合 X-Agent 做工具边界与 I/O schema 标准化，本项目自身不绑定任何特定 MCP Server。 + +## 6. 安全与数据处理（评审须知） + +- 线上服务不提供账号体系、不采集个人信息：仅使用演示宿主自带的 3 条虚构笔记；会话历史按部署配置可落盘（`YAI_DB_PATH`，Render 免费层为临时盘、实例重建即清空），不用于任何训练或分析用途。 +- 出站请求仅发往配置的 LLM 端点（线上为 DeepSeek 官方 API）；代码内无任何遥测/统计 SDK。 +- API Key 仅存在于部署平台 Secret 与本地 `.env`（gitignore），不入库、不入镜像层（`.dockerignore` 排除）。 +- 评审期端点开放调用（满足"可在线调用"要求），已加按 IP 的零依赖限流（每 IP 每分钟 30 次，超限返回 429 与 Retry-After；health/verification/tools 三个验证端点不受限）；不提供登录墙。 +- 依赖与授权清单见 `RIGHTS.md`。 + +## 7. 本地复现（隔离环境，5–10 分钟） + +```bash +git clone https://github.com/Gi-Tuu/yai-agent-core && cd yai-agent-core +uv venv && uv sync --extra dev --extra llm --extra server --extra mcp --extra openapi +uv run pytest # 125 passed，离线 +uv run ruff check src tests examples scripts +uv run python scripts/smoke_test.py # 同一内核自适应三个不同宿主（离线） +docker compose up --build # 容器化（容器内 8000，宿主 127.0.0.1:8001） +``` + +接真实模型：复制 `.env.example` 为 `.env` 填入 OpenAI 兼容 Key（DeepSeek 等），运行 +`uv run python examples/host_d_mcp/run.py` 可看到本地工具与 MCP 工具在同一注册表里协同。 + +## 8. 已知限制（诚实声明） + +- 免费层部署会休眠、冷启动约 30–90 秒（波动较大，建议先请求 `/health` 预热）；正式评审期将迁移常驻 VPS（手册见仓库 `docs/competitions/deployment.md`）。 +- 路由为"单次轻量 LLM 分类 + 确定性规则兜底"，不做多层反思/多智能体编排；持久化记忆为 SQLite（opt-in），免费层临时盘随实例重建清空、且不支持多进程共享，长期留存需挂盘或迁移常驻 VPS；限流按 IP 滑动窗口，不防御伪造 XFF，当前无账号体系与鉴权（列入后续版本计划）。 +- 不做 MCP Server、Multi-Agent、自进化写工具、向量记忆、内置 UI、coding agent（明确的 v0.1 红线，避免过度设计）。 diff --git a/submissions/mcp-hackathon/yai-agent-core/source/.dockerignore b/submissions/mcp-hackathon/yai-agent-core/source/.dockerignore new file mode 100644 index 0000000..90748c2 --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/.dockerignore @@ -0,0 +1,29 @@ +# 本地环境与密钥（绝不进镜像） +.env +.venv/ +venv/ + +# 本地 SQLite 数据（容器内如需持久化走挂载卷，不进镜像） +data/ +*.db +*.db-wal +*.db-shm + +# 版本控制与缓存 +.git/ +.github/ +.pytest_cache/ +.ruff_cache/ +**/__pycache__/ +*.pyc + +# 文档与生成产物（镜像只跑服务，不需要讲义） +docs/ +*.docx +*.pdf + +# 编辑器/系统 +.idea/ +.vscode/ +.DS_Store +Thumbs.db diff --git a/submissions/mcp-hackathon/yai-agent-core/source/.env.example b/submissions/mcp-hackathon/yai-agent-core/source/.env.example new file mode 100644 index 0000000..e305935 --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/.env.example @@ -0,0 +1,46 @@ +# 复制为 .env 后填写；.env 已被 .gitignore 排除，不会进仓库 +# +# DeepSeek 接入步骤： +# 1. 打开 https://platform.deepseek.com/ 注册并登录 +# 2. 左侧「API keys」→ 创建并复制 sk- 开头的 Key +# 3. 填到下面 OPENAI_API_KEY= 后面（等号两边不要加空格、不要加引号） +# 通义千问 / OpenAI / 本地 vLLM 等任何 OpenAI 兼容端点同理，改 BASE_URL 与模型名即可。 +OPENAI_API_KEY= +OPENAI_BASE_URL=https://api.deepseek.com +LLM_MODEL=deepseek-chat +# 复杂/规划任务使用的强模型（可选，缺省与 LLM_MODEL 相同） +LLM_STRONG_MODEL=deepseek-chat + +# X-Agent 部署验证（batteries/fastapi_server 读取） +YAI_PROJECT_SLUG=yai-agent-core + +# 持久化记忆（可选；不设置则用进程内内存，重启即失） +# YAI_DB_PATH=data/yai.db # 容器内路径；Render 免费层磁盘为临时存储，重启/redeploy 会丢 + +# 历史保留策略（可选；不设置则永不裁剪，行为与旧版一致） +# YAI_HISTORY_MAX_MESSAGES=200 # 保留最近 N 条消息（按轮对齐、整轮删除，至少留最后一轮） +# YAI_HISTORY_TTL_SECONDS=604800 # 历史存活秒数（7 天）；过期历史在写入与启动时清理，全部过期则清空 + +# 评审期限流（可选；默认开启，防公网误刷与失控循环） +# YAI_RATE_LIMIT_ENABLED=1 # 0/false 关闭（本地开发可关） +# YAI_RATE_LIMIT_PER_MINUTE=30 # 每 IP 每窗口允许的 POST /v1/agent/run 次数 +# YAI_RATE_LIMIT_WINDOW_SECONDS=60 + +# 外部 MCP Server（可选；不设置时 serve_example 只提供本地 native 工具， +# host_d_mcp 示例则回落到自带的本地 stdio 演示 Server） +# Streamable HTTP 形态（线上默认接公共免鉴权的 DeepWiki）： +# MCP_SERVER_URL=https://mcp.deepwiki.com/mcp +# stdio 子进程形态（二选一）： +# MCP_SERVER_COMMAND=python examples/host_d_mcp/demo_mcp_server.py + +# OpenAPI 发现（可选；不设置则不挂载任何 REST API） +# OPENAPI_SPEC_URL=https://petstore3.swagger.io/api/v3/openapi.json # 在线描述（JSON/YAML） +# OPENAPI_SPEC_PATH= # 本地描述文件路径，与 URL 二选一 +# OPENAPI_AUTH_TOKEN= # bearer / apiKey 共用的令牌 +# OPENAPI_BASE_URL= # 覆盖 spec servers[0].url +# OPENAPI_READ_ONLY=1 # 1/true/yes 时只注册 GET/HEAD +# YAI_GIT_COMMIT 保持注释状态： +# - 本地直接跑 uvicorn 时，留空会自动读取当前 git HEAD； +# - Docker 部署时由构建参数 --build-arg YAI_GIT_COMMIT=<40位commit> 固化； +# 不要在 .env 里写 YAI_GIT_COMMIT=（空值会在运行时覆盖镜像内固化的 commit）。 +# YAI_GIT_COMMIT= diff --git a/submissions/mcp-hackathon/yai-agent-core/source/.gitattributes b/submissions/mcp-hackathon/yai-agent-core/source/.gitattributes new file mode 100644 index 0000000..0258f15 --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/.gitattributes @@ -0,0 +1,11 @@ +# 默认让 Git 以 LF 归一化文本文件，工作区按平台检出 +* text=auto eol=lf + +# 二进制产物不做换行符与文本转换 +*.png binary +*.jpg binary +*.jpeg binary +*.gif binary +*.pdf binary +*.docx binary +*.zip binary diff --git a/submissions/mcp-hackathon/yai-agent-core/source/.github/workflows/ci.yml b/submissions/mcp-hackathon/yai-agent-core/source/.github/workflows/ci.yml new file mode 100644 index 0000000..0d675f9 --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/.github/workflows/ci.yml @@ -0,0 +1,44 @@ +name: CI + +on: + push: + branches: [main] + pull_request: + branches: [main] + +jobs: + test: + name: lint & test (${{ matrix.os }} / py${{ matrix.python-version }}) + runs-on: ${{ matrix.os }} + env: + # 用矩阵解释器覆盖仓库里的 .python-version(3.13)，保证 uv sync/run 不擅自换版本 + UV_PYTHON: ${{ matrix.python-version }} + strategy: + fail-fast: false + matrix: + os: [ubuntu-latest] + python-version: ["3.11", "3.12", "3.13"] + include: + - os: windows-latest + python-version: "3.13" + + steps: + - name: Checkout + uses: actions/checkout@v4 + + - name: Install uv + uses: astral-sh/setup-uv@v5 + with: + enable-cache: true + + - name: Set up Python ${{ matrix.python-version }} + run: uv python install ${{ matrix.python-version }} + + - name: Install project (dev + llm + server + mcp + openapi extras) + run: uv sync --extra dev --extra llm --extra server --extra mcp --extra openapi + + - name: Ruff lint + run: uv run ruff check src tests examples scripts + + - name: Pytest + run: uv run pytest diff --git a/submissions/mcp-hackathon/yai-agent-core/source/.github/workflows/keepwarm.yml b/submissions/mcp-hackathon/yai-agent-core/source/.github/workflows/keepwarm.yml new file mode 100644 index 0000000..de8d165 --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/.github/workflows/keepwarm.yml @@ -0,0 +1,20 @@ +# 评审期保活：X-Agent 自动门槛对 GET /health 的超时是 10 秒，而 Render 免费层 +# 15 分钟无流量会休眠（冷启动 30–90 秒）。评审窗口（2026-09-20 ~ 10-04）内每 10 分钟 +# 轻量唤醒一次；只打 GET /health（返回体 <200B，不触达模型、不花额度、不受限流影响）。 +# 评审结束后（10-04 之后）请手动停用本工作流（GitHub Actions 页 disable 即可）。 +name: keepwarm + +on: + schedule: + - cron: "*/10 * * * *" + workflow_dispatch: + +jobs: + ping-health: + runs-on: ubuntu-latest + permissions: + contents: read + steps: + - name: Wake review instance via GET /health + run: | + curl -sS --fail --max-time 90 https://yai-agent-core.onrender.com/health diff --git a/submissions/mcp-hackathon/yai-agent-core/source/.gitignore b/submissions/mcp-hackathon/yai-agent-core/source/.gitignore new file mode 100644 index 0000000..9f94ab7 --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/.gitignore @@ -0,0 +1,40 @@ +# Python +__pycache__/ +*.py[cod] +*.egg-info/ +.eggs/ +build/ +dist/ +.venv/ +venv/ + +# Env / secrets +.env +*.local + +# 本地 SQLite 记忆库与 WAL 旁车文件（含用户对话，绝不入库） +data/ +*.db +*.db-wal +*.db-shm + +# 本地 AI 协作者约定，只留本机、不推远端 +AGENTS.md + +# Test / tool caches +.pytest_cache/ +.ruff_cache/ +.coverage +htmlcov/ + +# Editor / OS +.idea/ +.vscode/ +.DS_Store +Thumbs.db + +# 由 scripts/build_walkthrough_docx.py 生成的讲义产物（需要时本地构建） +docs/exports/ + +# 杭州参赛材料截图（含个人信息，永不入库；目录由用户录材料时本地创建） +docs/competitions/hangzhou/evidence/ diff --git a/submissions/mcp-hackathon/yai-agent-core/source/.python-version b/submissions/mcp-hackathon/yai-agent-core/source/.python-version new file mode 100644 index 0000000..24ee5b1 --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/.python-version @@ -0,0 +1 @@ +3.13 diff --git a/submissions/mcp-hackathon/yai-agent-core/source/CONTRIBUTING.md b/submissions/mcp-hackathon/yai-agent-core/source/CONTRIBUTING.md new file mode 100644 index 0000000..9b4b16c --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/CONTRIBUTING.md @@ -0,0 +1,88 @@ +# 参与贡献 YAI Agent Core + +感谢你对 YAI Agent Core 的兴趣。本项目是一个**进程内嵌入式、自适应的 Agent 内核**：宿主软件只声明普通业务函数，Core 自动把函数变成工具、自适应选择执行策略并把全过程以事件流"喊"出来。在动手之前，请先读 [README.md](README.md) 的定位章节——我们不做又一个需要开发者自己拼装的 Agent 框架。 + +本文档同时是维护者本人的标准操作手册：环境怎么装、代码往哪放、提交前必须过哪些检查。 + +## 1. 开发环境 + +要求 Python 3.11+（开发与 CI 以 3.13 为准），包管理使用 [uv](https://docs.astral.sh/uv/)。 + +```bash +# 1. 创建并激活虚拟环境 +uv venv +.venv\Scripts\activate # Windows PowerShell；Linux/macOS 用 source .venv/bin/activate + +# 2. 安装：可编辑模式 + 开发/真实模型/在线API 可选依赖（接入 MCP/OpenAPI 再加对应 extra） +uv pip install -e ".[dev,llm,server]" +uv pip install -e ".[mcp]" # 仅在开发/运行 MCP Client 集成时需要 +uv pip install -e ".[openapi]" # 仅在开发/运行 OpenAPI 发现时需要（httpx + pyyaml） +# 一次装齐（全量 125 项测试）：uv sync --extra dev --extra llm --extra server --extra mcp --extra openapi + +# 3. 验证：离线测试与冒烟，全程不需要 API Key（激活 venv 后可直接用 pytest；未激活用 uv run pytest） +uv run pytest # 125 passed，离线（extras 组合与 CI 一致时无 skip） +uv run python scripts/smoke_test.py +``` + +需要跑通真实模型（DeepSeek 等 OpenAI 兼容端点）时，复制 `.env.example` 为 `.env` 并填入 Key： + +```bash +cp .env.example .env # Windows: copy .env.example .env +``` + +`.env` 已在 `.gitignore` 中，**永远不要把 API Key 提交进仓库**。 + +## 2. 架构红线（改动前必读） + +1. **内核本体零第三方硬依赖**。`pyproject.toml` 的 `dependencies` 必须保持为空；openai、fastapi、mcp 等只能出现在可选依赖（`llm` / `server` / `mcp`）里，并在对应模块内**懒加载**（`integrations/mcp/` 顶层禁止 import mcp，有 AST 测试守这条线）。 +2. **一切外部能力走 SPI 契约**（`src/yai_core/spi/`）：模型、通道、记忆、权限四个插槽必须可替换，Core 只依赖 `Protocol`，不依赖具体实现。 +3. **事件流只有一条出口**：工具执行等过程事件由执行方收集、统一由 `AgentLoop` yield、`AgentCore.astream` 是唯一对外 emit 点，不允许出现第二条事件路径。 +4. **每个自适应决策必须可观测**：新增任何"Core 自己做决定"的分支，都要通过 `AgentEvent` 发出对应事件，不允许静默决策。 +5. **v0.1 不做**：MCP Server、Multi-Agent、自进化写工具、向量记忆、内置 UI、coding agent。相关讨论先进 Issue。 + +## 3. 代码规范 + +- Linter / import 排序：[Ruff](https://docs.astral.sh/ruff/)，规则集见 `pyproject.toml`（`E,F,I,UP,B`），行宽 100。 +- 提交前必须本地通过： + + ```bash + ruff check src tests examples scripts + pytest + ``` + +- 类型注解为硬性要求：公开 API 必须带参数与返回值注解；数据结构优先用 `@dataclass`，枚举用 `StrEnum`。 +- 每个模块开头写模块 docstring，说明它在全景图中的位置；面向学习者，复杂逻辑块配行内注释。 +- **改了源码就要同步改逐行讲解**：`docs/walkthrough/` 与代码逐块对应，行为变化时同 PR 更新对应篇目。 + +## 4. 测试约定 + +- 测试**不允许依赖网络、API Key 或外部服务**。真实协议用假模块/假端点验证，参考 `tests/test_openai_compat.py`（注入假 `openai` 模块）、`tests/test_loop.py`（ScriptedModel）与 `tests/test_mcp_bridge.py`（内存 MCPServer 实例直连，不起子进程、不触网；文件首行 `pytest.importorskip` 保证最小环境可跳过）。 +- 新功能必须带测试：新策略、新工具来源、新 SPI 实现至少各一条端到端用例。 +- 修 Bug 先写一个能复现该 Bug 的失败测试，再修代码让它通过。 + +## 5. 常见开发任务怎么做 + +| 想做的事 | 动哪里 | 参考 | +|---|---|---| +| 让一个新软件被 Core 适配 | 新建 `examples/host_x/`，只写普通函数 + run 脚本 | `examples/host_a_notes/` | +| 支持一家新模型厂商 | 实现 `ModelProvider` 契约（OpenAI 兼容优先复用现有 provider） | `src/yai_core/llm/`、`spi/model.py` | +| 增加一种工具来源（MCP/OpenAPI） | 产出统一 `ToolSpec` 注册进 `ToolRegistry`，执行侧不改；MCP 范式见 `integrations/mcp/` | `integrations/mcp/client.py`、`discovery/introspect.py` | +| 增加一种执行策略 | 先在 `AdaptiveRouter` 加确定性规则并补测试，LLM 分类是 v0.2 的事 | `kernel/router.py` | +| 换记忆/权限/输入输出 | 实现对应 SPI，通过 `AgentCore(..., memory=/policy=/channel=)` 注入 | `src/yai_core/spi/` | + +## 6. 提交与 PR 流程 + +- 分支命名：`feat/xxx`、`fix/xxx`、`docs/xxx`、`test/xxx`、`chore/xxx`。 +- Commit message 使用 Conventional Commits：`feat: host_a 接入 DeepSeek 真实工具调用`、`fix: provider 直接消费 Context 产出的线格式消息`、`docs: 补 06 loop 逐行讲解`。 +- 一个 PR 只解决一件事；保持小步提交，不要把重构和功能混在一起。 +- PR 描述需说明：改了什么、为什么、怎么验证的（贴命令与结果）、是否改动了公开 API 或 walkthrough。 +- 合并前 checklist：`ruff check` 通过、`pytest` 全绿、新行为有测试、文档同步、无 Key/隐私泄露。 + +## 7. Issue 与讨论 + +- Bug 报告请附：系统与 Python 版本、复现命令、期望与实际结果、完整报错堆栈；模型相关问题注明厂商、模型名、是否离线测试可通过。 +- 功能建议先描述**宿主场景与痛点**（哪个软件、原本要写什么 Agent 代码），再谈方案；与"嵌入式自适应内核"定位不符的需求可能会被建议放到 Battery 或独立仓库。 + +## 8. 许可证 + +本项目采用 MIT 许可证，提交 PR 即表示你同意你的贡献以 MIT 许可发布。 diff --git a/submissions/mcp-hackathon/yai-agent-core/source/Dockerfile b/submissions/mcp-hackathon/yai-agent-core/source/Dockerfile new file mode 100644 index 0000000..7345487 --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/Dockerfile @@ -0,0 +1,46 @@ +# YAI Agent Core —— 在线 API 示例镜像（X-Agent 部署形态） +# 内核零硬依赖；镜像装 server + llm + mcp + openapi 四组可选依赖。 +# 构建：docker build -t yai-agent-core . +# 运行：docker run --rm -p 8000:8000 --env-file .env yai-agent-core + +FROM python:3.13-slim + +# 复用官方 uv 二进制 +COPY --from=ghcr.io/astral-sh/uv:0.12.10 /uv /uvx /bin/ + +WORKDIR /app + +# 直接装进系统环境，省去激活 venv +ENV UV_PROJECT_ENVIRONMENT=/usr/local \ + UV_COMPILE_BYTECODE=1 \ + UV_LINK_MODE=copy \ + PYTHONUNBUFFERED=1 + +# 构建时固化 pinned commit（X-Agent 硬门槛：部署版本与提交哈希一致） +# docker build --build-arg YAI_GIT_COMMIT=$(git rev-parse HEAD) -t yai-agent-core . +ARG YAI_GIT_COMMIT=dev +ENV YAI_GIT_COMMIT=${YAI_GIT_COMMIT} + +# PyPI 源可在构建时覆盖（网络受限环境传国内镜像，默认官方源保持中立） +# 例：--build-arg INDEX_URL=https://pypi.tuna.tsinghua.edu.cn/simple +ARG INDEX_URL=https://pypi.org/simple +ENV UV_INDEX_URL=${INDEX_URL} + +# 先拷依赖清单以利用层缓存；README 是 pyproject 的 readme 字段所需 +COPY pyproject.toml uv.lock README.md ./ +COPY src ./src +# 在线示例依赖 examples（宿主能力）与 scripts（启动模块） +COPY examples ./examples +COPY scripts ./scripts + +RUN uv pip install --system -e ".[server,llm,mcp,openapi]" + +# 默认 8000；托管平台（如 Render）通过 PORT 环境变量指定端口，CMD/HEALTHCHECK 均兼容 +EXPOSE 8000 + +# 容器级健康检查，直接打 X-Agent 要求的 /health 端点（shell 形式，运行时展开 $PORT） +HEALTHCHECK --interval=30s --timeout=5s --start-period=10s --retries=3 \ + CMD python -c "import os,urllib.request,sys; p=os.environ.get('PORT','8000'); sys.exit(0 if urllib.request.urlopen(f'http://127.0.0.1:{p}/health', timeout=4).status == 200 else 1)" + +# shell 形式让 ${PORT:-8000} 在启动时展开：自管环境 8000，Render 等平台用注入的 PORT +CMD uvicorn scripts.serve_example:app --host 0.0.0.0 --port ${PORT:-8000} diff --git a/submissions/mcp-hackathon/yai-agent-core/source/LICENSE b/submissions/mcp-hackathon/yai-agent-core/source/LICENSE new file mode 100644 index 0000000..a822b4b --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/LICENSE @@ -0,0 +1,21 @@ +MIT License + +Copyright (c) 2026 Gi-Tuu + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all +copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +SOFTWARE. diff --git a/submissions/mcp-hackathon/yai-agent-core/source/README.md b/submissions/mcp-hackathon/yai-agent-core/source/README.md new file mode 100644 index 0000000..9dd0be6 --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/README.md @@ -0,0 +1,131 @@ +# YAI Agent Core + +> 进程内嵌入式、自适应的 Agent 内核（Embeddable Self-Adaptive Agent Kernel）。 +> 宿主软件只声明"我有什么能力"，Core 自动发现能力、自适应选择策略并完成任务——**宿主不写一行 Agent Loop / Planner / 工具选择代码**。 + +## 定位：不是又一个 Agent 框架 + +| 形态 | 数据库类比 | Agent 世界 | 你要做什么 | +|---|---|---|---| +| 平台/SaaS | 云数据库控制台 | Dify、Coze | 注册账号在平台里搭 | +| 框架/SDK | ORM | LangGraph、CrewAI、OpenAI/Claude Agents SDK | 自己定义 Agent、工具、编排 | +| **嵌入式内核（本项目）** | **SQLite** | YAI Agent Core | **把现有软件接进来，能力自动长出来** | + +## 30 秒快速开始 + +```bash +uv venv +uv pip install -e ".[dev,llm,server]" +uv run python scripts/smoke_test.py # 离线冒烟：同一 Core 自适应三个不同宿主 +uv run pytest # 单元 + 端到端测试（不需要 API Key） +# 全量 125 项测试：建议一次装齐 extras（与 CI 一致） +# uv sync --extra dev --extra llm --extra server --extra mcp --extra openapi +``` + +**第一次读代码**：[`docs/reading-guide.md`](docs/reading-guide.md) 是学习路线；[`docs/walkthrough/00-index.md`](docs/walkthrough/00-index.md) 是每个源码文件的逐行讲解。 + +宿主接入只有三步： + +```python +from yai_core import AgentCore +import my_app_capabilities as cap # 宿主自己的普通业务函数 + +core = AgentCore.auto(cap, model) # ① 内省宿主能力，自动注册工具 +result = await core.run("搜索本周记录并整理成报告") # ② 自适应：direct/react/plan/clarify +print(result.final_text) # ③ 可交付结果 + 全程事件可观测 +``` + +## 自适应机制（当前能力） + +1. **能力自发现**：Python 函数 type hints + docstring 自动生成 JSON Schema 工具规格；外部 MCP Server 的工具经 MCP Client 同构接入注册表（v0.2 已落地，`[mcp]` 可选依赖） +2. **接入任意 REST API（OpenAPI 发现，可选）**：给一个 OpenAPI 3 描述（URL/文件/dict），自动把 operations 注册为工具（$ref 内联、path/query/body 入参合并、bearer/apiKey 鉴权、只读模式），`[openapi]` extra 懒加载 +3. **策略自适应**：Adaptive Router 将任务路由到 `direct / react / plan / clarify`；规则实现零成本可测，v0.2 已加 LLM 分类器（输出 `{strategy, reason, tier}`，异常/超时/非法输出自动回退规则，决策来源随事件流可审计） +4. **模型自适应**：标准任务/规划任务可路由到不同模型（tier: standard/strong），失败可回退；OpenAI 兼容（DeepSeek、通义千问等） +5. **宿主自适应（SPI）**：Model / Channel / Memory / Policy 四个契约宿主可替换，Core 提供零配置默认实现 +6. **过程可观测**：每次策略选择、工具调用、权限确认都通过 Observer 事件流对外发出 + +## 目录结构 + +``` +src/yai_core/ +├── core.py # AgentCore 门面（auto / run / astream） +├── types.py # ToolSpec / ChatMessage / AgentEvent / Strategy +├── spi/ # 宿主可替换契约：model / channel / memory / policy +├── discovery/ # 能力自发现（函数内省；v0.2 OpenAPI/MCP） +├── tools/ # ToolRegistry + ToolExecutor（Tool Bus） +├── kernel/ # AdaptiveRouter + AgentLoop + Context +├── llm/ # OpenAI 兼容模型后端（可选依赖） +├── memory/ policy/ channels/ # 默认实现（内存记忆 + SQLite 持久化 opt-in / 白名单权限 / CLI·收集通道） +├── integrations/ +│ ├── mcp/ # MCP Client 桥接（可选 [mcp] 依赖，懒加载，v0.2） +│ └── openapi/ # OpenAPI 3 发现 → 工具（可选 [openapi] 依赖，懒加载，v0.2） +└── batteries/ + └── fastapi_server/ # 在线 API + /health + X-Agent 验证端点 +examples/ +├── host_a_notes/ # 宿主 A：笔记应用（只有业务函数，零 Agent 代码） +├── host_b_data/ # 宿主 B：销售数据应用（同一 Core 零修改适配） +├── host_c_companion/ # 宿主 C：AI 陪伴应用（AMBRACE 回流形态预演） +└── host_d_mcp/ # 宿主 D：接入外部 MCP Server 工具（自带 stdio 演示 Server） +tests/ # 离线 ScriptedModel 端到端测试 +docs/ # 架构设计、代码学习导览、三个比赛的提交清单 +``` + +## 接入外部 MCP 工具（v0.2） + +```bash +uv pip install -e ".[mcp]" # 或 uv sync --extra mcp +uv run python examples/host_d_mcp/run.py # 自带本地 stdio 演示 Server，离线可跑 + +# 改接任意公共 MCP Server（HTTP 形态），无需改代码： +$env:MCP_SERVER_URL="https://mcp.deepwiki.com/mcp" # PowerShell +uv run python examples/host_d_mcp/run.py "用 MCP 工具问一下 modelcontextprotocol/python-sdk：Client 怎么初始化？" +``` + +在线 API 同样靠环境变量挂载外部 MCP（`scripts/serve_example.py` 的 lifespan +启动挂载、关闭断开、失败降级为仅本地工具）；线上实例默认挂公共免鉴权的 DeepWiki， +评审可直接 POST 任务让服务真实调用远程 MCP 工具。 + +```python +from yai_core.integrations.mcp import McpServerConfig, attach_mcp_tools + +# Streamable HTTP：McpServerConfig(alias="x", url="https://host/mcp") +# stdio 子进程： McpServerConfig(alias="x", command="uv", args=["run","server.py"]) +bridge = await attach_mcp_tools(core.registry, McpServerConfig(alias="demo", url=url)) +# 远端工具已作为 ToolSpec(source="mcp") 注册，Router/Loop/Executor 零感知 +await bridge.aclose() +``` + +## 在线 API（X-Agent 部署要求） + +```bash +uvicorn 启动示例见 docs/architecture.md +GET /health # {"status":"ok","commit":"..."} +GET /.well-known/xagent-verification.json # {"schemaVersion":1,"slug":...,"commit":...} +GET /v1/tools # 当前宿主自动发现的工具清单 +POST /v1/agent/run # {"task": "..."} -> 事件流 + 最终结果 +``` + +部署相关环境变量（完整清单见 `.env.example`）： + +```bash +# 持久化记忆（可选）：设置后落 SQLite，重启不丢 +YAI_DB_PATH=data/yai.db +# 历史保留策略（可选）：条数上限 / TTL 秒数，按轮对齐裁剪 +YAI_HISTORY_MAX_MESSAGES=200 +YAI_HISTORY_TTL_SECONDS=604800 +# 评审期限流（默认开启）：每 IP 每窗口 30 次 POST；0 关闭 +YAI_RATE_LIMIT_ENABLED=1 +YAI_RATE_LIMIT_PER_MINUTE=30 +YAI_RATE_LIMIT_WINDOW_SECONDS=60 +``` + +## 版本路线 + +- **v0.1（已完成）**：函数内省、规则路由、Agent Loop、SPI 默认实现、FastAPI Battery、三宿主 demo、容器化与 PaaS 部署 +- **v0.2（已完成）**：MCP Client、LLM 路由器（规则兜底）、SQLite 持久化记忆（opt-in，`YAI_DB_PATH`）、OpenAPI 发现（opt-in，`OPENAPI_SPEC_URL/PATH`） +- **v0.3（部分完成）**：历史保留策略（条数裁剪/TTL，opt-in，轮边界对齐，已落地）、限流 Battery（已落地）；检查点与失败恢复、Flutter Channel（后续） +- v1.0：作为 AMBRACE 的 Agent 内核回流嵌入 + +## 许可证 + +MIT diff --git a/submissions/mcp-hackathon/yai-agent-core/source/deploy/Caddyfile b/submissions/mcp-hackathon/yai-agent-core/source/deploy/Caddyfile new file mode 100644 index 0000000..af5e2e9 --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/deploy/Caddyfile @@ -0,0 +1,13 @@ +# Caddy 反代配置：自动向 Let's Encrypt 申请并续期 HTTPS 证书 +# 用法见 docs/competitions/deployment.md +# 把下面的域名换成你自己的域名 / DuckDNS 免费子域名； +# Caddy 与 app 在同一个 compose 网络里，直接用服务名:容器端口访问。 + +:80 { + # 占位：没有域名、只做 HTTP 连通性演练时用，正式部署请改成下面的域名形式 + reverse_proxy yai-agent-core:8000 +} + +# yai-agent-core.duckdns.org { +# reverse_proxy yai-agent-core:8000 +# } diff --git a/submissions/mcp-hackathon/yai-agent-core/source/docker-compose.deploy.yml b/submissions/mcp-hackathon/yai-agent-core/source/docker-compose.deploy.yml new file mode 100644 index 0000000..5d02d05 --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/docker-compose.deploy.yml @@ -0,0 +1,23 @@ +# 正式部署叠加文件：在基础 compose 之上增加 Caddy 反代（自动 HTTPS） +# 启动： +# YAI_GIT_COMMIT=$(git rev-parse HEAD) \ +# docker compose -f docker-compose.yml -f docker-compose.deploy.yml up -d --build +# 前置：deploy/Caddyfile 里的域名已解析到本机公网 IP，安全组/防火墙放行 80、443 +services: + caddy: + image: caddy:2 + container_name: yai-caddy + restart: unless-stopped + ports: + - "80:80" + - "443:443" + volumes: + - ./deploy/Caddyfile:/etc/caddy/Caddyfile:ro + - caddy-data:/data + - caddy-config:/config + depends_on: + - yai-agent-core + +volumes: + caddy-data: + caddy-config: diff --git a/submissions/mcp-hackathon/yai-agent-core/source/docker-compose.yml b/submissions/mcp-hackathon/yai-agent-core/source/docker-compose.yml new file mode 100644 index 0000000..acae6d6 --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/docker-compose.yml @@ -0,0 +1,20 @@ +# 本地/服务器一键起服务：docker compose up --build +# 环境变量从 .env 读取（OPENAI_API_KEY / OPENAI_BASE_URL / LLM_MODEL / YAI_PROJECT_SLUG） +services: + yai-agent-core: + build: + context: . + args: + YAI_GIT_COMMIT: "${YAI_GIT_COMMIT:-dev}" + INDEX_URL: "${INDEX_URL:-https://pypi.org/simple}" + image: yai-agent-core:latest + ports: + # 只绑回环：公网由 Caddy（docker-compose.deploy.yml）反代，不直接暴露容器端口 + # 本地直连调试仍可用 http://127.0.0.1:8001 + - "127.0.0.1:8001:8000" + env_file: + - .env + environment: + # 留空时容器内自动读不到 git，会回退 dev；生产部署显式传 40 位 commit + YAI_GIT_COMMIT: "${YAI_GIT_COMMIT:-}" + restart: unless-stopped diff --git a/submissions/mcp-hackathon/yai-agent-core/source/docs/architecture.md b/submissions/mcp-hackathon/yai-agent-core/source/docs/architecture.md new file mode 100644 index 0000000..cf1863d --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/docs/architecture.md @@ -0,0 +1,128 @@ +# YAI Agent Core 架构设计 + +## 1. 设计原则 + +1. **Library-first（进程内库）**：`pip install` 后运行在宿主进程内，不独立起服务、不要求云端。 +2. **Host-declares-capability**：宿主只声明能力（普通函数/OpenAPI/MCP），Core 负责一切 Agent 逻辑。 +3. **内核最小**：判断标准——"是不是任何宿主都需要？"否则进 batteries/ 或 adapter。 +4. **零硬依赖**：内核只用标准库；openai / fastapi 为可选依赖、懒加载。 +5. **自适应必须可解释**：每个决策产出 Observer 事件，禁止黑盒。 +6. **模型/通道/存储无关**：通过 SPI 契约解耦，Core 给零配置默认实现。 + +## 2. 分层 + +``` +宿主应用（AMBRACE / host_a / host_b） 只声明能力，零 Agent 代码 + │ 内省 / 注册 +能力自发现 Auto-Discovery（函数 / OpenAPI[v0.3] / MCP Client[v0.2 已落地]） + ▼ +YAI Kernel + ├─ Adaptive Router 任务分类 → direct/react/plan/clarify + 模型 tier + ├─ Agent Loop 按策略执行（工具循环、计划拆解、澄清重入） + ├─ Context 消息组装与 token 预算 + └─ Tool Bus 权限 → 执行（sync/async）→ 结构化结果 + ▲ +SPI 契约环（可替换 + 默认实现） + ModelProvider(OpenAI 兼容) / Channel(CLI·FastAPI·Flutter) + MemoryStore(内存→SQLite→向量) / PermissionPolicy(auto/ask/deny) + ▲ +Integrations（可选，懒加载）：MCP Client（integrations/mcp/，[mcp] extra） +Batteries（可选）：FastAPI Server、SQLite Memory +``` + +### 2.1 MCP Client 集成（v0.2 已落地） + +``` +MCP Server（HTTP / stdio 子进程 / 内存实例） + │ list_tools / call_tool（MCP Python SDK v2，可选依赖、懒加载） + ▼ +McpToolBridge（integrations/mcp/client.py） + ├─ sanitize_schema 清洗 SDK 生成 schema 里的私有键 + ├─ _to_spec 每个远端工具 → ToolSpec(source="mcp")，handler 为异步闭包 + └─ _flatten_call_result content 文本 / structured_content / is_error → 返回值或异常 + ▼ +ToolRegistry（与 Native 工具同构，Router/Loop/Executor 零感知） +``` +- 内核本体不 import mcp（AST 测试守红线）；`uv sync --extra mcp` 才启用。 +- 连接三态：`McpServerConfig.url`（Streamable HTTP）/ `command+args`（stdio 子进程）/ + `server`（内存实例，离线测试用）；`prefix` 解决多 Server 工具重名。 +- 生命周期：`async with McpToolBridge(...)` 或 `connect()/aclose()` 手动管理； + stdio 形态必须 aclose，否则子进程成为孤儿。 + +### 2.2 持久化记忆（SQLite，v0.2 已落地） + +`memory/sqlite_store.py` 提供 `SqliteStore`：MemoryStore 契约的 SQLite 实现（标准库、 +零新依赖）。history/kv 两张表，`scope` 列做会话隔离，`PRAGMA user_version` 做迁移钩子， +WAL + 单锁覆盖单进程并发；`history()` 保持契约的同步签名。装配走 `YAI_DB_PATH` +（`SqliteStore.from_env()`），未设置时回退 InMemoryStore，线上默认不开启（免费 PaaS 临时盘）。 +Loop/Core/宿主示例零改动。边界（历史裁剪、多进程写、临时盘持久性）见 walkthrough 第 11 章 H 节。 +历史保留策略（v0.3，opt-in）：`memory/retention.py` 提供纯函数 count_cut/ttl_cut， +两种 Store 以构造参数 max_messages / ttl_seconds / clock 对等支持；裁剪边界按"轮" +对齐（一条 user 到下一条 user 之前为一轮），保证 assistant(tool_calls)/tool 配对 +不被拆散；SQLite 构造时自动 prune 一次覆盖重启场景。MemoryStore 契约与 schema +版本（仍为 v1）不变；KV 的 TTL 需 schema v2 迁移，留待 v0.4。`Context._compact` +同步改为轮边界丢弃（kernel 内同源私有实现）。 + +### 2.3 OpenAPI 发现（v0.2 已落地） + +`integrations/openapi/` 把任意 OpenAPI 3 描述自动翻译成 ToolSpec(source="openapi")（alias 仅用于日志与 notes）： +spec.py 负责载入/版本闸/内部 $ref 内联（循环与外部引用保留并记 notes），discovery.py +纯函数地把 operations 规划成工具（operationId/合成命名、path/query/body 入参合并、 +include/exclude、read_only 只留 GET/HEAD、max_operations=40 截断），client.py 用懒加载的 +httpx 执行（bearer/apiKey 鉴权令牌走环境变量、调用期校验、204/非2xx/JSON/文本截断归一）。 +httpx/pyyaml 在 [openapi] extra，内核本体零硬依赖；测试全部走 httpx.MockTransport 离线。 +与 MCP 桥同构，在 serve_example 的 app_lifespan 中顺序挂载、共用关闭列表。 + +## 3. SPI 契约 + +| 契约 | 方法 | 默认实现 | 宿主何时替换 | +|---|---|---|---| +| ModelProvider | `achat(messages, tools, tier)` | OpenAICompatProvider（DeepSeek 等） | 接私有模型/本地模型 | +| Channel | `emit / ask / confirm` | CollectChannel、CliChannel | Web SSE、Flutter UI | +| MemoryStore | `history / put / get / clear` | InMemoryStore | SQLite、向量记忆 | +| PermissionPolicy | `check(tool, args) → allow/deny/ask` | AllowlistPolicy | 高危工具人工确认 | + +## 4. Adaptive Router 状态机 + +``` +任务文本 + 可用工具集 + ├─ 无工具 → direct（模型直接答） + ├─ 模糊短句 → clarify（Channel.ask 后重入） + ├─ 含行动词 + 多步骤信号 → plan（先拆解，再 react） + └─ 含行动词 → react（工具循环） +``` + +v0.2（已落地）：LLM 一次性分类输出 `{strategy, reason, tier}`，异常/超时/非法输出回退规则路由； +两条路径统一返回 RouteDecision，`strategy_selected` 事件带 `source=llm|rules` 可审计。 + +## 5. 启动在线 API（batteries） + +```python +import os, uvicorn +from yai_core import AgentCore, OpenAICompatProvider +from yai_core.batteries.fastapi_server import create_app +import my_app_capabilities as cap + +core = AgentCore.auto(cap, OpenAICompatProvider()) +app = create_app(core) +# 环境变量：YAI_GIT_COMMIT=<40位 commit>、YAI_PROJECT_SLUG= +# 容器内监听 8000；宿主机端口由部署侧映射（本项目约定 8001:8000） +# uvicorn module:app --host 0.0.0.0 --port 8000 +``` + +v0.3 评审期限流（默认开启）：`rate_limit.py` 提供每 IP 滑动窗口（`enabled=True`、 +`per_minute=30`、`window_seconds=60`，可用 `YAI_RATE_LIMIT_*` 调整或关闭）。中间件只拦 +`POST /v1/agent/run`，超限返回 429 + `Retry-After`（与响应体同源），被限请求不触达 +模型；三个 GET 验证端点永不限流（评审硬门槛）。客户端身份取 XFF 最左非空、回退对端 +地址；状态只在内存，重启清零；全局限流兜底不做（单实例）。 + +## 6. 与生态的差异化（诚实对比，用于比赛材料） + +- Claude/OpenAI Agents SDK、LangGraph：developer-builds-agent，工具/编排需显式定义，且绑定自家生态； +- agentic-kernel（TS）：嵌入式运行时理念相近，但仅 TypeScript 且无能力自发现/策略自适应； +- MCP：工具互操作**协议**，不是运行时；YAI 是 MCP 的消费者（v0.2 Client）而非竞争者； +- YAI：host-declares-capability、Python 进程内、模型/通道/存储全无关、自适应过程可观测。 + +## 7. 明确不做（v0.1 红线） + +MCP Server、Multi-Agent 编排、自进化写工具、向量长期记忆、内置 UI、coding agent 场景、队列/中间件、K8s。 diff --git a/submissions/mcp-hackathon/yai-agent-core/source/docs/competitions/deployment.md b/submissions/mcp-hackathon/yai-agent-core/source/docs/competitions/deployment.md new file mode 100644 index 0000000..263cbb9 --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/docs/competitions/deployment.md @@ -0,0 +1,147 @@ +# 公网部署手册（X-Agent 硬门槛落地指南） + +> 最后核实：2026-09-10。免费政策变化快，动手前点文末来源链接复核。 +> 目标：让 `https://<你的域名>/health` 等四个端点公网可访问，且返回的 commit 与提交 PR 里的 pinned commit 完全一致。 + +## 0. 要满足的硬门槛（对应 X-Agent 7 项硬门槛中的部署部分） + +| 门槛 | 本项目落地方式 | +|---|---| +| 已部署、公网可调用的 API | Docker Compose 常驻 VPS，Caddy 反代 443 | +| `GET /health` 返回 status + 40 位 commit | Battery 已实现；commit 构建时由 `--build-arg YAI_GIT_COMMIT` 固化 | +| `/.well-known/xagent-verification.json` 同源同 commit | Battery 已实现，与 /health 读同一个环境变量 | +| pinned commit | 部署哪个 commit，PR 的 `source/` 就放哪个 commit 的源码 | +| 可复现说明 | 本手册 + README 的两条 compose 命令 | + +## 1. 免费方案选型（2026-09 官方页面核实） + +| 方案 | 成本 | 是否常驻 | HTTPS 与域名 | 结论 | +|---|---|---|---|---| +| **Oracle Cloud Always Free** | 永久免费：2 台 AMD micro（1/8 OCPU、1GB）+ ARM Ampere A1（总量最多 4 OCPU/24GB，可开 1-2 台）、200GB 块存储、约 10TB/月出站流量 | 常驻不休眠 | 自备域名（免费 DuckDNS 即可），Caddy 自动签证书 | **正式部署首选** | +| Google Cloud e2-micro | 永久免费 1 台（限定美国 3 个区，1GB） | 常驻 | 同上 | 备选，注册同样要卡 | +| Render Free Web Service | 免费 | **15 分钟无流量休眠，冷启动约 30–90 秒（波动大）**；750 实例小时/月 | 自带 `*.onrender.com` 证书 | **今天做演练用**，评审期有被休眠打到的风险 | +| Fly.io | 无免费层，shared-cpu-1x 256MB 约 $3.14/月起 | 常驻 | 自带 `*.fly.dev` 证书 | 不想折腾 Oracle 时的便宜替代 | +| Koyeb | 免费实例已取消（官网只剩付费计划） | — | — | 排除 | +| Hugging Face Spaces | Docker/Gradio Space 创建已需付费计划；免费硬件会休眠 | 休眠 | 自带 | 排除 | +| 阿里云/腾讯云学生机 | 约 ¥10/月级 | 常驻 | **大陆机房域名走 443 需 ICP 备案（赶不上 09-19/10-04）**；海外地域免备案但学生价通常限大陆地域 | 不推荐用于本次比赛 | + +**建议路线**：今天先用 **Render 免费层 30 分钟拿到公网 HTTPS 地址**跑通全流程；正式提交前迁到 **Oracle Always Free + Caddy** 常驻。我们的服务只是转发到 DeepSeek，本机不跑模型，AMD 1GB 小机器都够用。 + +## 2. 路线 A：Render 免费层快速演练（零成本、约 30 分钟） + +仓库根目录已放好 `render.yaml`（Render Blueprint），平台名、端口、健康检查、非敏感变量都已声明， +只需在网页上连接仓库并粘贴一次 Key： + +1. 打开 https://render.com → 用 GitHub 账号登录并授权访问 `Gi-Tuu/yai-agent-core`。 +2. 控制台 **New → Blueprint**，选择 `yai-agent-core` 仓库，Render 会读取 `render.yaml` + 自动生成一个 Free 的 Docker Web Service（区域 Singapore，健康检查路径 `/health`）。 +3. Blueprint 向导会提示填写标记为 `sync: false` 的 Secret：`OPENAI_API_KEY` = DeepSeek Key，粘贴即可。 + 其余变量（`OPENAI_BASE_URL`、`LLM_MODEL`、`YAI_PROJECT_SLUG` 等）已在 yaml 里写好。 +4. 点 **Apply / Deploy**，云端开始构建（海外环境用官方 PyPI，不需要 `INDEX_URL`）。 +5. 两个自动化约定（已在代码里处理，无需手动操作）： + - **端口**：Render 注入 `PORT`（默认 10000），Dockerfile 的 CMD 是 + `--port ${PORT:-8000}`，本地/compose 仍是 8000，上了 Render 自动跟随； + - **commit**：Render 自动注入 `RENDER_GIT_COMMIT`（本次部署的完整 SHA）， + `serve_example.py` 的解析链 `YAI_GIT_COMMIT → RENDER_GIT_COMMIT → git HEAD → dev` + 会自动采用它，/health 与验证端点返回的 commit 天然等于部署的 commit。 + 注意解析时只接受完整 40 位小写哈希——镜像里烤的默认值 `dev` 不是合法哈希会被跳过 + （首部署实测：若不跳过，非空的 `dev` 会遮蔽平台注入的真实 SHA）。 +6. 部署完成后得到 `https://yai-agent-core.onrender.com`（名字以实际为准），按第 4 节验证四个端点。 +7. 风险：15 分钟无流量会休眠，评审机第一次访问可能撞上约 30–90 秒冷启动页（不是我们的 JSON）。 + **正式评审前必须换到常驻 VPS。** + +> 若不用 Blueprint、手动 New → Web Service：Language 选 Docker、Dockerfile Path 留空（根目录）、 +> Plan 选 Free，然后在 Environment 里补齐上面同样的变量即可，效果相同。 + +## 3. 路线 B：Oracle Always Free + Docker + Caddy（正式部署） + +### 3.1 注册与开机器 +1. 在 https://www.oracle.com/cloud/free/ 注册（需一张信用卡/借记卡做验证，不扣款；一人一号，信息真实）。 +2. Home Region **一旦选定不可更改**，建议 Tokyo / Seoul / Singapore（离大陆近、PyPI 与 DeepSeek 都通）。 +3. Create Instance： + - Image：Ubuntu 24.04 + - Shape：优先 `VM.Standard.A1.Flex`（ARM，给 1 OCPU/6GB 即可，抢不到容量就用 `VM.Standard.E2.1.Micro`，AMD 1GB 也能跑） + - 保存 SSH 私钥（页面可自动生成并下载） +4. VCN 安全列表（Security List）放行入站：tcp 80、tcp 443；tcp 22 建议只放行你自己的出口 IP。 + +### 3.2 装 Docker（SSH 上去后） +```bash +sudo apt update +sudo apt install -y docker.io docker-compose-v2 git +sudo usermod -aG docker ubuntu # 重新登录后免 sudo +``` + +### 3.3 拉代码、配环境、起服务 +```bash +git clone https://github.com/Gi-Tuu/yai-agent-core.git +cd yai-agent-core +cp .env.example .env +nano .env # 填 OPENAI_API_KEY、YAI_PROJECT_SLUG；YAI_GIT_COMMIT 保持注释 +nano deploy/Caddyfile # 把域名换成你的（见 3.4） + +git rev-parse HEAD # 记下这 40 位 commit，X-Agent 提交 PR 时用同一个 +YAI_GIT_COMMIT=$(git rev-parse HEAD) \ + docker compose -f docker-compose.yml -f docker-compose.deploy.yml up -d --build +``` +说明： +- 基础 compose 只把容器端口绑在 `127.0.0.1:8001`（本机调试用），公网只能经 Caddy 进入； +- deploy 叠加文件启动 Caddy，占用 80/443，首次请求时自动向 Let's Encrypt 申请证书并自动续期； +- ARM 机器无需改 Dockerfile，`python:3.13-slim` 有 arm64 镜像； +- 海外 VPS 构建用官方 PyPI 即可；若网络抽风，构建时加 `INDEX_URL=https://pypi.tuna.tsinghua.edu.cn/simple`。 + +### 3.4 免费域名（DuckDNS，不用买域名） +1. 打开 https://www.duckdns.org/ ，用 GitHub/Google 登录； +2. 新建子域名（如 `yai-agent-core`），把 A 记录填成 VPS 公网 IP； +3. 把 `deploy/Caddyfile` 改成： + ``` + yai-agent-core.duckdns.org { + reverse_proxy yai-agent-core:8000 + } + ``` +4. `docker compose -f docker-compose.yml -f docker-compose.deploy.yml restart caddy`， + 首次 HTTPS 访问时 Caddy 自动签好证书（`docker compose logs caddy` 可看到证书申请记录）。 + +### 3.5 更新版本（比赛迭代时反复用） +```bash +git pull +YAI_GIT_COMMIT=$(git rev-parse HEAD) \ + docker compose -f docker-compose.yml -f docker-compose.deploy.yml up -d --build +``` +重新构建后 /health 的 commit 自动变成新版本——**每次重新部署，X-Agent PR 里的 pinned commit 也要同步更新**。 + +## 4. 部署后验证清单（在自己电脑上跑） + +```bash +BASE=https://<你的域名> +curl $BASE/health # 期望 {"status":"ok","commit":"<40位>"} +curl $BASE/.well-known/xagent-verification.json # 期望 schemaVersion/slug/commit，commit 与上面一致 +curl $BASE/v1/tools # 期望工具清单 +curl -X POST $BASE/v1/agent/run -H "Content-Type: application/json" \ + -d '{"task":"列出我的全部笔记"}' # 期望 strategy/events/final_text +docker compose ps # caddy 与 app 均 healthy +``` +四项全过 = X-Agent 部署类硬门槛达标。 + +- [x] `YAI_DB_PATH`：Render Blueprint 已默认开启（`data/yai.db` → 容器内 `/app/data`，启动时自动建目录）；本地/容器不设置该变量时仍是进程内内存。 + **Render 免费层是临时盘，redeploy 后会丢库**：重建后历史清空属预期行为，对外演示口径需如实说明；VPS 形态请把该路径放在挂载卷上。 + +## 5. 安全与运维清单 + +- `.env` 只存在于服务器，不进 git、不进镜像（`.dockerignore` 已排除）； +- 安全组只开 22/80/443，容器端口不直接对公网开放（已绑回环）； +- Caddy 证书数据在 `caddy-data` 卷里，重启不丢、自动续期； +- 模型调用全部出站到 DeepSeek 云端，VPS 不跑模型，CPU/内存压力很小； +- 若海外 VPS 访问 `api.deepseek.com` 异常，先 `curl https://api.deepseek.com` 排查，必要时换 Oracle 区域（待首次部署实测）。 + +## 6. 参考来源（官方） + +- Oracle Cloud Free Tier：https://www.oracle.com/cloud/free/ +- Render Free 限制（休眠/750 小时）：https://render.com/docs/free +- Render Docker 部署（PORT/构建参数）：https://render.com/docs/docker +- Render 注入的环境变量（RENDER_GIT_COMMIT）：https://render.com/docs/environment-variables +- Render Blueprint（render.yaml）：https://render.com/docs/blueprint-spec +- Fly.io 定价（无免费层）：https://fly.io/docs/about/pricing/ +- Koyeb 定价（免费实例已取消）：https://www.koyeb.com/pricing +- Hugging Face Spaces（Docker Space 需付费）：https://huggingface.co/docs/hub/spaces-overview +- Caddy 文档（自动 HTTPS）：https://caddyserver.com/docs/ +- DuckDNS 免费域名：https://www.duckdns.org/ diff --git a/submissions/mcp-hackathon/yai-agent-core/source/docs/competitions/hangzhou.md b/submissions/mcp-hackathon/yai-agent-core/source/docs/competitions/hangzhou.md new file mode 100644 index 0000000..27749da --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/docs/competitions/hangzhou.md @@ -0,0 +1,24 @@ +# AI杭州·码动未来 2026 — AI+超级智能体赛道（高校组）提交清单 + +- 官网：https://aichallenge.msup.com.cn/ ｜ 赛题：/tracks +- 时间：初赛材料与组队报名 **09.19 同步关闭**（具体时刻以报名系统为准）；评审 09.20–09.26；100 强 09.30；决赛路演 10.31 + +## 初赛评分（5×20） + +| 维度 | YAI 对应 | +|---|---| +| 技术可行性 20 | 离线测试 + 在线 API 双验证 | +| 市场可行性 20 | "任何软件零改造获得数字员工"的通用性故事 | +| 综合创新性 20 | host-declares-capability 范式反转 + 自适应路由 | +| AI 大模型结合 20 | 方案文档写清分类/路由/工具循环全流程 | +| 赛道维度 20 | 任务理解与自主规划=Router；工具调用=Discovery+ToolBus；可验收交付=Channel 输出；端到端闭环=双宿主 demo | + +## 材料（详见 docs/competitions/hangzhou/提交清单.md，含 5 个待确认问题） + +- 创意/方案文档（含大模型环节细节） +- 可运行原型（Core + 一个办公场景宿主） +- 演示视频 ≤5 分钟（import 前 vs 后；双宿主自适应） +- 代码 + 说明文档 +- 三份落地文档：docs/competitions/hangzhou/{方案文档,演示脚本,提交清单}.md +- 决赛（若入围）：高校组 5 分钟路演 + 2 分钟答辩；**每组别前 3 名晋级，初赛成绩清零**；决赛维度为 技术可行性/市场可行性/综合创新性/项目完成度/团队潜力 +- 备注：模型加分与魔搭算力支持**待确认**（已在提交清单 §5 跟踪，确认前不作为既成事实） diff --git "a/submissions/mcp-hackathon/yai-agent-core/source/docs/competitions/hangzhou/\346\212\245\345\220\215\346\226\207\346\241\210.md" "b/submissions/mcp-hackathon/yai-agent-core/source/docs/competitions/hangzhou/\346\212\245\345\220\215\346\226\207\346\241\210.md" new file mode 100644 index 0000000..18be41b --- /dev/null +++ "b/submissions/mcp-hackathon/yai-agent-core/source/docs/competitions/hangzhou/\346\212\245\345\220\215\346\226\207\346\241\210.md" @@ -0,0 +1,81 @@ +# AI杭州初赛 · 报名系统填写文案包（复制即用） + +> v1.0，2026-09-14，豆包整理。所有内容只写仓库/线上可复现的事实；**真实姓名、学校、证件、联系方式只填报名系统，不写进任何公开材料**。 +> 使用方法：登录报名系统后，按实际字段长度选版本粘贴；系统字段与本文件不一致时，以系统为准并截图留痕到 `evidence/`。 +> 公开署名口径统一：队名 **YAI**（单人队），GitHub: **Gi-Tuu**。 + +## 1. 作品名称 + +- 主用：**YAI 数字员工——让现有软件零改造获得自适应 Agent 能力** +- 若系统限 20 字内：**YAI 数字员工：可内嵌的自适应 Agent 内核** +- 内核/仓库名（技术字段用）：`yai-agent-core`（YAI Agent Core） + +## 2. 一句话简介（三版，按字段限额选） + +- 30 字版：YAI 是可内嵌进现有软件的自适应 Agent 内核，宿主声明能力，内核自动完成理解、规划与工具调用。 +- 50 字版：YAI Agent Core 是进程内、零硬依赖的智能体内核：软件只需声明普通函数，内核即自适应完成意图路由、规划、工具调用（含 MCP）与结果交付，import 即得数字员工。 +- 80 字版：不同于又一个独立 Agent 应用，YAI 是可内嵌进现有软件的 Agent 内核（Library-first）。宿主只声明"我有什么能力"（普通 Python 函数 + 一行描述），内核在进程内自适应完成意图理解、策略路由、任务规划、本地/远程工具调用（含 MCP/OpenAPI）、记忆与可审计的结果交付，已在线部署并通过 125 项离线测试。 + +## 3. 作品介绍 / 项目概述 + +### 3.1 短版（约 300 字，适合"作品简介"类字段） + +YAI 数字员工解决一个被多数 Agent 产品忽略的问题：软件厂商想让自己的现有软件拥有 Agent 能力，仍然要自己接模型、写工具总线、写 Agent 循环、写记忆、做适配，门槛高且重复造轮子。YAI 反转范式——宿主软件只负责"声明能力"（普通业务函数加类型注解与 docstring），YAI 内核在进程内自适应完成其余全部：LLM 路由在 direct/react/plan/clarify 四种策略间选择（模型不可用时规则兜底，全程事件可审计），ReAct 循环经 JSON Schema 校验与权限白名单后调用本地函数、MCP Server 远程工具或 OpenAPI 服务工具，结果回灌后由模型收尾交付；记忆层支持 SQLite 持久化与条数/TTL 保留策略。内核本体零第三方运行时硬依赖，模型经 OpenAI 兼容协议可替换（当前演示用 DeepSeek）。作品已 Docker 部署上线、具备免登录在线 API，仓库含 4 个不同行业形态的宿主示例证明"同一内核换宿主即换岗位"，并配 125 项离线测试与 CI 四版本矩阵。 + +### 3.2 长版（约 800 字，适合"项目详细介绍/创意描述"字段；含大模型环节，满足评分硬要求） + +**痛点与创意。** 当下 Agent 领域的多数成果是独立应用或编排框架，软件厂商想让"自己已有的软件"获得 Agent 能力，仍要自行集成模型、工具总线、执行循环、记忆与权限体系。YAI 数字员工（内核名 YAI Agent Core）给出另一条路径：做一颗可内嵌的自适应内核，宿主只声明能力，内核适配宿主，而非宿主改造自己去适配框架。接入成本为一行 `AgentCore.auto(capabilities, model)`，capabilities 就是普通 Python 函数。 + +**大模型环节全链路（4 个调用点，全程可审计）。** ① 路由分类：每个任务先经一次轻量 LLM 分类，输出策略（direct 直接回答 / react 工具循环 / plan 先规划后执行 / clarify 反问澄清）、模型档位与中文理由；模型异常或输出非法时自动回退确定性规则路由，决策来源随事件流出。② 计划生成：仅 plan 策略触发，模型把任务拆为 2–5 个有序步骤并发 `plan_created` 事件。③ ReAct 推理与工具选择：模型在上下文中选择工具并产出参数，内核做 JSON Schema 校验、allowlist 权限检查后执行；工具来源三类同构——宿主本地函数、MCP Server 远程工具（官方 SDK，支持 Streamable HTTP/stdio/进程内三传输，在线实例已真实接入 DeepWiki）、OpenAPI spec 自动桥接工具。④ 收尾汇总：模型基于完整工具观察链产出可交付的最终结果。所有自适应决策经唯一事件出口 `astream` 以类型化事件流式发出，无静默决策。 + +**工程与落地。** 内核本体零第三方运行时硬依赖（模型客户端、FastAPI、MCP、HTTP 全部为可选 extra）；四个 SPI 契约（model/channel/memory/policy）支持逐项替换；SQLite 记忆带 scope 隔离、schema 版本钩子与条数/TTL 保留策略；在线服务提供 /health（实时返回 commit）、/v1/tools、POST /v1/agent/run，并实现每 IP 滑动窗口限流。仓库含 4 个宿主示例（办公笔记、销售数据、AI 陪伴、本地 MCP 演示），同一内核不改一行即切换岗位；125 项测试全部离线（假模型/MockTransport/注入时钟，不依赖网络与密钥），GitHub Actions 在 Ubuntu 3.11/3.12/3.13 与 Windows 3.13 四矩阵跑 ruff + pytest。 + +**演进路线。** 第一阶段作为独立开源内核（本作品）；第二阶段回流内嵌进开源 AI 陪伴项目 AMBRACE，验证真实 To C 软件内嵌路径；第三阶段经 MCP 标准化接入更广生态（已同步投稿 X-Agent MCP Hackathon）。多智能体、向量记忆、工具自生成等在公开路线图中，初赛版本不做宣称。 + +## 4. 创新点（分条，适合"项目亮点/创新点"字段，4 条） + +1. **范式创新：host-declares-capability / core-adapts。** 现有框架止步于提供积木，YAI 让已有软件以零 Agent 代码获得能力，定位是"可内嵌内核"而非又一个 Agent 应用；宿主接入只需一行 auto。 +2. **自适应路由可审计、可降级。** LLM 一次性输出策略/档位/理由，每个决策落类型化事件流；模型不可用时规则路由兜底，保证离线、断网、超额场景下的确定性退化。 +3. **三源工具同构 + 双协议桥接。** 本地函数、MCP Server、OpenAPI 服务在同一注册表/同一权限链/同一事件流中无差别运行，远程 MCP 工具已在线真实跑通。 +4. **内核零硬依赖与 SPI 四契约。** 模型、通道、记忆、权限全部面向契约编程，模型厂商可替换（DeepSeek/通义/OpenAI 仅改环境变量），可进程内嵌、可服务化部署。 + +## 5. 技术方案 / 架构说明（若系统有独立技术字段） + +- 分层：宿主声明 capabilities → discovery/introspect 内省为统一 ToolSpec → AdaptiveRouter（LLM 路由 + 规则兜底）→ AgentLoop（direct/react/plan/clarify）→ ToolExecutor（Schema 校验 → allowlist 权限 → 执行/回灌）→ 通道交付（CLI / collect / FastAPI）。 +- 大模型：OpenAI 兼容抽象层，当前演示使用 DeepSeek deepseek-chat，切换厂商仅改环境变量；路由用 standard 档、规划用 strong 档，成本与时延可控。 +- 记忆：内存态 + SQLite 持久化（opt-in），条数上限与 TTL 按对话轮边界裁剪，不拆散工具调用对。 +- 质量：125 项离线测试、ruff、CI 四矩阵、Dockerfile + render.yaml 一键部署、限流与保活工作流。 +- 诚实边界（如系统要求"不足与展望"字段直接用）：未做多智能体协作、向量检索/RAG、自进化写工具与内置 UI；在线实例为免费 PaaS（15 分钟休眠、冷启动约 30–90 秒且波动大、临时盘重建清空）；限流不防御伪造 X-Forwarded-For；无账号鉴权（评审免登录调用，鉴权在路线图）。 + +## 6. 团队介绍（单人队，两版，均不含真名） + +- 短版（约 80 字）：YAI 为单人参赛队，队员即作者本人，GitHub ID：Gi-Tuu，独立完成内核设计、开发、测试、部署与全部参赛材料。具备 Python 后端与开源工程实践，正在同步建设 AI 陪伴开源项目 AMBRACE，YAI 内核计划回流内嵌。 +- 长版（约 200 字，若系统有"团队优势/团队潜力"字段）：YAI 是单人战队，覆盖产品定义、架构设计、Python 工程化、CI/CD 与云部署全链路，独立完成本作品从 0 到在线运行的全部工作：内核采用零硬依赖的库形态设计，配套 125 项离线测试、四矩阵 CI、Docker/PaaS 部署与 15 篇源码逐行讲义（面向学习者的开源文档）。作者同时是开源 AI 陪伴项目 AMBRACE（github.com/Gi-Tuu/AMBRACE）的维护者，YAI 的架构需求来自该真实项目的内嵌场景，赛后将作为 Agent 能力底座回流，形成"比赛验证—开源沉淀—产品内嵌"的持续迭代闭环。 + +## 7. 链接与地址类字段 + +- 源码仓库：https://github.com/Gi-Tuu/yai-agent-core +- 在线原型（Base URL）：https://yai-agent-core.onrender.com +- 在线验证端点：https://yai-agent-core.onrender.com/health （实时返回冻结 commit） +- 工具清单端点：https://yai-agent-core.onrender.com/v1/tools +- 能力调用端点：POST https://yai-agent-core.onrender.com/v1/agent/run ，请求体 `{"task":"..."}`（免登录、免密钥） +- 关联开源项目：https://github.com/Gi-Tuu/AMBRACE （AI 陪伴宿主，回流目标） +- 冻结 commit：0a2634f3b13d690398c77d9119c3beecd4881929 +- 演示数据声明：全部为虚构笔记/虚构陪伴档案，无真实个人数据。 + +## 8. 关键词 / 标签（按系统限额挑 3–6 个） + +智能体内核、Agent、工具调用、MCP、自适应路由、任务规划、数字员工、开源、Library-first、大模型应用、ReAct、记忆 + +## 9. 模型与算力相关字段（待核实口径，见提交清单 §5 第 4 问） + +- 标准答复：作品使用 DeepSeek deepseek-chat（OpenAI 兼容接口），模型层为厂商可替换抽象，不绑定单一模型；未使用专项算力券。 +- 背景线索（**需在报名系统/选手群核实是否适用本届后再提**）：msup 活动页（event.msup.com.cn/hangzhou，时间线与本届官网不一致，疑似往届页）有"使用推荐平台通义千问、DeepSeek 有额外加分""算力由魔搭社区免费提供"的表述。若本届适用，我们已在用 DeepSeek，属于自然命中，无需改造；是否需要在报名时勾选/声明以系统为准。 + +## 10. 填写纪律清单（提交前逐项打勾） + +- [ ] 公开字段（作品介绍、团队介绍、视频、文档）无真名/学校/联系方式 +- [ ] 每个字段填完先截图再点下一页（存 evidence/，该目录不入库） +- [ ] 链接类字段填完用无痕窗口复验可打开 +- [ ] 截止时刻、单人资格、格式限额、模型加分四个问题在系统里找到答案并回填《提交清单.md》§5 +- [ ] 若系统要求 PDF/Word 版方案文档，按《提交清单.md》§4 导出（Mermaid 先在 GitHub 渲染截图嵌入） diff --git "a/submissions/mcp-hackathon/yai-agent-core/source/docs/competitions/hangzhou/\346\217\220\344\272\244\346\270\205\345\215\225.md" "b/submissions/mcp-hackathon/yai-agent-core/source/docs/competitions/hangzhou/\346\217\220\344\272\244\346\270\205\345\215\225.md" new file mode 100644 index 0000000..d2a57c7 --- /dev/null +++ "b/submissions/mcp-hackathon/yai-agent-core/source/docs/competitions/hangzhou/\346\217\220\344\272\244\346\270\205\345\215\225.md" @@ -0,0 +1,65 @@ +# AI杭州初赛提交清单（用户执行手册） + +> v0.3，2026-09-14：三个演示动作全部实测通过（在线笔记统计、本地 host_c 陪伴 plan 全链路、在线 MCP 提问）；新增《报名文案.md》复制即用文案包；host_c 段改本地运行（在线服务只挂 host_a）。报名系统字段必须由用户登录后核实，豆包不代填、不代注册。 +> 关键日期：初赛材料 + 组队报名 **09-19 同步关闭**（当天只做应急，主力 09-18 前完成）；评审 09.20–09.26；100 强 09-30；决赛路演 10-31（高校组 5 分钟路演 + 2 分钟答辩，每组别前 3 名晋级）。 + +## 1. 账号与报名（只能用户本人做） + +- [ ] 登录官网 https://aichallenge.msup.com.cn/ ，完成注册/实名认证（如系统要求） +- [ ] 选择赛道：**AI+超级智能体**；组别：**高校组**（若系统无组别选项则按实际页面填写并截图记录） +- [ ] 创建队伍：队名 **YAI**，单人；填写本人真实信息（姓名/学校/联系方式，以系统字段为准）——**真名只进报名系统**；公开仓库与对外材料统一只署队名 YAI 与 GitHub: Gi-Tuu（官网赛题页无材料署名/匿名要求，2026-09-13 核实） +- [ ] 记录报名系统显示的**截止具体时刻**（官网首页只写日期 09.19，未写时刻），回填到本文件 §5 +- [ ] 确认系统是否允许**单人参赛**（高校组）；若不允许，立即在选手群反馈并调整 +- [ ] 确认模型相关要求：是否指定/建议通义、DeepSeek 等模型，是否有加分或算力券（魔搭），回填 §5 + +## 2. 初赛材料四件套（系统上传字段以页面为准） + +| # | 材料 | 本地产物 | 状态 | +|---|---|---|---| +| 1 | 创意/方案文档（含大模型环节流程细节） | `docs/competitions/hangzhou/方案文档.md`（v0.3；待 Codex 终审与 zcode 入库；若系统只收 PDF/Word，导出步骤见 §4） | 已定稿待入库 | +| 1b | 报名字段文案（名称/简介/介绍/创新点/团队） | `docs/competitions/hangzhou/报名文案.md`（v1.0，复制即用，多字数版本） | 已就绪 | +| 2 | 可运行原型 | 在线 API https://yai-agent-core.onrender.com （冻结 0a2634f）+ GitHub https://github.com/Gi-Tuu/yai-agent-core | 已就绪，09-14 复测两端点正常 | +| 3 | 演示视频 ≤5 分钟 | 按《演示脚本.md》v0.3 于 09-18 录制，一次录三版；三个演示动作 09-14 均实测通过 | 脚本定稿待录 | +| 4 | 代码 + 说明文档 | README、`docs/walkthrough/` 00–14 逐行讲义、`docs/architecture.md`、CONTRIBUTING | 已就绪（随仓库公开） | + +## 3. 上传与截图留痕（每步截图存本地 `docs/competitions/hangzhou/evidence/`，该目录不入库） + +> 忽略纪律（zcode 入库时一并落实）：在 `.gitignore` 增加一行 `docs/competitions/hangzhou/evidence/`；提交前执行 `git status` 确认该目录未出现在暂存区。截图含报名系统个人信息，禁止推到公开仓库。 + +- [ ] 报名/组队成功页截图 +- [ ] 作品信息填写页截图（每个字段填完先截图再提交） +- [ ] 方案文档上传成功截图 +- [ ] 视频上传成功截图（记录系统是否转码、是否有封面） +- [ ] 仓库链接/在线地址填写截图 +- [ ] 最终提交确认页截图（含提交时间、作品编号，如有） +- [ ] 提交后用另一浏览器/无痕窗口复验：链接可打开、视频可播放 + +## 4. 方案文档导出（如系统要求 PDF/Word） + +- 仓库已有讲义构建链：`.\.venv\Scripts\python.exe scripts\build_walkthrough_docx.py`（docx 产物在 gitignore 的 `docs/exports/`）； +- PDF：先启动 LibreOffice headless 监听 2002，再用 LibreOffice 自带 python 跑 `scripts/lo_update_and_export.py `（venv python 无 uno 模块）； +- 方案文档是单文件 md，导出前先把 Mermaid 图在 GitHub 渲染后截图嵌入，或保留文字版全链路描述（§2.2 表格本身已完整描述流程，图失效不影响合规）。 + +## 5. 待确认问题（用户在系统/选手群核实后回填，禁止编造） + +1. [ ] 09-19 截止的**具体时刻**（系统页/公告原文）：__________ +2. [ ] 高校组**单人是否允许**（系统提示/群内组委会答复）：__________ +3. [ ] 初赛材料**确切上传字段与格式**（md/pdf/docx/视频大小上限/是否要封面图）：__________ +4. [ ] 模型使用是否有指定、加分或算力支持：__________（线索：msup 活动页 event.msup.com.cn/hangzhou 称"使用通义千问、DeepSeek 有额外加分、算力由魔搭社区提供"，但该页时间线与本届官网不一致、疑似往届页，须在系统/选手群核实本届口径；我们已在用 DeepSeek，若适用属自然命中） +5. [ ] 决赛"团队潜力"维度单人如何呈现（路演 FAQ 若有说明）：__________ + +## 6. 时间安排（与三赛总时间线对齐） + +| 日期 | 动作 | 责任 | +|---|---|---| +| 09-13 ~ 09-14 | 方案文档/演示脚本 v0.2→v0.3（Codex 审核意见已改完；09-14 豆包实测三个演示动作并出报名文案包） | 豆包 ✔ 待终审 | +| 09-15 ~ 09-16 | Codex 终审（随 X 批交接单 §B）；zcode 落实文档入库与 hangzhou.md 勘误 | Codex/zcode | +| 09-17 | 文档定稿（如需 PDF 当天导出）；用户完成 §1 账号报名、回填 §5 | 用户/豆包 | +| 09-18 | 录屏（一次三版，按 v0.3 脚本，host_c 段本地跑）；系统先上传占坑，再补传定稿 | 用户 | +| 09-19 | 截止日只做应急（补传/替换/联系组委会） | 用户 | + +## 7. 与 X-Agent 冻结的冲突防护（重要） + +- 杭州材料入库只动 `docs/competitions/`，**不触发 Render 部署**（Auto-Deploy 已关，线上锁死 0a2634f）； +- 09-19 前若 X-Agent PR 需要更新，优先处理 X-Agent（要重建快照 + 手动 redeploy + 改 reviewCommit），杭州文档提交与其错开； +- 录屏用的线上地址、commit 必须与 X-Agent PR 的 reviewCommit 一致（当前均为 0a2634f）。 diff --git "a/submissions/mcp-hackathon/yai-agent-core/source/docs/competitions/hangzhou/\346\226\271\346\241\210\346\226\207\346\241\243.md" "b/submissions/mcp-hackathon/yai-agent-core/source/docs/competitions/hangzhou/\346\226\271\346\241\210\346\226\207\346\241\243.md" new file mode 100644 index 0000000..f981d9b --- /dev/null +++ "b/submissions/mcp-hackathon/yai-agent-core/source/docs/competitions/hangzhou/\346\226\271\346\241\210\346\226\207\346\241\243.md" @@ -0,0 +1,189 @@ +# YAI 数字员工——让现有软件零改造获得自适应 Agent 能力 + +> 2026 AI杭州·码动未来 AI模型智能体创新大赛｜AI+超级智能体赛道｜高校组 +> 初赛创意/方案文档（v0.3，2026-09-14：v0.2 已按 Codex `40-review-hangzhou-entry.md` 完成 P1×3 + P2×5 修订；v0.3 将 §7 评审复现命令改为动作型措辞，规则/LLM 两条路由路径下均稳定命中工具调用） +> 写作纪律：本文只写仓库里可复现的事实（命令、数字、commit、线上响应），不写无法现场演示的能力。 + +## 0. 作品基本信息 + +| 项 | 内容 | +|---|---| +| 作品名 | YAI 数字员工（内核名 YAI Agent Core，发行包 `yai-agent-core`） | +| 赛道 | AI+超级智能体 | +| 组队 | 单人队，队名 **YAI**（GitHub: [Gi-Tuu](https://github.com/Gi-Tuu)）；参赛者真实姓名/学校等身份信息仅填写在报名系统，公开材料与代码仓不署真名 | +| 源码仓库 | https://github.com/Gi-Tuu/yai-agent-core | +| 在线原型 | https://yai-agent-core.onrender.com （免费 PaaS，Docker 部署） | +| 冻结 commit | `0a2634f3b13d690398c77d9119c3beecd4881929`（线上 /health 实时返回该值） | +| 模型 | DeepSeek `deepseek-chat`（OpenAI 兼容接口；模型可替换，内核不绑定厂商） | +| 主演示场景 | `examples/host_a_notes` 笔记/数据整理（办公提效） | +| 泛化佐证场景 | `examples/host_c_companion` 陪伴助手（同一内核换宿主即换岗位） | + +## 1. 痛点与创意（一句话） + +市面上的 Agent 产品大多是"又一个独立 Agent 应用/编排框架"：软件厂商想让自己的软件拥有 Agent 能力，仍然要自己接模型、写工具总线、写循环、写记忆、做适配。**YAI 反转了这个范式：宿主软件只负责"声明自己有什么能力"（普通业务函数 + 一行描述），YAI 内核在进程内自适应地完成意图理解、策略选择、规划、工具调用与结果交付**——宿主不写任何 Agent 代码，import 即得数字员工。 + +```python +# 宿主侧全部接入成本（examples/host_a_notes/run.py 同构）： +core = AgentCore.auto(capabilities, model) # capabilities 就是普通 Python 函数的列表 +result = await core.run("帮我统计一下笔记数量") # 或 async for event in core.astream(...) 拿事件流 +``` + +内核本体（`src/yai_core/`）**零第三方运行时硬依赖**（`pyproject.toml` 的 `dependencies = []`）；模型客户端、FastAPI 服务、MCP/OpenAPI 集成为可选 extra，按需安装。 + +## 2. 大模型环节全链路（评分硬要求：必须写清使用大模型的流程细节） + +### 2.1 全链路图（Mermaid，GitHub 直接渲染） + +```mermaid +flowchart TD + U[用户任务文本] --> D[能力自发现 introspect
宿主声明的函数 → 统一 ToolSpec] + D --> R{① LLM 路由器
一次性分类} + R -->|direct| A1[直接回答
模型自由生成] + R -->|react| A2[③ ReAct 循环] + R -->|plan| P[② Plan 模式：模型先拆步骤计划] + R -->|clarify| C[反问澄清] + R -.模型不可用/格式异常.-> RF[规则兜底路由
带工具即 react，可审计] + P --> A2 + A2 -->|模型输出 tool_calls| T[工具执行器 ToolExecutor
schema 校验 → allowlist 权限 → 执行] + T -->|native| TN[宿主本地函数] + T -->|mcp| TM[MCP Server 远程工具
如 DeepWiki，Streamable HTTP] + T -->|openapi| TO[OpenAPI 服务工具
spec 自动发现] + TN --> O[工具结果 tool_result 回灌上下文] + TM --> O + TO --> O + O -->|未完成| A2 + O -->|已完成| F[④ 模型收尾汇总 → 结构化结果 final_text] + A1 --> F + C --> F + F --> CH[通道交付：CLI / collect / FastAPI POST /v1/agent/run] + M[(SQLite / 内存记忆
条数+TTL 保留策略)] -.读写.-> A2 +``` + +### 2.2 每一次模型调用的职责（共 4 个可能的调用点） + +| # | 调用点 | 输入 | 模型产出 | 失败处理 | 对应代码 | +|---|---|---|---|---|---| +| ① | **路由分类**（每个任务恰好 1 次） | 用户任务 + 全部工具的 name/description | `strategy`（direct/react/plan/clarify）、`tier`、`reason` | 模型异常或 JSON 不合规时回退**规则路由**（有工具→react，无工具→direct），事件里 `source=rules` 可审计 | `kernel/router.py` | +| ② | **计划生成**（仅 plan 策略，1 次） | 任务 + 工具清单 | 有序步骤计划，发 `plan_created` 事件 | 计划为空则降级进 ReAct | `kernel/loop.py` | +| ③ | **ReAct 推理/工具选择**（0 到 N 轮） | 历史消息 + 工具结果 | 自然语言推理或 `tool_calls`（工具名+参数） | 参数经 JSON Schema 校验，非法即报错事件，不执行 | `kernel/loop.py`、`tools/executor.py`、`tools/schema.py` | +| ④ | **收尾汇总**（1 次） | 完整工具观察链 | 面向用户的最终答复 `final_text` | —— | `kernel/loop.py` | + +### 2.3 决策全程可审计：事件流实证 + +内核的每个自适应决策都通过**唯一事件出口** `AgentCore.astream` 以 `AgentEvent(type, data)` 流式发出，无静默决策。真实事件类型（`src/yai_core/types.py`）： + +```json +[ + {"type": "strategy_selected", "data": {"strategy": "react", "source": "llm", "reason": "任务需要查询笔记", "tier": "standard"}}, + {"type": "tool_call", "data": {"tool": "count_notes", "arguments": {}}}, + {"type": "tool_result", "data": {"tool": "count_notes", "ok": true, "preview": "3"}}, + {"type": "model_message","data": {"text": "你一共有 3 条笔记。"}}, + {"type": "done", "data": {"strategy": "react", "final_text": "你一共有 3 条笔记。"}} +] +``` + +字段口径（与源码逐行一致）：`tool_call` 为 `{tool, arguments}`；`tool_result` 为 `{tool, ok, preview|error}`，`preview` 是结果 JSON 文本的前 200 字符；`model_message` 为 `{text}`；`done` 为 `{strategy, final_text}`。 + +线上实测（2026-09-13，真实 DeepSeek）：原生工具任务"统计笔记数"十秒量级返回"3 条笔记"，事件链完整；MCP 任务（问 DeepWiki 上 python-sdk 的 Client 初始化）二十秒量级完成一次真实远程 MCP 工具调用并给出正确中文结论（时延含网络与免费实例冷启动波动，仅作参考）。 + +## 3. 五维评分逐项举证（各 20 分） + +### 3.1 技术可行性（20）——已运行，不是设想 + +- **在线可验收**：`GET https://yai-agent-core.onrender.com/health` 实时返回 `{"status":"ok","commit":"0a2634f…"}`；`GET /v1/tools` 列出当前工具；`POST /v1/agent/run`（请求体 `{"task": "..."}`）为真实能力端点。 +- **测试**：**125 项离线测试全绿**（假模型 / httpx MockTransport / 注入时钟，不依赖网络与 API Key），覆盖路由、循环、上下文压缩、记忆、保留策略、MCP 桥、OpenAPI 桥、限流、API。 +- **CI**：GitHub Actions 四矩阵（Ubuntu Python 3.11/3.12/3.13 + Windows 3.13）跑 ruff + pytest，最近一次 run 成功。 +- **可复现**：`uv sync --extra dev --extra llm --extra server --extra mcp --extra openapi` → `uv run pytest`（125 项全绿，命令与 CI 一致）→ `uv run python scripts/smoke_test.py`（一个内核冒烟跑通三个宿主）；`docker compose up --build` 容器化（容器内 8000）；PaaS 部署件为 `render.yaml` + `Dockerfile`。 +- **生产化细节**：POST 端点每 IP 滑动窗口限流（默认 30 次/分钟，超限返回 429 + Retry-After，GET 验证端点永久放行，不触达模型不花额度）；历史保留策略（默认 200 条 / 7 天 TTL，按对话轮边界裁剪，不会拆散工具调用对）。 + +### 3.2 市场可行性（20）——泛用性与落地路径 + +- **泛用性实证**：仓库内置 4 个宿主示例——办公笔记（host_a，3 个本地工具）、数据应用（host_b）、AI 陪伴（host_c，5 个工具：档案/回忆/记忆/心情/关怀建议）、本地 MCP 演示（host_d）。**同一份内核，不改一行内核代码，换 capabilities 即换岗位**。 +- **接入成本低**：宿主工具就是普通 Python 函数，类型注解 + docstring 自动转 JSON Schema（与 MCP 工具同构），无需学习新框架概念。 +- **落地路线明确**：第一阶段作为独立开源内核（本作品）；第二阶段回流内嵌进开源 AI 陪伴项目 AMBRACE（https://github.com/Gi-Tuu/AMBRACE），验证真实 To C 软件内嵌路径；第三阶段经 MCP 标准化接入更大生态（X-Agent MCP Hackathon 已同步投稿，PR #56）。 +- **商业模式友好**：Library-first、进程内运行，不强制托管、不抽成、不锁定模型厂商，软件厂商保留自己的数据与 UI。 + +### 3.3 综合创新性（20） + +1. **范式创新——host-declares-capability / core-adapts**：现有框架（LangChain/CrewAI/AutoGen 等）止步于"提供积木"，仍需开发者自己组装 Agent；YAI 让**已有软件零 Agent 代码**获得能力，定位是"可内嵌的内核"而非"又一个 Agent 应用"。 +2. **自适应路由可审计**：LLM 一次性输出策略决策（strategy/tier/reason），每个决策落事件流；模型不可用时有规则兜底，保证确定性退化。 +3. **双协议工具发现**：同一工具注册表面对三类来源——native 函数、MCP Server（官方 python-sdk，支持 Streamable HTTP / stdio / 进程内直连三种传输）、OpenAPI spec（最小规范解析 → 工具自动桥接，测试用 MockTransport 离线验证）。 +4. **内核零硬依赖 + SPI 四契约**（model/channel/memory/policy）：模型、通道、记忆、权限全部面向契约编程，宿主可逐项替换。 + +### 3.4 AI 大模型结合（20）——见 §2 全链路 + +补充事实：① 模型层为 OpenAI 兼容抽象（`llm/openai_compat.py`），DeepSeek/通义/OpenAI 仅改环境变量；② 上下文管理按轮边界压缩（`kernel/context.py`），避免长对话超窗且不切断工具调用对；③ 鼓励项"长短期记忆"已落地：SQLite 持久化（带 scope 隔离与 schema 版本钩子）+ 条数/TTL 保留；④ 鼓励项"工具调用"为核心能力，MCP 远程工具已在线真实跑通；⑤ 鼓励项"工作流编排"对应 plan 策略的显式计划事件。多智能体、多模态在路线图中（见 §6），初赛版本不宣称。 + +### 3.5 赛道维度（20）——任务理解/规划/工具/交付/闭环 + +| 赛道评分点 | 作品对应 | +|---|---| +| 模糊意图解析与任务拆解 | LLM 路由器 + plan 模式；意图不清走 clarify 反问 | +| 自主规划 | `plan_created` 事件给出有序步骤，再逐步执行 | +| 工具调用与环境交互（区别于问答机器人的关键） | Discovery 自发现 → ToolRegistry → Schema 校验 → Allowlist 权限 → Executor；native/MCP/OpenAPI 三源 | +| 结果交付与可验收性 | 结构化 RunResult（strategy/events/final_text）；FastAPI 上 POST 即得 JSON 事件序列；CLI/collect 双通道 | +| 场景价值与端到端闭环 | host_a"整理/统计笔记"全流程录屏演示；线上 curl 可现场复验 | +| 长短期记忆（鼓励项） | SQLite 持久化 + 200 条/7 天保留策略 | +| 检索增强 RAG（鼓励项） | OpenAPI/MCP 工具即外部知识入口（DeepWiki 远程查询实证）；向量检索在路线图，不冒称已具备 | + +## 4. 演示场景设计（与演示视频脚本一致，详见《演示脚本.md》） + +- **主场景（host_a 办公提效）**：3 条虚构笔记 + `list_notes(tag)` / `search_notes(keyword)` / `count_notes()` 三个工具，演示"统计笔记数 → 按关键词检索 → 汇总"端到端闭环，画面带事件流。 +- **换岗位（host_c）**：同一内核切到陪伴宿主，工具集与策略随之变化，证明泛化。 +- **能力纵深**：MCP 远程工具（DeepWiki）一次真实调用；SQLite 记忆持久化说明。 +- 全部演示数据为虚构，无真实个人数据。 + +## 5. 技术架构（简版） + +```text +宿主软件（host_a / host_c / 任意 Python 软件 / AMBRACE） + │ 声明 capabilities（普通函数）+ 选择 model/channel/memory/policy + ▼ +YAI Agent Core（进程内库，零第三方硬依赖） + ├── discovery/introspect 能力自发现（函数 → ToolSpec） + ├── kernel/router ① LLM 路由（规则兜底，可审计） + ├── kernel/context 轮边界压缩 + ├── kernel/loop ②③④ 计划/ReAct/收尾，事件流唯一出口 + ├── tools/ registry / executor / schema 校验 + ├── policy/allowlist 工具权限收口 + ├── memory/ inmemory + sqlite_store + retention（条数/TTL） + ├── spi/ model / channel / memory / policy 四契约 + ├── integrations/mcp MCP Client（HTTP/stdio/内存） + ├── integrations/openapi OpenAPI spec 解析与工具桥接 + └── batteries/fastapi_server /health /验证端点 /v1/tools /v1/agent/run + 限流中间件 +``` + +## 6. 诚实边界（可现场说明，不回避） + +- v0.1 明确**未做**：MCP Server、多智能体协作、自进化写工具、向量记忆/RAG、内置 UI、coding agent；这些在公开路线图中，初赛材料不宣称。 +- 在线实例为 Render 免费层：15 分钟无流量休眠（冷启动约 30–90 秒、波动较大，已配每 10 分钟保活工作流）；本地 SQLite 随临时盘重建即清空（演示数据本为虚构，不影响评审）。 +- 限流用于防误刷，不防御伪造 X-Forwarded-For（代码注释与提交材料均如实声明）。 +- 无账号体系/鉴权墙：评审无需登录即可调用，反而降低验收门槛；鉴权在路线图。 + +## 7. 关键复现命令（评审现场可用） + +```bash +# 线上（无需任何安装） +curl https://yai-agent-core.onrender.com/health +curl https://yai-agent-core.onrender.com/v1/tools +curl -X POST https://yai-agent-core.onrender.com/v1/agent/run \ + -H "Content-Type: application/json" -d '{"task":"帮我统计一下笔记总数"}' + +# 离线复现（Python 3.11+，uv） +git clone https://github.com/Gi-Tuu/yai-agent-core && cd yai-agent-core +git checkout 0a2634f3b13d690398c77d9119c3beecd4881929 +uv sync --extra dev --extra llm --extra server --extra mcp --extra openapi +uv run pytest # 125 项离线测试（命令与 CI 一致） +uv run ruff check src tests examples scripts +uv run python scripts/smoke_test.py # 三宿主自适应冒烟 +``` + +## 8. 附：评分→证据速查 + +| 维度 | 最强证据 | +|---|---| +| 技术可行性 | 线上 API + 125 测试 + CI 四矩阵 + Docker/Render 部署 | +| 市场可行性 | 4 宿主泛化实证 + 三行接入 + AMBRACE 回流路线 | +| 综合创新性 | 范式反转 + 可审计路由 + MCP/OpenAPI 双协议 + 内核零依赖 | +| AI 大模型结合 | §2 全链路图 + 4 个模型调用点职责 + 事件流实证 | +| 赛道维度 | 路由/规划/工具/交付/记忆逐项有模块与演示对应 | diff --git "a/submissions/mcp-hackathon/yai-agent-core/source/docs/competitions/hangzhou/\346\274\224\347\244\272\350\204\232\346\234\254.md" "b/submissions/mcp-hackathon/yai-agent-core/source/docs/competitions/hangzhou/\346\274\224\347\244\272\350\204\232\346\234\254.md" new file mode 100644 index 0000000..f5d4353 --- /dev/null +++ "b/submissions/mcp-hackathon/yai-agent-core/source/docs/competitions/hangzhou/\346\274\224\347\244\272\350\204\232\346\234\254.md" @@ -0,0 +1,55 @@ +# YAI 数字员工 · 初赛演示视频脚本（≤5 分钟） + +> v0.3，2026-09-14，按豆包实测修订：host_c 陪伴段改为**本地终端运行**（在线服务只挂载 host_a，不能在线 POST 陪伴任务，2026-09-14 实测确认）；补 POST #1 路由兜底重发预案；三个演示动作均已实测（host_a 在线、host_c 本地默认任务、MCP 在线提问）。 +> 硬约束：总时长 ≤ 5:00；在线 POST 限流 30 次/分钟/IP，本脚本在线 POST **至多 2 次**（host_c 段为本地运行，不计限流），安全；演示数据全部虚构。 + +## 0. 录制前置（开录前 10 分钟做完） + +1. 浏览器先访问一次 https://yai-agent-core.onrender.com/health 唤醒免费实例（冷启动约 30–90 秒，波动大），确认返回 `"commit":"0a2634f…"`； +2. 终端开好两个标签页：① 在线 curl（PowerShell 7 / pwsh）；② 本地运行（pwsh，已 `cd 'D:\YAI Agent Core'`，用于 host_c 段）；VS Code 单独开窗（已 checkout `0a2634f`）； +3. 本地备好 `examples/host_a_notes/capabilities.py`、`examples/host_c_companion/capabilities.py`、`src/yai_core/kernel/router.py` 三个文件标签； +4. 关闭无关通知；录屏分辨率 1080p；浏览器缩放到 125%，终端字号 16+； +5. 录屏中不出现 `.env`、API Key、任何真实个人信息。 + +## 1. 分镜时间轴 + +| 时间 | 画面操作 | 旁白要点（口播稿） | 素材/命令 | +|---|---|---|---| +| 0:00–0:30 | 标题卡 + 痛点画面（一个普通软件的函数列表） | "现有软件想拥有 Agent，要自己接模型、写工具总线、写循环和记忆。YAI 数字员工换了个方向：软件只声明自己会什么，内核在进程里自适应地完成剩下全部。" | 标题卡：作品名 + 队名 YAI | +| 0:30–1:00 | VS Code 打开 host_a `capabilities.py`：三个普通函数；再打开 `run.py` 展示 `AgentCore.auto(...)` | "宿主侧没有任何 Agent 代码：三个普通业务函数，类型注解和 docstring 就是全部声明；接入内核只有一行 auto。" | 代码特写：`list_notes/search_notes/count_notes`、`AgentCore.auto` | +| 1:00–1:30 | 终端 curl `/health`、`/v1/tools`（GET，不计限流） | "这是已经在线部署的原型，健康端点实时返回被评审的 commit；工具端点列出宿主声明后内核自动发现的全部工具，包括本地工具和远程 MCP 工具。" | `curl .../health`；`curl .../v1/tools` | +| 1:30–3:00 | **在线 POST 第 1 次**：任务"我一共有多少条笔记？"；展示返回的事件流 JSON（strategy_selected→tool_call→tool_result→done）与最终答复（2026-09-14 实测：在线 LLM 路由对该问法判 react，正确调 count_notes 返回 3 条） | "一次真实任务：内核先让模型做策略判断——这是工具型任务，走 ReAct；模型选择 count_notes，内核校验参数、过权限白名单后执行，结果回灌，模型收尾：3 条笔记。每一步决策都在事件流里，可审计、可回放。" | `curl -X POST .../v1/agent/run -d '{"task":"我一共有多少条笔记？"}'`；**兜底预案**：若返回 `strategy` 不是 react（LLM 分类偶发波动），原样重发一次动作型措辞 `{"task":"帮我统计一下笔记总数"}`（规则与 LLM 两条路径都稳定命中 react），重发不占额外准备时间 | +| 3:00–3:40 | VS Code 切到 host_c `capabilities.py`（5 个陪伴工具）；切到终端标签②**本地运行 host_c**（不是在线 POST——在线服务只挂载 host_a）：跑默认任务，展示 plan 策略下 3 个工具依次调用与最终关怀建议（2026-09-14 实测通过：plan → get_companion_profile → recall_memories → suggest_care_action → 完整汇报） | "同一个内核，换成陪伴宿主，只换 capabilities，工具集、路由策略随之改变——数字员工换了岗位，内核一行没动。这里还能看到 plan 模式：模型先拆出三步计划，再逐步调用工具。" | 命令：`.\.venv\Scripts\python.exe examples/host_c_companion/run.py`（默认任务即可，无需引号传参）；本地走 .env 的 DeepSeek，不计在线限流 | +| 3:40–4:20 | **在线 POST 第 2 次**：MCP 任务"DeepWiki 上 modelcontextprotocol python-sdk 的 Client 怎么初始化？"（2026-09-14 实测通过：read_wiki_structure → ask_question 两次远程 MCP 调用，二十秒量级，返回带代码的中文结论）；展示 `tool_call`/`tool_result` 事件，并切到 `/v1/tools` 指给观众看该工具的 `source` 字段为 `mcp`，最后落到中文结论 | "工具不止本地函数：内核内置 MCP 客户端，这是对 DeepWiki 远程 MCP Server 的一次真实调用，返回的结论来自远程知识库而不是模型背诵。" | 同端点 POST + `curl .../v1/tools`（GET）；注意"工具来源"看 `/v1/tools` 的 `source` 字段，事件流里没有该字段 | +| 4:20–4:45 | 切到仓库网页：Actions CI 绿勾、测试计数；SQLite 记忆文件/保留策略配置一笔带过 | "工程侧：125 项离线测试不依赖网络和密钥，CI 四个操作系统/版本矩阵全绿；记忆默认 SQLite 持久化，并带条数与 7 天 TTL 的保留策略。" | GitHub Actions 页、`tests/` 目录、`memory/retention.py` | +| 4:45–5:00 | 收尾卡：在线地址 + 仓库地址 + 一句话 | "YAI 数字员工：让已有软件零改造获得自适应 Agent 能力。谢谢。" | 收尾卡两行 URL | + +备用素材（剪辑取舍，不进主时间轴）：OpenAPI 工具发现（petstore 最小 spec 离线 demo）、三宿主冒烟脚本 `uv run python scripts/smoke_test.py` 终端录屏。 + +## 2. POST 预算核对（限流 30 次/分钟/IP） + +- 主时间轴**在线** POST：1:30 段 0 次（GET）；1:30–3:00 第 1 次（笔记统计）；3:00–3:40 为**本地运行**（host_c，不占在线额度）；3:40–4:20 第 2 次（MCP）；合计在线 **2 次**，远低于阈值。 +- host_c 段为本地进程（`examples/host_c_companion/run.py`），消耗的是本地 .env 的模型额度，与在线限流无关；若时间紧，该段可整段删（属泛化佐证，非主链路）。 +- 若录制失误重拍：在线 POST 每分钟不超过 30 次即可；被限流会收到 429 + `Retry-After`，等 60 秒再录。 +- GET（/health、/v1/tools、部署证明）不受限流影响，可随意刷新。 + +## 3. 冷启动与保活预案 + +- 每段录制开始前 1 分钟先 curl 一次 /health 预热； +- 仓库已配 keepwarm 工作流（每 10 分钟自动 GET /health），评审/录制窗口实例通常是热的； +- 若 POST 超 60 秒无响应：实例正在冷启动，等 1 分钟重试，不要连点（连点会浪费限流额度）。 + +## 4. 口播纪律（哪些话不能说） + +- 不说"支持任意工具/任意软件"（无法当场演示）；说"任何能提供普通 Python 函数的宿主，三行接入"。 +- 不说多智能体、RAG、向量记忆、自进化（v0.1 未做）；如被问到，答"在公开路线图中，初赛版本聚焦单内核自适应"。 +- 不贬低任何具体框架名字；只讲定位差异（"积木 vs 内嵌内核"）。 +- 数字只说可复现的：125 项测试、四矩阵、4 个示例宿主、3 个本地工具、5 个陪伴工具、冻结 commit 0a2634f。 + +## 5. 录制后剪辑三版分工 + +| 版本 | 素材取舍 | 时长 | +|---|---|---| +| 杭州主版（本脚本） | 全段，标题/收尾用杭州赛事口径 | ≤5:00 | +| X-Agent 版 | 0:30–1:00 代码段压缩，保留 curl/health/POST/MCP 段，收尾用英文地址卡 | 2–3 分钟 | +| 上海版 | 加重 CI/测试/讲义/架构段，弱化"数字员工"叙事，改"开源智能体内核"叙事 | 3–4 分钟 | diff --git a/submissions/mcp-hackathon/yai-agent-core/source/docs/competitions/shanghai.md b/submissions/mcp-hackathon/yai-agent-core/source/docs/competitions/shanghai.md new file mode 100644 index 0000000..5d4c706 --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/docs/competitions/shanghai.md @@ -0,0 +1,24 @@ +# 2026 上海开源软件应用创新大赛 提交清单 + +- 官网：https://www.oschina.net/os2026/ +- 时间：报名+提交至 10.11 24:00（邮件 oscc@oschina.cn）；入围公布 10.16；决赛 10.24 张江科学会堂 + +## 选赛道 + +首选 **智算云赛道（智能体框架/运行时方向）**；备选开源 AI 工具赛道（AI 开发工具）。 + +## 评审维度对应 + +| 维度 | 权重 | YAI 动作 | +|---|---|---| +| 技术创新 | 30% | 能力自发现+策略自适应；README 放与 5 类现有方案的诚实对比表 | +| 场景落地 | 30% | 双宿主 demo + 在线 API + 录屏，可部署可运行可测试 | +| 开源治理 | 20% | MIT LICENSE、README/CONTRIBUTING、GitHub Actions(CI)、pytest、Issue/PR 模板、规范 commit | +| 长期发展 | 20% | AMBRACE 回流路线图、版本路线、社区文档 | + +## 提交材料 + +1. 代码仓库链接（公开、完整可运行） +2. 作品介绍 PDF（背景/技术架构/应用场景/创新点） +3. 演示视频链接（核心功能与使用流程） +4. 个人/团队均可，建议 3–5 人；每项目限一个赛道 diff --git a/submissions/mcp-hackathon/yai-agent-core/source/docs/competitions/xagent.md b/submissions/mcp-hackathon/yai-agent-core/source/docs/competitions/xagent.md new file mode 100644 index 0000000..783c5bf --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/docs/competitions/xagent.md @@ -0,0 +1,49 @@ +# X-Agent AI MCP Hackathon 2026 提交清单（开放创新挑战赛） + +- 官网：https://xagt.ai/hackathon?lang=zh +- 提交仓库：https://github.com/xagentAI/xagt-plugin（Fork 后提 PR） +- 关键时间：报名+开发 09.02–09.19；技术审核评审 09.20–10.01；结果 10.02–10.04 + +## 硬门槛（7 项最低提交要求） + +1. 评审窗口内可调用的已部署 API +2. GET /health 返回 `{"status":"ok","commit":"<40位被审 commit>"}` +3. 完整源码放入 PR 的 `source/`（外链仓库不算提交） +4. 与部署一致的公开 GitHub pinned commit +5. 可复现的 setup/test/deploy/一次真实调用说明 +6. `/.well-known/xagent-verification.json` → `{"schemaVersion":1,"slug":...,"commit":...}` +7. 安全/数据/依赖/权利声明（RIGHTS.md） + +## 提交目录 + +``` +submissions/mcp-hackathon/-/ +├── SUBMISSION.md +├── submission.json +├── RIGHTS.md +├── source/ +└── verification/README.md +``` + +## YAI 的打法 + +- 卖点：嵌入式自适应 Agent 内核（官方赛道明列 Agent 基础设施） +- 杀手证据：同一 Core 挂载两个宿主能力集，API 完成两类不同任务 +- 不需要自建 MCP Server（官方验证后协助标准化） +- 禁止：链上安全/审计类项目 + +## 提交物骨架（已落地，2026-09-10 按官方 validate-submission.mjs 核对） + +- 元数据目录：`submissions/mcp-hackathon/yai-agent-core/`（SUBMISSION.md / RIGHTS.md / + verification/README.md / submission.template.json；`source/` 不入库，构建时生成） +- 构建 + 离线预检：`python scripts/build_xagent_submission.py` + （git archive HEAD 导出 source/、注入 reviewCommit、镜像官方结构/密钥/体积校验） +- 线上一致性预检：`python scripts/build_xagent_submission.py --online` + （校验 GitHub commit 可公开访问、/health 与验证端点的 slug/commit 三处一致） +- slug 统一定名 `yai-agent-core`（render.yaml、.env.example、验证端点、提交目录四处一致） +- 冻结提交时：Render 关 autoDeploy → 手动部署 pinned commit → 跑 --online 预检 → + fork xagt-plugin → 复制 dist 快照目录 → 提 PR（只动一个提交目录） +- 评审期保活（2026-09-20 ~ 10-04）：`.github/workflows/keepwarm.yml` 每 10 分钟 GET /health， + 规避 Render 免费层冷启动（30–90s）撞校验器 10s GET 超时；评审结束后手动停用。 +- 校验器口径（2026-09-13 复核官方 scripts/validate-submission.mjs）：10s 超时与 64KiB 上限 + 只卡 health / 部署证明两个 GET；POST 不进自动门槛；包体 5MiB/文件、20MiB/包、2000 文件上限。 diff --git a/submissions/mcp-hackathon/yai-agent-core/source/docs/reading-guide.md b/submissions/mcp-hackathon/yai-agent-core/source/docs/reading-guide.md new file mode 100644 index 0000000..a94f552 --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/docs/reading-guide.md @@ -0,0 +1,101 @@ +# YAI Agent Core 代码学习导览（边学边造专用） + +> 目标：不是"看懂每一行"，而是按顺序读完后，能向别人讲清楚 Core 怎么转起来，并能动手改。 +> 建议节奏：每天 1～2 站，配合运行与小练习；卡住超过 30 分钟就先跳过，在文件里留 `# Q:` 注释。 + +> **配套逐行讲解**：`docs/walkthrough/` 里有每个源码文件逐块、逐行的解释（00 总览 → 09 在线 API），本篇负责路线，walkthrough 负责抠细节，两篇对照着看。 + +## 0. 先跑起来（10 分钟） + +```powershell +cd "D:\YAI Agent Core" +.\.venv\Scripts\python.exe scripts\smoke_test.py +``` + +观察三个宿主输出的差异：**同一份 Core 代码没动**，只是换了 `capabilities`，自动发现的工具、选择的策略就不同。这就是整个项目的核心主张，先建立感性认识。 + +## 1. 推荐阅读顺序（7 站） + +### 站 1：`src/yai_core/types.py` —— 项目的"词汇表" +- 解决什么：全项目传递的数据长什么样（工具、消息、事件、策略）。 +- Python 知识点：`dataclass`（数据容器）、`StrEnum`（字符串枚举）、`Literal`、类型注解、`field(default_factory=...)`。 +- 读完标志：能说出 `ToolSpec / ChatMessage / ModelResponse / AgentEvent` 各自装什么。 +- 小练习：给 `EventType` 加一个 `RETRY = "retry"`，想想哪个环节会发出它。 + +### 站 2：`src/yai_core/discovery/introspect.py` —— "能力自发现"的魔法来源 +- 解决什么：宿主的普通函数如何自动变成带 JSON Schema 的工具。 +- Python 知识点：`inspect.signature`、类型注解如何被程序读取、`get_origin/get_args`（Optional 原理）、字典构造。 +- 关键理解：这里没有魔法，只是把函数签名"读"出来翻译成 LLM 认识的格式。 +- 小练习：在 `examples/host_a_notes/capabilities.py` 加一个带默认参数的新函数，重跑 smoke，看它是否自动出现。 + +### 站 3：`src/yai_core/tools/` —— 注册表与执行总线 +- `registry.py`：Python 知识点——类、字典封装、自定义异常（`KeyError/ValueError` 的使用场景）。 +- `executor.py`：重点看三件事——权限决策、`inspect.isawaitable` 如何让同步/异步函数都能跑、为什么用 try/except 把工具错误"回灌"给模型而不是崩溃。 +- 小练习：故意把工具函数改成 `raise ValueError("boom")`，观察 Agent 是否还能正常收尾。 + +### 站 4：`src/yai_core/kernel/router.py` —— 自适应决策的第一版 +- 解决什么：凭什么选 direct/react/plan/clarify。 +- Python 知识点：枚举比较、`any()/sum()` 生成器、纯函数（同样输入必同样输出，所以最好测）。 +- 对照测试读：`tests/test_router.py` 每个用例就是一条决策规则的"说明书"。 +- 小练习：加一个你自己的中文触发词，让"帮我看看"也能触发 react；同步加一条测试。 + +### 站 5：`src/yai_core/kernel/loop.py` —— Core 的心脏（最重要，慢读） +- 解决什么：策略选定后，模型与工具如何来回循环直到产出结果。 +- Python 知识点（正好是你的学习清单）： + - `async def / await`：为什么 IO 密集的 LLM 调用必须异步； + - **异步生成器** `async ... yield`、`async for`：事件为什么能"边跑边往外吐"； + - 控制流：plan 先拆步骤、react 循环、max_iters 兜底、clarify 递归重入。 +- 调试建议：在 `_react_cycle` 每轮循环开头打印 `len(ctx.messages)`，看消息历史如何增长。 +- 读完标志：能默画出"用户任务 → 模型 → 工具调用 → 工具结果 → 模型 → 最终答案"的闭环。 + +### 站 6：`src/yai_core/spi/` 与默认实现 —— 可替换的四个插槽 +- 解决什么：为什么 Core 不绑定模型厂商、不绑定 UI、不绑定数据库。 +- Python 知识点：`Protocol`（结构化子类型："只要长这样就能插进来"，不需要继承）、依赖注入（构造函数传入）。 +- 对照读：`llm/openai_compat.py`（真实插槽）、`channels/collect.py`（测试插槽）、`tests/test_loop.py` 里的 `ScriptedModel`（假插槽）。 +- 小练习：写一个 `EchoModel` 实现 `achat`（直接返回固定话），接进 Core 跑一次。 + +**加一站（v0.2）**：`src/yai_core/memory/sqlite_store.py` —— 同一个记忆插槽的第二个实现。 +对照 InMemoryStore 读：表结构、scope 隔离、user_version 迁移钩子、为什么同步 SQL 直接跑在 +async 方法里（见 walkthrough 第 11 章）。读完应能回答：为什么 Loop 一行没改就获得了持久记忆。 + +**再加一站（v0.2）**：`src/yai_core/integrations/openapi/` —— 对照第 10 章 MCP 桥读： +spec.py 的 $ref 内联与循环保护、discovery.py 的入参合并、client.py 的鉴权与响应归一。 +读完应能回答：为什么一份 OpenAPI 描述就能让 Core 不写一行适配代码获得一批工具（见 walkthrough 第 12 章）。 + +### 站 7：`src/yai_core/core.py` 与 `batteries/fastapi_server/app.py` +- `core.py` 是门面：宿主只需要认识 `AgentCore.auto()` 和 `run()`，内部全被藏起来（门面模式）。 +- Battery 展示"内核"与"外围"的边界：注意 fastapi/pydantic 是**懒加载**的，内核本体不依赖它们。 +- 小练习：用 `scripts/serve_example.py` 的写法，把 host_c_companion 也变成一个 HTTP 服务。 + +## 2. 术语对照表（第一次读会反复遇到） + +| 术语 | 在本项目里的意思 | +|---|---| +| 宿主 Host | 嵌入 Core 的现有软件（host_a/b/c，未来是 AMBRACE） | +| SPI | 宿主可替换、Core 给默认实现的接口契约（Model/Channel/Memory/Policy） | +| Adaptive Router | 决定任务走哪种执行策略的组件 | +| ReAct | 推理-调用工具-观察结果-再推理的循环 | +| Tool Bus | 统一执行工具的通道（权限、异常、结果格式化都在这） | +| Observer 事件流 | 运行过程对外发出的可观测事件，自适应决策不许黑盒 | +| Battery | 可选外围能力（HTTP 服务等），不属于内核 | + +## 3. 动手实验环境 + +- 推荐用 VS Code 打开 `D:\YAI Agent Core`，在 `loop.py` 行号左侧点一下设断点，F5 调试 `scripts/smoke_test.py`。 +- 常用命令： + ```powershell + .\.venv\Scripts\python.exe -m pytest # 全部测试 + .\.venv\Scripts\python.exe -m pytest -k router # 只跑路由测试 + .\.venv\Scripts\python.exe -m ruff check src tests examples scripts + ``` + +## 4. "学懂了"自检清单 + +- [ ] 能不看代码画出 Core 的分层图并说出每层文件 +- [ ] 能解释宿主为什么"零 Agent 代码" +- [ ] 能说出一次 react 循环中 messages 列表里依次出现了哪几种 role +- [ ] 能新增一个宿主函数并让 Agent 调用到它 +- [ ] 能写一个假 ModelProvider 离线测试一条新执行路径 +- [ ] 能指出哪部分代码是"内核绝不能依赖第三方"的边界 + +全部打勾后，再进入 Day 1-3（真实 DeepSeek 接入），那时你会清楚知道每一行在干什么。 diff --git a/submissions/mcp-hackathon/yai-agent-core/source/docs/walkthrough/00-index.md b/submissions/mcp-hackathon/yai-agent-core/source/docs/walkthrough/00-index.md new file mode 100644 index 0000000..0d054ec --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/docs/walkthrough/00-index.md @@ -0,0 +1,98 @@ +# 逐行讲解 00 · 导读：一次请求穿过整个 Core + +> 这套文档对 `src/yai_core/` 每个文件做逐块、逐行解释，面向"边学边造"的你。 +> 读法：先读本篇建立全局地图，再按编号逐篇对照源码看。每篇末尾有自检问题，答得上来再往下走。 + +## 0. 先记住一句话 + +**宿主只提供普通函数；Core 把函数变成工具，自己决定怎么用工具完成任务，并把过程一步步喊出来。** + +## 1. 一张全景图（数字就是执行顺序） + +``` +你的任务 "先查看状态，然后检索约定记忆，给出关怀建议" + │ + │ ① AgentCore.auto(宿主模块, 模型) 【core.py】 + │ └─ discover(宿主) 【discovery/introspect.py】 + │ 读函数签名/docstring → ToolSpec 列表 → 注册进 ToolRegistry【tools/registry.py】 + │ └─ （可选）attach_mcp_tools 接入外部 MCP 工具，同样注册进 ToolRegistry + │ 【integrations/mcp/client.py】 + │ + │ ② await core.run(任务) 【core.py】 + │ └─ AgentLoop.astream(任务) 【kernel/loop.py】 + │ + │ ③ Router.classify(任务, 注册表) → 策略 【kernel/router.py】 + │ 没有工具→direct / 行动词→react / 多步+行动→plan / 太模糊→clarify + │ + │ ④ Context 组装消息列表 【kernel/context.py】 + │ + │ ⑤（plan 时）先让强模型拆步骤，再补一条"按计划执行"的 user 指令 + │ + │ ⑥ ReAct 循环 【kernel/loop.py】 + │ 模型.achat(消息, 工具清单) 【llm/openai_compat.py / 任何 SPI 模型】 + │ ├─ 模型不调工具 → 最终答案，结束 + │ └─ 模型要调工具 → ToolExecutor.execute 【tools/executor.py】 + │ ├─ PermissionPolicy.check 权限 【policy/allowlist.py】 + │ ├─ 真正执行宿主的普通 Python 函数 + │ └─ 结果包成 tool 消息塞回 Context，继续循环 + │ + │ ⑦ 全过程的每个动作变成 AgentEvent，经 Channel 往外发 【channels/】 + │ ⑧ 历史写进 Memory（InMemoryStore / SqliteStore）【memory/】 + └ 返回 RunResult（策略 + 事件列表 + 最终文本） +``` + +## 2. 文件分工速查 + +| 文件 | 角色 | 类比 | +|---|---|---| +| `types.py` | 全项目通用的数据结构 | 普通话词典 | +| `spi/*.py` | 四个"插槽"的接口约定 | 插座标准 | +| `discovery/introspect.py` | 把函数读成工具规格 | 自动翻译官 | +| `tools/registry.py` | 工具花名册 | 电话簿 | +| `tools/executor.py` | 真正调用工具的地方 | 总机 | +| `kernel/router.py` | 决定用哪种打法 | 作战参谋 | +| `kernel/context.py` | 管理发给模型的消息 | 剪贴板 | +| `kernel/loop.py` | 主循环（心脏） | 发动机 | +| `memory/inmemory.py` | 默认记忆 | 短期便签本 | +| `memory/sqlite_store.py` | 持久化记忆（opt-in） | 带锁的笔记本 | +| `memory/retention.py` | 历史裁剪纯函数（条数/TTL，轮边界对齐） | 会碎纸的碎纸机 | +| `policy/allowlist.py` | 默认权限 | 门禁 | +| `channels/*.py` | 默认输入输出 | 显示屏/话筒 | +| `llm/openai_compat.py` | 真实模型适配 | 翻译给 DeepSeek 听 | +| `core.py` | 对外唯一门面 | 前台 | +| `integrations/mcp/client.py` | 接入外部 MCP Server 的工具 | 外接设备转接头 | +| `integrations/openapi/` | OpenAPI 发现（opt-in） | REST API 的自动翻译官 | +| `batteries/fastapi_server/app.py` | 包成 HTTP 服务 | 对外营业窗口 | +| `batteries/fastapi_server/ratelimit.py` | 评审期限流（每 IP 滑动窗口） | 门口的取号机 | + +## 3. 贯穿全项目的 5 个 Python 语法（先混个脸熟，后面逐个细讲） + +1. `from __future__ import annotations`：让类型注解延迟成字符串，写新式注解不报错。 +2. `async def / await / async for / yield`：异步与异步生成器，loop.py 的核心。 +3. `@dataclass`：几行代码写出"只装数据的类"。 +4. `Protocol`：不继承也能算"符合接口"（鸭子类型的书面版）。 +5. `X | None`、`list[dict]`：新式类型注解。 + +## 4. 分篇目录 + +- 01 · `types.py`：数据词汇表 +- 02 · `spi/`：四个可替换插槽 +- 03 · `discovery/introspect.py`：能力自发现 +- 04 · `tools/`：注册表 + 执行总线 +- 05 · `kernel/router.py` + `context.py`：决策与上下文 +- 06 · `kernel/loop.py`：主循环逐行（最重要） +- 07 · 默认实现：memory / policy / channels +- 08 · `llm/openai_compat.py` + `core.py`：真实模型与门面 +- 09 · `batteries/fastapi_server` + `Dockerfile`：变成在线 API 并容器化部署 +- 10 · `integrations/mcp/client.py`：MCP Client，把外部工具接进注册表 +- 11 · `memory/sqlite_store.py`：SQLite 持久化记忆（scope、迁移钩子、WAL） +- 12 · `integrations/openapi/`：OpenAPI 发现（REST API 零适配变工具，$ref/鉴权/只读闸） +- 13 · `memory/retention.py` + 两个 Store：历史保留策略（条数裁剪/TTL，轮边界对齐，opt-in） +- 14 · `batteries/fastapi_server/ratelimit.py`：限流 Battery（滑动窗口、429 + Retry-After、GET 放行） + +## 5. 自检（读完本篇应能回答） + +1. 宿主写的函数，是在哪一步变成工具的？ +2. 策略是在哪决定的？四种策略分别什么意思？ +3. 工具结果通过什么回到模型那里？ +4. 为什么说 Channel 是"显示屏"而 Core 本身不打印东西？ diff --git a/submissions/mcp-hackathon/yai-agent-core/source/docs/walkthrough/01-types.md b/submissions/mcp-hackathon/yai-agent-core/source/docs/walkthrough/01-types.md new file mode 100644 index 0000000..6d571b9 --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/docs/walkthrough/01-types.md @@ -0,0 +1,158 @@ +# 逐行讲解 01 · `types.py`：全项目的数据词汇表 + +> 目标：看懂项目里传递的每一种"数据包"长什么样。 +> 知识点：模块 docstring、`from __future__`、类型别名、StrEnum、dataclass、field。 + +## 块 1 · 文件头与导入（L1-L11） + +```python +"""YAI Agent Core 的核心数据类型。 + +刻意只依赖标准库：内核本体零第三方依赖，第三方能力全部通过 SPI 注入。 +""" +``` +- 三引号字符串放在文件最开头叫**模块 docstring**，调用 `help(模块)` 或 IDE 悬停时能看到。它也是给你自己看的设计说明。 + +```python +from __future__ import annotations +``` +- "未来导入"。Python 3.11 其实已经支持新注解，但加上它后，所有类型注解都不在运行时立刻求值（当成字符串处理），可以放心写 `list[ToolSpec]`、自引用等而不报错。**项目里每个文件第一行都是它，照抄即可。** + +```python +from collections.abc import Callable +from dataclasses import dataclass, field +from enum import StrEnum +from typing import Any, Literal +``` +- `Callable`："这是一个可以被调用的东西（函数）"的类型。注意它从 `collections.abc` 导入（现代写法），Ruff 会自动帮你从旧的 `typing` 挪过来。 +- `dataclass, field`：数据类装饰器和它的辅助函数，下面细讲。 +- `StrEnum`：字符串枚举（Python 3.11+），成员本身就是字符串。 +- `Any`：任意类型（放弃检查，只在确实无法确定时用）；`Literal[...]`：取值只能是列出的字面量之一。 + +## 块 2 · 角色类型别名（L13） + +```python +Role = Literal["system", "user", "assistant", "tool"] +``` +- 定义**类型别名**：以后写 `role: Role` 等价于 `role: Literal[...]`，IDE 会提示只能填这 4 种字符串，拼错立刻警告。 +- 这 4 个角色正是大模型对话协议里的角色：系统设定 / 用户 / 助手（模型）/ 工具回传。 + +## 块 3 · 两个枚举（L16-L36） + +```python +class Strategy(StrEnum): + DIRECT = "direct" + REACT = "react" + PLAN = "plan" + CLARIFY = "clarify" +``` +- 枚举 = "有限的几个候选值"。`Strategy.DIRECT` 既是枚举成员，`str(Strategy.DIRECT)` 又是 `"direct"`，这就是 StrEnum 比 `(str, Enum)` 更干净的地方。 +- 为什么不直接到处写字符串 `"react"`？因为字符串拼错不报错，而 `Strategy.REAC` 拼错会直接报 `AttributeError`，且 IDE 能自动补全。 + +`EventType` 同理，列出运行全过程可能出现的 9 种事件。**这就是"可观测"的词汇表**：以后每做一个动作，都从这里挑一个事件类型发出去，不会出现叫法不一。 + +## 块 4 · ToolSpec：工具的统一身份证（L39-L58） + +```python +@dataclass +class ToolSpec: + name: str + description: str + input_schema: dict[str, Any] + handler: Callable[..., Any] + source: Literal["native", "openapi", "mcp"] = "native" +``` +- `@dataclass` 会自动生成 `__init__`，所以你能直接 `ToolSpec(name="x", description=..., ...)`，不用手写构造函数。 +- 字段逐个看： + - `name`：工具名（模型靠它点名调用）； + - `description`：给模型看的"这个工具干嘛的"； + - `input_schema`：参数的 JSON Schema（什么参数、什么类型、哪些必填）； + - `handler`：真正干活的 Python 函数；`Callable[..., Any]` 表示"任意参数、返回任意值的可调用对象"； + - `source`：工具来源，默认 `"native"`（宿主自己的函数），未来 OpenAPI/MCP 来的工具也用**同一个类**装——这就是"同构"。 +- 注意写法规则：**没有默认值的字段必须排在有默认值的前面**（和函数参数一个道理）。 + +```python +def llm_schema(self) -> dict[str, Any]: + return { + "type": "function", + "function": { + "name": self.name, + "description": self.description, + "parameters": self.input_schema, + }, + } +``` +- 普通方法：把内部表示翻译成 OpenAI 兼容接口要求的工具形状。以后 DeepSeek 收到的就是这个字典。**"内部一种结构，对外按需翻译"是贯穿项目的手法。** + +## 块 5 · ChatMessage：一条对话消息（L61-L78） + +```python +@dataclass +class ChatMessage: + role: Role + content: str = "" + tool_calls: list[dict[str, Any]] | None = None + tool_call_id: str | None = None + name: str | None = None +``` +- `X | None`：要么是 X，要么是 None（等价旧写法 `Optional[X]`）。 +- 一条消息在不同角色下用不同字段： + - user/assistant 普通对话：主要用 `role + content`； + - assistant 决定调工具时：填 `tool_calls`（可能一次调多个）； + - 工具回传结果时：`role="tool"` + `tool_call_id`（对应哪次调用）+ `name`（哪个工具）。 + +```python +def to_llm_dict(self) -> dict[str, Any]: + d: dict[str, Any] = {"role": self.role, "content": self.content} + if self.tool_calls: + d["tool_calls"] = self.tool_calls + ... + return d +``` +- 先建一个最小字典，**有值才加键**：因为模型接口不喜欢收到 `tool_calls: None` 这种空字段。 +- `d: dict[str, Any] = {...}` 里的注解是写给人和 IDE 看的，运行不影响。 + +## 块 6 · 其余四个数据类（L81-L107） + +```python +@dataclass +class ToolCallRequest: + id: str + name: str + arguments: dict[str, Any] = field(default_factory=dict) +``` +- 模型说"我要调工具"时的结构化请求。 +- **重点：`field(default_factory=dict)`**。可变默认值（列表/字典）不能直接写 `={}`，否则所有实例会共享同一个字典！`default_factory=dict` 的意思是"每次新建时调用 `dict()` 生成一个新的"。下面 `ModelResponse.tool_calls`、`AgentEvent.data` 同理，这是 Python 经典坑，记住就好。 + +```python +@dataclass +class ModelResponse: + content: str = "" + tool_calls: list[ToolCallRequest] = field(default_factory=list) + raw: Any = None +``` +- 模型回复的统一形状：要么有正文 `content`，要么有工具调用，也可能都有。`raw` 保存厂商原始返回，调试用。 + +```python +@dataclass +class AgentEvent: + type: EventType + data: dict[str, Any] = field(default_factory=dict) +``` +- Observer 事件：`type` 说明发生了什么，`data` 装细节。Loop 里 `yield AgentEvent(...)` 就是在"对外广播"。 + +```python +@dataclass +class RunResult: + strategy: Strategy + events: list[AgentEvent] + final_text: str +``` +- `core.run()` 最终交给宿主的结果包：用了什么策略、全过程事件、最终文本。 + +## 自检 + +1. 为什么 `arguments` 要用 `field(default_factory=dict)` 而不能直接 `={}`？ +2. 一条 `role="tool"` 的消息为什么必须带 `tool_call_id`？ +3. `ToolSpec.source` 留了哪三种来源？这和"不重复造轮子"有什么关系？ +4. 把 `EventType` 里删掉一个、在 loop.py 里引用它会发生什么？（动手试） diff --git a/submissions/mcp-hackathon/yai-agent-core/source/docs/walkthrough/02-spi.md b/submissions/mcp-hackathon/yai-agent-core/source/docs/walkthrough/02-spi.md new file mode 100644 index 0000000..09fcd5c --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/docs/walkthrough/02-spi.md @@ -0,0 +1,107 @@ +# 逐行讲解 02 · `spi/`：四个可替换插槽 + +> 目标：理解 Core 为什么不绑定模型厂商、不绑定 UI、不绑定数据库。 +> 知识点：Protocol（结构化子类型 / 鸭子类型）、runtime_checkable、`...` 函数体、接口与实现分离。 + +## 0. 什么是 SPI + +SPI = Service Provider Interface（服务提供者接口）。意思是：**Core 只规定"你得长这样"，不规定"你是谁家的"。** +谁满足这套方法签名，谁就能插进 Core 当模型/通道/记忆/权限。Core 自己另外提供了"默认款"（见第 07 篇）。 + +四个文件结构几乎一样，学会一个就会四个。 + +## 1. `spi/model.py`：模型插槽 + +```python +from typing import Any, Protocol, runtime_checkable +from yai_core.types import ChatMessage, ModelResponse + +@runtime_checkable +class ModelProvider(Protocol): + async def achat( + self, + messages: list[ChatMessage], + tools: list[dict[str, Any]] | None = None, + *, + tier: str = "standard", + ) -> ModelResponse: + ... +``` + +逐行： +- `class Xxx(Protocol)`：声明一个**协议**。它不写实现，只写"符合本协议的对象必须有哪些方法、什么参数、返回什么"。 +- `@runtime_checkable`：允许用 `isinstance(obj, ModelProvider)` 运行时检查（没它只能做类型提示）。 +- `async def achat(...)`：模型调用是网络 IO，所以是异步方法。 +- `messages`：对话历史；`tools`：本轮给模型的工具清单（None=不让用工具）。 +- `*`：**仅限关键字参数分隔符**，它后面的 `tier` 调用时必须写名字 `tier="strong"`，防止位置传参搞错。`tier` 是模型路由的钩子：standard 走便宜模型，strong 走强模型（规划时用）。 +- 函数体只有 `...`（Ellipsis）：协议方法不需要实现，`...` 就是"占位、到此为止"。 + +**关键理解**：DeepSeek 适配（`OpenAICompatProvider`）、测试里的 `ScriptedModel`、示例里的 `OfflineScriptedModel` 都没有继承 `ModelProvider`，但因为它们都"恰好有一个签名一致的 `achat` 方法"，就都能被 Core 当模型用。这叫**结构化子类型**（俗称鸭子类型：走起来像鸭子就是鸭子）。 + +## 2. `spi/channel.py`：输入输出插槽 + +```python +@runtime_checkable +class Channel(Protocol): + async def emit(self, event: AgentEvent) -> None: ... + async def ask(self, question: str) -> str: ... + async def confirm(self, tool_name: str, arguments: dict[str, Any]) -> bool: ... +``` +- `emit`：Core 把运行事件往外发（打印、推给网页、推给 Flutter 都靠各自实现）。 +- `ask`：策略为 clarify 时反问用户，拿回一句回答。 +- `confirm`：权限策略为 ASK 时，问宿主"这个工具允许执行吗"，返回布尔。 +- 返回 `None` 表示这个方法没有有意义的返回值（只做动作）。 + +**为什么 Core 不直接 print？** 因为 Core 是内核，它不知道自己将来跑在终端、网页还是 Flutter 里。把"怎么显示/怎么问人"抽成 Channel，内核就和 UI 彻底解耦。 + +## 3. `spi/memory.py`：记忆插槽 + +```python +@runtime_checkable +class MemoryStore(Protocol): + async def append_history(self, message: ChatMessage) -> None: ... + def history(self) -> list[ChatMessage]: ... + async def put(self, key: str, value: str) -> None: ... + async def get(self, key: str) -> str | None: ... + async def clear(self) -> None: ... +``` +- v0.1 只要求两件事：**会话历史**（append/history）和**简单 KV**（put/get）。 +- 注意 `history()` 不是 async：它只是读内存列表，没有 IO，没必要异步。**同步/异步的选择标准：有没有等待 IO（网络/磁盘）。** +- 未来 `SqliteStore`、向量记忆只要实现这几个方法就能替换，Loop 一行不用改。 + +## 4. `spi/policy.py`：权限插槽 + +```python +class PermissionDecision(StrEnum): + ALLOW = "allow" + DENY = "deny" + ASK = "ask" + +@runtime_checkable +class PermissionPolicy(Protocol): + async def check(self, tool_name: str, arguments: dict[str, Any]) -> PermissionDecision: ... +``` +- 每次工具执行前问一句权限：直接放行 / 拒绝 / 先问人。 +- 三态而不是两态，是因为陪伴/数据类软件里"删除、发送、付款"这类动作必须有人确认，这是 AMBRACE 未来必备的安全闸。 + +## 5. `spi/__init__.py`：统一出口 + +```python +from yai_core.spi.channel import Channel +from yai_core.spi.memory import MemoryStore +from yai_core.spi.model import ModelProvider +from yai_core.spi.policy import PermissionDecision, PermissionPolicy +``` +- 把四个协议集中到 `yai_core.spi` 包名下，外部一行导入：`from yai_core.spi import ModelProvider, Channel`。 +- `__init__.py` 的作用：把一个文件夹标记为 Python 包，并决定"对外暴露什么"。 + +## 设计思想小结（比赛材料也用得上） + +> Core 面向协议编程，不面向具体实现编程。新增一种模型/UI/数据库 = 新写一个满足协议的小类，内核零修改——这正是"可扩展、可内嵌"的根。 + +## 自检 + +1. `ScriptedModel` 没有继承 `ModelProvider`，为什么能传给 AgentCore 当模型？ +2. `*, tier` 里的星号起什么作用？ +3. 为什么 `history()` 是同步方法而 `append_history` 是异步？ +4. 如果要接微信小程序当 UI，你需要实现哪个 SPI？实现哪几个方法？ diff --git a/submissions/mcp-hackathon/yai-agent-core/source/docs/walkthrough/03-discovery.md b/submissions/mcp-hackathon/yai-agent-core/source/docs/walkthrough/03-discovery.md new file mode 100644 index 0000000..def770e --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/docs/walkthrough/03-discovery.md @@ -0,0 +1,163 @@ +# 逐行讲解 03 · `discovery/introspect.py`：能力自发现 + +> 这是 YAI"宿主零 Agent 代码"的魔法来源。其实没有魔法——只是用标准库 `inspect` 把函数签名读出来。 +> 知识点：inspect.signature、类型注解的读取、Optional 原理、字典构建、模块/方法判断。 + +## 块 1 · 导入与类型映射表（L7-L22） + +```python +import inspect +import types +from typing import Any, get_args, get_origin +from yai_core.types import ToolSpec + +_PY_TO_JSON: dict[type, str] = { + str: "string", int: "integer", float: "number", + bool: "boolean", list: "array", dict: "object", +} +``` +- `inspect`：Python 反射标准库，可以在运行时读取"函数叫什么、有哪些参数、注解是什么、docstring 是什么"。 +- `get_origin / get_args`：拆解复杂注解的工具，比如把 `Optional[str]`（即 `str | None`）拆成 `(str, NoneType)`。 +- `_PY_TO_JSON`：Python 类型 → JSON Schema 类型名的对照表。**字典的键可以是类型本身**（类也是对象）。 +- 下划线前缀 `_PY_TO_JSON`：约定"模块内部使用"，`from xxx import *` 不会导出它。 + +## 块 2 · 把单个注解翻译成 JSON 类型（L25-L36） + +```python +def _annotation_to_json_type(annotation: Any) -> tuple[str, bool]: + if annotation is inspect.Parameter.empty: + return "string", False +``` +- 返回值标注 `tuple[str, bool]`：返回一个二元组（JSON 类型、是否可空）。 +- `inspect.Parameter.empty` 是个**哨兵对象**：当参数根本没写类型注解时，`param.annotation` 就是它。这里保守回退成 `"string"`。 + +```python + origin = get_origin(annotation) + if origin in (types.UnionType, getattr(__import__("typing"), "Union", object)): + args = [a for a in get_args(annotation) if a is not type(None)] + nullable = len(args) != len(get_args(annotation)) + if args: + return _PY_TO_JSON.get(args[0], "string"), nullable + return _PY_TO_JSON.get(annotation, "string"), False +``` +逐行： +- `get_origin(annotation)`：取出"外壳"。`str | None` 的外壳是 union 类型；普通 `str` 的外壳是 None。 +- 判断外壳是不是联合类型：`types.UnionType` 对应新式 `X | None`；`typing.Union` 对应老式 `Optional[X]`。两种写法都兼容。 + - 这里 `getattr(__import__("typing"), "Union", object)` 是"动态导入 typing 再取 Union"的防御写法，等价于先 `from typing import Union` 再用 `Union`（你自己写代码时用普通 import 更清晰）。 +- 列表推导式 `[a for a in get_args(...) if a is not type(None)]`：把 `NoneType` 过滤掉，剩下真实类型。 +- `nullable`：过滤前后数量不一样，说明里面原本有 None → 可空。 +- `dict.get(k, 默认)`：找不到映射就回退 `"string"`，绝不因为陌生类型崩溃。 + +## 块 3 · build_spec：一个函数 → 一张工具身份证（L39-L74） + +```python +def build_spec(fn: Any, *, name: str | None = None, source: str = "native") -> ToolSpec: + if not callable(fn): + raise TypeError(f"build_spec 需要可调用对象，得到 {type(fn)!r}") +``` +- `*,` 后面的参数必须用关键字传：`build_spec(f, name="x")`。 +- `callable(fn)`：判断是不是函数/可调用对象；不是就**快速失败**并给出清晰错误。 +- f-string 里 `!r` 表示用 `repr()` 显示（带引号/类型细节），调试信息更明确。 + +```python + sig = inspect.signature(fn) + properties: dict[str, Any] = {} + required: list[str] = [] +``` +- `inspect.signature(fn)` 拿到函数签名对象；后两个变量分别装"参数 schema"和"必填参数名"。 + +```python + for param_name, param in sig.parameters.items(): + if param.kind in (inspect.Parameter.VAR_POSITIONAL, inspect.Parameter.VAR_KEYWORD): + continue + json_type, nullable = _annotation_to_json_type(param.annotation) + prop: dict[str, Any] = {"type": json_type} + if param.default is inspect.Parameter.empty: + required.append(param_name) + else: + prop["default"] = param.default + if nullable: + prop["type"] = [json_type, "null"] + properties[param_name] = prop +``` +逐行： +- `sig.parameters` 是有序映射，键是参数名，值是参数对象。 +- `VAR_POSITIONAL`（`*args`）和 `VAR_KEYWORD`（`**kwargs`）无法表达成固定 JSON 参数，`continue` 跳过。 +- 每个参数生成一个 `{"type": ...}` 描述。 +- **没有默认值 = 必填**（加入 required）；有默认值就把默认值写进 schema，模型可以不传。 +- 可空时 JSON Schema 写法是 `"type": ["string", "null"]`。 +- 最后挂进 `properties[参数名]`。 + +```python + doc = inspect.getdoc(fn) or "" + description = doc.split("\n\n", 1)[0].strip() or name or fn.__name__ +``` +- `inspect.getdoc(fn)`：拿到函数 docstring（还会自动去掉缩进）。 +- `split("\n\n", 1)[0]`：只取第一段（空行之前）作为简介，避免把长篇说明塞给模型。 +- `A or B or C` 链式兜底：没 docstring 就用传入 name，再不行用函数自身的 `__name__`。 + +```python + schema: dict[str, Any] = {"type": "object", "properties": properties} + if required: + schema["required"] = required + return ToolSpec( + name=name or fn.__name__, description=description, + input_schema=schema, handler=fn, source=source, + ) +``` +- 拼成标准 JSON Schema：`{"type":"object","properties":{...},"required":[...]}`。 +- required 为空就不写这个键（干净）。 +- 产出 ToolSpec：函数本体存进 `handler`，以后执行就是调它。 + +## 块 4 · discover：自动扫出一批函数（L77-L100） + +```python +def discover(host: Any) -> list[ToolSpec]: + specs: list[ToolSpec] = [] + if inspect.ismodule(host): + module_name = host.__name__ + members = inspect.getmembers(host, inspect.isfunction) + for member_name, fn in members: + if member_name.startswith("_"): + continue + if getattr(fn, "__module__", None) != module_name: + continue + specs.append(build_spec(fn)) + return specs +``` +针对**模块**（我们的 `capabilities.py` 就是模块）： +- `inspect.getmembers(host, inspect.isfunction)`：列出模块里所有函数，返回 `(名字, 函数)` 列表。 +- 下划线开头的跳过（私有约定）。 +- **关键防线**：`fn.__module__ != module_name` 时跳过——因为模块顶部 `import xxx` 进来的函数也会被 getmembers 列出来！只保留"本模块自己定义的"，避免把 `date`、第三方函数误注册成工具。 + +```python + for member_name, fn in inspect.getmembers(host, inspect.ismethod): + if member_name.startswith("_"): + continue + specs.append(build_spec(fn)) + return specs +``` +针对**对象实例**（未来宿主用类组织能力时）：`inspect.ismethod` 只挑绑定方法，同样跳过私有方法。 + +## 串起来看 + +`examples/host_a_notes/capabilities.py` 里写： +```python +def search_notes(keyword: str) -> list[dict]: ... +``` +`discover(capabilities)` 会自动产出等价于： +```json +{"name": "search_notes", + "description": "按关键词搜索笔记标题与正文。", + "parameters": {"type": "object", + "properties": {"keyword": {"type": "string"}}, + "required": ["keyword"]}} +``` +宿主完全没写 Agent 代码，工具就"长出来了"。 + +## 自检 + +1. 为什么必须判断 `fn.__module__`？删掉这行会发生什么（可以在 host_a 顶部加个 import 试试）？ +2. 参数 `limit: int = 5` 会被翻译成什么 schema？必填吗？ +3. `Optional[str]` 经过 `_annotation_to_json_type` 返回什么？ +4. 给 host_c 新增一个带两个参数的函数，跑 smoke 观察自动发现结果。 diff --git a/submissions/mcp-hackathon/yai-agent-core/source/docs/walkthrough/04-tools.md b/submissions/mcp-hackathon/yai-agent-core/source/docs/walkthrough/04-tools.md new file mode 100644 index 0000000..77ded0d --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/docs/walkthrough/04-tools.md @@ -0,0 +1,146 @@ +# 逐行讲解 04 · `tools/`：注册表与执行总线 + +> 两个文件分工：`registry.py` 管"有哪些工具"，`executor.py` 管"怎么安全地调用一次工具"。 +> 知识点：类的封装、字典即存储、自定义异常、列表推导、async/sync 统一、错误回灌。 + +## A. `tools/registry.py` + +### A1. 初始化（L8-L12） +```python +class ToolRegistry: + def __init__(self) -> None: + self._tools: dict[str, ToolSpec] = {} +``` +- 内部就是一个字典：`工具名 -> ToolSpec`。**数据结构选对，代码就简单**：查找天然 O(1)。 +- `_tools` 下划线开头 = "外部别直接碰，走我的方法"（封装约定）。 + +### A2. 注册（L14-L21） +```python +def register(self, spec: ToolSpec) -> None: + if spec.name in self._tools: + raise ValueError(f"工具 {spec.name!r} 已注册，名称必须唯一") + self._tools[spec.name] = spec + +def register_many(self, specs: Iterable[ToolSpec]) -> None: + for spec in specs: + self.register(spec) +``` +- 重名立刻报错（快速失败），否则后注册的会悄悄覆盖前者，极难排查。 +- `register_many` 只是循环调用单个注册，**复用而不是重写**。 +- `Iterable[ToolSpec]`：任何可迭代对象（列表/生成器）都行，比写死 `list` 更宽松。 + +### A3. 查询（L23-L35） +```python +def get(self, name: str) -> ToolSpec: + if name not in self._tools: + raise KeyError(f"未知工具 {name!r}，当前可用：{list(self._tools)}") + return self._tools[name] + +def has(self, name: str) -> bool: + return name in self._tools + +def all(self) -> list[ToolSpec]: + return list(self._tools.values()) + +def llm_schemas(self) -> list[dict]: + return [spec.llm_schema() for spec in self._tools.values()] +``` +- `get` 找不到时把"当前有哪些工具"一并报出来，方便模型/开发者纠错。 +- `all()` 返回 `list(...)` 而不是直接给内部字典视图，防止外部改坏内部状态（防御性拷贝）。 +- `llm_schemas` 用列表推导式把每个 ToolSpec 翻译成模型要的格式——一行等价一个 for 循环。 + +### A4. 描述与长度（L37-L44） +```python +def describe(self) -> str: + if not self._tools: + return "（当前宿主没有提供任何工具）" + return "\n".join(f"- {s.name}: {s.description}" for s in self._tools.values()) + +def __len__(self) -> int: + return len(self._tools) +``` +- `describe()` 生成系统提示词里的"能力清单"文本。 +- `__len__` 是**魔术方法**：实现后就能写 `len(registry)`，router 里 `len(registry) == 0` 就是这么来的。 + +## B. `tools/executor.py` + +### B1. 构造（L19-L27） +```python +def __init__(self, registry, policy, channel) -> None: + self.registry = registry + self.policy = policy + self.channel = channel +``` +- 执行器需要三样东西：从注册表找工具、问权限策略做决策、通过 channel 向人确认。这就是典型的**依赖注入**——需要什么就传什么，不自己 new，方便替换和测试。 + +### B2. execute 的骨架与返回约定（L29-L35） +```python +async def execute(self, name, arguments) -> tuple[list[AgentEvent], bool, str]: + """返回 (过程事件列表, 是否成功, 文本结果)，永不向 Agent Loop 抛异常。""" + events: list[AgentEvent] = [] + if not self.registry.has(name): + return events, False, f"工具 {name!r} 不存在" +``` +- 三元组返回：过程中产生的**事件**、成功与否、给模型看的**文本结果**。 +- 铁律"永不抛异常"：工具是宿主写的，可能出错；但工具出错绝不能让整个 Agent 崩掉，而是把错误文本回灌给模型，让它自己换办法（在 06 篇会看到这条错误文本如何进入下一轮消息）。 + +### B3. 权限闸门（L37-L46） +```python +decision = await self.policy.check(name, arguments) +if decision == PermissionDecision.ASK: + events.append(AgentEvent(EventType.PERMISSION_ASKED, {...})) + approved = await self.channel.confirm(name, arguments) + if not approved: + return events, False, f"用户/宿主拒绝执行工具 {name}" +if decision == PermissionDecision.DENY: + return events, False, f"权限策略拒绝执行工具 {name}" +``` +- `await policy.check(...)`：权限判断本身也允许是异步的（比如要查数据库/问远程）。 +- ASK：先发一个"正在请求权限"的事件（UI 可据此弹确认框），再通过 channel 等人确认。 +- DENY / 拒绝都走同一条"返回失败文本"的路。 + +### B4. 真正执行（L48-L65） +```python +events.append(AgentEvent(EventType.TOOL_CALL, {"tool": name, "arguments": arguments})) +spec = self.registry.get(name) +try: + result = spec.handler(**arguments) + if inspect.isawaitable(result): + result = await result + text = json.dumps(result, ensure_ascii=False, default=str) +except Exception as exc: + events.append(AgentEvent(EventType.TOOL_RESULT, {"tool": name, "ok": False, "error": str(exc)})) + return events, False, f"工具 {name} 执行出错: {type(exc).__name__}: {exc}" +``` +逐行： +- 先发 TOOL_CALL 事件（UI 上显示"正在调用 xxx"）。 +- `spec.handler(**arguments)`：`**arguments` 把字典展开成关键字参数。模型给 `{"keyword":"周报"}`，等价于调用 `search_notes(keyword="周报")`。 +- **同步/异步统一**：宿主函数可能是普通函数也可能是 `async def`。先调用，若返回的是可等待对象（协程），就再 `await` 一下。这样两种宿主函数都支持。 +- `json.dumps(..., ensure_ascii=False)`：把任意 Python 对象（dict/list/数字）转成 JSON 文本；`ensure_ascii=False` 让中文直接显示而不是 `\uXXXX`；`default=str` 遇到不认识的类型就调 `str()` 兜底，不崩溃。 +- `except Exception as exc` 兜住所有业务异常，`type(exc).__name__` 取异常类名，组成错误文本返回。`# noqa: BLE001` 是告诉 Ruff"我知道这里捕获很宽，是故意的"。 + +```python +events.append(AgentEvent(EventType.TOOL_RESULT, {"tool": name, "ok": True, "preview": text[:200]})) +return events, True, text +``` +- 成功：发 TOOL_RESULT 事件，事件里只放前 200 字预览（避免 UI 被巨量数据刷屏），但**完整 text 返回给模型**。 + +## 一次工具调用的完整时序 + +``` +Loop 说：执行 search_notes({"keyword":"周报"}) + → Executor: 有这个工具吗？ + → Policy: allow / deny / ask？ + → 发 TOOL_CALL 事件 + → handler(**arguments)，必要时 await + → json.dumps 成文本 + → 发 TOOL_RESULT 事件 + → 把 (events, ok, text) 交回 Loop +``` + +## 自检 + +1. 为什么工具出错不能 raise 到 Loop？错误最后以什么形式回到模型？ +2. `**arguments` 展开的是哪一步产生的字典？ +3. Executor 怎么同时支持同步函数和 async 函数？ +4. 为什么 TOOL_RESULT 事件里只放 200 字预览，而返回值给全文？ diff --git a/submissions/mcp-hackathon/yai-agent-core/source/docs/walkthrough/05-router-context.md b/submissions/mcp-hackathon/yai-agent-core/source/docs/walkthrough/05-router-context.md new file mode 100644 index 0000000..fbd4406 --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/docs/walkthrough/05-router-context.md @@ -0,0 +1,227 @@ +# 逐行讲解 05 · `kernel/router.py` 与 `kernel/context.py` + +> Router 决定"用什么打法"，Context 管理"发给模型的消息本"。都很短，但都是决策核心。 + +## A. `kernel/router.py`：自适应路由 + +### A1. 信号词表（router.py 顶部） +```python +_PLAN_HINTS = ("然后", "接着", "之后", "再把", "分步", "步骤", "先", "并且", + "同时", "对比", "整理成", "汇总成", "最终", "一共", "分别") +_ACTION_HINTS = ("查", "找", "搜", "列出", "统计", "计算", "导出", "获取", + "读取", "记录", "新增", "整理", "分析", "筛选", "生成", + # 显式的工具/MCP 调用意图（v0.2 接外部 MCP Server 后补齐） + "问一下", "查询", "调用", "工具", "mcp") +_CLARIFY_HINTS = ("随便", "你看着办", "什么都行", "帮我弄一下") +``` +- 三个元组就是三张"关键词表"。这是 v0.1 的确定性规则实现：**零成本、离线可跑、每条规则都能写单元测试**（见 `tests/test_router.py`）。 +- 元组而不是列表：这些表不该被运行时修改，元组语义更准确。 +- 最后五个词是一次真实回归补的：任务写"用 MCP 工具**问一下**……"时，旧词表没有任何动作信号，被路由成 direct，结果模型想调工具却拿不到工具清单，只能把工具调用写成文本。规则路由是 LLM 路由的兜底，**兜底也必须覆盖最直白的工具意图表达**。 + +### A2. 类与构造（L27-L29） +```python +class AdaptiveRouter: + def __init__(self, *, min_plan_steps: int = 2) -> None: + self.min_plan_steps = min_plan_steps +``` +- 预留参数 `min_plan_steps`（v0.2 LLM 分类器会用到）。v0.1 先占住扩展位，这叫"为变化留门，但不提前实现"。 + +### A3. classify 决策函数（L31-L47）——按顺序读，顺序就是优先级 +```python +def classify(self, task: str, registry: ToolRegistry) -> Strategy: + text = task.strip() + if not text: + return Strategy.CLARIFY +``` +- `strip()` 去掉首尾空白；空任务无法处理 → 反问。 + +```python + if any(h in text for h in _CLARIFY_HINTS) and len(text) < 12: + return Strategy.CLARIFY +``` +- `any(生成器)`：只要有一个信号词命中就为 True。 +- **为什么还要 `len(text) < 12`？** 防止误杀：一句很长、很具体但恰好含"随便"二字的任务不该被当成模糊请求。规则系统要靠这种"组合条件"降低误判。 + +```python + if len(registry) == 0: + return Strategy.DIRECT +``` +- 宿主一个工具都没有，再复杂也没法调工具，只能让模型直接回答。注意它在行动判断**之前**——能力边界优先于用户意图。 + +```python + # 拉丁字母提示词（如 mcp）大小写不敏感；中文提示词按原文匹配。 + lowered = text.lower() + wants_action = any( + (h in lowered) if h.isascii() else (h in text) for h in _ACTION_HINTS + ) + multi_step = sum(1 for h in _PLAN_HINTS if h in text) >= 1 + if multi_step and wants_action: + return Strategy.PLAN + if wants_action: + return Strategy.REACT + return Strategy.DIRECT +``` +- `wants_action`：像需要动手的任务。 +- `h.isascii()` 判断提示词是不是纯拉丁字母（如 `"mcp"`）：是就对**小写化后的任务**匹配，让 "MCP"、"mcp"、"Mcp" 都能命中；中文词不受影响（中文没有大小写，`lower()` 也不会改它，但保持语义清晰）。 +- 生成器表达式里的三元表达式 `(h in lowered) if h.isascii() else (h in text)`：逐个提示词选择匹配文本，`any(...)` 有一个命中即 True。 +- `multi_step`：`sum(1 for h in ... if 命中)` 是"数命中了几个多步信号"的生成器写法；命中 ≥1 就算多步。 +- 决策优先级：**多步且要动手 → PLAN（先规划再执行）；只动手 → REACT；其余 → DIRECT。** +- 最后一行注释解释了一个反直觉点：DIRECT 时模型并非被禁止用工具，只是首轮不塞工具清单（在 06 篇看 `use_tools`）。 + +> v0.2 已加 LLM 分类器（见 C 节），**规则实现保留作兜底**：模型分类失败/超时时回退到这里。 +> 这种"智能方案 + 确定性兜底"是生产级 Agent 的常见结构。 + +## B. `kernel/context.py`：消息本与 token 预算 + +### B1. 初始化（L9-L11） +```python +def __init__(self, system_prompt: str, *, max_chars: int = 24000) -> None: + self.max_chars = max_chars + self.messages: list[ChatMessage] = [ChatMessage(role="system", content=system_prompt)] +``` +- 一次运行对应一个 Context。创建时**第一条永远是 system 消息**（角色设定 + 工具清单）。 +- v0.1 用字符数粗略估 token（中文约 1 字 ≈ 1～2 token），所以预算叫 `max_chars`；v2 再换精确的 tokenizer。 + +### B2. 追加并自动压缩（L13-L25） +```python +def add(self, message: ChatMessage) -> None: + self.messages.append(message) + self._compact() +``` +- 每次追加后立刻检查是否超预算，调用方不用操心。 + +```python +def _compact(self) -> None: + total = sum(len(m.content) for m in m for m in self.messages) # 示意 +``` +实际代码： +```python + total = sum(len(m.content) for m in self.messages) + i = 1 + while total > self.max_chars and i < len(self.messages) - 1: + total -= len(self.messages[i].content) + i += 1 + if i > 1: + self.messages = [self.messages[0], *self.messages[i:]] +``` +逐行： +- 先算所有消息内容总字符数（生成器求和）。 +- `i = 1`：**从下标 1 开始**，因为下标 0 是 system 消息，永远保留；最后一条也保留（`i < len-1`），因为它通常是当前问题。 +- while 循环：只要还超预算，就"虚拟跳过"第 i 条并累加 i。 +- `[self.messages[0], *self.messages[i:]]`：`*` 解包——保留 system，拼接从 i 开始的剩余消息，中间旧消息被丢弃。 +- 这是最简单的"滑动窗口"记忆压缩；v2 会换成摘要式压缩。 + +### B3. 输出给模型（L27-L28） +```python +def llm_messages(self) -> list[dict]: + return [m.to_llm_dict() for m in self.messages] +``` +- 把内部 ChatMessage 列表统一转成模型接口要的字典列表。再次体现"内部对象、边界翻译"。 + +## C. LLM 路由器（v0.2）：模型分类 + 规则兜底 + +规则路由零成本、可测试，但覆盖不了千变万化的自然表达（"用 MCP 工具问一下"就是补了 +又补的例子）。v0.2 增加一次**轻量模型分类**：让模型直接输出结构化路由 JSON， +解析失败/超时/非法输出时**自动回退 A 节的规则**。规则实现一行没删，它是兜底。 + +### C1. 决策记录 RouteDecision（dataclass） +```python +@dataclass +class RouteDecision: + strategy: Strategy # 四种策略之一 + source: str # "llm"（模型分类）或 "rules"（规则，含兜底） + reason: str # 人话理由，随事件流给用户/评委看 + tier: str = "standard" # 建议模型档位：standard 便宜快 / strong 给规划等重活 +``` +- 规则路径以前只返回一个 `Strategy` 枚举，现在统一返回 `RouteDecision`—— + **每个决策都带来源、理由、档位**，对应红线"每个自适应决策必须发事件、禁止静默决策"。 +- `classify()`（同步，返回枚举）保留给外部兜底调用；内部新增 `_rules()` 返回完整记录。 + +### C2. 规则路径改造 `_rules()` +原来 `classify` 里的每个 `return Strategy.X` 都换成 +`return RouteDecision(Strategy.X, "rules", "理由", 档位)`，判定顺序与条件完全不变； +`classify()` 变成一行：`return self._rules(task, registry).strategy`。 +注意 plan 分支带 `"strong"`：多步规划是重活，建议用强模型（见 06 篇 `_make_plan`）。 + +### C3. 异步入口 `aclassify()`——短路、尝试、兜底 +```python +async def aclassify(self, task, registry) -> RouteDecision: + text = task.strip() + if not text or self.model is None or len(registry) == 0: + return self._rules(task, registry) # 三种情况不浪费模型调用 + try: + raw = await asyncio.wait_for( + self._llm_classify(text, registry), timeout=self.classify_timeout) + return self._parse(raw, registry) + except Exception as exc: # 网络/超时/JSON 非法/策略越界 + fallback = self._rules(task, registry) + fallback.reason = f"LLM 分类失败（{type(exc).__name__}），回退规则：{fallback.reason}" + return fallback +``` +- **三个短路条件**：空任务（必澄清）、没配模型（纯规则部署）、宿主无工具（必 direct）—— + 能力边界判断永远在本地，不花一次模型调用，也不会被模型带偏。 +- `asyncio.wait_for` 给分类加硬超时（默认 15s）：路由是主流程的第一道关，不能卡死。 +- `except Exception` 兜底一切：**分类是增强而不是依赖**。失败理由里写清异常类型， + 事件流里能直接看到"这次为什么走了规则"。 + +### C4. 分类调用 `_llm_classify()` +```python +prompt = ("你是嵌入式 Agent 的任务路由器。……只输出一个 JSON 对象……\n" + '{"strategy": "direct|react|plan|clarify", "tier": "standard|strong",' + ' "reason": "不超过30字的中文理由"}\n' + "策略判定标准：……\n宿主可用工具：\n{逐行 name: description}\n任务：{task}") +resp = await self.model.achat(messages, tools=None, tier="standard") +``` +- `tools=None`：分类轮**不给工具清单的 function-calling 形式**，而是把工具的 + name/description 以文本列进提示词——分类只需要"看得懂有什么能力"，不调工具。 +- 固定 `tier="standard"`：路由本身用最便宜快的模型/档位，成本一次调用、几十 token。 +- 走的还是 SPI 的 `ModelProvider.achat`：DeepSeek、离线假模型、未来的本地模型一视同仁。 + +### C5. 解析与校验 `_parse()` +```python +fenced = re.search(r"\{.*\}", text, flags=re.DOTALL) # 容忍 ```json 围栏与前后啰嗦 +data = json.loads(fenced.group(0)) +if data["strategy"] not in {s.value for s in Strategy}: + raise ValueError(...) # 非法策略 -> 触发兜底 +if len(registry) == 0 and strategy in (REACT, PLAN): + raise ValueError(...) # 模型让调不存在的工具 -> 兜底 +tier = data.get("tier", "standard") +if tier not in ("standard", "strong"): + tier = "standard" # 档位非法：降级而不是报错 +``` +- 用"截取第一个 `{` 到最后一个 `}`"容忍模型套代码块或说客套话（实测常见）。 +- **校验而不是信任模型输出**：策略值必须是四枚举之一；无工具却选工具策略直接判非法； + 只有档位字段采取"非法即归一化"的宽容策略（它不影响安全，只影响成本）。 + +### C6. 接线：AgentCore 开关 + Loop 事件 +- `AgentCore(..., llm_router=False)`：默认关闭（零额外调用、离线测试完全确定）； + 开启时构造 `AdaptiveRouter(model=model)`，把同一个模型后端注入路由器。 +- `AgentLoop.astream` 改为 `decision = await self.router.aclassify(...)`， + `STRATEGY_SELECTED` 事件数据从 `{"strategy"}` 扩成 + `{"strategy","source","reason","tier"}`（strategy 键保留，老断言不破）。 +- `_make_plan(..., tier=decision.tier)`：规划轮的模型档位由路由决策建议， + 规则路由的 plan 默认 strong，LLM 路由可按需给 standard。 + +### C7. 实测（DeepSeek） +- "你好，简单介绍一下你自己" → `direct / llm / "闲聊自我介绍，无需调用工具"`； +- "搜索笔记里关于比赛的内容并总结" → `react / llm / "搜索笔记即可，单步工具调用"`； +- 分类输出乱码/超时时自动回退规则，事件 reason 以"LLM 分类失败（…），回退规则："开头。 + +## 两个文件如何协作 + +Loop 开始时： +1. `await router.aclassify(任务, 注册表)` → 得到 RouteDecision（LLM 或规则兜底）； +2. `Context(系统提示词)` → 建消息本； +3. 之后每轮模型回复、工具结果都 `ctx.add(...)`，超预算自动压缩； +4. 每次调模型前 `ctx.llm_messages()` 取最新快照。 + +## 自检 + +1. classify 的四个 if 顺序能不能调换？为什么"没有工具"必须排在前面？ +2. "随便帮我写个周报框架，要包含本周进展和下周计划"会被路由成什么？为什么？ +3. `_compact` 为什么从下标 1 开始、且保留最后一条？ +4. 给 `_ACTION_HINTS` 加一个你常用的动词，并在 `tests/test_router.py` 加对应测试。 +5. LLM 分类失败有哪几种情况？代码分别在哪里兜底？为什么兜底理由要写进事件？ +6. 分类轮为什么 `tools=None`、tier 固定 standard？ +7. 模型返回 `{"strategy":"react"}` 但宿主一个工具都没有，怎么走？为什么？ +8. `llm_router` 为什么默认关闭？哪些部署形态会希望它关着？ diff --git a/submissions/mcp-hackathon/yai-agent-core/source/docs/walkthrough/06-loop.md b/submissions/mcp-hackathon/yai-agent-core/source/docs/walkthrough/06-loop.md new file mode 100644 index 0000000..ee9cfff --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/docs/walkthrough/06-loop.md @@ -0,0 +1,213 @@ +# 逐行讲解 06 · `kernel/loop.py`：Core 的心脏（最重要，慢读） + +> 建议配合断点读：在 `astream`、`_react_cycle` 里设断点，跑 `scripts/smoke_test.py` 看每一步。 +> 知识点：异步生成器、`yield` 事件流、async for、递归重入、ReAct 循环、消息角色闭环。 + +## 块 1 · 系统提示词模板（L27-L33） +```python +_SYSTEM_TEMPLATE = """你是运行在宿主软件内部的 AI 助手。\ +你只能通过"工具"操作宿主的能力，不要编造工具不存在的数据。\ +当任务完成时，直接给出可交付的最终结果。 + +宿主当前提供的能力： +{tools} +""" +``` +- 这是发给模型的"人设与规矩"。`{tools}` 占位符运行时被 `registry.describe()` 替换。 +- 行尾反斜杠 `\` 表示字符串里不换行（三句人设连成一段），空行才真正分段。 + +## 块 2 · 构造（L36-L54） +```python +def __init__(self, model, registry, executor, channel, memory, + router: AdaptiveRouter | None = None, *, max_iters: int = 6) -> None: + ... + self.router = router or AdaptiveRouter() + self.max_iters = max_iters +``` +- 五大依赖全部注入。`router or AdaptiveRouter()`：调用方没给就用默认款（`None or x` 结果是 x，这是常见的默认值惯用法）。 +- `max_iters=6`：工具循环最多 6 轮，**防止模型反复调工具停不下来**（失控保护）。 + +## 块 3 · astream：总调度（L56-L92） + +```python +async def astream(self, task: str) -> AsyncIterator[AgentEvent]: +``` +- 关键语法：`async def` + 函数体内有 `yield` = **异步生成器**。调用它得到一个"异步事件流"，外部用 `async for event in core.astream(...)` 逐个取事件。好处：任务还在跑，UI 就能实时显示"正在调工具…"，而不是干等 30 秒拿一个最终结果。 + +```python + decision = await self.router.aclassify(task, self.registry) + strategy = decision.strategy + yield AgentEvent(EventType.STRATEGY_SELECTED, { + "strategy": strategy.value, "source": decision.source, + "reason": decision.reason, "tier": decision.tier}) +``` +- 第一步决策策略，立刻"喊出来"（发事件）。`aclassify` 是 v0.2 的异步入口： + 配置了 LLM 路由就先模型分类、失败回退规则，返回带 `source/reason/tier` 的 RouteDecision + （见 05 篇 C 节）；事件里保留 `strategy` 键，老的消费方不受影响。 + +```python + if strategy == Strategy.CLARIFY: + yield AgentEvent(EventType.CLARIFY_REQUESTED, {"question": task}) + answer = await self.channel.ask(task) + async for ev in self.astream(answer): + yield ev + return +``` +- 澄清分支：发事件 → 通过 channel 问用户拿到回答 → **用回答重新调用自己**（递归重入，重新走一遍路由）→ 把内部流的事件继续往外 yield（`async for ... yield` 叫"代理转发"）→ `return` 结束本次。 + +```python + ctx = Context(_SYSTEM_TEMPLATE.format(tools=self.registry.describe())) + for msg in self.memory.history(): + ctx.add(msg) + ctx.add(ChatMessage(role="user", content=task)) +``` +- 建消息本：system（含工具清单）→ 历史记忆 → 当前用户任务。 +- `str.format(tools=...)` 填充模板。 + +```python + if strategy == Strategy.PLAN: + async for ev in self._make_plan(ctx, task): + yield ev +``` +- plan 策略：先规划（额外一轮强模型调用），事件同样转发。 + +```python + # 计划只是"助手说过的话"，必须再推一把，模型才会进入工具执行； + # 否则真实模型会把计划本身当成最终答复（离线脚本模型曾掩盖此问题）。 + ctx.add( + ChatMessage( + role="user", + content="请按上面的计划逐步调用工具执行，拿到全部结果后给出最终汇报。", + ) + ) +``` +- **这是接真实模型后才暴露、离线测试没抓到的坑**（Day 1-3 修复）。 +- 拆完计划后，消息本最后两条是 `user：拆步骤指令 → assistant：计划文本`，对话停在"助手刚说完计划"。真实模型会认为轮次该结束了，于是把计划原文当最终答复，**一个工具都不调**。 +- 修复办法：补一条 user 消息明确下令"按计划执行"。这模拟了多轮对话里用户的追问，模型才会带着计划进入下面的 ReAct 循环。 +- 教训：**离线脚本模型（ScriptedModel）只会按剧本走，测不出"模型愿不愿意继续"这类问题**；关键路径必须用真实模型回归一次。 + +```python + final_text = "" + async for ev in self._react_cycle(ctx, use_tools=strategy != Strategy.DIRECT): + yield ev + if ev.type == EventType.MODEL_MESSAGE: + final_text = ev.data.get("text", final_text) +``` +- 进入主循环。`use_tools=strategy != DIRECT`：只有 react/plan 才把工具清单给模型；direct 首轮不给。 +- 一边转发事件，一边顺手记下最终文本（MODEL_MESSAGE 事件里）。`dict.get(k, 默认)` 找不到键时保留旧值。 + +```python + await self.memory.append_history(ChatMessage(role="user", content=task)) + await self.memory.append_history(ChatMessage(role="assistant", content=final_text)) + yield AgentEvent(EventType.DONE, {"strategy": strategy.value, "final_text": final_text}) +``` +- 收尾：把这一轮问答写进记忆，发 DONE 事件（携带最终结果）。 + +## 块 4 · _make_plan：先拆步骤（L94-L106） +```python +prompt = ("把下面的任务拆成 2-5 个可执行步骤，每行一个步骤，用 1. 2. 3. 编号，" + "只输出步骤本身：\n" + task) +ctx.add(ChatMessage(role="user", content=prompt)) +resp = await self.model.achat(ctx.llm_messages(), tools=None, tier="strong") +``` +- 拼一个"只做规划"的提示词，加进消息本。 +- `tools=None`：规划轮不许调工具，只输出文字。 +- `tier="strong"`：模型路由钩子，规划这种难活交给强模型。 + +```python +steps = [s.strip() for s in re.findall(r"\d+[.、)]\s*(.+)", resp.content)] +if not steps: + steps = [task] +plan_text = "\n".join(f"{i + 1}. {s}" for i, s in enumerate(steps)) +ctx.add(ChatMessage(role="assistant", content=plan_text)) +yield AgentEvent(EventType.PLAN_CREATED, {"steps": steps}) +``` +- 正则 `\d+[.、)]\s*(.+)` 匹配 "1. / 1、/ 1)" 开头的步骤行，`(.+)` 捕获步骤正文。 +- 模型没按格式输出时兜底：把整个任务当成唯一步骤，**绝不让空计划卡住流程**。 +- 把计划作为 assistant 消息放回消息本——这样后续工具循环"看得到自己刚定的计划"。 +- 发 PLAN_CREATED 事件，UI 可展示计划。 + +## 块 5 · _react_cycle：ReAct 工具循环（L108-L164） + +### 5.1 循环开头 +```python +tools_schema = self.registry.llm_schemas() if use_tools else None +for _ in range(self.max_iters): +``` +- 准备工具清单（direct 时为 None）。 +- `for _ in range(n)`：`_` 表示"这个循环变量我用不到"；最多 n 轮。 + +### 5.2 调模型，网络错误不崩 +```python +try: + resp = await self.model.achat(ctx.llm_messages(), tools=tools_schema) +except Exception as exc: + yield AgentEvent(EventType.ERROR, {"error": f"{type(exc).__name__}: {exc}"}) + return +``` +- 把当前消息本快照 + 工具清单发给模型。模型挂了（网络/Key/限流）就发 ERROR 事件并优雅结束，而不是抛栈崩溃。 + +### 5.3 模型不调工具 = 任务收尾 +```python +if not resp.tool_calls: + text = resp.content.strip() + ctx.add(ChatMessage(role="assistant", content=text)) + yield AgentEvent(EventType.MODEL_MESSAGE, {"text": text}) + return +``` +- 空列表/None 都算"没有工具调用"（`not []` 为 True）。 +- 模型给的自然语言就是最终答案：入消息本、发事件、`return` 结束循环。**循环的唯一正常出口在这里。** + +### 5.4 模型要调工具：先把"调用请求"记账 +```python +ctx.add(ChatMessage( + role="assistant", content=resp.content, + tool_calls=[{"id": tc.id, "type": "function", + "function": {"name": tc.name, + "arguments": json.dumps(tc.arguments, ensure_ascii=False)}} + for tc in resp.tool_calls], +)) +``` +- OpenAI 协议要求：assistant 发起工具调用时，要先以 assistant 角色把调用记录原样放回消息历史，否则下一轮会报"tool_call 找不到对应 assistant 消息"。 +- 注意 `arguments` 要序列化成 **JSON 字符串**（协议要求字符串，不是对象）。 + +### 5.5 逐个执行并把结果回填 +```python +for call in resp.tool_calls: + tool_events, ok, result_text = await self.executor.execute(call.name, call.arguments) + for tool_event in tool_events: + yield tool_event + ctx.add(ChatMessage(role="tool", content=result_text, + tool_call_id=call.id, name=call.name)) +``` +- 模型可能一轮要多个工具，逐个执行。 +- executor 返回的事件逐个转发（TOOL_CALL/TOOL_RESULT/PERMISSION_ASKED）。 +- **关键闭环**：每个工具结果以 `role="tool"` 消息放回消息本，并用 `tool_call_id` 对应到是哪次调用。下一轮模型就能"看到"工具返回了什么，再决定继续调还是收尾。 + +### 5.6 迭代上限兜底（L156-L164） +```python +# for 循环正常跑完（6 轮都在调工具、没收尾）才会走到这里 +ctx.add(ChatMessage(role="user", + content="已达到工具调用上限，请基于已有结果直接给出最终答案。")) +resp = await self.model.achat(ctx.llm_messages(), tools=None) +yield AgentEvent(EventType.MODEL_MESSAGE, {"text": resp.content.strip()}) +``` +- 如果 6 轮都没结束，强制再问模型一次且**不给工具**（想调也没得调），逼它基于已有观察交答案。这保证 run 一定会终止。 + +## 一张时序表（react 两轮的消息本变化） + +| 时刻 | 消息本内容（角色：内容） | +|---|---| +| 开始 | system：人设+工具清单 → user：任务 | +| 第1轮模型返回工具调用 | + assistant：我要调 search_notes | +| 执行后 | + tool：工具返回的 JSON | +| 第2轮模型给最终答案 | + assistant：最终自然语言 → MODEL_MESSAGE，结束 | + +## 自检（这篇必须全懂再往下） + +1. 异步生成器和普通 async 函数的区别？为什么 Agent 过程适合"边跑边 yield"？ +2. clarify 分支是怎么重新进入路由的？ +3. 为什么 assistant 的 tool_calls 和 tool 结果都必须写回消息本？缺了 tool_call_id 会怎样？ +4. 循环有哪三个出口？（正常收尾 / 错误 / 上限兜底） +5. direct 策略下 `tools_schema` 是什么？模型此时还能调工具吗？ +6. 为什么 plan 拆完步骤后必须再补一条 user 消息？离线脚本模型为什么没暴露这个问题？ diff --git a/submissions/mcp-hackathon/yai-agent-core/source/docs/walkthrough/07-defaults.md b/submissions/mcp-hackathon/yai-agent-core/source/docs/walkthrough/07-defaults.md new file mode 100644 index 0000000..30991f9 --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/docs/walkthrough/07-defaults.md @@ -0,0 +1,131 @@ +# 逐行讲解 07 · 默认实现：memory / policy / channels + +> SPI 只定契约，这四个文件是"开箱即用的默认款"。都很短，合在一起讲。 +> 知识点：默认实现与接口解耦、防御性拷贝、asyncio.to_thread、字典映射替代长 if。 + +## A. `memory/inmemory.py`：内存记忆 + +```python +class InMemoryStore: + def __init__(self) -> None: + self._history: list[ChatMessage] = [] + self._kv: dict[str, str] = {} +``` +- 两个私有容器：历史消息列表、键值小仓库。全在内存里，进程退出即清空——v0.1 够用，v2 换 SQLite 实现同一套方法即可持久化。 + +```python +async def append_history(self, message: ChatMessage) -> None: + self._history.append(message) + +def history(self) -> list[ChatMessage]: + return list(self._history) +``` +- 追加是 async（为了和 SPI 契约一致，将来换成数据库时本来就要 await）。 +- `history()` 返回 `list(...)` 浅拷贝：外部遍历/改这份列表不会动到内部存储。 + +```python +async def put(self, key, value) -> None: + self._kv[key] = value + +async def get(self, key) -> str | None: + return self._kv.get(key) + +async def clear(self) -> None: + self._history.clear() + self._kv.clear() +``` +- KV 读写；`dict.get` 找不到返回 None；clear 同时清空两块。 +- **对照 SPI 看**：方法签名和 `spi/memory.py` 一一对应，但不需要继承——这就是第 02 篇说的结构化子类型。 + +## B. `policy/allowlist.py`：白名单权限 + +```python +def __init__(self, allowed: Iterable[str] = (), *, mode: str = "auto") -> None: + self.allowed = set(allowed) + self.mode = mode +``` +- `allowed` 白名单；转成 `set` 让"是否在白名单"的判断 O(1)。 +- 默认参数用不可变的空元组 `()` 而不是空列表/集合（可变默认参数坑，和 dataclass 那条同理）。 +- 三种模式：`auto`（白名单放行，其余询问）、`allow_all`（全自动，演示/测试用）、`deny_all`（默认拒绝，最保守）。 + +```python +async def check(self, tool_name: str, arguments: dict) -> PermissionDecision: + if tool_name in self.allowed: + return PermissionDecision.ALLOW + if self.mode == "allow_all": + return PermissionDecision.ALLOW + if self.mode == "deny_all": + return PermissionDecision.DENY + return PermissionDecision.ASK +``` +- 决策顺序：白名单优先（任何模式下都放行）→ 再看模式 → auto 兜底返回 ASK。 +- 在 `core.py` 里，`auto_approve_tools=True`（默认）会选 `allow_all`，让你本地跑 demo 不被确认打断；做真实产品时关掉它走 ASK。 + +## C. `channels/collect.py`：收集通道（测试/API 用） + +```python +class CollectChannel: + def __init__(self, *, auto_confirm: bool = True, default_answer: str = "") -> None: + self.events: list[AgentEvent] = [] + self.auto_confirm = auto_confirm + self.default_answer = default_answer + + async def emit(self, event: AgentEvent) -> None: + self.events.append(event) + + async def ask(self, question: str) -> str: + return self.default_answer + + async def confirm(self, tool_name, arguments) -> bool: + return self.auto_confirm +``` +- 三个方法正好实现 SPI Channel：emit 把事件存进列表（事后可断言/可转 JSON）、ask 给预设回答、confirm 给预设是否批准。 +- **它为什么重要**：测试和 HTTP API 没有"真人"可问，必须有一个不交互、只记录的通道。`tests/test_loop.py` 断言事件序列、FastAPI Battery 返回事件数组，靠的都是它。 + +## D. `channels/cli.py`：终端通道（人看的） + +```python +_LABELS = { + EventType.STRATEGY_SELECTED: "策略", + EventType.PLAN_CREATED: "计划", + EventType.MODEL_MESSAGE: "回复", + EventType.TOOL_CALL: "调用工具", + ... +} +``` +- 用字典把事件类型映射成中文标签。**用字典查表代替一长串 if/elif**，是这段代码想让你学的手法。 + +```python +async def emit(self, event: AgentEvent) -> None: + label = _LABELS.get(event.type, event.type.value) + if event.type == EventType.TOOL_CALL: + print(f" [{label}] {event.data['tool']}({event.data['arguments']})") + elif event.type == EventType.STRATEGY_SELECTED: + print(f" [{label}] {event.data['strategy']}") + elif event.type == EventType.MODEL_MESSAGE: + print(f" [{label}] {event.data.get('text', '')}") + else: + print(f" [{label}] {event.data}") +``` +- 不同事件 data 结构不同，所以分三种定制打印，其余直接打印字典。 +- `data['tool']`（确定有键，缺了是 bug 该报错）vs `data.get('text','')`（可空，给默认）——**两种取值方式的选择体现你对数据是否必填的判断**。 + +```python +async def ask(self, question: str) -> str: + return await asyncio.to_thread(input, f" [澄清] {question} > ") +``` +- **重点难点**：`input()` 是阻塞函数，会卡住整个事件循环！`asyncio.to_thread(input, 提示)` 把它丢到另一个线程执行，await 其结果，既保留同步输入体验又不阻塞异步循环。confirm 同理。 +- `answer.strip().lower() in ("y","yes","是")`：去空白、转小写再判断，兼容 `Y / yes / 是`。 + +## 四个默认款的共同设计套路 + +1. 都实现 SPI 协议但不继承它； +2. 构造零参数或带安全默认值，做到"装上就能跑"； +3. 需要真人/外部系统的地方留好替换点（channel.ask/confirm）。 + +## 自检 + +1. 为什么 `history()` 要返回拷贝？直接 `return self._history` 有什么风险？ +2. 默认参数为什么写 `allowed=()` 而不是 `allowed=[]` 或 `set()`？ +3. 为什么不能在 async 函数里直接调 `input()`？`asyncio.to_thread` 解决了什么？ +4. 试着写一个只打印 TOOL_CALL 事件、忽略其他事件的 QuietChannel，接进 AgentCore 跑一次。 diff --git a/submissions/mcp-hackathon/yai-agent-core/source/docs/walkthrough/08-model-and-core.md b/submissions/mcp-hackathon/yai-agent-core/source/docs/walkthrough/08-model-and-core.md new file mode 100644 index 0000000..0af6cb8 --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/docs/walkthrough/08-model-and-core.md @@ -0,0 +1,164 @@ +# 逐行讲解 08 · `llm/openai_compat.py` 与 `core.py` + +> 前者把"任意 OpenAI 兼容模型"插进 ModelProvider 插槽；后者是宿主认识的唯一门面。 + +## A. `llm/openai_compat.py`：真实模型适配 + +### A1. 懒加载第三方库（L13-L33） +```python +def __init__(self, *, api_key=None, base_url=None, model=None, strong_model=None): + try: + from openai import AsyncOpenAI + except ImportError as exc: + raise ImportError( + "使用 OpenAICompatProvider 需要安装可选依赖：uv pip install -e '.[llm]'" + ) from exc +``` +- **import 写在方法内部 = 懒加载**：只有真正实例化模型时才要求装 openai。这样内核在"没装 openai、只用离线假模型"时也能 import、能测试——零硬依赖原则的落地。 +- `raise ... from exc`：保留原始错误链（caused-by），调试时能看到根因。 +- `AsyncOpenAI`：openai 库的异步客户端，和我们全异步的 Loop 配套。 + +```python +self.client = AsyncOpenAI( + api_key=api_key or os.getenv("OPENAI_API_KEY", "missing"), + base_url=base_url or os.getenv("OPENAI_BASE_URL"), +) +self.model = model or os.getenv("LLM_MODEL", "deepseek-chat") +self.strong_model = strong_model or os.getenv("LLM_STRONG_MODEL") or self.model +``` +- 参数优先，其次读环境变量（`.env` 里配置），再给默认值。`A or B or C` 链式兜底再次出现。 +- **为什么换个 base_url 就能接 DeepSeek/通义**：它们都提供 OpenAI 兼容接口，请求格式一样，只是地址和模型名不同。这就是"模型无关"。 + +### A2. achat：内部消息 → 厂商请求（L35-L49） +```python +async def achat(self, messages: list[dict[str, Any]], + tools: list[dict[str, Any]] | None = None, *, tier="standard"): + # messages 由 Context.llm_messages() 产出，已经是 OpenAI 线格式 dict + kwargs: dict[str, Any] = { + "model": self.strong_model if tier == "strong" else self.model, + "messages": messages, + } + if tools: + kwargs["tools"] = tools + kwargs["tool_choice"] = "auto" +``` +- 根据 tier 选模型：规划用强模型，平时用普通模型（省钱/快）。 +- **消息在这里只透传、不转换**：`Context.llm_messages()` 已经把内部 `ChatMessage` 逐个 `to_llm_dict()` 转成了 OpenAI 线格式 dict（见第 05 篇），Provider 直接转发即可。这里最初多写了一层 `to_llm_dict()`，对 dict 再调一次方法，真接 DeepSeek 必崩（Day 1-3 修复，离线假模块没暴露）——**格式转换只做一次，且在边界上做**。 +- 形参类型因此是 `list[dict[str, Any]]`：Provider 插槽面向"厂商线格式"，不认识内核的 ChatMessage 类。 +- 只有确实有工具时才传 tools，并设 `tool_choice="auto"`（让模型自行决定是否调用）。 + +```python +completion = await self.client.chat.completions.create(**kwargs) +msg = completion.choices[0].message +``` +- 真正的网络调用，await。返回结构里第 0 个 choice 的 message 就是模型回复。 + +### A3. 解析工具调用，抹平厂商形状（L54-L62） +```python +tool_calls: list[ToolCallRequest] = [] +for tc in getattr(msg, "tool_calls", None) or []: + try: + args = json.loads(tc.function.arguments or "{}") + except json.JSONDecodeError: + args = {} + tool_calls.append(ToolCallRequest(id=tc.id, name=tc.function.name, arguments=args)) +return ModelResponse(content=msg.content or "", tool_calls=tool_calls, raw=completion) +``` +- `getattr(msg, "tool_calls", None)`：属性可能不存在，安全取值；`... or []`：存在但为 None 时也变空列表。 +- 模型给的参数是 **JSON 字符串**，`json.loads` 解析成字典；模型偶尔会吐出非法 JSON，解析失败就用空字典兜底，不崩。 +- 最终统一返回我们自己的 `ModelResponse`——**厂商 SDK 的数据结构到此为止，不许泄漏进内核**，以后换厂商只改这一个文件。 + +## B. `core.py`：门面（Facade） + +### B1. 构造 = 把所有零件组装起来（L22-L47） +```python +def __init__(self, model, *, channel=None, memory=None, policy=None, + router=None, auto_approve_tools=True, llm_router=False): + self.model = model + self.registry = ToolRegistry() + self.channel = channel or CollectChannel() + self.memory = memory or InMemoryStore() + self.policy = policy or AllowlistPolicy( + mode="allow_all" if auto_approve_tools else "auto") + if router is not None: + self.router = router # 显式传入优先 + else: + self.router = AdaptiveRouter(model=model if llm_router else None) + self.executor = ToolExecutor(self.registry, self.policy, self.channel) + self._loop = AgentLoop(model=self.model, registry=self.registry, + executor=self.executor, channel=self.channel, + memory=self.memory, router=self.router) +``` +- 组装顺序：先建无依赖的注册表/默认组件 → 再建执行器（依赖注册表、策略、通道）→ 最后建 Loop（依赖全部）。**依赖顺序就是创建顺序。** +- 每个 SPI 都是"传了用你的，没传用默认款"。宿主可以只给一个 model，其他全自动。 +- `llm_router`（v0.2）：开启才把 model 注入路由器做模型分类（失败回退规则，见 05 篇 C 节）； + 默认关闭，离线测试与极简部署零额外模型调用。 +- `_loop` 下划线：外部不该直接操作发动机，走门面方法。 + +### B2. auto：一行接入（L51-L56） +```python +@classmethod +def auto(cls, host: object, model: ModelProvider, **kwargs: object) -> AgentCore: + core = cls(model, **kwargs) + core.register_tools(discover(host)) + return core +``` +- `@classmethod` + 第一个参数 `cls`：这是"工厂方法"，`AgentCore.auto(...)` 内部先构造自己、再自动发现宿主能力并注册、返回装好的 core。 +- `**kwargs` 把 channel/policy 等自定义参数透传给构造函数，保持 auto 也能高度定制。 +- **这就是 YAI 的招牌三行**：`core = AgentCore.auto(宿主, 模型)` → 能力自动长出来。 + +### B3. 工具查看（L58-L65） +```python +def register_tools(self, specs): self.registry.register_many(specs) + +def list_tools(self): + return [{"name": s.name, "description": s.description, "source": s.source} + for s in self.registry.all()] +``` +- 手动补注册的入口（除 auto 外，也允许手工加工具）。 +- `list_tools` 返回精简字典（不含 handler 这种不能序列化的东西），供 `/v1/tools` API 直接吐 JSON。 + +### B4. 两种运行方式（L69-L91） +```python +async def astream(self, task: str) -> AsyncIterator[AgentEvent]: + async for event in self._loop.astream(task): + await self.channel.emit(event) + yield event +``` +- 流式：转发 Loop 事件的**唯一出口**，并在这里统一 `channel.emit`。注意第 04 篇重构后，Executor 不再自己发事件，所有事件都从这条路径经过——**全项目事件流只有一条路径**，便于排查。 + +```python +async def run(self, task: str) -> RunResult: + events, final_text, strategy = [], "", None + async for event in self.astream(task): + events.append(event) + data = event.data + if "strategy" in data: + from yai_core.types import Strategy + strategy = Strategy(data["strategy"]) + if event.type.value == "done": + final_text = data.get("final_text", "") + return RunResult(strategy=strategy or self.router.classify(task, self.registry), + events=events, final_text=final_text) +``` +- `run` 是"懒人版"：内部消费 astream，把事件攒起来，最后打包成 RunResult。 +- 从事件数据里反推策略；兜底再 classify 一次（防御）。 +- 函数内 import Strategy 只是为了避免顶部循环导入的写法，你也可以放到顶部（这里没有真正的环，后续可简化）。 + +## 两条接入路径对比 + +```python +# 路径 1：要实时过程（CLI/Web SSE/Flutter 流式 UI） +async for ev in core.astream(task): # 边跑边渲染 + +# 路径 2：只要最终结果（脚本/HTTP 普通响应） +result = await core.run(task) # result.final_text / .events +``` + +## 自检 + +1. openai 为什么在 `__init__` 里才 import？顶层 import 会破坏什么？ +2. DeepSeek、通义千问为什么能用同一个 Provider？要改哪几个配置？ +3. ChatMessage → 厂商 dict 的转换发生在哪一层？为什么 Provider 里不能再转一次？ +4. `AgentCore.auto` 内部按什么顺序组装零件？ +5. `run` 和 `astream` 分别适合什么场景？为什么说事件流只有一条路径？ diff --git a/submissions/mcp-hackathon/yai-agent-core/source/docs/walkthrough/09-battery.md b/submissions/mcp-hackathon/yai-agent-core/source/docs/walkthrough/09-battery.md new file mode 100644 index 0000000..0bb3234 --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/docs/walkthrough/09-battery.md @@ -0,0 +1,154 @@ +# 逐行讲解 09 · `batteries/fastapi_server/app.py`：把 Core 变成在线 API + +> Battery = 可选外围。内核不依赖 FastAPI；只有要部署成 HTTP 服务时才用它。 +> 知识点：可选依赖的导入守卫、Pydantic 请求模型、闭包捕获、路由装饰器、JSON 安全序列化。 +> 配套启动示例：`scripts/serve_example.py`。 + +## 块 1 · 依赖守卫（L15-L21） +```python +try: + from fastapi import FastAPI + from pydantic import BaseModel +except ImportError as exc: + raise ImportError( + "FastAPI Battery 需要可选依赖：uv pip install -e '.[server]'" + ) from exc +``` +- 模块被 import 时就尝试引入 fastapi/pydantic；没装就给出**可操作的安装提示**，而不是让用户面对一堆难懂的 traceback。 +- 注意：这个文件属于 Battery，允许依赖第三方；`yai_core` 内核文件（types/kernel/spi...）依然零硬依赖。边界要清楚。 + +## 块 2 · 请求体模型（L24-L25） +```python +class RunRequest(BaseModel): + task: str +``` +- Pydantic 模型：声明 HTTP 请求体长什么样。客户端 POST `{"task": "..."}`，FastAPI 自动校验：缺字段/类型错会直接返回 422，并把 JSON 转成 `req.task`。 +- **踩过的坑（真实记录）**：这个类最初写在 `create_app` 函数内部，FastAPI 无法把闭包里的模型识别成请求体，报 422 query 参数缺失。提到模块级后正常——所以框架的"魔法"也有边界，遇到怪错先怀疑作用域。 + +## 块 3 · create_app：工厂函数 +```python +def create_app(core: Any, lifespan: Any = None) -> FastAPI: + app = FastAPI(title="YAI Agent Core API", version="0.1.0", lifespan=lifespan) + commit = os.getenv("YAI_GIT_COMMIT", "dev") + slug = os.getenv("YAI_PROJECT_SLUG", "yai-agent-core") +``` +- **应用工厂**：传入一个已组装好的 core，返回一个 HTTP app。这样同一份代码可以挂不同宿主的 core。 +- `core: Any`：Battery 不反向依赖内核具体类型，避免循环依赖，也方便测试时传假 core。 +- commit/slug 从环境变量读，部署 X-Agent 时注入真实 pinned commit；本地缺省 "dev"。 +- 可选 `lifespan` 形参（v0.2 加）：把 FastAPI 的生命周期钩子（启动挂载外部 MCP、 + 关闭断开连接）留给宿主脚本注入，电池本身不认识 MCP——依赖方向仍然是"宿主 → 电池 → 内核"。 + 具体用法见第 10 章块 10。 + +## 块 4 · 四个路由（L33-L54） + +### 4.1 健康检查（X-Agent 硬门槛） +```python +@app.get("/health") +async def health() -> dict: + return {"status": "ok", "commit": commit} +``` +- `@app.get(...)`：路由装饰器，把 URL 和函数绑定。 +- 返回 dict，FastAPI 自动转 JSON。X-Agent 审核机就靠这个端点确认服务在线且 commit 与提交一致。 + +### 4.2 验证文件（X-Agent 硬门槛） +```python +@app.get("/.well-known/xagent-verification.json") +async def verification() -> dict: + return {"schemaVersion": 1, "slug": slug, "commit": commit} +``` +- 固定路径、固定字段（官方契约）。`/.well-known/` 是业界放站点元信息的惯例目录。 + +### 4.3 工具清单 +```python +@app.get("/v1/tools") +async def list_tools() -> list[dict]: + return core.list_tools() +``` +- 直接复用门面方法，把"自动发现了哪些能力"暴露出去，评委 curl 一下就能看到宿主能力集。 + +### 4.4 执行任务 +```python +@app.post("/v1/agent/run") +async def run_agent(req: RunRequest) -> dict: + result = await core.run(req.task) + return { + "strategy": result.strategy.value, + "final_text": result.final_text, + "events": [ + {"type": e.type.value, "data": _jsonable(e.data)} for e in result.events + ], + } +``` +- 请求体由 Pydantic 自动解析成 `req`。 +- `await core.run(...)`：异步框架配异步内核，一个进程就能并发处理多个请求。 +- 响应三部分：用了什么策略、最终结果、**全过程事件**（这是 YAI 的差异化：别的黑盒 API 只给结果，我们给可审计过程）。 +- 列表推导式逐个事件转成可 JSON 化的字典。 + +## 块 5 · JSON 安全兜底（L59-L63） +```python +def _jsonable(data: dict) -> dict: + out: dict[str, Any] = {} + for k, v in data.items(): + out[k] = v if isinstance(v, str | int | float | bool | list | dict | None) else str(v) +``` +- 事件 data 里可能混进枚举、异常对象等不能直接 json.dumps 的东西。 +- `isinstance(v, 白名单类型)`：是 JSON 原生类型就原样保留，否则 `str(v)` 转字符串，保证响应永远不会因为序列化失败而 500。 +- 这是"边界层做防御"的典型：内部可以灵活，对外输出必须规整。 + +## 块 6 · 怎么启动（对照 `scripts/serve_example.py`） +```python +core = AgentCore.auto(capabilities, _model) # 组装内核（有 Key 用真模型，否则离线模型） +app = create_app(core) # 包成 HTTP 应用 +``` +启动脚本还做了两件部署相关的小事： +- `load_dotenv()`：自动读项目根 `.env`（Key、base_url、slug 都在里面），不用手动 set 环境变量； +- `YAI_GIT_COMMIT` 留空时自动执行 `git rev-parse HEAD` 取 40 位 commit——本地直跑永远和当前代码同源。 + +本地直跑（**宿主机统一用 8001**；8000 是容器内端口，且本机 8000 可能被别的程序占用）： +```powershell +uv run uvicorn scripts.serve_example:app --host 127.0.0.1 --port 8001 +``` +然后： +```powershell +curl http://localhost:8001/health +curl -X POST http://localhost:8001/v1/agent/run -H "Content-Type: application/json" -d '{"task":"列出全部笔记"}' +``` + +## 块 7 · 容器化部署（对照 `Dockerfile` 与 `docker-compose.yml`） +端口约定：**容器内永远监听 8000**（Dockerfile 的 EXPOSE、HEALTHCHECK 都打 8000），宿主机映射 `8001:8000`。这样镜像可以原样部署到任何机器，宿主机端口冲突只改映射、不改镜像。 + +Dockerfile 的几个教学点： +```dockerfile +COPY --from=ghcr.io/astral-sh/uv:0.12.10 /uv /uvx /bin/ # 从官方 uv 镜像里直接拷二进制 +ARG YAI_GIT_COMMIT=dev +ENV YAI_GIT_COMMIT=${YAI_GIT_COMMIT} # 构建时把 pinned commit 烤进镜像 +ARG INDEX_URL=https://pypi.org/simple +ENV UV_INDEX_URL=${INDEX_URL} # 网络受限时构建参数换国内镜像源 +HEALTHCHECK ... CMD python -c "urllib 请求 /health ..." # 容器级健康检查，打同一个端点 +``` +- **commit 在构建时固化**：镜像里没有 `.git`（被 `.dockerignore` 排除），运行时取不到哈希，所以用 `--build-arg YAI_GIT_COMMIT=$(git rev-parse HEAD)` 在构建期注入。注意 `.env` 里不要留 `YAI_GIT_COMMIT=` 空行——空值会在运行时覆盖镜像里烤好的值。 +- `.dockerignore` 把 `.env`、`.venv`、`.git`、`docs/` 全部挡在镜像外：密钥不进镜像、镜像只装跑服务需要的东西。 +- 一键起：`docker compose up --build`（compose 经 `env_file: .env` 注入密钥）。 +- 踩坑记录：容器内访问官方 PyPI 会超时，构建时加 `--build-arg INDEX_URL=https://pypi.tuna.tsinghua.edu.cn/simple`；宿主机端口被占时换宿主端口（如 8002:8000），容器内 8000 不动。 +- **PaaS 平台的端口约定**：Render 这类平台不让你自己决定监听端口，它会注入 `PORT` 环境变量（Render 默认 10000），只把流量转发到容器的这个端口。所以 CMD 写成 shell 形式 `--port ${PORT:-8000}`：自管环境没有 `PORT` 就听 8000，上了平台自动听平台指定的端口。同理，平台还会注入"本次部署的 commit"（Render 是 `RENDER_GIT_COMMIT`），启动脚本按 `YAI_GIT_COMMIT → RENDER_GIT_COMMIT → git HEAD → dev` 的顺序解析，且只认完整 40 位哈希（镜像里烤的默认值 `dev` 不是合法哈希，会被自动跳过，平台注入的真实 SHA 才会生效——这是 Render 首部署时实测出来的坑），验证端点在任何环境都能报出真实版本。这就是"一次构建、处处可部署"的写法：**环境差异全部走环境变量，代码不写死。** + +## 一次 HTTP 请求的完整链路 +``` +客户端 POST /v1/agent/run + → Pydantic 校验请求体 + → core.run(task) + → Router 选策略 → Loop 跑 ReAct → Executor 调宿主函数 → 事件流 + → 结果经 _jsonable 规整 + → JSON 响应回客户端 +``` + +## 自检 + +1. 为什么 Pydantic 模型必须放模块级而不能放在 create_app 里？ +2. `/health` 里的 commit 为什么要从环境变量读，而不是写死？ +3. 为什么响应里要带 events？这对比赛评审意味着什么？ +4. `_jsonable` 防的是什么问题？删掉它、在事件 data 里放一个枚举会怎样？ +5. 把 host_c_companion 也包成一个 app（改 serve_example 即可），用 curl 跑通。 +6. 为什么 commit 要在构建镜像时用 ARG/ENV 固化，而不是容器启动后再读 git？ +7. 容器内端口为什么固定 8000、宿主机却映射 8001？端口冲突时该改哪一边？ +8. 部署到 Render 时为什么不需要改代码就能监听平台端口？`${PORT:-8000}` 这种写法叫什么、解决了什么问题？ diff --git a/submissions/mcp-hackathon/yai-agent-core/source/docs/walkthrough/10-mcp-client.md b/submissions/mcp-hackathon/yai-agent-core/source/docs/walkthrough/10-mcp-client.md new file mode 100644 index 0000000..b30eec4 --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/docs/walkthrough/10-mcp-client.md @@ -0,0 +1,333 @@ +# 逐行讲解 10 · `integrations/mcp/client.py`：把外部 MCP Server 的工具接进 Core + +> MCP（Model Context Protocol）是"工具界的 USB-C"：任何 MCP Server 暴露的工具， +> 任何 MCP Client 都能用同一套协议调用，不用为每个服务写专用对接代码。 +> 本章实现的是 **MCP Client**（我们去用别人的工具）；v0.1 红线明确不做 MCP Server。 +> 知识点：可选依赖懒加载、协议适配层、闭包按值捕获、JSON Schema 清洗、 +> 三种传输（内存 / stdio / HTTP）、协议返回值归一。 +> 配套示例：`examples/host_d_mcp/`（自带一个本地 stdio 演示 Server）。 + +## 块 0 · 先搞清楚 MCP 在架构里的位置 + +``` +AgentCore + └── ToolRegistry ← 工具唯一注册表，里面的每张"身份证"都是 ToolSpec + ├── Native Tools ← 宿主自己的函数（discovery 自动发现） + ├── MCP Tools ← 本章：外部 MCP Server 的工具，被包成 ToolSpec + └── （未来）OpenAPI Tools +``` +关键思想只有一句：**MCP 工具在注册表里和本地函数长得一模一样**。Router、Loop、 +Executor、权限策略、事件流全部零改动——它们根本不知道工具在本机还是在远端。 +适配层只负责两件事：`list_tools` 把远端工具"翻译"成 ToolSpec；调用时把 +`call_tool` 的协议返回值"翻译"回普通返回值/异常。 + +MCP Python SDK（`pip install mcp`）2026 年已进入 **v2 稳定线**（v2.x），高层 API： + +```python +from mcp import Client, StdioServerParameters +from mcp.server import MCPServer # 写 Server 用，本章测试/示例会用到 + +async with Client(target) as client: # target 三种形态，见块 3 + tools = (await client.list_tools()).tools # 列工具 + result = await client.call_tool("add", {"a": 1, "b": 2}) # 调工具 +``` + +## 块 1 · 模块定位与零依赖红线（L1-L19） +```python +from dataclasses import dataclass, field +from typing import Any +from yai_core.types import ToolSpec +``` +- 本文件**顶层只 import 标准库和内核自己的 types**，没有 `import mcp`。 +- 内核红线：`pyproject.toml` 的 `dependencies` 永远为空；mcp 放在可选依赖组 + `mcp = ["mcp>=2.0,<3"]` 里，用户 `uv sync --extra mcp` 才有。 +- 这样做的好处：只想要本地工具的宿主（比如未来内嵌进 AMBRACE 的移动端） + 不会被 mcp 那一长串传递依赖（anyio/httpx/pydantic…）拖累体积。 +- 测试里有一条 AST 静态检查（`test_no_toplevel_mcp_import_keeps_kernel_dependency_free`）， + 用语法树保证谁都不能手滑在顶层 import mcp——**红线用测试守住，不靠自觉**。 + +## 块 2 · JSON Schema 白名单清洗（L22-L73） +```python +_SCHEMA_KEYS = frozenset({"type", "properties", "required", "items", "enum", ...}) + +def sanitize_schema(schema: Any) -> Any: + if isinstance(schema, dict): + cleaned: dict[str, Any] = {} + for key, value in schema.items(): + if key in ("properties", "$defs") and isinstance(value, dict): + cleaned[key] = {name: sanitize_schema(sub) for name, sub in value.items()} + elif key in _SCHEMA_KEYS: + cleaned[key] = sanitize_schema(value) + return cleaned or dict(_EMPTY_SCHEMA) + if isinstance(schema, list): + return [sanitize_schema(item) for item in schema] + return schema +``` +- MCP SDK 会从 Python 类型注解自动生成工具的入参 schema，但里面夹带实现私有键， + 实测形如 `{'title': 'echoArguments', 'properties': {'text': {'title': 'Text', ...}}}`。 + 个别 OpenAI 兼容接口对多余键敏感，喂给模型前递归只保留 JSON Schema 标准关键字。 +- **真实踩坑（测试先抓到的）**：第一版写成"所有键都过白名单"，结果连 + `properties` 里的**属性名**（如 `text`）也被删了——白名单只该作用于 schema + 关键字层，`properties`/`$defs` 的键是用户定义的名字，必须原样保留、只清洗值。 +- `cleaned or 空schema`：清洗后若为空（Server 没给 schema），给一个最小合法的 + `{"type":"object","properties":{}}`，别让下游拿到空 dict。 +- `frozenset`：不可变常量集合，查找 O(1) 且不会被任何代码改坏。 + +## 块 3 · 连接配置 McpServerConfig（L76-L93） +```python +@dataclass +class McpServerConfig: + alias: str + url: str | None = None # ① Streamable HTTP，部署形态 + command: str | None = None # ② stdio 子进程命令 + args: list[str] = field(default_factory=list) + env: dict[str, str] | None = None + prefix: str = "" # 工具名前缀，多 Server 重名时去重 + server: Any = None # ③ MCPServer 实例，内存直连（测试用） +``` +三种 target 对应 MCP 的三种接法： +1. **url**：`https://host/mcp`，跨网络调远端服务（X-Agent 生态里的 MCP 服务多是这种）； +2. **command+args**：SDK 帮你拉起一个本地子进程，通过 stdin/stdout 通信（stdio）。 + 好处是工具运行在独立进程，崩了不拖垮宿主；`env` 可以给它单独传密钥； +3. **server**：直接传 MCPServer 实例做内存直连，不起进程、不触网——**测试专用**， + 我们的离线测试全靠它，CI 里不需要任何网络。 +- `prefix`：两个 Server 都有 `search` 时，注册表会因重名报错；加 `"shop__"` 这类 + 前缀即可区分。注意前缀只改**本地注册名**，远端调用仍用原名（块 6）。 +- `field(default_factory=list)`：dataclass 里可变默认值不能写 `= []`（会被所有实例 + 共享，经典 Python 坑），必须用工厂函数。 + +## 块 4 · 协议返回值归一 _flatten_call_result（L95-L112） +```python +content = getattr(result, "content", []) or [] +if getattr(result, "is_error", False): + texts = [b.text for b in content if getattr(b, "text", None)] + raise RuntimeError("; ".join(texts) or "MCP 工具返回错误") +texts = [b.text for b in content if getattr(b, "text", None)] +if texts: + return "\n".join(texts) +structured = getattr(result, "structured_content", None) +if structured is not None: + return structured +return "" +``` +MCP `call_tool` 返回的 `CallToolResult` 有三种信息，实测（SDK v2.2）： +- `content`：内容块列表，文本块是 `TextContent`，取 `.text`。这是 MCP **面向 LLM 的 + 规范输出**，所以优先用它； +- `structured_content`：结构化结果。注意两个实测细节：普通 `return "字符串"` 会被 + 包成 `{'result': '...'}`，而返回 Pydantic 模型则直接展开成 dict； +- `is_error`：**蛇形命名**（不是协议 JSON 里的 isError），工具抛 ToolError 时 + SDK 不向客户端抛异常，而是返回 `is_error=True` + 错误文本块。 +- 归一策略：错误 → 抛 `RuntimeError`，交给 ToolExecutor 既有的"异常回灌模型"路径 + （和本地工具报错走同一条路）；正常 → 文本优先、结构化兜底、都没有给空串。 +- 全用 `getattr(..., 默认值)` 而不是直接取属性：对 SDK 小版本差异保持韧性。 + +## 块 5 · connect：懒加载、建连、列工具（L141-L154） +```python +async def connect(self) -> list[ToolSpec]: + try: + from mcp import Client, StdioServerParameters + except ImportError as exc: + raise ImportError( + "MCP 集成需要可选依赖：uv sync --extra mcp（或 pip install 'yai-agent-core[mcp]'）" + ) from exc + self._client = Client(self._build_target(StdioServerParameters)) + await self._client.__aenter__() + listed = await self._client.list_tools() + self._specs = [self._to_spec(tool) for tool in listed.tools] + return self._specs +``` +- **懒加载**：`from mcp import ...` 写在方法体内。没装 mcp 的环境导入本模块不报错， + 只有真正 `connect()` 时才提示安装命令——`raise ... from exc` 保留原始报错链。 +- `Client(target)` 是异步上下文管理器，我们要把连接存起来跨多次调用使用， + 所以不写 `async with`，而是手动 `__aenter__()`，配对 `aclose()` 里的 `__aexit__()`。 +- `list_tools()` 返回分页结果（`.tools` + `.next_cursor`）；v0.2 工具数量少，先取 + 首页，未来接大 Server 再补游标翻页（SDK 官方教程里有分页范式）。 +- 列表推导式把每个远端工具交给 `_to_spec` 翻译成 ToolSpec。 + +## 块 6 · _to_spec：一个远端工具 → 一张 ToolSpec（L168-L185） +```python +def _to_spec(self, tool: Any) -> ToolSpec: + remote_name = tool.name + local_name = f"{self.config.prefix}{remote_name}" + schema = sanitize_schema(getattr(tool, "input_schema", None)) or dict(_EMPTY_SCHEMA) + + async def handler(**kwargs: Any) -> Any: + result = await self._client.call_tool(remote_name, kwargs) + return _flatten_call_result(result) + + return ToolSpec(name=local_name, description=..., input_schema=schema, + handler=handler, source="mcp") +``` +- **闭包按值捕获**：`handler` 是异步闭包，`remote_name` 是 `_to_spec` 的局部变量， + 每次调用生成一个新闭包、各自记住自己的工具名。若图省事在循环体里用可变的 + 循环变量，所有闭包最后会指向同一个名字——这是闭包经典坑，这里天然避开。 +- 本地名可能带前缀，远端只认原名，所以闭包内部坚持用 `remote_name`。 +- `handler(**kwargs)`：Executor 调用规范就是"关键字参数展开"，和本地函数完全一致； + 返回值交回 Executor 统一 `json.dumps`（所以字符串结果会被 JSON 编码成带引号形式， + 这是既有契约，测试里用 `json.loads` 断言）。 +- `source="mcp"`：ToolSpec 早预留好的字段，`core.list_tools()` 会如实标注来源， + 评委一眼能看出哪些是外部生态工具。 + +## 块 7 · 生命周期与便捷函数（L134-L139、L187-L203） +```python +async def __aenter__(self) -> McpToolBridge: + await self.connect() + return self + +async def aclose(self) -> None: + if self._client is not None: + await self._client.__aexit__(None, None, None) + self._client = None + +async def attach_mcp_tools(registry, config) -> McpToolBridge: + bridge = McpToolBridge(config) + specs = await bridge.connect() + registry.register_many(specs) + return bridge +``` +- 两种用法：`async with McpToolBridge(cfg) as b:` 自动关连接；或手动 + `connect()/aclose()`（host_d 用后者，因为要在整个任务期间保持连接、任务结束才关）。 +- `aclose()` 幂等：关完置 `None`，重复调用不报错。 +- stdio 形态下 `aclose()` 会终止子进程——**不关掉就会在后台留孤儿进程**， + host_d 用 `try/finally` 保证任何退出路径都关。 +- `attach_mcp_tools` 是给宿主的一行流：建连 + 翻译 + 注册，返回 bridge 供稍后关闭。 + +## 块 8 · 演示 Server（`examples/host_d_mcp/demo_mcp_server.py`） +```python +from mcp.server import MCPServer +mcp = MCPServer("YAI-DemoTools") + +@mcp.tool() +def add(a: int, b: int) -> int: + """Add two integers and return the sum.""" + return a + b + +if __name__ == "__main__": + mcp.run() # 默认 stdio 传输：stdin/stdout 即 MCP 通道 +``` +- 写 MCP Server 简单到"类型注解 + docstring 即 schema"，不用手写 JSON Schema。 +- `mcp.run()` 默认走 stdio；也可以 `run("streamable-http", port=...)` 起 HTTP。 +- 这个文件同时是教学样本：未来你想把 AMBRACE 的能力开放给别的 MCP 宿主， + 照这个样子包一层即可（那是 v1 之后的事，v0.1 红线不做 Server）。 + +## 块 9 · 宿主接线（`examples/host_d_mcp/run.py`） +```python +def build_config(): + url = os.getenv("MCP_SERVER_URL") # ① 环境变量给 URL → HTTP + if url: return McpServerConfig(alias="remote", url=url) + command_line = os.getenv("MCP_SERVER_COMMAND") # ② 给命令 → stdio + if command_line: + parts = shlex.split(command_line, posix=(os.name != "nt")) + return McpServerConfig(alias="stdio", command=parts[0], args=parts[1:]) + return McpServerConfig(alias="demo-stdio", # ③ 缺省拉起自带演示 Server + command=sys.executable, args=[str(demo_server)]) + +bridge = await attach_mcp_tools(core.registry, build_config()) +try: + await stream(core, task, backend) +finally: + await bridge.aclose() +``` +- 同一份宿主代码，靠环境变量在 HTTP / stdio / 本地演示三种部署形态间切换， + 这就是"传输无关"的适配层价值。 +- `shlex.split` 把命令字符串切成 argv；Windows 下 `posix=False` 保留反斜杠路径。 +- host_d 还注册了一个本地函数 `host_label`：跑起来你会在工具列表里同时看到 + `native` 和 `mcp` 两种来源——统一注册表的直接证据。 +- 运行：`.venv/Scripts/python.exe examples/host_d_mcp/run.py`（需 `--extra mcp`）。 + +## 块 10 · 部署期接线：config_from_env 与 FastAPI lifespan（线上也能调 MCP） + +host_d 里"读环境变量 → 构造 config"的逻辑被收敛成可复用函数 `config_from_env`： + +```python +def config_from_env(*, alias="remote", + url_env="MCP_SERVER_URL", + command_env="MCP_SERVER_COMMAND", env=None): + environ = os.environ if env is None else env + if url := environ.get(url_env): + return McpServerConfig(alias=alias, url=url) # HTTP 形态 + if command_line := environ.get(command_env): + parts = shlex.split(command_line, posix=(os.name != "nt")) + if parts: + return McpServerConfig(alias=alias, command=parts[0], args=parts[1:]) + return None # 没配置 → None +``` +- `env=None` 时默认读 `os.environ`，测试时可传入假字典——纯函数、离线可测。 +- 返回 `None` 而不是抛异常：**"不接外部 MCP"是合法部署形态**，调用方据此决定跳过。 + +在线服务 `scripts/serve_example.py` 用 FastAPI 的 lifespan 在进程启停时挂载/断开： + +```python +@contextlib.asynccontextmanager +async def app_lifespan(_app): + bridges = [] + try: + from yai_core.integrations.mcp import attach_mcp_tools, config_from_env + if (cfg := config_from_env(alias="remote")) is not None: + try: + bridges.append(await attach_mcp_tools(core.registry, cfg)) + except Exception as exc: # 外部 Server 挂了是运行时常态 + print(f"[警告] 外部 MCP 挂载失败，仅提供本地工具：{exc}") + yield # ← 服务在这期间对外提供请求 + finally: + for bridge in bridges: + with contextlib.suppress(Exception): # 关闭阶段任何异常都不能拖住停机 + await bridge.aclose() + +app = create_app(core, lifespan=app_lifespan) +``` +> v0.2 持久化记忆落地后，app_lifespan 的 finally 段同时负责关闭 SqliteStore（探测式调用 close()），见第 11 章 G 节。 + +逐行要点： +- **优雅降级**：MCP 挂载失败只打印警告，native 工具、`/health`、验证端点照常服务。 + 外部依赖永远不能成为内核启动的单点——这是嵌入式内核的自我要求。 +- `contextlib.suppress(Exception)`：停机清理阶段"尽力而为"，连接早断了也不该抛栈。 +- `create_app(core, lifespan=...)`：battery 的 `create_app` 增加了可选 lifespan 形参， + 电池本身不认识 MCP，接线仍由宿主脚本决定（依赖方向不反转）。 +- 镜像侧：Dockerfile 的依赖安装改为 `.[server,llm,mcp]`；Render 侧 `render.yaml` + 增加普通环境变量 `MCP_SERVER_URL=https://mcp.deepwiki.com/mcp`（公共免鉴权 DeepWiki）。 + **接哪个 MCP Server 是部署期配置，代码一行不用改。** + +### 一次真实端到端（DeepSeek × DeepWiki MCP） + +设置 `MCP_SERVER_URL=https://mcp.deepwiki.com/mcp` 后跑 host_d，任务 +"用 MCP 工具问一下 GitHub 仓库 modelcontextprotocol/python-sdk：Client 初始化最小代码？"： +1. 第一次跑路由误判成 `direct`（不传工具清单），模型把工具调用写成了文本标签—— + 规则词表缺"问一下/工具/mcp"这类**显式工具意图**； +2. 给 `_ACTION_HINTS` 补词、拉丁词改大小写不敏感匹配，并在 `tests/test_router.py` + 加 3 条回归测试（见 05 篇 A1）； +3. 重跑：路由 `react` → DeepSeek 发出标准 function call → HTTP 调远程 + `ask_question` → 真实 wiki 内容回灌 → 模型产出中文结论与代码。 +这条链路（本服务 → LLM 规划 → Streamable HTTP MCP → 结果回灌 → 模型总结） +就是 X-Agent "MCP 产品化"评分项最硬的证据，且可被评审用 curl 复现。 + +## 测试策略（`tests/test_mcp_bridge.py` + `tests/test_battery_api.py`） +- 文件首行 `pytest.importorskip("mcp")`：最小安装（无 mcp extra）的环境整文件跳过， + 内核老测试照常全绿；CI 矩阵统一加装 `--extra mcp` 后这些用例才真正执行。 +- 用块 3 的第 ③ 种形态（内存 MCPServer 实例）测：文本工具、Pydantic 结构化工具、 + ToolError 错误工具各一个，不起子进程、不触网、毫秒级。 +- 端到端用例把 MCP 工具塞进真的 `ToolExecutor`（配 allow_all 策略 + CollectChannel）， + 验证成功路径的事件序列和失败路径的 `ok=False` 回灌——证明对 Loop 完全透明。 +- `test_config_from_env`：空环境返回 None、URL/命令两种形态的解析，纯函数离线覆盖。 +- `tests/test_battery_api.py::test_lifespan_attaches_mcp_tools`：用 TestClient 跑 + lifespan，内存 MCP Server 的工具必须出现在 `/v1/tools` 且 `source=="mcp"`， + 这是线上部署形态（块 10）的离线回放。 +- stdio 子进程路径、公共 HTTP MCP（DeepWiki）端到端在开发期用临时探针/示例实测， + 不进自动化测试，避免给 CI 引入网络与平台差异；实测步骤沉淀在本章块 10。 + +## 自检 + +1. 为什么 `import mcp` 必须写在 connect() 方法体内而不是模块顶层？哪条测试在守这条红线？ +2. sanitize_schema 第一版误删了工具属性名（如 text），根因是什么？为什么 properties + 的键不能过白名单？ +3. MCP 工具执行失败时，SDK v2 是抛异常还是返回 is_error？我们为什么要把它翻译成 + RuntimeError 再抛一次？ +4. `handler` 闭包为什么用 `_to_spec` 的局部变量 remote_name，而不是直接用注册名？ + 如果两个 Server 都有 search 工具，prefix 怎么配、远端收到的是哪个名字？ +5. MCP 的三种连接 target 分别是什么？为什么测试选内存直连？ +6. 为什么 host_d 要用 try/finally 调 aclose？不关掉 stdio 形态会留下什么？ +7. 让 host_d 改接一个 HTTP 形态的 MCP Server，需要改代码吗？要改什么？ +8. 本章新增的代码，哪些属于"内核零依赖"范围，哪些属于可选集成？边界由什么机制保证？ +9. 线上服务启动时外部 MCP Server 不可达，为什么不能让服务启动失败？代码怎么实现降级？ +10. "用 MCP 工具问一下……"第一次被路由成 direct 导致什么现象？为什么规则兜底也必须 + 覆盖显式工具意图？ diff --git a/submissions/mcp-hackathon/yai-agent-core/source/docs/walkthrough/11-sqlite-memory.md b/submissions/mcp-hackathon/yai-agent-core/source/docs/walkthrough/11-sqlite-memory.md new file mode 100644 index 0000000..7530d34 --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/docs/walkthrough/11-sqlite-memory.md @@ -0,0 +1,180 @@ +# 逐行讲解 11 · SQLite 持久化记忆：把"便签本"换成"笔记本" + +> 对应文件：`src/yai_core/memory/sqlite_store.py`、`src/yai_core/spi/memory.py`。 +> 读前先读第 07 章（InMemoryStore）。本章只新增一个契约实现，**不改契约、不改 Loop**。 + +## A. 先回顾：记忆契约长什么样 + +`spi/memory.py` 五个方法（注意第 2 个是**同步**方法，其余是 async）： + +```python +async def append_history(self, message: ChatMessage) -> None # 追加一条历史 +def history(self) -> list[ChatMessage] # 取全部历史（同步） +async def put(self, key: str, value: str) -> None # KV 写 +async def get(self, key: str) -> str | None # KV 读 +async def clear(self) -> None # 清空 +``` + +Loop 只在两个地方碰记忆（`kernel/loop.py`）： + +1. 任务开始：`for msg in self.memory.history(): ctx.add(msg)` —— 把历史回放进上下文； +2. 任务结束：写 user、assistant 两条历史。 + +**关键认知：Loop 只认识契约，不认识具体实现。** 所以只要新类实现了这五个方法， +Loop、Core、三个 host 示例一行都不用改——这就是 SPI（插槽）的意义，也是本章最好的教学点。 + +## B. 为什么放 memory/ 而不是 integrations/ + +MCP 客户端放在 `integrations/`，因为它依赖第三方 `mcp` 包；SQLite 用的 `sqlite3` +是 Python 自带标准库，零依赖、零 extra，和 InMemoryStore 是同一层东西，所以放在 `memory/`。 +判断口诀：**要装第三方包才能用的能力进 integrations，标准库能力留在本体包。** + +## C. 表结构：两张表 + 一个版本号 + +```sql +CREATE TABLE IF NOT EXISTS history ( + id INTEGER PRIMARY KEY AUTOINCREMENT, -- 自增主键，顺序以它为准 + scope TEXT NOT NULL DEFAULT 'default', -- 会话/宿主隔离标签 + role TEXT NOT NULL, -- user/assistant/system/tool + content TEXT NOT NULL DEFAULT '', + tool_calls TEXT, -- ChatMessage.tool_calls 的 JSON 文本，无则 NULL + tool_call_id TEXT, + name TEXT, + created_at TEXT NOT NULL DEFAULT (CURRENT_TIMESTAMP) +); +CREATE INDEX IF NOT EXISTS idx_history_scope_id ON history(scope, id); -- 按会话取历史的常用路径 + +CREATE TABLE IF NOT EXISTS kv ( + scope TEXT NOT NULL DEFAULT 'default', + key TEXT NOT NULL, + value TEXT NOT NULL, + updated_at TEXT NOT NULL DEFAULT (CURRENT_TIMESTAMP), + PRIMARY KEY (scope, key) -- 复合主键：同会话内 key 唯一 +); + +PRAGMA user_version = 1; -- schema 版本，迁移钩子 +``` + +逐块解释： + +- **为什么顺序用 `id` 不用 `created_at`**：CURRENT_TIMESTAMP 精度到秒，同一轮任务 + 连续写两条消息可能同一秒，时间戳分不出先后；自增 id 严格递增。 +- **为什么 history 要建 `(scope, id)` 索引**：查询永远是"某 scope 的全部历史，按 id 排序"， + 索引前缀就是 scope，一次索引扫描拿完。 +- **KV 为什么是复合主键 `(scope, key)`**：不同会话允许有同名 key（比如都叫 "profile"）， + 单 key 主键会互相覆盖。 +- **为什么 tool_calls 用 TEXT 存 JSON**：SQLite 是动态类型但没有原生 list/dict； + ChatMessage 里只有 tool_calls 是结构化字段，`json.dumps/json.loads` 往返最简单。 +- **`IF NOT EXISTS`**：重复打开同一个库不报错，幂等初始化靠它。 + +### C1. 迁移钩子 user_version + +SQLite 内置一个整数 `PRAGMA user_version`，专门留给应用存 schema 版本： + +```python +version = int(conn.execute("PRAGMA user_version").fetchone()[0]) +if version == 0: # 全新数据库：建表并写版本号 + conn.executescript(_SCHEMA_SQL); conn.commit() +elif version > _SCHEMA_VERSION: # 未来版本：旧代码打开新库，直接拒绝，避免写坏 + raise RuntimeError(...) +# version == 当前版本：什么都不做 +``` + +以后表结构要改（v0.3 加列、加表），就在这里加 `if version == 1: ...迁移到 2` 的分支。 +**注意：PRAGMA user_version 不能用 ? 参数化，版本号必须是 SQL 字面量。** + +## D. 连接策略：线程、锁与 WAL + +```python +self._lock = threading.Lock() +self._conn = sqlite3.connect(db_path, check_same_thread=False) +self._conn.row_factory = sqlite3.Row +if not self._is_memory: + self._conn.execute("PRAGMA journal_mode=WAL") + self._conn.execute("PRAGMA synchronous=NORMAL") +``` + +- `check_same_thread=False`：sqlite3 默认禁止"在 A 线程建连、在 B 线程使用"， + 而 FastAPI/uvicorn 会把同步函数丢到线程池，不同请求可能落在不同线程。 + 关掉这个保护后，**互斥要自己负责**——所以每个方法体都在 `with self._lock:` 里。 +- `row_factory = sqlite3.Row`：查出来的行能用 `row["role"]` 按列名取值，比下标好读。 +- WAL（Write-Ahead Logging）：文件形态下读写不互相阻塞、崩溃更稳；内存库不需要。 + 副作用是产生 `-wal`/`-shm` 两个旁车文件，所以 `.gitignore`/`.dockerignore` 要忽略它们。 +- `synchronous=NORMAL`：WAL 模式下安全且更快。 + +### D1. 为什么 async 方法里直接跑同步 SQL（不引 aiosqlite） + +契约方法是 `async def`，但 sqlite3 是同步驱动。v0.2 的每次操作都是单条小事务 +（一行 INSERT / 主键点查），毫秒级返回，不会真的卡住事件循环；引入 aiosqlite 要多一个 +依赖、多一套连接生命周期，收益为零。**边界要记牢**：批量导入、长事务、高并发写场景 +才需要异步驱动或连接池，那时再换不迟——这是有意识的取舍，不是偷懒。 + +### D2. 为什么 history() 是同步的也要加锁 + +契约里 `history()` 不是 async（Loop 启动时直接 `for ... in history()`）。 +但它同样访问连接，而别的 async 方法可能正在别的线程里写——同步方法也要进同一把锁。 + +## E. 字段往返：最容易错的三个边界 + +```python +tool_calls = None if message.tool_calls is None else json.dumps(...) +``` + +| 情形 | 存进去 | 读回来 | +|---|---|---| +| `tool_calls=None`（普通消息） | NULL | None | +| `tool_calls=[{...}]`（工具调用消息） | JSON 文本 | list[dict] | +| `tool_calls=[]`（空列表） | `"[]"` | **[]，不是 None** | + +第三行是最容易写错的：`None` 和 `[]` 在 Python 里都是假值，图省事写 +`json.dumps(x) if x else None` 就会把空列表吞成 NULL，与 InMemoryStore（原样保留 []） +行为不一致，参数化对等测试会立刻红。`tool_call_id/name` 同理：None 存 NULL， +**空字符串按空字符串存**，不折叠。 + +## F. UPSERT 与 scope 语义 + +KV 覆盖写用 SQLite 的 UPSERT（需要 SQLite ≥ 3.24，Python 3.11+ 自带版本远高于此）： + +```sql +INSERT INTO kv(scope, key, value) VALUES (?, ?, ?) +ON CONFLICT(scope, key) DO UPDATE SET value = excluded.value, updated_at = CURRENT_TIMESTAMP +``` + +`excluded` 是"这次试图插入但撞了主键的值"的固定别名。 + +- `clear()` 只删**当前 scope** 的两张表行；一个文件可以装多个会话，互不干扰。 +- 需要多会话的宿主：构造多个 `SqliteStore(path, scope="user-a")` 实例，契约方法签名不变。 + +## G. 装配：from_env 与 lifespan 关闭 + +```python +@classmethod +def from_env(cls, env=None): + raw = (environ.get("YAI_DB_PATH") or "").strip() + return None if not raw else cls(raw) +``` + +- 返回 None 而不是抛异常："不持久化"是合法部署形态，`SqliteStore.from_env() or InMemoryStore()` + 一行完成回退，不配置环境变量时行为与改动前**完全一致**。 +- `env` 参数允许测试注入假字典，绝不碰真实 `os.environ`。 +- `close()` 不是契约方法（Protocol 里没有），所以 serve_example 用 + `getattr(_store, "close", None)` 探测式调用，InMemoryStore 没有这个方法就跳过。 + +## H. 诚实的边界（写进比赛材料也不心虚） + +1. **Render 免费层磁盘是临时的**：redeploy/休眠回收后文件丢失，要"永久记忆"得挂持久卷或 VPS； +2. **历史裁剪已落地、摘要归档未做**：Context 层有 24000 字符压缩兜底；持久层的条数上限/TTL + 已在 v0.3 落地（`memory/retention.py`，由宿主按 env 注入，见第 13 章），摘要归档仍列入后续规划； +3. **单 worker + 单文件**：多进程同时写一个文件可能 `database is locked`，v0.2 用 WAL+锁覆盖单进程场景； +4. **DB 里是用户对话**：不进 git、不进镜像、不进提交快照、日志不打印内容（启动只印路径）。 + +## 自检 + +1. 为什么 SqliteStore 放在 `memory/` 而 MCP 客户端放在 `integrations/`？ +2. `history()` 为什么是同步方法？为什么同步方法也要持锁？ +3. `tool_calls=[]` 落库再读出应该是什么？写错会怎样？ +4. `PRAGMA user_version` 的作用是什么？打开一个版本号更高的库会怎样？ +5. 为什么顺序按 `id` 而不是 `created_at`？ +6. `from_env()` 为什么返回 None 而不是给默认路径？ +7. 为什么 v0.2 不引入 aiosqlite？什么场景下才需要？ +8. 为什么 Loop / Core / 三个 host 示例不需要任何改动就能用上 SQLite 记忆？ diff --git a/submissions/mcp-hackathon/yai-agent-core/source/docs/walkthrough/12-openapi-discovery.md b/submissions/mcp-hackathon/yai-agent-core/source/docs/walkthrough/12-openapi-discovery.md new file mode 100644 index 0000000..b59e231 --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/docs/walkthrough/12-openapi-discovery.md @@ -0,0 +1,140 @@ +# 逐行讲解 12 · OpenAPI 发现：让任意 REST API 零适配变成工具 + +> 对应目录：`src/yai_core/integrations/openapi/`（spec.py / discovery.py / client.py）。 +> 读前先读第 10 章（MCP 桥）——本章与它同构，只是"外部能力"从 MCP Server 换成了 REST API。 + +## A. OpenAPI 是什么，为什么它能做"发现" + +OpenAPI（前身 Swagger）是 REST API 的**机器可读说明书**：一个 JSON/YAML 文件里写清楚了 +有哪些路径（paths）、每个路径支持哪些 HTTP 方法（operations）、要什么参数、请求体长什么样、 +怎么鉴权。主流后端框架（FastAPI、Spring、NestJS）都能自动导出它。 + +MCP 是"专门为 AI 工具设计的协议"；OpenAPI 是"互联网上已经存在几十年的 REST 世界的说明书"。 +YAI 两者都接：MCP 面向新一代工具生态，OpenAPI 面向存量的海量 REST API。**发现的含义**： +宿主只要给一个 spec 地址，Core 自动读出工具清单并注册，不用为每个 API 手写一个函数。 + +## B. 三个文件的分工（先记住这张图） + +```text +spec.py 载入（dict/文件/URL）→ 版本校验 → 内部 $ref 内联展开 → (spec, notes) +discovery.py 纯函数：spec + config → list[OperationPlan]（名字/入参/方法/路径/鉴权） +client.py 桥：connect() 串起前两步并生成 ToolSpec；handler 闭包负责真实 HTTP 调用 +``` + +和 MCP 桥一样：顶层不 import httpx/pyyaml（内核零硬依赖），全部在函数里懒加载， +缺依赖时报 `uv sync --extra openapi`。 + +## C. spec.py：载入、校验、$ref 展开 + +### C1. 三选一载入与版本闸 + +`load_spec` 按 `config.spec / config.path / config.url` 三选一：文件读字节（先查 +`max_spec_bytes` 体积闸），URL 用 httpx 拉取（测试时注入 MockTransport）；`.yaml/.yml` +或 content-type 含 yaml 才 import pyyaml，其余按 JSON 解析。然后两道版本闸： + +- 没有 `openapi` 字段但有 `swagger: 2.x` → 明确报错让用户先转 OpenAPI 3； +- 版本号不是 3 开头 → 报错（v0.2 不支持 3 之外的世界）。 + +### C2. $ref 是什么，为什么要展开 + +OpenAPI 复用结构靠 JSON Reference：`{"$ref": "#/components/schemas/Pet"}` 指向文档内 +另一个节点。模型看不懂 $ref，所以发现前要**内联展开**。`resolve_refs` 是一次带"展开栈"的 +递归遍历： + +- 内部引用（`#/` 开头）：沿 JSON Pointer 找到目标，深拷贝后递归展开； +- **循环引用**（Category.children.items 指回 Category）：如果当前 ref 已在展开栈里， + 说明绕成环了，停止展开、把 `{"$ref": ...}` 原样留下并记一条 note——否则无限递归； +- **外部引用**（指向另一个 URL/文件）：v0.2 不跨文档抓取，原样保留 + note； +- 3.1 允许 $ref 带兄弟键，内联后兄弟键覆盖同名属性。 + +notes 是这个模块的一贯设计：**遇到不完美的输入不静默、不崩溃，降级处理并留痕**， +启动日志打印给宿主看。 + +## D. discovery.py：operation → 工具 + +### D1. 工具命名（两条规则 + 去重） + +1. 有合法 `operationId`：驼峰转蛇形（listPets → list_pets）、非法字符变下划线、截 64； +2. 没有：用方法+路径合成（`GET /pets/{petId}` → `get_pets_pet_id`：去花括号、连字符转下划线、 + 驼峰转蛇形、全小写）。 +同一 spec 内撞名追加 `__2/__3` 并记 note；**跨来源（native/mcp/openapi）撞名不在这处理**—— +ToolRegistry.register 本来就直接报错，让宿主的 prefix 去解决。 + +### D2. 入参 schema 的合并（最需要细心的一段） + +工具的入参是一个扁平 JSON Schema（object），来源有三处： + +- **path 参数**（`in: path`）：OpenAPI 规定恒必填，强制进 required；调用时填进 URL 模板； +- **query 参数**（`in: query`）：按声明决定是否必填；header/cookie 参数 v0.2 直接忽略 + （不暴露给模型，避免模型伪造内部头）； +- **requestBody（application/json）**：schema 是 object 就**拍平合并**（Pet 的 id/name/category + 变成工具的顶层入参，required 并集去重保序）；是数组等非 object 类型就包成一个 `body` 入参。 + +每个子 schema 都过一遍 `sanitize_schema`（第 10 章已见过，本批次它归位到 `tools/schema.py`， +MCP 桥和 OpenAPI 桥共用）。 + +### D3. 过滤与截断 + +- `include_paths / exclude_paths`：按路径**前缀**白/黑名单（先白后黑）； +- `read_only=True`：只留 GET/HEAD——在线演示服务的安全闸，写操作不暴露到公网； +- `max_operations=40`：超出截断并记 note，防止一个巨型 spec 注册几百个工具撑爆系统提示词。 + +工具描述统一成 `[METHOD /path] summary description`，截 1000 字符——模型一眼知道这工具打哪。 + +## E. client.py：注册与执行 + +### E1. connect 做四件事 + +载入+展开（spec.py）→ 发现计划（discovery.py）→ 解析 base_url（override > servers[0]， +相对地址按 spec 的 URL 补全）→ 建 `httpx.AsyncClient` 并把每个 plan 闭包成 ToolSpec。 +同时做**鉴权审计**：oauth2/basic/mutualTLS 暂不支持，注册期只记 note（不阻断）。 + +### E2. 一次调用的完整路径（handler 闭包） + +```text +模型给出参数 kwargs + → _auth_for：按 security 挑方案（bearer→Authorization 头；apiKey→头/query）， + 令牌只从环境变量读，缺失在【调用期】抛错（注册期不报错，允许先发现后配钥） + → _build_path：path 参数 quote(safe="") 填模板（参数里的 / 也编码，防路径穿越） + → _build_query：query 参数组装；bool → true/false；list 交给 httpx 展开成重复键 + → _build_body：拍平型按 body_fields 重组 dict；包裹型取 body + → client.request(method, url, params, json, headers) + → 响应归一：204→""；非 2xx→RuntimeError（走工具错误事件通道）； + JSON content-type→.json()；文本超 max_result_chars(16000)→截断加 …[truncated] +``` + +为什么令牌缺失是**调用期**而不是注册期报错：发现是"看菜单"，调用才是"点菜"； +宿主可能先把工具清单展示出来，稍后才配置密钥。 + +### E3. 为什么用 httpx 而不是 requests + +- 全栈异步：handler 是 async 闭包，跑在 Loop 的事件循环里，不能用同步 requests 阻塞循环； +- `MockTransport`：测试可以不触网地断言 method/url/headers/body，这是选型的决定性理由； +- 同步拉 spec 用短生命周期的 `httpx.Client`（只在启动时跑一次），执行期统一 AsyncClient。 + +## F. 安全边界（写进比赛材料） + +1. 在线演示端点 `read_only=True` 硬编码，公网只暴露 GET/HEAD； +2. 令牌只从环境变量读，不进 spec、不进日志、不进事件； +3. path 参数全编码；非 2xx 不把响应体直接喂模型（抛错并截断 500 字符）； +4. 结果文本 16000 字符截断（对照 Context 24000 上限，给模型的工具结果不能反客为主）； +5. 不支持的鉴权方案显式记 note，绝不"假装支持"发匿名请求到需要鉴权的写接口 + （需要鉴权却没令牌 = 调用期 RuntimeError）。 + +## G. 测试怎么做到全程离线 + +所有 HTTP 都不真实发出：`httpx.MockTransport(handler)` 接收 request、返回预制 response， +还能在 handler 里**断言请求本身**（方法、路径、query 重复键、Authorization 头、JSON body）。 +spec 用仓库内 `tests/fixtures/petstore.min.json`（含 $ref、递归 schema、bearer/apiKey、404）。 +这就是"测试不触网"纪律在集成层的标准打法，和 MCP 桥用内存假 server 是同一个思想。 + +## 自检 + +1. 为什么 OpenAPI 发现能做到"零适配接入"？它依赖 spec 里的哪些信息？ +2. 循环 $ref 和外部 $ref 分别怎么处理？为什么不能一律递归展开？ +3. object 型 requestBody 和数组型 requestBody 生成的入参 schema 有什么不同？ +4. path 参数为什么强制必填？为什么 quote 要 `safe=""`？ +5. 令牌缺失为什么在调用期而不是注册期报错？ +6. read_only 过滤为什么是在线演示服务的硬要求？ +7. 为什么选 httpx？MockTransport 在测试里替代了什么？ +8. sanitize_schema 为什么从 mcp/client.py 归位到 tools/schema.py？ diff --git a/submissions/mcp-hackathon/yai-agent-core/source/docs/walkthrough/13-history-retention.md b/submissions/mcp-hackathon/yai-agent-core/source/docs/walkthrough/13-history-retention.md new file mode 100644 index 0000000..41c5277 --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/docs/walkthrough/13-history-retention.md @@ -0,0 +1,157 @@ +# 逐行讲解 13 · 历史保留策略：会"忘事"的记忆才跑得久 + +> 对应代码：`memory/retention.py`（新增）、`memory/inmemory.py`、`memory/sqlite_store.py`、 +> `kernel/context.py`（_compact 修复）。v0.3，opt-in：不配置环境变量时行为与旧版完全一致。 + +## A. 为什么需要裁剪：记忆只会涨，不会自己落 + +SQLite 记忆落地后出现一个新问题：`history` 表只增不减。Loop 每跑一轮就追加两条 +（user 任务 + assistant 最终答复，见 `kernel/loop.py` 末尾），下一轮启动时 +`for msg in self.memory.history()` 全量回放给模型。跑得越久： + +1. 每次请求的 token 越多，越慢越贵（评审期每一分钱都是 DeepSeek 额度）； +2. 超长上下文更容易触发模型的"注意力稀释"，答非所问； +3. 几个月前的陈旧对话永远占着上下文。 + +v0.3 给出两个 opt-in 开关：**条数上限**（`YAI_HISTORY_MAX_MESSAGES`）与 +**存活时间 TTL**（`YAI_HISTORY_TTL_SECONDS`）。默认都不开——"忘事"是策略， +不是内核该擅自做的决定。 + +## B. 最大的坑：不能按"第几条"硬删 + +OpenAI 兼容的对话接口要求消息序列合法，其中一条铁律： + +- `assistant` 消息带 `tool_calls`（"我要调工具"）之后，**必须**紧跟对应 `tool` 消息（工具结果）。 + +假设历史是这样（一轮任务里模型调了工具）： + +``` +user "查一下订单" +assistant tool_calls=[get_orders] ← 工具调用的发起 +tool "订单结果..." ← 必须跟在发起后面 +user "谢谢" +assistant "不客气" +``` + +如果按"只留最近 3 条"硬删，会从第 2、3 条之间切开：`tool` 留下了、它配对的 +`assistant(tool_calls)` 没了——这叫**孤儿 tool 消息**，发给 DeepSeek 直接 400。 + +所以裁剪边界必须落在**一轮的开头**。 + +## C. "轮"的定义（全章统一口径） + +一条 `role == "user"` 的消息，到下一条 user 消息之前，算**一轮**： + +``` +user ┐ 第 1 轮 +assistant ┘ +user ┐ 第 2 轮（含工具调用） +assistant(tool_calls) +tool ┘ +user ┐ 第 3 轮 +assistant ┘ +``` + +历史开头若有非 user 消息（理论上的边界情况），归入"第 0 轮"，与相邻轮同生共死。 +裁剪只在轮与轮之间下刀，任何一轮内部都不可切。 + +## D. retention.py：把"下刀位置"算成纯函数 + +两个 Store（内存/SQLite）的删除逻辑必须**逐字节一致**，所以边界计算抽成纯函数， +放在 `memory/retention.py`，存储实现只负责"取角色序列"和"按边界删"。 + +### D1. 条数裁剪 count_cut：边界向后对齐 + +```python +candidate = len(roles) - max_messages # 朴素切点 +k = _next_round_start(roles, candidate) # 从切点向后找第一个轮首 +``` + +6 条消息、上限 2 条：朴素切点 = 4，而 roles[4] 正好是 user → k=4，删 [0,4)， +留最后一轮。若朴素切点落在一轮中间（比如上限 3，切点=4 之前的 3 是 assistant）， +就**往后**退到这一轮结束后的下一个轮首——宁可少留，不可切轮。找不到后续轮首 +（只有一轮、或单轮自身就超限）→ 返回 None，**宁可超限也不裁**。 + +### D2. TTL 裁剪 ttl_cut：边界向前对齐 + +TTL 先数"从头开始连续过期"的条数 n（`expired[i]` 由存储层按 cutoff 算好， +严格 `<`，恰好等于 cutoff 的保留），再从 n 往**前**找最近的轮首： + +- 过期前缀恰好结束在轮边界（n 本身就是轮首）→ 删整轮； +- 过期前缀伸进了一轮中间 → 退回到这一轮开头，整轮保留（不能切一半）； +- **全部过期**（n == len）→ 返回 len，整库清空。空历史是合法序列，TTL 的语义 + 是"过期就该删"，这一条高于条数裁剪"至少留最后一轮"的约束。 + +### D3. 两个边界取 max + +条数裁剪和 TTL 可能同时命中，各自得到一个删除上界。两个上界都落在轮首， +较大的那个仍然是轮首，所以直接 `max(k_count, k_ttl)` 一次删完，工具对依旧完整。 + +## E. InMemoryStore：并行时间戳列表 + +ChatMessage 没有时间字段（也不该为存储策略改 `types.py` 的核心数据结构）， +于是用一个与 `_history` **严格同长同序**的 `_timestamps` 列表记录每条消息的时间： + +```python +async def append_history(self, message): + self._history.append(message) + self._timestamps.append(self._clock()) # 注入时钟，测试可拨快 + self.prune() # 未配置策略时立即返回 0 +``` + +`prune()` 是非契约方法：`spi/memory.py` 的 Protocol 五个方法一个没加， +它和 `SqliteStore.close()` 同属"宿主探测式调用"的先例，内核契约保持稳定。 + +## F. SqliteStore：取行 → 算边界 → 按 id 删 + +`_prune_locked()`（调用方已持锁）三步走： + +1. `SELECT id, role, created_at ... ORDER BY id ASC` 取本 scope 全部历史； +2. 复用 retention 的两个纯函数算出删除上界 k； +3. `DELETE ... WHERE id < rows[k]["id"]`（k == 行数时整 scope 清空）。 + +注意 TTL **不用**裸 `DELETE ... WHERE created_at < ?`——那会绕过轮对齐、 +切散工具对。会话历史量级很小，统一走 Python 算边界更安全。 + +两个细节： + +- **created_at 改由 Python 侧注入时钟写入**（列默认 CURRENT_TIMESTAMP 保留给 + 外部插入）。否则测试在毫秒内跑完，DB 时钟根本不前进，假时钟管不到落库时间， + 两种 Store 就没法做对等测试。 +- **构造时自动 prune 一次**：服务重启后库里可能全是过期数据，打开连接、建完 + schema 就清一遍，覆盖"重启场景"。 + +## G. Context._compact：同一类 bug 的另一处 + +`kernel/context.py` 的 `_compact()` 是**单次请求内**的字符预算压缩（与跨请求的 +记忆裁剪是两层），旧实现按下标逐个丢消息，同样可能切散工具对。本批一并修复： +候补边界向后对齐到轮首，之后没有新一轮就宁可超预算也不裁。kernel 不能反向 +依赖 memory 包，所以那里保留一份同源私有实现——两处规则改动时必须同步。 + +## H. env 解析与装配：只解析一次 + +`retention_from_env()` 是唯一入口：空白=未设置（静默）；0/负数/非整数=忽略并 +`warnings.warn`（不崩、不静默）。`serve_example.py` 启动时解析一次，显式传给 +`SqliteStore.from_env(retention=...)`，回落 InMemoryStore 时用同一组参数， +避免非法值 warning 两次。 + +## I. 诚实的边界 + +- KV（键值记忆）没有 TTL：给 kv 表加过期时间要 `ALTER TABLE`（schema v1→v2 + 迁移），是第一次实战迁移，留到 v0.4 单独做。 +- 裁剪不发 AgentEvent：它是存储维护，不是自适应决策，Loop 不感知； + 可观测性由 `prune()` 返回值与启动日志一行承担。 +- 条数上限是"上限"不是"目标值"：轮对齐后实际保留可能少于配置值。 +- 多进程/多实例共享同一个 SQLite 文件的场景仍不在支持范围（v0.2 已声明）。 +- **两种实现的时间精度不同**：SQLite 侧 `created_at` 落库是**秒级**文本 + （`strftime("%Y-%m-%d %H:%M:%S")`），内存实现保留**微秒**。TTL 以秒/天为量级时两者等价， + 但当"消息时间戳与 cutoff 相差不足 1 秒"时，两种实现可能给出不同结果——不要假设它们逐比特一致。 + +## 自检 + +1. 为什么删除边界必须落在轮首？切散了会发生什么？ +2. 条数裁剪的边界向哪个方向对齐？TTL 呢？为什么方向相反？ +3. TTL 判定全部过期时为什么允许整库清空，而条数裁剪永远保留最后一轮？ +4. `prune()` 为什么不写进 MemoryStore 契约？ +5. SQLite 的 created_at 为什么改由 Python 侧写入？ +6. Context._compact 和 Store 的 prune 是同一层东西吗？分别在什么时候触发？ diff --git a/submissions/mcp-hackathon/yai-agent-core/source/docs/walkthrough/14-rate-limit-battery.md b/submissions/mcp-hackathon/yai-agent-core/source/docs/walkthrough/14-rate-limit-battery.md new file mode 100644 index 0000000..91490f4 --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/docs/walkthrough/14-rate-limit-battery.md @@ -0,0 +1,106 @@ +# 逐行讲解 14 · 限流 Battery：评审期保护公网 POST 端点 + +> 对应代码：`batteries/fastapi_server/ratelimit.py`（新增）、`app.py`（中间件挂载）。 +> v0.3，纯标准库（collections/threading/math），零新依赖；默认开启是对外承诺值。 + +## A. 为什么限流、限哪里 + +线上 `/v1/agent/run` 是真金白银的端点：每次 POST 都会调一次 DeepSeek。评审期最怕 +两类事故——失控脚本死循环重试把额度烧光、爬虫误扫打爆免费实例。限流 Battery 的 +答案很克制： + +- **只拦 `POST /v1/agent/run`**，白名单写死在 `_LIMITED_PATHS`； +- **三个 GET 端点（/health、/.well-known/xagent-verification.json、/v1/tools）永不限**： + 它们是 X-Agent 评审的硬门槛验证路径，任何"顺手全局限一下"都可能让评审官看到 429—— + 这是本批的第一设计红线； +- 中间件 + 路径白名单（而不是逐路由 `Depends`）：以后新增 POST 路由时， + "忘记挂限流"比"忘记加 Depends"更不容易发生——白名单是默认在场的一道闸。 + +默认值 `enabled=True / per_minute=30 / window_seconds=60` 是对外承诺： +每 IP 每分钟 30 次 POST，正常评审用不完，失控脚本立刻被拦。 + +## B. 滑动窗口日志：最好解释的算法 + +```python +hits: dict[str, deque[float]] # 每 key 一个时间戳队列 + +def check(key): + now = time_func() + while hits[key] and hits[key][0] <= now - window: # 1. 弹出窗口外时间戳 + hits[key].popleft() + if len(hits[key]) >= per_minute: # 2. 剩余长度已达上限 → 拒 + retry_after = max(1, ceil(oldest + window - now)) + return False, retry_after + hits[key].append(now) # 3. 记录本次并放行 + return True, 0 +``` + +对比固定窗口（"每分钟清零计数器"）：固定窗口在边界处有 2× 突发（59 秒 30 次 + +61 秒 30 次 = 2 秒 60 次）；滑动窗口日志语义就是字面的"任意 60 秒内最多 30 次"， +没有边界突发，也最好向评审解释。代价是 O(窗口内请求数) 内存——单实例演示流量下 +可以忽略。 + +`Retry-After = max(1, ceil(oldest + window - now))`：队首（最老）请求过期的那一刻 +就是配额腾出空位的那一刻，向上取整保证至少等 1 秒。**响应头与响应体里的 +`retry_after` 来自同一次计算**——不一致会让客户端重试策略无所适从。 + +## C. client_ip：信任边界要写清楚 + +```python +X-Forwarded-For 最左非空段 → 缺失回退 request.client.host → 再缺省 "unknown" +``` + +Render 边缘代理会为每个请求附加 XFF，所以取 XFF 最左即真实客户端 IP； +不依赖 uvicorn `--proxy-headers`，部署形态少一个变量。 + +**威胁模型如实写**：这套识别防的是误刷/爬虫/失控循环；**不防**蓄意伪造 XFF 的 +分布式攻击——攻击者可以随便声明 `X-Forwarded-For: 8.8.8.8` 换桶。那要靠鉴权或 +人机验证，超出 v0.3 范围。文档里不装强，评审官反而信得过。 + +## D. 并发与生命周期：两处"防御性多虑" + +- `threading.Lock` 包住 `check()`：目标路由是 async，deque 操作中间没有 await， + 单事件循环下理论原子；但 TestClient 会跨线程、将来同步路由也可能跨线程， + 锁成本近乎为零，买了保险。 +- 状态只在内存：进程重启清零，不落盘、不引 Redis。演示服务重启后限流从零开始， + 这在评审语境下是可接受的边界（攻击者拿到的也只是重新数 30 次）。 + +## E. 装配：create_app 只加一个关键字参数 + +```python +def create_app(core, lifespan=None, *, rate_limit: RateLimitConfig | None = None): + config = rate_limit if rate_limit is not None else RateLimitConfig.from_env() + if config.enabled: + ...注册中间件... +``` + +- `None` → `from_env()`：既有调用（`create_app(core)`、`create_app(core, lifespan=...)`） + 零改动，行为即"默认开启"； +- `enabled=False` 时**根本不注册中间件**：关闭态零开销、零行为变化， + 本地开发设 `YAI_RATE_LIMIT_ENABLED=0` 即回到改造前； +- 被限请求在中间件层直接返回 429，**不进 `core.run`**——一分模型钱都不花 + （测试用计数模型断言：N+1 次请求只调 N 次模型）。 + +## F. 测试：假时钟贯穿，禁止 sleep + +窗口是 60 秒，真实等待不可能出现在测试里。全部用 `time_func` 注入假时钟： +`now = [0.0]`，`clock.advance(seconds=61)` 一行"等"过一分钟。能注入的前提是 +`check()` 只通过 `time_func()` 取时间——**永远不直接调 time.monotonic**， +这是可测性的代价与回报。边界语义钉死在用例里：恰好等于窗口的时间戳按过期清除 +（`<=`），`retry_after` 恒 ≥ 1。 + +## G. 诚实的边界 + +1. 不防伪造 XFF 的分布式攻击（见 C 节）； +2. 重启清零，无跨实例共享计数——多实例部署要做全局限流，先解决状态共享； +3. 全局限流兜底（整实例总配额）暂不做，模块 docstring 留了 TODO 位； +4. `X-Forwarded-For` 链上只有最左段被信任，右段可能是任意代理追加的，不做校验。 + +## 自检 + +1. 为什么三个 GET 端点永远不限流？加"软限"会怎样？ +2. 滑动窗口日志与固定窗口计数差在哪？本批为什么选前者？ +3. `Retry-After` 怎么算的？为什么和响应体必须同源？ +4. 伪造 XFF 能绕过本限流吗？那属于哪一层的问题？ +5. 为什么 `enabled=False` 时不注册中间件，而不是注册了直接放行？ +6. 被限请求为什么必须在中间件层返回，而不是放进去让模型拒绝？ diff --git a/submissions/mcp-hackathon/yai-agent-core/source/examples/demo_model.py b/submissions/mcp-hackathon/yai-agent-core/source/examples/demo_model.py new file mode 100644 index 0000000..fbb823c --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/examples/demo_model.py @@ -0,0 +1,29 @@ +"""示例共用：无 API Key 时使用的脚本化离线模型（演示"零配置可跑"）。""" + +from yai_core import ModelResponse, ToolCallRequest + + +class OfflineScriptedModel: + """行为：规划轮先给计划；第一次拿到工具清单时调用首个工具；之后收尾。""" + + def __init__(self) -> None: + self.calls = 0 + self._tool_used = False + + async def achat(self, messages, tools=None, *, tier="standard"): + self.calls += 1 + # 第一次拿到工具时调用第一个工具（react 首轮 / plan 的执行首轮都适用） + if tools and not self._tool_used: + self._tool_used = True + first_tool = tools[0]["function"]["name"] + return ModelResponse( + content="", + tool_calls=[ToolCallRequest(id="demo-1", name=first_tool, arguments={})], + ) + # 规划轮（无工具）：输出步骤计划 + if self.calls == 1: + return ModelResponse(content="1. 筛选目标数据\n2. 调用宿主能力执行\n3. 整理最终结果") + # 收尾：基于工具观察回答 + last_tool_msg = next((m for m in reversed(messages) if m["role"] == "tool"), None) + observed = last_tool_msg["content"] if last_tool_msg else "（无工具结果）" + return ModelResponse(content=f"离线演示完成，宿主能力返回：{observed[:120]}") diff --git a/submissions/mcp-hackathon/yai-agent-core/source/examples/host_a_notes/__init__.py b/submissions/mcp-hackathon/yai-agent-core/source/examples/host_a_notes/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/submissions/mcp-hackathon/yai-agent-core/source/examples/host_a_notes/capabilities.py b/submissions/mcp-hackathon/yai-agent-core/source/examples/host_a_notes/capabilities.py new file mode 100644 index 0000000..c330ea1 --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/examples/host_a_notes/capabilities.py @@ -0,0 +1,30 @@ +"""宿主 A：一个极简笔记应用的业务能力层。 + +注意：这里没有任何 Agent 代码——只有普通业务函数。 +YAI Agent Core 通过内省自动把它们变成可被 Agent 调用的工具。 +""" + +from __future__ import annotations + +_NOTES: list[dict] = [ + {"id": 1, "title": "Core 骨架", "content": "完成 SPI 四契约与 Agent Loop", "tag": "工作"}, + {"id": 2, "title": "比赛清单", "content": "X-Agent 0919 截止，需要部署健康端点", "tag": "工作"}, + {"id": 3, "title": "购物", "content": "买咖啡豆和牛奶", "tag": "生活"}, +] + + +def list_notes(tag: str = "") -> list[dict]: + """列出全部笔记，可按标签筛选。""" + if tag: + return [n for n in _NOTES if n["tag"] == tag] + return _NOTES + + +def search_notes(keyword: str) -> list[dict]: + """按关键词搜索笔记标题与正文。""" + return [n for n in _NOTES if keyword in n["title"] or keyword in n["content"]] + + +def count_notes() -> int: + """统计笔记总数。""" + return len(_NOTES) diff --git a/submissions/mcp-hackathon/yai-agent-core/source/examples/host_a_notes/run.py b/submissions/mcp-hackathon/yai-agent-core/source/examples/host_a_notes/run.py new file mode 100644 index 0000000..ecd2878 --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/examples/host_a_notes/run.py @@ -0,0 +1,34 @@ +"""宿主 A 演示：同一个 Core 自动适配笔记应用。 + +运行：.venv/Scripts/python.exe examples/host_a_notes/run.py [可选任务文本] +有 OPENAI_API_KEY（.env）时走真实模型，否则走离线脚本模型。 +""" + +from __future__ import annotations + +import asyncio +import sys +from pathlib import Path + +sys.path.insert(0, str(Path(__file__).resolve().parents[1])) # examples/ + +from runner_common import bootstrap, build_model, load_dotenv, stream # noqa: E402 + +bootstrap() + +from host_a_notes import capabilities # noqa: E402 +from yai_core import AgentCore # noqa: E402 + +DEFAULT_TASK = "列出我的全部笔记" + + +async def main() -> None: + load_dotenv() + model, backend = build_model() + core = AgentCore.auto(capabilities, model) + task = " ".join(sys.argv[1:]).strip() or DEFAULT_TASK + await stream(core, task, backend) + + +if __name__ == "__main__": + asyncio.run(main()) diff --git a/submissions/mcp-hackathon/yai-agent-core/source/examples/host_b_data/__init__.py b/submissions/mcp-hackathon/yai-agent-core/source/examples/host_b_data/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/submissions/mcp-hackathon/yai-agent-core/source/examples/host_b_data/capabilities.py b/submissions/mcp-hackathon/yai-agent-core/source/examples/host_b_data/capabilities.py new file mode 100644 index 0000000..f07d0c0 --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/examples/host_b_data/capabilities.py @@ -0,0 +1,30 @@ +"""宿主 B：一个极简销售数据应用的业务能力层（与宿主 A 完全不同的领域）。""" + +from __future__ import annotations + +_RECORDS = [ + {"order": "A001", "category": "硬件", "amount": 1200, "region": "华东"}, + {"order": "A002", "category": "软件", "amount": 800, "region": "华南"}, + {"order": "A003", "category": "硬件", "amount": 1500, "region": "华东"}, + {"order": "A004", "category": "服务", "amount": 600, "region": "华北"}, +] + + +def list_records() -> list[dict]: + """列出全部销售记录。""" + return _RECORDS + + +def filter_by_category(category: str = "") -> list[dict]: + """按品类筛选销售记录，品类为空时返回全部。""" + if category: + return [r for r in _RECORDS if r["category"] == category] + return _RECORDS + + +def sum_amount(category: str = "") -> int: + """统计销售额，可按品类筛选后汇总。""" + rows = _RECORDS + if category: + rows = [r for r in _RECORDS if r["category"] == category] + return sum(r["amount"] for r in rows) diff --git a/submissions/mcp-hackathon/yai-agent-core/source/examples/host_b_data/run.py b/submissions/mcp-hackathon/yai-agent-core/source/examples/host_b_data/run.py new file mode 100644 index 0000000..b0b070e --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/examples/host_b_data/run.py @@ -0,0 +1,33 @@ +"""宿主 B 演示：同一份 Core、零修改，自动适配销售数据应用。 + +运行：.venv/Scripts/python.exe examples/host_b_data/run.py [可选任务文本] +""" + +from __future__ import annotations + +import asyncio +import sys +from pathlib import Path + +sys.path.insert(0, str(Path(__file__).resolve().parents[1])) # examples/ + +from runner_common import bootstrap, build_model, load_dotenv, stream # noqa: E402 + +bootstrap() + +from host_b_data import capabilities # noqa: E402 +from yai_core import AgentCore # noqa: E402 + +DEFAULT_TASK = "先筛选硬件品类，然后统计销售额并整理成报告" + + +async def main() -> None: + load_dotenv() + model, backend = build_model() + core = AgentCore.auto(capabilities, model) + task = " ".join(sys.argv[1:]).strip() or DEFAULT_TASK + await stream(core, task, backend) + + +if __name__ == "__main__": + asyncio.run(main()) diff --git a/submissions/mcp-hackathon/yai-agent-core/source/examples/host_c_companion/__init__.py b/submissions/mcp-hackathon/yai-agent-core/source/examples/host_c_companion/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/submissions/mcp-hackathon/yai-agent-core/source/examples/host_c_companion/capabilities.py b/submissions/mcp-hackathon/yai-agent-core/source/examples/host_c_companion/capabilities.py new file mode 100644 index 0000000..f786e71 --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/examples/host_c_companion/capabilities.py @@ -0,0 +1,63 @@ +"""宿主 C：极简 AI 陪伴应用能力层 —— AMBRACE（拥爱）的缩影。 + +这是 YAI 未来回流 AMBRACE 后的形态预演： +陪伴业务（状态、记忆、心情、主动关怀）照常写成普通函数， +Agent 能力（该回忆什么、何时主动关心、怎么串起来）由 Core 自适应提供。 +""" + +from __future__ import annotations + +from datetime import date + +_PROFILE = {"name": "小拥", "mood": "平静", "energy": 62, "bond_days": 128} + +_MOOD_LOG = [ + {"day": "09-06", "mood": "焦虑", "note": "担心三个比赛来不及"}, + {"day": "09-07", "mood": "开心", "note": "YAI Core 骨架跑通了"}, +] + +_MEMORIES = [ + {"id": 1, "kind": "偏好", "content": "深夜写代码时喜欢听 lofi，不喜欢被催进度"}, + {"id": 2, "kind": "约定", "content": "每周五晚上一起做一周复盘"}, + {"id": 3, "kind": "经历", "content": "一起从零做 AMBRACE，报名了三个比赛"}, +] + + +def get_companion_profile() -> dict: + """获取陪伴对象当前的状态档案。""" + return dict(_PROFILE) + + +def recall_memories(keyword: str = "") -> list[dict]: + """回忆与关键词相关的长期记忆，关键词为空时返回全部。""" + if not keyword: + return list(_MEMORIES) + return [m for m in _MEMORIES if keyword in m["kind"] or keyword in m["content"]] + + +def save_memory(kind: str = "日常", content: str = "") -> dict: + """把一条新的长期记忆写入陪伴记忆库。""" + item = {"id": len(_MEMORIES) + 1, "kind": kind, "content": content} + _MEMORIES.append(item) + return {"saved": True, "memory": item, "total": len(_MEMORIES)} + + +def log_mood(mood: str = "平静", note: str = "") -> dict: + """记录此刻心情，并返回陪伴状态摘要。""" + entry = {"day": date.today().strftime("%m-%d"), "mood": mood, "note": note} + _MOOD_LOG.append(entry) + return {"logged": entry, "profile": dict(_PROFILE), "recent_moods": _MOOD_LOG[-3:]} + + +def suggest_care_action() -> dict: + """根据陪伴状态给出一条主动关怀建议（AMBRACE 主动行为的最小雏形）。""" + if _PROFILE["energy"] < 70: + action = "提醒休息，陪他聊五分钟而不是推进任务" + reason = "能量值偏低，优先安抚情绪" + elif _PROFILE["bond_days"] > 100: + action = "翻出一条共同记忆，主动开启回忆话题" + reason = "羁绊天数较长，用共同经历增强连接" + else: + action = "轻打个招呼，问问今天过得怎样" + reason = "状态平稳，常规陪伴即可" + return {"action": action, "reason": reason, "based_on": dict(_PROFILE)} diff --git a/submissions/mcp-hackathon/yai-agent-core/source/examples/host_c_companion/run.py b/submissions/mcp-hackathon/yai-agent-core/source/examples/host_c_companion/run.py new file mode 100644 index 0000000..cfb611a --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/examples/host_c_companion/run.py @@ -0,0 +1,33 @@ +"""宿主 C 演示：同一份 Core 零修改，嵌入一个 AI 陪伴应用（AMBRACE 预演）。 + +运行：.venv/Scripts/python.exe examples/host_c_companion/run.py [可选任务文本] +""" + +from __future__ import annotations + +import asyncio +import sys +from pathlib import Path + +sys.path.insert(0, str(Path(__file__).resolve().parents[1])) # examples/ + +from runner_common import bootstrap, build_model, load_dotenv, stream # noqa: E402 + +bootstrap() + +from host_c_companion import capabilities # noqa: E402 +from yai_core import AgentCore # noqa: E402 + +DEFAULT_TASK = "先查看小拥的状态，然后检索和约定有关的记忆，给出主动关怀建议" + + +async def main() -> None: + load_dotenv() + model, backend = build_model() + core = AgentCore.auto(capabilities, model) + task = " ".join(sys.argv[1:]).strip() or DEFAULT_TASK + await stream(core, task, backend) + + +if __name__ == "__main__": + asyncio.run(main()) diff --git a/submissions/mcp-hackathon/yai-agent-core/source/examples/host_d_mcp/__init__.py b/submissions/mcp-hackathon/yai-agent-core/source/examples/host_d_mcp/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/submissions/mcp-hackathon/yai-agent-core/source/examples/host_d_mcp/demo_mcp_server.py b/submissions/mcp-hackathon/yai-agent-core/source/examples/host_d_mcp/demo_mcp_server.py new file mode 100644 index 0000000..b472adf --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/examples/host_d_mcp/demo_mcp_server.py @@ -0,0 +1,29 @@ +"""host_d 配套的本地 stdio MCP Server（演示用，零网络、零账号）。 + +被 run.py 以子进程方式拉起；也可以手动运行观察： + .venv/Scripts/python.exe examples/host_d_mcp/demo_mcp_server.py +（stdio 服务通过标准输入输出通信，直接运行会安静等待客户端，属正常现象。） +""" + +from __future__ import annotations + +from mcp.server import MCPServer + +mcp = MCPServer("YAI-DemoTools") + + +@mcp.tool() +def add(a: int, b: int) -> int: + """Add two integers and return the sum.""" + return a + b + + +@mcp.tool() +def weather(city: str) -> str: + """Get a demo weather report for a city (mock data, not real).""" + return f"{city} 今天晴，26℃，东北风 2 级（演示数据，非真实天气）。" + + +if __name__ == "__main__": + # MCPServer.run() 默认 stdio 传输：把进程的 stdin/stdout 变成 MCP 通道。 + mcp.run() diff --git a/submissions/mcp-hackathon/yai-agent-core/source/examples/host_d_mcp/run.py b/submissions/mcp-hackathon/yai-agent-core/source/examples/host_d_mcp/run.py new file mode 100644 index 0000000..868226c --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/examples/host_d_mcp/run.py @@ -0,0 +1,75 @@ +"""宿主 D 演示：Core 通过 MCP Client 接入外部 MCP Server 的工具。 + +默认以 stdio 子进程方式拉起同目录 demo_mcp_server.py（离线可跑）； +也可以用环境变量改接任意 MCP Server： + MCP_SERVER_URL=http://127.0.0.1:8000/mcp # Streamable HTTP + MCP_SERVER_COMMAND="uv run server.py" # stdio 命令（空格分词） + +运行：.venv/Scripts/python.exe examples/host_d_mcp/run.py [可选任务文本] +""" + +from __future__ import annotations + +import asyncio +import os +import shlex +import sys +from pathlib import Path + +sys.path.insert(0, str(Path(__file__).resolve().parents[1])) # examples/ + +from runner_common import bootstrap, build_model, load_dotenv, stream # noqa: E402 + +bootstrap() + +from yai_core import AgentCore, build_spec # noqa: E402 + +DEFAULT_TASK = "用 MCP 工具算一下 17 加 25，再查一下湛江的天气，最后用一句话汇总" + + +def host_label() -> str: + """host_d 自己的本地工具：演示 Native 与 MCP 工具在同一注册表共存。""" + return "host_d（本地宿主）在线" + + +def build_config(): + """按环境变量构造 McpServerConfig；缺省回落到自带的本地 stdio 演示 Server。""" + from yai_core.integrations.mcp import McpServerConfig + + url = os.getenv("MCP_SERVER_URL") + if url: + return McpServerConfig(alias="remote", url=url) + command_line = os.getenv("MCP_SERVER_COMMAND") + if command_line: + parts = shlex.split(command_line, posix=(os.name != "nt")) + return McpServerConfig(alias="stdio", command=parts[0], args=parts[1:]) + demo_server = Path(__file__).with_name("demo_mcp_server.py") + return McpServerConfig( + alias="demo-stdio", + command=sys.executable, + args=[str(demo_server)], + ) + + +async def main() -> None: + load_dotenv() + model, backend = build_model() + core = AgentCore(model) + core.register_tools([build_spec(host_label)]) + + try: + from yai_core.integrations.mcp import attach_mcp_tools + except ImportError as exc: + print(f"[缺少依赖] {exc}") + return + + bridge = await attach_mcp_tools(core.registry, build_config()) + try: + task = " ".join(sys.argv[1:]).strip() or DEFAULT_TASK + await stream(core, task, backend) + finally: + await bridge.aclose() # 断开 stdio 子进程 / HTTP 连接，不留后台进程 + + +if __name__ == "__main__": + asyncio.run(main()) diff --git a/submissions/mcp-hackathon/yai-agent-core/source/examples/runner_common.py b/submissions/mcp-hackathon/yai-agent-core/source/examples/runner_common.py new file mode 100644 index 0000000..128938b --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/examples/runner_common.py @@ -0,0 +1,80 @@ +"""三个示例宿主共用的运行脚手架：路径引导、.env 加载、模型选择、事件流打印。 + +各宿主的 run.py 只负责声明自己的 capabilities 与默认任务，不重复这些样板。 +""" + +from __future__ import annotations + +import os +import sys +from pathlib import Path + +ROOT = Path(__file__).resolve().parents[1] + + +def bootstrap() -> None: + """把 src/ 与 examples/ 放进 sys.path，使脚本可直接运行、无需安装。""" + sys.path.insert(0, str(ROOT / "src")) + sys.path.insert(0, str(ROOT / "examples")) + + +def load_dotenv() -> None: + """极简 .env 加载器：只认 KEY=VALUE，不覆盖已存在的环境变量，内核保持零依赖。""" + env_path = ROOT / ".env" + if not env_path.exists(): + return + for line in env_path.read_text(encoding="utf-8").splitlines(): + line = line.strip() + if not line or line.startswith("#") or "=" not in line: + continue + key, value = line.split("=", 1) + os.environ.setdefault(key.strip(), value.strip()) + + +def build_model(): + """有 Key 走 OpenAI 兼容真实模型（DeepSeek 等），否则回退离线脚本模型。""" + if os.getenv("OPENAI_API_KEY"): + from yai_core import OpenAICompatProvider + + model = OpenAICompatProvider() + label = f"真实模型 {os.getenv('OPENAI_BASE_URL', '(SDK默认)')} :: {model.model}" + return model, label + from demo_model import OfflineScriptedModel + + return OfflineScriptedModel(), "离线脚本模型（未检测到 OPENAI_API_KEY）" + + +async def stream(core, task: str, backend: str) -> None: + """跑任务并把 Observer 事件流按人类可读方式打印出来。""" + from yai_core import EventType + + print("=" * 60) + print("后端：", backend) + print("自动发现的工具：", [t["name"] for t in core.list_tools()]) + print("任务：", task) + print("-" * 60) + + async for event in core.astream(task): + if event.type == EventType.STRATEGY_SELECTED: + print(f"[路由] 选定策略：{event.data['strategy']}") + elif event.type == EventType.PLAN_CREATED: + print("[计划] 拆出步骤：") + for i, step in enumerate(event.data["steps"], 1): + print(f" {i}. {step}") + elif event.type == EventType.TOOL_CALL: + print(f"[工具] 调用 {event.data['tool']}({event.data['arguments']})") + elif event.type == EventType.TOOL_RESULT: + preview = event.data.get("preview") or event.data.get("error", "") + print(f"[观察] 返回：{str(preview)[:120]}") + elif event.type == EventType.PERMISSION_ASKED: + print(f"[权限] 请求确认：{event.data['tool']}({event.data['arguments']})") + elif event.type == EventType.CLARIFY_REQUESTED: + print(f"[反问] {event.data['question']}") + elif event.type == EventType.MODEL_MESSAGE: + print(f"[模型] {event.data['text']}") + elif event.type == EventType.ERROR: + print(f"[错误] {event.data['error']}") + elif event.type == EventType.DONE: + print("-" * 60) + print(f"完成（策略 {event.data['strategy']}）") + print("最终结果：", event.data["final_text"]) diff --git a/submissions/mcp-hackathon/yai-agent-core/source/pyproject.toml b/submissions/mcp-hackathon/yai-agent-core/source/pyproject.toml new file mode 100644 index 0000000..254d545 --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/pyproject.toml @@ -0,0 +1,50 @@ +[project] +name = "yai-agent-core" +version = "0.1.0" +description = "YAI Agent Core — an embeddable, self-adaptive agent kernel for host applications" +readme = "README.md" +requires-python = ">=3.11" +license = "MIT" +authors = [{ name = "Gi-Tuu" }] +keywords = ["agent", "llm", "tool-calling", "mcp", "runtime", "embedded", "kernel"] +dependencies = [] + +[project.optional-dependencies] +# 真实模型接入（OpenAI 兼容：DeepSeek / 通义千问 / OpenAI 等） +llm = ["openai>=1.40"] +# FastAPI Battery：在线 API、健康端点、X-Agent 部署验证端点 +server = [ + "fastapi>=0.115", + "uvicorn[standard]>=0.30", + "pydantic>=2.7", +] +# MCP Client 集成：接入外部 MCP Server 的工具（v2 稳定线，内核本体不依赖） +mcp = ["mcp>=2.0,<3"] +# OpenAPI 发现：把任意 OpenAPI 3 REST API 自动注册为工具（httpx 调用、pyyaml 解析 YAML 描述） +openapi = ["httpx>=0.27", "pyyaml>=6.0"] +dev = [ + "pytest>=8.0", + "ruff>=0.6", + "httpx>=0.27", +] +# 构建 docs/walkthrough 讲义 Word（PDF 导出走 LibreOffice UNO，无需 pip 包） +docs = ["python-docx>=1.1"] + +[build-system] +requires = ["hatchling"] +build-backend = "hatchling.build" + +[tool.hatch.build.targets.wheel] +packages = ["src/yai_core"] + +[tool.ruff] +line-length = 100 +target-version = "py311" +src = ["src", "tests", "examples"] + +[tool.ruff.lint] +select = ["E", "F", "I", "UP", "B"] + +[tool.pytest.ini_options] +testpaths = ["tests"] +addopts = "-q" diff --git a/submissions/mcp-hackathon/yai-agent-core/source/render.yaml b/submissions/mcp-hackathon/yai-agent-core/source/render.yaml new file mode 100644 index 0000000..f0a806d --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/render.yaml @@ -0,0 +1,41 @@ +# Render Blueprint（https://render.com/docs/blueprint-spec） +# 用法：Render 控制台 New → Blueprint → 连接 GitHub 仓库 yai-agent-core， +# Render 会按本文件自动创建免费 Docker Web Service；首次部署时按提示填写 OPENAI_API_KEY。 +# 说明： +# - PORT 由 Render 自动注入（默认 10000），Dockerfile 的 CMD 已兼容； +# - RENDER_GIT_COMMIT 由 Render 自动注入为本次部署的 commit，/health 直接读取，无需手填； +# - 免费实例 15 分钟无流量会休眠，仅用于演练，正式评审请用常驻 VPS（见 +# docs/competitions/deployment.md）。 +services: + - type: web + name: yai-agent-core + runtime: docker + plan: free + region: singapore + dockerfilePath: ./Dockerfile + healthCheckPath: /health + autoDeploy: true + envVars: + - key: OPENAI_API_KEY + sync: false # Secret：首次部署时在控制台粘贴，不入库 + - key: OPENAI_BASE_URL + value: https://api.deepseek.com + - key: LLM_MODEL + value: deepseek-chat + - key: LLM_STRONG_MODEL + value: deepseek-chat + - key: YAI_PROJECT_SLUG + value: yai-agent-core # X-Agent 提交 slug：必须与提交目录名、验证 JSON 一致 + - key: MCP_SERVER_URL + # 公共免鉴权 MCP Server（DeepWiki）：让线上 API 也能真实调用外部 MCP 工具 + value: https://mcp.deepwiki.com/mcp + - key: YAI_DB_PATH + # 持久化记忆（v0.2）：容器内相对路径 -> /app/data/yai.db，进程启动时自动建目录。 + # 注意：Render 免费层磁盘是临时盘，redeploy 后会丢库，演示口径见 docs/competitions/deployment.md + value: data/yai.db + - key: YAI_HISTORY_MAX_MESSAGES + # 历史保留策略（v0.3）：保留最近 N 条消息，按对话轮对齐裁剪（不拆散工具调用对） + value: "200" + - key: YAI_HISTORY_TTL_SECONDS + # 超过 7 天的历史在写入与启动时清理；两者都是 opt-in，不设置则不裁剪 + value: "604800" diff --git a/submissions/mcp-hackathon/yai-agent-core/source/scripts/build_walkthrough_docx.py b/submissions/mcp-hackathon/yai-agent-core/source/scripts/build_walkthrough_docx.py new file mode 100644 index 0000000..908a063 --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/scripts/build_walkthrough_docx.py @@ -0,0 +1,410 @@ +"""把 docs/walkthrough/ 下按 NN- 编号的分册合并排版成一份 Word 讲义（可再转 PDF）。 + +运行：.venv/Scripts/python.exe scripts/build_walkthrough_docx.py +设计：内容全部来自已有 markdown，脚本只负责解析与排版，不新增正文事实。 +""" + +from __future__ import annotations + +import re +from pathlib import Path + +from docx import Document +from docx.enum.section import WD_SECTION +from docx.enum.style import WD_STYLE_TYPE +from docx.enum.table import WD_TABLE_ALIGNMENT +from docx.enum.text import WD_ALIGN_PARAGRAPH +from docx.oxml import OxmlElement +from docx.oxml.ns import qn +from docx.shared import Cm, Pt, RGBColor + +ROOT = Path(__file__).resolve().parents[1] +SRC_DIR = ROOT / "docs" / "walkthrough" +OUT_DIR = ROOT / "docs" / "exports" +OUT_DOCX = OUT_DIR / "YAI-Agent-Core-源码逐行讲解.docx" + +# 自动收录所有 NN- 开头的分册并按编号排序，新增章节无需改本脚本 +CHAPTERS = sorted(p.name for p in SRC_DIR.glob("[0-9][0-9]-*.md")) + + +# ---------- 样式工具 ---------- + +def set_east_asian(style, ascii_font: str, ea_font: str, size: Pt, + bold: bool | None = None, color: str = "1A1B1C") -> None: + style.font.name = ascii_font + style.font.size = size + style.font.color.rgb = RGBColor.from_string(color) + if bold is not None: + style.font.bold = bold + rpr = style.element.get_or_add_rPr() + rfonts = rpr.find(qn("w:rFonts")) + if rfonts is None: + rfonts = OxmlElement("w:rFonts") + rpr.append(rfonts) + rfonts.set(qn("w:ascii"), ascii_font) + rfonts.set(qn("w:hAnsi"), ascii_font) + rfonts.set(qn("w:eastAsia"), ea_font) + + +def shade_paragraph(par, fill: str) -> None: + ppr = par._p.get_or_add_pPr() + shd = OxmlElement("w:shd") + shd.set(qn("w:val"), "clear") + shd.set(qn("w:color"), "auto") + shd.set(qn("w:fill"), fill) + ppr.append(shd) + + +def shade_run(run, fill: str) -> None: + rpr = run._r.get_or_add_rPr() + shd = OxmlElement("w:shd") + shd.set(qn("w:val"), "clear") + shd.set(qn("w:color"), "auto") + shd.set(qn("w:fill"), fill) + rpr.append(shd) + + +def preserve_spaces(run) -> None: + t = run._r.find(qn("w:t")) + if t is not None: + t.set(qn("xml:space"), "preserve") + + +_INLINE = re.compile(r"(\*\*.+?\*\*|`.+?`|\[[^\]]+\]\([^)]+\))") + + +def add_inline(par, text: str, *, base_size: Pt | None = None) -> None: + """解析 **粗体**、`行内代码`、[链接](url)。""" + for token in _INLINE.split(text): + if not token: + continue + if token.startswith("**") and token.endswith("**"): + run = par.add_run(token[2:-2]) + run.bold = True + elif token.startswith("`") and token.endswith("`"): + run = par.add_run(token[1:-1]) + run.font.name = "Consolas" + run.font.size = Pt(10.5) + rpr = run._r.get_or_add_rPr() + rfonts = OxmlElement("w:rFonts") + rfonts.set(qn("w:ascii"), "Consolas") + rfonts.set(qn("w:hAnsi"), "Consolas") + rfonts.set(qn("w:eastAsia"), "宋体") + rpr.append(rfonts) + shade_run(run, "F2F2F2") + elif token.startswith("[") and "](" in token: + label, url = token[1:].split("](", 1) + run = par.add_run(f"{label}（{url[:-1]}）") + run.font.color.rgb = RGBColor.from_string("1F4E79") + else: + run = par.add_run(token) + if base_size is not None: + run.font.size = base_size + preserve_spaces(run) + + +# ---------- Markdown 分块解析 ---------- + +def _is_block_start(line: str) -> bool: + return ( + line.startswith("```") + or bool(re.match(r"^#{1,4} ", line)) + or line.startswith("|") + or line.startswith(">") + or bool(re.match(r"^[-*] ", line)) + or bool(re.match(r"^\d+\.\s", line)) + or line.strip() in ("---", "") + ) + + +def parse_md(text: str) -> list[tuple[str, object]]: + blocks: list[tuple[str, object]] = [] + lines = text.splitlines() + i = 0 + while i < len(lines): + line = lines[i] + if line.strip().startswith("```"): + buf: list[str] = [] + i += 1 + while i < len(lines) and not lines[i].strip().startswith("```"): + buf.append(lines[i]) + i += 1 + i += 1 + blocks.append(("code", "\n".join(buf))) + continue + m = re.match(r"^(#{1,4}) ", line) + if m: + blocks.append((f"h{len(m.group(1))}", line[len(m.group(0)):].strip())) + i += 1 + continue + if line.startswith("|"): + rows = [] + while i < len(lines) and lines[i].startswith("|"): + rows.append(lines[i]) + i += 1 + blocks.append(("table", rows)) + continue + if line.startswith(">"): + buf = [] + while i < len(lines) and lines[i].startswith(">"): + buf.append(lines[i].lstrip(">").strip()) + i += 1 + blocks.append(("quote", " ".join(buf))) + continue + if re.match(r"^[-*] ", line): + items = [] + while i < len(lines) and re.match(r"^[-*] ", lines[i]): + items.append(lines[i][2:]) + i += 1 + blocks.append(("ul", items)) + continue + if re.match(r"^\d+\.\s", line): + items = [] + while i < len(lines) and re.match(r"^\d+\.\s", lines[i]): + items.append(re.sub(r"^\d+\.\s", "", lines[i])) + i += 1 + blocks.append(("ol", items)) + continue + if line.strip() in ("---", ""): + i += 1 + continue + buf = [line] + i += 1 + while i < len(lines) and not _is_block_start(lines[i]): + buf.append(lines[i]) + i += 1 + blocks.append(("p", " ".join(buf))) + return blocks + + +def parse_table(rows: list[str]) -> tuple[list[str], list[list[str]]]: + matrix = [[c.strip() for c in r.strip().strip("|").split("|")] for r in rows] + header = matrix[0] + body = [r for r in matrix[2:]] # 第二行是 --- 分隔行 + return header, body + + +# ---------- docx 构建 ---------- + +def build() -> None: + OUT_DIR.mkdir(parents=True, exist_ok=True) + doc = Document() + + # 页面：A4 + 2.5cm + sec = doc.sections[0] + sec.page_width, sec.page_height = Cm(21.0), Cm(29.7) + sec.top_margin = sec.bottom_margin = Cm(2.5) + sec.left_margin = sec.right_margin = Cm(2.5) + + # 样式 + normal = doc.styles["Normal"] + set_east_asian(normal, "Arial", "宋体", Pt(12)) + normal.paragraph_format.line_spacing = 1.5 + ppr = normal.element.get_or_add_pPr() + ind = OxmlElement("w:ind") + ind.set(qn("w:firstLineChars"), "200") + ppr.append(ind) + + for name, size in (("Heading 1", 16), ("Heading 2", 14), ("Heading 3", 12)): + st = doc.styles[name] + set_east_asian(st, "Arial", "黑体", Pt(size), bold=True, color="000000") + title_style = doc.styles["Title"] + set_east_asian(title_style, "Arial", "黑体", Pt(22), bold=True) + # 去掉默认 Title 样式的蓝色下划线边框 + title_ppr = title_style.element.get_or_add_pPr() + title_bdr = title_ppr.find(qn("w:pBdr")) + if title_bdr is not None: + title_ppr.remove(title_bdr) + + # 打开时自动更新域（让 Word/LibreOffice 生成目录页码） + update_fields = OxmlElement("w:updateFields") + update_fields.set(qn("w:val"), "true") + doc.settings.element.append(update_fields) + + # 取 List Number 样式背后的抽象编号，供每个有序列表独立从 1 开始 + numbering_el = doc.part.numbering_part.element + ln_numpr = doc.styles["List Number"].element.find(qn("w:pPr")).find(qn("w:numPr")) + base_num_id = int(ln_numpr.find(qn("w:numId")).get(qn("w:val"))) + base_num = next( + n for n in numbering_el.findall(qn("w:num")) + if int(n.get(qn("w:numId"))) == base_num_id + ) + abstract_num_id = int(base_num.find(qn("w:abstractNumId")).get(qn("w:val"))) + + def new_restart_num_id() -> int: + existing = [int(n.get(qn("w:numId"))) for n in numbering_el.findall(qn("w:num"))] + num_id = max(existing) + 1 + num = OxmlElement("w:num") + num.set(qn("w:numId"), str(num_id)) + aref = OxmlElement("w:abstractNumId") + aref.set(qn("w:val"), str(abstract_num_id)) + num.append(aref) + override = OxmlElement("w:lvlOverride") + override.set(qn("w:ilvl"), "0") + start = OxmlElement("w:startOverride") + start.set(qn("w:val"), "1") + override.append(start) + num.append(override) + numbering_el.append(num) + return num_id + + code_style = doc.styles.add_style("CodeBlock", WD_STYLE_TYPE.PARAGRAPH) + code_style.base_style = doc.styles["Normal"] + set_east_asian(code_style, "Consolas", "宋体", Pt(10)) + code_style.paragraph_format.line_spacing = 1.15 + code_style.paragraph_format.left_indent = Cm(0.4) + code_style.paragraph_format.space_before = Pt(0) + code_style.paragraph_format.space_after = Pt(0) + cpr = code_style.element.get_or_add_pPr() + cind = OxmlElement("w:ind") + cind.set(qn("w:firstLine"), "0") + cind.set(qn("w:firstLineChars"), "0") + cpr.append(cind) + + quote_style = doc.styles.add_style("QuoteBlock", WD_STYLE_TYPE.PARAGRAPH) + quote_style.base_style = doc.styles["Normal"] + set_east_asian(quote_style, "Arial", "楷体", Pt(11), color="444444") + quote_style.paragraph_format.left_indent = Cm(0.6) + qpr = quote_style.element.get_or_add_pPr() + qind = OxmlElement("w:ind") + qind.set(qn("w:firstLine"), "0") + qpr.append(qind) + + # ---- 封面 ---- + for _ in range(5): + doc.add_paragraph() + t = doc.add_paragraph(style="Title") + t.alignment = WD_ALIGN_PARAGRAPH.CENTER + t.add_run("YAI Agent Core\n源码逐行讲解") + sub = doc.add_paragraph() + sub.alignment = WD_ALIGN_PARAGRAPH.CENTER + r = sub.add_run("00–14 分册合订 · 边学边造配套讲义") + r.font.size = Pt(13) + meta = doc.add_paragraph() + meta.alignment = WD_ALIGN_PARAGRAPH.CENTER + meta_text = ( + "对应代码主线（MCP Client · OpenAPI 发现 · SQLite 持久化记忆）" + "　|　Gi-Tuu　|　2026-09" + ) + r = meta.add_run(meta_text) + r.font.size = Pt(10.5) + r.font.color.rgb = RGBColor.from_string("666666") + + # ---- 目录（独立一节）---- + doc.add_section(WD_SECTION.NEW_PAGE) + toc_title = doc.add_paragraph() + tt_run = toc_title.add_run("目录") + tt_run.bold = True + tt_run.font.size = Pt(16) + rpr = tt_run._r.get_or_add_rPr() + rf = OxmlElement("w:rFonts") + rf.set(qn("w:ascii"), "Arial") + rf.set(qn("w:hAnsi"), "Arial") + rf.set(qn("w:eastAsia"), "黑体") + rpr.append(rf) + toc_par = doc.add_paragraph() + fld_begin = OxmlElement("w:fldChar") + fld_begin.set(qn("w:fldCharType"), "begin") + instr = OxmlElement("w:instrText") + instr.set(qn("xml:space"), "preserve") + instr.text = ' TOC \\o "1-2" \\h \\z \\u ' + fld_sep = OxmlElement("w:fldChar") + fld_sep.set(qn("w:fldCharType"), "separate") + hint = OxmlElement("w:t") + hint.text = "（在 Word 中右键此处选择“更新域”即可生成带页码目录）" + fld_end = OxmlElement("w:fldChar") + fld_end.set(qn("w:fldCharType"), "end") + run_el = toc_par.add_run()._r + for el in (fld_begin, instr, fld_sep, hint, fld_end): + run_el.append(el) + + # ---- 正文（独立一节，页码从 1 开始）---- + body_section = doc.add_section(WD_SECTION.NEW_PAGE) + body_section.footer.is_linked_to_previous = False + footer_par = body_section.footer.paragraphs[0] + footer_par.alignment = WD_ALIGN_PARAGRAPH.CENTER + fb = OxmlElement("w:fldChar") + fb.set(qn("w:fldCharType"), "begin") + it = OxmlElement("w:instrText") + it.set(qn("xml:space"), "preserve") + it.text = " PAGE " + fe = OxmlElement("w:fldChar") + fe.set(qn("w:fldCharType"), "end") + fr = footer_par.add_run()._r + for el in (fb, it, fe): + fr.append(el) + pgnum = OxmlElement("w:pgNumType") + pgnum.set(qn("w:start"), "1") + body_section._sectPr.append(pgnum) + + def render_blocks(blocks: list[tuple[str, object]]) -> None: + for kind, payload in blocks: + if kind.startswith("h"): + doc.add_paragraph(str(payload), style=f"Heading {kind[1]}") + elif kind == "p": + par = doc.add_paragraph() + add_inline(par, str(payload)) + elif kind == "quote": + par = doc.add_paragraph(style="QuoteBlock") + add_inline(par, str(payload)) + elif kind == "ul": + for item in payload: # type: ignore[assignment] + par = doc.add_paragraph(style="List Bullet") + add_inline(par, item) + elif kind == "ol": + num_id = new_restart_num_id() + for item in payload: # type: ignore[assignment] + par = doc.add_paragraph(style="List Number") + ppr = par._p.get_or_add_pPr() + numpr = OxmlElement("w:numPr") + ilvl = OxmlElement("w:ilvl") + ilvl.set(qn("w:val"), "0") + nid = OxmlElement("w:numId") + nid.set(qn("w:val"), str(num_id)) + numpr.append(ilvl) + numpr.append(nid) + ppr.append(numpr) + add_inline(par, item) + elif kind == "code": + for code_line in str(payload).split("\n"): + par = doc.add_paragraph(style="CodeBlock") + run = par.add_run(code_line if code_line else " ") + preserve_spaces(run) + shade_paragraph(par, "F4F5F7") + elif kind == "table": + header, body = parse_table(payload) # type: ignore[arg-type] + table = doc.add_table(rows=1, cols=len(header)) + table.style = "Table Grid" + table.alignment = WD_TABLE_ALIGNMENT.CENTER + hdr = table.rows[0].cells + for j, h in enumerate(header): + hdr[j].text = "" + run = hdr[j].paragraphs[0].add_run(h) + run.bold = True + run.font.size = Pt(10.5) + tcpr = hdr[j]._tc.get_or_add_tcPr() + shd = OxmlElement("w:shd") + shd.set(qn("w:val"), "clear") + shd.set(qn("w:fill"), "D9D9D9") + tcpr.append(shd) + for row in body: + cells = table.add_row().cells + for j, val in enumerate(row): + if j >= len(cells): + break + cells[j].text = "" + add_inline(cells[j].paragraphs[0], val, base_size=Pt(10.5)) + doc.add_paragraph() + + for idx, fname in enumerate(CHAPTERS): + text = (SRC_DIR / fname).read_text(encoding="utf-8") + render_blocks(parse_md(text)) + if idx != len(CHAPTERS) - 1: + doc.add_page_break() + + doc.save(OUT_DOCX) + print(f"saved: {OUT_DOCX}") + + +if __name__ == "__main__": + build() diff --git a/submissions/mcp-hackathon/yai-agent-core/source/scripts/build_xagent_submission.py b/submissions/mcp-hackathon/yai-agent-core/source/scripts/build_xagent_submission.py new file mode 100644 index 0000000..5ea8299 --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/scripts/build_xagent_submission.py @@ -0,0 +1,266 @@ +"""构建 X-Agent MCP Hackathon 提交快照并做离线预检（纯标准库）。 + +做什么： + 1. 取当前 git HEAD 的 40 位 SHA 作为 reviewCommit； + 2. 用 `git archive HEAD` 把【已提交的源码】原样导出到 source/（不含 .git、 + 未跟踪文件、.env，天然满足"评审基线 = pinned commit"）； + 3. 拷贝 SUBMISSION.md / RIGHTS.md / verification/，渲染 submission.json； + 4. 按官方 scripts/validate-submission.mjs 的同等规则做离线预检 + （结构、manifest、文件大小/数量、密钥特征、curl 证据）； + 5. --online 时额外校验：GitHub commit 可公开访问、线上 health/proof 与 + reviewCommit、slug 三处一致。 + +用法： + python scripts/build_xagent_submission.py # 构建 + 离线预检 + python scripts/build_xagent_submission.py --online # 再加线上一致性校验 + +产物：dist/xagent-submission/yai-agent-core/（dist/ 已 gitignore）。 +提交时把该目录整体复制到 xagt-plugin 仓库的 submissions/mcp-hackathon/ 下提 PR。 +""" + +from __future__ import annotations + +import argparse +import io +import json +import re +import shutil +import subprocess +import tarfile +import urllib.request +from pathlib import Path + +ROOT = Path(__file__).resolve().parents[1] +SLUG = "yai-agent-core" +META_DIR = ROOT / "submissions" / "mcp-hackathon" / SLUG +OUT_ROOT = ROOT / "dist" / "xagent-submission" +OUT_DIR = OUT_ROOT / SLUG + +# 下面这组常量与官方 validate-submission.mjs 对齐（2026-09 核对）。 +MAX_FILES = 2000 +MAX_FILE_BYTES = 5 * 1024 * 1024 +MAX_TOTAL_BYTES = 20 * 1024 * 1024 +SLUG_RE = re.compile(r"^[a-z0-9]+(?:-[a-z0-9]+)*$") +SHA_RE = re.compile(r"^[a-f0-9]{40}$") +FORBIDDEN_DIRS = {"node_modules", ".git", "dist", "build", ".next"} +IMPL_EXT_RE = re.compile( + r"\.(?:[cm]?[jt]sx?|py|go|rs|java|kt|kts|c|cc|cpp|h|hpp|cs|fs|rb|php|swift" + r"|scala|sh|bash|sol|vy|ex|exs|erl|clj|lua|r|jl|ipynb|html|vue|svelte|sql)$", + re.IGNORECASE, +) +SECRET_PATTERNS = [ + re.compile(r"-----BEGIN (?:RSA |EC |OPENSSH )?PRIVATE KEY-----"), + re.compile(r"\bAKIA[0-9A-Z]{16}\b"), + re.compile(r"\bgh[pousr]_[A-Za-z0-9]{36,}\b"), + re.compile(r"\bsk-[A-Za-z0-9_-]{20,}\b"), + re.compile(r"\bxox[baprs]-[A-Za-z0-9-]{20,}\b"), +] + + +def git(*args: str) -> str: + return subprocess.run( + ["git", *args], cwd=ROOT, capture_output=True, text=True, check=True + ).stdout.strip() + + +def fail(msg: str) -> None: + raise SystemExit(f"[预检失败] {msg}") + + +def build() -> str: + sha = git("rev-parse", "HEAD") + if not SHA_RE.match(sha): + fail(f"HEAD 不是合法 40 位 SHA：{sha!r}") + + # 工作区未提交改动只警告：评审基线是已推送的 commit，快照里不会带上这些改动。 + dirty = git("status", "--porcelain") + if dirty: + print("[警告] 工作区有未提交改动，不会进入快照（git archive 只取 HEAD）：") + for line in dirty.splitlines()[:10]: + print(" ", line) + + if OUT_ROOT.exists(): + shutil.rmtree(OUT_ROOT) + (OUT_DIR / "verification").mkdir(parents=True) + + # 1) 元数据文件 + for fname in ("SUBMISSION.md", "RIGHTS.md"): + shutil.copy2(META_DIR / fname, OUT_DIR / fname) + shutil.copy2( + META_DIR / "verification" / "README.md", + OUT_DIR / "verification" / "README.md", + ) + + # 2) 渲染 submission.json（把 __REVIEW_COMMIT__ 换成 HEAD SHA） + template = json.loads((META_DIR / "submission.template.json").read_text("utf-8")) + template["reviewCommit"] = sha + (OUT_DIR / "submission.json").write_text( + json.dumps(template, ensure_ascii=False, indent=2) + "\n", "utf-8" + ) + + # 3) git archive 导出 pinned commit 的完整源码到 source/ + tar_bytes = subprocess.run( + ["git", "archive", "--format=tar", "HEAD"], + cwd=ROOT, capture_output=True, check=True, + ).stdout + source_dir = OUT_DIR / "source" + with tarfile.open(fileobj=io.BytesIO(tar_bytes), mode="r:") as tar: + # 安全：拒绝绝对路径与 .. 路径（git archive 不会有，双保险） + for member in tar.getmembers(): + if member.name.startswith(("/",)) or ".." in Path(member.name).parts: + fail(f"归档内出现非法路径：{member.name}") + tar.extractall(source_dir, filter="data") # py3.12+ 的 data 过滤更安全 + + print(f"[构建] reviewCommit = {sha}") + print(f"[构建] 快照目录 = {OUT_DIR}") + return sha + + +def preflight_offline() -> dict: + """镜像官方校验器的离线检查（不含网络）。""" + checks: list[str] = [] + + # --- 必备文件 --- + required = ["submission.json", "SUBMISSION.md", "RIGHTS.md", + "verification/README.md"] + for rel in required: + p = OUT_DIR / rel + if not p.is_file() or p.stat().st_size == 0: + fail(f"{rel} 缺失或为空") + checks.append("必备文件齐全且非空") + + # --- manifest --- + manifest = json.loads((OUT_DIR / "submission.json").read_text("utf-8")) + if manifest.get("schemaVersion") != 1: + fail("submission.json schemaVersion 必须为 1") + if manifest.get("slug") != SLUG or not SLUG_RE.match(SLUG): + fail("slug 非法或与目录名不一致") + for key in ("name", "slug", "sourceRepository", "reviewCommit", "apiBaseUrl", + "healthCheckUrl", "deploymentProofUrl"): + if not isinstance(manifest.get(key), str) or not manifest[key].strip(): + fail(f"submission.json 缺少字段 {key}") + if not SHA_RE.match(manifest["reviewCommit"]): + fail("reviewCommit 必须是 40 位 SHA") + if not re.match(r"^https://github\.com/[^/]+/[^/]+/?$", manifest["sourceRepository"]): + fail("sourceRepository 必须是公开的 https github 仓库 URL") + for key in ("apiBaseUrl", "healthCheckUrl", "deploymentProofUrl"): + url = manifest[key] + if not url.startswith("https://") or "localhost" in url: + fail(f"{key} 必须是公网 HTTPS URL") + origins = {re.match(r"https://[^/]+", manifest[k]).group(0) for k in + ("apiBaseUrl", "healthCheckUrl", "deploymentProofUrl")} + if len(origins) != 1: + fail("API / health / deployment-proof 必须同源") + if not manifest["deploymentProofUrl"].endswith("/.well-known/xagent-verification.json"): + fail("deploymentProofUrl 路径必须是 /.well-known/xagent-verification.json") + checks.append("submission.json 结构与 URL 契约合法") + + # --- 遍历 source/：大小、数量、禁目录、实现文件、密钥扫描 --- + total = 0 + count = 0 + has_impl = False + for path in sorted((OUT_DIR / "source").rglob("*")): + if path.is_symlink(): + fail(f"不允许符号链接：{path.relative_to(OUT_DIR)}") + if path.is_dir(): + if path.name in FORBIDDEN_DIRS: + fail(f"不允许的目录：{path.relative_to(OUT_DIR)}") + continue + rel = path.relative_to(OUT_DIR).as_posix() + count += 1 + size = path.stat().st_size + total += size + if size > MAX_FILE_BYTES: + fail(f"单文件超过 5MiB：{rel}") + if total > MAX_TOTAL_BYTES: + fail("源码总体积超过 20MiB") + if count > MAX_FILES: + fail("文件数超过 2000") + if IMPL_EXT_RE.search(rel): + has_impl = True + name = path.name.lower() + if name.startswith(".env") and "example" not in name: + fail(f"疑似密钥文件：{rel}") + if re.search(r"\.(pem|p12|pfx|key)$", name): + fail(f"疑似密钥文件类型：{rel}") + try: + text = path.read_text("utf-8") + except (UnicodeDecodeError, PermissionError): + continue # 二进制文件跳过文本特征扫描 + for pat in SECRET_PATTERNS: + if pat.search(text): + fail(f"命中密钥特征 {pat.pattern}：{rel}") + if not has_impl: + fail("source/ 内没有实现文件") + checks.append(f"source/ 共 {count} 个文件、{total/1024:.0f} KiB，无禁目录/密钥特征") + + # --- verification 证据 --- + ver = (OUT_DIR / "verification" / "README.md").read_text("utf-8") + if not re.search(r"curl\s", ver) or "health" not in ver: + fail("verification/README.md 必须包含可复现 curl 命令与 health 证据") + checks.append("verification/README.md 含 curl 与 health 证据") + + print("[离线预检] 全部通过：") + for c in checks: + print(" ✓", c) + return manifest + + +def http_json(url: str) -> dict: + req = urllib.request.Request(url, headers={"User-Agent": "yai-submission-check", + "Accept": "application/json"}) + with urllib.request.urlopen(req, timeout=30) as resp: # noqa: S310 - 固定官方 URL + return json.loads(resp.read().decode("utf-8")) + + +def preflight_online(manifest: dict) -> None: + sha = manifest["reviewCommit"] + # 1) GitHub commit 必须可公开访问 + owner_repo = manifest["sourceRepository"].removeprefix("https://github.com/").strip("/") + commit_url = f"https://api.github.com/repos/{owner_repo}/commits/{sha}" + try: + http_json(commit_url) + print("[线上预检] ✓ GitHub 上可公开验证 reviewCommit") + except Exception as exc: # noqa: BLE001 + fail(f"GitHub commit 不可公开验证：{exc}") + + # 2) health：status 健康且 commit 一致 + health = http_json(manifest["healthCheckUrl"]) + health_commit = health.get("commit") or health.get("version") + if health.get("status") not in ("ok", "healthy"): + fail(f"health status 非 ok/healthy：{health.get('status')!r}") + if health_commit != sha: + fail( + f"health commit {health_commit!r} != reviewCommit {sha!r}" + "（是否忘了等部署完成，或正式提交时没关 autoDeploy？）" + ) + print("[线上预检] ✓ /health 在线且 commit 与 reviewCommit 一致") + + # 3) deployment proof：schemaVersion / slug / commit 一致 + proof = http_json(manifest["deploymentProofUrl"]) + if (proof.get("schemaVersion") != 1 or proof.get("slug") != manifest["slug"] + or proof.get("commit") != sha): + fail(f"部署证明不一致：{proof}") + print("[线上预检] ✓ /.well-known/xagent-verification.json 的 slug/commit 一致") + + +def main() -> None: + parser = argparse.ArgumentParser() + parser.add_argument("--online", action="store_true", help="额外做线上一致性校验") + args = parser.parse_args() + + build() + manifest = preflight_offline() + if args.online: + preflight_online(manifest) + print( + "\n[下一步] 1) 确认该 commit 已推送且线上部署完成（正式提交时在 Render 关 autoDeploy）；\n" + " 2) fork https://github.com/xagentAI/xagt-plugin ；\n" + " 3) 把 dist/xagent-submission/yai-agent-core 整个目录复制到\n" + " fork 的 submissions/mcp-hackathon/ 下；\n" + " 4) 提 PR（只动这一个目录），PR 描述按官方模板勾选确认项。" + ) + + +if __name__ == "__main__": + main() diff --git a/submissions/mcp-hackathon/yai-agent-core/source/scripts/lo_update_and_export.py b/submissions/mcp-hackathon/yai-agent-core/source/scripts/lo_update_and_export.py new file mode 100644 index 0000000..de313a6 --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/scripts/lo_update_and_export.py @@ -0,0 +1,68 @@ +"""通过 UNO 连接已在监听的 LibreOffice：更新目录域、回存 docx、导出 PDF。 + +用法（先启动监听）： + soffice --headless --invisible --norestore "--accept=socket,host=localhost,port=2002;urp;" + "C:\\Program Files\\LibreOffice\\program\\python.exe" scripts/lo_update_and_export.py +""" + +import sys +import time +from pathlib import Path + +import uno +from com.sun.star.beans import PropertyValue + + +def prop(name: str, value): + p = PropertyValue() + p.Name = name + p.Value = value + return p + + +def main() -> None: + docx_path = Path(sys.argv[1]).resolve() + pdf_path = Path(sys.argv[2]).resolve() + + local_ctx = uno.getComponentContext() + resolver = local_ctx.ServiceManager.createInstanceWithContext( + "com.sun.star.bridge.UnoUrlResolver", local_ctx + ) + ctx = None + for _ in range(30): + try: + ctx = resolver.resolve( + "uno:socket,host=localhost,port=2002;urp;StarOffice.ComponentContext" + ) + break + except Exception: + time.sleep(1) + if ctx is None: + raise RuntimeError("无法连接 LibreOffice 监听端口") + + desktop = ctx.ServiceManager.createInstanceWithContext( + "com.sun.star.frame.Desktop", ctx + ) + doc = desktop.loadComponentFromURL( + uno.systemPathToFileUrl(str(docx_path)), "_blank", 0, + (prop("Hidden", True),), + ) + + # 更新全部目录/索引 + indexes = doc.getDocumentIndexes() + for i in range(indexes.getCount()): + indexes.getByIndex(i).update() + # 更新普通域（页码等） + doc.getTextFields().refresh() + + doc.store() # 回存 docx（目录缓存随之写入） + doc.storeToURL( + uno.systemPathToFileUrl(str(pdf_path)), + (prop("FilterName", "writer_pdf_Export"),), + ) + doc.close(False) + print("indexes updated; docx stored; pdf exported") + + +if __name__ == "__main__": + main() diff --git a/submissions/mcp-hackathon/yai-agent-core/source/scripts/serve_example.py b/submissions/mcp-hackathon/yai-agent-core/source/scripts/serve_example.py new file mode 100644 index 0000000..a7e004d --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/scripts/serve_example.py @@ -0,0 +1,157 @@ +"""在线 API 启动示例（X-Agent 部署形态）。 + +本地直跑（宿主机统一用 8001，容器内才是 8000）： + uv run uvicorn scripts.serve_example:app --host 127.0.0.1 --port 8001 +容器化： + docker compose up --build # 容器内监听 8000，宿主机映射 8001:8000 +环境变量（写在项目根 .env 即可，脚本启动时自动加载）： + OPENAI_API_KEY / OPENAI_BASE_URL / LLM_MODEL 真实模型（缺省走离线演示模型） + YAI_GIT_COMMIT=<40位 commit> YAI_PROJECT_SLUG= X-Agent 验证端点 + commit 解析顺序：YAI_GIT_COMMIT → 平台注入（如 RENDER_GIT_COMMIT）→ 当前 git HEAD → dev + （只接受完整 40 位哈希，镜像默认值 dev 等占位会被跳过） +""" + +from __future__ import annotations + +import contextlib +import os +import re +import subprocess +import sys +from pathlib import Path + +_SHA40 = re.compile(r"[0-9a-f]{40}") + +ROOT = Path(__file__).resolve().parents[1] +sys.path.insert(0, str(ROOT / "src")) +sys.path.insert(0, str(ROOT / "examples")) + +from host_a_notes import capabilities # noqa: E402 +from runner_common import build_model, load_dotenv # noqa: E402 +from yai_core import AgentCore # noqa: E402 +from yai_core.batteries.fastapi_server import RateLimitConfig, create_app # noqa: E402 +from yai_core.integrations.openapi import attach_openapi_tools # noqa: E402 +from yai_core.integrations.openapi import ( # noqa: E402 + config_from_env as openapi_config_from_env, +) +from yai_core.memory import InMemoryStore, SqliteStore, retention_from_env # noqa: E402 + + +def _git_commit() -> str: + """读取当前 git HEAD 的完整 40 位 commit；非 git 环境回退 dev。""" + try: + out = subprocess.run( + ["git", "rev-parse", "HEAD"], + cwd=ROOT, + capture_output=True, + text=True, + check=True, + timeout=5, + ) + return out.stdout.strip() + except (OSError, subprocess.SubprocessError): + return "dev" + + +def _valid_sha(value: str | None) -> str | None: + """只接受完整 40 位小写哈希；dev、空串、短 SHA 等占位值一律视为无效。""" + if value and _SHA40.fullmatch(value.strip()): + return value.strip() + return None + + +load_dotenv() +# commit 解析链：YAI_GIT_COMMIT（构建期固化）→ 平台注入（Render 为 RENDER_GIT_COMMIT） +# → 当前 git HEAD（本地联调）→ dev。 +# 注意镜像 ENV 里烤着默认值 dev（非合法哈希），必须跳过它，平台注入的真实 SHA 才能生效。 +os.environ["YAI_GIT_COMMIT"] = ( + _valid_sha(os.environ.get("YAI_GIT_COMMIT")) + or _valid_sha(os.environ.get("RENDER_GIT_COMMIT")) + or _git_commit() +) + +_model, _backend = build_model() +print(f"serve_example 后端：{_backend}") +print(f"验证端点 commit：{os.environ['YAI_GIT_COMMIT']}") + +# llm_router=True：先让模型做一次轻量分类（strategy/tier/reason）， +# 分类失败/超时自动回退确定性规则，事件流里带 source=llm|rules 可审计。 +# 持久化记忆 opt-in：设置 YAI_DB_PATH 才落 SQLite；不设置时用进程内内存。 +# 历史保留策略 opt-in：YAI_HISTORY_MAX_MESSAGES / YAI_HISTORY_TTL_SECONDS； +# env 只在这一层解析一次（非法值只 warning 一次），两种 Store 对等生效。 +_retention = retention_from_env() +_sqlite_store = SqliteStore.from_env(retention=_retention) +if _sqlite_store is not None: + _store = _sqlite_store +else: + _store = InMemoryStore(max_messages=_retention[0], ttl_seconds=_retention[1]) +if _retention != (None, None): + print( + f"历史保留策略：max_messages={_retention[0]}，ttl_seconds={_retention[1]}" + "（opt-in，按轮对齐裁剪；SQLite 构造时已自动 prune 一次）" + ) +core = AgentCore.auto(capabilities, _model, llm_router=True, memory=_store) + + +@contextlib.asynccontextmanager +async def app_lifespan(_app): + """启停生命周期：挂载外部 MCP；停机时断开连接并关闭记忆存储。 + + MCP 与 OpenAPI 两个集成相互独立：缺 extra / 外部服务不可达 / 描述拉取失败 + 都只告警、不阻断启动。本地 native 工具与验证端点必须始终可用。 + """ + bridges = [] + try: + # MCP 与 OpenAPI 各自独立：任一集成缺依赖 / 挂载失败都只告警，不影响另一个与本地工具。 + try: + from yai_core.integrations.mcp import attach_mcp_tools, config_from_env + except ImportError as exc: # 没装 [mcp] extra 是合法部署形态 + print(f"[serve_example] 未安装 [mcp] extra，跳过 MCP 挂载：{exc}") + else: + cfg = config_from_env(alias="remote") + if cfg is not None: + try: + bridge = await attach_mcp_tools(core.registry, cfg) + bridges.append(bridge) + names = [s.name for s in bridge.specs] + print(f"MCP 已挂载（{cfg.alias}）：{names}") + except Exception as exc: # noqa: BLE001 - 外部依赖不可用是运行时常态 + print(f"[警告] 外部 MCP 挂载失败，仅提供本地工具：{type(exc).__name__}: {exc}") + + # OpenAPI 发现（opt-in）：配置 OPENAPI_SPEC_URL/PATH 才挂载。 + # 在线演示服务强制只读：只注册 GET/HEAD，写操作绝不暴露到公网演示端点。 + openapi_config = openapi_config_from_env(alias="rest") + if openapi_config is not None: + openapi_config.read_only = True + try: + openapi_bridge = await attach_openapi_tools(core.registry, openapi_config) + bridges.append(openapi_bridge) + print( + f"[serve_example] OpenAPI 已挂载：{openapi_config.url or openapi_config.path}，" + f"工具 {len(openapi_bridge.specs)} 个（read_only=True）" + ) + for note in openapi_bridge.notes: + print(f" note: {note}") + except ImportError as exc: + print(f"[serve_example] 未安装 [openapi] extra，跳过 OpenAPI 挂载：{exc}") + except Exception as exc: # OpenAPI 故障不拖垮本地服务 + print(f"[serve_example] OpenAPI 挂载失败，降级跳过：{exc}") + yield + finally: + for bridge in bridges: + with contextlib.suppress(Exception): + await bridge.aclose() + # close() 不是 MemoryStore 契约方法：探测式调用，InMemoryStore 没有就跳过。 + close_store = getattr(_store, "close", None) + if close_store is not None: + close_store() + + +# 评审期限流（默认开启）：显式 from_env 并打印一行策略，便于部署核对。 +_rate_limit = RateLimitConfig.from_env() +print( + f"限流策略：enabled={_rate_limit.enabled}，" + f"per_minute={_rate_limit.per_minute}，window_seconds={_rate_limit.window_seconds}" + "（仅 POST /v1/agent/run；GET 验证端点不受限）" +) +app = create_app(core, lifespan=app_lifespan, rate_limit=_rate_limit) diff --git a/submissions/mcp-hackathon/yai-agent-core/source/scripts/smoke_test.py b/submissions/mcp-hackathon/yai-agent-core/source/scripts/smoke_test.py new file mode 100644 index 0000000..70d5d27 --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/scripts/smoke_test.py @@ -0,0 +1,52 @@ +"""端到端冒烟：同一 Core 嵌入三个不同宿主，零 Agent 代码各自长出能力。 + +运行：python scripts/smoke_test.py +""" + +from __future__ import annotations + +import asyncio +import sys +from pathlib import Path + +ROOT = Path(__file__).resolve().parents[1] +sys.path.insert(0, str(ROOT / "src")) +sys.path.insert(0, str(ROOT / "examples")) + +from demo_model import OfflineScriptedModel # noqa: E402 +from host_a_notes import capabilities as notes_app # noqa: E402 +from host_b_data import capabilities as data_app # noqa: E402 +from host_c_companion import capabilities as companion_app # noqa: E402 +from yai_core import AgentCore, EventType # noqa: E402 + +_VISIBLE = ( + EventType.STRATEGY_SELECTED, + EventType.PLAN_CREATED, + EventType.TOOL_CALL, + EventType.MODEL_MESSAGE, + EventType.DONE, +) + + +async def run_host(title: str, host: object, task: str) -> None: + print(f"\n===== {title} =====") + core = AgentCore.auto(host, OfflineScriptedModel()) + print(f"自动发现工具: {[t['name'] for t in core.list_tools()]}") + async for event in core.astream(task): + if event.type in _VISIBLE: + print(f" {event.type.value}: {event.data}") + + +async def main() -> None: + await run_host("宿主 A 笔记应用", notes_app, "搜索笔记里和比赛有关的内容") + await run_host("宿主 B 数据应用", data_app, "先筛选硬件品类，然后统计销售额") + await run_host( + "宿主 C AI 陪伴（AMBRACE 预演）", + companion_app, + "先查看小拥的状态，然后检索和约定有关的记忆，给出主动关怀建议", + ) + print("\n冒烟测试通过：同一内核已自适应三个不同宿主。") + + +if __name__ == "__main__": + asyncio.run(main()) diff --git a/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/__init__.py b/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/__init__.py new file mode 100644 index 0000000..308241e --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/__init__.py @@ -0,0 +1,44 @@ +"""YAI Agent Core —— 进程内嵌入式自适应 Agent 内核。 + +宿主软件只声明能力，Core 自动发现、自适应规划与执行。 +""" + +from yai_core.core import AgentCore +from yai_core.discovery import build_spec, discover +from yai_core.kernel import AdaptiveRouter, AgentLoop, Context, RouteDecision +from yai_core.llm.openai_compat import OpenAICompatProvider +from yai_core.tools import ToolExecutor, ToolRegistry +from yai_core.types import ( + AgentEvent, + ChatMessage, + EventType, + ModelResponse, + RunResult, + Strategy, + ToolCallRequest, + ToolSpec, +) + +__version__ = "0.1.0" + +__all__ = [ + "AgentCore", + "AdaptiveRouter", + "RouteDecision", + "AgentLoop", + "Context", + "ToolRegistry", + "ToolExecutor", + "OpenAICompatProvider", + "build_spec", + "discover", + "AgentEvent", + "ChatMessage", + "EventType", + "ModelResponse", + "RunResult", + "Strategy", + "ToolCallRequest", + "ToolSpec", + "__version__", +] diff --git a/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/batteries/__init__.py b/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/batteries/__init__.py new file mode 100644 index 0000000..28e6f2d --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/batteries/__init__.py @@ -0,0 +1 @@ +"""Batteries：可选的外围能力（服务器、MCP client 等），不属于内核。""" diff --git a/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/batteries/fastapi_server/__init__.py b/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/batteries/fastapi_server/__init__.py new file mode 100644 index 0000000..86b732b --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/batteries/fastapi_server/__init__.py @@ -0,0 +1,4 @@ +from yai_core.batteries.fastapi_server.app import create_app +from yai_core.batteries.fastapi_server.ratelimit import RateLimitConfig + +__all__ = ["create_app", "RateLimitConfig"] diff --git a/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/batteries/fastapi_server/app.py b/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/batteries/fastapi_server/app.py new file mode 100644 index 0000000..b537de7 --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/batteries/fastapi_server/app.py @@ -0,0 +1,104 @@ +"""FastAPI Battery：把内嵌 Core 暴露为在线 API。 + +内置 X-Agent AI MCP Hackathon 要求的两个验证端点： +- GET /health -> {"status":"ok","commit":"<40位>"} +- GET /.well-known/xagent-verification.json -> {"schemaVersion":1,"slug":...,"commit":...} + +注意：本模块属于可选 Battery，允许依赖 fastapi/pydantic；yai_core 内核仍零硬依赖。 +""" + +from __future__ import annotations + +import os +from typing import Any + +try: + from fastapi import FastAPI + from fastapi.responses import JSONResponse + from pydantic import BaseModel +except ImportError as exc: # pragma: no cover - 仅在缺少可选依赖时触发 + raise ImportError( + "FastAPI Battery 需要可选依赖：uv pip install -e '.[server]'" + ) from exc + +from yai_core.batteries.fastapi_server.ratelimit import ( + RateLimitConfig, + SlidingWindowLimiter, + client_ip, +) + +# 限流只拦这一条 POST：三个 GET 端点（health / verification / tools）是 +# X-Agent 评审硬门槛路径，任何超限状态下都必须无条件 200。 +_LIMITED_METHOD = "POST" +_LIMITED_PATHS = frozenset({"/v1/agent/run"}) + + +class RunRequest(BaseModel): + task: str + + +def create_app( + core: Any, lifespan: Any = None, *, rate_limit: RateLimitConfig | None = None +) -> FastAPI: + app = FastAPI(title="YAI Agent Core API", version="0.1.0", lifespan=lifespan) + commit = os.getenv("YAI_GIT_COMMIT", "dev") + slug = os.getenv("YAI_PROJECT_SLUG", "yai-agent-core") + + # 评审期限流（opt-out via env）：None -> 从环境变量读默认策略； + # enabled=False 时不注册中间件，零开销、零行为变化。 + config = rate_limit if rate_limit is not None else RateLimitConfig.from_env() + if config.enabled: + limiter = SlidingWindowLimiter(config) + + @app.middleware("http") + async def _rate_limit_middleware(request, call_next): + if request.method == _LIMITED_METHOD and request.url.path in _LIMITED_PATHS: + key = client_ip( + request.headers.get("x-forwarded-for"), + request.client.host if request.client else None, + ) + allowed, retry_after = limiter.check(key) + if not allowed: + # 被限请求在中间件层直接返回：不进 core.run，一分模型钱都不花。 + return JSONResponse( + status_code=429, + content={ + "error": "rate_limited", + "detail": "请求过于频繁，请稍后重试", + "retry_after": retry_after, + }, + headers={"Retry-After": str(retry_after)}, + ) + return await call_next(request) + + @app.get("/health") + async def health() -> dict: + return {"status": "ok", "commit": commit} + + @app.get("/.well-known/xagent-verification.json") + async def verification() -> dict: + return {"schemaVersion": 1, "slug": slug, "commit": commit} + + @app.get("/v1/tools") + async def list_tools() -> list[dict]: + return core.list_tools() + + @app.post("/v1/agent/run") + async def run_agent(req: RunRequest) -> dict: + result = await core.run(req.task) + return { + "strategy": result.strategy.value, + "final_text": result.final_text, + "events": [ + {"type": e.type.value, "data": _jsonable(e.data)} for e in result.events + ], + } + + return app + + +def _jsonable(data: dict) -> dict: + out: dict[str, Any] = {} + for k, v in data.items(): + out[k] = v if isinstance(v, str | int | float | bool | list | dict | None) else str(v) + return out diff --git a/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/batteries/fastapi_server/ratelimit.py b/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/batteries/fastapi_server/ratelimit.py new file mode 100644 index 0000000..298d723 --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/batteries/fastapi_server/ratelimit.py @@ -0,0 +1,114 @@ +"""评审期限流：每 IP 滑动窗口限流 Battery（v0.3，纯标准库）。 + +威胁模型（如实声明）：本模块只防"误刷"——手滑重试、爬虫、失控循环； +**不防**蓄意伪造 X-Forwarded-For 的分布式攻击（那需要鉴权/人机验证，超出 v0.3）。 +客户端身份取 XFF 最左非空 IP（Render 边缘代理会附加 XFF），缺失回退对端地址。 + +TODO(v0.4)：全局兜底限流（跨实例/全实例总配额）暂不做——免费层单实例， +分布式计数属后续议题；目前只有每 IP 维度。 +""" + +from __future__ import annotations + +import math +import os +import time +import warnings +from collections import deque +from collections.abc import Callable +from dataclasses import dataclass, field +from threading import Lock + +_ENABLED_ENV = "YAI_RATE_LIMIT_ENABLED" +_PER_MINUTE_ENV = "YAI_RATE_LIMIT_PER_MINUTE" +_WINDOW_ENV = "YAI_RATE_LIMIT_WINDOW_SECONDS" + + +def _truthy_enabled(raw: str | None) -> bool: + """enabled 解析：未设置视为开启；显式 0/false/no/off 才关闭。""" + if raw is None or not raw.strip(): + return True + return raw.strip().lower() not in {"0", "false", "no", "off"} + + +def _parse_positive_int(raw: str | None, env_name: str, default: int) -> int: + """正整数解析：未设置/空白回退默认（静默）；非法值回退默认 + warning。""" + if raw is None or not raw.strip(): + return default + try: + value = int(raw.strip()) + except ValueError: + warnings.warn(f"{env_name}={raw!r} 不是合法整数，回退默认值 {default}", stacklevel=2) + return default + if value <= 0: + warnings.warn(f"{env_name}={value} 必须为正整数，回退默认值 {default}", stacklevel=2) + return default + return value + + +@dataclass +class RateLimitConfig: + """限流配置；默认值（开启 / 30 次 / 60 秒）是对外承诺，改动须先改 10-plan。""" + + enabled: bool = True + per_minute: int = 30 + window_seconds: int = 60 + time_func: Callable[[], float] = field(default=time.monotonic) + + @classmethod + def from_env(cls, env: dict[str, str] | None = None) -> RateLimitConfig: + """从环境变量构造；env=None 读真实 os.environ，测试注入假字典。""" + environ = env if env is not None else os.environ + return cls( + enabled=_truthy_enabled(environ.get(_ENABLED_ENV)), + per_minute=_parse_positive_int( + environ.get(_PER_MINUTE_ENV), _PER_MINUTE_ENV, 30 + ), + window_seconds=_parse_positive_int( + environ.get(_WINDOW_ENV), _WINDOW_ENV, 60 + ), + ) + + +class SlidingWindowLimiter: + """每 key 一个时间戳 deque；请求时先清窗口外时间戳，再判断是否超限。 + + 状态只在内存（进程重启清零），不落盘、不引 Redis。 + """ + + def __init__(self, config: RateLimitConfig) -> None: + self._per_minute = config.per_minute + self._window = config.window_seconds + self._time_func = config.time_func + self._hits: dict[str, deque[float]] = {} + # 防御性互斥：目标路由是 async 且 deque 操作无 await 间隙，单事件循环下 + # 理论原子；但 TestClient / 将来同步路由会跨线程，锁成本近乎为零。 + self._lock = Lock() + + def check(self, key: str) -> tuple[bool, int]: + """返回 (是否放行, 超限时建议等待的整秒数)。""" + now = self._time_func() + with self._lock: + hits = self._hits.setdefault(key, deque()) + # 窗口边界用 <= 清除：正好等于窗口的请求视为过期。 + cutoff = now - self._window + while hits and hits[0] <= cutoff: + hits.popleft() + if len(hits) >= self._per_minute: + oldest = hits[0] + retry_after = max(1, math.ceil(oldest + self._window - now)) + return False, retry_after + hits.append(now) + return True, 0 + + +def client_ip(x_forwarded_for: str | None, peer_host: str | None) -> str: + """XFF 取最左非空段；缺失回退对端地址；再缺省 "unknown"。""" + if x_forwarded_for: + for part in x_forwarded_for.split(","): + candidate = part.strip() + if candidate: + return candidate + if peer_host: + return peer_host + return "unknown" diff --git a/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/channels/__init__.py b/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/channels/__init__.py new file mode 100644 index 0000000..9026842 --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/channels/__init__.py @@ -0,0 +1,4 @@ +from yai_core.channels.cli import CliChannel +from yai_core.channels.collect import CollectChannel + +__all__ = ["CliChannel", "CollectChannel"] diff --git a/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/channels/cli.py b/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/channels/cli.py new file mode 100644 index 0000000..6deb5a1 --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/channels/cli.py @@ -0,0 +1,40 @@ +from __future__ import annotations + +import asyncio + +from yai_core.types import AgentEvent, EventType + +_LABELS = { + EventType.STRATEGY_SELECTED: "策略", + EventType.PLAN_CREATED: "计划", + EventType.MODEL_MESSAGE: "回复", + EventType.TOOL_CALL: "调用工具", + EventType.TOOL_RESULT: "工具结果", + EventType.PERMISSION_ASKED: "权限确认", + EventType.CLARIFY_REQUESTED: "需要澄清", + EventType.ERROR: "错误", +} + + +class CliChannel: + """终端通道：把 Observer 事件流打印成人可读的过程。""" + + async def emit(self, event: AgentEvent) -> None: + label = _LABELS.get(event.type, event.type.value) + if event.type == EventType.TOOL_CALL: + print(f" [{label}] {event.data['tool']}({event.data['arguments']})") + elif event.type == EventType.STRATEGY_SELECTED: + print(f" [{label}] {event.data['strategy']}") + elif event.type == EventType.MODEL_MESSAGE: + print(f" [{label}] {event.data.get('text', '')}") + else: + print(f" [{label}] {event.data}") + + async def ask(self, question: str) -> str: + return await asyncio.to_thread(input, f" [澄清] {question} > ") + + async def confirm(self, tool_name: str, arguments: dict) -> bool: + answer = await asyncio.to_thread( + input, f" [确认] 允许执行 {tool_name}({arguments})? [y/N] " + ) + return answer.strip().lower() in ("y", "yes", "是") diff --git a/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/channels/collect.py b/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/channels/collect.py new file mode 100644 index 0000000..285772b --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/channels/collect.py @@ -0,0 +1,21 @@ +from __future__ import annotations + +from yai_core.types import AgentEvent + + +class CollectChannel: + """收集全部事件的通道：测试、API Battery、批处理使用。""" + + def __init__(self, *, auto_confirm: bool = True, default_answer: str = "") -> None: + self.events: list[AgentEvent] = [] + self.auto_confirm = auto_confirm + self.default_answer = default_answer + + async def emit(self, event: AgentEvent) -> None: + self.events.append(event) + + async def ask(self, question: str) -> str: + return self.default_answer + + async def confirm(self, tool_name: str, arguments: dict) -> bool: + return self.auto_confirm diff --git a/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/core.py b/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/core.py new file mode 100644 index 0000000..474a330 --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/core.py @@ -0,0 +1,97 @@ +"""AgentCore 门面：宿主接入的唯一入口。 + + from yai_core import AgentCore + core = AgentCore.auto(my_app) # 内省宿主能力，自动注册工具 + result = await core.run("整理本周笔记") # 自适应选策略/工具/模型 +""" + +from __future__ import annotations + +from collections.abc import AsyncIterator + +from yai_core.channels import CollectChannel +from yai_core.discovery import discover +from yai_core.kernel import AdaptiveRouter, AgentLoop +from yai_core.memory import InMemoryStore +from yai_core.policy import AllowlistPolicy +from yai_core.spi import Channel, MemoryStore, ModelProvider, PermissionPolicy +from yai_core.tools import ToolExecutor, ToolRegistry +from yai_core.types import AgentEvent, RunResult, ToolSpec + + +class AgentCore: + def __init__( + self, + model: ModelProvider, + *, + channel: Channel | None = None, + memory: MemoryStore | None = None, + policy: PermissionPolicy | None = None, + router: AdaptiveRouter | None = None, + auto_approve_tools: bool = True, + llm_router: bool = False, + ) -> None: + self.model = model + self.registry = ToolRegistry() + self.channel = channel or CollectChannel() + self.memory = memory or InMemoryStore() + self.policy = policy or AllowlistPolicy(mode="allow_all" if auto_approve_tools else "auto") + # llm_router=True 时把模型注入路由器：先 LLM 分类、失败回退规则； + # 默认关闭，保持零额外模型调用、离线测试完全确定。 + if router is not None: + self.router = router + else: + self.router = AdaptiveRouter(model=model if llm_router else None) + self.executor = ToolExecutor(self.registry, self.policy, self.channel) + self._loop = AgentLoop( + model=self.model, + registry=self.registry, + executor=self.executor, + channel=self.channel, + memory=self.memory, + router=self.router, + ) + + # ---------- 接入 ---------- + + @classmethod + def auto(cls, host: object, model: ModelProvider, **kwargs: object) -> AgentCore: + """内省宿主模块/对象，自动发现并注册全部公开能力。""" + core = cls(model, **kwargs) # type: ignore[arg-type] + core.register_tools(discover(host)) + return core + + def register_tools(self, specs: list[ToolSpec]) -> None: + self.registry.register_many(specs) + + def list_tools(self) -> list[dict]: + return [ + {"name": s.name, "description": s.description, "source": s.source} + for s in self.registry.all() + ] + + # ---------- 运行 ---------- + + async def astream(self, task: str) -> AsyncIterator[AgentEvent]: + async for event in self._loop.astream(task): + await self.channel.emit(event) + yield event + + async def run(self, task: str) -> RunResult: + events: list[AgentEvent] = [] + final_text = "" + strategy = None + async for event in self.astream(task): + events.append(event) + data = event.data + if "strategy" in data: + from yai_core.types import Strategy + + strategy = Strategy(data["strategy"]) + if event.type.value == "done": + final_text = data.get("final_text", "") + return RunResult( + strategy=strategy or self.router.classify(task, self.registry), + events=events, + final_text=final_text, + ) diff --git a/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/discovery/__init__.py b/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/discovery/__init__.py new file mode 100644 index 0000000..0e330c2 --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/discovery/__init__.py @@ -0,0 +1,5 @@ +"""能力自发现：把宿主已有的函数/对象自动转成 ToolSpec。""" + +from yai_core.discovery.introspect import build_spec, discover + +__all__ = ["build_spec", "discover"] diff --git a/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/discovery/introspect.py b/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/discovery/introspect.py new file mode 100644 index 0000000..84e49b4 --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/discovery/introspect.py @@ -0,0 +1,100 @@ +"""Python 函数内省：type hints + docstring -> JSON Schema 工具规格。 + +这是"宿主只声明能力、Core 自动长出 Agent"的第一块基石。 +v0.2 计划：openapi.py（OpenAPI 文档 -> 工具）、mcp.py（MCP tools/list -> 工具）。 +""" + +from __future__ import annotations + +import inspect +import types +from typing import Any, get_args, get_origin + +from yai_core.types import ToolSpec + +_PY_TO_JSON: dict[type, str] = { + str: "string", + int: "integer", + float: "number", + bool: "boolean", + list: "array", + dict: "object", +} + + +def _annotation_to_json_type(annotation: Any) -> tuple[str, bool]: + """返回 (json 类型, 是否可空)。无法识别时回退为 string。""" + if annotation is inspect.Parameter.empty: + return "string", False + # Optional[X] / X | None + origin = get_origin(annotation) + if origin in (types.UnionType, getattr(__import__("typing"), "Union", object)): + args = [a for a in get_args(annotation) if a is not type(None)] + nullable = len(args) != len(get_args(annotation)) + if args: + return _PY_TO_JSON.get(args[0], "string"), nullable + return _PY_TO_JSON.get(annotation, "string"), False + + +def build_spec(fn: Any, *, name: str | None = None, source: str = "native") -> ToolSpec: + """把一个 Python 可调用对象转换成 ToolSpec。""" + if not callable(fn): + raise TypeError(f"build_spec 需要可调用对象，得到 {type(fn)!r}") + + sig = inspect.signature(fn) + properties: dict[str, Any] = {} + required: list[str] = [] + + for param_name, param in sig.parameters.items(): + if param.kind in (inspect.Parameter.VAR_POSITIONAL, inspect.Parameter.VAR_KEYWORD): + continue + json_type, nullable = _annotation_to_json_type(param.annotation) + prop: dict[str, Any] = {"type": json_type} + if param.default is inspect.Parameter.empty: + required.append(param_name) + else: + prop["default"] = param.default + if nullable: + prop["type"] = [json_type, "null"] + properties[param_name] = prop + + doc = inspect.getdoc(fn) or "" + description = doc.split("\n\n", 1)[0].strip() or name or fn.__name__ + + schema: dict[str, Any] = {"type": "object", "properties": properties} + if required: + schema["required"] = required + + return ToolSpec( + name=name or fn.__name__, + description=description, + input_schema=schema, + handler=fn, + source=source, # type: ignore[arg-type] + ) + + +def discover(host: Any) -> list[ToolSpec]: + """从模块 / 类实例 / 对象上自动发现公开可调用能力。 + + - 模块：只收该模块内定义的函数（避免把 import 进来的函数误注册） + - 对象实例：收公开方法（不以 _ 开头） + """ + specs: list[ToolSpec] = [] + + if inspect.ismodule(host): + module_name = host.__name__ + members = inspect.getmembers(host, inspect.isfunction) + for member_name, fn in members: + if member_name.startswith("_"): + continue + if getattr(fn, "__module__", None) != module_name: + continue + specs.append(build_spec(fn)) + return specs + + for member_name, fn in inspect.getmembers(host, inspect.ismethod): + if member_name.startswith("_"): + continue + specs.append(build_spec(fn)) + return specs diff --git a/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/integrations/__init__.py b/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/integrations/__init__.py new file mode 100644 index 0000000..ee305dd --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/integrations/__init__.py @@ -0,0 +1,5 @@ +"""可选集成层：把外部生态能力接入内核，全部懒加载、零硬依赖。 + +- integrations.mcp：MCP Client，把外部 MCP Server 的工具注册进 ToolRegistry。 +- integrations.openapi：OpenAPI 发现，把任意 OpenAPI 3 REST API 自动注册为工具。 +""" diff --git a/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/integrations/mcp/__init__.py b/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/integrations/mcp/__init__.py new file mode 100644 index 0000000..26c20d0 --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/integrations/mcp/__init__.py @@ -0,0 +1,17 @@ +"""MCP Client 集成：把外部 MCP Server 的工具变成 Core 自己的工具。""" + +from yai_core.integrations.mcp.client import ( + McpServerConfig, + McpToolBridge, + attach_mcp_tools, + config_from_env, + sanitize_schema, +) + +__all__ = [ + "McpServerConfig", + "McpToolBridge", + "attach_mcp_tools", + "config_from_env", + "sanitize_schema", +] diff --git a/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/integrations/mcp/client.py b/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/integrations/mcp/client.py new file mode 100644 index 0000000..e6bd247 --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/integrations/mcp/client.py @@ -0,0 +1,179 @@ +"""MCP Client 桥接层：外部 MCP Server 工具 → ToolRegistry 里的 ToolSpec。 + +设计要点（对应内核红线）： +1. 顶层不 import mcp：内核本体零第三方硬依赖，mcp 是可选依赖（pyproject 的 + [mcp] extra），只在 connect() 内部懒加载；没装时给出可操作的报错。 +2. 工具同构：MCP 工具被转换成 ToolSpec(source="mcp")，handler 是一个异步闭包。 + Router / Loop / Executor 完全感知不到工具在本机还是远端 MCP Server 上—— + 它们只面对统一的 ToolSpec，这就是"Native 与 MCP 统一"的落点。 +3. 结果归一：MCP CallToolResult 的 content 文本块 / structured_content / + is_error 三种形态在这里被翻译成 Executor 熟悉的"返回值或抛异常"。 +""" + +from __future__ import annotations + +import os +import shlex +from dataclasses import dataclass, field +from typing import Any + +from yai_core.tools.schema import EMPTY_OBJECT_SCHEMA, sanitize_schema +from yai_core.types import ToolSpec + +# 兼容别名：本模块下方代码沿用旧名 _EMPTY_SCHEMA，保持零改动。 +_EMPTY_SCHEMA = EMPTY_OBJECT_SCHEMA + + +@dataclass +class McpServerConfig: + """一个 MCP Server 的连接配置，url / command / server 三选一。 + + - url：Streamable HTTP（如 https://example.com/mcp），部署形态最常用； + - command(+args/env)：拉起本地 stdio 子进程作为 MCP Server； + - server：已构造好的 MCPServer 实例，内存直连（主要给离线测试用）； + - prefix：工具名前缀（如 "demo__"），多个 Server 工具重名时去重；默认不加。 + """ + + alias: str + url: str | None = None + command: str | None = None + args: list[str] = field(default_factory=list) + env: dict[str, str] | None = None + prefix: str = "" + server: Any | None = None + + +def config_from_env( + *, + alias: str = "remote", + url_env: str = "MCP_SERVER_URL", + command_env: str = "MCP_SERVER_COMMAND", + env: dict[str, str] | None = None, +) -> McpServerConfig | None: + """从环境变量构造 MCP Server 配置；两个变量都没设置时返回 None。 + + - ：Streamable HTTP URL，部署形态最常用（如线上挂公共 MCP Server）； + - ：stdio 启动命令（空格分词，Windows 按系统规则切分）。 + 让"是否接外部 MCP、接哪个"成为部署期配置，代码不用改。 + """ + environ = os.environ if env is None else env + url = environ.get(url_env) + if url: + return McpServerConfig(alias=alias, url=url) + command_line = environ.get(command_env) + if command_line: + parts = shlex.split(command_line, posix=(os.name != "nt")) + if parts: + return McpServerConfig(alias=alias, command=parts[0], args=parts[1:]) + return None + + +def _flatten_call_result(result: Any) -> Any: + """把 MCP CallToolResult 翻译成工具返回值（可被 json.dumps 序列化）。 + + 顺序：is_error → 抛异常（交给 ToolExecutor 走失败回灌，模型能看到错误）； + 否则优先 content 里的文本块（MCP 面向 LLM 的规范输出）； + 没有文本再回退 structured_content；都没有返回空字符串。 + """ + content = getattr(result, "content", []) or [] + if getattr(result, "is_error", False): + texts = [b.text for b in content if getattr(b, "text", None)] + raise RuntimeError("; ".join(texts) or "MCP 工具返回错误") + texts = [b.text for b in content if getattr(b, "text", None)] + if texts: + return "\n".join(texts) + structured = getattr(result, "structured_content", None) + if structured is not None: + return structured + return "" + + +class McpToolBridge: + """一个 MCP Server 连接 ↔ 注册到 ToolRegistry 的一组 ToolSpec。 + + 用法:: + + bridge = McpToolBridge(McpServerConfig(alias="demo", url="https://x/mcp")) + specs = await bridge.connect() # 建连 + list_tools + 生成 ToolSpec + core.register_tools(specs) + ... + await bridge.aclose() + + 也支持 async with 自动关连接。 + """ + + def __init__(self, config: McpServerConfig) -> None: + self.config = config + self._client: Any = None + self._specs: list[ToolSpec] = [] + + async def __aenter__(self) -> McpToolBridge: + await self.connect() + return self + + async def __aexit__(self, *exc: object) -> None: + await self.aclose() + + async def connect(self) -> list[ToolSpec]: + # 懒加载：只有真正使用 MCP 集成时才要求安装 mcp 包。 + try: + from mcp import Client, StdioServerParameters + except ImportError as exc: + raise ImportError( + "MCP 集成需要可选依赖：uv sync --extra mcp（或 pip install 'yai-agent-core[mcp]'）" + ) from exc + + self._client = Client(self._build_target(StdioServerParameters)) + await self._client.__aenter__() + listed = await self._client.list_tools() + self._specs = [self._to_spec(tool) for tool in listed.tools] + return self._specs + + def _build_target(self, stdio_params_cls: Any) -> Any: + """把配置翻译成 mcp.Client 接受的三种 target：URL / stdio 参数 / Server 实例。""" + c = self.config + chosen = sum(x is not None for x in (c.url, c.command, c.server)) + if chosen != 1: + raise ValueError("McpServerConfig 必须且只能提供 url / command / server 之一") + if c.url is not None: + return c.url + if c.server is not None: + return c.server + return stdio_params_cls(command=c.command, args=c.args, env=c.env) + + def _to_spec(self, tool: Any) -> ToolSpec: + """一个 MCP Tool 描述 → 一个统一 ToolSpec。""" + remote_name = tool.name + local_name = f"{self.config.prefix}{remote_name}" + schema = sanitize_schema(getattr(tool, "input_schema", None)) or dict(_EMPTY_SCHEMA) + + async def handler(**kwargs: Any) -> Any: + # 闭包按值捕获 remote_name：本地注册名可能带前缀，远端只认工具原名。 + result = await self._client.call_tool(remote_name, kwargs) + return _flatten_call_result(result) + + return ToolSpec( + name=local_name, + description=getattr(tool, "description", "") or remote_name, + input_schema=schema, + handler=handler, + source="mcp", + ) + + async def aclose(self) -> None: + if self._client is not None: + await self._client.__aexit__(None, None, None) + self._client = None + + @property + def specs(self) -> list[ToolSpec]: + """connect 之后可用：本次从该 Server 注册的工具规格（副本）。""" + return list(self._specs) + + +async def attach_mcp_tools(registry: Any, config: McpServerConfig) -> McpToolBridge: + """便捷函数：连接 MCP Server 并把工具直接注册进 ToolRegistry，返回 bridge 供关闭。""" + bridge = McpToolBridge(config) + specs = await bridge.connect() + registry.register_many(specs) + return bridge diff --git a/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/integrations/openapi/__init__.py b/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/integrations/openapi/__init__.py new file mode 100644 index 0000000..4803a0a --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/integrations/openapi/__init__.py @@ -0,0 +1,29 @@ +"""OpenAPI 发现集成：把任意符合 OpenAPI 3 的 REST API 自动注册为 Core 工具。 + +与 MCP 桥同构：懒加载 httpx/pyyaml（[openapi] 可选依赖），发现结果统一成 +ToolSpec(source="openapi")，Router / Loop / Executor 感知不到工具来自 REST +（alias 仅用于日志与 notes）。 +""" + +from yai_core.integrations.openapi.client import ( + OpenApiToolBridge, + attach_openapi_tools, +) +from yai_core.integrations.openapi.discovery import OperationPlan, plan_operations +from yai_core.integrations.openapi.spec import ( + OpenApiSpecConfig, + config_from_env, + load_spec, + resolve_refs, +) + +__all__ = [ + "OpenApiSpecConfig", + "OpenApiToolBridge", + "OperationPlan", + "attach_openapi_tools", + "config_from_env", + "load_spec", + "plan_operations", + "resolve_refs", +] diff --git a/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/integrations/openapi/client.py b/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/integrations/openapi/client.py new file mode 100644 index 0000000..a175f85 --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/integrations/openapi/client.py @@ -0,0 +1,235 @@ +"""执行阶段：OpenAPI 工具桥。 + +一个 OpenAPI 描述 = 一个桥：connect() 载入/展开/发现并注册 ToolSpec， +每个工具是一个闭包 handler，负责鉴权、填路径、拼 query、发 body、归一响应。 +httpx 只在 connect() 内懒加载；测试通过 transport= 注入 httpx.MockTransport，全程离线。 +""" + +from __future__ import annotations + +import os +from typing import Any +from urllib.parse import quote + +from yai_core.integrations.openapi.discovery import OperationPlan, plan_operations +from yai_core.integrations.openapi.spec import ( + OpenApiSpecConfig, + load_spec, + resolve_base_url, + resolve_refs, +) +from yai_core.types import ToolSpec + +_SUPPORTED_SECURITY = {"http", "apiKey"} + + +class OpenApiToolBridge: + """发现并执行一个 OpenAPI 描述暴露的 REST 操作。""" + + def __init__(self, config: OpenApiSpecConfig, *, transport: Any = None) -> None: + self.config = config + self._transport = transport # 测试注入 httpx.MockTransport；生产为 None + self._client: Any = None + self._specs: list[ToolSpec] = [] + self._notes: list[str] = [] + self._spec: dict | None = None + self._plans: list[OperationPlan] = [] + self._base_url: str | None = None + self._security_schemes: dict[str, dict] = {} + + @property + def specs(self) -> list[ToolSpec]: + return list(self._specs) + + @property + def notes(self) -> list[str]: + return list(self._notes) + + async def connect(self) -> list[ToolSpec]: + try: + import httpx + except ImportError as exc: + raise ImportError( + "OpenAPI 集成需要可选依赖：uv sync --extra openapi" + "（或 pip install 'yai-agent-core[openapi]'）" + ) from exc + + raw = load_spec(self.config, transport=self._transport) + spec, ref_notes = resolve_refs(raw) + self._notes.extend(ref_notes) + plans, plan_notes = plan_operations(spec, self.config) + self._notes.extend(plan_notes) + + self._spec = spec + self._plans = plans + self._base_url = resolve_base_url(self.config, spec) + self._security_schemes = ( + (spec.get("components") or {}).get("securitySchemes") or {} + ) + self._audit_security(plans) + + self._client = httpx.AsyncClient( + timeout=httpx.Timeout(self.config.timeout), + transport=self._transport, + headers=dict(self.config.extra_headers), + ) + self._specs = [self._plan_to_spec(plan) for plan in plans] + return self.specs + + def _audit_security(self, plans: list[OperationPlan]) -> None: + """注册期审计：oauth2/basic/mutualTLS 暂不支持，记 note 但不阻断发现。""" + seen: set[str] = set() + for plan in plans: + for requirement in plan.security: + for scheme_name in requirement: + scheme = self._security_schemes.get(scheme_name) + if scheme is None: + continue + kind = scheme.get("type") + if kind not in _SUPPORTED_SECURITY and scheme_name not in seen: + seen.add(scheme_name) + self._notes.append( + f"鉴权方案 {scheme_name}（{kind}）暂不支持，" + "相关工具将按匿名请求发送" + ) + + async def aclose(self) -> None: + if self._client is not None: + await self._client.aclose() + self._client = None + + async def __aenter__(self) -> OpenApiToolBridge: + await self.connect() + return self + + async def __aexit__(self, *exc: object) -> None: + await self.aclose() + + # ---------- 执行期小步骤（每个都可独立推理） ---------- + + def _token_from_env(self) -> str | None: + env_name = self.config.auth_token_env + if not env_name: + return None + raw = (os.environ.get(env_name) or "").strip() + return raw or None + + async def _auth_for(self, plan: OperationPlan) -> tuple[dict, dict]: + """按 security 要求挑第一个能满足的方案；都不满足且不允许匿名 → 调用期报错。""" + headers: dict[str, str] = {} + query: dict[str, str] = {} + requirements = plan.security or [] + allows_anonymous = any(not requirement for requirement in requirements) + for requirement in requirements: + for scheme_name, _scopes in requirement.items(): + scheme = self._security_schemes.get(scheme_name) + if scheme is None: + continue + kind = scheme.get("type") + if kind == "http" and str(scheme.get("scheme", "")).lower() == "bearer": + token = self._token_from_env() + if token: + headers["Authorization"] = f"Bearer {token}" + return headers, query + elif kind == "apiKey": + token = self._token_from_env() + if token: + where = scheme.get("in") + key_name = scheme.get("name", "X-Api-Key") + if where == "header": + headers[key_name] = token + elif where == "query": + query[key_name] = token + return headers, query + if requirements and not allows_anonymous: + raise RuntimeError( + f"工具 {plan.name} 需要鉴权，但环境变量 {self.config.auth_token_env} 未设置令牌" + ) + return headers, query + + def _build_path(self, plan: OperationPlan, kwargs: dict) -> str: + path = plan.path_template + for name in plan.path_params: + if name not in kwargs: + raise RuntimeError(f"调用 {plan.name} 缺少路径参数：{name}") + # safe=""：路径段里的 / 也要编码，避免参数值破坏路径结构。 + path = path.replace("{" + name + "}", quote(str(kwargs[name]), safe="")) + return path + + def _build_query(self, plan: OperationPlan, kwargs: dict) -> dict: + query: dict[str, Any] = {} + for name in plan.query_params: + if name in kwargs and kwargs[name] is not None: + value = kwargs[name] + if isinstance(value, bool): + value = "true" if value else "false" # httpx 默认会渲染成 True/False + query[name] = value # list 值由 httpx 展开成重复键 + return query + + def _build_body(self, plan: OperationPlan, kwargs: dict) -> Any: + if not plan.body_fields: + return None + if plan.body_wrapped: + return kwargs.get("body") + return {name: kwargs[name] for name in plan.body_fields if name in kwargs} + + def _plan_to_spec(self, plan: OperationPlan) -> ToolSpec: + async def handler(**kwargs: Any) -> Any: + if self._client is None: + raise RuntimeError("OpenApiToolBridge 尚未 connect()") + if not self._base_url: + raise RuntimeError( + "spec 未声明 servers[0].url 且未配置 base_url_override，无法调用工具" + ) + auth_headers, auth_query = await self._auth_for(plan) + path = self._build_path(plan, kwargs) + query = self._build_query(plan, kwargs) + query.update(auth_query) + body = self._build_body(plan, kwargs) + + url = self._base_url.rstrip("/") + path + request_headers = dict(auth_headers) + if body is not None: + request_headers.setdefault("Content-Type", "application/json") + + resp = await self._client.request( + plan.method, + url, + params=query or None, + json=body if body is not None else None, + headers=request_headers, + ) + if resp.status_code == 204: + return "" + if resp.status_code < 200 or resp.status_code >= 300: + # 非 2xx 走工具错误通道（Executor 捕获 RuntimeError → tool_result 失败事件）。 + raise RuntimeError( + f"HTTP {resp.status_code} from {plan.method} {path}: {resp.text[:500]}" + ) + content_type = resp.headers.get("content-type", "") + if "application/json" in content_type.lower(): + return resp.json() + text = resp.text + if len(text) > self.config.max_result_chars: + return text[: self.config.max_result_chars] + "…[truncated]" + return text + + return ToolSpec( + name=plan.name, + description=plan.description, + input_schema=plan.input_schema, + handler=handler, + # 来源可枚举，与 types.ToolSpec.source 的 Literal 契约对齐；alias 只用于日志/notes。 + source="openapi", + ) + + +async def attach_openapi_tools( + registry: Any, config: OpenApiSpecConfig, *, transport: Any = None +) -> OpenApiToolBridge: + """发现并把工具注册进 registry，返回桥（宿主在停机时 await bridge.aclose()）。""" + bridge = OpenApiToolBridge(config, transport=transport) + specs = await bridge.connect() + for spec in specs: + registry.register(spec) + return bridge diff --git a/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/integrations/openapi/discovery.py b/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/integrations/openapi/discovery.py new file mode 100644 index 0000000..4a61123 --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/integrations/openapi/discovery.py @@ -0,0 +1,218 @@ +"""发现阶段：把 OpenAPI paths/operations 翻译成工具执行计划（OperationPlan）。 + +本模块纯函数、零 IO、零第三方依赖，输出交给 client.py 闭包执行。 +""" + +from __future__ import annotations + +import re +from dataclasses import dataclass, field +from typing import Any + +from yai_core.integrations.openapi.spec import ( + _HTTP_METHODS, + _READ_ONLY_METHODS, + OpenApiSpecConfig, +) +from yai_core.tools.schema import EMPTY_OBJECT_SCHEMA, sanitize_schema + + +@dataclass +class OperationPlan: + """一个 REST 操作翻译成工具的中间表示。""" + + name: str + description: str + input_schema: dict[str, Any] + method: str + path_template: str + path_params: tuple[str, ...] + query_params: tuple[str, ...] + body_fields: tuple[str, ...] + body_wrapped: bool + body_required: bool + security: list[dict] = field(default_factory=list) + + +def _camel_to_snake(segment: str) -> str: + """petId → pet_id；listPets → list_pets（小写边界前插下划线）。""" + return re.sub(r"(?<=[a-z0-9])(?=[A-Z])", "_", segment).lower() + + +def _clean_operation_id(operation_id: str) -> str: + """operationId 合法化：驼峰转蛇形、非法字符变下划线、截断 64 字符。""" + name = _camel_to_snake(operation_id) + name = re.sub(r"[^a-z0-9_-]+", "_", name).strip("_") + return name[:64].strip("_") + + +def _synthetic_name(method: str, path: str) -> str: + """没有 operationId 时合成：GET /pets/{petId} → get_pets_pet_id。""" + parts = [method.lower()] + for segment in path.strip("/").split("/"): + if not segment: + continue + segment = segment.strip("{}").replace("-", "_") + parts.append(_camel_to_snake(segment)) + return re.sub(r"[^a-z0-9_]+", "_", "_".join(parts))[:64].strip("_") + + +def _dedupe_name(name: str, used: set[str], notes: list[str]) -> str: + """同一 spec 内重名追加 __2/__3（跨来源重名由 ToolRegistry 直接报错，不在这里吞）。""" + if name not in used: + used.add(name) + return name + suffix = 2 + while f"{name}__{suffix}" in used: + suffix += 1 + final = f"{name}__{suffix}" + used.add(final) + notes.append(f"同一 spec 内工具名冲突，{name} 的第 {suffix - 1} 个重名操作改名为 {final}") + return final + + +def _parameter_property(parameter: dict) -> tuple[str, dict, bool]: + name = parameter["name"] + schema = sanitize_schema(parameter.get("schema") or {}) + if parameter.get("description") and isinstance(schema, dict): + schema.setdefault("description", parameter["description"]) + return name, schema, bool(parameter.get("required", False)) + + +def _merge_body( + properties: dict, required: list[str], body_schema: dict, notes: list[str] +) -> tuple[tuple[str, ...], bool]: + """requestBody 的 schema 并入入参：object 拍平合并；其他类型包成 {"body": ...}。""" + body_schema = sanitize_schema(body_schema) + if isinstance(body_schema, dict) and body_schema.get("type") == "object": + body_props = body_schema.get("properties") or {} + for name, sub in body_props.items(): + if name in properties: + notes.append(f"body 字段与路径/查询参数同名 {name}，body 侧覆盖") + properties[name] = sub + for name in body_schema.get("required") or []: + if name not in required: + required.append(name) + return tuple(body_props.keys()), False + properties["body"] = body_schema + return ("body",), True + + +def _path_allowed(path: str, config: OpenApiSpecConfig) -> bool: + """先 include 白名单（前缀匹配），再 exclude 黑名单。""" + if config.include_paths and not any( + path.startswith(prefix) for prefix in config.include_paths + ): + return False + if config.exclude_paths and any(path.startswith(prefix) for prefix in config.exclude_paths): + return False + return True + + +def plan_operations( + spec: dict, config: OpenApiSpecConfig +) -> tuple[list[OperationPlan], list[str]]: + """遍历 paths，产出操作计划列表与 notes（read_only 过滤、截断都在这里）。""" + notes: list[str] = [] + plans: list[OperationPlan] = [] + used_names: set[str] = set() + paths = spec.get("paths") or {} + + for path, path_item in paths.items(): + if not isinstance(path_item, dict): + continue + if "$ref" in path_item: + notes.append(f"路径级 $ref 不展开，跳过：{path}") + continue + if not _path_allowed(path, config): + continue + shared_parameters = path_item.get("parameters") or [] + for method, operation in path_item.items(): + method_l = method.lower() + if method_l not in _HTTP_METHODS or not isinstance(operation, dict): + continue + if config.read_only and method_l not in _READ_ONLY_METHODS: + continue + + properties: dict[str, Any] = {} + required: list[str] = [] + path_params: list[str] = [] + query_params: list[str] = [] + + # pathItem 级与 operation 级 parameters 合并（后者优先语义由后写覆盖体现）。 + for parameter in [*shared_parameters, *(operation.get("parameters") or [])]: + if not isinstance(parameter, dict): + continue + where = parameter.get("in") + if where not in {"path", "query"}: + continue # header / cookie 参数不暴露给模型（v0.2 边界） + name, sub_schema, is_required = _parameter_property(parameter) + properties[name] = sub_schema + if where == "path": + path_params.append(name) + if name not in required: + required.append(name) # OpenAPI 规定 path 参数恒为 required + else: + query_params.append(name) + if is_required and name not in required: + required.append(name) + + body_fields: tuple[str, ...] = () + body_wrapped = False + body_required = False + request_body = operation.get("requestBody") + if isinstance(request_body, dict): + content = request_body.get("content") or {} + json_entry = content.get("application/json") + if json_entry and isinstance(json_entry.get("schema"), dict): + body_fields, body_wrapped = _merge_body( + properties, required, json_entry["schema"], notes + ) + body_required = bool(request_body.get("required", False)) + if body_required and body_wrapped and "body" not in required: + required.append("body") + + operation_id = operation.get("operationId") + raw_name = ( + _clean_operation_id(operation_id) + if operation_id + else _synthetic_name(method_l, path) + ) + name = _dedupe_name(raw_name, used_names, notes) + if config.prefix: + name = f"{config.prefix}_{name}" + + summary = (operation.get("summary") or "").strip() + description = (operation.get("description") or "").strip() + tail = f"{summary} {description}".strip() + tool_description = f"[{method.upper()} {path}] {tail}".strip()[:1000] + + input_schema = sanitize_schema( + {"type": "object", "properties": properties, "required": required} + ) + if not properties: + input_schema = dict(EMPTY_OBJECT_SCHEMA) + + plans.append( + OperationPlan( + name=name, + description=tool_description, + input_schema=input_schema, + method=method.upper(), + path_template=path, + path_params=tuple(path_params), + query_params=tuple(query_params), + body_fields=body_fields, + body_wrapped=body_wrapped, + body_required=body_required, + # operation 级 security 缺省回退全局 security。 + security=operation.get("security", spec.get("security")) or [], + ) + ) + + if len(plans) > config.max_operations: + notes.append( + f"操作数 {len(plans)} 超过 max_operations={config.max_operations}，已截断" + ) + plans = plans[: config.max_operations] + return plans, notes diff --git a/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/integrations/openapi/spec.py b/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/integrations/openapi/spec.py new file mode 100644 index 0000000..d929458 --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/integrations/openapi/spec.py @@ -0,0 +1,203 @@ +"""OpenAPI 描述载入、版本校验与内部 $ref 展开。 + +顶层只 import 标准库；httpx / pyyaml 一律函数内懒加载（内核零硬依赖红线）。 +""" + +from __future__ import annotations + +import copy +import json +import os +from dataclasses import dataclass, field +from pathlib import Path +from typing import Any +from urllib.parse import urljoin + +_READ_ONLY_METHODS = frozenset({"get", "head"}) +_HTTP_METHODS = frozenset({"get", "post", "put", "patch", "delete", "head", "options"}) + + +@dataclass +class OpenApiSpecConfig: + """一个 OpenAPI 描述的接入配置。url / path / spec 三选一。""" + + alias: str = "rest" + url: str | None = None + path: str | Path | None = None + spec: dict | None = None + prefix: str = "" + base_url_override: str | None = None + auth_token_env: str | None = "OPENAPI_AUTH_TOKEN" + extra_headers: dict[str, str] = field(default_factory=dict) + read_only: bool = False + max_operations: int = 40 + include_paths: tuple[str, ...] = () + exclude_paths: tuple[str, ...] = () + timeout: float = 15.0 + max_spec_bytes: int = 2 * 1024 * 1024 + max_result_chars: int = 16_000 + + +def _truthy(value: str | None) -> bool: + return (value or "").strip().lower() in {"1", "true", "yes", "on"} + + +def config_from_env( + *, + alias: str = "rest", + url_env: str = "OPENAPI_SPEC_URL", + path_env: str = "OPENAPI_SPEC_PATH", + token_env: str = "OPENAPI_AUTH_TOKEN", + base_url_env: str = "OPENAPI_BASE_URL", + read_only_env: str = "OPENAPI_READ_ONLY", + env: dict[str, str] | None = None, +) -> OpenApiSpecConfig | None: + """从环境变量构造配置；URL 与 PATH 都没配时返回 None（装配方据此跳过）。""" + environ = os.environ if env is None else env + url = (environ.get(url_env) or "").strip() or None + raw_path = (environ.get(path_env) or "").strip() or None + if url is None and raw_path is None: + return None + base = (environ.get(base_url_env) or "").strip() or None + # 只记录变量名，不判断令牌是否存在：缺令牌由调用期报错，且报错要点名这个变量。 + return OpenApiSpecConfig( + alias=alias, + url=url, + path=Path(raw_path) if raw_path else None, + base_url_override=base, + auth_token_env=token_env, + read_only=_truthy(environ.get(read_only_env)), + ) + + +def _load_from_path(path: Path, max_bytes: int) -> dict: + p = Path(path).expanduser() + data = p.read_bytes() + if len(data) > max_bytes: + raise ValueError(f"OpenAPI 描述超过 {max_bytes} 字节上限：{p}") + suffix = p.suffix.lower() + if suffix in {".yaml", ".yml"}: + try: + import yaml # 懒加载：只有 YAML 描述才需要 pyyaml + except ImportError as exc: + raise ImportError( + "解析 YAML 形式的 OpenAPI 描述需要可选依赖：uv sync --extra openapi" + ) from exc + loaded = yaml.safe_load(data.decode("utf-8")) + else: + loaded = json.loads(data.decode("utf-8")) + if not isinstance(loaded, dict): + raise ValueError("OpenAPI 描述根节点必须是对象") + return loaded + + +def _load_from_url(config: OpenApiSpecConfig, transport: Any) -> dict: + try: + import httpx # 懒加载 + except ImportError as exc: + raise ImportError( + "OpenAPI 集成需要可选依赖：uv sync --extra openapi" + "（或 pip install 'yai-agent-core[openapi]'）" + ) from exc + # transport 仅供测试注入 httpx.MockTransport；生产为 None，走真实网络。 + with httpx.Client(timeout=config.timeout, transport=transport) as client: + resp = client.get(config.url) # type: ignore[arg-type] + if resp.status_code < 200 or resp.status_code >= 300: + raise RuntimeError(f"拉取 OpenAPI 描述失败：HTTP {resp.status_code}") + if len(resp.content) > config.max_spec_bytes: + raise ValueError(f"OpenAPI 描述超过 {config.max_spec_bytes} 字节上限") + ctype = resp.headers.get("content-type", "") + if "yaml" in ctype or str(config.url).endswith((".yaml", ".yml")): + try: + import yaml + except ImportError as exc: + raise ImportError( + "解析 YAML 形式的 OpenAPI 描述需要可选依赖：uv sync --extra openapi" + ) from exc + loaded = yaml.safe_load(resp.text) + else: + loaded = resp.json() + if not isinstance(loaded, dict): + raise ValueError("OpenAPI 描述根节点必须是对象") + return loaded + + +def load_spec(config: OpenApiSpecConfig, *, transport: Any = None) -> dict: + """三选一载入（dict / 文件 / URL）并校验是 OpenAPI 3；非法输入给可操作错误。""" + if config.spec is not None: + raw = config.spec + elif config.path is not None: + raw = _load_from_path(config.path, config.max_spec_bytes) + elif config.url is not None: + raw = _load_from_url(config, transport) + else: + raise ValueError("OpenApiSpecConfig 必须提供 url / path / spec 之一") + if not isinstance(raw, dict): + raise ValueError("OpenAPI 描述根节点必须是对象") + if "openapi" not in raw: + if str(raw.get("swagger", "")).startswith("2"): + raise ValueError("不支持 Swagger 2.0，请先转换为 OpenAPI 3（3.0.x / 3.1.x）") + raise ValueError("缺少 openapi 版本字段，不是合法的 OpenAPI 3 描述") + if not str(raw["openapi"]).startswith("3."): + raise ValueError(f"仅支持 OpenAPI 3.x，收到版本：{raw['openapi']}") + return raw + + +def _resolve_pointer(root: dict, pointer: str) -> Any: + """按 JSON Pointer（#/a/b/1）在根节点里取目标。""" + cur: Any = root + for part in pointer.lstrip("#/").split("/"): + part = part.replace("~1", "/").replace("~0", "~") # Pointer 转义 + cur = cur[part] + return cur + + +def resolve_refs(spec: dict) -> tuple[dict, list[str]]: + """内联展开文档内部 $ref，返回（深拷贝后的新 spec, notes）。 + + - 内部 $ref（#/...）：递归内联；正在展开的引用链上再次命中 = 循环，保留 $ref 原样并记 note； + - 外部 $ref（http/另一文件）：不解析，原样保留并记 note（v0.2 不跨文档抓取）。 + """ + notes: list[str] = [] + root = copy.deepcopy(spec) + + def walk(node: Any, stack: frozenset[str]) -> Any: + if isinstance(node, dict): + ref = node.get("$ref") + if isinstance(ref, str): + if not ref.startswith("#"): + note = f"外部 $ref 不解析，原样保留：{ref}" + if note not in notes: + notes.append(note) + return {"$ref": ref} + if ref in stack: + note = f"检测到循环 $ref：{ref}，该处保留原样" + if note not in notes: + notes.append(note) + return {"$ref": ref} + target = _resolve_pointer(root, ref) + resolved = walk(target, stack | {ref}) + siblings = {k: v for k, v in node.items() if k != "$ref"} + if isinstance(resolved, dict) and siblings: + # 3.1 允许 $ref 与兄弟键共存：内联目标后用兄弟键覆盖同名字段。 + return {**resolved, **{k: walk(v, stack) for k, v in siblings.items()}} + return resolved + return {k: walk(v, stack) for k, v in node.items()} + if isinstance(node, list): + return [walk(v, stack) for v in node] + return node + + return walk(root, frozenset()), notes + + +def resolve_base_url(config: OpenApiSpecConfig, spec: dict) -> str | None: + """base_url 优先级：显式 override > servers[0].url；相对 server 地址按 spec URL 解析。""" + if config.base_url_override: + return config.base_url_override + servers = spec.get("servers") or [] + if servers and isinstance(servers[0], dict) and servers[0].get("url"): + url = servers[0]["url"] + if config.url and not url.startswith("http"): + return urljoin(config.url, url) + return url + return None diff --git a/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/kernel/__init__.py b/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/kernel/__init__.py new file mode 100644 index 0000000..ba7f670 --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/kernel/__init__.py @@ -0,0 +1,7 @@ +"""YAI Kernel：自适应路由 + Agent Loop + 上下文管理。""" + +from yai_core.kernel.context import Context +from yai_core.kernel.loop import AgentLoop +from yai_core.kernel.router import AdaptiveRouter, RouteDecision + +__all__ = ["AdaptiveRouter", "AgentLoop", "Context", "RouteDecision"] diff --git a/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/kernel/context.py b/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/kernel/context.py new file mode 100644 index 0000000..2f26b8c --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/kernel/context.py @@ -0,0 +1,42 @@ +from __future__ import annotations + +from yai_core.types import ChatMessage + + +class Context: + """单次运行的对话上下文。v0.1 用朴素字符估算做 token 预算，v2 换 tiktoken。""" + + def __init__(self, system_prompt: str, *, max_chars: int = 24000) -> None: + self.max_chars = max_chars + self.messages: list[ChatMessage] = [ChatMessage(role="system", content=system_prompt)] + + def add(self, message: ChatMessage) -> None: + self.messages.append(message) + self._compact() + + def _compact(self) -> None: + """超预算时丢弃最旧的整轮历史：system 永留，且至少保留最后一轮。 + + v0.3 修复：旧实现按下标逐个丢，可能从 assistant(tool_calls)/tool 配对中间 + 切开，发给 OpenAI 兼容接口会直接 400。现改为把候补丢弃边界**向后对齐到 + 轮首**（role == "user"），规则与 memory/retention.py 同源；为避免 kernel + 反向依赖 memory 包，这里保留一份私有实现，两处改动必须同步（第 13 章讲义）。 + 候补边界之后没有新一轮时，宁可超预算也保留最后一轮（含其工具消息）。 + """ + total = sum(len(m.content) for m in self.messages) + i = 1 + while total > self.max_chars and i < len(self.messages) - 1: + total -= len(self.messages[i].content) + i += 1 + if i <= 1: + return + aligned = i + while aligned < len(self.messages) and self.messages[aligned].role != "user": + aligned += 1 + if aligned >= len(self.messages): + # 候补边界之后没有新一轮：保留最后一轮，不做裁剪。 + return + self.messages = [self.messages[0], *self.messages[aligned:]] + + def llm_messages(self) -> list[dict]: + return [m.to_llm_dict() for m in self.messages] diff --git a/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/kernel/loop.py b/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/kernel/loop.py new file mode 100644 index 0000000..2824c1c --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/kernel/loop.py @@ -0,0 +1,177 @@ +"""Agent Loop：按 Adaptive Router 选定的策略执行任务。 + +- direct: 一次模型调用直接回答 +- react: 推理 <-> 工具调用循环，直到模型不再调用工具 +- plan: 先生成步骤计划，再带计划进入 react 循环 +- clarify: 通过 Channel 反问后重新路由 +""" + +from __future__ import annotations + +import json +import re +from collections.abc import AsyncIterator + +from yai_core.kernel.context import Context +from yai_core.kernel.router import AdaptiveRouter +from yai_core.spi import Channel, MemoryStore, ModelProvider +from yai_core.tools.executor import ToolExecutor +from yai_core.tools.registry import ToolRegistry +from yai_core.types import ( + AgentEvent, + ChatMessage, + EventType, + Strategy, +) + +_SYSTEM_TEMPLATE = """你是运行在宿主软件内部的 AI 助手。\ +你只能通过"工具"操作宿主的能力，不要编造工具不存在的数据。\ +当任务完成时，直接给出可交付的最终结果。 + +宿主当前提供的能力： +{tools} +""" + + +class AgentLoop: + def __init__( + self, + model: ModelProvider, + registry: ToolRegistry, + executor: ToolExecutor, + channel: Channel, + memory: MemoryStore, + router: AdaptiveRouter | None = None, + *, + max_iters: int = 6, + ) -> None: + self.model = model + self.registry = registry + self.executor = executor + self.channel = channel + self.memory = memory + self.router = router or AdaptiveRouter() + self.max_iters = max_iters + + async def astream(self, task: str) -> AsyncIterator[AgentEvent]: + decision = await self.router.aclassify(task, self.registry) + strategy = decision.strategy + # 决策来源（llm/rules）、理由与模型档位随事件流出：每次自适应决策都可审计。 + yield AgentEvent( + EventType.STRATEGY_SELECTED, + { + "strategy": strategy.value, + "source": decision.source, + "reason": decision.reason, + "tier": decision.tier, + }, + ) + + if strategy == Strategy.CLARIFY: + yield AgentEvent(EventType.CLARIFY_REQUESTED, {"question": task}) + answer = await self.channel.ask(task) + async for ev in self.astream(answer): + yield ev + return + + ctx = Context(_SYSTEM_TEMPLATE.format(tools=self.registry.describe())) + for msg in self.memory.history(): + ctx.add(msg) + ctx.add(ChatMessage(role="user", content=task)) + + if strategy == Strategy.PLAN: + async for ev in self._make_plan(ctx, task, tier=decision.tier): + yield ev + # 计划只是"助手说过的话"，必须再推一把，模型才会进入工具执行； + # 否则真实模型会把计划本身当成最终答复（离线脚本模型曾掩盖此问题）。 + ctx.add( + ChatMessage( + role="user", + content="请按上面的计划逐步调用工具执行，拿到全部结果后给出最终汇报。", + ) + ) + + final_text = "" + async for ev in self._react_cycle(ctx, use_tools=strategy != Strategy.DIRECT): + yield ev + if ev.type == EventType.MODEL_MESSAGE: + final_text = ev.data.get("text", final_text) + + await self.memory.append_history(ChatMessage(role="user", content=task)) + await self.memory.append_history(ChatMessage(role="assistant", content=final_text)) + yield AgentEvent(EventType.DONE, {"strategy": strategy.value, "final_text": final_text}) + + async def _make_plan( + self, ctx: Context, task: str, *, tier: str = "strong" + ) -> AsyncIterator[AgentEvent]: + prompt = ( + "把下面的任务拆成 2-5 个可执行步骤，每行一个步骤，用 1. 2. 3. 编号，" + "只输出步骤本身：\n" + task + ) + ctx.add(ChatMessage(role="user", content=prompt)) + # 档位由路由器建议（LLM 路由可给 standard/strong），规则路由的 plan 默认 strong。 + resp = await self.model.achat(ctx.llm_messages(), tools=None, tier=tier) + steps = [s.strip() for s in re.findall(r"\d+[.、)]\s*(.+)", resp.content)] + if not steps: + steps = [task] + plan_text = "\n".join(f"{i + 1}. {s}" for i, s in enumerate(steps)) + ctx.add(ChatMessage(role="assistant", content=plan_text)) + yield AgentEvent(EventType.PLAN_CREATED, {"steps": steps}) + + async def _react_cycle( + self, ctx: Context, *, use_tools: bool + ) -> AsyncIterator[AgentEvent]: + tools_schema = self.registry.llm_schemas() if use_tools else None + for _ in range(self.max_iters): + try: + resp = await self.model.achat(ctx.llm_messages(), tools=tools_schema) + except Exception as exc: # noqa: BLE001 + yield AgentEvent(EventType.ERROR, {"error": f"{type(exc).__name__}: {exc}"}) + return + + if not resp.tool_calls: + text = resp.content.strip() + ctx.add(ChatMessage(role="assistant", content=text)) + yield AgentEvent(EventType.MODEL_MESSAGE, {"text": text}) + return + + ctx.add( + ChatMessage( + role="assistant", + content=resp.content, + tool_calls=[ + { + "id": tc.id, + "type": "function", + "function": {"name": tc.name, "arguments": json.dumps( + tc.arguments, ensure_ascii=False + )}, + } + for tc in resp.tool_calls + ], + ) + ) + for call in resp.tool_calls: + tool_events, ok, result_text = await self.executor.execute( + call.name, call.arguments + ) + for tool_event in tool_events: + yield tool_event + ctx.add( + ChatMessage( + role="tool", + content=result_text, + tool_call_id=call.id, + name=call.name, + ) + ) + + # 达到迭代上限：要求模型基于已有观察收尾 + ctx.add( + ChatMessage( + role="user", + content="已达到工具调用上限，请基于已有结果直接给出最终答案。", + ) + ) + resp = await self.model.achat(ctx.llm_messages(), tools=None) + yield AgentEvent(EventType.MODEL_MESSAGE, {"text": resp.content.strip()}) diff --git a/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/kernel/router.py b/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/kernel/router.py new file mode 100644 index 0000000..1cf0570 --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/kernel/router.py @@ -0,0 +1,153 @@ +"""Adaptive Router：把任务路由到 direct / react / plan / clarify。 + +v0.1 使用确定性规则（可测试、零成本、离线可跑）； +v0.2 增加 LLM 分类器（一次轻量模型调用，输出结构化策略 JSON）， + 分类失败时自动回退到本规则实现——这就是"模型自适应"的兜底设计。 + +- classify()：纯规则，同步、零成本、永远可用（最终兜底）； +- aclassify()：优先 LLM 分类（配置了模型时），任何异常/超时/非法输出都回退规则。 + 两条路径都返回 RouteDecision（策略 + 决策来源 + 理由 + 模型档位）， + 保证"每一次自适应决策都可观测、可解释"。 +""" + +from __future__ import annotations + +import asyncio +import json +import re +from dataclasses import dataclass + +from yai_core.tools.registry import ToolRegistry +from yai_core.types import Strategy + +# 多步骤信号：出现时倾向先规划再执行 +_PLAN_HINTS = ( + "然后", "接着", "之后", "再把", "分步", "步骤", "先", "并且", "同时", + "对比", "整理成", "汇总成", "最终", "一共", "分别", +) +# 行动信号：需要调用工具 +_ACTION_HINTS = ( + "查", "找", "搜", "列出", "统计", "计算", "导出", "获取", "读取", + "记录", "新增", "整理", "分析", "筛选", "生成", + # 显式的工具/MCP 调用意图（v0.2 接外部 MCP Server 后补齐） + "问一下", "查询", "调用", "工具", "mcp", +) +# 过于模糊、需要反问 +_CLARIFY_HINTS = ("随便", "你看着办", "什么都行", "帮我弄一下") + + +@dataclass +class RouteDecision: + """一次路由决策的完整记录：策略、决策来源、理由、建议模型档位。""" + + strategy: Strategy + source: str # "llm"：模型分类；"rules"：规则（含 LLM 失败后的兜底） + reason: str + tier: str = "standard" # "standard"（便宜快）/ "strong"（规划等重活） + + +class AdaptiveRouter: + def __init__( + self, + *, + min_plan_steps: int = 2, + model: object | None = None, + classify_timeout: float = 15.0, + ) -> None: + self.min_plan_steps = min_plan_steps + # model 可选：注入了才启用 LLM 分类；不注入时 aclassify 直接走规则。 + self.model = model + self.classify_timeout = classify_timeout + + # ---------- 规则路径（同步、永远可用的兜底） ---------- + + def classify(self, task: str, registry: ToolRegistry) -> Strategy: + return self._rules(task, registry).strategy + + def _rules(self, task: str, registry: ToolRegistry) -> RouteDecision: + text = task.strip() + if not text: + return RouteDecision(Strategy.CLARIFY, "rules", "任务为空，需要反问澄清") + if any(h in text for h in _CLARIFY_HINTS) and len(text) < 12: + return RouteDecision(Strategy.CLARIFY, "rules", "任务过于模糊，先澄清") + if len(registry) == 0: + # 宿主没有任何能力 -> 只能直接回答（能力边界优先于用户意图） + return RouteDecision(Strategy.DIRECT, "rules", "宿主无任何工具，直接回答") + # 拉丁字母提示词（如 mcp）大小写不敏感；中文提示词按原文匹配。 + lowered = text.lower() + wants_action = any( + (h in lowered) if h.isascii() else (h in text) for h in _ACTION_HINTS + ) + multi_step = sum(1 for h in _PLAN_HINTS if h in text) >= 1 + if multi_step and wants_action: + return RouteDecision( + Strategy.PLAN, "rules", "命中多步骤+行动信号，先规划再执行", "strong" + ) + if wants_action: + return RouteDecision(Strategy.REACT, "rules", "命中行动信号，进入工具循环") + # 有工具但任务像闲聊/问答：直接答（模型仍可在 react 循环里自行决定用工具） + return RouteDecision(Strategy.DIRECT, "rules", "无需工具的直接问答") + + # ---------- LLM 路径（失败一律回退规则） ---------- + + async def aclassify(self, task: str, registry: ToolRegistry) -> RouteDecision: + text = task.strip() + # 空任务、未配置模型、宿主无工具：直接走规则，不浪费一次模型调用。 + if not text or self.model is None or len(registry) == 0: + return self._rules(task, registry) + try: + raw = await asyncio.wait_for( + self._llm_classify(text, registry), timeout=self.classify_timeout + ) + decision = self._parse(raw, registry) + return decision + except Exception as exc: # noqa: BLE001 - 分类是增强不是依赖，任何失败都兜底 + fallback = self._rules(task, registry) + fallback.reason = f"LLM 分类失败（{type(exc).__name__}），回退规则：{fallback.reason}" + return fallback + + async def _llm_classify(self, task: str, registry: ToolRegistry) -> str: + """一次轻量模型调用，要求只输出路由 JSON。""" + tools_text = "\n".join( + f"- {s.name}: {s.description}" for s in registry.all() + ) + prompt = ( + "你是嵌入式 Agent 的任务路由器。根据任务与宿主可用工具，只输出一个 JSON 对象，" + "不要输出 JSON 以外的任何内容：\n" + '{"strategy": "direct|react|plan|clarify", ' + '"tier": "standard|strong", "reason": "不超过30字的中文理由"}\n' + "策略判定标准：\n" + "- direct：闲聊、知识问答、写作、解释，不需要调用工具；\n" + "- react：需要调用工具（查询/搜索/计算/读取/调用 MCP 等），单步即可完成；\n" + "- plan：明显多步骤、需要先拆解计划再逐步执行；\n" + "- clarify：任务过于模糊、缺少必要对象，无法执行。\n" + f"宿主可用工具：\n{tools_text}\n" + f"任务：{task}" + ) + messages = [ + {"role": "system", "content": "你是严谨的路由器，只输出合法 JSON。"}, + {"role": "user", "content": prompt}, + ] + resp = await self.model.achat(messages, tools=None, tier="standard") + return resp.content + + def _parse(self, content: str, registry: ToolRegistry) -> RouteDecision: + """解析模型输出为 RouteDecision；非法/越界输出抛异常交 aclassify 兜底。""" + text = content.strip() + # 容忍模型套 ```json 代码块或在 JSON 前后啰嗦：截取第一个 { 到最后一个 }。 + fenced = re.search(r"\{.*\}", text, flags=re.DOTALL) + if fenced is None: + raise ValueError("分类输出中没有 JSON 对象") + data = json.loads(fenced.group(0)) + strategy_value = data.get("strategy") + if strategy_value not in {s.value for s in Strategy}: + raise ValueError(f"非法策略值：{strategy_value!r}") + strategy = Strategy(strategy_value) + # 能力边界兜底：模型让调工具但宿主没有工具，强制 direct。 + if len(registry) == 0 and strategy in (Strategy.REACT, Strategy.PLAN): + raise ValueError("宿主无工具却被路由到工具策略") + tier = data.get("tier", "standard") + if tier not in ("standard", "strong"): + tier = "standard" + reason = str(data.get("reason") or "").strip() or "LLM 分类（模型未给理由）" + return RouteDecision(strategy, "llm", reason, tier) diff --git a/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/llm/__init__.py b/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/llm/__init__.py new file mode 100644 index 0000000..f840a4a --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/llm/__init__.py @@ -0,0 +1,3 @@ +from yai_core.llm.openai_compat import OpenAICompatProvider + +__all__ = ["OpenAICompatProvider"] diff --git a/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/llm/openai_compat.py b/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/llm/openai_compat.py new file mode 100644 index 0000000..aa90064 --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/llm/openai_compat.py @@ -0,0 +1,62 @@ +"""OpenAI 兼容模型后端：DeepSeek / 通义千问 / OpenAI / 本地 vLLM 等同一套代码。""" + +from __future__ import annotations + +import json +import os +from typing import Any + +from yai_core.types import ModelResponse, ToolCallRequest + + +class OpenAICompatProvider: + def __init__( + self, + *, + api_key: str | None = None, + base_url: str | None = None, + model: str | None = None, + strong_model: str | None = None, + ) -> None: + try: + from openai import AsyncOpenAI # noqa: PLC0415 + except ImportError as exc: + raise ImportError( + "使用 OpenAICompatProvider 需要安装可选依赖：uv pip install -e '.[llm]'" + ) from exc + + self.client = AsyncOpenAI( + api_key=api_key or os.getenv("OPENAI_API_KEY", "missing"), + base_url=base_url or os.getenv("OPENAI_BASE_URL"), + ) + self.model = model or os.getenv("LLM_MODEL", "deepseek-chat") + self.strong_model = strong_model or os.getenv("LLM_STRONG_MODEL") or self.model + + async def achat( + self, + messages: list[dict[str, Any]], + tools: list[dict[str, Any]] | None = None, + *, + tier: str = "standard", + ) -> ModelResponse: + # messages 由 Context.llm_messages() 产出，已经是 OpenAI 线格式 dict + kwargs: dict[str, Any] = { + "model": self.strong_model if tier == "strong" else self.model, + "messages": messages, + } + if tools: + kwargs["tools"] = tools + kwargs["tool_choice"] = "auto" + + completion = await self.client.chat.completions.create(**kwargs) + msg = completion.choices[0].message + + tool_calls: list[ToolCallRequest] = [] + for tc in getattr(msg, "tool_calls", None) or []: + try: + args = json.loads(tc.function.arguments or "{}") + except json.JSONDecodeError: + args = {} + tool_calls.append(ToolCallRequest(id=tc.id, name=tc.function.name, arguments=args)) + + return ModelResponse(content=msg.content or "", tool_calls=tool_calls, raw=completion) diff --git a/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/memory/__init__.py b/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/memory/__init__.py new file mode 100644 index 0000000..53c877c --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/memory/__init__.py @@ -0,0 +1,5 @@ +from yai_core.memory.inmemory import InMemoryStore +from yai_core.memory.retention import retention_from_env +from yai_core.memory.sqlite_store import SqliteStore + +__all__ = ["InMemoryStore", "SqliteStore", "retention_from_env"] diff --git a/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/memory/inmemory.py b/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/memory/inmemory.py new file mode 100644 index 0000000..680787c --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/memory/inmemory.py @@ -0,0 +1,77 @@ +from __future__ import annotations + +from collections.abc import Callable +from datetime import datetime, timedelta + +from yai_core.memory.retention import count_cut, ttl_cut, utc_now +from yai_core.types import ChatMessage + + +class InMemoryStore: + """默认记忆实现：会话历史 + 简单 KV。v2 再换向量实现。 + + v0.3 起构造函数支持历史保留策略（全部 opt-in，默认 None = 永不裁剪， + 行为与旧版逐字节一致）： + - max_messages：保留最近 N 条消息（按轮对齐，整轮删除，至少留最后一轮）； + - ttl_seconds：超过 N 秒的历史在写入时与显式 prune() 时清理； + - clock：可注入时钟（测试用假时钟推进时间，禁止 sleep 等真实时间）。 + ChatMessage 没有时间字段（不改 types.py），时间戳用与 _history 严格 + 同长同序的并行列表 _timestamps 保存。 + """ + + def __init__( + self, + *, + max_messages: int | None = None, + ttl_seconds: int | None = None, + clock: Callable[[], datetime] | None = None, + ) -> None: + self._history: list[ChatMessage] = [] + self._timestamps: list[datetime] = [] # 与 _history 严格同长同序 + self._kv: dict[str, str] = {} + self._max_messages = max_messages + self._ttl_seconds = ttl_seconds + self._clock = clock or utc_now + + async def append_history(self, message: ChatMessage) -> None: + self._history.append(message) + self._timestamps.append(self._clock()) + # opt-in：未配置任何策略时 prune() 立即返回 0，等价于旧版"只追加"。 + self.prune() + + def history(self) -> list[ChatMessage]: + return list(self._history) + + def prune(self) -> int: + """按保留策略裁剪历史前缀，返回删除条数；KV 不动。 + + 非 MemoryStore 契约方法（与 SqliteStore.close() 同一先例：宿主探测式 + 调用，spi/memory.py 的 Protocol 不扩面）。两种策略同时命中时取更大的 + 删除上界——两个上界都落在轮首，较大者仍是轮首，工具调用对依然完整。 + """ + roles = [m.role for m in self._history] + k_count = count_cut(roles, self._max_messages) + k_ttl = None + if self._ttl_seconds is not None: + cutoff = self._clock() - timedelta(seconds=self._ttl_seconds) + # 严格 <：时间戳恰好等于 cutoff 的消息保留（边界语义钉在测试里）。 + expired = [ts < cutoff for ts in self._timestamps] + k_ttl = ttl_cut(roles, expired) + cuts = [k for k in (k_count, k_ttl) if k is not None] + if not cuts: + return 0 + k = max(cuts) + del self._history[:k] + del self._timestamps[:k] + return k + + async def put(self, key: str, value: str) -> None: + self._kv[key] = value + + async def get(self, key: str) -> str | None: + return self._kv.get(key) + + async def clear(self) -> None: + self._history.clear() + self._timestamps.clear() + self._kv.clear() diff --git a/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/memory/retention.py b/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/memory/retention.py new file mode 100644 index 0000000..ba5760c --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/memory/retention.py @@ -0,0 +1,121 @@ +"""历史保留策略纯函数：条数裁剪与 TTL 的删除边界计算（v0.3，opt-in）。 + +只放纯函数与 env 解析，不碰任何存储实现：InMemoryStore 与 SqliteStore 共用 +同一套"轮边界对齐"规则，保证两种实现的裁剪结果逐字节一致。 + +轮（round）的定义：一条 role == "user" 的消息到下一条 user 消息之前为一轮； +历史开头的非 user 消息归入"第 0 轮"，与相邻轮同生共死。 +为什么必须按轮裁剪：assistant(tool_calls) 与其后的 tool 消息必须成对出现， +从中间切开后发给 OpenAI 兼容接口会直接 400（详见 walkthrough 第 13 章）。 +""" + +from __future__ import annotations + +import os +import warnings +from datetime import UTC, datetime + +_MAX_ENV = "YAI_HISTORY_MAX_MESSAGES" +_TTL_ENV = "YAI_HISTORY_TTL_SECONDS" + + +def utc_now() -> datetime: + """统一 UTC 时钟；SQLite 的 CURRENT_TIMESTAMP 同为 UTC 文本，可直接比较。""" + return datetime.now(UTC) + + +def _parse_positive_int(raw: str | None, env_name: str) -> int | None: + """解析正整数环境变量。 + + 未设置/空白 -> None（静默，等同未配置）； + 0/负数/非整数 -> None + warning（不崩、不静默、不裁剪）。 + """ + if raw is None or not raw.strip(): + return None + try: + value = int(raw.strip()) + except ValueError: + warnings.warn( + f"{env_name}={raw!r} 不是合法整数，忽略（不裁剪历史）", stacklevel=2 + ) + return None + if value <= 0: + warnings.warn( + f"{env_name}={value} 必须为正整数，忽略（不裁剪历史）", stacklevel=2 + ) + return None + return value + + +def retention_from_env( + env: dict[str, str] | None = None, +) -> tuple[int | None, int | None]: + """读历史保留策略，返回 (max_messages, ttl_seconds)，未配置项为 None。 + + env=None 读真实 os.environ；测试注入假字典，绝不碰真实环境变量。 + 这是两个 Store 与 serve_example 共用的唯一 env 解析入口。 + """ + environ = os.environ if env is None else env + return ( + _parse_positive_int(environ.get(_MAX_ENV), _MAX_ENV), + _parse_positive_int(environ.get(_TTL_ENV), _TTL_ENV), + ) + + +def _next_round_start(roles: list[str], start: int) -> int | None: + """从 start（含）向后找第一个轮首下标（role == "user"），找不到返回 None。""" + for i in range(start, len(roles)): + if roles[i] == "user": + return i + return None + + +def _prev_round_start(roles: list[str], start: int) -> int | None: + """从 start（含）向前找最近的轮首下标；start 允许等于 len（整体过期场景）。""" + for i in range(min(start, len(roles) - 1), -1, -1): + if roles[i] == "user": + return i + return None + + +def count_cut(roles: list[str], max_messages: int | None) -> int | None: + """条数裁剪：返回删除上界 k（删 [0, k)），不裁返回 None。 + + 候选边界 = len(roles) - max_messages，再向后对齐到轮首： + - 对齐保证删除点落在一轮开头，不切散 assistant(tool_calls)/tool 配对； + - 找不到后续轮首（只有一轮、或单轮自身超限）-> 不裁，宁可超限也不破坏序列； + - max_messages 是"上限"而非"目标值"，对齐后实际保留条数可能少于上限。 + """ + if max_messages is None or max_messages <= 0: + return None + candidate = len(roles) - max_messages + if candidate <= 0: + return None + k = _next_round_start(roles, candidate) + if k is None or k <= 0: + return None + return k + + +def ttl_cut(roles: list[str], expired: list[bool]) -> int | None: + """TTL 裁剪：返回删除上界 k（删 [0, k)），不裁返回 None。 + + expired[i] 表示第 i 条是否已过期（严格早于 cutoff；恰好等于 cutoff 不算过期）。 + 先数"从头开始连续过期"的条数 n，再把边界向前对齐到轮首： + - 全部过期（n == len）：返回 len，整库清空——空历史合法，TTL 语义高于 + "至少保留最后一轮"（该约束只作用于条数裁剪）； + - 否则边界必须落在轮首且 k > 0；只过期到首轮中间（k=0）则不裁，避免孤儿 tool。 + """ + n = 0 + for is_expired in expired: + if not is_expired: + break + n += 1 + if n == 0: + return None + if n == len(roles): + return n + k = _prev_round_start(roles, n) + if k is None or k <= 0: + return None + return k diff --git a/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/memory/sqlite_store.py b/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/memory/sqlite_store.py new file mode 100644 index 0000000..83a8d31 --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/memory/sqlite_store.py @@ -0,0 +1,304 @@ +"""SQLite 持久化记忆：MemoryStore 契约的第一个持久化实现（opt-in）。 + +为什么放在 memory/ 而不是 integrations/：sqlite3 是 Python 标准库， +零第三方依赖、零可选 extra，不属于"外部生态集成"，与 InMemoryStore 同层。 + +设计要点（对应 10-plan-sqlite-memory.md §4 与 10-plan-history-trim-ttl.md §4）： +1. 完整实现 spi/memory.py 的 MemoryStore 契约（五方法），Loop / Core / 三个 host + 示例零改动即可把"便签本"换成"笔记本"； +2. history() 按契约保持同步方法；其余 async 方法内执行同步小事务（单条毫秒级， + v0.2 不引入 aiosqlite，边界与取舍写进 walkthrough 第 11 章）； +3. scope 实现会话/宿主隔离，默认 "default"，不传参与 InMemoryStore 的单空间行为对齐； +4. PRAGMA user_version 作为 schema 迁移钩子（v0.3 仍是 v1，历史裁剪不动 schema）； +5. check_same_thread=False 只是放开 sqlite 的线程限制，真正的互斥由 self._lock 保证 + （uvicorn 会把同步函数丢到线程池，多线程可能同时碰一个连接）； +6. v0.3 历史保留策略（opt-in）：max_messages/ttl_seconds/clock 与 InMemoryStore 对等； + created_at 由注入时钟在 Python 侧写入（与内存实现的时间戳列表同口径，假时钟可测）， + 列默认 CURRENT_TIMESTAMP 保留给外部/手工插入；构造时自动 prune 一次覆盖重启场景。 +""" + +from __future__ import annotations + +import json +import os +import sqlite3 +import threading +from collections.abc import Callable +from datetime import datetime, timedelta +from pathlib import Path + +from yai_core.memory.retention import ( + count_cut, + retention_from_env, + ttl_cut, + utc_now, +) +from yai_core.types import ChatMessage + +# 当前代码支持的 schema 版本；_ensure_schema 用它判断"未来版本数据库"并拒绝打开。 +_SCHEMA_VERSION = 1 + +# 建表语句整体作为一个脚本执行；PRAGMA user_version 不能参数化，必须写字面量。 +_SCHEMA_SQL = """ +CREATE TABLE IF NOT EXISTS history ( + id INTEGER PRIMARY KEY AUTOINCREMENT, + scope TEXT NOT NULL DEFAULT 'default', + role TEXT NOT NULL, + content TEXT NOT NULL DEFAULT '', + tool_calls TEXT, + tool_call_id TEXT, + name TEXT, + created_at TEXT NOT NULL DEFAULT (CURRENT_TIMESTAMP) +); +CREATE INDEX IF NOT EXISTS idx_history_scope_id ON history(scope, id); + +CREATE TABLE IF NOT EXISTS kv ( + scope TEXT NOT NULL DEFAULT 'default', + key TEXT NOT NULL, + value TEXT NOT NULL, + updated_at TEXT NOT NULL DEFAULT (CURRENT_TIMESTAMP), + PRIMARY KEY (scope, key) +); + +PRAGMA user_version = 1; +""" + +_DB_PATH_ENV = "YAI_DB_PATH" + +# created_at 的 UTC 文本格式，与 SQLite CURRENT_TIMESTAMP 输出完全一致，可直接字符串比较。 +_TS_FORMAT = "%Y-%m-%d %H:%M:%S" + + +class SqliteStore: + """会话历史 + KV 落 SQLite 的 MemoryStore 实现。 + + 用法:: + + store = SqliteStore("data/yai.db") # 文件形态（自动建父目录） + store = SqliteStore(":memory:") # 内存形态（测试主入口） + store = SqliteStore.from_env() # 读 YAI_DB_PATH，未设置返回 None + # 历史保留策略（opt-in，与 InMemoryStore 对等）： + store = SqliteStore("data/yai.db", max_messages=200, ttl_seconds=604800) + """ + + def __init__( + self, + path: str | Path = ":memory:", + *, + scope: str = "default", + max_messages: int | None = None, + ttl_seconds: int | None = None, + clock: Callable[[], datetime] | None = None, + ) -> None: + self._scope = scope + self._max_messages = max_messages + self._ttl_seconds = ttl_seconds + self._clock = clock or utc_now + # 所有 DB 访问（含同步 history()）都在这把锁内，保证多线程下连接安全。 + self._lock = threading.Lock() + self._is_memory = str(path) == ":memory:" + if self._is_memory: + db_path = ":memory:" + else: + # expanduser 支持 "~/..."；父目录不存在就建，宿主少写一行初始化代码。 + p = Path(path).expanduser() + p.parent.mkdir(parents=True, exist_ok=True) + db_path = str(p) + # check_same_thread=False：允许线程池线程使用连接；互斥交给 self._lock。 + self._conn: sqlite3.Connection | None = sqlite3.connect( + db_path, check_same_thread=False + ) + # Row 工厂：读出的行可以用 row["role"] 按列名访问，少出错。 + self._conn.row_factory = sqlite3.Row + if not self._is_memory: + # WAL：读写不互斥、崩溃更稳；:memory: 不需要也设不了。 + self._conn.execute("PRAGMA journal_mode=WAL") + # NORMAL：WAL 下安全且更快（fsync 频率降低）。 + self._conn.execute("PRAGMA synchronous=NORMAL") + self._ensure_schema() + # 启动清理：覆盖"服务重启后过期/超量历史仍在库"的场景（仅配置了策略时动作）。 + if self._max_messages is not None or self._ttl_seconds is not None: + self.prune() + + @classmethod + def from_env( + cls, + env: dict[str, str] | None = None, + *, + retention: tuple[int | None, int | None] | None = None, + ) -> SqliteStore | None: + """从 YAI_DB_PATH 构造；未设置或为空白时返回 None（装配方据此回退 InMemoryStore）。 + + env=None 读真实 os.environ；测试注入假字典，绝不碰真实环境变量。 + retention 可由装配方预先解析后显式传入（serve_example 只解析一次 env， + 避免非法值重复 warning）；缺省在本方法内调用 retention_from_env。 + """ + environ = os.environ if env is None else env + raw = (environ.get(_DB_PATH_ENV) or "").strip() + if not raw: + return None + if retention is None: + retention = retention_from_env(environ) + max_messages, ttl_seconds = retention + return cls(raw, max_messages=max_messages, ttl_seconds=ttl_seconds) + + def _ensure_schema(self) -> None: + """建表（版本 0）或核对版本；版本高于本代码支持值时直接报错，拒绝乱开。""" + with self._lock: + conn = self._require_conn_locked() + version = int(conn.execute("PRAGMA user_version").fetchone()[0]) + if version == 0: + conn.executescript(_SCHEMA_SQL) + conn.commit() + elif version > _SCHEMA_VERSION: + raise RuntimeError( + f"数据库 schema 版本 {version} 高于本代码支持的 {_SCHEMA_VERSION}，" + "请升级 yai-agent-core" + ) + # version == _SCHEMA_VERSION：幂等，什么都不做（重复初始化不报错、不丢数据） + + def _require_conn_locked(self) -> sqlite3.Connection: + """关闭后任何方法都给统一错误；调用方必须已持有 self._lock。""" + if self._conn is None: + raise RuntimeError("SqliteStore 已关闭") + return self._conn + + async def append_history(self, message: ChatMessage) -> None: + # tool_calls 是 list[dict]，落库序列化为 JSON 文本；None 才存 NULL。 + # 易错点：空列表 [] 要存成 "[]"，读回仍是 []，不能折叠成 NULL（对等测试红线）。 + tool_calls = ( + None + if message.tool_calls is None + else json.dumps(message.tool_calls, ensure_ascii=False, default=str) + ) + # created_at 用注入时钟在 Python 侧写：与 InMemoryStore 的时间戳同口径， + # TTL 才能用假时钟做确定性测试；列默认 CURRENT_TIMESTAMP 仍兜底外部插入。 + created_at = self._clock().strftime(_TS_FORMAT) + with self._lock: + conn = self._require_conn_locked() + conn.execute( + "INSERT INTO history(scope, role, content, tool_calls, tool_call_id," + " name, created_at) VALUES (?, ?, ?, ?, ?, ?, ?)", + ( + self._scope, + message.role, + message.content, + tool_calls, + message.tool_call_id, + message.name, + created_at, + ), + ) + conn.commit() + self._prune_locked() + + def history(self) -> list[ChatMessage]: + """同步方法（MemoryStore 契约如此，Loop 启动时直接迭代回放）。 + + 顺序以自增 id 为准而不是 created_at：同一秒内多条消息时时间戳没有区分度。 + 返回全新列表、全新对象，外部改不到内部状态（与 InMemoryStore 返回副本一致）。 + """ + with self._lock: + conn = self._require_conn_locked() + rows = conn.execute( + "SELECT role, content, tool_calls, tool_call_id, name FROM history" + " WHERE scope = ? ORDER BY id ASC", + (self._scope,), + ).fetchall() + messages: list[ChatMessage] = [] + for row in rows: + raw_calls = row["tool_calls"] + tool_calls = json.loads(raw_calls) if raw_calls is not None else None + messages.append( + ChatMessage( + role=row["role"], + content=row["content"], + tool_calls=tool_calls, + tool_call_id=row["tool_call_id"], + name=row["name"], + ) + ) + return messages + + def _prune_locked(self) -> int: + """按保留策略删除本 scope 的历史前缀，返回删除条数；KV 不动。 + + 调用方必须已持有 self._lock。统一走"取行 → Python 算轮对齐边界 → 按 id + 删前缀"，条数裁剪与 TTL 共用一条路径（裸 DELETE created_at 会绕过轮对齐， + 可能切散工具调用对）。TTL 判定全部过期时（k == 行数）整 scope 清空。 + """ + conn = self._require_conn_locked() + rows = conn.execute( + "SELECT id, role, created_at FROM history WHERE scope = ? ORDER BY id ASC", + (self._scope,), + ).fetchall() + if not rows: + return 0 + roles = [r["role"] for r in rows] + k_count = count_cut(roles, self._max_messages) + k_ttl = None + if self._ttl_seconds is not None: + cutoff = self._clock() - timedelta(seconds=self._ttl_seconds) + cutoff_text = cutoff.strftime(_TS_FORMAT) + # created_at 为 UTC 文本，同格式字符串比较即时间比较；严格 <，等于 cutoff 保留。 + expired = [r["created_at"] < cutoff_text for r in rows] + k_ttl = ttl_cut(roles, expired) + cuts = [k for k in (k_count, k_ttl) if k is not None] + if not cuts: + return 0 + k = max(cuts) + if k >= len(rows): + # TTL 判定全部过期：整 scope 历史清空（KV 保留）。 + cur = conn.execute("DELETE FROM history WHERE scope = ?", (self._scope,)) + else: + # rows[k] 是保留段首行；删掉它之前（同 scope）的所有行，即整轮前缀。 + first_kept_id = rows[k]["id"] + cur = conn.execute( + "DELETE FROM history WHERE scope = ? AND id < ?", + (self._scope, first_kept_id), + ) + deleted = cur.rowcount if cur.rowcount is not None else 0 + conn.commit() + return deleted + + def prune(self) -> int: + """非 MemoryStore 契约方法：显式触发一次历史裁剪，返回删除条数；KV 不动。""" + with self._lock: + return self._prune_locked() + + async def put(self, key: str, value: str) -> None: + """KV 写入（UPSERT）：同 scope 同 key 覆盖并刷新 updated_at。""" + with self._lock: + conn = self._require_conn_locked() + conn.execute( + "INSERT INTO kv(scope, key, value) VALUES (?, ?, ?)" + " ON CONFLICT(scope, key) DO UPDATE SET value = excluded.value," + " updated_at = CURRENT_TIMESTAMP", + (self._scope, key, value), + ) + conn.commit() + + async def get(self, key: str) -> str | None: + """KV 读取；未命中返回 None（不是 KeyError），与 InMemoryStore 对齐。""" + with self._lock: + conn = self._require_conn_locked() + row = conn.execute( + "SELECT value FROM kv WHERE scope = ? AND key = ?", + (self._scope, key), + ).fetchone() + return None if row is None else row["value"] + + async def clear(self) -> None: + """清空**当前 scope** 的历史与 KV；其他会话/宿主的数据不动。""" + with self._lock: + conn = self._require_conn_locked() + conn.execute("DELETE FROM history WHERE scope = ?", (self._scope,)) + conn.execute("DELETE FROM kv WHERE scope = ?", (self._scope,)) + conn.commit() + + def close(self) -> None: + """关闭连接（非 MemoryStore 契约方法，供宿主 lifespan 停机调用，幂等）。""" + with self._lock: + if self._conn is not None: + self._conn.close() + self._conn = None diff --git a/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/policy/__init__.py b/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/policy/__init__.py new file mode 100644 index 0000000..653408d --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/policy/__init__.py @@ -0,0 +1,3 @@ +from yai_core.policy.allowlist import AllowlistPolicy + +__all__ = ["AllowlistPolicy"] diff --git a/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/policy/allowlist.py b/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/policy/allowlist.py new file mode 100644 index 0000000..8e7244e --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/policy/allowlist.py @@ -0,0 +1,32 @@ +from __future__ import annotations + +from collections.abc import Iterable + +from yai_core.spi import PermissionDecision + + +class AllowlistPolicy: + """默认权限策略。 + + - mode="auto": 白名单内工具自动放行，其余询问 + - mode="allow_all": 全部自动放行（本地演示/测试用） + - mode="deny_all": 除白名单外全部拒绝 + """ + + def __init__( + self, + allowed: Iterable[str] = (), + *, + mode: str = "auto", + ) -> None: + self.allowed = set(allowed) + self.mode = mode + + async def check(self, tool_name: str, arguments: dict) -> PermissionDecision: + if tool_name in self.allowed: + return PermissionDecision.ALLOW + if self.mode == "allow_all": + return PermissionDecision.ALLOW + if self.mode == "deny_all": + return PermissionDecision.DENY + return PermissionDecision.ASK diff --git a/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/spi/__init__.py b/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/spi/__init__.py new file mode 100644 index 0000000..4388b54 --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/spi/__init__.py @@ -0,0 +1,14 @@ +"""SPI（Service Provider Interface）：宿主可替换、Core 提供默认实现的契约层。""" + +from yai_core.spi.channel import Channel +from yai_core.spi.memory import MemoryStore +from yai_core.spi.model import ModelProvider +from yai_core.spi.policy import PermissionDecision, PermissionPolicy + +__all__ = [ + "Channel", + "MemoryStore", + "ModelProvider", + "PermissionDecision", + "PermissionPolicy", +] diff --git a/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/spi/channel.py b/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/spi/channel.py new file mode 100644 index 0000000..3f2697a --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/spi/channel.py @@ -0,0 +1,22 @@ +"""通道契约：Core 不假设 UI 形态（CLI / Web / Flutter 都实现同一接口）。""" + +from __future__ import annotations + +from typing import Any, Protocol, runtime_checkable + +from yai_core.types import AgentEvent + + +@runtime_checkable +class Channel(Protocol): + async def emit(self, event: AgentEvent) -> None: + """接收 Observer 事件流（思考过程、工具状态、错误等）。""" + ... + + async def ask(self, question: str) -> str: + """策略为 clarify 时，向宿主/用户反问并取回回答。""" + ... + + async def confirm(self, tool_name: str, arguments: dict[str, Any]) -> bool: + """权限策略为 ask 时，请求宿主确认是否执行该工具。""" + ... diff --git a/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/spi/memory.py b/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/spi/memory.py new file mode 100644 index 0000000..8cfa804 --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/spi/memory.py @@ -0,0 +1,20 @@ +"""记忆存储契约：v0.1 只要求会话历史与简单 KV，向量记忆是 v2。""" + +from __future__ import annotations + +from typing import Protocol, runtime_checkable + +from yai_core.types import ChatMessage + + +@runtime_checkable +class MemoryStore(Protocol): + async def append_history(self, message: ChatMessage) -> None: ... + + def history(self) -> list[ChatMessage]: ... + + async def put(self, key: str, value: str) -> None: ... + + async def get(self, key: str) -> str | None: ... + + async def clear(self) -> None: ... diff --git a/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/spi/model.py b/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/spi/model.py new file mode 100644 index 0000000..fba91d6 --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/spi/model.py @@ -0,0 +1,32 @@ +"""模型提供者契约：Core 不绑定任何模型厂商。""" + +from __future__ import annotations + +from typing import Any, Protocol, runtime_checkable + +from yai_core.types import ModelResponse + + +@runtime_checkable +class ModelProvider(Protocol): + """任何实现该协议的对象都可作为 Core 的模型后端。 + + - OpenAI 兼容实现见 ``yai_core.llm.openai_compat`` + - 测试/离线演示可使用脚本化假模型 + """ + + async def achat( + self, + messages: list[dict[str, Any]], + tools: list[dict[str, Any]] | None = None, + *, + tier: str = "standard", + ) -> ModelResponse: + """单轮对话。 + + Args: + messages: OpenAI 线格式消息字典列表（由 Context.llm_messages() 产出）。 + tools: OpenAI 形状的工具描述列表；None 表示本轮不提供工具。 + tier: "standard" / "strong"，供模型路由（便宜模型 vs 强模型）。 + """ + ... diff --git a/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/spi/policy.py b/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/spi/policy.py new file mode 100644 index 0000000..c3c5aed --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/spi/policy.py @@ -0,0 +1,17 @@ +"""权限策略契约：高风险工具调用必须可被宿主拦截/确认。""" + +from __future__ import annotations + +from enum import StrEnum +from typing import Any, Protocol, runtime_checkable + + +class PermissionDecision(StrEnum): + ALLOW = "allow" + DENY = "deny" + ASK = "ask" + + +@runtime_checkable +class PermissionPolicy(Protocol): + async def check(self, tool_name: str, arguments: dict[str, Any]) -> PermissionDecision: ... diff --git a/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/tools/__init__.py b/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/tools/__init__.py new file mode 100644 index 0000000..5965e83 --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/tools/__init__.py @@ -0,0 +1,7 @@ +"""工具层：注册表 + 执行器（Tool Bus）+ 公共 schema 清洗。""" + +from yai_core.tools.executor import ToolExecutor +from yai_core.tools.registry import ToolRegistry +from yai_core.tools.schema import EMPTY_OBJECT_SCHEMA, sanitize_schema + +__all__ = ["ToolExecutor", "ToolRegistry", "sanitize_schema", "EMPTY_OBJECT_SCHEMA"] diff --git a/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/tools/executor.py b/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/tools/executor.py new file mode 100644 index 0000000..b8d4f80 --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/tools/executor.py @@ -0,0 +1,65 @@ +from __future__ import annotations + +import inspect +import json +from typing import Any + +from yai_core.spi import Channel, PermissionDecision, PermissionPolicy +from yai_core.tools.registry import ToolRegistry +from yai_core.types import AgentEvent, EventType + + +class ToolExecutor: + """Tool Bus：权限检查 -> 执行（同步/异步 handler 均可）-> 结构化结果。 + + 执行过程中产生的 Observer 事件由 execute 返回， + 由 AgentLoop 统一 yield（保证事件流只有一条路径）。 + """ + + def __init__( + self, + registry: ToolRegistry, + policy: PermissionPolicy, + channel: Channel, + ) -> None: + self.registry = registry + self.policy = policy + self.channel = channel + + async def execute( + self, name: str, arguments: dict[str, Any] + ) -> tuple[list[AgentEvent], bool, str]: + """返回 (过程事件列表, 是否成功, 文本结果)，永不向 Agent Loop 抛异常。""" + events: list[AgentEvent] = [] + if not self.registry.has(name): + return events, False, f"工具 {name!r} 不存在" + + decision = await self.policy.check(name, arguments) + if decision == PermissionDecision.ASK: + events.append( + AgentEvent(EventType.PERMISSION_ASKED, {"tool": name, "arguments": arguments}) + ) + approved = await self.channel.confirm(name, arguments) + if not approved: + return events, False, f"用户/宿主拒绝执行工具 {name}" + if decision == PermissionDecision.DENY: + return events, False, f"权限策略拒绝执行工具 {name}" + + events.append(AgentEvent(EventType.TOOL_CALL, {"tool": name, "arguments": arguments})) + spec = self.registry.get(name) + try: + result = spec.handler(**arguments) + if inspect.isawaitable(result): + result = await result + text = json.dumps(result, ensure_ascii=False, default=str) + except Exception as exc: # noqa: BLE001 - 工具错误必须回灌给模型而不是崩溃 + events.append( + AgentEvent(EventType.TOOL_RESULT, {"tool": name, "ok": False, + "error": str(exc)}) + ) + return events, False, f"工具 {name} 执行出错: {type(exc).__name__}: {exc}" + + events.append( + AgentEvent(EventType.TOOL_RESULT, {"tool": name, "ok": True, "preview": text[:200]}) + ) + return events, True, text diff --git a/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/tools/registry.py b/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/tools/registry.py new file mode 100644 index 0000000..30ce080 --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/tools/registry.py @@ -0,0 +1,44 @@ +from __future__ import annotations + +from collections.abc import Iterable + +from yai_core.types import ToolSpec + + +class ToolRegistry: + """统一工具注册表：Native / OpenAPI / MCP 工具在此同构。""" + + def __init__(self) -> None: + self._tools: dict[str, ToolSpec] = {} + + def register(self, spec: ToolSpec) -> None: + if spec.name in self._tools: + raise ValueError(f"工具 {spec.name!r} 已注册，名称必须唯一") + self._tools[spec.name] = spec + + def register_many(self, specs: Iterable[ToolSpec]) -> None: + for spec in specs: + self.register(spec) + + def get(self, name: str) -> ToolSpec: + if name not in self._tools: + raise KeyError(f"未知工具 {name!r}，当前可用：{list(self._tools)}") + return self._tools[name] + + def has(self, name: str) -> bool: + return name in self._tools + + def all(self) -> list[ToolSpec]: + return list(self._tools.values()) + + def llm_schemas(self) -> list[dict]: + return [spec.llm_schema() for spec in self._tools.values()] + + def describe(self) -> str: + """给系统提示词用的工具清单文本。""" + if not self._tools: + return "（当前宿主没有提供任何工具）" + return "\n".join(f"- {s.name}: {s.description}" for s in self._tools.values()) + + def __len__(self) -> int: + return len(self._tools) diff --git a/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/tools/schema.py b/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/tools/schema.py new file mode 100644 index 0000000..c96e579 --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/tools/schema.py @@ -0,0 +1,65 @@ +"""JSON Schema 清洗：喂给模型的工具入参 schema 只保留标准关键字。 + +MCP SDK 自动生成的 input_schema 带 title 等实现私有键，OpenAPI 描述里也常混入 +xml/example/deprecated 等 OpenAPI 专有注解；个别 OpenAI 兼容接口对多余键敏感， +注册进 ToolRegistry 前统一递归清洗一遍。MCP 桥与 OpenAPI 桥共用本模块。 +""" + +from __future__ import annotations + +from typing import Any + +# JSON Schema 标准关键字白名单（draft 2020-12 常用子集，覆盖工具入参所需）。 +_SCHEMA_KEYS = frozenset( + { + "type", + "properties", + "required", + "items", + "enum", + "description", + "default", + "const", + "anyOf", + "oneOf", + "allOf", + "not", + "minimum", + "maximum", + "exclusiveMinimum", + "exclusiveMaximum", + "minLength", + "maxLength", + "pattern", + "minItems", + "maxItems", + "uniqueItems", + "multipleOf", + "format", + "additionalProperties", + "$defs", + "$ref", + } +) + +# 空对象 schema 的公开常量（操作没有任何入参时使用）。 +EMPTY_OBJECT_SCHEMA: dict[str, Any] = {"type": "object", "properties": {}} + + +def sanitize_schema(schema: Any) -> Any: + """递归只保留 JSON Schema 标准关键字；dict/list 之外的原值原样返回。 + + 注意 properties / $defs 的键是"属性名/定义名"而不是 schema 关键字， + 必须原样保留，只清洗它们的值。 + """ + if isinstance(schema, dict): + cleaned: dict[str, Any] = {} + for key, value in schema.items(): + if key in ("properties", "$defs") and isinstance(value, dict): + cleaned[key] = {name: sanitize_schema(sub) for name, sub in value.items()} + elif key in _SCHEMA_KEYS: + cleaned[key] = sanitize_schema(value) + return cleaned or dict(EMPTY_OBJECT_SCHEMA) + if isinstance(schema, list): + return [sanitize_schema(item) for item in schema] + return schema diff --git a/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/types.py b/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/types.py new file mode 100644 index 0000000..55534dc --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/src/yai_core/types.py @@ -0,0 +1,107 @@ +"""YAI Agent Core 的核心数据类型。 + +刻意只依赖标准库：内核本体零第三方依赖，第三方能力全部通过 SPI 注入。 +""" + +from __future__ import annotations + +from collections.abc import Callable +from dataclasses import dataclass, field +from enum import StrEnum +from typing import Any, Literal + +Role = Literal["system", "user", "assistant", "tool"] + + +class Strategy(StrEnum): + """Adaptive Router 可选的执行策略。""" + + DIRECT = "direct" # 无需工具，模型直接回答 + REACT = "react" # 工具循环：推理 -> 调用 -> 观察 -> 再推理 + PLAN = "plan" # 先拆解计划，再按计划执行工具循环 + CLARIFY = "clarify" # 意图不清，先向宿主/用户反问 + + +class EventType(StrEnum): + """Observer 事件流类型——每一次"自适应决策"都必须可观测。""" + + STRATEGY_SELECTED = "strategy_selected" + PLAN_CREATED = "plan_created" + MODEL_MESSAGE = "model_message" + TOOL_CALL = "tool_call" + TOOL_RESULT = "tool_result" + PERMISSION_ASKED = "permission_asked" + CLARIFY_REQUESTED = "clarify_requested" + ERROR = "error" + DONE = "done" + + +@dataclass +class ToolSpec: + """统一工具规格。Native / OpenAPI / MCP 工具在 Registry 中同构。""" + + name: str + description: str + input_schema: dict[str, Any] # JSON Schema（与 MCP tools 形状一致） + handler: Callable[..., Any] # 同步函数；异步函数同样支持 + source: Literal["native", "openapi", "mcp"] = "native" + + def llm_schema(self) -> dict[str, Any]: + """转换成 OpenAI 兼容的 function-calling 工具描述。""" + return { + "type": "function", + "function": { + "name": self.name, + "description": self.description, + "parameters": self.input_schema, + }, + } + + +@dataclass +class ChatMessage: + role: Role + content: str = "" + # assistant 发起的工具调用：[{"id","name","arguments"}] + tool_calls: list[dict[str, Any]] | None = None + tool_call_id: str | None = None + name: str | None = None + + def to_llm_dict(self) -> dict[str, Any]: + d: dict[str, Any] = {"role": self.role, "content": self.content} + if self.tool_calls: + d["tool_calls"] = self.tool_calls + if self.tool_call_id: + d["tool_call_id"] = self.tool_call_id + if self.name: + d["name"] = self.name + return d + + +@dataclass +class ToolCallRequest: + id: str + name: str + arguments: dict[str, Any] = field(default_factory=dict) + + +@dataclass +class ModelResponse: + """ModelProvider 的统一返回，屏蔽各家 SDK 差异。""" + + content: str = "" + tool_calls: list[ToolCallRequest] = field(default_factory=list) + raw: Any = None + + +@dataclass +class AgentEvent: + type: EventType + data: dict[str, Any] = field(default_factory=dict) + + +@dataclass +class RunResult: + strategy: Strategy + events: list[AgentEvent] + final_text: str diff --git a/submissions/mcp-hackathon/yai-agent-core/source/submissions/mcp-hackathon/yai-agent-core/RIGHTS.md b/submissions/mcp-hackathon/yai-agent-core/source/submissions/mcp-hackathon/yai-agent-core/RIGHTS.md new file mode 100644 index 0000000..637af5e --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/submissions/mcp-hackathon/yai-agent-core/RIGHTS.md @@ -0,0 +1,56 @@ +# RIGHTS · 权利与授权声明 + +## 1. 提交人 + +- 提交团队：**YAI**（单人团队） +- 提交人 / 版权人：**Gi-Tuu**（https://github.com/Gi-Tuu） +- 项目仓库：https://github.com/Gi-Tuu/yai-agent-core +- 提交人声明：本项目全部代码、文档、示例均由本人原创编写，对代码、服务、依赖与数据拥有提交所需的全部权利；不存在未披露的第三方代码抄袭、虚假部署或身份操纵。 + +## 2. 项目许可证 + +本项目以 **MIT License** 开源，许可证全文见 `source/LICENSE`： + +> Copyright (c) 2026 Gi-Tuu + +任何人（含 X-Agent 评审与后续 MCP 标准化流程）可在 MIT 条款下使用、复制、修改、合并、发布、再许可与分发。 + +## 3. 第三方依赖许可证 + +内核本体（`src/yai_core/` 的核心部分）**零第三方运行时依赖**，仅使用 Python 标准库。 +下列依赖全部为可选 extras（按需安装、模块内懒加载），均为 MIT / BSD / Apache 类宽松许可证，完整版本锁定见 `source/uv.lock`，各依赖的许可证原文随其分发包提供： + +| 依赖（extras） | 用途 | 许可证 | +|---|---|---| +| openai（llm） | OpenAI 兼容模型客户端（线上接 DeepSeek） | Apache-2.0 | +| fastapi（server） | HTTP API 框架 | MIT | +| uvicorn[standard]（server） | ASGI 服务器 | BSD-3-Clause | +| pydantic（server） | 请求模型与数据校验 | MIT | +| starlette（fastapi 传递依赖） | ASGI 工具集 | BSD-3-Clause | +| mcp（mcp） | 官方 Model Context Protocol Python SDK v2 | MIT | +| anyio / httpx / httpcore（传递依赖） | 异步与 HTTP 运行时 | MIT / BSD-3-Clause | +| pydantic-core / typing-extensions / sniffio / h11 / idna 等 | 运行时支撑库 | MIT / BSD / PSF 类宽松许可 | + +开发期工具（pytest、ruff、python-docx 等）仅用于测试与文档构建，**不进入运行时镜像与服务**。 +如评审需要逐包许可证清单，可在隔离环境执行 `uv tree` / 查看 `uv.lock` 完整复现。 + +## 4. 数据与外部服务 + +- 线上服务不采集、不存储、不转发任何用户个人数据；内置示例数据（3 条演示笔记、演示天气文案）均为虚构。 +- 运行时唯一的外部出站请求是发往模型 API（线上为 DeepSeek，https://api.deepseek.com）的任务推理请求，遵循该服务方的公开服务条款；提交人对发送内容负责，不包含任何第三方隐私数据。 +- 不使用任何未授权的付费资源、私有数据集或抓取数据。 + +## 5. 提交与存档授权 + +提交人授权 X-Agent 官方及评审流程： + +1. 在隔离评审环境中拉取、构建、运行本提交的 `source/` 与在线服务，进行硬门槛校验、源码评审、安全与数据审查； +2. 在通过评审后，将与评审基线 commit 一致的完整源码复制到官方存档 ref、生成不可变的验收 release； +3. 对入选项目按公开规则进行 MCP 标准化适配（适配器与提交包由 X-Agent 侧拥有，底层能力的真实性、运行与维护责任由提交人承担）。 + +提交人理解：通过评审不构成 OKX 收录、上架、流量或收益的承诺；撤回未合并 PR 即视为退赛；已验收/获奖的源码将保留在官方存档中。 + +## 6. 商标与署名 + +- "YAI Agent Core" 与 "AMBRACE（拥爱）"为提交人自有项目名称； +- DeepSeek、OKX、X-Agent、Render、GitHub 等名称归各自权利人所有，本项目仅作技术兼容性描述，不暗示任何背书或关联关系。 diff --git a/submissions/mcp-hackathon/yai-agent-core/source/submissions/mcp-hackathon/yai-agent-core/SUBMISSION.md b/submissions/mcp-hackathon/yai-agent-core/source/submissions/mcp-hackathon/yai-agent-core/SUBMISSION.md new file mode 100644 index 0000000..df69135 --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/submissions/mcp-hackathon/yai-agent-core/SUBMISSION.md @@ -0,0 +1,111 @@ +# YAI Agent Core · X-Agent MCP Hackathon 提交说明 + +- **项目名**：YAI Agent Core（yai-agent-core） +- **提交团队**：YAI（单人开发者 Gi-Tuu，https://github.com/Gi-Tuu） +- **一句话定位**：进程内嵌入式、自适应的 Agent 内核——已有软件只需声明自己的普通业务函数（或挂载 MCP Server），Core 自动发现能力、自适应选择执行策略并完成任务，**宿主不写一行 Agent Loop / Planner / 工具选择代码**。 +- **在线 API**：https://yai-agent-core.onrender.com +- **源码仓库**：https://github.com/Gi-Tuu/yai-agent-core（MIT） +- **评审基线 commit**：以 `submission.json` 的 `reviewCommit`（40 位 SHA）为准，与 `/health`、`/.well-known/xagent-verification.json` 三处一致。 + +--- + +## 1. 解决什么真实问题 + +市面上的 Agent 形态分两类：平台型（Dify/Coze，要把东西搬进别人的云）和框架型（LangGraph/OpenAI Agents SDK，开发者仍要自己定义 Agent、工具、编排）。 +大量已有软件（笔记应用、数据后台、陪伴 App）想要 Agent 能力，但不想重写、不想上云、也不想在业务代码里堆 Agent 胶水代码。 + +YAI Agent Core 类比"Agent 世界的 SQLite"：以库的形式运行在宿主进程内，范式是 **host-declares-capability / core-adapts**： + +1. 宿主只提供普通 Python 函数（type hints + docstring），Core 内省生成工具规格； +2. 外部 MCP Server 的工具经 MCP Client 同构接入（v0.2 已落地）； + Core 同时内置 OpenAPI 发现（可选）：任意 OpenAPI 3 REST API 提供描述即可被自动注册为工具， + 与 MCP 工具在同一 Tool Bus 上同构调度（read_only 只读模式可用于公网演示）； +3. Adaptive Router 把任务路由到 `direct / react / plan / clarify` 四种策略： + v0.2 起先由模型做一次轻量分类（输出 `{strategy, reason, tier}` JSON）， + 超时/异常/非法输出自动回退确定性规则，**两条路径都返回带来源的决策记录**； +4. Agent Loop 完成 ReAct 工具循环 / 计划拆解执行（规划轮使用路由建议的模型档位）； +5. 每一次策略选择（含 `source=llm|rules` 与理由）、工具调用、权限确认都作为事件流出， + **过程可审计，不是黑盒**。 + +它不是又一个需要开发者拼装的 Agent 框架，而是可以"装进软件里"的内核；项目最终将回流嵌入开源 AI Companion 项目 AMBRACE。 + +## 2. 在线能力（评审可直接调用） + +| 端点 | 方法 | 说明 | +|---|---|---| +| `/health` | GET | 健康检查，返回 `status` 与本次部署的 40 位 commit | +| `/.well-known/xagent-verification.json` | GET | 部署证明：`schemaVersion=1` + `slug` + `commit` | +| `/v1/tools` | GET | 当前宿主注册的全部工具（含 `source: native/mcp/openapi` 来源标注；线上实例同时挂载本地笔记工具与公共 DeepWiki MCP Server 的 3 个远程工具） | +| `/v1/agent/run` | POST | 入参 `{"task": "..."}`，返回策略、最终结果与**全过程事件流**；任务涉及外部仓库问答时会真实发起 MCP 工具调用 | + +可复现的 curl 命令与期望输出见 `verification/README.md`。 + +> 免费实例 15 分钟无流量会休眠，首次请求冷启动约 30–90 秒，请耐心等待或先请求一次 `/health` 唤醒。 + +## 3. 工程与架构 + +``` +src/yai_core/ +├── types.py # ToolSpec / AgentEvent / Strategy 等核心数据结构（零依赖） +├── spi/ # Model / Channel / Memory / Policy 四个可替换契约 +├── discovery/ # 宿主函数内省 → ToolSpec（能力自发现） +├── tools/ # ToolRegistry（统一花名册）+ ToolExecutor（权限→执行→事件） +├── kernel/ # AdaptiveRouter（策略路由）+ Context + AgentLoop（主循环） +├── llm/ # OpenAI 兼容模型后端（DeepSeek 等，可选依赖、懒加载） +├── memory/ policy/ channels/ # 默认实现：内存记忆 + SQLite 持久化（opt-in）/ 白名单权限 / CLI·收集通道 +├── integrations/ +│ ├── mcp/ # MCP Client 桥接（可选 [mcp] 依赖、懒加载） +│ └── openapi/ # OpenAPI 3 发现 → 工具（可选 [openapi] 依赖、懒加载） +└── batteries/fastapi_server/ # 在线 API Battery（可选 [server] 依赖，含限流中间件；历史保留由宿主按 env 注入） +``` + +关键工程原则： + +- **内核本体零第三方硬依赖**：`pyproject.toml` 的 `dependencies` 为空；openai / fastapi / mcp / httpx 全部归入可选 extras（llm / server / mcp / openapi）并在模块内懒加载，有 AST 测试防止顶层误引入。 +- **工具同构**：本地函数与外部 MCP 工具在 ToolRegistry 中都是 ToolSpec，Router/Loop/Executor 对工具位置零感知。 +- **错误回灌而非崩溃**：工具（含 MCP 工具）异常被捕获为失败结果回灌模型，事件流照常完整。 +- **可复现**：`uv.lock` 锁定全部依赖；Dockerfile 多阶段构建、`docker compose` 一键起；Render Blueprint（`render.yaml`）即点即部署。 + +## 4. 测试与可观测 + +- 离线测试 **125 项**全部通过（截至 v0.3，以 `pytest -q` 实跑为准；不需要网络与 API Key）：用 ScriptedModel 假模型、内存态 MCP Server 假外部服务、`httpx.MockTransport` 假 REST 端点，覆盖路由、ReAct/Plan 循环、权限、MCP/OpenAPI 桥接、记忆保留策略、限流与 API 端点。 +- GitHub Actions CI 矩阵：Ubuntu × Python 3.11/3.12/3.13 + Windows × 3.13。 +- 每次运行返回完整事件序列（strategy_selected / plan_created / tool_call / tool_result / done…），可直接作为评审的"能力证据"。 +- 长期运行的记忆治理：历史支持条数上限与 TTL（opt-in，按对话轮对齐裁剪，不拆散工具调用对），SQLite 存储在写入与启动时自动清理过期历史，裁剪规则为纯函数并有对等测试。 + +## 5. MCP 产品化准备（对应 15 分评分项） + +- 工具边界清晰：每个工具有 name / description / JSON Schema 入参，MCP 工具 schema 经白名单清洗后与本地工具同构； +- 已实现 MCP Client（官方 Python SDK v2），支持 Streamable HTTP、stdio 子进程、内存直连三种传输； +- **线上 API 自身即 MCP 消费方**：部署期通过 `MCP_SERVER_URL` 环境变量挂载公共免鉴权 MCP Server（DeepWiki），评审可直接 POST 任务让线上服务真实调用远程 MCP 工具，挂载失败不影响本地工具与验证端点（优雅降级）； +- 错误语义明确：MCP `is_error` 统一翻译为失败结果并产生 `tool_result(ok=false)` 事件； +- 权限、副作用边界在 Tool Bus 一层统一收口；超时（规划中）同样收口于此；已实现评审期限流（每 IP 每分钟 30 次、429 + Retry-After，GET 验证端点不受限）； +- 入选后可直接配合 X-Agent 做工具边界与 I/O schema 标准化，本项目自身不绑定任何特定 MCP Server。 + +## 6. 安全与数据处理（评审须知） + +- 线上服务不提供账号体系、不采集个人信息：仅使用演示宿主自带的 3 条虚构笔记；会话历史按部署配置可落盘（`YAI_DB_PATH`，Render 免费层为临时盘、实例重建即清空），不用于任何训练或分析用途。 +- 出站请求仅发往配置的 LLM 端点（线上为 DeepSeek 官方 API）；代码内无任何遥测/统计 SDK。 +- API Key 仅存在于部署平台 Secret 与本地 `.env`（gitignore），不入库、不入镜像层（`.dockerignore` 排除）。 +- 评审期端点开放调用（满足"可在线调用"要求），已加按 IP 的零依赖限流（每 IP 每分钟 30 次，超限返回 429 与 Retry-After；health/verification/tools 三个验证端点不受限）；不提供登录墙。 +- 依赖与授权清单见 `RIGHTS.md`。 + +## 7. 本地复现（隔离环境，5–10 分钟） + +```bash +git clone https://github.com/Gi-Tuu/yai-agent-core && cd yai-agent-core +uv venv && uv sync --extra dev --extra llm --extra server --extra mcp --extra openapi +uv run pytest # 125 passed，离线 +uv run ruff check src tests examples scripts +uv run python scripts/smoke_test.py # 同一内核自适应三个不同宿主（离线） +docker compose up --build # 容器化（容器内 8000，宿主 127.0.0.1:8001） +``` + +接真实模型：复制 `.env.example` 为 `.env` 填入 OpenAI 兼容 Key（DeepSeek 等），运行 +`uv run python examples/host_d_mcp/run.py` 可看到本地工具与 MCP 工具在同一注册表里协同。 + +## 8. 已知限制（诚实声明） + +- 免费层部署会休眠、冷启动约 30–90 秒（波动较大，建议先请求 `/health` 预热）；正式评审期将迁移常驻 VPS（手册见仓库 `docs/competitions/deployment.md`）。 +- 路由为"单次轻量 LLM 分类 + 确定性规则兜底"，不做多层反思/多智能体编排；持久化记忆为 SQLite（opt-in），免费层临时盘随实例重建清空、且不支持多进程共享，长期留存需挂盘或迁移常驻 VPS；限流按 IP 滑动窗口，不防御伪造 XFF，当前无账号体系与鉴权（列入后续版本计划）。 +- 不做 MCP Server、Multi-Agent、自进化写工具、向量记忆、内置 UI、coding agent（明确的 v0.1 红线，避免过度设计）。 diff --git a/submissions/mcp-hackathon/yai-agent-core/source/submissions/mcp-hackathon/yai-agent-core/submission.template.json b/submissions/mcp-hackathon/yai-agent-core/source/submissions/mcp-hackathon/yai-agent-core/submission.template.json new file mode 100644 index 0000000..fb6f094 --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/submissions/mcp-hackathon/yai-agent-core/submission.template.json @@ -0,0 +1,10 @@ +{ + "schemaVersion": 1, + "name": "YAI Agent Core", + "slug": "yai-agent-core", + "sourceRepository": "https://github.com/Gi-Tuu/yai-agent-core", + "reviewCommit": "__REVIEW_COMMIT__", + "apiBaseUrl": "https://yai-agent-core.onrender.com", + "healthCheckUrl": "https://yai-agent-core.onrender.com/health", + "deploymentProofUrl": "https://yai-agent-core.onrender.com/.well-known/xagent-verification.json" +} diff --git a/submissions/mcp-hackathon/yai-agent-core/source/submissions/mcp-hackathon/yai-agent-core/verification/README.md b/submissions/mcp-hackathon/yai-agent-core/source/submissions/mcp-hackathon/yai-agent-core/verification/README.md new file mode 100644 index 0000000..bce6785 --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/submissions/mcp-hackathon/yai-agent-core/verification/README.md @@ -0,0 +1,104 @@ +# 在线验证手册（verification） + +- **API 同源基址**：`https://yai-agent-core.onrender.com` +- **评审基线 commit**：以 `../submission.json` 的 `reviewCommit`（40 位 SHA）为准。 +- **冷启动提示**：免费实例 15 分钟无流量会休眠，首次请求约 30–90 秒冷启动；建议先 curl 一次 health 唤醒，再做后续验证。 +- 以下 curl 命令在任意装有 curl 的环境可直接复现（Windows PowerShell / macOS / Linux 均可）。 + +## 1. health 健康检查（硬门槛） + +```bash +curl -sS https://yai-agent-core.onrender.com/health +``` + +期望返回（commit 必须与 reviewCommit 完全一致）： + +```json +{"status": "ok", "commit": "<40位 reviewCommit>"} +``` + +## 2. 部署证明端点（硬门槛，与 health 同源同 commit） + +```bash +curl -sS https://yai-agent-core.onrender.com/.well-known/xagent-verification.json +``` + +期望返回： + +```json +{"schemaVersion": 1, "slug": "yai-agent-core", "commit": "<40位 reviewCommit>"} +``` + +## 3. 工具清单（能力自发现 + 来源标注） + +```bash +curl -sS https://yai-agent-core.onrender.com/v1/tools +``` + +期望返回宿主演示应用自动发现的 3 个 native 工具（count_notes / list_notes / search_notes） +以及线上通过 MCP Client 挂载的 3 个 `source: "mcp"` 远程工具（ask_question / +read_wiki_contents / read_wiki_structure，来自公共免鉴权的 DeepWiki MCP Server）。 + +## 4. 真实 Agent 任务（POST，会真实调用 DeepSeek 模型） + +> 限流说明：`POST /v1/agent/run` 每 IP 每分钟 30 次；超限返回 429 与 `Retry-After`， +> 稍后重试即可。健康与验证端点（本手册第 1–3 节）不受限。 + +```bash +curl -sS -X POST https://yai-agent-core.onrender.com/v1/agent/run \ + -H "Content-Type: application/json" \ + -d '{"task": "搜索笔记里关于比赛的内容并总结"}' \ + --max-time 180 +``` + +期望返回 JSON，包含： + +- `strategy`：自适应路由结果（该任务通常为 `plan` 或 `react`）； +- `events[0]`（`strategy_selected`）带 `source`（`llm` 模型分类 / `rules` 规则兜底）、 + `reason`（中文决策理由）与 `tier`（standard/strong）——决策本身可审计； +- `final_text`：模型基于真实工具结果给出的中文总结； +- `events`：完整过程事件序列（`strategy_selected` → `tool_call` → `tool_result`（ok=true）→ … → `done`），证明工具被真实调用而非提示词演示。 + +PowerShell 若对内联 JSON 引号处理不一致，可改用： + +```powershell +$body = @{ task = "搜索笔记里关于比赛的内容并总结" } | ConvertTo-Json -Compress +curl.exe -sS -X POST https://yai-agent-core.onrender.com/v1/agent/run ` + -H "Content-Type: application/json" --data $body --max-time 180 +``` + +## 4b. 真实外部 MCP 工具调用（MCP 产品化硬证据） + +```bash +curl -sS -X POST https://yai-agent-core.onrender.com/v1/agent/run \ + -H "Content-Type: application/json" \ + -d '{"task": "用 MCP 工具问一下 GitHub 仓库 modelcontextprotocol/python-sdk：MCP 的 Client 怎么初始化？用中文给结论。"}' \ + --max-time 180 +``` + +期望：`strategy` 为 `react`；`events` 中出现对 `ask_question` 的 +`tool_call` / `tool_result(ok=true)`（该工具的来源标注 `source: "mcp"` 在第 3 节 `/v1/tools` 清单中查看，事件体本身不带 source 字段）；`final_text` 是基于远程 MCP 返回内容的中文回答。 +该调用链为：本服务 → DeepSeek 规划工具调用 → Streamable HTTP 调远程 MCP Server → 结果回灌 → 模型总结。 + +## 5. 本地/隔离环境复现 + +```bash +git clone https://github.com/Gi-Tuu/yai-agent-core +cd yai-agent-core +git checkout +uv sync --extra dev --extra llm --extra server --extra mcp --extra openapi +uv run pytest # 125 项离线测试全绿（截至 v0.3，以 pytest -q 实跑为准），不需要 API Key + # 注：extras 组合与 CI 一致（dev/llm/server/mcp/openapi），实跑 125 passed，无 skip +uv run ruff check src tests examples scripts +uv run python scripts/smoke_test.py # 三宿主自适应冒烟（离线） +docker compose up --build # 容器化：容器内 8000，宿主 127.0.0.1:8001 +# 本地容器验证：curl http://127.0.0.1:8001/health +``` + +## 6. 证据留存 + +- 部署平台：Render 免费层 Docker Web Service（Blueprint 见 `source/render.yaml`）， + 平台注入 `RENDER_GIT_COMMIT`，服务启动时按 `YAI_GIT_COMMIT → RENDER_GIT_COMMIT → git HEAD → dev` + 解析且只接受 40 位哈希，保证 health 上报的就是本次部署的真实 commit； +- CI：每次推送在 GitHub Actions（Ubuntu 3.11/3.12/3.13 + Windows 3.13）执行 ruff + pytest，状态见仓库 README 徽章与 Actions 页； +- 正式评审期如迁移常驻 VPS，仅更换部署环境，端点契约、slug、commit 校验逻辑不变，并会通过补充 PR 披露。 diff --git a/submissions/mcp-hackathon/yai-agent-core/source/tests/fixtures/petstore.min.json b/submissions/mcp-hackathon/yai-agent-core/source/tests/fixtures/petstore.min.json new file mode 100644 index 0000000..3f2e985 --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/tests/fixtures/petstore.min.json @@ -0,0 +1,74 @@ +{ + "openapi": "3.0.3", + "info": { "title": "Petstore Min", "version": "1.0" }, + "servers": [{ "url": "http://petstore.test/api/v3" }], + "security": [{ "bearerAuth": [] }], + "paths": { + "/pets": { + "get": { + "operationId": "listPets", + "summary": "列出宠物", + "parameters": [ + { "name": "limit", "in": "query", "schema": { "type": "integer" } }, + { "name": "tags", "in": "query", "schema": { "type": "array", "items": { "type": "string" } } }, + { "name": "verbose", "in": "query", "schema": { "type": "boolean" } }, + { "name": "X-Trace", "in": "header", "schema": { "type": "string" } } + ], + "responses": { "200": { "description": "ok" } } + }, + "post": { + "operationId": "createPet", + "summary": "创建宠物", + "requestBody": { + "required": true, + "content": { "application/json": { "schema": { "$ref": "#/components/schemas/Pet" } } } + }, + "responses": { "201": { "description": "created" } } + } + }, + "/pets/{petId}": { + "parameters": [ + { "name": "petId", "in": "path", "required": true, "schema": { "type": "integer" } } + ], + "get": { "summary": "查宠物", "responses": { "200": { "description": "ok" }, "404": { "description": "missing" } } }, + "delete": { "operationId": "deletePet", "summary": "删宠物", "responses": { "204": { "description": "gone" } } } + }, + "/echo/{kind}": { + "post": { + "operationId": "echoBody", + "parameters": [ + { "name": "kind", "in": "path", "required": true, "schema": { "type": "string" } } + ], + "requestBody": { + "required": true, + "content": { "application/json": { "schema": { "type": "array", "items": { "type": "string" } } } } + }, + "responses": { "200": { "description": "ok" } } + } + } + }, + "components": { + "schemas": { + "Pet": { + "type": "object", + "required": ["id", "name"], + "properties": { + "id": { "type": "integer", "format": "int64" }, + "name": { "type": "string" }, + "category": { "$ref": "#/components/schemas/Category" } + } + }, + "Category": { + "type": "object", + "properties": { + "name": { "type": "string" }, + "children": { "type": "array", "items": { "$ref": "#/components/schemas/Category" } } + } + } + }, + "securitySchemes": { + "bearerAuth": { "type": "http", "scheme": "bearer" }, + "keyHeader": { "type": "apiKey", "in": "header", "name": "X-Api-Key" } + } + } +} diff --git a/submissions/mcp-hackathon/yai-agent-core/source/tests/test_battery_api.py b/submissions/mcp-hackathon/yai-agent-core/source/tests/test_battery_api.py new file mode 100644 index 0000000..c6666f5 --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/tests/test_battery_api.py @@ -0,0 +1,101 @@ +"""FastAPI Battery 端点测试：离线脚本模型 + TestClient，不需要 API Key 与网络。""" + +from __future__ import annotations + +import contextlib + +import pytest +from fastapi.testclient import TestClient + +from yai_core import AgentCore, ModelResponse, build_spec +from yai_core.batteries.fastapi_server import create_app + + +class ScriptedModel: + def __init__(self, text: str) -> None: + self._text = text + + async def achat(self, messages, tools=None, *, tier="standard"): + return ModelResponse(content=self._text) + + +def list_notes() -> list: + """列出全部笔记。""" + return [{"id": 1, "title": "Core 骨架"}] + + +def _client(monkeypatch) -> TestClient: + monkeypatch.setenv("YAI_GIT_COMMIT", "0" * 40) + monkeypatch.setenv("YAI_PROJECT_SLUG", "yai-test") + core = AgentCore(ScriptedModel("你好，我是内嵌助手。")) + core.register_tools([build_spec(list_notes)]) + return TestClient(create_app(core)) + + +def test_health(monkeypatch) -> None: + resp = _client(monkeypatch).get("/health") + assert resp.status_code == 200 + body = resp.json() + assert body["status"] == "ok" + assert len(body["commit"]) == 40 # X-Agent 硬门槛：40 位 commit + + +def test_xagent_verification(monkeypatch) -> None: + resp = _client(monkeypatch).get("/.well-known/xagent-verification.json") + assert resp.status_code == 200 + body = resp.json() + assert body == {"schemaVersion": 1, "slug": "yai-test", "commit": "0" * 40} + + +def test_tools_endpoint_lists_discovered_capabilities(monkeypatch) -> None: + resp = _client(monkeypatch).get("/v1/tools") + assert resp.status_code == 200 + names = [t["name"] for t in resp.json()] + assert "list_notes" in names + + +def test_agent_run_endpoint_returns_events_and_text(monkeypatch) -> None: + resp = _client(monkeypatch).post("/v1/agent/run", json={"task": "你好"}) + assert resp.status_code == 200 + body = resp.json() + assert body["strategy"] == "direct" + assert body["final_text"].startswith("你好") + event_types = [e["type"] for e in body["events"]] + assert "strategy_selected" in event_types + assert event_types[-1] == "done" + + +def test_lifespan_attaches_mcp_tools(monkeypatch) -> None: + """lifespan 挂载的外部 MCP 工具要出现在 /v1/tools（线上部署形态的离线回放）。""" + pytest.importorskip("mcp") + from mcp.server import MCPServer + + from yai_core.integrations.mcp import McpServerConfig, attach_mcp_tools + + monkeypatch.setenv("YAI_GIT_COMMIT", "0" * 40) + monkeypatch.setenv("YAI_PROJECT_SLUG", "yai-test") + + server = MCPServer("TestWiki") + + @server.tool() + def ask_question(repoName: str, question: str) -> str: + """Ask a question about a repository.""" + return f"wiki answer for {repoName}: {question}" + + core = AgentCore(ScriptedModel("ok")) + core.register_tools([build_spec(list_notes)]) + + @contextlib.asynccontextmanager + async def lifespan(_app): + bridge = await attach_mcp_tools( + core.registry, McpServerConfig(alias="wiki", server=server) + ) + try: + yield + finally: + await bridge.aclose() + + with TestClient(create_app(core, lifespan=lifespan)) as client: + tools = {t["name"]: t for t in client.get("/v1/tools").json()} + assert "list_notes" in tools # native 工具仍在 + assert tools["ask_question"]["source"] == "mcp" # MCP 工具同构挂载 diff --git a/submissions/mcp-hackathon/yai-agent-core/source/tests/test_context_compact.py b/submissions/mcp-hackathon/yai-agent-core/source/tests/test_context_compact.py new file mode 100644 index 0000000..14a97cd --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/tests/test_context_compact.py @@ -0,0 +1,67 @@ +"""Context._compact 轮边界丢弃专项：压缩不得拆散 assistant(tool_calls)/tool 对。""" + +from __future__ import annotations + +from yai_core.kernel.context import Context +from yai_core.types import ChatMessage + + +def _tool_round(marker: str, big: int) -> list[ChatMessage]: + """构造一轮含工具调用的历史：user(大) -> assistant(tool_calls) -> tool(大)。""" + return [ + ChatMessage(role="user", content=marker * big), + ChatMessage( + role="assistant", + content="", + tool_calls=[{"id": marker, "name": "t", "arguments": {}}], + ), + ChatMessage(role="tool", content=marker * big, tool_call_id=marker), + ] + + +def test_compact_drops_whole_round_and_keeps_system() -> None: + ctx = Context("系统提示", max_chars=10) + ctx.messages.extend(_tool_round("旧", 50)) + ctx.messages.extend( + [ + ChatMessage(role="user", content="新任务"), + ChatMessage(role="assistant", content="完成"), + ] + ) + ctx._compact() + assert [m.role for m in ctx.messages] == ["system", "user", "assistant"] + assert ctx.messages[0].content == "系统提示" + assert ctx.messages[1].content == "新任务" + + +def test_compact_within_budget_unchanged() -> None: + ctx = Context("系统提示", max_chars=24000) + ctx.messages.extend(_tool_round("x", 10)) + before = list(ctx.messages) + ctx._compact() + assert ctx.messages == before + + +def test_compact_keeps_last_round_even_if_over_budget() -> None: + ctx = Context("系统提示", max_chars=10) + ctx.messages.extend(_tool_round("大", 50)) # 只有一轮且超预算 + ctx._compact() + # 宁可超预算也不裁：system + 完整工具轮（4 条） + assert [m.role for m in ctx.messages] == [ + "system", + "user", + "assistant", + "tool", + ] + + +def test_compact_triggered_via_add_path() -> None: + ctx = Context("系统提示", max_chars=10) + ctx.messages.extend(_tool_round("旧", 50)) + # 公共 add 路径追加新一轮时触发压缩，旧工具轮整轮消失、新轮完整 + ctx.add(ChatMessage(role="user", content="新")) + ctx.add(ChatMessage(role="assistant", content="好")) + roles = [m.role for m in ctx.messages] + assert roles[0] == "system" + assert "tool" not in roles # 旧工具轮被整轮删掉，没有孤儿 tool 残留 + assert roles[-2:] == ["user", "assistant"] diff --git a/submissions/mcp-hackathon/yai-agent-core/source/tests/test_discovery.py b/submissions/mcp-hackathon/yai-agent-core/source/tests/test_discovery.py new file mode 100644 index 0000000..f71726b --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/tests/test_discovery.py @@ -0,0 +1,25 @@ +from yai_core import build_spec + + +def search_notes(keyword: str, limit: int = 5) -> list: + """按关键词搜索笔记。""" + return [] + + +def test_build_spec_basic_types_and_required() -> None: + spec = build_spec(search_notes) + assert spec.name == "search_notes" + assert spec.description == "按关键词搜索笔记。" + props = spec.input_schema["properties"] + assert props["keyword"]["type"] == "string" + assert props["limit"]["type"] == "integer" + assert props["limit"]["default"] == 5 + assert spec.input_schema["required"] == ["keyword"] + + +def test_llm_schema_shape() -> None: + spec = build_spec(search_notes) + llm = spec.llm_schema() + assert llm["type"] == "function" + assert llm["function"]["name"] == "search_notes" + assert "parameters" in llm["function"] diff --git a/submissions/mcp-hackathon/yai-agent-core/source/tests/test_loop.py b/submissions/mcp-hackathon/yai-agent-core/source/tests/test_loop.py new file mode 100644 index 0000000..1ac5523 --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/tests/test_loop.py @@ -0,0 +1,138 @@ +"""端到端测试：用脚本化假模型离线验证 react 循环，不需要 API Key。""" + +import asyncio + +from yai_core import AgentCore, ModelResponse, ToolCallRequest, build_spec + + +class ScriptedModel: + """按预设顺序返回响应的假模型，用于离线测试。""" + + def __init__(self, responses: list[ModelResponse]) -> None: + self._responses = responses + self.calls = 0 + + async def achat(self, messages, tools=None, *, tier="standard"): + resp = self._responses[min(self.calls, len(self._responses) - 1)] + self.calls += 1 + return resp + + +NOTES = {"周报": ["周一完成 Core 骨架", "周三跑通工具调用"], "其他": ["买菜"]} + + +def search_notes(keyword: str) -> list: + """搜索宿主笔记库。""" + return NOTES.get(keyword, []) + + +def test_react_loop_calls_tool_and_finishes() -> None: + model = ScriptedModel( + [ + ModelResponse( + content="", + tool_calls=[ToolCallRequest(id="c1", name="search_notes", + arguments={"keyword": "周报"})], + ), + ModelResponse(content="本周周报包含 2 条记录：Core 骨架、工具调用。"), + ] + ) + core = AgentCore(model) + core.register_tools([build_spec(search_notes)]) + + result = asyncio.run(core.run("搜索笔记里关于周报的内容并总结")) + + event_types = [e.type.value for e in result.events] + assert "strategy_selected" in event_types + assert "tool_call" in event_types + assert "tool_result" in event_types + assert event_types[-1] == "done" + assert "周报" in result.final_text + assert model.calls == 2 + + +def test_plan_strategy_still_executes_tools() -> None: + """回归：plan 拆完步骤后必须真正进入工具循环，不能把计划当最终答复。""" + + def search_notes(keyword: str) -> list: + """搜索宿主笔记库。""" + return ["X-Agent 0919 截止"] if keyword == "比赛" else [] + + model = ScriptedModel( + [ + ModelResponse(content="1. 搜索比赛笔记\n2. 统计总数并汇报"), # 规划轮（无 tools） + ModelResponse( + content="", + tool_calls=[ToolCallRequest(id="p1", name="search_notes", + arguments={"keyword": "比赛"})], + ), + ModelResponse(content="找到 1 条比赛相关笔记。"), + ] + ) + core = AgentCore(model) + core.register_tools([build_spec(search_notes)]) + + result = asyncio.run(core.run("先搜索比赛笔记，然后汇报")) + + assert result.strategy.value == "plan" + event_types = [e.type.value for e in result.events] + assert "plan_created" in event_types + assert "tool_call" in event_types + assert "tool_result" in event_types + assert "比赛" in result.final_text + + +def test_direct_answer_without_tools() -> None: + model = ScriptedModel([ModelResponse(content="你好，我是内嵌助手。")]) + core = AgentCore(model) + result = asyncio.run(core.run("你好")) + assert result.strategy.value == "direct" + assert result.final_text.startswith("你好") + + +def test_llm_router_decision_flows_through_loop() -> None: + """开启 llm_router 后：分类来源/理由/档位进事件，plan 用分类建议的 strong 档。""" + + class ClassifierThenPlan(ScriptedModel): + async def achat(self, messages, tools=None, *, tier="standard"): + self.tiers.append(tier) + self.calls += 1 + # 第 1 次调用是路由分类（系统提示含"路由器"） + if self.calls == 1: + return ModelResponse( + content='{"strategy": "plan", "tier": "strong",' + ' "reason": "先拆解再执行"}' + ) + # 第 2 次是规划轮 + if self.calls == 2: + return ModelResponse(content="1. 搜索比赛笔记\n2. 汇报结果") + # 之后走父类的脚本队列（工具调用 + 最终答复） + return self._responses[min(self.calls - 1, len(self._responses) - 1)] + + def __init__(self, responses) -> None: + super().__init__(responses) + self.tiers = [] + + model = ClassifierThenPlan( + [ + ModelResponse( + content="", + tool_calls=[ToolCallRequest(id="p1", name="search_notes", + arguments={"keyword": "比赛"})], + ), + ModelResponse(content="找到 1 条比赛笔记。"), + ] + ) + core = AgentCore(model, llm_router=True) + core.register_tools([build_spec(search_notes)]) + + result = asyncio.run(core.run("先搜索比赛笔记，然后汇报")) + + selected = next(e for e in result.events if e.type.value == "strategy_selected") + assert selected.data["source"] == "llm" + assert selected.data["strategy"] == "plan" + assert selected.data["tier"] == "strong" + # 分类用 standard（轻量快），规划轮按建议用 strong，工具循环回 standard + assert model.tiers[0] == "standard" + assert model.tiers[1] == "strong" + assert result.final_text.startswith("找到") diff --git a/submissions/mcp-hackathon/yai-agent-core/source/tests/test_mcp_bridge.py b/submissions/mcp-hackathon/yai-agent-core/source/tests/test_mcp_bridge.py new file mode 100644 index 0000000..a42da56 --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/tests/test_mcp_bridge.py @@ -0,0 +1,197 @@ +"""MCP Client 桥接层测试：内存直连 MCPServer，全程不起子进程、不触网。 + +未安装 mcp 可选依赖时整文件自动跳过（内核本体仍保持零依赖可测）。 +""" + +import ast +import json +import pathlib + +import pytest + +pytest.importorskip("mcp") # 没装 [mcp] extra 的环境（如最小 CI）跳过本文件 + +from mcp.server import MCPServer # noqa: E402 +from mcp.server.mcpserver.exceptions import ToolError # noqa: E402 +from pydantic import BaseModel # noqa: E402 + +from yai_core.channels import CollectChannel # noqa: E402 +from yai_core.integrations.mcp import ( # noqa: E402 + McpServerConfig, + McpToolBridge, + attach_mcp_tools, + config_from_env, + sanitize_schema, +) +from yai_core.policy import AllowlistPolicy # noqa: E402 +from yai_core.tools import ToolExecutor, ToolRegistry # noqa: E402 + + +class Book(BaseModel): + title: str + year: int + + +def build_server() -> MCPServer: + """构造内存 MCP Server：一个文本工具、一个结构化工具、一个必错工具。""" + server = MCPServer("TestShop") + + @server.tool() + def echo(text: str) -> str: + """Echo back the text.""" + return f"echo: {text}" + + @server.tool() + def make_book(title: str, year: int = 2026) -> Book: + """Make a structured book.""" + return Book(title=title, year=year) + + @server.tool() + def boom() -> str: + """Always fails.""" + raise ToolError("boom-message") + + return server + + +def test_connect_registers_mcp_tools() -> None: + import asyncio + + async def scenario() -> None: + bridge = McpToolBridge(McpServerConfig(alias="t", server=build_server())) + specs = await bridge.connect() + assert {s.name for s in specs} == {"echo", "make_book", "boom"} + assert all(s.source == "mcp" for s in specs) + # SDK 自动生成的 schema 带 title 私有键，必须被清洗掉 + echo = next(s for s in specs if s.name == "echo") + assert "title" not in echo.input_schema + assert echo.input_schema["required"] == ["text"] + registry = ToolRegistry() + registry.register_many(specs) + assert registry.has("echo") + await bridge.aclose() + + asyncio.run(scenario()) + + +def test_prefix_namespacing_keeps_remote_name() -> None: + """本地名加前缀防重名，但闭包内部仍调用远端原名。""" + import asyncio + + async def scenario() -> None: + cfg = McpServerConfig(alias="t", server=build_server(), prefix="demo__") + async with McpToolBridge(cfg) as bridge: + registry = ToolRegistry() + registry.register_many(bridge.specs) + assert registry.has("demo__echo") + spec = registry.get("demo__echo") + text = await spec.handler(text="hi") + assert text == "echo: hi" + + asyncio.run(scenario()) + + +def test_handler_text_and_structured_results() -> None: + import asyncio + + async def scenario() -> None: + async with McpToolBridge(McpServerConfig(alias="t", server=build_server())) as b: + specs = {s.name: s for s in b.specs} + assert await specs["echo"].handler(text="hi") == "echo: hi" + book_text = await specs["make_book"].handler(title="Dune", year=1965) + assert "Dune" in book_text and "1965" in book_text + + asyncio.run(scenario()) + + +def test_error_tool_raises_for_executor() -> None: + """MCP is_error 结果必须翻译成异常，由 Executor 统一走失败回灌。""" + import asyncio + + async def scenario() -> None: + async with McpToolBridge(McpServerConfig(alias="t", server=build_server())) as b: + boom = next(s for s in b.specs if s.name == "boom") + with pytest.raises(RuntimeError, match="boom-message"): + await boom.handler() + + asyncio.run(scenario()) + + +def test_executor_runs_mcp_tools_end_to_end() -> None: + """MCP 工具经过 ToolExecutor 与 Native 工具行为一致（含权限/事件/错误）。""" + import asyncio + + async def scenario() -> None: + registry = ToolRegistry() + bridge = await attach_mcp_tools( + registry, McpServerConfig(alias="t", server=build_server()) + ) + executor = ToolExecutor(registry, AllowlistPolicy(mode="allow_all"), CollectChannel()) + + events, ok, text = await executor.execute("echo", {"text": "hi"}) + assert ok is True + # Executor 对一切返回值统一 json.dumps，字符串结果即 JSON 字符串 + assert json.loads(text) == "echo: hi" + assert events[0].data["tool"] == "echo" + + events2, ok2, text2 = await executor.execute("boom", {}) + assert ok2 is False + assert "boom-message" in text2 + assert events2[-1].data["ok"] is False + + await bridge.aclose() + + asyncio.run(scenario()) + + +def test_config_requires_exactly_one_target() -> None: + import asyncio + + async def scenario() -> None: + with pytest.raises(ValueError, match="之一"): + await McpToolBridge(McpServerConfig(alias="t")).connect() + with pytest.raises(ValueError, match="之一"): + await McpToolBridge( + McpServerConfig(alias="t", url="http://x/mcp", server=build_server()) + ).connect() + + asyncio.run(scenario()) + + +def test_sanitize_schema() -> None: + raw = { + "title": "echoArguments", + "type": "object", + "properties": {"text": {"title": "Text", "type": "string"}}, + "required": ["text"], + } + clean = sanitize_schema(raw) + assert "title" not in clean and "title" not in clean["properties"]["text"] + assert clean["type"] == "object" + assert sanitize_schema({}) == {"type": "object", "properties": {}} + assert sanitize_schema(["a", 1]) == ["a", 1] + + +def test_config_from_env() -> None: + """部署期通过环境变量决定接哪个 MCP Server；未配置时返回 None（不报错）。""" + assert config_from_env(env={}) is None + + url_cfg = config_from_env(alias="deepwiki", env={"MCP_SERVER_URL": "https://x/mcp"}) + assert url_cfg is not None and url_cfg.url == "https://x/mcp" and url_cfg.alias == "deepwiki" + + cmd_cfg = config_from_env(env={"MCP_SERVER_COMMAND": "python server.py --stdio"}) + assert cmd_cfg is not None and cmd_cfg.command == "python" + assert cmd_cfg.args == ["server.py", "--stdio"] + + +def test_no_toplevel_mcp_import_keeps_kernel_dependency_free() -> None: + """红线：client.py 顶层不允许 import mcp，mcp 只能在函数体内懒加载。""" + client_path = pathlib.Path(__file__).parents[1] / "src" / "yai_core" / ( + "integrations/mcp/client.py" + ) + tree = ast.parse(client_path.read_text(encoding="utf-8")) + for node in tree.body: # 只检查模块顶层语句 + if isinstance(node, ast.Import): + assert all(not a.name.startswith("mcp") for a in node.names) + if isinstance(node, ast.ImportFrom): + assert node.module is None or not node.module.startswith("mcp") diff --git a/submissions/mcp-hackathon/yai-agent-core/source/tests/test_memory_retention.py b/submissions/mcp-hackathon/yai-agent-core/source/tests/test_memory_retention.py new file mode 100644 index 0000000..3a4b06e --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/tests/test_memory_retention.py @@ -0,0 +1,314 @@ +"""历史保留策略测试：纯函数边界 + 两种 Store 参数化对等 + SQLite 专项。 + +全程离线：内存库 / tmp_path 文件库 / 注入假时钟，零网络、零 Key、零 sleep。 +""" + +from __future__ import annotations + +import asyncio +import warnings +from datetime import UTC, datetime, timedelta + +import pytest + +from yai_core.memory import InMemoryStore, SqliteStore, retention_from_env +from yai_core.memory.retention import count_cut, ttl_cut +from yai_core.types import ChatMessage + + +def run(coro): + """同步测试里跑一个协程的小工具（仓库既有风格，不引入 pytest-asyncio）。""" + return asyncio.run(coro) + + +class FakeClock: + """可手动推进的时钟：测试推进时间而不是 sleep 等真实窗口。""" + + def __init__(self, start: datetime) -> None: + self.now = start + + def __call__(self) -> datetime: + return self.now + + def advance(self, **kwargs) -> None: + self.now += timedelta(**kwargs) + + +def append_roles(store, roles: list[str]) -> None: + """按简写角色序列追加消息；a_tc=带 tool_calls 的 assistant，tool=其工具结果。""" + for idx, role in enumerate(roles): + if role == "a_tc": + message = ChatMessage( + role="assistant", + content="", + tool_calls=[{"id": f"c{idx}", "name": "t", "arguments": {}}], + ) + elif role == "tool": + message = ChatMessage( + role="tool", content="结果", tool_call_id=f"c{idx - 1}" + ) + else: + message = ChatMessage( + role={"u": "user", "a": "assistant"}[role], + content=f"{role}{idx}", + ) + run(store.append_history(message)) + + +def assert_well_formed(messages: list[ChatMessage]) -> None: + """工具调用对完整性：无孤儿 tool、无被截断的 tool_calls 助手消息。""" + for i, message in enumerate(messages): + if message.role == "tool": + prev = messages[i - 1] + assert prev.role == "assistant" and prev.tool_calls, f"孤儿 tool 消息 @ {i}" + if message.role == "assistant" and message.tool_calls: + assert i + len(message.tool_calls) < len(messages), f"截断的 tool_calls @ {i}" + for _j in range(len(message.tool_calls)): + assert messages[i + 1 + _j].role == "tool" + + +def install_deleted_counter(store) -> dict[str, int]: + """累计 append 触发的内部裁剪删除条数（两种实现挂钩点不同）。""" + total = {"n": 0} + orig_prune = store.prune + + def counting_prune() -> int: + result = orig_prune() + total["n"] += result + return result + + store.prune = counting_prune + orig_locked = getattr(store, "_prune_locked", None) + if orig_locked is not None: + + def counting_locked() -> int: + result = orig_locked() + total["n"] += result + return result + + store._prune_locked = counting_locked + return total + + +@pytest.fixture(params=["memory", "sqlite"]) +def make_store(request, tmp_path): + """同一组对等用例分别构造 InMemoryStore 与 SqliteStore（每个用例独立 db 文件）。""" + opened: list = [] + + def _make(**kwargs): + if request.param == "memory": + store = InMemoryStore(**kwargs) + else: + store = SqliteStore(tmp_path / f"ret_{len(opened)}.db", **kwargs) + opened.append(store) + return store + + yield _make + + for store in opened: + close = getattr(store, "close", None) + if close is not None: + close() + + +# ---------- A 组：纯函数边界（不依赖任何 Store） ---------- + +def test_count_cut_round_alignment() -> None: + three_rounds = ["user", "assistant"] * 3 + assert count_cut(three_rounds, 2) == 4 + assert count_cut(three_rounds, 3) == 4 # 候选落在 assistant 上，后移到下一轮首 + assert count_cut(three_rounds, 6) is None # 恰好不裁 + assert count_cut(three_rounds, None) is None + # 单轮（即使自身超限）不裁，至少保留最后一轮 + assert count_cut(["user", "assistant", "assistant", "assistant", "assistant"], 2) is None + # 历史开头的非 user 消息归"第 0 轮"，随第一轮一起删 + assert count_cut(["assistant", "user", "assistant", "user", "assistant"], 2) == 3 + assert count_cut(["user", "assistant"], 2) is None + assert count_cut([], 5) is None + + +def test_ttl_cut_round_alignment() -> None: + roles = ["user", "assistant"] * 3 + assert ttl_cut(roles, [True] * 4 + [False] * 2) == 4 + assert ttl_cut(roles, [True] * 2 + [False] * 4) == 2 # 恰好整轮过期 + assert ttl_cut(roles, [True] + [False] * 5) is None # 只过期到首轮中间，不裁 + assert ttl_cut(roles, [False] * 6) is None + assert ttl_cut(roles, [True] * 6) == 6 # 全部过期：整库清空（空历史合法） + # 前导非 user 消息（第 0 轮）全部过期时随全库清空 + assert ttl_cut(["assistant", "user", "assistant"], [True] * 3) == 3 + + +def test_retention_from_env_states() -> None: + assert retention_from_env({}) == (None, None) + assert retention_from_env({"YAI_HISTORY_MAX_MESSAGES": "200"}) == (200, None) + assert retention_from_env({"YAI_HISTORY_TTL_SECONDS": "604800"}) == (None, 604800) + # 空白等同未设置，静默 + with warnings.catch_warnings(record=True) as caught: + warnings.simplefilter("always") + assert retention_from_env({"YAI_HISTORY_MAX_MESSAGES": " "}) == (None, None) + assert caught == [] + # 0 / 负数 / 非整数：回退 None 且每项各一条 warning + for bad in ("0", "-3", "abc"): + with warnings.catch_warnings(record=True) as caught: + warnings.simplefilter("always") + assert retention_from_env( + {"YAI_HISTORY_MAX_MESSAGES": bad, "YAI_HISTORY_TTL_SECONDS": bad} + ) == (None, None) + assert len(caught) == 2 + + +# ---------- B 组：两种 Store 参数化对等 ---------- + +def test_default_keeps_everything(make_store) -> None: + store = make_store() + append_roles(store, ["u", "a"] * 25) + assert len(store.history()) == 50 + + +def test_count_trim_keeps_last_round_and_reports_deleted(make_store) -> None: + store = make_store(max_messages=2) + deleted = install_deleted_counter(store) + append_roles(store, ["u", "a", "u", "a", "u", "a"]) + assert [m.role for m in store.history()] == ["user", "assistant"] + assert deleted["n"] == 4 # 增量裁剪累计删掉 4 条 + assert_well_formed(store.history()) + + +def test_exact_boundary_no_delete(make_store) -> None: + store = make_store(max_messages=6) + append_roles(store, ["u", "a"] * 3) + assert len(store.history()) == 6 + assert store.prune() == 0 + + +def test_single_round_over_limit_not_trimmed(make_store) -> None: + store = make_store(max_messages=2) + append_roles(store, ["u", "a", "a", "a", "a"]) + assert len(store.history()) == 5 + assert store.prune() == 0 + + +def test_tool_pairs_never_split(make_store) -> None: + # 朴素按条硬删会在第 3/4 条切开工具对；轮对齐后必须完整 + store = make_store(max_messages=3) + append_roles(store, ["u", "a_tc", "tool", "u", "a"]) + assert_well_formed(store.history()) + + store = make_store(max_messages=4) + append_roles(store, ["u", "a_tc", "tool", "u", "a_tc", "tool", "u", "a"]) + assert_well_formed(store.history()) + assert [m.role for m in store.history()] == ["user", "assistant"] + + +def test_ttl_drops_expired_round_keeps_recent(make_store) -> None: + # 基准取真实 UTC 当前时刻并抹掉微秒：SQLite 落库为秒级 UTC 文本，必须同基准 + clock = FakeClock(datetime.now(UTC).replace(microsecond=0)) + store = make_store(ttl_seconds=60, clock=clock) + append_roles(store, ["u", "a"]) + clock.advance(seconds=120) + append_roles(store, ["u", "a"]) + assert [m.role for m in store.history()] == ["user", "assistant"] + assert_well_formed(store.history()) + + +def test_ttl_equal_cutoff_is_retained(make_store) -> None: + clock = FakeClock(datetime.now(UTC).replace(microsecond=0)) + store = make_store(ttl_seconds=60, clock=clock) + append_roles(store, ["u", "a"]) + clock.advance(seconds=60) # cutoff 恰好等于消息时间戳：严格 < 语义下保留 + assert store.prune() == 0 + assert len(store.history()) == 2 + + +def test_ttl_all_expired_clears_store(make_store) -> None: + clock = FakeClock(datetime.now(UTC).replace(microsecond=0)) + store = make_store(ttl_seconds=60, clock=clock) + append_roles(store, ["u", "a"]) + clock.advance(seconds=61) # 唯一一轮也全部过期 -> 整库清空 + assert store.prune() == 2 + assert store.history() == [] + + +def test_prune_idempotent(make_store) -> None: + store = make_store(max_messages=2) + append_roles(store, ["u", "a"] * 3) + first = store.prune() + assert first == 0 # append 时已裁完，显式再裁无东西可删 + assert store.prune() == 0 + + +def test_clear_resets_history_and_timestamps(make_store) -> None: + store = make_store(max_messages=2) + append_roles(store, ["u", "a"]) + run(store.clear()) + assert store.history() == [] + # 清空后重新写入，裁剪逻辑仍正常（时间戳列表没有残留） + append_roles(store, ["u", "a", "u", "a", "u", "a"]) + assert [m.role for m in store.history()] == ["user", "assistant"] + + +# ---------- C 组：SqliteStore 专项 ---------- + +def test_scope_isolation_under_retention(tmp_path) -> None: + db = tmp_path / "scope.db" + a = SqliteStore(db, scope="a", max_messages=2) + b = SqliteStore(db, scope="b", max_messages=2) + try: + append_roles(a, ["u", "a", "u", "a", "u", "a"]) + append_roles(b, ["u", "a"]) + assert [m.role for m in a.history()] == ["user", "assistant"] + assert len(b.history()) == 2 # A 的裁剪不动 B + finally: + a.close() + b.close() + + +def test_startup_prune_on_construction(tmp_path) -> None: + db = tmp_path / "startup.db" + old = SqliteStore(db) # 旧实例：未配置保留策略 + append_roles(old, ["u", "a"]) + old.close() + # 新实例：把时钟拨到 30 天后并配置 1 小时 TTL，构造期 prune 应清空过期历史 + future = FakeClock(datetime.now(UTC).replace(microsecond=0) + timedelta(days=30)) + fresh = SqliteStore(db, ttl_seconds=3600, clock=future) + try: + assert fresh.history() == [] + finally: + fresh.close() + + +def test_close_then_prune_raises(tmp_path) -> None: + store = SqliteStore(tmp_path / "closed.db", max_messages=2) + store.close() + with pytest.raises(RuntimeError, match="已关闭"): + store.prune() + + +def test_from_env_passes_retention(tmp_path) -> None: + store = SqliteStore.from_env( + env={ + "YAI_DB_PATH": str(tmp_path / "env.db"), + "YAI_HISTORY_MAX_MESSAGES": "2", + "YAI_HISTORY_TTL_SECONDS": "60", + } + ) + assert store is not None + try: + assert store._max_messages == 2 + assert store._ttl_seconds == 60 + finally: + store.close() + + +def test_from_env_explicit_retention_tuple(tmp_path) -> None: + # 无路径仍返回 None（即使显式传了 retention） + assert SqliteStore.from_env(env={}, retention=(4, None)) is None + store = SqliteStore.from_env( + env={"YAI_DB_PATH": str(tmp_path / "env2.db")}, retention=(4, None) + ) + assert store is not None + try: + assert store._max_messages == 4 + assert store._ttl_seconds is None + finally: + store.close() diff --git a/submissions/mcp-hackathon/yai-agent-core/source/tests/test_openai_compat.py b/submissions/mcp-hackathon/yai-agent-core/source/tests/test_openai_compat.py new file mode 100644 index 0000000..a6f0f55 --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/tests/test_openai_compat.py @@ -0,0 +1,131 @@ +"""OpenAICompatProvider 协议层测试：用假 openai 模块离线验证 DeepSeek 同款链路。 + +不发任何网络请求，验证四件事： +1. 第一次请求携带 OpenAI function-calling 的 tools 描述； +2. provider 能把 SDK 返回的 tool_calls 解析成 ToolCallRequest； +3. 宿主函数被真正执行； +4. 第二次请求把结果以 role="tool" + tool_call_id 回灌（DeepSeek/OpenAI 硬性协议）。 +""" + +from __future__ import annotations + +import asyncio +import sys +import types +from typing import Any + +from yai_core import AgentCore, OpenAICompatProvider, build_spec + +# ---------- 假 openai SDK ---------- + +class _FakeFunction: + def __init__(self, name: str, arguments: str) -> None: + self.name = name + self.arguments = arguments + + +class _FakeToolCall: + def __init__(self, call_id: str, name: str, arguments: str) -> None: + self.id = call_id + self.type = "function" + self.function = _FakeFunction(name, arguments) + + +class _FakeMessage: + def __init__(self, content: str | None, tool_calls: list[_FakeToolCall] | None = None) -> None: + self.content = content + self.tool_calls = tool_calls + + +class _FakeChoice: + def __init__(self, message: _FakeMessage) -> None: + self.message = message + + +class _FakeCompletions: + def __init__(self, script: list[_FakeMessage], captured: list[dict[str, Any]]) -> None: + self._script = script + self._captured = captured + self.calls = 0 + + async def create(self, **kwargs: Any) -> Any: + self._captured.append(kwargs) + message = self._script[min(self.calls, len(self._script) - 1)] + self.calls += 1 + return types.SimpleNamespace(choices=[_FakeChoice(message)]) + + +class _FakeAsyncOpenAI: + script: list[_FakeMessage] = [] + captured: list[dict[str, Any]] = [] + + def __init__(self, **kwargs: Any) -> None: + self.chat = types.SimpleNamespace( + completions=_FakeCompletions(_FakeAsyncOpenAI.script, _FakeAsyncOpenAI.captured) + ) + + +def _install_fake_openai( + monkeypatch, script: list[_FakeMessage], captured: list[dict[str, Any]] +) -> None: + _FakeAsyncOpenAI.script = script + _FakeAsyncOpenAI.captured = captured + fake_module = types.ModuleType("openai") + fake_module.AsyncOpenAI = _FakeAsyncOpenAI # type: ignore[attr-defined] + monkeypatch.setitem(sys.modules, "openai", fake_module) + + +# ---------- 宿主能力（普通函数） ---------- + +def count_notes() -> int: + """统计笔记总数。""" + return 3 + + +def test_tool_call_roundtrip_and_tool_message_feedback(monkeypatch) -> None: + script = [ + # 第一轮：模型决定调 count_notes + _FakeMessage(None, [_FakeToolCall("call_1", "count_notes", "{}")]), + # 第二轮：模型拿到工具结果后收尾 + _FakeMessage("你一共有 3 条笔记。", None), + ] + captured: list[dict[str, Any]] = [] + _install_fake_openai(monkeypatch, script, captured) + + provider = OpenAICompatProvider(api_key="test-key", base_url="http://localhost:1234") + core = AgentCore(provider) + core.register_tools([build_spec(count_notes)]) + + result = asyncio.run(core.run("统计一下笔记数量")) + + event_types = [e.type.value for e in result.events] + assert result.strategy.value == "react" + assert "tool_call" in event_types + assert "tool_result" in event_types + assert "3 条" in result.final_text + + # 第一次请求必须带 tools 清单，且形状是 OpenAI function-calling 规范 + first_request = captured[0] + assert first_request["tools"][0]["type"] == "function" + assert first_request["tools"][0]["function"]["name"] == "count_notes" + + # 第二次请求必须把工具结果以 role=tool 回灌，id 与模型下发的一致 + second_messages = captured[1]["messages"] + tool_messages = [m for m in second_messages if m["role"] == "tool"] + assert len(tool_messages) == 1 + assert tool_messages[0]["tool_call_id"] == "call_1" + assert tool_messages[0]["content"] == "3" + + +def test_plain_answer_sends_no_tools(monkeypatch) -> None: + captured: list[dict[str, Any]] = [] + _install_fake_openai(monkeypatch, [_FakeMessage("你好，我是内嵌助手。", None)], captured) + + provider = OpenAICompatProvider(api_key="test-key", base_url="http://localhost:1234") + core = AgentCore(provider) + result = asyncio.run(core.run("你好")) + + assert result.strategy.value == "direct" + assert result.final_text.startswith("你好") + # direct 策略不应下发 tools + assert "tools" not in captured[0] diff --git a/submissions/mcp-hackathon/yai-agent-core/source/tests/test_openapi_bridge.py b/submissions/mcp-hackathon/yai-agent-core/source/tests/test_openapi_bridge.py new file mode 100644 index 0000000..34fa4a4 --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/tests/test_openapi_bridge.py @@ -0,0 +1,357 @@ +"""OpenAPI 发现桥测试：spec 解析、$ref、发现命名、MockTransport 调用、鉴权、端到端。 + +离线原则：所有 HTTP 走 httpx.MockTransport；不触网、不依赖真实 Key。 +""" + +import ast +import json +import pathlib + +import pytest + +pytest.importorskip("httpx") # 没装 [dev]/[openapi] extra 的环境整体跳过 +import httpx # noqa: E402 + +from yai_core import AgentCore, ModelResponse, ToolCallRequest # noqa: E402 +from yai_core.integrations.openapi import ( # noqa: E402 + OpenApiSpecConfig, + OpenApiToolBridge, + attach_openapi_tools, + config_from_env, + load_spec, + plan_operations, + resolve_refs, +) + +FIXTURE = pathlib.Path(__file__).parent / "fixtures" / "petstore.min.json" + + +@pytest.fixture +def spec_dict() -> dict: + return json.loads(FIXTURE.read_text(encoding="utf-8")) + + +@pytest.fixture +def resolved(spec_dict): + spec, notes = resolve_refs(spec_dict) + return spec, notes + + +def _handler_factory(captured: list): + def handler(request: httpx.Request) -> httpx.Response: + captured.append(request) + path = request.url.path + if request.method == "GET" and path == "/api/v3/pets": + return httpx.Response(200, json=[{"id": 1, "name": "旺财"}]) + if request.method == "POST" and path == "/api/v3/pets": + return httpx.Response(201, json={"created": True}) + if request.method == "GET" and path.startswith("/api/v3/pets/"): + if path.endswith("/999"): + return httpx.Response(404, text="not found") + return httpx.Response(200, json={"id": 7, "name": "小黑"}) + if request.method == "DELETE": + return httpx.Response(204) + if request.method == "POST" and path.startswith("/api/v3/echo/"): + return httpx.Response(200, json=json.loads(request.content.decode())) + return httpx.Response(404, text="unmatched") + + return handler + + +def _transport(captured): + return httpx.MockTransport(_handler_factory(captured)) + + +def _bridge(spec_dict, captured): + return OpenApiToolBridge( + OpenApiSpecConfig(spec=spec_dict, alias="rest"), + transport=_transport(captured), + ) + + +# ---------- 1. $ref 展开与循环保留 ---------- + +def test_resolve_internal_refs_and_keep_cycles(resolved): + spec, notes = resolved + pet = spec["components"]["schemas"]["Pet"] + assert pet["properties"]["name"]["type"] == "string" + category = pet["properties"]["category"] # 内部 $ref 已内联 + assert category["properties"]["name"]["type"] == "string" + recursive = category["properties"]["children"]["items"] + assert recursive.get("$ref") == "#/components/schemas/Category" # 循环保留原样 + assert any("循环" in note for note in notes) + + +# ---------- 2. 发现与命名 ---------- + +def test_operation_naming(resolved): + spec, _ = resolved + plans, _ = plan_operations(spec, OpenApiSpecConfig(spec=spec)) + names = [p.name for p in plans] + assert names == ["list_pets", "create_pet", "get_pets_pet_id", "delete_pet", "echo_body"] + methods = {p.name: p.method for p in plans} + assert methods["get_pets_pet_id"] == "GET" + + +# ---------- 3. 入参合并 ---------- + +def test_parameters_and_body_merge(resolved): + spec, _ = resolved + plans, _ = plan_operations(spec, OpenApiSpecConfig(spec=spec)) + by_name = {p.name: p for p in plans} + + list_plan = by_name["list_pets"] + assert set(list_plan.query_params) == {"limit", "tags", "verbose"} + assert "X-Trace" not in list_plan.input_schema["properties"] # header 参数不暴露 + assert "limit" not in list_plan.input_schema.get("required", []) + + create_plan = by_name["create_pet"] + assert set(create_plan.body_fields) == {"id", "name", "category"} + assert create_plan.body_wrapped is False + assert set(create_plan.input_schema["required"]) == {"id", "name"} + # $ref 展开后的嵌套 schema 仍在 + assert create_plan.input_schema["properties"]["category"]["type"] == "object" + + get_one = by_name["get_pets_pet_id"] + assert get_one.path_params == ("petId",) + assert "petId" in get_one.input_schema["required"] # path 参数强制必填 + + echo = by_name["echo_body"] + assert echo.body_wrapped is True and echo.body_fields == ("body",) + assert "body" in echo.input_schema["required"] + + +# ---------- 4. read_only / 截断 / 前缀过滤 ---------- + +def test_read_only_filters_writes(resolved): + spec, _ = resolved + plans, _ = plan_operations(spec, OpenApiSpecConfig(spec=spec, read_only=True)) + assert all(p.method in {"GET", "HEAD"} for p in plans) + assert "create_pet" not in [p.name for p in plans] + + +def test_max_operations_truncation(resolved): + spec, _ = resolved + plans, notes = plan_operations(spec, OpenApiSpecConfig(spec=spec, max_operations=2)) + assert len(plans) == 2 + assert any("截断" in note for note in notes) + + +def test_include_exclude_paths(resolved): + spec, _ = resolved + inc, _ = plan_operations(spec, OpenApiSpecConfig(spec=spec, include_paths=("/pets",))) + assert all(p.path_template.startswith("/pets") for p in inc) + exc, _ = plan_operations(spec, OpenApiSpecConfig(spec=spec, exclude_paths=("/pets",))) + assert all(not p.path_template.startswith("/pets") for p in exc) + + +# ---------- 5. MockTransport 端到端调用 ---------- + +def _run(coro): + import asyncio + + return asyncio.run(coro) + + +def test_get_query_bool_list_and_bearer(spec_dict, monkeypatch): + monkeypatch.setenv("OPENAPI_AUTH_TOKEN", "test-token") + captured: list = [] + bridge = _bridge(spec_dict, captured) + specs = _run(bridge.connect()) + by_name = {s.name: s for s in specs} + assert all(s.source == "openapi" for s in specs) + + result = _run(by_name["list_pets"].handler(limit=2, tags=["cat", "dog"], verbose=True)) + req = captured[-1] + assert req.method == "GET" + assert req.url.path == "/api/v3/pets" + params = req.url.params + assert params.get("limit") == "2" + assert params.get_list("tags") == ["cat", "dog"] + assert params.get("verbose") == "true" + assert req.headers["Authorization"] == "Bearer test-token" + assert result == [{"id": 1, "name": "旺财"}] + _run(bridge.aclose()) + + +def test_post_flattened_object_body(spec_dict, monkeypatch): + monkeypatch.setenv("OPENAPI_AUTH_TOKEN", "test-token") + captured: list = [] + bridge = _bridge(spec_dict, captured) + specs = _run(bridge.connect()) + _run({s.name: s for s in specs}["create_pet"].handler( + id=42, name="布偶", category={"name": "猫"} + )) + req = captured[-1] + assert req.method == "POST" and req.url.path == "/api/v3/pets" + assert json.loads(req.content) == {"id": 42, "name": "布偶", "category": {"name": "猫"}} + assert req.headers["Content-Type"] == "application/json" + _run(bridge.aclose()) + + +def test_path_fill_204_404_and_wrapped_body(spec_dict, monkeypatch): + monkeypatch.setenv("OPENAPI_AUTH_TOKEN", "test-token") + captured: list = [] + bridge = _bridge(spec_dict, captured) + specs = _run(bridge.connect()) + by_name = {s.name: s for s in specs} + + _run(by_name["get_pets_pet_id"].handler(petId=7)) + assert captured[-1].url.path == "/api/v3/pets/7" + + assert _run(by_name["delete_pet"].handler(petId=7)) == "" # 204 → 空串 + + with pytest.raises(RuntimeError, match="HTTP 404"): + _run(by_name["get_pets_pet_id"].handler(petId=999)) + + _run(by_name["echo_body"].handler(kind="x", body=["a", "b"])) # 非 object body 包裹 + assert json.loads(captured[-1].content) == ["a", "b"] + _run(bridge.aclose()) + + +def test_apikey_header_auth(spec_dict, monkeypatch): + monkeypatch.setenv("OPENAPI_AUTH_TOKEN", "test-token") + key_spec = json.loads(json.dumps(spec_dict)) + key_spec["security"] = [{"keyHeader": []}] + captured: list = [] + bridge = OpenApiToolBridge( + OpenApiSpecConfig(spec=key_spec), transport=_transport(captured) + ) + specs = _run(bridge.connect()) + _run({s.name: s for s in specs}["list_pets"].handler(limit=1)) + assert captured[-1].headers["X-Api-Key"] == "test-token" + _run(bridge.aclose()) + + +def test_missing_token_raises_at_call_time(spec_dict, monkeypatch): + monkeypatch.delenv("OPENAPI_AUTH_TOKEN", raising=False) + captured: list = [] + bridge = _bridge(spec_dict, captured) + specs = _run(bridge.connect()) # 注册期不报错 + with pytest.raises(RuntimeError, match="OPENAPI_AUTH_TOKEN"): + _run({s.name: s for s in specs}["list_pets"].handler()) + _run(bridge.aclose()) + + +def test_missing_token_message_names_env_var(spec_dict, monkeypatch): + """回归（40-review P3-1）：config_from_env 路径下缺令牌，报错要点名环境变量而非 None。""" + monkeypatch.delenv("OPENAPI_AUTH_TOKEN", raising=False) + env_cfg = config_from_env(env={"OPENAPI_SPEC_PATH": "spec.json"}) + cfg = OpenApiSpecConfig(spec=spec_dict, auth_token_env=env_cfg.auth_token_env) + bridge = OpenApiToolBridge(cfg, transport=_transport([])) + specs = _run(bridge.connect()) + with pytest.raises(RuntimeError, match="OPENAPI_AUTH_TOKEN"): + _run({s.name: s for s in specs}["list_pets"].handler()) + _run(bridge.aclose()) + + +def test_result_text_truncation(spec_dict, monkeypatch): + monkeypatch.setenv("OPENAPI_AUTH_TOKEN", "t") + + def handler(request: httpx.Request) -> httpx.Response: + return httpx.Response(200, text="x" * 20000, headers={"content-type": "text/plain"}) + + bridge = OpenApiToolBridge( + OpenApiSpecConfig(spec=spec_dict, max_result_chars=100), + transport=httpx.MockTransport(handler), + ) + specs = _run(bridge.connect()) + out = _run({s.name: s for s in specs}["list_pets"].handler()) + assert out.endswith("…[truncated]") and len(out) == len("…[truncated]") + 100 + _run(bridge.aclose()) + + +# ---------- 6. config_from_env / load_spec 校验 / YAML ---------- + +def test_config_from_env_states(): + assert config_from_env(env={}) is None + cfg = config_from_env( + env={"OPENAPI_SPEC_URL": "http://x/openapi.json", "OPENAPI_READ_ONLY": "yes"} + ) + assert cfg.url == "http://x/openapi.json" and cfg.read_only is True + cfg_path = config_from_env(env={"OPENAPI_SPEC_PATH": "spec.yaml"}) + assert str(cfg_path.path) == "spec.yaml" + + +def test_reject_swagger2_and_non_openapi3(): + with pytest.raises(ValueError, match="Swagger 2.0"): + load_spec(OpenApiSpecConfig(spec={"swagger": "2.0", "paths": {}})) + with pytest.raises(ValueError, match="3.x"): + load_spec(OpenApiSpecConfig(spec={"openapi": "2.5"})) + + +def test_yaml_spec_loads(tmp_path): + pytest.importorskip("yaml") + p = tmp_path / "spec.yaml" + p.write_text( + "openapi: 3.0.3\ninfo:\n title: T\n version: '1.0'\n" + "paths:\n /ping:\n get:\n operationId: ping\n" + " summary: ping\n responses:\n '200':\n description: ok\n", + encoding="utf-8", + ) + spec = load_spec(OpenApiSpecConfig(path=p)) + assert "/ping" in spec["paths"] + + +def test_missing_httpx_error_message(monkeypatch): + """缺 httpx 时 connect() 的报错必须提示 extra 名（模拟 builtins 导入失败代价高， + 这里做字符串契约校验：错误文案在源码中固定）。""" + client_path = pathlib.Path(__file__).parents[1] / "src" / "yai_core" / ( + "integrations/openapi/client.py" + ) + text = client_path.read_text(encoding="utf-8") + assert "uv sync --extra openapi" in text + + +# ---------- 7. 注册进 AgentCore 的端到端 react ---------- + +class _ScriptedToolModel: + def __init__(self): + self.calls = 0 + + async def achat(self, messages, tools=None, *, tier="standard"): + self.calls += 1 + if self.calls == 1: + return ModelResponse( + content="", + tool_calls=[ToolCallRequest(id="c1", name="list_pets", arguments={"limit": 1})], + ) + return ModelResponse(content="查到了宠物") + + +def test_agent_core_end_to_end_with_openapi_tool(spec_dict, monkeypatch): + monkeypatch.setenv("OPENAPI_AUTH_TOKEN", "test-token") + captured: list = [] + core = AgentCore(_ScriptedToolModel()) + bridge = _run( + attach_openapi_tools(core.registry, OpenApiSpecConfig(spec=spec_dict), + transport=_transport(captured)) + ) + assert "list_pets" in core.registry.describe() + assert core.registry._tools["list_pets"].source == "openapi" + + import asyncio + + result = asyncio.run(core.run("列一下宠物")) + assert result.final_text == "查到了宠物" + event_types = [e.type.value for e in result.events] + assert "tool_call" in event_types and "tool_result" in event_types + assert captured[-1].url.path == "/api/v3/pets" + _run(bridge.aclose()) + + +# ---------- 8. 红线：openapi 模块顶层不得 import httpx / yaml ---------- + +@pytest.mark.parametrize( + "relative", + ["integrations/openapi/spec.py", "integrations/openapi/discovery.py", + "integrations/openapi/client.py"], +) +def test_no_toplevel_third_party_imports(relative): + path = pathlib.Path(__file__).parents[1] / "src" / "yai_core" / relative + tree = ast.parse(path.read_text(encoding="utf-8")) + for node in tree.body: # 只检查模块顶层语句 + if isinstance(node, ast.Import): + assert all(not a.name.startswith(("httpx", "yaml")) for a in node.names) + if isinstance(node, ast.ImportFrom): + assert node.module is None or not node.module.startswith(("httpx", "yaml")) diff --git a/submissions/mcp-hackathon/yai-agent-core/source/tests/test_rate_limit.py b/submissions/mcp-hackathon/yai-agent-core/source/tests/test_rate_limit.py new file mode 100644 index 0000000..000cbb0 --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/tests/test_rate_limit.py @@ -0,0 +1,214 @@ +"""限流 Battery 测试：滑动窗口、429 + Retry-After、GET 放行、假时钟全离线。 + +统一范式：TestClient + 计数版 ScriptedModel + 假时钟（now 列表），禁止 time.sleep。 +""" + +from __future__ import annotations + +import warnings + +from fastapi.testclient import TestClient + +from yai_core import AgentCore, ModelResponse, build_spec +from yai_core.batteries.fastapi_server import RateLimitConfig, create_app +from yai_core.batteries.fastapi_server.ratelimit import SlidingWindowLimiter, client_ip + + +class CountingModel: + """记录 achat 调用次数：断言被限请求一分模型钱都不花。""" + + def __init__(self) -> None: + self.calls = 0 + + async def achat(self, messages, tools=None, *, tier="standard"): + self.calls += 1 + return ModelResponse(content="好的") + + +def list_notes() -> list: + """列出全部笔记。""" + return [{"id": 1, "title": "Core 骨架"}] + + +class FakeClock: + """可推进的假时钟（秒）；测试推进时间而不是 sleep 等真实窗口。""" + + def __init__(self) -> None: + self.now = [0.0] + + def __call__(self) -> float: + return self.now[0] + + def advance(self, seconds: float) -> None: + self.now[0] += seconds + + +def make_client(model: CountingModel, config: RateLimitConfig | None) -> TestClient: + core = AgentCore(model) + core.register_tools([build_spec(list_notes)]) + return TestClient(create_app(core, rate_limit=config)) + + +def limited_config(clock: FakeClock, per_minute: int = 2) -> RateLimitConfig: + """小配额便于测试：per_minute 次 200，之后 429。""" + return RateLimitConfig( + enabled=True, per_minute=per_minute, window_seconds=60, time_func=clock + ) + + +# ---------- 1/2. 超限 429 + Retry-After；推进假时钟后恢复 ---------- + +def test_over_limit_returns_429_then_recovers(monkeypatch) -> None: + monkeypatch.setenv("YAI_GIT_COMMIT", "0" * 40) + clock = FakeClock() + model = CountingModel() + client = make_client(model, limited_config(clock, per_minute=2)) + + assert client.post("/v1/agent/run", json={"task": "1"}).status_code == 200 + assert client.post("/v1/agent/run", json={"task": "2"}).status_code == 200 + + limited = client.post("/v1/agent/run", json={"task": "3"}) + assert limited.status_code == 429 + body = limited.json() + assert body["error"] == "rate_limited" + assert isinstance(body["retry_after"], int) and body["retry_after"] >= 1 + assert limited.headers["Retry-After"] == str(body["retry_after"]) # 同一计算源 + + clock.advance(seconds=61) # 越过窗口：滑动窗口语义下恢复 + assert client.post("/v1/agent/run", json={"task": "4"}).status_code == 200 + + +# ---------- 3. 429 状态下三个 GET 端点仍 200（评审硬门槛） ---------- + +def test_get_endpoints_never_limited(monkeypatch) -> None: + monkeypatch.setenv("YAI_GIT_COMMIT", "0" * 40) + monkeypatch.setenv("YAI_PROJECT_SLUG", "yai-test") + clock = FakeClock() + client = make_client(CountingModel(), limited_config(clock, per_minute=1)) + + assert client.post("/v1/agent/run", json={"task": "1"}).status_code == 200 + assert client.post("/v1/agent/run", json={"task": "2"}).status_code == 429 + + assert client.get("/health").status_code == 200 + assert client.get("/.well-known/xagent-verification.json").status_code == 200 + assert client.get("/v1/tools").status_code == 200 + + +# ---------- 4. enabled=False 全放行 ---------- + +def test_disabled_config_allows_everything(monkeypatch) -> None: + monkeypatch.setenv("YAI_GIT_COMMIT", "0" * 40) + clock = FakeClock() + config = RateLimitConfig( + enabled=False, per_minute=1, window_seconds=60, time_func=clock + ) + client = make_client(CountingModel(), config) + for _i in range(5): + assert client.post("/v1/agent/run", json={"task": "x"}).status_code == 200 + + +# ---------- 5. 每 IP 隔离 ---------- + +def test_per_ip_isolation(monkeypatch) -> None: + monkeypatch.setenv("YAI_GIT_COMMIT", "0" * 40) + clock = FakeClock() + client = make_client(CountingModel(), limited_config(clock, per_minute=1)) + + ok_a = client.post( + "/v1/agent/run", json={"task": "a"}, headers={"X-Forwarded-For": "1.1.1.1"} + ) + ok_b = client.post( + "/v1/agent/run", json={"task": "b"}, headers={"X-Forwarded-For": "2.2.2.2"} + ) + limited_a = client.post( + "/v1/agent/run", json={"task": "a2"}, headers={"X-Forwarded-For": "1.1.1.1"} + ) + assert ok_a.status_code == 200 + assert ok_b.status_code == 200 # 另一个 IP 有独立配额 + assert limited_a.status_code == 429 # 同一 IP 超限 + + +# ---------- 6. client_ip() 六种输入 ---------- + +def test_client_ip_inputs() -> None: + assert client_ip(None, "10.0.0.1") == "10.0.0.1" # 无 XFF：回退对端 + assert client_ip("1.2.3.4", "10.0.0.1") == "1.2.3.4" # 单级 + assert client_ip("1.2.3.4, 5.6.7.8", "10.0.0.1") == "1.2.3.4" # 多级取最左 + assert client_ip(" , 5.6.7.8", "10.0.0.1") == "5.6.7.8" # 含空段：跳过取非空 + assert client_ip(" , ", "10.0.0.1") == "10.0.0.1" # 全空：回退对端 + assert client_ip(None, None) == "unknown" # 双缺省 + + +# ---------- 7. 被限请求不触达模型 ---------- + +def test_limited_request_never_reaches_model(monkeypatch) -> None: + monkeypatch.setenv("YAI_GIT_COMMIT", "0" * 40) + clock = FakeClock() + model = CountingModel() + client = make_client(model, limited_config(clock, per_minute=2)) + + statuses = [ + client.post("/v1/agent/run", json={"task": str(i)}).status_code + for i in range(4) + ] + assert statuses == [200, 200, 429, 429] + assert model.calls == 2 # 4 次请求只调用 2 次模型 + + +# ---------- 8. env 三态与非法值 ---------- + +def test_from_env_states(monkeypatch) -> None: + monkeypatch.delenv("YAI_RATE_LIMIT_ENABLED", raising=False) + monkeypatch.delenv("YAI_RATE_LIMIT_PER_MINUTE", raising=False) + monkeypatch.delenv("YAI_RATE_LIMIT_WINDOW_SECONDS", raising=False) + config = RateLimitConfig.from_env() + assert (config.enabled, config.per_minute, config.window_seconds) == (True, 30, 60) + + config = RateLimitConfig.from_env( + env={ + "YAI_RATE_LIMIT_ENABLED": "0", + "YAI_RATE_LIMIT_PER_MINUTE": "10", + "YAI_RATE_LIMIT_WINDOW_SECONDS": "30", + } + ) + assert (config.enabled, config.per_minute, config.window_seconds) == (False, 10, 30) + + with warnings.catch_warnings(record=True) as caught: + warnings.simplefilter("always") + config = RateLimitConfig.from_env( + env={"YAI_RATE_LIMIT_PER_MINUTE": "-3", "YAI_RATE_LIMIT_WINDOW_SECONDS": "x"} + ) + assert (config.enabled, config.per_minute, config.window_seconds) == (True, 30, 60) + assert len(caught) == 2 + + +# ---------- 9. 窗口边界：正好等于窗口的请求视为过期 ---------- + +def test_window_boundary_inclusive_expiry(monkeypatch) -> None: + monkeypatch.setenv("YAI_GIT_COMMIT", "0" * 40) + clock = FakeClock() + limiter = SlidingWindowLimiter(limited_config(clock, per_minute=1)) + + allowed, _ = limiter.check("1.1.1.1") + assert allowed is True + clock.advance(seconds=60) # 恰好等于窗口：<= 清除语义下视为过期 + allowed, retry_after = limiter.check("1.1.1.1") + assert allowed is True + + # 超限瞬间 retry_after 至少为 1 + clock.now[0] = 60.5 + limiter.check("2.2.2.2") + allowed, retry_after = limiter.check("2.2.2.2") + assert allowed is False and retry_after >= 1 + + +# ---------- 10. 默认开启不破坏既有零配置调用 ---------- + +def test_default_create_app_still_works(monkeypatch) -> None: + monkeypatch.setenv("YAI_GIT_COMMIT", "0" * 40) + monkeypatch.delenv("YAI_RATE_LIMIT_ENABLED", raising=False) + core = AgentCore(CountingModel()) + core.register_tools([build_spec(list_notes)]) + client = TestClient(create_app(core)) # 与 test_battery_api.py 同款零配置调用 + assert client.get("/health").status_code == 200 + assert client.post("/v1/agent/run", json={"task": "你好"}).status_code == 200 diff --git a/submissions/mcp-hackathon/yai-agent-core/source/tests/test_router.py b/submissions/mcp-hackathon/yai-agent-core/source/tests/test_router.py new file mode 100644 index 0000000..c3ff4ea --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/tests/test_router.py @@ -0,0 +1,168 @@ +import asyncio + +import pytest + +from yai_core import AdaptiveRouter, ModelResponse, Strategy, ToolRegistry, build_spec + + +def _registry_with_tools() -> ToolRegistry: + reg = ToolRegistry() + + def search_notes(keyword: str) -> list: + """搜索笔记。""" + return [] + + reg.register(build_spec(search_notes)) + return reg + + +class ScriptedClassifier: + """测试用分类模型：返回预设内容，可记录调用并可模拟异常/超时。""" + + def __init__(self, content: str = "", *, raises: Exception | None = None, + sleep: float = 0.0) -> None: + self._content = content + self._raises = raises + self._sleep = sleep + self.calls = 0 + self.tiers: list[str] = [] + + async def achat(self, messages, tools=None, *, tier="standard"): + self.calls += 1 + self.tiers.append(tier) + if self._raises is not None: + raise self._raises + if self._sleep: + await asyncio.sleep(self._sleep) + return ModelResponse(content=self._content) + + +def test_no_tools_goes_direct() -> None: + router = AdaptiveRouter() + assert router.classify("你好", ToolRegistry()) == Strategy.DIRECT + + +def test_action_goes_react() -> None: + router = AdaptiveRouter() + assert router.classify("搜索笔记里关于周报的内容", _registry_with_tools()) == Strategy.REACT + + +def test_multistep_goes_plan() -> None: + router = AdaptiveRouter() + task = "先搜索订单，然后统计数量并整理成报告" + assert router.classify(task, _registry_with_tools()) == Strategy.PLAN + + +def test_vague_goes_clarify() -> None: + router = AdaptiveRouter() + assert router.classify("随便", _registry_with_tools()) == Strategy.CLARIFY + + +def test_explicit_mcp_intent_goes_react() -> None: + # 显式要求用（MCP）工具提问，即使没有"查/搜"等动词也必须进工具循环， + # 否则 direct 路径不传 tools，模型只能把工具调用写成文本（v0.2 实测回归）。 + router = AdaptiveRouter() + task = "用 MCP 工具问一下 GitHub 仓库 python-sdk：Client 怎么初始化？" + assert router.classify(task, _registry_with_tools()) == Strategy.REACT + + +def test_explicit_mcp_intent_case_insensitive() -> None: + router = AdaptiveRouter() + assert router.classify("调用 mcp 工具查询天气", _registry_with_tools()) == Strategy.REACT + + +def test_mcp_multistep_goes_plan() -> None: + router = AdaptiveRouter() + task = "先用 MCP 工具问一下这个仓库的结构，然后整理成一句话总结" + assert router.classify(task, _registry_with_tools()) == Strategy.PLAN + + +# ---------- aclassify：LLM 分类 + 规则兜底 ---------- + +def test_aclassify_without_model_uses_rules() -> None: + router = AdaptiveRouter() + decision = asyncio.run(router.aclassify("搜索笔记", _registry_with_tools())) + assert decision.source == "rules" + assert decision.strategy == Strategy.REACT + + +def test_aclassify_llm_valid_decision() -> None: + model = ScriptedClassifier( + '{"strategy": "react", "tier": "standard", "reason": "需要调用搜索工具"}' + ) + router = AdaptiveRouter(model=model) + decision = asyncio.run(router.aclassify("帮我看看笔记里有啥", _registry_with_tools())) + assert decision.source == "llm" + assert decision.strategy == Strategy.REACT + assert decision.tier == "standard" + assert "搜索工具" in decision.reason + assert model.calls == 1 # 只做一次轻量分类调用 + + +def test_aclassify_llm_tolerates_fences_and_prose() -> None: + model = ScriptedClassifier('好的，结果如下：\n```json\n{"strategy": "plan", ' + '"tier": "strong", "reason": "多步任务"}\n```') + router = AdaptiveRouter(model=model) + decision = asyncio.run(router.aclassify("先查再汇总", _registry_with_tools())) + assert decision.strategy == Strategy.PLAN and decision.tier == "strong" + + +def test_aclassify_llm_garbage_falls_back_to_rules() -> None: + model = ScriptedClassifier("我不太确定你在说什么") + router = AdaptiveRouter(model=model) + decision = asyncio.run(router.aclassify("搜索笔记里的周报", _registry_with_tools())) + assert decision.source == "rules" # 解析失败 -> 规则兜底 + assert decision.strategy == Strategy.REACT + assert "回退" in decision.reason + + +def test_aclassify_llm_exception_falls_back_to_rules() -> None: + model = ScriptedClassifier(raises=RuntimeError("network down")) + router = AdaptiveRouter(model=model) + decision = asyncio.run(router.aclassify("搜索笔记", _registry_with_tools())) + assert decision.source == "rules" and decision.strategy == Strategy.REACT + + +def test_aclassify_llm_timeout_falls_back_to_rules() -> None: + model = ScriptedClassifier('{"strategy": "react"}', sleep=0.3) + router = AdaptiveRouter(model=model, classify_timeout=0.05) + decision = asyncio.run(router.aclassify("搜索笔记", _registry_with_tools())) + assert decision.source == "rules" and decision.strategy == Strategy.REACT + + +def test_aclassify_llm_invalid_strategy_falls_back() -> None: + model = ScriptedClassifier('{"strategy": "fly-to-moon", "reason": "瞎编"}') + router = AdaptiveRouter(model=model) + decision = asyncio.run(router.aclassify("搜索笔记", _registry_with_tools())) + assert decision.source == "rules" + + +def test_aclassify_no_tools_skips_model_call() -> None: + # 能力边界优先：宿主没工具时，连分类模型都不该调用。 + model = ScriptedClassifier('{"strategy": "react"}') + router = AdaptiveRouter(model=model) + decision = asyncio.run(router.aclassify("搜索一下", ToolRegistry())) + assert decision.strategy == Strategy.DIRECT and model.calls == 0 + + +def test_aclassify_empty_task_skips_model_call() -> None: + model = ScriptedClassifier('{"strategy": "clarify"}') + router = AdaptiveRouter(model=model) + decision = asyncio.run(router.aclassify(" ", _registry_with_tools())) + assert decision.strategy == Strategy.CLARIFY and model.calls == 0 + + +def test_rules_plan_defaults_to_strong_tier() -> None: + router = AdaptiveRouter() + decision = asyncio.run( + router.aclassify("先搜索订单，然后统计数量并整理成报告", _registry_with_tools()) + ) + assert decision.strategy == Strategy.PLAN and decision.tier == "strong" + + +@pytest.mark.parametrize("bad_tier", ["ultra", "", 3]) +def test_aclassify_bad_tier_normalizes(bad_tier) -> None: + model = ScriptedClassifier(f'{{"strategy": "react", "tier": "{bad_tier}"}}') + router = AdaptiveRouter(model=model) + decision = asyncio.run(router.aclassify("查笔记", _registry_with_tools())) + assert decision.tier == "standard" diff --git a/submissions/mcp-hackathon/yai-agent-core/source/tests/test_sqlite_memory.py b/submissions/mcp-hackathon/yai-agent-core/source/tests/test_sqlite_memory.py new file mode 100644 index 0000000..9246fe7 --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/source/tests/test_sqlite_memory.py @@ -0,0 +1,240 @@ +"""SqliteStore 测试：契约对等（与 InMemoryStore 跑同一组断言）+ 持久化专项。 + +全程离线：内存库与 tmp_path 文件库，零网络、零 Key。 +""" + +import asyncio +import sqlite3 + +import pytest + +from yai_core import AgentCore, ChatMessage, ModelResponse +from yai_core.memory import InMemoryStore, SqliteStore + + +def run(coro): + """同步测试里跑一个协程的小工具（仓库既有风格，不引入 pytest-asyncio）。""" + return asyncio.run(coro) + + +@pytest.fixture(params=["memory", "sqlite"]) +def store(request, tmp_path): + """同一组对等用例分别跑 InMemoryStore 与 SqliteStore。""" + if request.param == "memory": + yield InMemoryStore() + else: + s = SqliteStore(tmp_path / "t.db") + yield s + s.close() + + +# ---------- A 组：契约对等（两种实现必须行为一致） ---------- + +def test_empty_history(store) -> None: + assert store.history() == [] + + +def test_append_history_order_and_fields(store) -> None: + run(store.append_history(ChatMessage(role="user", content="第一条"))) + run(store.append_history(ChatMessage(role="assistant", content="第二条"))) + hist = store.history() + assert [m.role for m in hist] == ["user", "assistant"] + assert [m.content for m in hist] == ["第一条", "第二条"] + + +def test_kv_put_get_overwrite_and_missing(store) -> None: + assert run(store.get("k")) is None + run(store.put("k", "v1")) + assert run(store.get("k")) == "v1" + run(store.put("k", "v2")) + assert run(store.get("k")) == "v2" + + +def test_clear_empties_history_and_kv(store) -> None: + run(store.append_history(ChatMessage(role="user", content="x"))) + run(store.put("k", "v")) + run(store.clear()) + assert store.history() == [] + assert run(store.get("k")) is None + + +def test_tool_calls_roundtrip_including_empty_list(store) -> None: + with_calls = ChatMessage( + role="assistant", + content="", + tool_calls=[{"id": "1", "name": "t", "arguments": {"a": 1}}], + ) + run(store.append_history(with_calls)) + assert store.history()[0].tool_calls == with_calls.tool_calls + + # 空列表必须原样往返（存 "[]"），不能被折叠成 None。 + run(store.append_history(ChatMessage(role="assistant", content="", tool_calls=[]))) + assert store.history()[1].tool_calls == [] + + +def test_optional_fields_roundtrip(store) -> None: + run( + store.append_history( + ChatMessage(role="tool", content="结果", tool_call_id="c1", name="t") + ) + ) + m = store.history()[0] + assert m.tool_call_id == "c1" + assert m.name == "t" + + run(store.append_history(ChatMessage(role="user", content=""))) + missing = store.history()[1] + assert missing.tool_call_id is None + assert missing.name is None + + +# ---------- B 组：SqliteStore 专项 ---------- + +def test_persistence_across_instances(tmp_path) -> None: + db = tmp_path / "p.db" + first = SqliteStore(db) + run(first.append_history(ChatMessage(role="user", content="持久的我"))) + run(first.put("k", "v")) + first.close() + + second = SqliteStore(db) # 重新打开同一文件，数据必须还在 + try: + assert second.history()[0].content == "持久的我" + assert run(second.get("k")) == "v" + finally: + second.close() + + +def test_scope_isolation_and_scoped_clear(tmp_path) -> None: + db = tmp_path / "s.db" + a = SqliteStore(db, scope="a") + b = SqliteStore(db, scope="b") + try: + run(a.append_history(ChatMessage(role="user", content="A 的消息"))) + run(b.put("kb", "vb")) + + assert len(a.history()) == 1 + assert b.history() == [] + assert run(a.get("kb")) is None + assert run(b.get("kb")) == "vb" + + run(a.clear()) # 只清 scope=a + assert a.history() == [] + assert b.history() == [] + assert run(b.get("kb")) == "vb" # b 的 KV 不受影响 + finally: + a.close() + b.close() + + +def test_memory_databases_are_independent() -> None: + a = SqliteStore(":memory:") + b = SqliteStore(":memory:") + try: + run(a.append_history(ChatMessage(role="user", content="只在 A"))) + assert len(a.history()) == 1 + assert b.history() == [] + finally: + a.close() + b.close() + + +def test_reinit_same_file_is_idempotent(tmp_path) -> None: + db = tmp_path / "r.db" + first = SqliteStore(db) + run(first.put("k", "v")) + first.close() + + second = SqliteStore(db) + third = SqliteStore(db) # 同文件重复构造：不报错、不丢数据 + try: + assert run(second.get("k")) == "v" + assert run(third.get("k")) == "v" + finally: + second.close() + third.close() + + +def test_from_env_states(tmp_path) -> None: + assert SqliteStore.from_env(env={}) is None + assert SqliteStore.from_env(env={"YAI_DB_PATH": " "}) is None + + store = SqliteStore.from_env(env={"YAI_DB_PATH": str(tmp_path / "env.db")}) + assert store is not None + try: + run(store.put("k", "v")) + assert run(store.get("k")) == "v" + finally: + store.close() + + +def test_parent_dir_created(tmp_path) -> None: + nested = tmp_path / "nested" / "deep" / "m.db" + store = SqliteStore(nested) + try: + assert nested.parent.exists() + finally: + store.close() + + +def test_schema_version_baseline_and_future_guard(tmp_path) -> None: + db = tmp_path / "v.db" + store = SqliteStore(db) + store.close() + + conn = sqlite3.connect(db) + assert conn.execute("PRAGMA user_version").fetchone()[0] == 1 + conn.execute("PRAGMA user_version = 2") # 模拟"未来版本"数据库 + conn.commit() + conn.close() + + with pytest.raises(RuntimeError, match="schema 版本"): + SqliteStore(db) + + +def test_operations_after_close_raise(tmp_path) -> None: + store = SqliteStore(tmp_path / "c.db") + store.close() + with pytest.raises(RuntimeError, match="已关闭"): + store.history() + + +# ---------- C 组：Loop 集成（证明消费点零改动） ---------- + +class _OneShotModel: + def __init__(self, content: str) -> None: + self.content = content + + async def achat(self, messages, tools=None, *, tier="standard"): + return ModelResponse(content=self.content) + + +class _CapturingModel: + """记录第二轮真正发给模型的消息（dict 形态），用于断言历史回放。""" + + def __init__(self) -> None: + self.seen: list[dict] = [] + + async def achat(self, messages, tools=None, *, tier="standard"): + self.seen.extend(messages) + return ModelResponse(content="第二轮答复") + + +def test_loop_replays_persisted_history(tmp_path) -> None: + store = SqliteStore(tmp_path / "loop.db") + + first = AgentCore(_OneShotModel("第一轮答复"), memory=store) + r1 = asyncio.run(first.run("你好")) + assert r1.final_text == "第一轮答复" + + second_model = _CapturingModel() + second = AgentCore(second_model, memory=store) # 复用同一个 store + r2 = asyncio.run(second.run("在吗")) + + contents = [m["content"] for m in second_model.seen] + # 第二轮上下文里必须能看到上一轮的 user 与 assistant（持久记忆的端到端证据） + assert "你好" in 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}, +] + +[[package]] +name = "yai-agent-core" +version = "0.1.0" +source = { editable = "." } + +[package.optional-dependencies] +dev = [ + { name = "httpx" }, + { name = "pytest" }, + { name = "ruff" }, +] +docs = [ + { name = "python-docx" }, +] +llm = [ + { name = "openai" }, +] +mcp = [ + { name = "mcp" }, +] +openapi = [ + { name = "httpx" }, + { name = "pyyaml" }, +] +server = [ + { name = "fastapi" }, + { name = "pydantic" }, + { name = "uvicorn", extra = ["standard"] }, +] + +[package.metadata] +requires-dist = [ + { name = "fastapi", marker = "extra == 'server'", specifier = ">=0.115" }, + { name = "httpx", marker = "extra == 'dev'", specifier = ">=0.27" }, + { name = "httpx", marker = "extra == 'openapi'", specifier = ">=0.27" }, + { name = "mcp", marker = "extra == 'mcp'", specifier = ">=2.0,<3" }, + { name = "openai", marker = "extra == 'llm'", specifier = ">=1.40" }, + { name = "pydantic", marker = "extra == 'server'", specifier = ">=2.7" }, + { name = "pytest", marker = "extra == 'dev'", specifier = ">=8.0" }, + { name = "python-docx", marker = "extra == 'docs'", specifier = ">=1.1" }, + { name = "pyyaml", marker = "extra == 'openapi'", specifier = ">=6.0" }, + { name = "ruff", marker = "extra == 'dev'", specifier = ">=0.6" }, + { name = "uvicorn", extras = ["standard"], marker = "extra == 'server'", specifier = ">=0.30" }, +] +provides-extras = ["llm", "server", "mcp", "openapi", "dev", "docs"] diff --git a/submissions/mcp-hackathon/yai-agent-core/submission.json b/submissions/mcp-hackathon/yai-agent-core/submission.json new file mode 100644 index 0000000..9c4ab33 --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/submission.json @@ -0,0 +1,10 @@ +{ + "schemaVersion": 1, + "name": "YAI Agent Core", + "slug": "yai-agent-core", + "sourceRepository": "https://github.com/Gi-Tuu/yai-agent-core", + "reviewCommit": "81729f9d39d1f2f0db279265ab6cc5d387a3921f", + "apiBaseUrl": "https://yai-agent-core.onrender.com", + "healthCheckUrl": "https://yai-agent-core.onrender.com/health", + "deploymentProofUrl": "https://yai-agent-core.onrender.com/.well-known/xagent-verification.json" +} diff --git a/submissions/mcp-hackathon/yai-agent-core/verification/README.md b/submissions/mcp-hackathon/yai-agent-core/verification/README.md new file mode 100644 index 0000000..bce6785 --- /dev/null +++ b/submissions/mcp-hackathon/yai-agent-core/verification/README.md @@ -0,0 +1,104 @@ +# 在线验证手册（verification） + +- **API 同源基址**：`https://yai-agent-core.onrender.com` +- **评审基线 commit**：以 `../submission.json` 的 `reviewCommit`（40 位 SHA）为准。 +- **冷启动提示**：免费实例 15 分钟无流量会休眠，首次请求约 30–90 秒冷启动；建议先 curl 一次 health 唤醒，再做后续验证。 +- 以下 curl 命令在任意装有 curl 的环境可直接复现（Windows PowerShell / macOS / Linux 均可）。 + +## 1. health 健康检查（硬门槛） + +```bash +curl -sS https://yai-agent-core.onrender.com/health +``` + +期望返回（commit 必须与 reviewCommit 完全一致）： + +```json +{"status": "ok", "commit": "<40位 reviewCommit>"} +``` + +## 2. 部署证明端点（硬门槛，与 health 同源同 commit） + +```bash +curl -sS https://yai-agent-core.onrender.com/.well-known/xagent-verification.json +``` + +期望返回： + +```json +{"schemaVersion": 1, "slug": "yai-agent-core", "commit": "<40位 reviewCommit>"} +``` + +## 3. 工具清单（能力自发现 + 来源标注） + +```bash +curl -sS https://yai-agent-core.onrender.com/v1/tools +``` + +期望返回宿主演示应用自动发现的 3 个 native 工具（count_notes / list_notes / search_notes） +以及线上通过 MCP Client 挂载的 3 个 `source: "mcp"` 远程工具（ask_question / +read_wiki_contents / read_wiki_structure，来自公共免鉴权的 DeepWiki MCP Server）。 + +## 4. 真实 Agent 任务（POST，会真实调用 DeepSeek 模型） + +> 限流说明：`POST /v1/agent/run` 每 IP 每分钟 30 次；超限返回 429 与 `Retry-After`， +> 稍后重试即可。健康与验证端点（本手册第 1–3 节）不受限。 + +```bash +curl -sS -X POST https://yai-agent-core.onrender.com/v1/agent/run \ + -H "Content-Type: application/json" \ + -d '{"task": "搜索笔记里关于比赛的内容并总结"}' \ + --max-time 180 +``` + +期望返回 JSON，包含： + +- `strategy`：自适应路由结果（该任务通常为 `plan` 或 `react`）； +- `events[0]`（`strategy_selected`）带 `source`（`llm` 模型分类 / `rules` 规则兜底）、 + `reason`（中文决策理由）与 `tier`（standard/strong）——决策本身可审计； +- `final_text`：模型基于真实工具结果给出的中文总结； +- `events`：完整过程事件序列（`strategy_selected` → `tool_call` → `tool_result`（ok=true）→ … → `done`），证明工具被真实调用而非提示词演示。 + +PowerShell 若对内联 JSON 引号处理不一致，可改用： + +```powershell +$body = @{ task = "搜索笔记里关于比赛的内容并总结" } | ConvertTo-Json -Compress +curl.exe -sS -X POST https://yai-agent-core.onrender.com/v1/agent/run ` + -H "Content-Type: application/json" --data $body --max-time 180 +``` + +## 4b. 真实外部 MCP 工具调用（MCP 产品化硬证据） + +```bash +curl -sS -X POST https://yai-agent-core.onrender.com/v1/agent/run \ + -H "Content-Type: application/json" \ + -d '{"task": "用 MCP 工具问一下 GitHub 仓库 modelcontextprotocol/python-sdk：MCP 的 Client 怎么初始化？用中文给结论。"}' \ + --max-time 180 +``` + +期望：`strategy` 为 `react`；`events` 中出现对 `ask_question` 的 +`tool_call` / `tool_result(ok=true)`（该工具的来源标注 `source: "mcp"` 在第 3 节 `/v1/tools` 清单中查看，事件体本身不带 source 字段）；`final_text` 是基于远程 MCP 返回内容的中文回答。 +该调用链为：本服务 → DeepSeek 规划工具调用 → Streamable HTTP 调远程 MCP Server → 结果回灌 → 模型总结。 + +## 5. 本地/隔离环境复现 + +```bash +git clone https://github.com/Gi-Tuu/yai-agent-core +cd yai-agent-core +git checkout +uv sync --extra dev --extra llm --extra server --extra mcp --extra openapi +uv run pytest # 125 项离线测试全绿（截至 v0.3，以 pytest -q 实跑为准），不需要 API Key + # 注：extras 组合与 CI 一致（dev/llm/server/mcp/openapi），实跑 125 passed，无 skip +uv run ruff check src tests examples scripts +uv run python scripts/smoke_test.py # 三宿主自适应冒烟（离线） +docker compose up --build # 容器化：容器内 8000，宿主 127.0.0.1:8001 +# 本地容器验证：curl http://127.0.0.1:8001/health +``` + +## 6. 证据留存 + +- 部署平台：Render 免费层 Docker Web Service（Blueprint 见 `source/render.yaml`）， + 平台注入 `RENDER_GIT_COMMIT`，服务启动时按 `YAI_GIT_COMMIT → RENDER_GIT_COMMIT → git HEAD → dev` + 解析且只接受 40 位哈希，保证 health 上报的就是本次部署的真实 commit； +- CI：每次推送在 GitHub Actions（Ubuntu 3.11/3.12/3.13 + Windows 3.13）执行 ruff + pytest，状态见仓库 README 徽章与 Actions 页； +- 正式评审期如迁移常驻 VPS，仅更换部署环境，端点契约、slug、commit 校验逻辑不变，并会通过补充 PR 披露。